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Liu Y, Qi L, Ye B, Wang A, Lu J, Qu L, Luo P, Wang L, Jiang A. MOICS, a novel classier deciphering immune heterogeneity and aid precise management of clear cell renal cell carcinoma at multiomics level. Cancer Biol Ther 2024; 25:2345977. [PMID: 38659199 PMCID: PMC11057626 DOI: 10.1080/15384047.2024.2345977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Accepted: 04/17/2024] [Indexed: 04/26/2024] Open
Abstract
Recent studies have indicated that the tumor immune microenvironment plays a pivotal role in the initiation and progression of clear cell renal cell carcinoma (ccRCC). However, the characteristics and heterogeneity of tumor immunity in ccRCC, particularly at the multiomics level, remain poorly understood. We analyzed immune multiomics datasets to perform a consensus cluster analysis and validate the clustering results across multiple internal and external ccRCC datasets; and identified two distinctive immune phenotypes of ccRCC, which we named multiomics immune-based cancer subtype 1 (MOICS1) and subtype 2 (MOICS2). The former, MOICS1, is characterized by an immune-hot phenotype with poor clinical outcomes, marked by significant proliferation of CD4+ and CD8+ T cells, fibroblasts, and high levels of immune inhibitory signatures; the latter, MOICS2, exhibits an immune-cold phenotype with favorable clinical characteristics, characterized by robust immune activity and high infiltration of endothelial cells and immune stimulatory signatures. Besides, a significant negative correlation between immune infiltration and angiogenesis were identified. We further explored the mechanisms underlying these differences, revealing that negatively regulated endopeptidase activity, activated cornification, and neutrophil degranulation may promote an immune-deficient phenotype, whereas enhanced monocyte recruitment could ameliorate this deficiency. Additionally, significant differences were observed in the genomic landscapes between the subtypes: MOICS1 exhibited mutations in TTN, BAP1, SETD2, MTOR, MUC16, CSMD3, and AKAP9, while MOICS2 was characterized by notable alterations in the TGF-β pathway. Overall, our work demonstrates that multi-immune omics remodeling analysis enhances the understanding of the immune heterogeneity in ccRCC and supports precise patient management.
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Affiliation(s)
- Ying Liu
- Department of Urology, Changhai Hospital, Naval Medical University (Second Military Medical University), Shanghai, China
| | - Lin Qi
- Department of Orthopedics, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Changsha, Hunan, China
| | - Bicheng Ye
- School of Clinical Medicine, Medical College of Yangzhou Polytechnic College, Yangzhou, China
| | - Anbang Wang
- Department of Urology, Changzheng Hospital, Naval Medical University (Second Military Medical University), Shanghai, China
| | - Juan Lu
- Vocational Education Center, Naval Medical University (Second Military Medical University), Shanghai, China
| | - Le Qu
- Department of Urology, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Peng Luo
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Linhui Wang
- Department of Urology, Changhai Hospital, Naval Medical University (Second Military Medical University), Shanghai, China
| | - Aimin Jiang
- Department of Urology, Changhai Hospital, Naval Medical University (Second Military Medical University), Shanghai, China
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2
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Zhou Z, Zhang R, Zhou A, Lv J, Chen S, Zou H, Zhang G, Lin T, Wang Z, Zhang Y, Weng S, Han X, Liu Z. Proteomics appending a complementary dimension to precision oncotherapy. Comput Struct Biotechnol J 2024; 23:1725-1739. [PMID: 38689716 PMCID: PMC11058087 DOI: 10.1016/j.csbj.2024.04.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 04/11/2024] [Accepted: 04/17/2024] [Indexed: 05/02/2024] Open
Abstract
Recent advances in high-throughput proteomic profiling technologies have facilitated the precise quantification of numerous proteins across multiple specimens concurrently. Researchers have the opportunity to comprehensively analyze the molecular signatures in plentiful medical specimens or disease pattern cell lines. Along with advances in data analysis and integration, proteomics data could be efficiently consolidated and employed to recognize precise elementary molecular mechanisms and decode individual biomarkers, guiding the precision treatment of tumors. Herein, we review a broad array of proteomics technologies and the progress and methods for the integration of proteomics data and further discuss how to better merge proteomics in precision medicine and clinical settings.
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Affiliation(s)
- Zhaokai Zhou
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
- Department of Urology, The First Affiliated Hospital of Zhengzhou University, Henan 450052, China
| | - Ruiqi Zhang
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Aoyang Zhou
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Jinxiang Lv
- Department of Gastroenterology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Shuang Chen
- Center of Reproductive Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Haijiao Zou
- Center of Reproductive Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Ge Zhang
- Department of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Ting Lin
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Zhan Wang
- Department of Urology, The First Affiliated Hospital of Zhengzhou University, Henan 450052, China
| | - Yuyuan Zhang
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Siyuan Weng
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Xinwei Han
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
- Interventional Institute of Zhengzhou University, Zhengzhou, Henan 450052, China
- Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan 450052, China
| | - Zaoqu Liu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
- Interventional Institute of Zhengzhou University, Zhengzhou, Henan 450052, China
- Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan 450052, China
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
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3
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Zhang J, Zeng X, Guo Q, Sheng Z, Chen Y, Wan S, Zhang L, Zhang P. Small cell lung cancer: emerging subtypes, signaling pathways, and therapeutic vulnerabilities. Exp Hematol Oncol 2024; 13:78. [PMID: 39103941 DOI: 10.1186/s40164-024-00548-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2024] [Accepted: 07/27/2024] [Indexed: 08/07/2024] Open
Abstract
Small cell lung cancer (SCLC) is a recalcitrant cancer characterized by early metastasis, rapid tumor growth and poor prognosis. In recent decades, the epidemiology, initiation and mutation characteristics of SCLC, as well as abnormal signaling pathways contributing to its progression, have been widely studied. Despite extensive investigation, fewer drugs have been approved for SCLC. Recent advancements in multi-omics studies have revealed diverse classifications of SCLC that are featured by distinct characteristics and therapeutic vulnerabilities. With the accumulation of SCLC samples, different subtypes of SCLC and specific treatments for these subtypes were further explored. The identification of different molecular subtypes has opened up novel avenues for the treatment of SCLC; however, the inconsistent and uncertain classification of SCLC has hindered the translation from basic research to clinical applications. Therefore, a comprehensives review is essential to conclude these emerging subtypes and related drugs targeting specific therapeutic vulnerabilities within abnormal signaling pathways. In this current review, we summarized the epidemiology, risk factors, mutation characteristics of and classification, related molecular pathways and treatments for SCLC. We hope that this review will facilitate the translation of molecular subtyping of SCLC from theory to clinical application.
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Affiliation(s)
- Jing Zhang
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, 200433, China.
| | - Xiaoping Zeng
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, 200433, China
| | - Qiji Guo
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, 200433, China
| | - Zhenxin Sheng
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, 200433, China
| | - Yan Chen
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, 200433, China
| | - Shiyue Wan
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, 200433, China
| | - Lele Zhang
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, 200433, China
| | - Peng Zhang
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, 200433, China.
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4
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Chen S, Wang X, Zhang J, Jiang L, Gao F, Xiang J, Yang S, Yang W, Zheng J, Han X. Deep learning-based diagnosis and survival prediction of patients with renal cell carcinoma from primary whole slide images. Pathology 2024:S0031-3025(24)00185-5. [PMID: 39168777 DOI: 10.1016/j.pathol.2024.05.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 05/06/2024] [Accepted: 05/20/2024] [Indexed: 08/23/2024]
Abstract
There is an urgent clinical demand to explore novel diagnostic and prognostic biomarkers for renal cell carcinoma (RCC). We proposed deep learning-based artificial intelligence strategies. The study included 1752 whole slide images from multiple centres. Based on the pixel-level of RCC segmentation, the diagnosis diagnostic model achieved an area under the receiver operating characteristic curve (AUC) of 0.977 (95% CI 0.969-0.984) in the external validation cohort. In addition, our diagnostic model exhibited excellent performance in the differential diagnosis of RCC from renal oncocytoma, which achieved an AUC of 0.951 (0.922-0.972). The graderisk for the recognition of high-grade tumour achieved AUCs of 0.840 (0.805-0.871) in the Cancer Genome Atlas (TCGA) cohort, 0.857 (0.813-0.894) in the Shanghai General Hospital (General) cohort, and 0.894 (0.842-0.933) in the Clinical Proteomic Tumor Analysis Consortium (CPTAC) cohort, for the recognition of high-grade tumour. The OSrisk for predicting 5-year survival status achieved an AUC of 0.784 (0.746-0.819) in the TCGA cohort, which was further verified in the independent general cohort and the CPTAC cohort, with AUCs of 0.774 (0.723-0.820) and 0.702 (0.632-0.765), respectively. Moreover, the competing-risk nomogram (CRN) showed its potential to be a prognostic indicator, with a hazard ratio (HR) of 5.664 (3.893-8.239, p<0.0001), outperforming other traditional clinical prognostic indicators. Kaplan-Meier survival analysis further illustrated that our CRN could significantly distinguish patients with high survival risk. Deep learning-based artificial intelligence could be a useful tool for clinicians to diagnose and predict the prognosis of RCC patients, thus improving the process of individualised treatment.
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Affiliation(s)
- Siteng Chen
- Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiyue Wang
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Liren Jiang
- Department of Pathology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Feng Gao
- Department of Pathology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | | | | | | | - Junhua Zheng
- Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Xiao Han
- Tencent AI Lab, Shenzhen, China.
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5
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Dai C, Cao J, Tang Y, Jiang Y, Luo C, Zheng J. YTHDF3 phase separation regulates HSPA13-dependent clear cell renal cell carcinoma development and immune evasion. Cancer Sci 2024; 115:2588-2601. [PMID: 38811341 PMCID: PMC11309927 DOI: 10.1111/cas.16228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 05/06/2024] [Accepted: 05/09/2024] [Indexed: 05/31/2024] Open
Abstract
Insufficient understanding about the immune evasion mechanism leads to the inability in predicting current immunotherapy effects in clear cell renal cell carcinoma (ccRCC) and sensitizing ccRCC to immunotherapy. RNA binding proteins (RBPs) can promote tumor progression and immune evasion. However, research on RBPs, particularly m6A reader YTHDF3, in ccRCC development and immune evasion is limited. In this study, we found that YTHDF3 level was downregulated in ccRCC and was an independent prognostic biomarker for ccRCC. Decreased YTHDF3 expression was correlated with the malignancy, immune evasion, and poor response to anti-programmed death ligand 1 (PD-L1)/CTLA-4 in ccRCC. YTHDF3 overexpression restrained ccRCC cell malignancy, PD-L1 expression, CD8+ T cell infiltration and activities in vivo, indicating its inhibitory role in ccRCC development and immune evasion. Mechanistically, YTHDF3 WT was found to have phase separation characteristics and suppress ccRCC malignancy and immune evasion. Whereas YTHDF3 mutant, which disrupted phase separation, abolished its function. YTHDF3 enhanced the degradation of its target mRNA HSPA13 by phase separation and recruiting DDX6, resulting in the downregulation of the downstream immune checkpoint PD-L1. HSPA13 overexpression restored ccRCC malignancy and immune evasion suppressed by YTHDF3 overexpression. In all, our results identify a new model of YTHDF3 in regulating ccRCC progression and immune evasion through phase separation.
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Affiliation(s)
- Chenyun Dai
- Beijing Key Laboratory of Cancer Invasion and Metastasis Research, Department of Biochemistry and Molecular Biology, School of Basic Medical SciencesCapital Medical UniversityBeijingChina
- Laboratory for Clinical MedicineCapital Medical UniversityBeijingChina
| | - Jianfu Cao
- Beijing Key Laboratory of Cancer Invasion and Metastasis Research, Department of Biochemistry and Molecular Biology, School of Basic Medical SciencesCapital Medical UniversityBeijingChina
- Laboratory for Clinical MedicineCapital Medical UniversityBeijingChina
| | - Yuangui Tang
- Beijing Key Laboratory of Cancer Invasion and Metastasis Research, Department of Biochemistry and Molecular Biology, School of Basic Medical SciencesCapital Medical UniversityBeijingChina
| | - Yuxiao Jiang
- Beijing Key Laboratory of Cancer Invasion and Metastasis Research, Department of Biochemistry and Molecular Biology, School of Basic Medical SciencesCapital Medical UniversityBeijingChina
| | - Chenghua Luo
- Department of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic DiseasesShihezi University School of MedicineShiheziChina
- Department of Pathology, The First Affiliated HospitalShihezi UniversityShiheziChina
| | - Junfang Zheng
- Beijing Key Laboratory of Cancer Invasion and Metastasis Research, Department of Biochemistry and Molecular Biology, School of Basic Medical SciencesCapital Medical UniversityBeijingChina
- Laboratory for Clinical MedicineCapital Medical UniversityBeijingChina
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6
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Li C, Hu M, Cai S, Yang G, Yang L, Jing H, Xing L, Sun X. Dysfunction of CD8 + T cells around tumor cells leads to occult lymph node metastasis in NSCLC patients. Cancer Sci 2024; 115:2528-2539. [PMID: 38720474 PMCID: PMC11309950 DOI: 10.1111/cas.16206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 04/16/2024] [Accepted: 04/19/2024] [Indexed: 08/10/2024] Open
Abstract
Occult lymph node metastasis (OLNM) is one of the main causes of regional recurrence in inoperable N0 non-small cell lung cancer (NSCLC) patients following stereotactic ablation body radiotherapy (SABR) treatment. The integration of immunotherapy and SABR (I-SABR) has shown preliminary efficiency in mitigating this recurrence. Therefore, it is necessary to explore the functional dynamics of critical immune effectors, particularly CD8+ T cells in the development of OLNM. In this study, tissue microarrays (TMAs) and multiplex immunofluorescence (mIF) were used to identify CD8+ T cells and functional subsets (cytotoxic CD8+ T cells/predysfunctional CD8+ T cells (CD8+ Tpredys)/dysfunctional CD8+ T cells (CD8+ Tdys)/other CD8+ T cells) among the no lymph node metastasis, OLNM, and clinically evident lymph node metastasis (CLNM) groups. As the degree of lymph node metastasis escalated, the density of total CD8+ T cells and CD8+ Tdys cells, as well as their proximity to tumor cells, increased progressively and remarkably in the invasive margin (IM). In the tumor center (TC), both the density and proximity of CD8+ Tpredys cells to tumor cells notably decreased in the OLNM group compared with the group without metastasis. Furthermore, positive correlations were found between the dysfunction of CD8+ T cells and HIF-1α+CD8 and cancer microvessels (CMVs). In conclusion, the deterioration in CD8+ T cell function and interactive dynamics between CD8+ T cells and tumor cells play a vital role in the development of OLNM in NSCLC. Strategies aimed at improving hypoxia or targeting CMVs could potentially enhance the efficacy of I-SABR.
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Affiliation(s)
- Chaozhuo Li
- School of Clinical MedicineShandong Second Medical UniversityWeifangChina
- Department of Radiation Oncology, Shandong Cancer Hospital and InstituteShandong First Medical University and Shandong Academy of Medical SciencesJinanChina
| | - Mengyu Hu
- Department of Radiation Oncology, Shandong Cancer Hospital and InstituteShandong First Medical University and Shandong Academy of Medical SciencesJinanChina
- Shandong Cancer Hospital and InstituteShandong First Medical University and Shandong Academy of Medical SciencesJinanChina
| | - Siqi Cai
- Department of Radiation Oncology, Shandong Cancer Hospital and InstituteShandong First Medical University and Shandong Academy of Medical SciencesJinanChina
- Cheeloo College of MedicineShandong UniversityJinanChina
| | - Guanqun Yang
- Department of Radiation Oncology, Shandong Cancer Hospital and InstituteShandong First Medical University and Shandong Academy of Medical SciencesJinanChina
- Cheeloo College of MedicineShandong UniversityJinanChina
| | - Liying Yang
- Department of Radiation Oncology, Shandong Cancer Hospital and InstituteShandong First Medical University and Shandong Academy of Medical SciencesJinanChina
- Cheeloo College of MedicineShandong UniversityJinanChina
| | - Hongbiao Jing
- Department of Pathology, Shandong Cancer Hospital and InstituteShandong First Medical University and Shandong Academy of Medical SciencesJinanChina
| | - Ligang Xing
- Department of Radiation Oncology, Shandong Cancer Hospital and InstituteShandong First Medical University and Shandong Academy of Medical SciencesJinanChina
| | - Xiaorong Sun
- Department of Nuclear Medicine, Shandong Cancer Hospital and InstituteShandong First Medical University and Shandong Academy of Medical SciencesJinanChina
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Pan B, Kang J, Zheng R, Wei C, Zhi Y. Molecular mechanism of ferroptosis and its application in the treatment of clear cell renal cell carcinoma. Pathol Res Pract 2024; 260:155324. [PMID: 38905897 DOI: 10.1016/j.prp.2024.155324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 04/09/2024] [Accepted: 04/19/2024] [Indexed: 06/23/2024]
Abstract
Clear cell renal cell carcinoma (ccRCC) is a common malignant tumor of the urinary tract, the incidence of which is continuously increasing and affects human health worldwide. Despite advances in existing treatments, treatment outcomes still need to be improved due to higher rates of postoperative recurrence, chemotherapy resistance, etc.; thus, there is an urgent need for innovative therapeutic approaches. Ferroptosis is a recently found type of regulated cell death that is characterized primarily by the buildup of lipid peroxidation products and fatal reactive oxygen species created by iron metabolism, which plays a crucial role in tumor progression and therapy.With the molecular mechanisms associated with ferroptosis being increasingly studied and refined, triggering ferroptosis by regulators that target ferroptosis and ccRCC may be the key to developing potential therapeutic strategies for ccRCC. Therefore, ferroptosis is expected to be a new breakthrough in treating ccRCC. This paper examines the mechanism of ferroptosis, the regulatory mechanism of ferroptosis in ccRCC, and the potential application of ferroptosis in combination with other therapies for the treatment of ccRCC. The goal is to offer novel perspectives for the research and clinical application of ferroptosis in the treatment of ccRCC.
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Affiliation(s)
- Beifen Pan
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China; National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China; Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
| | - Jiali Kang
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China; National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China; Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
| | - Rongxin Zheng
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China; National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China; Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
| | - Cuiping Wei
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China; National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China; Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
| | - Yong Zhi
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China; National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China.
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8
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Vallés‐Martí A, de Goeij‐de Haas RR, Henneman AA, Piersma SR, Pham TV, Knol JC, Verheij J, Dijk F, Halfwerk H, Giovannetti E, Jiménez CR, Bijlsma MF. Kinase activities in pancreatic ductal adenocarcinoma with prognostic and therapeutic avenues. Mol Oncol 2024; 18:2020-2041. [PMID: 38650175 PMCID: PMC11306541 DOI: 10.1002/1878-0261.13625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 12/12/2023] [Accepted: 02/21/2024] [Indexed: 04/25/2024] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with a limited number of known driver mutations but considerable cancer cell heterogeneity. Phosphoproteomics provides a direct read-out of aberrant signaling and the resultant clinically relevant phenotype. Mass spectrometry (MS)-based proteomics and phosphoproteomics were applied to 42 PDAC tumors. Data encompassed over 19 936 phosphoserine or phosphothreonine (pS/T; in 5412 phosphoproteins) and 1208 phosphotyrosine (pY; in 501 phosphoproteins) sites and a total of 3756 proteins. Proteome data identified three distinct subtypes with tumor intrinsic and stromal features. Subsequently, three phospho-subtypes were apparent: two tumor intrinsic (Phos1/2) and one stromal (Phos3), resembling known PDAC molecular subtypes. Kinase activity was analyzed by the Integrative iNferred Kinase Activity (INKA) scoring. Phospho-subtypes displayed differential phosphorylation signals and kinase activity, such as FGR and GSK3 activation in Phos1, SRC kinase family and EPHA2 in Phos2, and EGFR, INSR, MET, ABL1, HIPK1, JAK, and PRKCD in Phos3. Kinase activity analysis of an external PDAC cohort supported our findings and underscored the importance of PI3K/AKT and ERK pathways, among others. Interestingly, unfavorable patient prognosis correlated with higher RTK, PAK2, STK10, and CDK7 activity and high proliferation, whereas long survival was associated with MYLK and PTK6 activity, which was previously unknown. Subtype-associated activity profiles can guide therapeutic combination approaches in tumor and stroma-enriched tissues, and emphasize the critical role of parallel signaling pathways. In addition, kinase activity profiling identifies potential disease markers with prognostic significance.
