1
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Huang RH, Ge ZL, Xu G, Zeng QM, Jiang B, Xiao GC, Xia W, Wu YT, Liao YF. Prognosis and diagnosis of prostate cancer based on hypergraph regularization sparse least partial squares regression algorithm. Aging (Albany NY) 2024; 16:9599-9624. [PMID: 38829766 PMCID: PMC11210239 DOI: 10.18632/aging.205889] [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: 07/31/2023] [Accepted: 02/29/2024] [Indexed: 06/05/2024]
Abstract
BACKGROUND Prostate cancer (PCa) is a malignant tumor of the male reproductive system, and its incidence has increased significantly in recent years. This study aimed to further identify candidate biomarkers with prognostic and diagnostic significance by integrating gene expression and DNA methylation data from PCa patients through association analysis. MATERIAL AND METHODS To this end, this paper proposes a sparse partial least squares regression algorithm based on hypergraph regularization (HR-SPLS) by integrating and clustering two kinds of data. Next, module 2, with the most significant weight, was selected for further analysis according to the weight of each module related to DNA methylation and mRNAs. Based on the DNA methylation sites in module 2, this paper uses multiple machine learning methods to construct a PCa diagnosis-related model of 10-DNA methylation sites. RESULTS The results of Receiver Operating Characteristic (ROC) analysis showed that the DNA methylation-related diagnostic model we constructed could diagnose PCa patients with high accuracy. Subsequently, based on the mRNAs in module 2, we constructed a prognostic model for 7-mRNAs (MYH11, ACTG2, DDR2, CDC42EP3, MARCKSL1, LMOD1, and MYLK) using multivariate Cox regression analysis. The prognostic model could predict the disease free survival of PCa patients with moderate to high accuracy (area under the curve (AUC) =0.761). In addition, Gene Set EnrichmentAnalysis (GSEA) and immune analysis indicated that the prognosis of patients in the risk group might be related to immune cell infiltration. CONCLUSIONS Our findings may provide new methods and insights for identifying disease-related biomarkers by integrating DNA methylation and gene expression data.
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Affiliation(s)
- Ruo-Hui Huang
- Department of Urology, First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, China
| | - Zi-Lu Ge
- First Clinical Medical College, Gannan Medical University, Ganzhou, Jiangxi, China
| | - Gang Xu
- Department of Urology, First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, China
| | - Qing-Ming Zeng
- Department of Urology, First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, China
| | - Bo Jiang
- Department of Urology, First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, China
| | - Guan-Cheng Xiao
- Department of Urology, First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, China
| | - Wei Xia
- Department of Urology, First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, China
| | - Yu-Ting Wu
- Department of Urology, First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, China
| | - Yun-Feng Liao
- Department of Urology, First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, China
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Lu B, Liu Y, Yao Y, Yang T, Zhang H, Yang X, Huang R, Zhou W, Pan X, Cui X. Advances in sequencing and omics studies in prostate cancer: unveiling molecular pathogenesis and clinical applications. Front Oncol 2024; 14:1355551. [PMID: 38800374 PMCID: PMC11116611 DOI: 10.3389/fonc.2024.1355551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 04/16/2024] [Indexed: 05/29/2024] Open
Abstract
Background Prostate cancer (PCa) is one of the most threatening health problems for the elderly males. However, our understanding of the disease has been limited by the research technology for a long time. Recently, the maturity of sequencing technology and omics studies has been accelerating the studies of PCa, establishing themselves as an essential impetus in this field. Methods We assessed Web of Science (WoS) database for publications of sequencing and omics studies in PCa on July 3rd, 2023. Bibliometrix was used to conduct ulterior bibliometric analysis of countries/affiliations, authors, sources, publications, and keywords. Subsequently, purposeful large amounts of literature reading were proceeded to analyze research hotspots in this field. Results 3325 publications were included in the study. Research associated with sequencing and omics studies in PCa had shown an obvious increase recently. The USA and China were the most productive countries, and harbored close collaboration. CHINNAIYAN AM was identified as the most influential author, and CANCER RESEARCH exhibited huge impact in this field. Highly cited publications and their co-citation relationships were used to filtrate literatures for subsequent literature reading. Based on keyword analysis and large amounts of literature reading, 'the molecular pathogenesis of PCa' and 'the clinical application of sequencing and omics studies in PCa' were summarized as two research hotspots in the field. Conclusion Sequencing technology had a deep impact on the studies of PCa. Sequencing and omics studies in PCa helped researchers reveal the molecular pathogenesis, and provided new possibilities for the clinical practice of PCa.