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Affiliation(s)
- Andrea Vallés‐Martí
- Department of Medical Oncology, Amsterdam University Medical CenterVU UniversityAmsterdamThe Netherlands
- OncoProteomics LaboratoryCancer Center AmsterdamThe Netherlands
- Cancer BiologyCancer Center AmsterdamThe Netherlands
- Pharmacology LaboratoryCancer Center AmsterdamThe Netherlands
| | - Richard R. de Goeij‐de Haas
- Department of Medical Oncology, Amsterdam University Medical CenterVU UniversityAmsterdamThe Netherlands
- OncoProteomics LaboratoryCancer Center AmsterdamThe Netherlands
| | - Alex A. Henneman
- Department of Medical Oncology, Amsterdam University Medical CenterVU UniversityAmsterdamThe Netherlands
- OncoProteomics LaboratoryCancer Center AmsterdamThe Netherlands
| | - Sander R. Piersma
- Department of Medical Oncology, Amsterdam University Medical CenterVU UniversityAmsterdamThe Netherlands
- OncoProteomics LaboratoryCancer Center AmsterdamThe Netherlands
| | - Thang V. Pham
- Department of Medical Oncology, Amsterdam University Medical CenterVU UniversityAmsterdamThe Netherlands
- OncoProteomics LaboratoryCancer Center AmsterdamThe Netherlands
| | - Jaco C. Knol
- Department of Medical Oncology, Amsterdam University Medical CenterVU UniversityAmsterdamThe Netherlands
- OncoProteomics LaboratoryCancer Center AmsterdamThe Netherlands
| | - Joanne Verheij
- Department of PathologyAmsterdam University Medical CenterThe Netherlands
| | - Frederike Dijk
- Department of PathologyAmsterdam University Medical CenterThe Netherlands
| | - Hans Halfwerk
- Department of PathologyAmsterdam University Medical CenterThe Netherlands
| | - Elisa Giovannetti
- Department of Medical Oncology, Amsterdam University Medical CenterVU UniversityAmsterdamThe Netherlands
- Pharmacology LaboratoryCancer Center AmsterdamThe Netherlands
- Cancer Pharmacology Lab, AIRC Start‐Up UnitFondazione Pisana per la ScienzaSan Giuliano TermeItaly
| | - Connie R. Jiménez
- Department of Medical Oncology, Amsterdam University Medical CenterVU UniversityAmsterdamThe Netherlands
- OncoProteomics LaboratoryCancer Center AmsterdamThe Netherlands
| | - Maarten F. Bijlsma
- Cancer BiologyCancer Center AmsterdamThe Netherlands
- Laboratory for Experimental Oncology and Radiobiology, Center for Experimental and Molecular Medicine, Amsterdam University Medical CenterUniversity of AmsterdamThe Netherlands
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9
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Lee JS, Dan T, Zhang H, Cheng Y, Rehfeld F, Brugarolas J, Mendell JT. An ultraconserved snoRNA-like element in long noncoding RNA CRNDE promotes ribosome biogenesis and cell proliferation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.23.604857. [PMID: 39091767 PMCID: PMC11291168 DOI: 10.1101/2024.07.23.604857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Cancer cells frequently upregulate ribosome production to support tumorigenesis. While small nucleolar RNAs (snoRNAs) are critical for ribosome biogenesis, the roles of other classes of noncoding RNAs in this process remain largely unknown. Here we performed CRISPRi screens to identify essential long noncoding RNAs (lncRNAs) in renal cell carcinoma (RCC) cells. This revealed that an alternatively-spliced isoform of lncRNA Colorectal Neoplasia Differentially Expressed containing an ultraconserved element (UCE), referred to as CRNDE UCE, is required for RCC cell proliferation. CRNDE UCE localizes to the nucleolus and promotes 60S ribosomal subunit biogenesis. The UCE of CRNDE functions as an unprocessed C/D box snoRNA that directly interacts with ribosomal RNA precursors. This facilitates delivery of eIF6, a key 60S biogenesis factor, which binds to CRNDE UCE through a sequence element adjacent to the UCE. These findings highlight the functional versatility of snoRNA sequences and expand the known mechanisms through which noncoding RNAs orchestrate ribosome biogenesis.
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Affiliation(s)
- Jong-Sun Lee
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Tu Dan
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - He Zhang
- Quantitative Biomedical Research Center, Peter O’Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Yujing Cheng
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Frederick Rehfeld
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - James Brugarolas
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Kidney Cancer Program, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Joshua T. Mendell
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Hamon Center for Regenerative Science and Medicine, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
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10
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Zhang Y, Li J, Feng L, Cheng Y, Shi L, Yang Q, Wang Z, Yi X, Zhong G, Sun X, Cheng Z, Guo M. STAC3 as a poor prognostic biomarker in renal clear cell carcinoma: relationship with immune infiltration. Am J Cancer Res 2024; 14:3294-3316. [PMID: 39113874 PMCID: PMC11301302 DOI: 10.62347/eaqw3113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Accepted: 06/17/2024] [Indexed: 08/10/2024] Open
Abstract
Calcium ions (Ca2+) are crucial in tumorigenesis and progression, with their elevated levels indicating a negative prognosis in Kidney Renal Clear Cell Carcinoma (KIRC). The influence of genes regulating calcium ions on the survival outcomes of KIRC patients and their interaction with the tumor's immune microenvironment is yet to be fully understood. This study analyzed gene expression data from KIRC tumor and adjacent non-tumor tissues using the TCGA-KIRC dataset to pinpoint genes that are differentially expressed in KIRC. Intersection of these genes with those regulating calcium ions highlighted specific calcium ion-regulating genes that exhibit differential expression in KIRC. Subsequently, prognostic risk models were developed using univariate Cox and LASSO-Cox regression analyses to verify their diagnostic precision. Additionally, the study investigated the correlation between tumor immunity and KIRC patient outcomes, assessing the contribution of STAC3 genes to tumor immunity. Further exploration entailed SSGASE, single-cell analysis, pseudotime analysis and both in vivo and in vitro experiments to evaluate STAC3's role in tumor immunity and progression. Notably, STAC3 was significantly overexpressed in tumor specimens and positively correlated with the degree of malignancy of KIRC, affecting patients' prognosis. Elevated STAC3 expression correlated with enhanced immune infiltration in KIRC tumors. Furthermore, silencing STAC3 curtailed KIRC cell proliferation, migration, invasion, and stemness properties. Experimental models in mice confirmed that STAC3 knockdown led to a reduction in tumor growth. Elevated STAC3 expression is intricately linked with immune infiltration in KIRC tumors, as well as with the aggressive biological behaviors of tumor cells, including their proliferation, migration, and invasion. Targeting STAC3 presents a promising strategy to augment the efficacy of current therapeutic approaches and to better the survival outcomes of patients with KIRC.
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Affiliation(s)
- Yingnan Zhang
- The Fourth Affiliated Hospital of Harbin Medical University Harbin 150001, Heilongjiang, China
| | - Jingtao Li
- The Fourth Affiliated Hospital of Harbin Medical University Harbin 150001, Heilongjiang, China
| | - Luwen Feng
- The Fourth Affiliated Hospital of Harbin Medical University Harbin 150001, Heilongjiang, China
| | - Yue Cheng
- The Fourth Affiliated Hospital of Harbin Medical University Harbin 150001, Heilongjiang, China
| | - Linlin Shi
- The Fourth Affiliated Hospital of Harbin Medical University Harbin 150001, Heilongjiang, China
| | - Qian Yang
- The Fourth Affiliated Hospital of Harbin Medical University Harbin 150001, Heilongjiang, China
| | - Zhaoyang Wang
- The Fourth Affiliated Hospital of Harbin Medical University Harbin 150001, Heilongjiang, China
| | - Xuan Yi
- The Fourth Affiliated Hospital of Harbin Medical University Harbin 150001, Heilongjiang, China
| | - Guocai Zhong
- The Fourth Affiliated Hospital of Harbin Medical University Harbin 150001, Heilongjiang, China
| | - Xueying Sun
- The Fourth Affiliated Hospital of Harbin Medical University Harbin 150001, Heilongjiang, China
| | - Zhifeng Cheng
- The Fourth Affiliated Hospital of Harbin Medical University Harbin 150001, Heilongjiang, China
| | - Min Guo
- The Fourth Affiliated Hospital of Harbin Medical University Harbin 150001, Heilongjiang, China
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11
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Li Z, Wan J, Li S, Tang Y, Lin YCD, Ni J, Cai X, Yu J, Huang HD, Lee TY. Multi-Omics Characterization of E3 Regulatory Patterns in Different Cancer Types. Int J Mol Sci 2024; 25:7639. [PMID: 39062881 PMCID: PMC11276688 DOI: 10.3390/ijms25147639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Revised: 07/01/2024] [Accepted: 07/05/2024] [Indexed: 07/28/2024] Open
Abstract
Ubiquitination, a post-translational modification, refers to the covalent attachment of ubiquitin molecules to substrates. This modification plays a critical role in diverse cellular processes such as protein degradation. The specificity of ubiquitination for substrates is regulated by E3 ubiquitin ligases. Dysregulation of ubiquitination has been associated with numerous diseases, including cancers. In our study, we first investigated the protein expression patterns of E3 ligases across 12 cancer types. Our findings indicated that E3 ligases tend to be up-regulated and exhibit reduced tissue specificity in tumors. Moreover, the correlation of protein expression between E3 ligases and substrates demonstrated significant changes in cancers, suggesting that E3-substrate specificity alters in tumors compared to normal tissues. By integrating transcriptome, proteome, and ubiquitylome data, we further characterized the E3-substrate regulatory patterns in lung squamous cell carcinoma. Our analysis revealed that the upregulation of the SKP2 E3 ligase leads to excessive degradation of BRCA2, potentially promoting tumor cell proliferation and metastasis. Furthermore, the upregulation of E3 ubiquitin-protein ligase TRIM33 was identified as a biomarker associated with a favorable prognosis by inhibiting the cell cycle. This work exemplifies how leveraging multi-omics data to analyze E3 ligases across various cancers can unveil prognosis biomarkers and facilitate the identification of potential drug targets for cancer therapy.
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Affiliation(s)
- Zhongyan Li
- Warshel Institute for Computational Biology, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China; (Z.L.); (J.W.)
| | - Jingting Wan
- Warshel Institute for Computational Biology, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China; (Z.L.); (J.W.)
| | - Shangfu Li
- Warshel Institute for Computational Biology, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China; (Z.L.); (J.W.)
| | - Yun Tang
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, No. 75, Boai Street, Hsinchu 300, Taiwan
| | - Yang-Chi-Dung Lin
- Warshel Institute for Computational Biology, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China; (Z.L.); (J.W.)
| | - Jie Ni
- Warshel Institute for Computational Biology, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China; (Z.L.); (J.W.)
| | - Xiaoxuan Cai
- Warshel Institute for Computational Biology, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China; (Z.L.); (J.W.)
| | - Jinhan Yu
- Warshel Institute for Computational Biology, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China; (Z.L.); (J.W.)
| | - Hsien-Da Huang
- Warshel Institute for Computational Biology, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China; (Z.L.); (J.W.)
| | - Tzong-Yi Lee
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, No. 75, Boai Street, Hsinchu 300, Taiwan
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12
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Slobodyanyuk M, Bahcheli AT, Klein ZP, Bayati M, Strug LJ, Reimand J. Directional integration and pathway enrichment analysis for multi-omics data. Nat Commun 2024; 15:5690. [PMID: 38971800 PMCID: PMC11227559 DOI: 10.1038/s41467-024-49986-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 06/26/2024] [Indexed: 07/08/2024] Open
Abstract
Omics techniques generate comprehensive profiles of biomolecules in cells and tissues. However, a holistic understanding of underlying systems requires joint analyses of multiple data modalities. We present DPM, a data fusion method for integrating omics datasets using directionality and significance estimates of genes, transcripts, or proteins. DPM allows users to define how the input datasets are expected to interact directionally given the experimental design or biological relationships between the datasets. DPM prioritises genes and pathways that change consistently across the datasets and penalises those with inconsistent directionality. To demonstrate our approach, we characterise gene and pathway regulation in IDH-mutant gliomas by jointly analysing transcriptomic, proteomic, and DNA methylation datasets. Directional integration of survival information in ovarian cancer reveals candidate biomarkers with consistent prognostic signals in transcript and protein expression. DPM is a general and adaptable framework for gene prioritisation and pathway analysis in multi-omics datasets.
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Affiliation(s)
- Mykhaylo Slobodyanyuk
- Computational Biology Program, Ontario Institute for Cancer Research, 661 University Ave Suite 510, Toronto, ON M5G 0A3, Canada
- Department of Medical Biophysics, University of Toronto, 101 College Str Suite 15-701, Toronto, ON M5G 1L7, Canada
| | - Alexander T Bahcheli
- Computational Biology Program, Ontario Institute for Cancer Research, 661 University Ave Suite 510, Toronto, ON M5G 0A3, Canada
- Department of Molecular Genetics, University of Toronto, 1 King's College Circle Room 4386, Toronto, ON M5S 1A8, Canada
| | - Zoe P Klein
- Computational Biology Program, Ontario Institute for Cancer Research, 661 University Ave Suite 510, Toronto, ON M5G 0A3, Canada
- Department of Molecular Genetics, University of Toronto, 1 King's College Circle Room 4386, Toronto, ON M5S 1A8, Canada
| | - Masroor Bayati
- Computational Biology Program, Ontario Institute for Cancer Research, 661 University Ave Suite 510, Toronto, ON M5G 0A3, Canada
- Department of Medical Biophysics, University of Toronto, 101 College Str Suite 15-701, Toronto, ON M5G 1L7, Canada
| | - Lisa J Strug
- Program in Genetics and Genome Biology, the Hospital for Sick Children Research Institute, 686 Bay Str, Toronto, ON M5G 0A4, Canada
- Departments of Statistical Sciences, Computer Science and Division of Biostatistics, University of Toronto, 700 University Avenue, Toronto, ON M5G 1Z5, Canada
| | - Jüri Reimand
- Computational Biology Program, Ontario Institute for Cancer Research, 661 University Ave Suite 510, Toronto, ON M5G 0A3, Canada.
- Department of Medical Biophysics, University of Toronto, 101 College Str Suite 15-701, Toronto, ON M5G 1L7, Canada.
- Department of Molecular Genetics, University of Toronto, 1 King's College Circle Room 4386, Toronto, ON M5S 1A8, Canada.
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13
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Wang Y, Lih TM, Lee JW, Ohtsuka T, Hozaka Y, Mino-Kenudson M, Adsay NV, Luchini C, Scarpa A, Maker AV, Kim GE, Paulino J, Chen L, Jiao L, Sun Z, Goodman D, Pflüger MJ, Roberts NJ, Matthaei H, Wood LD, Furukawa T, Zhang H, Hruban RH. Multi-omic profiling of intraductal papillary neoplasms of the pancreas reveals distinct expression patterns and potential markers of progression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.07.602385. [PMID: 39005476 PMCID: PMC11245086 DOI: 10.1101/2024.07.07.602385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
In order to advance our understanding of precancers in the pancreas, 69 pancreatic intraductal papillary neoplasms (IPNs), including 64 intraductal papillary mucinous neoplasms (IPMNs) and 5 intraductal oncocytic papillary neoplasms (IOPNs), 32 pancreatic cyst fluid samples, 104 invasive pancreatic ductal adenocarcinomas (PDACs), 43 normal adjacent tissues (NATs), and 76 macro-dissected normal pancreatic ducts (NDs) were analyzed by mass spectrometry. A total of 10,246 proteins and 22,284 glycopeptides were identified in all tissue samples, and 756 proteins with more than 1.5-fold increase in abundance in IPMNs relative to NDs were identified, 45% of which were also identified in cyst fluids. The over-expression of selected proteins was validated by immunolabeling. Proteins and glycoproteins overexpressed in IPMNs included those involved in glycan biosynthesis and the immune system. In addition, multiomics clustering identified two subtypes of IPMNs. This study provides a foundation for understanding tumor progression and targets for earlier detection and therapies. Significance This multilevel characterization of intraductal papillary neoplasms of the pancreas provides a foundation for understanding the changes in protein and glycoprotein expression during the progression from normal duct to intraductal papillary neoplasm, and to invasive pancreatic carcinoma, providing a foundation for informed approaches to earlier detection and treatment.
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14
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Hu Y, Schnaubelt M, Chen L, Zhang B, Hoang T, Lih TM, Zhang Z, Zhang H. MS-PyCloud: A Cloud Computing-Based Pipeline for Proteomic and Glycoproteomic Data Analyses. Anal Chem 2024; 96:10145-10151. [PMID: 38869158 DOI: 10.1021/acs.analchem.3c01497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2024]
Abstract
Rapid development and wide adoption of mass spectrometry-based glycoproteomic technologies have empowered scientists to study proteins and protein glycosylation in complex samples on a large scale. This progress has also created unprecedented challenges for individual laboratories to store, manage, and analyze proteomic and glycoproteomic data, both in the cost for proprietary software and high-performance computing and in the long processing time that discourages on-the-fly changes of data processing settings required in explorative and discovery analysis. We developed an open-source, cloud computing-based pipeline, MS-PyCloud, with graphical user interface (GUI), for proteomic and glycoproteomic data analysis. The major components of this pipeline include data file integrity validation, MS/MS database search for spectral assignments to peptide sequences, false discovery rate estimation, protein inference, quantitation of global protein levels, and specific glycan-modified glycopeptides as well as other modification-specific peptides such as phosphorylation, acetylation, and ubiquitination. To ensure the transparency and reproducibility of data analysis, MS-PyCloud includes open-source software tools with comprehensive testing and versioning for spectrum assignments. Leveraging public cloud computing infrastructure via Amazon Web Services (AWS), MS-PyCloud scales seamlessly based on analysis demand to achieve fast and efficient performance. Application of the pipeline to the analysis of large-scale LC-MS/MS data sets demonstrated the effectiveness and high performance of MS-PyCloud. The software can be downloaded at https://github.com/huizhanglab-jhu/ms-pycloud.