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Affiliation(s)
- Bingnan Lu
- Department of Urology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yifan Liu
- Department of Urology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuntao Yao
- Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianyue Yang
- Department of Urology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Haoyu Zhang
- Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xinyue Yang
- Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Runzhi Huang
- Department of Burn Surgery, The First Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Wang Zhou
- Department of Urology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiuwu Pan
- Department of Urology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xingang Cui
- Department of Urology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
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3
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Zhao S, Li Y, Xu J, Shen L. APOBEC3C is a novel target for the immune treatment of lower-grade gliomas. Neurol Res 2024; 46:227-242. [PMID: 38007705 DOI: 10.1080/01616412.2023.2287340] [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: 07/27/2023] [Accepted: 11/21/2023] [Indexed: 11/28/2023]
Abstract
BACKGROUND Apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC) type 3C (A3C) has been identified as a cancer molecular biomarker in the past decade. However, the practical role of A3C in lower-grade gliomas (LGGs) in improving the clinical outcome remains unclear. This study aims to discuss the function of A3C in immunotherapy in LGGs. METHODS The RNA-Sequencing (RNA-seq) and corresponding clinical data were extracted from UCSC Xena and the results were verified in the Chinese Glioma Genome Atlas (CGGA). Weighted gene co-expression network analysis (WGCNA) was used for screening A3C-related genes. Comprehensive bioinformation analyses were performed and multiple levels of expression, survival rate, and biological functions were assessed to explore the functions of A3C. RESULTS A3C expression was significantly higher in LGGs than in normal tissues but lower than in glioblastoma (GBM), indicating its role as an independent prognosis predictor for LGGs. Twenty-eight A3C-related genes were found with WGCNA for unsupervised clustering analysis and three modification patterns with different outcomes and immune cell infiltration were identified. A3C and the A3C score were also correlated with immune cell infiltration and the expression of immune checkpoints. In addition, the A3C score was correlated with increased sensitivity to chemotherapy. Single-cell RNA (scRNA) analysis indicated that A3C most probably expresses on immune cells, such as T cells, B cells and macrophage. CONCLUSIONS A3C is an immune-related prognostic biomarker in LGGs. Developing drugs to block A3C could enhance the efficiency of immunotherapy and improve disease survival.Abbreviation: A3C: Apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC) type 3C; LGGs: lower-grade gliomas; CGGA: Chinese Glioma Genome Atlas; WGCNA: Weighted gene co-expression network analysis; scRNA: Single-cell RNA; HGG: higher-grade glioma; OS: overall survival; TME: tumor microenvironment; KM: Kaplan-Meier; PFI: progression-free interval; IDH: isocitrate dehydrogenase; ROC: receiver operating characteristic; GS: gene significance; MM: module membership; TIMER: Tumor IMmune Estimation Resource; GSVA: gene set variation analysis; ssGSEA: single-sample gene-set enrichment analysis; PCA: principal component analysis; AUC: area under ROC curve; HAVCR2: hepatitis A virus cellular receptor 2; PDCD1: programmed cell death 1; PDCD1LG2: PDCD1 ligand 2; PTPRC: protein tyrosine phosphatase receptor type C; ACC: Adrenocortical carcinoma; BLCA: Bladder Urothelial Carcinoma;BRCA: Breast invasive carcinoma; CESC: Cervical squamous cell carcinoma and endocervical adenocarcinoma; CHOLCholangiocarcinoma; COADColon adenocarcinoma; DLBC: Lymphoid Neoplasm Diffuse Large B-cell Lymphoma; ESCA: Esophageal carcinoma; GBM: Glioblastoma multiforme; HNSC: Head and Neck squamous cell carcinoma; KICH: Kidney Chromophobe; KIRC: Kidney renal clear cell carcinoma; KIRP: Kidney renal papillary cell carcinoma; LAML: Acute Myeloid Leukemia; LGG: Brain Lower Grade Glioma; LIHC: Liver hepatocellular carcinoma; LUAD: Lung adenocarcinoma; LUSC: Lung squamous cell carcinoma; MESO: Mesothelioma; OV: Ovarian serous cystadenocarcinoma; PAAD: Pancreatic adenocarcinoma; PCPG: Pheochromocytoma and Paraganglioma; PRAD: Prostate adenocarcinoma; READ: Rectum adenocarcinoma; SARC: Sarcoma; SKCM: Skin Cutaneous Melanoma; STAD: Stomach adenocarcinoma; TGCT: Testicular Germ Cell Tumors; THCA: Thyroid carcinoma; THYM: Thymoma; UCEC: Uterine Corpus Endometrial Carcinoma; UCS: Uterine Carcinosarcoma; UVM: Uveal Melanoma.
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Affiliation(s)
- Shufa Zhao
- Department of Neurosurgery, Huzhou Cent Hospital, Affiliated Cent Hospital Huzhou University, Huzhou, Zhejiang, China
| | - Yuntao Li
- Department of Neurosurgery, Huzhou Cent Hospital, Affiliated Cent Hospital Huzhou University, Huzhou, Zhejiang, China
| | - Jie Xu
- Department of Neurosurgery, Huzhou Cent Hospital, Affiliated Cent Hospital Huzhou University, Huzhou, Zhejiang, China
| | - Liang Shen
- Department of Neurosurgery, The affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou, Jiangsu, China
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Zhong Q, Sun R, Aref AT, Noor Z, Anees A, Zhu Y, Lucas N, Poulos RC, Lyu M, Zhu T, Chen GB, Wang Y, Ding X, Rutishauser D, Rupp NJ, Rueschoff JH, Poyet C, Hermanns T, Fankhauser C, Rodríguez Martínez M, Shao W, Buljan M, Neumann JF, Beyer A, Hains PG, Reddel RR, Robinson PJ, Aebersold R, Guo T, Wild PJ. Proteomic-based stratification of intermediate-risk prostate cancer patients. Life Sci Alliance 2024; 7:e202302146. [PMID: 38052461 PMCID: PMC10698198 DOI: 10.26508/lsa.202302146] [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: 05/09/2023] [Revised: 11/22/2023] [Accepted: 11/23/2023] [Indexed: 12/07/2023] Open
Abstract
Gleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in the Gleason grade group (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or overtreatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign sample runs from 278 patients. Three proteins (F5, TMEM126B, and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomize prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management.
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Affiliation(s)
- Qing Zhong
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Rui Sun
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Adel T Aref
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Zainab Noor
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Asim Anees
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Yi Zhu
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Natasha Lucas
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Rebecca C Poulos
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Mengge Lyu
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Tiansheng Zhu
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Guo-Bo Chen
- Urology & Nephrology Center, Department of Urology, Clinical Research Institute, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China
| | - Yingrui Wang
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Xuan Ding
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Dorothea Rutishauser
- Department of Pathology and Molecular Pathology, University Hospital Zürich, Zürich, Switzerland
| | - Niels J Rupp
- Department of Pathology and Molecular Pathology, University Hospital Zürich, Zürich, Switzerland
| | - Jan H Rueschoff
- Department of Pathology and Molecular Pathology, University Hospital Zürich, Zürich, Switzerland
| | - Cédric Poyet
- Department of Urology, University Hospital Zürich, Zürich, Switzerland
| | - Thomas Hermanns
- Department of Urology, University Hospital Zürich, Zürich, Switzerland
| | - Christian Fankhauser
- Department of Urology, University Hospital Zürich, Zürich, Switzerland
- Department of Urology, Cantonal Hospital Lucerne, Lucerne, Switzerland
| | | | - Wenguang Shao
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Marija Buljan
- Empa - Swiss Federal Laboratories for Materials Science and Technology, St. Gallen, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | | | | | - Peter G Hains
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Roger R Reddel
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Phillip J Robinson
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland
- Faculty of Science, University of Zürich, Zürich, Switzerland
| | - Tiannan Guo
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Peter J Wild
- Goethe University Frankfurt, Dr. Senckenberg Institute of Pathology, University Hospital Frankfurt, Frankfurt am Main, Germany
- Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany
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Zhong H, Zhu J, Liu S, Ghoneim DH, Surendran P, Liu T, Fahle S, Butterworth A, Ashad Alam M, Deng HW, Yu H, Wu C, Wu L. Identification of blood protein biomarkers associated with prostate cancer risk using genetic prediction models: analysis of over 140,000 subjects. Hum Mol Genet 2023; 32:3181-3193. [PMID: 37622920 PMCID: PMC10630250 DOI: 10.1093/hmg/ddad139] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 08/01/2023] [Accepted: 08/18/2023] [Indexed: 08/26/2023] Open
Abstract