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Affiliation(s)
- Yingwei Hu
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Michael Schnaubelt
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Li Chen
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Bai Zhang
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Trung Hoang
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - T Mamie Lih
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Zhen Zhang
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Hui Zhang
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
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15
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Bacigalupa ZA, Arner EN, Vlach LM, Wolf MM, Brown WA, Krystofiak ES, Ye X, Hongo RA, Landis M, Amason EK, Beckermann KE, Rathmell WK, Rathmell JC. HIF-2α expression and metabolic signaling require ACSS2 in clear cell renal cell carcinoma. J Clin Invest 2024; 134:e164249. [PMID: 38941296 PMCID: PMC11178540 DOI: 10.1172/jci164249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 05/01/2024] [Indexed: 06/30/2024] Open
Abstract
Clear cell renal cell carcinoma (ccRCC) is an aggressive cancer driven by VHL loss and aberrant HIF-2α signaling. Identifying means to regulate HIF-2α thus has potential therapeutic benefit. Acetyl-CoA synthetase 2 (ACSS2) converts acetate to acetyl-CoA and is associated with poor patient prognosis in ccRCC. Here we tested the effects of ACSS2 on HIF-2α and cancer cell metabolism and growth in ccRCC models and clinical samples. ACSS2 inhibition reduced HIF-2α levels and suppressed ccRCC cell line growth in vitro, in vivo, and in cultures of primary ccRCC patient tumors. This treatment reduced glycolytic signaling, cholesterol metabolism, and mitochondrial integrity, all of which are consistent with loss of HIF-2α. Mechanistically, ACSS2 inhibition decreased chromatin accessibility and HIF-2α expression and stability. While HIF-2α protein levels are widely regulated through pVHL-dependent proteolytic degradation, we identify a potential pVHL-independent pathway of degradation via the E3 ligase MUL1. We show that MUL1 can directly interact with HIF-2α and that overexpression of MUL1 decreased HIF-2α levels in a manner partially dependent on ACSS2. These findings identify multiple mechanisms to regulate HIF-2α stability and ACSS2 inhibition as a strategy to complement HIF-2α-targeted therapies and deplete pathogenically stabilized HIF-2α.
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Affiliation(s)
- Zachary A. Bacigalupa
- Department of Medicine
- Department of Pathology, Microbiology, and Immunology, and
- Vanderbilt Center for Immunobiology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Emily N. Arner
- Department of Medicine
- Department of Pathology, Microbiology, and Immunology, and
| | | | - Melissa M. Wolf
- Department of Medicine
- Department of Pathology, Microbiology, and Immunology, and
| | | | - Evan S. Krystofiak
- Cell Imaging Shared Resource, Vanderbilt University, Nashville, Tennessee, USA
| | - Xiang Ye
- Department of Pathology, Microbiology, and Immunology, and
| | - Rachel A. Hongo
- Department of Medicine
- Department of Pathology, Microbiology, and Immunology, and
| | - Madelyn Landis
- Department of Medicine
- Department of Pathology, Microbiology, and Immunology, and
| | | | | | - W. Kimryn Rathmell
- Department of Medicine
- Vanderbilt Center for Immunobiology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jeffrey C. Rathmell
- Department of Pathology, Microbiology, and Immunology, and
- Vanderbilt Center for Immunobiology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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16
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Guo T, Wang X, Wang T, Zhang J, Liu Y, Chen S, Wang X, Yang X, Wang C, Wang X. Dynamic changes of SCGN expression imply different phases of clear cell renal cell carcinoma progression. Discov Oncol 2024; 15:205. [PMID: 38831128 PMCID: PMC11147981 DOI: 10.1007/s12672-024-01071-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 05/29/2024] [Indexed: 06/05/2024] Open
Abstract
The secretagogin (SCGN) was originally identified as a secreted calcium-binding protein present in the cytoplasm. Recent studies have found that SCGN has a close relationship with cancer. However, its role in the occurrence, progression, and prognosis of clear cell renal cell carcinoma (ccRCC) remains unclear. In this study, we utilized a mutual authentication method based on public databases and clinical samples to determine the role of SCGN in the progression and prognosis of ccRCC. Firstly, we comprehensively analyzed the expression characteristics of SCGN in ccRCC in several public databases. Subsequently, we systematically evaluated SCGN expression on 252 microarrays of ccRCC tissues from different grades. It was found that SCGN was absent in all the normal kidney tissues and significantly overexpressed in ccRCC tumor tissues. In addition, the expression level of SCGN gradually decreased with an increase in tumor grade, and the percentage of SCGN staining positivity over 50% was 86.7% (13/15) and 73.4% (58/79) in Grade1 and Grade2, respectively, while it was only 8.3% (12/144) in Grade3, and the expression of SCGN was completely absent in Grade4 (0/14) and distant metastasis group (0/4). Additionally, the expression of SCGN was strongly correlated with the patient's prognosis, with the higher the expression levels of SCGN being associated with longer overall survival and disease-free survival of patients. In conclusion, our results suggest that reduced expression of SCGN in cancer cells is correlated with the progression and prognosis of ccRCC.
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Affiliation(s)
- Tuanjie Guo
- Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xuan Wang
- Department of Pathology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tao Wang
- Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jian Zhang
- Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yang Liu
- Department of Pathology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Siteng Chen
- Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xu Wang
- Department of Pathology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaoqun Yang
- Department of Pathology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Chaofu Wang
- Department of Pathology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Department of Pathology, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Xiang Wang
- Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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17
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Simoni M, Menegazzi C, Fracassi C, Biffi CC, Genova F, Tenace NP, Lucianò R, Raimondi A, Tacchetti C, Brugarolas J, Mazza D, Bernardi R. PML restrains p53 activity and cellular senescence in clear cell renal cell carcinoma. EMBO Mol Med 2024; 16:1324-1351. [PMID: 38730056 PMCID: PMC11178789 DOI: 10.1038/s44321-024-00077-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 04/23/2024] [Accepted: 04/25/2024] [Indexed: 05/12/2024] Open
Abstract
Clear-cell renal cell carcinoma (ccRCC), the major subtype of RCC, is frequently diagnosed at late/metastatic stage with 13% 5-year disease-free survival. Functional inactivation of the wild-type p53 protein is implicated in ccRCC therapy resistance, but the detailed mechanisms of p53 malfunction are still poorly characterized. Thus, a better understanding of the mechanisms of disease progression and therapy resistance is required. Here, we report a novel ccRCC dependence on the promyelocytic leukemia (PML) protein. We show that PML is overexpressed in ccRCC and that PML depletion inhibits cell proliferation and relieves pathologic features of anaplastic disease in vivo. Mechanistically, PML loss unleashed p53-dependent cellular senescence thus depicting a novel regulatory axis to limit p53 activity and senescence in ccRCC. Treatment with the FDA-approved PML inhibitor arsenic trioxide induced PML degradation and p53 accumulation and inhibited ccRCC expansion in vitro and in vivo. Therefore, by defining non-oncogene addiction to the PML gene, our work uncovers a novel ccRCC vulnerability and lays the foundation for repurposing an available pharmacological intervention to restore p53 function and chemosensitivity.
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Affiliation(s)
- Matilde Simoni
- Division of Experimental Oncology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Chiara Menegazzi
- Division of Experimental Oncology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Cristina Fracassi
- Division of Experimental Oncology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Claudia C Biffi
- Division of Experimental Oncology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Medical Advisor, Sanofi, Milan, Italy
| | - Francesca Genova
- Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Nazario Pio Tenace
- Department of Pathology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Roberta Lucianò
- Department of Pathology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Andrea Raimondi
- Experimental Imaging Center, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Carlo Tacchetti
- Experimental Imaging Center, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Universita' Vita-Salute San Raffaele, Milan, Italy
| | - James Brugarolas
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Internal Medicine, Division of Hematology/Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Davide Mazza
- Experimental Imaging Center, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Rosa Bernardi
- Division of Experimental Oncology, IRCCS San Raffaele Scientific Institute, Milan, Italy.
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18
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Wakamatsu M, Muramatsu H, Sato H, Ishikawa M, Konno R, Nakajima D, Hamada M, Okuno Y, Kawashima Y, Hama A, Ito M, Iwafuchi H, Takahashi Y, Ohara O. Integrated proteogenomic analysis for inherited bone marrow failure syndrome. Leukemia 2024; 38:1256-1265. [PMID: 38740980 PMCID: PMC11147772 DOI: 10.1038/s41375-024-02263-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2024] [Revised: 04/19/2024] [Accepted: 04/23/2024] [Indexed: 05/16/2024]
Abstract
Recent advances in in-depth data-independent acquisition proteomic analysis have enabled comprehensive quantitative analysis of >10,000 proteins. Herein, an integrated proteogenomic analysis for inherited bone marrow failure syndrome (IBMFS) was performed to reveal their biological features and to develop a proteomic-based diagnostic assay in the discovery cohort; dyskeratosis congenita (n = 12), Fanconi anemia (n = 11), Diamond-Blackfan anemia (DBA, n = 9), Shwachman-Diamond syndrome (SDS, n = 6), ADH5/ALDH2 deficiency (n = 4), and other IBMFS (n = 18). Unsupervised proteomic clustering identified eight independent clusters (C1-C8), with the ribosomal pathway specifically downregulated in C1 and C2, enriched for DBA and SDS, respectively. Six patients with SDS had significantly decreased SBDS protein expression, with two of these not diagnosed by DNA sequencing alone. Four patients with ADH5/ALDH2 deficiency showed significantly reduced ADH5 protein expression. To perform a large-scale rapid IBMFS screening, targeted proteomic analysis was performed on 417 samples from patients with IBMFS-related hematological disorders (n = 390) and healthy controls (n = 27). SBDS and ADH5 protein expressions were significantly reduced in SDS and ADH5/ALDH2 deficiency, respectively. The clinical application of this first integrated proteogenomic analysis would be useful for the diagnosis and screening of IBMFS, where appropriate clinical screening tests are lacking.
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Affiliation(s)
- Manabu Wakamatsu
- Department of Pediatrics, Nagoya University Graduate School of Medicine, Showa-ku, Nagoya, 466-8560, Japan
| | - Hideki Muramatsu
- Department of Pediatrics, Nagoya University Graduate School of Medicine, Showa-ku, Nagoya, 466-8560, Japan.
| | - Hironori Sato
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, 292-0818, Japan
- Department of Pediatrics, Chiba University Graduate School of Medicine, Chuo-ku, Chiba, 260-8670, Japan
| | - Masaki Ishikawa
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, 292-0818, Japan
| | - Ryo Konno
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, 292-0818, Japan
| | - Daisuke Nakajima
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, 292-0818, Japan
| | - Motoharu Hamada
- Department of Pediatrics, Nagoya University Graduate School of Medicine, Showa-ku, Nagoya, 466-8560, Japan
- Department of Virology, Nagoya City University Graduate School of Medical Sciences, Mizuho-ku, Nagoya, 464-0083, Japan
| | - Yusuke Okuno
- Department of Virology, Nagoya City University Graduate School of Medical Sciences, Mizuho-ku, Nagoya, 464-0083, Japan
| | - Yusuke Kawashima
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, 292-0818, Japan.
| | - Asahito Hama
- Department of Hematology and Oncology, Children's Medical Center, Japanese Red Cross Aichi Medical Center Nagoya First Hospital, Nakamura-ku, Nagoya, 453-8511, Japan
| | - Masafumi Ito
- Department of Pathology, Japanese Red Cross Aichi Medical Center Nagoya First Hospital, Nakamura-ku, Nagoya, 453-8511, Japan
| | - Hideto Iwafuchi
- Department of Pathology, Shizuoka Children's Hospital, Aoi-ku, Shizuoka, 420-095, Japan
| | - Yoshiyuki Takahashi
- Department of Pediatrics, Nagoya University Graduate School of Medicine, Showa-ku, Nagoya, 466-8560, Japan
| | - Osamu Ohara
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, 292-0818, Japan
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19
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Li J, Cao Q, Tong M. Deciphering anoikis resistance and identifying prognostic biomarkers in clear cell renal cell carcinoma epithelial cells. Sci Rep 2024; 14:12044. [PMID: 38802480 PMCID: PMC11130322 DOI: 10.1038/s41598-024-62978-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 05/23/2024] [Indexed: 05/29/2024] Open
Abstract
This study tackles the persistent prognostic and management challenges of clear cell renal cell carcinoma (ccRCC), despite advancements in multimodal therapies. Focusing on anoikis, a critical form of programmed cell death in tumor progression and metastasis, we investigated its resistance in cancer evolution. Using single-cell RNA sequencing from seven ccRCC patients, we assessed the impact of anoikis-related genes (ARGs) and identified differentially expressed genes (DEGs) in Anoikis-related epithelial subclusters (ARESs). Additionally, six ccRCC RNA microarray datasets from the GEO database were analyzed for robust DEGs. A novel risk prognostic model was developed through LASSO and multivariate Cox regression, validated using BEST, ULCAN, and RT-PCR. The study included functional enrichment, immune infiltration analysis in the tumor microenvironment (TME), and drug sensitivity assessments, leading to a predictive nomogram integrating clinical parameters. Results highlighted dynamic ARG expression patterns and enhanced intercellular interactions in ARESs, with significant KEGG pathway enrichment in MYC + Epithelial subclusters indicating enhanced anoikis resistance. Additionally, all ARESs were identified in the spatial context, and their locational relationships were explored. Three key prognostic genes-TIMP1, PECAM1, and CDKN1A-were identified, with the high-risk group showing greater immune infiltration and anoikis resistance, linked to poorer prognosis. This study offers a novel ccRCC risk signature, providing innovative approaches for patient management, prognosis, and personalized treatment.
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Affiliation(s)
- Junyi Li
- Department of Urology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, 121001, Liaoning, China
| | - Qingfei Cao
- Department of Urology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, 121001, Liaoning, China
| | - Ming Tong
- Department of Urology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, 121001, Liaoning, China.
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20
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Li GX, Chen L, Hsiao Y, Mannan R, Zhang Y, Luo J, Petralia F, Cho H, Hosseini N, Leprevost FDV, Calinawan A, Li Y, Anand S, Dagar A, Geffen Y, Kumar-Sinha C, Chugh S, Le A, Ponce S, Guo S, Zhang C, Schnaubelt M, Al Deen NN, Chen F, Caravan W, Houston A, Hopkins A, Newton CJ, Wang X, Polasky DA, Haynes S, Yu F, Jing X, Chen S, Robles AI, Mesri M, Thiagarajan M, An E, Getz GA, Linehan WM, Hostetter G, Jewell SD, Chan DW, Wang P, Omenn GS, Mehra R, Ricketts CJ, Ding L, Chinnaiyan AM, Cieslik MP, Dhanasekaran SM, Zhang H, Nesvizhskii AI. Comprehensive proteogenomic characterization of rare kidney tumors. Cell Rep Med 2024; 5:101547. [PMID: 38703764 PMCID: PMC11148773 DOI: 10.1016/j.xcrm.2024.101547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 09/29/2023] [Accepted: 04/10/2024] [Indexed: 05/06/2024]
Abstract
Non-clear cell renal cell carcinomas (non-ccRCCs) encompass diverse malignant and benign tumors. Refinement of differential diagnosis biomarkers, markers for early prognosis of aggressive disease, and therapeutic targets to complement immunotherapy are current clinical needs. Multi-omics analyses of 48 non-ccRCCs compared with 103 ccRCCs reveal proteogenomic, phosphorylation, glycosylation, and metabolic aberrations in RCC subtypes. RCCs with high genome instability display overexpression of IGF2BP3 and PYCR1. Integration of single-cell and bulk transcriptome data predicts diverse cell-of-origin and clarifies RCC subtype-specific proteogenomic signatures. Expression of biomarkers MAPRE3, ADGRF5, and GPNMB differentiates renal oncocytoma from chromophobe RCC, and PIGR and SOSTDC1 distinguish papillary RCC from MTSCC. This study expands our knowledge of proteogenomic signatures, biomarkers, and potential therapeutic targets in non-ccRCC.
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Affiliation(s)
- Ginny Xiaohe Li
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Lijun Chen
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
| | - Yi Hsiao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Rahul Mannan
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yuping Zhang
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jie Luo
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Francesca Petralia
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Hanbyul Cho
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Noshad Hosseini
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | | | - Anna Calinawan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Yize Li
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Shankara Anand
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Aniket Dagar
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yifat Geffen
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Cancer Center and Department of Pathology, Massachusetts General Hospital, Boston, MA 02115, USA
| | - Chandan Kumar-Sinha
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Seema Chugh
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Anne Le
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA; Department of Chemical and Biomolecular Engineering, Johns Hopkins University Whiting School of Engineering, Baltimore, MD 21218, USA; Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Sean Ponce
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University Whiting School of Engineering, Baltimore, MD 21218, USA
| | - Shenghao Guo
- Department of Biomedical Engineering, Johns Hopkins University Whiting School of Engineering, Baltimore, MD 21218, USA
| | - Cissy Zhang
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
| | - Michael Schnaubelt
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
| | - Nataly Naser Al Deen
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Feng Chen
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Wagma Caravan
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Andrew Houston
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Alex Hopkins
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | | | - Xiaoming Wang
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Daniel A Polasky
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Sarah Haynes
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Xiaojun Jing
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Siqi Chen
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Ana I Robles
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, MD 20850, USA
| | - Mehdi Mesri
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, MD 20850, USA
| | | | - Eunkyung An
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, MD 20850, USA
| | - Gad A Getz
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - W Marston Linehan
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | | | - Scott D Jewell
- Van Andel Research Institute, Grand Rapids, MI 49503, USA
| | - Daniel W Chan
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA; Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA; Department of Urology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Pei Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Gilbert S Omenn
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Internal Medicine, Human Genetics, and School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Rohit Mehra
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Christopher J Ricketts
- Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Li Ding
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA; Department of Genetics, Washington University in St. Louis, St. Louis, MO 63130, USA; Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Arul M Chinnaiyan
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Howard Hughes Medical Institute, University of Michigan, Ann Arbor, MI 48109, USA; Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA; Department of Urology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Marcin P Cieslik
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Saravana M Dhanasekaran
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
| | - Hui Zhang
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA; Department of Chemical and Biomolecular Engineering, Johns Hopkins University Whiting School of Engineering, Baltimore, MD 21218, USA; Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA; Department of Urology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
| | - Alexey I Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA.
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21
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Kohler D, Staniak M, Yu F, Nesvizhskii AI, Vitek O. An MSstats workflow for detecting differentially abundant proteins in large-scale data-independent acquisition mass spectrometry experiments with FragPipe processing. Nat Protoc 2024:10.1038/s41596-024-01000-3. [PMID: 38769142 DOI: 10.1038/s41596-024-01000-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 03/11/2024] [Indexed: 05/22/2024]
Abstract
Technological advances in mass spectrometry and proteomics have made it possible to perform larger-scale and more-complex experiments. The volume and complexity of the resulting data create major challenges for downstream analysis. In particular, next-generation data-independent acquisition (DIA) experiments enable wider proteome coverage than more traditional targeted approaches but require computational workflows that can manage much larger datasets and identify peptide sequences from complex and overlapping spectral features. Data-processing tools such as FragPipe, DIA-NN and Spectronaut have undergone substantial improvements to process spectral features in a reasonable time. Statistical analysis tools are needed to draw meaningful comparisons between experimental samples, but these tools were also originally designed with smaller datasets in mind. This protocol describes an updated version of MSstats that has been adapted to be compatible with large-scale DIA experiments. A very large DIA experiment, processed with FragPipe, is used as an example to demonstrate different MSstats workflows. The choice of workflow depends on the user's computational resources. For datasets that are too large to fit into a standard computer's memory, we demonstrate the use of MSstatsBig, a companion R package to MSstats. The protocol also highlights key decisions that have a major effect on both the results and the processing time of the analysis. The MSstats processing can be expected to take 1-3 h depending on the usage of MSstatsBig. The protocol can be run in the point-and-click graphical user interface MSstatsShiny or implemented with minimal coding expertise in R.