Prostate cancer (PCa) brings huge public health burden in men. A growing number of conventional observational studies report associations of multiple circulating proteins with PCa risk. However, the existing findings may be subject to incoherent biases of conventional epidemiologic studies. To better characterize their associations, herein, we evaluated associations of genetically predicted concentrations of plasma proteins with PCa risk. We developed comprehensive genetic prediction models for protein levels in plasma. After testing 1308 proteins in 79 194 cases and 61 112 controls of European ancestry included in the consortia of BPC3, CAPS, CRUK, PEGASUS, and PRACTICAL, 24 proteins showed significant associations with PCa risk, including 16 previously reported proteins and eight novel proteins. Of them, 14 proteins showed negative associations and 10 showed positive associations with PCa risk. For 18 of the identified proteins, potential functional somatic changes of encoding genes were detected in PCa patients in The Cancer Genome Atlas (TCGA). Genes encoding these proteins were significantly involved in cancer-related pathways. We further identified drugs targeting the identified proteins, which may serve as candidates for drug repurposing for treating PCa. In conclusion, this study identifies novel protein biomarker candidates for PCa risk, which may provide new perspectives on the etiology of PCa and improve its therapeutic strategies.
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Affiliation(s)
- Hua Zhong
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, 701 Ilalo Street, Honolulu, HI 96813, United States
| | - Jingjing Zhu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, 701 Ilalo Street, Honolulu, HI 96813, United States
| | - Shuai Liu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, 701 Ilalo Street, Honolulu, HI 96813, United States
| | - Dalia H Ghoneim
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, 701 Ilalo Street, Honolulu, HI 96813, United States
| | - Praveen Surendran
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Papworth Road, Cambridge Biomedical Campus, Cambridge, CB2 0BB, United Kingdom
| | - Tao Liu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Sarah Fahle
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Papworth Road, Cambridge Biomedical Campus, Cambridge, CB2 0BB, United Kingdom
| | - Adam Butterworth
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Papworth Road, Cambridge Biomedical Campus, Cambridge, CB2 0BB, United Kingdom
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Papworth Road, Cambridge Biomedical Campus, Cambridge, CB2 0BB, United Kingdom
| | - Md Ashad Alam
- Tulane Center for Biomedical Informatics and Genomics, Division of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, 1440 Canal Street, New Orleans, LA 70112, United States
- Center for Outcomes Research, Ochsner Clinic Foundation, New Orleans, LA 70121, United States
| | - Hong-Wen Deng
- Tulane Center for Biomedical Informatics and Genomics, Division of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, 1440 Canal Street, New Orleans, LA 70112, United States
| | - Herbert Yu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, 701 Ilalo Street, Honolulu, HI 96813, United States
| | - Chong Wu
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX 77030, United States
| | - Lang Wu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, 701 Ilalo Street, Honolulu, HI 96813, United States
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Pan J, Zhang X, Xu J, Chang Z, Xin Z, Wang G. Landscape of Exhausted T Cells in Tuberculosis Revealed by Single-Cell Sequencing. Microbiol Spectr 2023; 11:e0283922. [PMID: 36916943 PMCID: PMC10100881 DOI: 10.1128/spectrum.02839-22] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 02/13/2023] [Indexed: 03/16/2023] Open
Abstract
Tuberculosis, a contagious bacterial infection caused by Mycobacterium tuberculosis, is a substantial global health problem, impacting millions of lives annually. Exhausted T-cell signatures are critical for predicting clinical responses to tuberculosis infection. To obtain a panoramic transcriptional profile of T cells, we performed single-cell RNA-sequencing analysis of CD4+ T and CD8+ T cells isolated from peripheral blood mononuclear cells of healthy individuals and patients with tuberculosis. We identified seven subsets in CD8+ T cells and eight subsets in CD4+ T cells and elucidated the transcriptomic landscape changes and characteristics of each subset. We further investigated the cell-to-cell relationship of each subgroup of the two cell types. Different signature genes and pathways of exhausted CD4+ and CD8+ T cells were examined. We identified 12 genes with potential associations of T-cell exhaustion after tuberculosis infection. We also identified five genes as potential exhaustion marker genes. The CD8-EX3 subcluster in CD8+ T-exhausted cells was identified as an exhaustion-specific subcluster. The identified gene module further clarified the key factors influencing CD8+ T cell exhaustion. These data provide new insights into T-cell signatures in tuberculosis-exhausted populations. IMPORTANCE Identifying the changes in immune cells in response to infection can provide a better understanding of the effects of Mycobacterium tuberculosis on the host immune system. We performed single-cell RNA-sequencing analysis of CD4+ T and CD8+ T cells isolated from peripheral blood mononuclear cells of healthy individuals and patients with tuberculosis to reveal the cellular characteristics. Different signature genes and pathways of exhausted CD4+ and CD8+ T cells were examined. These will facilitate a more comprehensive understanding of the onset and underlying mechanism of T-cell exhaustion during active Mtb infection.