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Affiliation(s)
- Devon Kohler
- Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA
- Barnett Institute for Chemical and Biological Analysis, Northeastern University, Boston, MA, USA
| | | | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Alexey I Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Olga Vitek
- Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA.
- Barnett Institute for Chemical and Biological Analysis, Northeastern University, Boston, MA, USA.
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22
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Riscal R, Gardner SM, Coffey NJ, Carens M, Mesaros C, Xu JP, Xue Y, Davis L, Demczyszyn S, Vogt A, Olia A, Finan JM, Godfrey J, Schultz DC, Blair IA, Keith B, Marmorstein R, Skuli N, Simon MC. Bile Acid Metabolism Mediates Cholesterol Homeostasis and Promotes Tumorigenesis in Clear Cell Renal Cell Carcinoma. Cancer Res 2024; 84:1570-1582. [PMID: 38417134 PMCID: PMC11096083 DOI: 10.1158/0008-5472.can-23-0821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 10/20/2023] [Accepted: 02/23/2024] [Indexed: 03/01/2024]
Abstract
Clear cell renal cell carcinoma (ccRCC) incidence has risen steadily over the last decade. Elevated lipid uptake and storage is required for ccRCC cell viability. As stored cholesterol is the most abundant component in ccRCC intracellular lipid droplets, it may also play an important role in ccRCC cellular homeostasis. In support of this hypothesis, ccRCC cells acquire exogenous cholesterol through the high-density lipoprotein receptor SCARB1, inhibition or suppression of which induces apoptosis. Here, we showed that elevated expression of 3 beta-hydroxy steroid dehydrogenase type 7 (HSD3B7), which metabolizes cholesterol-derived oxysterols in the bile acid biosynthetic pathway, is also essential for ccRCC cell survival. Development of an HSD3B7 enzymatic assay and screening for small-molecule inhibitors uncovered the compound celastrol as a potent HSD3B7 inhibitor with low micromolar activity. Repressing HSD3B7 expression genetically or treating ccRCC cells with celastrol resulted in toxic oxysterol accumulation, impaired proliferation, and increased apoptosis in vitro and in vivo. These data demonstrate that bile acid synthesis regulates cholesterol homeostasis in ccRCC and identifies HSD3B7 as a plausible therapeutic target. SIGNIFICANCE The bile acid biosynthetic enzyme HSD3B7 is essential for ccRCC cell survival and can be targeted to induce accumulation of cholesterol-derived oxysterols and apoptotic cell death.
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Affiliation(s)
- Romain Riscal
- Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania
- IRCM, Institut de Recherche en Cancérologie de Montpellier, INSERM U1194, Université de Montpellier, Institut régional du Cancer de Montpellier, Montpellier, France
| | - Sarah M Gardner
- Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania
- Department of Biochemistry and Biophysics, Graduate Group in Biochemistry and Molecular Biophysics, Perelman School of Medicine University of Pennsylvania, Philadelphia, Pennsylvania
| | - Nathan J Coffey
- Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Madeleine Carens
- Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Clementina Mesaros
- Centers for Cancer Pharmacology and Excellence in Environmental Toxicology, Department of Pharmacology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Jimmy P Xu
- Centers for Cancer Pharmacology and Excellence in Environmental Toxicology, Department of Pharmacology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Yizheng Xue
- Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania
- Department of Urology, Ren Ji Hospital, Shanghai, P.R. China
| | - Leah Davis
- Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Sara Demczyszyn
- Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Austin Vogt
- Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Adam Olia
- Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Jennifer M Finan
- Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Jason Godfrey
- Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania
| | - David C Schultz
- Department of Biochemistry and Biophysics, High-throughput Screening Core, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Ian A Blair
- Centers for Cancer Pharmacology and Excellence in Environmental Toxicology, Department of Pharmacology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Brian Keith
- Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Ronen Marmorstein
- Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania
- Department of Biochemistry and Biophysics, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Nicolas Skuli
- Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania
- Stem Cell and Xenograft Core, University of Pennsylvania, Philadelphia, Pennsylvania
| | - M Celeste Simon
- Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania
- Departement of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, Pennsylvania
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23
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Iacobas DA, Iacobas S. Papillary Thyroid Cancer Remodels the Genetic Information Processing Pathways. Genes (Basel) 2024; 15:621. [PMID: 38790250 PMCID: PMC11120757 DOI: 10.3390/genes15050621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Revised: 05/10/2024] [Accepted: 05/13/2024] [Indexed: 05/26/2024] Open
Abstract
The genetic causes of the differentiated, highly treatable, and mostly non-fatal papillary thyroid cancer (PTC) are not yet fully understood. The mostly accepted PTC etiology blames the altered sequence or/and expression level of certain biomarker genes. However, tumor heterogeneity and the patient's unique set of favoring factors question the fit-for-all gene biomarkers. Publicly accessible gene expression profiles of the cancer nodule and the surrounding normal tissue from a surgically removed PTC tumor were re-analyzed to determine the cancer-induced alterations of the genomic fabrics responsible for major functional pathways. Tumor data were compared with those of standard papillary and anaplastic thyroid cancer cell lines. We found that PTC regulated numerous genes associated with DNA replication, repair, and transcription. Results further indicated that changes of the gene networking in functional pathways and the homeostatic control of transcript abundances also had major contributions to the PTC phenotype occurrence. The purpose to proliferate and invade the entire gland may explain the substantial transcriptomic differences we detected between the cells of the cancer nodule and those spread in homo-cellular cultures (where they need only to survive). In conclusion, the PTC etiology should include the complex molecular mechanisms involved in the remodeling of the genetic information processing pathways.
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Affiliation(s)
- Dumitru Andrei Iacobas
- Personalized Genomics Laboratory, Undergraduate Medical Academy, Prairie View A&M University, Prairie View, TX 77446, USA
| | - Sanda Iacobas
- Department of Pathology, New York Medical College, Valhalla, NY 10595, USA;
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24
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Chavali K, Coker H, Youngblood E, Karaduta O. Proteogenomics in Nephrology: A New Frontier in Nephrological Research. Curr Issues Mol Biol 2024; 46:4595-4608. [PMID: 38785547 PMCID: PMC11120334 DOI: 10.3390/cimb46050279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 05/03/2024] [Accepted: 05/05/2024] [Indexed: 05/25/2024] Open
Abstract
Proteogenomics represents a transformative intersection in nephrology, uniting genomics, transcriptomics, and proteomics to unravel the molecular intricacies of kidney diseases. This review encapsulates the methodological essence of proteogenomics and its profound implications in chronic kidney disease (CKD) research. We explore the proteogenomic pipeline, highlighting the integrated analysis of genomic, transcriptomic, and proteomic data and its pivotal role in enhancing our understanding of kidney pathologies. Through case studies, we showcase the application of proteogenomics in clear cell renal cell carcinoma (ccRCC) and Autosomal Recessive Polycystic Kidney Disease (ARPKD), emphasizing its potential in personalized treatment strategies and biomarker discovery. The review also addresses the challenges in proteogenomic analysis, including data integration complexities and bioinformatics limitations, and proposes solutions for advancing the field. Ultimately, this review underscores the prospective future of proteogenomics in nephrology, particularly in advancing personalized medicine and providing novel therapeutic insights.
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Affiliation(s)
- Kavya Chavali
- Adventist Health Hanford Family Medicine Residency Program, ONE Adventist Health Way, Roseville, CA 95661, USA
| | - Holley Coker
- Department of Physician Assistant Studies, University of Arkansas for Medical Sciences, 4301 W Markham Street, Little Rock, AR 72205, USA
| | - Emily Youngblood
- Department of Physician Assistant Studies, University of Arkansas for Medical Sciences, 4301 W Markham Street, Little Rock, AR 72205, USA
| | - Oleg Karaduta
- Department of Physician Assistant Studies, University of Arkansas for Medical Sciences, 4301 W Markham Street, Little Rock, AR 72205, USA
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25
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Sjöberg E. Molecular mechanisms and clinical relevance of endothelial cell cross-talk in clear cell renal cell carcinoma. Ups J Med Sci 2024; 129:10632. [PMID: 38863726 PMCID: PMC11165252 DOI: 10.48101/ujms.v129.10632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 03/17/2024] [Accepted: 04/03/2024] [Indexed: 06/13/2024] Open
Abstract
Background Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer in adults and stands out as one of the most vascularized and immune-infiltrated solid tumors. Overproduction of vascular endothelial growth factor A promotes uncontrolled growth of abnormal vessels and immunosuppression, and the tumor microenvironment (TME) has a prominent role in disease progression, drug targeting and drug response, and for patient outcome. Methods Studies of experimental models, large-scale omics approaches, and patient prognosis and therapy prediction, using gene expression signatures and tissue biomarker analysis, have been reviewed for enhanced understanding of the endothelium in ccRCC and the interplay with the surrounding TME. Results Preclinical and clinical studies have discovered molecular mechanisms of endothelial cross-talk of relevance for disease progression, patient prognosis, and therapy prediction. There is, however, a lack of representative ccRCC experimental models. Omics approaches have identified clinically relevant subsets of angiogenic and immune-infiltrated tumors with distinct molecular signatures and distinct endothelial cell and immune cell populations in patients. Conclusions Recent genetically engineered ccRCC mouse models together with emerging evidence from single cell RNA sequencing data open up for future validation studies, including multiplex imaging of ccRCC patient cohorts. These studies are of importance for therapy benefit and personalized treatment of ccRCC patients.
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Affiliation(s)
- Elin Sjöberg
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
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26
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Russo GC, Crawford AJ, Clark D, Cui J, Carney R, Karl MN, Su B, Starich B, Lih TS, Kamat P, Zhang Q, Nair PR, Wu PH, Lee MH, Leong HS, Zhang H, Rebecca VW, Wirtz D. E-cadherin interacts with EGFR resulting in hyper-activation of ERK in multiple models of breast cancer. Oncogene 2024; 43:1445-1462. [PMID: 38509231 DOI: 10.1038/s41388-024-03007-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 02/29/2024] [Accepted: 03/05/2024] [Indexed: 03/22/2024]
Abstract
The loss of intercellular adhesion molecule E-cadherin is a hallmark of the epithelial-mesenchymal transition (EMT), during which tumor cells transition into an invasive phenotype. Accordingly, E-cadherin has long been considered a tumor suppressor gene; however, E-cadherin expression is paradoxically correlated with breast cancer survival rates. Using novel multi-compartment organoids and multiple in vivo models, we show that E-cadherin promotes a hyper-proliferative phenotype in breast cancer cells via interaction with the transmembrane receptor EGFR. The E-cad and EGFR interaction results in activation of the MEK/ERK signaling pathway, leading to a significant increase in proliferation via activation of transcription factors, including c-Fos. Pharmacological inhibition of MEK activity in E-cadherin positive breast cancer significantly decreases both tumor growth and macro-metastasis in vivo. This work provides evidence for a novel role of E-cadherin in breast tumor progression and identifies a new target to treat hyper-proliferative E-cadherin-positive breast tumors, thus providing the foundation to utilize E-cadherin as a biomarker for specific therapeutic success.
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Affiliation(s)
- Gabriella C Russo
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
- Johns Hopkins Physical Sciences-Oncology Center and Institute for NanoBioTechnology, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
| | - Ashleigh J Crawford
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
- Johns Hopkins Physical Sciences-Oncology Center and Institute for NanoBioTechnology, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
| | - David Clark
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD, 21231, USA
| | - Julie Cui
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
| | - Ryan Carney
- Department of Biophysics, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
| | - Michelle N Karl
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
- Johns Hopkins Physical Sciences-Oncology Center and Institute for NanoBioTechnology, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
| | - Boyang Su
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Bartholomew Starich
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
- Johns Hopkins Physical Sciences-Oncology Center and Institute for NanoBioTechnology, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
| | - Tung-Shing Lih
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD, 21231, USA
| | - Pratik Kamat
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
- Johns Hopkins Physical Sciences-Oncology Center and Institute for NanoBioTechnology, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
| | - Qiming Zhang
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
| | - Praful R Nair
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
- Johns Hopkins Physical Sciences-Oncology Center and Institute for NanoBioTechnology, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
| | - Pei-Hsun Wu
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
- Johns Hopkins Physical Sciences-Oncology Center and Institute for NanoBioTechnology, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
| | - Meng-Horng Lee
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
| | - Hon S Leong
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Biological Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Hui Zhang
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD, 21231, USA
| | - Vito W Rebecca
- Department of Biochemistry and Molecular Biology, Johns Hopkins University School of Public Health, Baltimore, MD, 21231, USA
| | - Denis Wirtz
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA.
- Johns Hopkins Physical Sciences-Oncology Center and Institute for NanoBioTechnology, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA.
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Mehra R, Nallandhighal S, Cotta B, Knuth Z, Su F, Kasputis A, Zhang Y, Wang R, Cao X, Udager AM, Dhanasekaran SM, Cieslik MP, Morgan TM, Salami SS. Discovery and Validation of a 15-Gene Prognostic Signature for Clear Cell Renal Cell Carcinoma. JCO Precis Oncol 2024; 8:e2300565. [PMID: 38810179 DOI: 10.1200/po.23.00565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 01/11/2024] [Accepted: 03/15/2024] [Indexed: 05/31/2024] Open
Abstract
PURPOSE Develop and validate gene expression-based biomarker associated with recurrent disease to facilitate risk stratification of clear cell renal cell carcinoma (ccRCC). MATERIALS AND METHODS We retrospectively identified 110 patients who underwent radical nephrectomy for ccRCC (discovery cohort). Patients who recurred were matched on the basis of grade/stage to patients without recurrence. Capture whole-transcriptome sequencing was performed on RNA isolated from archival tissue using the Illumina platform. We developed a gene-expression signature to predict recurrence-free survival/disease-free survival (DFS) using a 15-fold lasso and elastic-net regularized linear Cox model. We derived the 31-gene cell cycle progression (mxCCP) score using RNA-seq data for each patient. Kaplan-Meier (KM) curves and multivariable Cox proportional hazard testing were used to validate the independent prognostic impact of the gene-expression signature on DFS, disease-specific survival (DSS), and overall survival (OS) in two validation data sets (combined n = 761). RESULTS After quality control, the discovery cohort comprised 50 patients with recurrence and 41 patients without, with a median follow-up of 26 and 36 months, respectively. We developed a 15-gene (15G) signature, which was independently associated with worse DFS and DSS (DFS: hazard ratio [HR], 11.08 [95% CI, 4.9 to 25.1]; DSS: HR, 9.67 [95% CI, 3.4 to 27.7]) in a multivariable model adjusting for clinicopathologic parameters (including stage, size, grade, and necrosis [SSIGN] score and Memorial Sloan Kettering Cancer Center nomogram) and mxCCP score. The 15G signature was also independently associated with worse DFS and DSS in both validation data sets (Validation A [n = 382], DFS: HR, 2.6 [95% CI, 1.6 to 4.3]; DSS: HR, 3 [95% CI, 1.4 to 6.1] and Validation B (n = 379), DFS: HR, 2.1 [95% CI, 1.2 to 3.6]; OS: HR, 3 [95% CI, 1.6 to 5.7]) adjusting for clinicopathologic variables and mxCCP score. CONCLUSION We developed and validated a novel 15G prognostic signature to improve risk stratification of patients with ccRCC. Pending further validation, this signature has the potential to facilitate optimal treatment allocation.
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Affiliation(s)
- Rohit Mehra
- University of Michigan Rogel Cancer Center, Ann Arbor, MI
- Michigan Center for Translational Pathology, Michigan Medicine, Ann Arbor, MI
- Department of Pathology, Michigan Medicine, Ann Arbor, MI
| | | | | | - Zayne Knuth
- Department of Urology, Michigan Medicine, Ann Arbor, MI
| | - Fengyun Su
- Michigan Center for Translational Pathology, Michigan Medicine, Ann Arbor, MI
- Department of Pathology, Michigan Medicine, Ann Arbor, MI
| | - Amy Kasputis
- Department of Urology, Michigan Medicine, Ann Arbor, MI
| | - Yuping Zhang
- Michigan Center for Translational Pathology, Michigan Medicine, Ann Arbor, MI
- Department of Pathology, Michigan Medicine, Ann Arbor, MI
| | - Rui Wang
- Michigan Center for Translational Pathology, Michigan Medicine, Ann Arbor, MI
- Department of Pathology, Michigan Medicine, Ann Arbor, MI
| | - Xuhong Cao
- Michigan Center for Translational Pathology, Michigan Medicine, Ann Arbor, MI
- Department of Pathology, Michigan Medicine, Ann Arbor, MI
- Howard Hughes Medical Institute, University of Michigan, Ann Arbor, MI
| | - Aaron M Udager
- University of Michigan Rogel Cancer Center, Ann Arbor, MI
- Michigan Center for Translational Pathology, Michigan Medicine, Ann Arbor, MI
- Department of Pathology, Michigan Medicine, Ann Arbor, MI
| | - Saravana M Dhanasekaran
- Michigan Center for Translational Pathology, Michigan Medicine, Ann Arbor, MI
- Department of Pathology, Michigan Medicine, Ann Arbor, MI
| | - Marcin P Cieslik
- Michigan Center for Translational Pathology, Michigan Medicine, Ann Arbor, MI
- Department of Pathology, Michigan Medicine, Ann Arbor, MI
- Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI
| | - Todd M Morgan
- University of Michigan Rogel Cancer Center, Ann Arbor, MI
- Department of Urology, Michigan Medicine, Ann Arbor, MI
| | - Simpa S Salami
- University of Michigan Rogel Cancer Center, Ann Arbor, MI
- Michigan Center for Translational Pathology, Michigan Medicine, Ann Arbor, MI
- Department of Urology, Michigan Medicine, Ann Arbor, MI
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28
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Groeneveld CS, Sanchez-Quiles V, Dufour F, Shi M, Dingli F, Nicolle R, Chapeaublanc E, Poullet P, Jeffery D, Krucker C, Maillé P, Vacherot F, Vordos D, Benhamou S, Lebret T, Micheau O, Zinovyev A, Loew D, Allory Y, de Reyniès A, Bernard-Pierrot I, Radvanyi F. Proteogenomic Characterization of Bladder Cancer Reveals Sensitivity to Apoptosis Induced by Tumor Necrosis Factor-related Apoptosis-inducing Ligand in FGFR3-mutated Tumors. Eur Urol 2024; 85:483-494. [PMID: 37380559 DOI: 10.1016/j.eururo.2023.05.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 04/26/2023] [Accepted: 05/26/2023] [Indexed: 06/30/2023]
Abstract
BACKGROUND Molecular understanding of muscle-invasive (MIBC) and non-muscle-invasive (NMIBC) bladder cancer is currently based primarily on transcriptomic and genomic analyses. OBJECTIVE To conduct proteogenomic analyses to gain insights into bladder cancer (BC) heterogeneity and identify underlying processes specific to tumor subgroups and therapeutic outcomes. DESIGN, SETTING, AND PARTICIPANTS Proteomic data were obtained for 40 MIBC and 23 NMIBC cases for which transcriptomic and genomic data were already available. Four BC-derived cell lines harboring FGFR3 alterations were tested with interventions. INTERVENTION Recombinant tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), second mitochondrial-derived activator of caspases mimetic (birinapant), pan-FGFR inhibitor (erdafitinib), and FGFR3 knockdown. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Proteomic groups from unsupervised analyses (uPGs) were characterized using clinicopathological, proteomic, genomic, transcriptomic, and pathway enrichment analyses. Additional enrichment analyses were performed for FGFR3-mutated tumors. Treatment effects on cell viability for FGFR3-altered cell lines were evaluated. Synergistic treatment effects were evaluated using the zero interaction potency model. RESULTS AND LIMITATIONS Five uPGs, covering both NMIBC and MIBC, were identified and bore coarse-grained similarity to transcriptomic subtypes underlying common features of these different entities; uPG-E was associated with the Ta pathway and enriched in FGFR3 mutations. Our analyses also highlighted enrichment of proteins involved in apoptosis in FGFR3-mutated tumors, not captured through transcriptomics. Genetic and pharmacological inhibition demonstrated that FGFR3 activation regulates TRAIL receptor expression and sensitizes cells to TRAIL-mediated apoptosis, further increased by combination with birinapant. CONCLUSIONS This proteogenomic study provides a comprehensive resource for investigating NMIBC and MIBC heterogeneity and highlights the potential of TRAIL-induced apoptosis as a treatment option for FGFR3-mutated bladder tumors, warranting a clinical investigation. PATIENT SUMMARY We integrated proteomics, genomics, and transcriptomics to refine molecular classification of bladder cancer, which, combined with clinical and pathological classification, should lead to more appropriate management of patients. Moreover, we identified new biological processes altered in FGFR3-mutated tumors and showed that inducing apoptosis represents a new potential therapeutic option.