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Affiliation(s)
- Jiahui Pan
- Key Laboratory of Zoonosis Research, Ministry of Education, College of Basic Medical Science, Jilin University, Changchun, China
| | - Xinyue Zhang
- Key Laboratory of Zoonosis Research, Ministry of Education, College of Basic Medical Science, Jilin University, Changchun, China
| | - Jianting Xu
- The First Hospital of Jilin University, Changchun, China
| | - Zecheng Chang
- Key Laboratory of Zoonosis Research, Ministry of Education, College of Basic Medical Science, Jilin University, Changchun, China
| | - Zhuoyuan Xin
- Key Laboratory of Zoonosis Research, Ministry of Education, College of Basic Medical Science, Jilin University, Changchun, China
| | - Guoqing Wang
- Key Laboratory of Zoonosis Research, Ministry of Education, College of Basic Medical Science, Jilin University, Changchun, China
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7
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Xiao S, Yan Z, Zeng F, Lu Y, Qiu J, Zhu X. Identification of a pyroptosis-related prognosis gene signature and its relationship with an immune microenvironment in gliomas. Medicine (Baltimore) 2022; 101:e29391. [PMID: 35839032 PMCID: PMC11132325 DOI: 10.1097/md.0000000000029391] [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: 10/19/2021] [Accepted: 04/12/2022] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Glioma is the most common type of primary brain cancer, and the prognosis of most patients with glioma is poor. Pyroptosis is a newly discovered inflammatory programmed cell death. However, the expression of pyroptosis-related genes (PRGs) in glioma and its correlation with prognosis are unclear. METHODS 27 pyroptosis genes differentially expressed between glioma and adjacent normal tissues were identified. All glioma cases could be stratified into 2 subtypes based on these differentially expressed PRGs. The prognostic value of each PRG was evaluated to construct a prognostic model. RESULTS A novel 16-gene signature was constructed by using the least absolute shrinkage and selection operator Cox regression method. Then, patients with glioma were divided into low- and high-risk groups in the TCGA cohort. The survival rate of patients in the low-risk group was significantly higher than that in the high-risk group (P = .001). Patients with glioma from the Gene Expression Omnibus (GEO) cohort were stratified into 2 risk groups by using the median risk score. The overall survival (OS) of the low-risk group was longer than that of the high-risk group (P = .001). The risk score was considered an independent prognostic factor of the OS of patients with glioma. Gene ontology and Kyoto Encylopedia of Genes and Genomes analysis showed that the differentially expressed PRGs were mainly related to neutrophil activation involved in immune responses, focal adhesion, cell cycle, and p53 signaling pathway. CONCLUSION PRGs could predict the prognosis of glioma and play significant roles in a tumor immune microenvironment.