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Affiliation(s)
- Clarice S Groeneveld
- Equipe labellisée Ligue Contre le Cancer, CNRS, UMR144, Institut Curie, PSL Research University, Paris, France; Centre de Recherche des Cordeliers, AP-HP, Université Paris Cité, Paris, France
| | - Virginia Sanchez-Quiles
- Equipe labellisée Ligue Contre le Cancer, CNRS, UMR144, Institut Curie, PSL Research University, Paris, France
| | - Florent Dufour
- Equipe labellisée Ligue Contre le Cancer, CNRS, UMR144, Institut Curie, PSL Research University, Paris, France; Inovarion, Paris, France
| | - Mingjun Shi
- Equipe labellisée Ligue Contre le Cancer, CNRS, UMR144, Institut Curie, PSL Research University, Paris, France; Department of Urology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Florent Dingli
- Centre de Recherche, CurieCoreTech Mass Spectrometry Proteomics, Institut Curie, PSL Research University, Paris, France
| | - Rémy Nicolle
- Centre de Recherche sur l'Inflammation (CRI), INSERM, U1149, CNRS, ERL 8252, Université Paris Cité, Paris, France
| | - Elodie Chapeaublanc
- Equipe labellisée Ligue Contre le Cancer, CNRS, UMR144, Institut Curie, PSL Research University, Paris, France
| | - Patrick Poullet
- INSERM U900, MINES ParisTech, Institut Curie, PSL Research University, Paris, France
| | - Daniel Jeffery
- Urology Medico-Scientific Program, Department of Translational Research, Institut Curie, PSL Research University, Paris, France
| | - Clémentine Krucker
- Equipe labellisée Ligue Contre le Cancer, CNRS, UMR144, Institut Curie, PSL Research University, Paris, France
| | - Pascale Maillé
- Département de Pathologie, Hôpital Henri Mondor, APHP, Créteil, France
| | | | - Dimitri Vordos
- Service d'Urologie, Hôpital Henri Mondor, APHP, Créteil, France
| | | | - Thierry Lebret
- Service d'Urologie, Hôpital Foch, UVSQ, Université Paris-Saclay, Suresnes, France
| | - Olivier Micheau
- INSERM, LNC UMR1231, Université Bourgogne Franche-Comté, Dijon, France
| | - Andrei Zinovyev
- INSERM U900, MINES ParisTech, Institut Curie, PSL Research University, Paris, France
| | - Damarys Loew
- Centre de Recherche, CurieCoreTech Mass Spectrometry Proteomics, Institut Curie, PSL Research University, Paris, France
| | - Yves Allory
- Equipe labellisée Ligue Contre le Cancer, CNRS, UMR144, Institut Curie, PSL Research University, Paris, France; Department of Pathology, Institut Curie, UVSQ, Université Paris-Saclay, Saint-Cloud, France
| | - Aurélien de Reyniès
- Centre de Recherche des Cordeliers, AP-HP, Université Paris Cité, Paris, France
| | - Isabelle Bernard-Pierrot
- Equipe labellisée Ligue Contre le Cancer, CNRS, UMR144, Institut Curie, PSL Research University, Paris, France
| | - François Radvanyi
- Equipe labellisée Ligue Contre le Cancer, CNRS, UMR144, Institut Curie, PSL Research University, Paris, France.
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Urrutia AA, Mesa-Ciller C, Guajardo-Grence A, Alkan HF, Soro-Arnáiz I, Vandekeere A, Ferreira Campos AM, Igelmann S, Fernández-Arroyo L, Rinaldi G, Lorendeau D, De Bock K, Fendt SM, Aragonés J. HIF1α-dependent uncoupling of glycolysis suppresses tumor cell proliferation. Cell Rep 2024; 43:114103. [PMID: 38607920 PMCID: PMC11063627 DOI: 10.1016/j.celrep.2024.114103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 11/20/2023] [Accepted: 03/27/2024] [Indexed: 04/14/2024] Open
Abstract
Hypoxia-inducible factor-1α (HIF1α) attenuates mitochondrial activity while promoting glycolysis. However, lower glycolysis is compromised in human clear cell renal cell carcinomas, in which HIF1α acts as a tumor suppressor by inhibiting cell-autonomous proliferation. Here, we find that, unexpectedly, HIF1α suppresses lower glycolysis after the glyceraldehyde 3-phosphate dehydrogenase (GAPDH) step, leading to reduced lactate secretion in different tumor cell types when cells encounter a limited pyruvate supply such as that typically found in the tumor microenvironment in vivo. This is because HIF1α-dependent attenuation of mitochondrial oxygen consumption increases the NADH/NAD+ ratio that suppresses the activity of the NADH-sensitive GAPDH glycolytic enzyme. This is manifested when pyruvate supply is limited, since pyruvate acts as an electron acceptor that prevents the increment of the NADH/NAD+ ratio. Furthermore, this anti-glycolytic function provides a molecular basis to explain how HIF1α can suppress tumor cell proliferation by increasing the NADH/NAD+ ratio.
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Affiliation(s)
- Andrés A Urrutia
- Research Unit, Hospital of Santa Cristina, Research Institute Princesa (IIS IP), Autonomous University of Madrid, 28009 Madrid, Spain
| | - Claudia Mesa-Ciller
- Research Unit, Hospital of Santa Cristina, Research Institute Princesa (IIS IP), Autonomous University of Madrid, 28009 Madrid, Spain
| | - Andrea Guajardo-Grence
- Research Unit, Hospital of Santa Cristina, Research Institute Princesa (IIS IP), Autonomous University of Madrid, 28009 Madrid, Spain
| | - H Furkan Alkan
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB Center for Cancer Biology, VIB, Herestraat 49, 3000 Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Herestraat 49, 3000 Leuven, Belgium
| | - Inés Soro-Arnáiz
- Laboratory of Exercise and Health, Department of Health Sciences and Technology, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland
| | - Anke Vandekeere
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB Center for Cancer Biology, VIB, Herestraat 49, 3000 Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Herestraat 49, 3000 Leuven, Belgium
| | - Ana Margarida Ferreira Campos
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB Center for Cancer Biology, VIB, Herestraat 49, 3000 Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Herestraat 49, 3000 Leuven, Belgium
| | - Sebastian Igelmann
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB Center for Cancer Biology, VIB, Herestraat 49, 3000 Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Herestraat 49, 3000 Leuven, Belgium
| | - Lucía Fernández-Arroyo
- Research Unit, Hospital of Santa Cristina, Research Institute Princesa (IIS IP), Autonomous University of Madrid, 28009 Madrid, Spain
| | - Gianmarco Rinaldi
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB Center for Cancer Biology, VIB, Herestraat 49, 3000 Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Herestraat 49, 3000 Leuven, Belgium
| | - Doriane Lorendeau
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB Center for Cancer Biology, VIB, Herestraat 49, 3000 Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Herestraat 49, 3000 Leuven, Belgium
| | - Katrien De Bock
- Laboratory of Exercise and Health, Department of Health Sciences and Technology, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland
| | - Sarah-Maria Fendt
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB Center for Cancer Biology, VIB, Herestraat 49, 3000 Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Herestraat 49, 3000 Leuven, Belgium
| | - Julián Aragonés
- Research Unit, Hospital of Santa Cristina, Research Institute Princesa (IIS IP), Autonomous University of Madrid, 28009 Madrid, Spain; CIBER de Enfermedades Cardiovasculares (CIBERCV), Carlos III Health Institute, Madrid, Spain.
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30
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Zhao D, Guo Y, Wei H, Jia X, Zhi Y, He G, Nie W, Huang L, Wang P, Laster KV, Liu Z, Wang J, Lee MH, Dong Z, Liu K. Multi-omics characterization of esophageal squamous cell carcinoma identifies molecular subtypes and therapeutic targets. JCI Insight 2024; 9:e171916. [PMID: 38652547 PMCID: PMC11141925 DOI: 10.1172/jci.insight.171916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 04/12/2024] [Indexed: 04/25/2024] Open
Abstract
Esophageal squamous cell carcinoma (ESCC) is the predominant form of esophageal cancer and is characterized by an unfavorable prognosis. To elucidate the distinct molecular alterations in ESCC and investigate therapeutic targets, we performed a comprehensive analysis of transcriptomics, proteomics, and phosphoproteomics data derived from 60 paired treatment-naive ESCC and adjacent nontumor tissue samples. Additionally, we conducted a correlation analysis to describe the regulatory relationship between transcriptomic and proteomic processes, revealing alterations in key metabolic pathways. Unsupervised clustering analysis of the proteomics data stratified patients with ESCC into 3 subtypes with different molecular characteristics and clinical outcomes. Notably, subtype III exhibited the worst prognosis and enrichment in proteins associated with malignant processes, including glycolysis and DNA repair pathways. Furthermore, translocase of inner mitochondrial membrane domain containing 1 (TIMMDC1) was validated as a potential prognostic molecule for ESCC. Moreover, integrated kinase-substrate network analysis using the phosphoproteome nominated candidate kinases as potential targets. In vitro and in vivo experiments further confirmed casein kinase II subunit α (CSNK2A1) as a potential kinase target for ESCC. These underlying data represent a valuable resource for researchers that may provide better insights into the biology and treatment of ESCC.
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Affiliation(s)
- Dengyun Zhao
- Department of Pathophysiology, School of Basic Medical Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
- China-US (Henan) Hormel Cancer Institute, Zhengzhou, Henan, China
- Tianjian Laboratory of Advanced Biomedical Sciences, Zhengzhou, Henan, China
| | - Yaping Guo
- Department of Pathophysiology, School of Basic Medical Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
- The Collaborative Innovation Center of Henan Province for Cancer Chemoprevention, Zhengzhou, Henan, China
- State Key Laboratory of Esophageal Cancer Prevention and Treatment, Zhengzhou University, Zhengzhou, Henan, China
| | - Huifang Wei
- Department of Pathophysiology, School of Basic Medical Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
- China-US (Henan) Hormel Cancer Institute, Zhengzhou, Henan, China
| | - Xuechao Jia
- Department of Pathophysiology, School of Basic Medical Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
- China-US (Henan) Hormel Cancer Institute, Zhengzhou, Henan, China
| | - Yafei Zhi
- Department of Pathophysiology, School of Basic Medical Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
- China-US (Henan) Hormel Cancer Institute, Zhengzhou, Henan, China
| | - Guiliang He
- China-US (Henan) Hormel Cancer Institute, Zhengzhou, Henan, China
| | - Wenna Nie
- China-US (Henan) Hormel Cancer Institute, Zhengzhou, Henan, China
| | - Limeng Huang
- China-US (Henan) Hormel Cancer Institute, Zhengzhou, Henan, China
| | - Penglei Wang
- Department of Pathophysiology, School of Basic Medical Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
- China-US (Henan) Hormel Cancer Institute, Zhengzhou, Henan, China
| | | | - Zhicai Liu
- Linzhou Cancer Hospital, Anyang, Henan, China
| | - Jinwu Wang
- Linzhou Cancer Hospital, Anyang, Henan, China
| | - Mee-Hyun Lee
- Department of Pathophysiology, School of Basic Medical Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
- China-US (Henan) Hormel Cancer Institute, Zhengzhou, Henan, China
- College of Korean Medicine, Dongshin University, Naju, Jeonnam, Republic of Korea
| | - Zigang Dong
- Department of Pathophysiology, School of Basic Medical Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
- China-US (Henan) Hormel Cancer Institute, Zhengzhou, Henan, China
- Tianjian Laboratory of Advanced Biomedical Sciences, Zhengzhou, Henan, China
- The Collaborative Innovation Center of Henan Province for Cancer Chemoprevention, Zhengzhou, Henan, China
- State Key Laboratory of Esophageal Cancer Prevention and Treatment, Zhengzhou University, Zhengzhou, Henan, China
- Provincial Cooperative Innovation Center for Cancer Chemoprevention, Zhengzhou University, Zhengzhou, Henan, China
| | - Kangdong Liu
- Department of Pathophysiology, School of Basic Medical Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
- China-US (Henan) Hormel Cancer Institute, Zhengzhou, Henan, China
- Tianjian Laboratory of Advanced Biomedical Sciences, Zhengzhou, Henan, China
- The Collaborative Innovation Center of Henan Province for Cancer Chemoprevention, Zhengzhou, Henan, China
- State Key Laboratory of Esophageal Cancer Prevention and Treatment, Zhengzhou University, Zhengzhou, Henan, China
- Provincial Cooperative Innovation Center for Cancer Chemoprevention, Zhengzhou University, Zhengzhou, Henan, China
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31
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Yin K, Zhao M, Xu Y, Zheng Z, Huang S, Liang D, Dong H, Guo Y, Lin L, Song J, Zhang H, Zheng J, Zhu Z, Yang C. Well-Paired-Seq2: High-Throughput and High-Sensitivity Strategy for Characterizing Low RNA-Content Cell/Nucleus Transcriptomes. Anal Chem 2024; 96:6301-6310. [PMID: 38597061 DOI: 10.1021/acs.analchem.3c05785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/11/2024]
Abstract
Single-cell RNA sequencing (scRNA-seq) is a transformative technology that unravels the intricate cellular state heterogeneity. However, the Poisson-dependent cell capture and low sensitivity in scRNA-seq methods pose challenges for throughput and samples with a low RNA-content. Herein, to address these challenges, we present Well-Paired-Seq2 (WPS2), harnessing size-exclusion and quasi-static hydrodynamics for efficient cell capture. WPS2 exploits molecular crowding effect, tailing activity enhancement in reverse transcription, and homogeneous enzymatic reaction in the initial bead-based amplification to achieve 3116 genes and 8447 transcripts with an average of ∼20000 reads per cell. WPS2 detected 1420 more genes and 4864 more transcripts than our previous Well-Paired-Seq. It sensitively characterizes transcriptomes of low RNA-content single cells and nuclei, overcoming the Poisson limit for cell and barcoded bead capture. WPS2 also profiles transcriptomes from frozen clinical samples, revealing heterogeneous tumor copy number variations and intercellular crosstalk in clear cell renal cell carcinomas. Additionally, we provide the first single-cell-level characterization of rare metanephric adenoma (MA) and uncover potential specific markers. With the advantages of high sensitivity and high throughput, WPS2 holds promise for diverse basic and clinical research.
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Affiliation(s)
- Kun Yin
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
- Institute of Molecular Medicine, State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200120, China
| | - Meijuan Zhao
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - Yiling Xu
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - Zhong Zheng
- Institute of Molecular Medicine, State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200120, China
| | - Shanqing Huang
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - Dianyi Liang
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - He Dong
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - Ye Guo
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - Li Lin
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - Jia Song
- Institute of Molecular Medicine, State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200120, China
| | - Huimin Zhang
- Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen 361005, China
| | - Junhua Zheng
- Institute of Molecular Medicine, State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200120, China
| | - Zhi Zhu
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - Chaoyong Yang
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
- Institute of Molecular Medicine, State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200120, China
- Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen 361005, China
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Manda V, Pavelka J, Lau E. Proteomics applications in next generation induced pluripotent stem cell models. Expert Rev Proteomics 2024; 21:217-228. [PMID: 38511670 PMCID: PMC11065590 DOI: 10.1080/14789450.2024.2334033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 03/08/2024] [Indexed: 03/22/2024]
Abstract
INTRODUCTION Induced pluripotent stem (iPS) cell technology has transformed biomedical research. New opportunities now exist to create new organoids, microtissues, and body-on-a-chip systems for basic biology investigations and clinical translations. AREAS COVERED We discuss the utility of proteomics for attaining an unbiased view into protein expression changes during iPS cell differentiation, cell maturation, and tissue generation. The ability to discover cell-type specific protein markers during the differentiation and maturation of iPS-derived cells has led to new strategies to improve cell production yield and fidelity. In parallel, proteomic characterization of iPS-derived organoids is helping to realize the goal of bridging in vitro and in vivo systems. EXPERT OPINIONS We discuss some current challenges of proteomics in iPS cell research and future directions, including the integration of proteomic and transcriptomic data for systems-level analysis.
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Affiliation(s)
- Vyshnavi Manda
- Department of Medicine, Division of Cardiology, University of Colorado School of Medicine, Aurora, Colorado, USA
- Consortium for Fibrosis Research and Translation, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Jay Pavelka
- Department of Medicine, Division of Cardiology, University of Colorado School of Medicine, Aurora, Colorado, USA
- Consortium for Fibrosis Research and Translation, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Edward Lau
- Department of Medicine, Division of Cardiology, University of Colorado School of Medicine, Aurora, Colorado, USA
- Consortium for Fibrosis Research and Translation, University of Colorado School of Medicine, Aurora, Colorado, USA
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Coffey NJ, Simon MC. Metabolic alterations in hereditary and sporadic renal cell carcinoma. Nat Rev Nephrol 2024; 20:233-250. [PMID: 38253811 PMCID: PMC11165401 DOI: 10.1038/s41581-023-00800-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/30/2023] [Indexed: 01/24/2024]
Abstract
Kidney cancer is the seventh leading cause of cancer in the world, and its incidence is on the rise. Renal cell carcinoma (RCC) is the most common form and is a heterogeneous disease comprising three major subtypes that vary in their histology, clinical course and driver mutations. These subtypes include clear cell RCC, papillary RCC and chromophobe RCC. Molecular analyses of hereditary and sporadic forms of RCC have revealed that this complex and deadly disease is characterized by metabolic pathway alterations in cancer cells that lead to deregulated oxygen and nutrient sensing, as well as impaired tricarboxylic acid cycle activity. These metabolic changes facilitate tumour growth and survival. Specifically, studies of the metabolic features of RCC have led to the discovery of oncometabolites - fumarate and succinate - that can promote tumorigenesis, moonlighting functions of enzymes, and substrate auxotrophy owing to the disruption of pathways that enable the production of arginine and cholesterol. These metabolic alterations within RCC can be exploited to identify new therapeutic targets and interventions, in combination with novel approaches that minimize the systemic toxicity of metabolic inhibitors and reduce the risk of drug resistance owing to metabolic plasticity.
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Affiliation(s)
- Nathan J Coffey
- Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - M Celeste Simon
- Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, PA, USA.
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Avelar RA, Gupta R, Carvette G, da Veiga Leprevost F, Colina J, Teitel J, Nesvizhskii AI, O’Connor CM, Hatzoglou M, Shenolikar S, Arvan P, Narla G, DiFeo A. Integrated stress response plasticity governs normal cell adaptation to chronic stress via the PP2A-TFE3-ATF4 pathway. RESEARCH SQUARE 2024:rs.3.rs-4013396. [PMID: 38585734 PMCID: PMC10996823 DOI: 10.21203/rs.3.rs-4013396/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
The integrated stress response (ISR) regulates cell fate during conditions of stress by leveraging the cell's capacity to endure sustainable and efficient adaptive stress responses. Protein phosphatase 2A (PP2A) activity modulation has been shown to be successful in achieving both therapeutic efficacy and safety across various cancer models; however, the molecular mechanisms driving its selective antitumor effects remain unclear. Here, we show for the first time that ISR plasticity relies on PP2A activation to regulate drug response and dictate cellular fate under conditions of chronic stress. We demonstrate that genetic and chemical modulation of the PP2A leads to chronic proteolytic stress and triggers an ISR to dictate cell fate. More specifically, we uncovered that the PP2A-TFE3-ATF4 pathway governs ISR cell plasticity during endoplasmic reticular and cellular stress independent of the unfolded protein response. We further show that normal cells reprogram their genetic signatures to undergo ISR-mediated adaptation and homeostatic recovery thereby successfully avoiding toxicity following PP2A-mediated stress. Conversely, oncogenic specific cytotoxicity induced by chemical modulation of PP2A is achieved by activating chronic and irreversible ISR in cancer cells. Our findings propose that a differential response to chemical modulation of PP2A is determined by intrinsic ISR plasticity, providing a novel biological vulnerability to selectively induce cancer cell death and improve targeted therapeutic efficacy.
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Affiliation(s)
- Rita A. Avelar
- Department of Pathology, The University of Michigan, Ann Arbor, MI 48109, USA
- Rogel Cancer Center, The University of Michigan, Ann Arbor, MI 48109, USA
| | - Riya Gupta
- Department of Pathology, The University of Michigan, Ann Arbor, MI 48109, USA
- Rogel Cancer Center, The University of Michigan, Ann Arbor, MI 48109, USA
| | - Gracie Carvette
- Department of Pathology, The University of Michigan, Ann Arbor, MI 48109, USA
- Rogel Cancer Center, The University of Michigan, Ann Arbor, MI 48109, USA
| | | | - Jose Colina
- Department of Pathology, The University of Michigan, Ann Arbor, MI 48109, USA
- Rogel Cancer Center, The University of Michigan, Ann Arbor, MI 48109, USA
| | - Jessica Teitel
- Department of Pathology, The University of Michigan, Ann Arbor, MI 48109, USA
- Rogel Cancer Center, The University of Michigan, Ann Arbor, MI 48109, USA
| | - Alexey I. Nesvizhskii
- Department of Pathology, The University of Michigan, Ann Arbor, MI 48109, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Caitlin M. O’Connor
- Rogel Cancer Center, The University of Michigan, Ann Arbor, MI 48109, USA
- Department of Internal Medicine, Division of Genetic Medicine, University of Michigan, Ann Arbor, MI 48109, USA
| | - Maria Hatzoglou
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Shirish Shenolikar
- Emeritus Professor, Duke-NUS Medical School, Singapore
- Professor Emeritus, Duke University School of Medicine, USA
| | - Peter Arvan
- Division of Metabolism Endocrinology and Diabetes, University of Michigan Medical Center, Ann Arbor, MI 48109, USA
| | - Goutham Narla
- Rogel Cancer Center, The University of Michigan, Ann Arbor, MI 48109, USA
- Department of Internal Medicine, Division of Genetic Medicine, University of Michigan, Ann Arbor, MI 48109, USA
| | - Analisa DiFeo
- Department of Pathology, The University of Michigan, Ann Arbor, MI 48109, USA
- Rogel Cancer Center, The University of Michigan, Ann Arbor, MI 48109, USA
- Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, MI 48109, USA
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Lundy DJ, Szomolay B, Liao CT. Systems Approaches to Cell Culture-Derived Extracellular Vesicles for Acute Kidney Injury Therapy: Prospects and Challenges. FUNCTION 2024; 5:zqae012. [PMID: 38706963 PMCID: PMC11065115 DOI: 10.1093/function/zqae012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 03/02/2024] [Accepted: 03/05/2024] [Indexed: 05/07/2024] Open
Abstract
Acute kidney injury (AKI) is a heterogeneous syndrome, comprising diverse etiologies of kidney insults that result in high mortality and morbidity if not well managed. Although great efforts have been made to investigate underlying pathogenic mechanisms of AKI, there are limited therapeutic strategies available. Extracellular vesicles (EV) are membrane-bound vesicles secreted by various cell types, which can serve as cell-free therapy through transfer of bioactive molecules. In this review, we first overview the AKI syndrome and EV biology, with a particular focus on the technical aspects and therapeutic application of cell culture-derived EVs. Second, we illustrate how multi-omic approaches to EV miRNA, protein, and genomic cargo analysis can yield new insights into their mechanisms of action and address unresolved questions in the field. We then summarize major experimental evidence regarding the therapeutic potential of EVs in AKI, which we subdivide into stem cell and non-stem cell-derived EVs. Finally, we highlight the challenges and opportunities related to the clinical translation of animal studies into human patients.
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Affiliation(s)
- David J Lundy
- Graduate Institute of Biomedical Materials & Tissue Engineering, Taipei Medical University, Taipei 235603, Taiwan
- International PhD Program in Biomedical Engineering, Taipei Medical University, Taipei 235603, Taiwan
- Center for Cell Therapy, Taipei Medical University Hospital, Taipei 110301, Taiwan
| | - Barbara Szomolay
- Systems Immunity Research Institute, Cardiff University School of Medicine, Cardiff CF14 4XN, UK
- Division of Infection and Immunity, Cardiff University School of Medicine, Cardiff CF14 4XN, UK
| | - Chia-Te Liao
- Division of Nephrology, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City 23561, Taiwan
- Division of Nephrology, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan
- Research Center of Urology and Kidney, Taipei Medical University, Taipei 110, Taiwan
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36
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Jiang W, Jaehnig EJ, Liao Y, Yaron-Barir TM, Johnson JL, Cantley LC, Zhang B. Illuminating the Dark Cancer Phosphoproteome Through a Machine-Learned Co-Regulation Map of 26,280 Phosphosites. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.19.585786. [PMID: 38562798 PMCID: PMC10983930 DOI: 10.1101/2024.03.19.585786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Mass spectrometry-based phosphoproteomics offers a comprehensive view of protein phosphorylation, but limited knowledge about the regulation and function of most phosphosites restricts our ability to extract meaningful biological insights from phosphoproteomics data. To address this, we combine machine learning and phosphoproteomic data from 1,195 tumor specimens spanning 11 cancer types to construct CoPheeMap, a network mapping the co-regulation of 26,280 phosphosites. Integrating network features from CoPheeMap into a machine learning model, CoPheeKSA, we achieve superior performance in predicting kinase-substrate associations. CoPheeKSA reveals 24,015 associations between 9,399 phosphosites and 104 serine/threonine kinases, including many unannotated phosphosites and under-studied kinases. We validate the accuracy of these predictions using experimentally determined kinase-substrate specificities. By applying CoPheeMap and CoPheeKSA to phosphosites with high computationally predicted functional significance and cancer-associated phosphosites, we demonstrate the effectiveness of these tools in systematically illuminating phosphosites of interest, revealing dysregulated signaling processes in human cancer, and identifying under-studied kinases as putative therapeutic targets.
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Holguin-Cruz JA, Bui JM, Jha A, Na D, Gsponer J. Widespread alteration of protein autoinhibition in human cancers. Cell Syst 2024; 15:246-263.e7. [PMID: 38366601 DOI: 10.1016/j.cels.2024.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 06/20/2023] [Accepted: 01/26/2024] [Indexed: 02/18/2024]
Abstract
Autoinhibition is a prevalent allosteric regulatory mechanism in signaling proteins. Reduced autoinhibition underlies the tumorigenic effect of some known cancer drivers, but whether autoinhibition is altered generally in cancer remains elusive. Here, we demonstrate that cancer-associated missense mutations, in-frame insertions/deletions, and fusion breakpoints are enriched within inhibitory allosteric switches (IASs) across all cancer types. Selection for IASs that are recurrently mutated in cancers identifies established and unknown cancer drivers. Recurrent missense mutations in IASs of these drivers are associated with distinct, cancer-specific changes in molecular signaling. For the specific case of PPP3CA, the catalytic subunit of calcineurin, we provide insights into the molecular mechanisms of altered autoinhibition by cancer mutations using biomolecular simulations, and demonstrate that such mutations are associated with transcriptome changes consistent with increased calcineurin signaling. Our integrative study shows that autoinhibition-modulating genetic alterations are positively selected for by cancer cells.
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Affiliation(s)
- Jorge A Holguin-Cruz
- Michael Smith Laboratories, University of British Columbia, Vancouver, BC V6T 1Z4, Canada; Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Jennifer M Bui
- Michael Smith Laboratories, University of British Columbia, Vancouver, BC V6T 1Z4, Canada; Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Ashwani Jha
- Michael Smith Laboratories, University of British Columbia, Vancouver, BC V6T 1Z4, Canada; Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Dokyun Na
- School of Integrative Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 156-756, Republic of Korea
| | - Jörg Gsponer
- Michael Smith Laboratories, University of British Columbia, Vancouver, BC V6T 1Z4, Canada; Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
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Xu X, Khunsriraksakul C, Eales JM, Rubin S, Scannali D, Saluja S, Talavera D, Markus H, Wang L, Drzal M, Maan A, Lay AC, Prestes PR, Regan J, Diwadkar AR, Denniff M, Rempega G, Ryszawy J, Król R, Dormer JP, Szulinska M, Walczak M, Antczak A, Matías-García PR, Waldenberger M, Woolf AS, Keavney B, Zukowska-Szczechowska E, Wystrychowski W, Zywiec J, Bogdanski P, Danser AHJ, Samani NJ, Guzik TJ, Morris AP, Liu DJ, Charchar FJ, Tomaszewski M. Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets. Nat Commun 2024; 15:2359. [PMID: 38504097 PMCID: PMC10950894 DOI: 10.1038/s41467-024-46132-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 02/14/2024] [Indexed: 03/21/2024] Open
Abstract
Genetic mechanisms of blood pressure (BP) regulation remain poorly defined. Using kidney-specific epigenomic annotations and 3D genome information we generated and validated gene expression prediction models for the purpose of transcriptome-wide association studies in 700 human kidneys. We identified 889 kidney genes associated with BP of which 399 were prioritised as contributors to BP regulation. Imputation of kidney proteome and microRNAome uncovered 97 renal proteins and 11 miRNAs associated with BP. Integration with plasma proteomics and metabolomics illuminated circulating levels of myo-inositol, 4-guanidinobutanoate and angiotensinogen as downstream effectors of several kidney BP genes (SLC5A11, AGMAT, AGT, respectively). We showed that genetically determined reduction in renal expression may mimic the effects of rare loss-of-function variants on kidney mRNA/protein and lead to an increase in BP (e.g., ENPEP). We demonstrated a strong correlation (r = 0.81) in expression of protein-coding genes between cells harvested from urine and the kidney highlighting a diagnostic potential of urinary cell transcriptomics. We uncovered adenylyl cyclase activators as a repurposing opportunity for hypertension and illustrated examples of BP-elevating effects of anticancer drugs (e.g. tubulin polymerisation inhibitors). Collectively, our studies provide new biological insights into genetic regulation of BP with potential to drive clinical translation in hypertension.
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Affiliation(s)
- Xiaoguang Xu
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | | | - James M Eales
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Sebastien Rubin
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - David Scannali
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Sushant Saluja
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - David Talavera
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Havell Markus
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Lida Wang
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Maciej Drzal
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Akhlaq Maan
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Abigail C Lay
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Priscilla R Prestes
- Health Innovation and Transformation Centre, Federation University Australia, Ballarat, Australia
| | - Jeniece Regan
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Avantika R Diwadkar
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Matthew Denniff
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Grzegorz Rempega
- Department of Urology, Medical University of Silesia, Katowice, Poland
| | - Jakub Ryszawy
- Department of Urology, Medical University of Silesia, Katowice, Poland
| | - Robert Król
- Department of General, Vascular and Transplant Surgery, Faculty of Medical Sciences in Katowice, Medical University of Silesia, Katowice, Poland
| | - John P Dormer
- Department of Cellular Pathology, University Hospitals of Leicester, Leicester, UK
| | - Monika Szulinska
- Department of Obesity, Metabolic Disorders Treatment and Clinical Dietetics, Karol Marcinkowski University of Medical Sciences, Poznan, Poland
| | - Marta Walczak
- Department of Internal Diseases, Metabolic Disorders and Arterial Hypertension, Poznan University of Medical Sciences, Poznan, Poland
| | - Andrzej Antczak
- Department of Urology and Uro-oncology, Karol Marcinkowski University of Medical Sciences, Poznan, Poland
| | - Pamela R Matías-García
- Institute of Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- German Research Center for Cardiovascular Disease (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Melanie Waldenberger
- Institute of Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- German Research Center for Cardiovascular Disease (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Adrian S Woolf
- Division of Cell Matrix Biology and Regenerative Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Royal Manchester Children's Hospital and Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, UK
| | - Bernard Keavney
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
- Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust Manchester, Manchester Royal Infirmary, Manchester, UK
| | | | - Wojciech Wystrychowski
- Department of General, Vascular and Transplant Surgery, Faculty of Medical Sciences in Katowice, Medical University of Silesia, Katowice, Poland
| | - Joanna Zywiec
- Department of Internal Medicine, Diabetology and Nephrology, Zabrze, Medical University of Silesia, Katowice, Poland
| | - Pawel Bogdanski
- Department of Obesity, Metabolic Disorders Treatment and Clinical Dietetics, Karol Marcinkowski University of Medical Sciences, Poznan, Poland
| | - A H Jan Danser
- Department of Internal Medicine, Division of Pharmacology and Vascular Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Tomasz J Guzik
- Department of Internal Medicine, Jagiellonian University Medical College, Kraków, Poland
- Centre for Cardiovascular Sciences, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
- Center for Medical Genomics OMICRON, Jagiellonian University Medical College, Kraków, Poland
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal & Dermatological Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Dajiang J Liu
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Fadi J Charchar
- Health Innovation and Transformation Centre, Federation University Australia, Ballarat, Australia
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- Department of Physiology, University of Melbourne, Melbourne, Australia
| | - Maciej Tomaszewski
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK.
- Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust Manchester, Manchester Royal Infirmary, Manchester, UK.
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Chen R, Wu J, Che Y, Jiao Y, Sun H, Zhao Y, Chen P, Meng L, Zhao T. Machine learning-driven prognostic analysis of cuproptosis and disulfidptosis-related lncRNAs in clear cell renal cell carcinoma: a step towards precision oncology. Eur J Med Res 2024; 29:176. [PMID: 38491523 PMCID: PMC10943875 DOI: 10.1186/s40001-024-01763-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 03/01/2024] [Indexed: 03/18/2024] Open
Abstract
Cuproptosis and disulfidptosis, recently discovered mechanisms of cell death, have demonstrated that differential expression of key genes and long non-coding RNAs (lncRNAs) profoundly influences tumor development and affects their drug sensitivity. Clear cell renal cell carcinoma (ccRCC), the most common subtype of kidney cancer, presently lacks research utilizing cuproptosis and disulfidptosis-related lncRNAs (CDRLRs) as prognostic markers. In this study, we analyzed RNA-seq data, clinical information, and mutation data from The Cancer Genome Atlas (TCGA) on ccRCC and cross-referenced it with known cuproptosis and disulfidptosis-related genes (CDRGs). Using the LASSO machine learning algorithm, we identified four CDRLRs-ACVR2B-AS1, AC095055.1, AL161782.1, and MANEA-DT-that are strongly associated with prognosis and used them to construct a prognostic risk model. To verify the model's reliability and validate these four CDRLRs as significant prognostic factors, we performed dataset grouping validation, followed by RT-qPCR and external database validation for differential expression and prognosis of CDRLRs in ccRCC. Gene function and pathway analysis were conducted using Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) for high- and low-risk groups. Additionally, we have analyzed the tumor mutation burden (TMB) and the immune microenvironment (TME), employing the oncoPredict and Immunophenoscore (IPS) algorithms to assess the sensitivity of diverse risk categories to targeted therapeutics and immunosuppressants. Our predominant objective is to refine prognostic predictions for patients with ccRCC and inform treatment decisions by conducting an exhaustive study on cuproptosis and disulfidptosis.
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Affiliation(s)
- Ronghui Chen
- School of Clinical Medicine, Shandong Second Medical University, Weifang, 261053, China
- Department of Oncology, People's Hospital of Rizhao, Rizhao, 276826, China
| | - Jun Wu
- Department of Oncology, People's Hospital of Rizhao, Rizhao, 276826, China
| | - Yinwei Che
- Department of Central Laboratory, Shandong Provincial Key Medical and Health Laboratory, Rizhao Key Laboratory of Basic Research on Anesthesia and Respiratory Intensive Care, The People's Hospital of Rizhao, Rizhao, 276826, Shandong, China
| | - Yuzhuo Jiao
- Department of Central Laboratory, Shandong Provincial Key Medical and Health Laboratory, Rizhao Key Laboratory of Basic Research on Anesthesia and Respiratory Intensive Care, The People's Hospital of Rizhao, Rizhao, 276826, Shandong, China
| | - Huashan Sun
- Department of Central Laboratory, Shandong Provincial Key Medical and Health Laboratory, Rizhao Key Laboratory of Basic Research on Anesthesia and Respiratory Intensive Care, The People's Hospital of Rizhao, Rizhao, 276826, Shandong, China
| | - Yinuo Zhao
- Department of Pathology, People's Hospital of Rizhao, Rizhao, 276826, China
| | - Pingping Chen
- Department of Pathology, People's Hospital of Rizhao, Rizhao, 276826, China
| | - Lingxin Meng
- Department of Oncology, People's Hospital of Rizhao, Rizhao, 276826, China.
| | - Tao Zhao
- Department of Central Laboratory, Shandong Provincial Key Medical and Health Laboratory, Rizhao Key Laboratory of Basic Research on Anesthesia and Respiratory Intensive Care, The People's Hospital of Rizhao, Rizhao, 276826, Shandong, China
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40
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Bateman NW, Abulez T, Soltis AR, McPherson A, Choi S, Garsed DW, Pandey A, Tian C, Hood BL, Conrads KA, Teng PN, Oliver J, Gist G, Mitchell D, Litzi TJ, Tarney CM, Crothers BA, Mhawech-Fauceglia P, Dalgard CL, Wilkerson MD, Pierobon M, Petricoin EF, Yan C, Meerzaman D, Bodelon C, Wentzensen N, Lee JSH, Huntsman DG, Shah S, Shriver CD, Phippen NT, Darcy KM, Bowtell DDL, Conrads TP, Maxwell GL. Proteogenomic analysis of enriched HGSOC tumor epithelium identifies prognostic signatures and therapeutic vulnerabilities. NPJ Precis Oncol 2024; 8:68. [PMID: 38480868 PMCID: PMC10937683 DOI: 10.1038/s41698-024-00519-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 01/15/2024] [Indexed: 03/17/2024] Open
Abstract
We performed a deep proteogenomic analysis of bulk tumor and laser microdissection enriched tumor cell populations from high-grade serous ovarian cancer (HGSOC) tissue specimens spanning a broad spectrum of purity. We identified patients with longer progression-free survival had increased immune-related signatures and validated proteins correlating with tumor-infiltrating lymphocytes in 65 tumors from an independent cohort of HGSOC patients, as well as with overall survival in an additional 126 HGSOC patient cohort. We identified that homologous recombination deficient (HRD) tumors are enriched in pathways associated with metabolism and oxidative phosphorylation that we validated in independent patient cohorts. We further identified that polycomb complex protein BMI-1 is elevated in HR proficient (HRP) tumors, that elevated BMI-1 correlates with poor overall survival in HRP but not HRD HGSOC patients, and that HRP HGSOC cells are uniquely sensitive to BMI-1 inhibition.
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Affiliation(s)
- Nicholas W Bateman
- Gynecologic Cancer Center of Excellence, Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.
- The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc, Bethesda, MD, USA.
- The John P. Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University and Walter Reed National Military Medical Center, Bethesda, MD, USA.
| | - Tamara Abulez
- Gynecologic Cancer Center of Excellence, Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc, Bethesda, MD, USA
| | - Anthony R Soltis
- The American Genome Center, Collaborative Health Initiative Research Program, Department of Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Andrew McPherson
- Department of Computational Oncology, Memorial Sloan Kettering Cancer Center, Manhattan, NY, USA
| | - Seongmin Choi
- Department of Computational Oncology, Memorial Sloan Kettering Cancer Center, Manhattan, NY, USA
| | - Dale W Garsed
- Peter MacCallum Cancer Centre, Parkville, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Victoria, Australia
| | - Ahwan Pandey
- Peter MacCallum Cancer Centre, Parkville, Melbourne, Victoria, Australia
| | - Chunqiao Tian
- Gynecologic Cancer Center of Excellence, Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc, Bethesda, MD, USA
| | - Brian L Hood
- Gynecologic Cancer Center of Excellence, Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc, Bethesda, MD, USA
| | - Kelly A Conrads
- Gynecologic Cancer Center of Excellence, Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc, Bethesda, MD, USA
| | - Pang-Ning Teng
- Gynecologic Cancer Center of Excellence, Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc, Bethesda, MD, USA
| | - Julie Oliver
- Gynecologic Cancer Center of Excellence, Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc, Bethesda, MD, USA
| | - Glenn Gist
- Gynecologic Cancer Center of Excellence, Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc, Bethesda, MD, USA
| | - Dave Mitchell
- Gynecologic Cancer Center of Excellence, Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc, Bethesda, MD, USA
| | - Tracy J Litzi
- Gynecologic Cancer Center of Excellence, Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc, Bethesda, MD, USA
| | - Christopher M Tarney
- Gynecologic Cancer Center of Excellence, Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Barbara A Crothers
- The Joint Pathology Center, Defense Health Agency, National Capital Region Medical Directorate, Silver Spring, MD, USA
| | - Paulette Mhawech-Fauceglia
- Department of Anatomic Pathology, Division of Gynecologic Pathology, University of Southern California, Los Angeles, CA, USA
| | - Clifton L Dalgard
- The American Genome Center, Collaborative Health Initiative Research Program, Department of Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Matthew D Wilkerson
- The American Genome Center, Collaborative Health Initiative Research Program, Department of Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Mariaelena Pierobon
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA, USA
| | - Emanuel F Petricoin
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA, USA
| | - Chunhua Yan
- Center for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, MD, USA
| | - Daoud Meerzaman
- Center for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, MD, USA
| | - Clara Bodelon
- Division of Cancer Epidemiology and Genetics National Cancer Institute, Rockville, MD, USA
| | - Nicolas Wentzensen
- Division of Cancer Epidemiology and Genetics National Cancer Institute, Rockville, MD, USA
| | - Jerry S H Lee
- Ellison Institute for Transformative Medicine, University of Southern California, Los Angeles, CA, USA
| | - David G Huntsman
- Department of Pathology and Laboratory Medicine, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Sohrab Shah
- Department of Computational Oncology, Memorial Sloan Kettering Cancer Center, Manhattan, NY, USA
| | - Craig D Shriver
- The John P. Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University and Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - Neil T Phippen
- Gynecologic Cancer Center of Excellence, Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Kathleen M Darcy
- Gynecologic Cancer Center of Excellence, Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc, Bethesda, MD, USA
- The John P. Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University and Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - David D L Bowtell
- Peter MacCallum Cancer Centre, Parkville, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Victoria, Australia
| | - Thomas P Conrads
- Gynecologic Cancer Center of Excellence, Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.
- The John P. Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University and Walter Reed National Military Medical Center, Bethesda, MD, USA.
- Women's Health Integrated Research Center, Women's Service Line, Inova Health System, Falls Church, VA, USA.
| | - G Larry Maxwell
- Gynecologic Cancer Center of Excellence, Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.
- The John P. Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University and Walter Reed National Military Medical Center, Bethesda, MD, USA.
- Women's Health Integrated Research Center, Women's Service Line, Inova Health System, Falls Church, VA, USA.
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41
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Yi H, Liu L, Zhang J, Guo K, Cao Y, Sun P, Wang H. GALNT2 targeted by miR-139-5p promotes proliferation of clear cell renal cell carcinoma via inhibition of LATS2 activation. Discov Oncol 2024; 15:73. [PMID: 38478152 PMCID: PMC10937861 DOI: 10.1007/s12672-024-00930-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 03/08/2024] [Indexed: 03/17/2024] Open
Abstract
Polypeptide N-Acetylgalactosaminyltransferase (GALNTs) are critical enzymes that initiate mucin type-O glycosylation, and are closely associated with the occurrence and development of multiple cancers. However, the significance of GALNT2 in clear cell renal cell carcinoma (ccRCC) progression remains largely undetermined. Based on public multi-omics analysis, GALNT2 was strongly elevated in ccRCC versus adjoining nontumor tissues, and it displayed a relationship with poor overall survival (OS) of ccRCC patients. In addition, GALNT2 over-expression accelerated proliferation of renal cancer cell (RCC) lines. In contrast, GALNT2 knockdown using shRNAs suppressed cell proliferation, and this was rescued by LATS2 knockdown. Similarly, GALNT2 deficiency enhanced p-LATS2/LATS2 expression. LATS2 is activated by phosphorylation (p-LATS2) and, in turn, phosphorylate the downstream substrate protein YAP. Phosphorylated YAP (p-YAP) stimulated its degradation and cytoplasmic retention, as it was unable to translocate to the nucleus. This resulted in reduced cell proliferation. Subsequently, we explored the upstream miRNAs of GALNT2. Using dual luciferase reporter assay, we revealed that miR-139-5p interacted with the 3' UTR of GALNT2. Low miR-139-5p expression was associated with worse ccRCC patient outcome. Based on our experiments, miR-139-5p overexpression inhibited RCC proliferation, and this phenotype was rescued by GALNT2 overexpression. Given these evidences, the miR-139-5p-GALNT2-LATS2 axis is critical for RCC proliferation, and it is an excellent candidate for a new therapeutic target in ccRCC.
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Affiliation(s)
- Haisheng Yi
- Department of Andrology, The First Hospital of Jilin University, Changchun, 130012, China
| | - Lingyun Liu
- Department of Andrology, The First Hospital of Jilin University, Changchun, 130012, China
| | - Jingshun Zhang
- Reproductive Medical Center, Department of Obstetrics and Gynecology, The Second Hospital of Jilin University, Changchun, 130041, China
| | - Kaimin Guo
- Department of Andrology, The First Hospital of Jilin University, Changchun, 130012, China
| | - Yin Cao
- Department of Andrology, The First Hospital of Jilin University, Changchun, 130012, China
| | - Penghao Sun
- Department of Andrology, The First Hospital of Jilin University, Changchun, 130012, China
| | - Hongliang Wang
- Department of Andrology, The First Hospital of Jilin University, Changchun, 130012, China.
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42
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Kim KH, Migliozzi S, Koo H, Hong JH, Park SM, Kim S, Kwon HJ, Ha S, Garofano L, Oh YT, D'Angelo F, Kim CI, Kim S, Lee JY, Kim J, Hong J, Jang EH, Mathon B, Di Stefano AL, Bielle F, Laurenge A, Nesvizhskii AI, Hur EM, Yin J, Shi B, Kim Y, Moon KS, Kwon JT, Lee SH, Lee SH, Gwak HS, Lasorella A, Yoo H, Sanson M, Sa JK, Park CK, Nam DH, Iavarone A, Park JB. Integrated proteogenomic characterization of glioblastoma evolution. Cancer Cell 2024; 42:358-377.e8. [PMID: 38215747 PMCID: PMC10939876 DOI: 10.1016/j.ccell.2023.12.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 07/11/2023] [Accepted: 12/14/2023] [Indexed: 01/14/2024]
Abstract
The evolutionary trajectory of glioblastoma (GBM) is a multifaceted biological process that extends beyond genetic alterations alone. Here, we perform an integrative proteogenomic analysis of 123 longitudinal glioblastoma pairs and identify a highly proliferative cellular state at diagnosis and replacement by activation of neuronal transition and synaptogenic pathways in recurrent tumors. Proteomic and phosphoproteomic analyses reveal that the molecular transition to neuronal state at recurrence is marked by post-translational activation of the wingless-related integration site (WNT)/ planar cell polarity (PCP) signaling pathway and BRAF protein kinase. Consistently, multi-omic analysis of patient-derived xenograft (PDX) models mirror similar patterns of evolutionary trajectory. Inhibition of B-raf proto-oncogene (BRAF) kinase impairs both neuronal transition and migration capability of recurrent tumor cells, phenotypic hallmarks of post-therapy progression. Combinatorial treatment of temozolomide (TMZ) with BRAF inhibitor, vemurafenib, significantly extends the survival of PDX models. This study provides comprehensive insights into the biological mechanisms of glioblastoma evolution and treatment resistance, highlighting promising therapeutic strategies for clinical intervention.
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Affiliation(s)
- Kyung-Hee Kim
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea; Proteomics Core Facility, Research Core Center, Research Institute, National Cancer Center, Goyang, Korea
| | - Simona Migliozzi
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Harim Koo
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea; Department of Biomedical Informatics, Korea University College of Medicine, Seoul, Korea; Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Korea
| | - Jun-Hee Hong
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea
| | - Seung Min Park
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea
| | - Sooheon Kim
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea
| | - Hyung Joon Kwon
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea
| | - Seokjun Ha
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea
| | - Luciano Garofano
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Young Taek Oh
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Fulvio D'Angelo
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Chan Il Kim
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea
| | - Seongsoo Kim
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea
| | - Ji Yoon Lee
- Department of Biomedical Informatics, Korea University College of Medicine, Seoul, Korea; Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Korea
| | - Jiwon Kim
- Department of Biomedical Informatics, Korea University College of Medicine, Seoul, Korea; Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Korea
| | - Jisoo Hong
- Department of Biomedical Informatics, Korea University College of Medicine, Seoul, Korea; Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Korea
| | - Eun-Hae Jang
- Laboratory of Neuroscience, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul, Korea
| | - Bertrand Mathon
- Service de Neurochirurgie, AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France
| | - Anna-Luisa Di Stefano
- Institut de Neurologie, AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Sorbonne Université, Inserm, CNRS, UMR S 1127, Paris Brain Institute (ICM), Equipe labellisée LNCC, Paris, France; Onconeurotek, AP-HP, Hôpital Pitié-Salpêtrière, F-75013 Paris, France; Department of Neurology, Foch Hospital, Suresnes, France
| | - Franck Bielle
- Institut de Neurologie, AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Sorbonne Université, Inserm, CNRS, UMR S 1127, Paris Brain Institute (ICM), Equipe labellisée LNCC, Paris, France; Onconeurotek, AP-HP, Hôpital Pitié-Salpêtrière, F-75013 Paris, France
| | - Alice Laurenge
- Institut de Neurologie, AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Sorbonne Université, Inserm, CNRS, UMR S 1127, Paris Brain Institute (ICM), Equipe labellisée LNCC, Paris, France; Onconeurotek, AP-HP, Hôpital Pitié-Salpêtrière, F-75013 Paris, France
| | | | - Eun-Mi Hur
- Laboratory of Neuroscience, College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Seoul, Korea; BK21 Four Future Veterinary Medicine Leading Education & Research Center, College of Veterinary Medicine, Seoul National University, Seoul, Korea
| | - Jinlong Yin
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea; Henan-Macquarie University Joint Centre for Biomedical Innovation, School of Life Sciences, Henan University, Kaifeng, Henan, China
| | - Bingyang Shi
- Henan-Macquarie University Joint Centre for Biomedical Innovation, School of Life Sciences, Henan University, Kaifeng, Henan, China
| | - Youngwook Kim
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea
| | - Kyung-Sub Moon
- Department of Neurosurgery, Chonnam National University Hwasun Hospital and Medical School, Hwasun, Korea
| | - Jeong Taik Kwon
- Department of Neurosurgery, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Korea
| | - Shin Heon Lee
- Department of Neurosurgery, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Korea
| | - Seung Hoon Lee
- Department of Neurosurgery, Eulji University School of Medicine, Daejeon, Korea
| | - Ho Shin Gwak
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea
| | - Anna Lasorella
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA; Department of Biochemistry, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Heon Yoo
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea
| | - Marc Sanson
- Institut de Neurologie, AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Sorbonne Université, Inserm, CNRS, UMR S 1127, Paris Brain Institute (ICM), Equipe labellisée LNCC, Paris, France; Onconeurotek, AP-HP, Hôpital Pitié-Salpêtrière, F-75013 Paris, France.
| | - Jason K Sa
- Department of Biomedical Informatics, Korea University College of Medicine, Seoul, Korea; Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Korea.
| | - Chul-Kee Park
- Deparment of Neurosurgery, Seoul National University College of Medicine, Seoul, Korea.
| | - Do-Hyun Nam
- Department of Neurosurgery and Samsung Advanced Institute for Health Sciences and Technology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
| | - Antonio Iavarone
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA; Department of Neurological Surgery and Department of Biochemistry, University of Miami Miller School of Medicine, Miami, FL, USA.
| | - Jong Bae Park
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea; Department of Clinical Research, Research Institute and Hospital, National Cancer Center, Goyang, Korea.
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43
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Hsiao Y, Zhang H, Li GX, Deng Y, Yu F, Kahrood HV, Steele JR, Schittenhelm RB, Nesvizhskii AI. Analysis and visualization of quantitative proteomics data using FragPipe-Analyst. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.05.583643. [PMID: 38496650 PMCID: PMC10942459 DOI: 10.1101/2024.03.05.583643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
The FragPipe computational proteomics platform is gaining widespread popularity among the proteomics research community because of its fast processing speed and user-friendly graphical interface. Although FragPipe produces well-formatted output tables that are ready for analysis, there is still a need for an easy-to-use and user-friendly downstream statistical analysis and visualization tool. FragPipe-Analyst addresses this need by providing an R shiny web server to assist FragPipe users in conducting downstream analyses of the resulting quantitative proteomics data. It supports major quantification workflows including label-free quantification, tandem mass tags, and data-independent acquisition. FragPipe-Analyst offers a range of useful functionalities, such as various missing value imputation options, data quality control, unsupervised clustering, differential expression (DE) analysis using Limma, and gene ontology and pathway enrichment analysis using Enrichr. To support advanced analysis and customized visualizations, we also developed FragPipeAnalystR, an R package encompassing all FragPipe-Analyst functionalities that is extended to support site-specific analysis of post-translational modifications (PTMs). FragPipe-Analyst and FragPipeAnalystR are both open-source and freely available.
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Affiliation(s)
- Yi Hsiao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Haijian Zhang
- Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
| | - Ginny Xiaohe Li
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yamei Deng
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Hossein Valipour Kahrood
- Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
- Monash Genomics & Bioinformatics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
| | - Joel R. Steele
- Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
| | - Ralf B. Schittenhelm
- Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
| | - Alexey I. Nesvizhskii
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
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44
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He Y, Luo Y, Huang L, Zhang D, Hou H, Liang Y, Deng S, Zhang P, Liang S. Novel inhibitors targeting the PGK1 metabolic enzyme in glycolysis exhibit effective antitumor activity against kidney renal clear cell carcinoma in vitro and in vivo. Eur J Med Chem 2024; 267:116209. [PMID: 38354523 DOI: 10.1016/j.ejmech.2024.116209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 01/29/2024] [Accepted: 01/31/2024] [Indexed: 02/16/2024]
Abstract
Our previous research has revealed phosphoglycerate kinase 1 (PGK1) enhances tumorigenesis and sorafenib resistance of kidney renal clear cell carcinoma (KIRC) by regulating glycolysis, so that PGK1 is a promising drug target. Herein we performed structure-based virtual screening and series of anticancer pharmaceutical experiments in vitro and in vivo to identify novel small-molecule PGK1-targeted compounds. As results, the compounds CHR-6494 and Z57346765 were screened and confirmed to specifically bind to PGK1 and significantly reduced the metabolic enzyme activity of PGK1 in glycolysis, which inhibited KIRC cell proliferation in a dose-dependent manner. While CHR-6494 showed greater anti-KIRC efficacy and fewer side effects than Z57346765 on nude mouse xenograft model. Mechanistically, CHR-9464 impeded glycolysis by decreasing the metabolic enzyme activity of PGK1 and suppressed histone H3T3 phosphorylation to inhibit KIRC cell proliferation. Z57346765 induced expression changes of genes related to cell metabolism, DNA replication and cell cycle. Overall, we screened two novel PGK1 inhibitors, CHR-6494 and Z57346765, for the first time and discovered their potent anti-KIRC effects by suppressing PGK1 metabolic enzyme activity in glycolysis.
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Affiliation(s)
- Yu He
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
| | - Yinheng Luo
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
| | - Lan Huang
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
| | - Dan Zhang
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
| | - Huijin Hou
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
| | - Yue Liang
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
| | - Shi Deng
- Department of Urinary Surgery, West China Hospital, West China Medical School, Sichuan University, Chengdu, 610041, PR China.
| | - Peng Zhang
- Department of Urinary Surgery, West China Hospital, West China Medical School, Sichuan University, Chengdu, 610041, PR China.
| | - Shufang Liang
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
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45
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Yue L, Gong T, Jiang W, Qian L, Gong W, Sun Y, Cai X, Xu H, Liu F, Wang H, Li S, Zhu Y, Zheng Z, Wu Q, Guo T. Proteomic profiling of ovarian clear cell carcinomas identifies prognostic biomarkers for chemotherapy. Proteomics 2024; 24:e2300242. [PMID: 38171885 DOI: 10.1002/pmic.202300242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 11/17/2023] [Accepted: 11/20/2023] [Indexed: 01/05/2024]
Abstract
Clear cell ovarian carcinoma (CCOC) is a relatively rare subtype of ovarian cancer (OC) with high degree of resistance to standard chemotherapy. Little is known about the underlying molecular mechanisms, and it remains a challenge to predict its prognosis after chemotherapy. Here, we first analyzed the proteome of 35 formalin-fixed paraffin-embedded (FFPE) CCOC tissue specimens from a cohort of 32 patients with CCOC (H1 cohort) and characterized 8697 proteins using data-independent acquisition mass spectrometry (DIA-MS). We then performed proteomic analysis of 28 fresh frozen (FF) CCOC tissue specimens from an independent cohort of 24 patients with CCOC (H2 cohort), leading to the identification of 9409 proteins with DIA-MS. After bioinformatics analysis, we narrowed our focus to 15 proteins significantly correlated with the recurrence free survival (RFS) in both cohorts. These proteins are mainly involved in DNA damage response, extracellular matrix (ECM), and mitochondrial metabolism. Parallel reaction monitoring (PRM)-MS was adopted to validate the prognostic potential of the 15 proteins in the H1 cohort and an independent confirmation cohort (H3 cohort). Interferon-inducible transmembrane protein 1 (IFITM1) was observed as a robust prognostic marker for CCOC in both PRM data and immunohistochemistry (IHC) data. Taken together, this study presents a CCOC proteomic data resource and a single promising protein, IFITM1, which could potentially predict the recurrence and survival of CCOC.
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Affiliation(s)
- Liang Yue
- School of Life Sciences, Fudan University, Shanghai, China
- Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Tingting Gong
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University
| | - Wenhao Jiang
- Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Liujia Qian
- Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Wangang Gong
- Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
- Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
| | - Yaoting Sun
- Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Xue Cai
- Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Heli Xu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Fanghua Liu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - He Wang
- Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Sainan Li
- Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- National Health Commission Key Laboratory of Reproductive Health, Institute of Reproductive and Child Health, Peking University, Beijing, China
| | - Yi Zhu
- Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Zhiguo Zheng
- Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
- Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
| | - Qijun Wu
- Department of Clinical Epidemiology, Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Tiannan Guo
- Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
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46
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Hu J, Wang SG, Hou Y, Chen Z, Liu L, Li R, Li N, Zhou L, Yang Y, Wang L, Wang L, Yang X, Lei Y, Deng C, Li Y, Deng Z, Ding Y, Kuang Y, Yao Z, Xun Y, Li F, Li H, Hu J, Liu Z, Wang T, Hao Y, Jiao X, Guan W, Tao Z, Ren S, Chen K. Multi-omic profiling of clear cell renal cell carcinoma identifies metabolic reprogramming associated with disease progression. Nat Genet 2024; 56:442-457. [PMID: 38361033 PMCID: PMC10937392 DOI: 10.1038/s41588-024-01662-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 01/10/2024] [Indexed: 02/17/2024]
Abstract
Clear cell renal cell carcinoma (ccRCC) is a complex disease with remarkable immune and metabolic heterogeneity. Here we perform genomic, transcriptomic, proteomic, metabolomic and spatial transcriptomic and metabolomic analyses on 100 patients with ccRCC from the Tongji Hospital RCC (TJ-RCC) cohort. Our analysis identifies four ccRCC subtypes including De-clear cell differentiated (DCCD)-ccRCC, a subtype with distinctive metabolic features. DCCD cancer cells are characterized by fewer lipid droplets, reduced metabolic activity, enhanced nutrient uptake capability and a high proliferation rate, leading to poor prognosis. Using single-cell and spatial trajectory analysis, we demonstrate that DCCD is a common mode of ccRCC progression. Even among stage I patients, DCCD is associated with worse outcomes and higher recurrence rate, suggesting that it cannot be cured by nephrectomy alone. Our study also suggests a treatment strategy based on subtype-specific immune cell infiltration that could guide the clinical management of ccRCC.
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Affiliation(s)
- Junyi Hu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shao-Gang Wang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yaxin Hou
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhaohui Chen
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lilong Liu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ruizhi Li
- Shanghai Luming Biotech, Shanghai, China
| | - Nisha Li
- Shanghai Luming Biotech, Shanghai, China
- Shanghai OE Biotech, Shanghai, China
| | - Lijie Zhou
- Department of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yu Yang
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Liping Wang
- Department of Pathology, Baylor Scott & White Medical Center, Temple, TX, USA
| | - Liang Wang
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiong Yang
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yichen Lei
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Changqi Deng
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yang Li
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhiyao Deng
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuhong Ding
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yingchun Kuang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhipeng Yao
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yang Xun
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Fan Li
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Heng Li
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jia Hu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zheng Liu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tao Wang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Hao
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xuanmao Jiao
- Pennsylvania Cancer and Regenerative Medicine Research Center, Baruch S. Blumberg Institute, Philadelphia, PA, USA
| | - Wei Guan
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Zhen Tao
- Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Tianjin's Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Shancheng Ren
- Department of Urology, Second Affiliated Hospital of Naval Medical University, Shanghai, China.
| | - Ke Chen
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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47
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Jiang L, Qin J, Dai Y, Zhao S, Zhan Q, Cui P, Ren L, Wang X, Zhang R, Gao C, Zhou Y, Cai S, Wang G, Xie W, Tang X, Shi M, Ma F, Liu J, Wang T, Wang C, Svrcek M, Bardier-Dupas A, Emile JF, de Mestier L, Bachet JB, Nicolle R, Cros J, Laurent-Puig P, Wei M, Song B, Jing W, Guo S, Zheng K, Jiang H, Wang H, Deng X, Chen H, Tian Q, Wang S, Shi S, Jin G, Yin T, Fang H, Chen S, Shen B. Prospective observational study on biomarkers of response in pancreatic ductal adenocarcinoma. Nat Med 2024; 30:749-761. [PMID: 38287168 DOI: 10.1038/s41591-023-02790-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 12/21/2023] [Indexed: 01/31/2024]
Abstract
Adjuvant chemotherapy benefits patients with resected pancreatic ductal adenocarcinoma (PDAC), but the compromised physical state of post-operative patients can hinder compliance. Biomarkers that identify candidates for prompt adjuvant therapy are needed. In this prospective observational study, 1,171 patients with PDAC who underwent pancreatectomy were enrolled and extensively followed-up. Proteomic profiling of 191 patient samples unveiled clinically relevant functional protein modules. A proteomics-level prognostic risk model was established for PDAC, with its utility further validated using a publicly available external cohort. More importantly, through an interaction effect regression analysis leveraging both clinical and proteomic datasets, we discovered two biomarkers (NDUFB8 and CEMIP2), indicative of the overall sensitivity of patients with PDAC to adjuvant chemotherapy. The biomarkers were validated through immunohistochemistry on an internal cohort of 386 patients. Rigorous validation extended to two external multicentic cohorts-a French multicentric cohort (230 patients) and a cohort from two grade-A tertiary hospitals in China (466 patients)-enhancing the robustness and generalizability of our findings. Moreover, experimental validation through functional assays was conducted on PDAC cell lines and patient-derived organoids. In summary, our cohort-scale integration of clinical and proteomic data demonstrates the potential of proteomics-guided prognosis and biomarker-aided adjuvant chemotherapy for PDAC.
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Affiliation(s)
- Lingxi Jiang
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Research Institute of Pancreatic Diseases, Shanghai Key Laboratory of Translational Research for Pancreatic Neoplasms, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- State Key Laboratory of Systems Medicine for Cancer, Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jiejie Qin
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Research Institute of Pancreatic Diseases, Shanghai Key Laboratory of Translational Research for Pancreatic Neoplasms, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- State Key Laboratory of Systems Medicine for Cancer, Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yuting Dai
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shulin Zhao
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Research Institute of Pancreatic Diseases, Shanghai Key Laboratory of Translational Research for Pancreatic Neoplasms, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- State Key Laboratory of Systems Medicine for Cancer, Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Qian Zhan
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Research Institute of Pancreatic Diseases, Shanghai Key Laboratory of Translational Research for Pancreatic Neoplasms, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- State Key Laboratory of Systems Medicine for Cancer, Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Peng Cui
- Burning Rock Biotech, Guangzhou, China
| | - Lingjie Ren
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Research Institute of Pancreatic Diseases, Shanghai Key Laboratory of Translational Research for Pancreatic Neoplasms, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- State Key Laboratory of Systems Medicine for Cancer, Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Xuelong Wang
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Research Institute of Pancreatic Diseases, Shanghai Key Laboratory of Translational Research for Pancreatic Neoplasms, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- State Key Laboratory of Systems Medicine for Cancer, Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Ruihong Zhang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chenxu Gao
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yanting Zhou
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | | | | | | | - Xiaomei Tang
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Research Institute of Pancreatic Diseases, Shanghai Key Laboratory of Translational Research for Pancreatic Neoplasms, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- State Key Laboratory of Systems Medicine for Cancer, Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Minmin Shi
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Research Institute of Pancreatic Diseases, Shanghai Key Laboratory of Translational Research for Pancreatic Neoplasms, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- State Key Laboratory of Systems Medicine for Cancer, Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Fangfang Ma
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Research Institute of Pancreatic Diseases, Shanghai Key Laboratory of Translational Research for Pancreatic Neoplasms, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- State Key Laboratory of Systems Medicine for Cancer, Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jia Liu
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Research Institute of Pancreatic Diseases, Shanghai Key Laboratory of Translational Research for Pancreatic Neoplasms, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- State Key Laboratory of Systems Medicine for Cancer, Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Ting Wang
- Department of Pathology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chaofu Wang
- Department of Pathology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Magali Svrcek
- Department of Pathology, Saint-Antoine Hospital - Sorbonne Universités, Paris, France
| | - Armelle Bardier-Dupas
- Department of Pathology, Pitié-Salpêtrière Hospital - Sorbonne Universités, Paris, France
| | - Jean Francois Emile
- Department of Pathology, Ambroise Paré Hospital - Université Saint Quentin en Yvelines, Paris, France
| | - Louis de Mestier
- Department of Pancreatology, Université Paris Cité - FHU MOSAIC, Beaujon Hospital, Clichy, France
| | - Jean-Baptiste Bachet
- Department of Gastroenterology, Pitié-Salpêtrière Hospital - Sorbonne Universités, Paris, France
| | - Remy Nicolle
- Université Paris Cité, FHU MOSAIC, Centre de Recherche sur l'Inflammation (CRI), INSERM, U1149, CNRS, ERL 8252, Paris, France
| | - Jerome Cros
- Department of Pathology, Université Paris Cité - FHU MOSAIC, Beaujon Hospital, Clichy, France
| | - Pierre Laurent-Puig
- Department of Biochemistry, Hôpital Européen Georges Pompidou, Centre de Recherche des Cordeliers, INSERM UMRS1138, CNRS, Sorbonne Université, USPC, Université Paris Cité, Equipe labellisée Ligue Nationale contre le cancer, CNRS, Paris, France
| | - Miaoyan Wei
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Bin Song
- Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Naval Medical University (Second Military Medical University), Shanghai, China
| | - Wei Jing
- Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Naval Medical University (Second Military Medical University), Shanghai, China
| | - Shiwei Guo
- Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Naval Medical University (Second Military Medical University), Shanghai, China
| | - Kailian Zheng
- Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Naval Medical University (Second Military Medical University), Shanghai, China
| | - Hui Jiang
- Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Naval Medical University (Second Military Medical University), Shanghai, China
- Department of Pathology, Changhai Hospital, Naval Medical University (Second Military Medical University), Shanghai, China
| | - Huan Wang
- Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Naval Medical University (Second Military Medical University), Shanghai, China
| | - Xiaxing Deng
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Research Institute of Pancreatic Diseases, Shanghai Key Laboratory of Translational Research for Pancreatic Neoplasms, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- State Key Laboratory of Systems Medicine for Cancer, Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Hao Chen
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Research Institute of Pancreatic Diseases, Shanghai Key Laboratory of Translational Research for Pancreatic Neoplasms, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- State Key Laboratory of Systems Medicine for Cancer, Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Qiang Tian
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shengyue Wang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Si Shi
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
| | - Gang Jin
- Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Naval Medical University (Second Military Medical University), Shanghai, China.
| | - Tong Yin
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Hai Fang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Saijuan Chen
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Baiyong Shen
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Research Institute of Pancreatic Diseases, Shanghai Key Laboratory of Translational Research for Pancreatic Neoplasms, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- State Key Laboratory of Systems Medicine for Cancer, Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, China.
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48
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Petralia F, Ma W, Yaron TM, Caruso FP, Tignor N, Wang JM, Charytonowicz D, Johnson JL, Huntsman EM, Marino GB, Calinawan A, Evangelista JE, Selvan ME, Chowdhury S, Rykunov D, Krek A, Song X, Turhan B, Christianson KE, Lewis DA, Deng EZ, Clarke DJB, Whiteaker JR, Kennedy JJ, Zhao L, Segura RL, Batra H, Raso MG, Parra ER, Soundararajan R, Tang X, Li Y, Yi X, Satpathy S, Wang Y, Wiznerowicz M, González-Robles TJ, Iavarone A, Gosline SJC, Reva B, Robles AI, Nesvizhskii AI, Mani DR, Gillette MA, Klein RJ, Cieslik M, Zhang B, Paulovich AG, Sebra R, Gümüş ZH, Hostetter G, Fenyö D, Omenn GS, Cantley LC, Ma'ayan A, Lazar AJ, Ceccarelli M, Wang P. Pan-cancer proteogenomics characterization of tumor immunity. Cell 2024; 187:1255-1277.e27. [PMID: 38359819 PMCID: PMC10988632 DOI: 10.1016/j.cell.2024.01.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 09/29/2023] [Accepted: 01/16/2024] [Indexed: 02/17/2024]
Abstract
Despite the successes of immunotherapy in cancer treatment over recent decades, less than <10%-20% cancer cases have demonstrated durable responses from immune checkpoint blockade. To enhance the efficacy of immunotherapies, combination therapies suppressing multiple immune evasion mechanisms are increasingly contemplated. To better understand immune cell surveillance and diverse immune evasion responses in tumor tissues, we comprehensively characterized the immune landscape of more than 1,000 tumors across ten different cancers using CPTAC pan-cancer proteogenomic data. We identified seven distinct immune subtypes based on integrative learning of cell type compositions and pathway activities. We then thoroughly categorized unique genomic, epigenetic, transcriptomic, and proteomic changes associated with each subtype. Further leveraging the deep phosphoproteomic data, we studied kinase activities in different immune subtypes, which revealed potential subtype-specific therapeutic targets. Insights from this work will facilitate the development of future immunotherapy strategies and enhance precision targeting with existing agents.
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Affiliation(s)
- Francesca Petralia
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Weiping Ma
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Tomer M Yaron
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY 10021, USA; Englander Institute for Precision Medicine, Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, USA; Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032, USA
| | - Francesca Pia Caruso
- BIOGEM Institute of Molecular Biology and Genetics, 83031 Ariano Irpino, Italy; Department of Electrical Engineering and Information Technologies, University of Naples "Federico II", Naples, Italy
| | - Nicole Tignor
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Joshua M Wang
- Institute for Systems Genetics, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Daniel Charytonowicz
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jared L Johnson
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY 10021, USA; Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA; Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA
| | - Emily M Huntsman
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY 10021, USA; Englander Institute for Precision Medicine, Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, USA
| | - Giacomo B Marino
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Anna Calinawan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - John Erol Evangelista
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Myvizhi Esai Selvan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Shrabanti Chowdhury
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Dmitry Rykunov
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Azra Krek
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Xiaoyu Song
- Institute for Healthcare Delivery Science, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Berk Turhan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Karen E Christianson
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - David A Lewis
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Eden Z Deng
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Daniel J B Clarke
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jeffrey R Whiteaker
- Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Jacob J Kennedy
- Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Lei Zhao
- Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Rossana Lazcano Segura
- Departments of Pathology & Genomic Medicine, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Harsh Batra
- Department of Translational Molecular Pathology, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Maria Gabriela Raso
- Department of Translational Molecular Pathology, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Edwin Roger Parra
- Department of Translational Molecular Pathology, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Rama Soundararajan
- Department of Translational Molecular Pathology, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Ximing Tang
- Department of Translational Molecular Pathology, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Yize Li
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Xinpei Yi
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Shankha Satpathy
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Ying Wang
- Institute for Systems Genetics, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Maciej Wiznerowicz
- Department of Medical Biotechnology, Poznan University of Medical Sciences, 61-701 Poznań, Poland; International Institute for Molecular Oncology, 60-203 Poznań, Poland; Department of Oncology, Heliodor Swiecicki Clinical Hospital, 60-203 Poznań, Poland
| | - Tania J González-Robles
- Institute for Systems Genetics, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Antonio Iavarone
- Department of Neurological Surgery, Department of Biochemistry, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Sara J C Gosline
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Boris Reva
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ana I Robles
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, MD 20850, USA
| | - Alexey I Nesvizhskii
- Departments of Pathology and Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - D R Mani
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Michael A Gillette
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Robert J Klein
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Marcin Cieslik
- Departments of Pathology and Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Bing Zhang
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Amanda G Paulovich
- Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Robert Sebra
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Zeynep H Gümüş
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Lipschultz Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Galen Hostetter
- Pathology and Biorepository Core, Van Andel Research Institute, Grand Rapids, MI 49503, USA
| | - David Fenyö
- Institute for Systems Genetics, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Gilbert S Omenn
- Departments of Computational Medicine & Bioinformatics, Internal Medicine, Human Genetics, & Environmental Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Lewis C Cantley
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY 10021, USA; Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA; Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA
| | - Avi Ma'ayan
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Alexander J Lazar
- Departments of Pathology & Genomic Medicine, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Michele Ceccarelli
- Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL, USA; Department of Public Health Sciences, University of Miami, Miami, FL, USA
| | - Pei Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
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49
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Feng S, Calinawan A, Pugliese P, Wang P, Ceccarelli M, Petralia F, Gosline SJC. Decomprolute is a benchmarking platform designed for multiomics-based tumor deconvolution. CELL REPORTS METHODS 2024; 4:100708. [PMID: 38412834 PMCID: PMC10921018 DOI: 10.1016/j.crmeth.2024.100708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 10/23/2023] [Accepted: 01/18/2024] [Indexed: 02/29/2024]
Abstract
Tumor deconvolution enables the identification of diverse cell types that comprise solid tumors. To date, however, both the algorithms developed to deconvolve tumor samples, and the gold-standard datasets used to assess the algorithms are geared toward the analysis of gene expression (e.g., RNA sequencing) rather than protein levels. Despite the popularity of gene expression datasets, protein levels often provide a more accurate view of rare cell types. To facilitate the use, development, and reproducibility of multiomic deconvolution algorithms, we introduce Decomprolute, a Common Workflow Language framework that leverages containerization to compare tumor deconvolution algorithms across multiomic datasets. Decomprolute incorporates the large-scale multiomic datasets produced by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), which include matched mRNA expression and proteomic data from thousands of tumors across multiple cancer types to build a fully open-source, containerized proteogenomic tumor deconvolution benchmarking platform. http://pnnl-compbio.github.io/decomprolute.
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Affiliation(s)
- Song Feng
- Pacific Northwest National Laboratory, Seattle, WA, USA
| | - Anna Calinawan
- Icahn School of Medicine at Mount Sinai School, New York, NY, USA
| | | | - Pei Wang
- Icahn School of Medicine at Mount Sinai School, New York, NY, USA
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50
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Iacobas DA. Advanced Molecular Solutions for Cancer Therapy-The Good, the Bad, and the Ugly of the Biomarker Paradigm. Curr Issues Mol Biol 2024; 46:1694-1699. [PMID: 38534725 DOI: 10.3390/cimb46030109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 02/17/2024] [Indexed: 03/28/2024] Open
Abstract
Identifying the most effective actionable molecules whose "smart" manipulation might selectively kill/slow down/stop the proliferation of cancer cells, with few side effects on the normal cells of the tissue, was for decades the single major objective of countless investigators [...].
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Affiliation(s)
- Dumitru Andrei Iacobas
- Laboratory of Personalized Genomics, Undergraduate Medical Academy, Prairie View A&M University, Prairie View, TX 77446, USA
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