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Affiliation(s)
- Shengying Xiao
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi 530021, P.R. China
- Department of Oncology, Hunan Provincial People’s Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, Hunan 410016, P.R. China
| | - Zhiguang Yan
- Department of Orthopedics, Ningxiang Hospital Affiliated to Hunan University of Chinese Medicine, Ningxiang, Hunan, 410600, P.R. China
| | - Furen Zeng
- Department of Oncology, Hunan Provincial People’s Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, Hunan 410016, P.R. China
| | - Yichen Lu
- Department of Oncology, Hunan Provincial People’s Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, Hunan 410016, P.R. China
| | - Jun Qiu
- Department of Oncology, Hunan Provincial People’s Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, Hunan 410016, P.R. China
| | - Xiaodong Zhu
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi 530021, P.R. China
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Tan Y, Chen Q, Pan S, An W, Xu H, Xing Y, Zhang J. LMOD1, an oncogene associated with Lauren classification, regulates the metastasis of gastric cancer cells through the FAK-AKT/mTOR pathway. BMC Cancer 2022; 22:474. [PMID: 35488236 PMCID: PMC9055720 DOI: 10.1186/s12885-022-09541-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 04/11/2022] [Indexed: 11/10/2022] Open
Abstract
Background The Lauren classification of gastric tumors strongly correlates with prognosis. The purpose of this study was to explore the specific molecular mechanism of Lauren classification of gastric cancer and provide a possible theoretical basis for the treatment of gastric cancer. Methods We standardized the gene expression data of five Gene Expression Omnibus gastric cancer databases and constructed a Weighted Co-expression Network Analysis (WGCNA) model based on clinicopathological information. The overall survival (OS) and disease-free survival (DFS) curves were extracted from the Cancer Genome Atlas (TCGA) and GSE62254 databases. Western blotting was used to measure protein expression in cells and tissues. Scratch and transwell experiments were used to test the migration ability of tumor cells. Immunohistochemistry was used to measure tissue protein expression in clinical tissue samples to correlate to survival data. Results The WGCNA model demonstrated that blue cyan was highly correlated with the Lauren classification of the tumor (r = 0.24, P = 7 × 1016). A protein-protein interaction network was used to visualize the genes in the blue cyan module. The OS and PFS TCGA analysis revealed that LMOD1 was a gene of interest. The proportion of diffuse gastric cancer patients with high expression of LMOD1 was significantly higher than that of intestinal type patients. LMOD1 promoted the migration of gastric cancer cells by regulating the FAK-Akt/mTOR pathway in vitro. Additionally, a Gene Set Enrichment Analysis using the TCGA and GSE62254 databases, and western blot data, showed that LMOD1 could promote an epithelial-mesenchymal transition (EMT), thus potentially affecting the occurrence of peritoneal metastasis of gastric cancer. Immunohistochemistry showed that LMOD1 was highly expressed in cancer tissues, and the prognosis of patients with high LMOD1 expression was poor. Conclusion LMOD1 is an oncogene associated with diffuse gastric cancer and can affect the occurrence and development of EMT by regulating the FAK-Akt/mTOR pathway. LMOD1 can therefore promote peritoneal metastasis of gastric cancer cells and can be used as a novel therapeutic target for gastric cancer. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-022-09541-0.
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Affiliation(s)
- Yuen Tan
- Department of Gastric Surgery, Liaoning Cancer Hospital and Institute, Cancer Hospital of China Medical University, No 44 of Xiaoheyan Road, Dadong District, Shenyang, 110042, China.,Department of Surgical Oncology, First Affiliated Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, China
| | - Qingchuan Chen
- Department of Surgical Oncology, First Affiliated Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, China
| | - Siwei Pan
- Department of Surgical Oncology, First Affiliated Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, China
| | - Wen An
- Department of Surgical Oncology, First Affiliated Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, China
| | - Huimian Xu
- Department of Surgical Oncology, First Affiliated Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, China.
| | - Yao Xing
- Department of Cell Biology, Key Laboratory of Cell Biology of Ministry of Public Health, and Key Laboratory of Medical Cell Biology of Ministry of Education, China Medical University, No. 77, Puhe Road, Shenyang North New Area, Shenyang, 110122, Liaoning, China.
| | - Jianjun Zhang
- Department of Gastric Surgery, Liaoning Cancer Hospital and Institute, Cancer Hospital of China Medical University, No 44 of Xiaoheyan Road, Dadong District, Shenyang, 110042, China.
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9
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Bernardino RMM, Leão R, Henrique R, Pinheiro LC, Kumar P, Suravajhala P, Beck HC, Carvalho AS, Matthiesen R. Extracellular Vesicle Proteome in Prostate Cancer: A Comparative Analysis of Mass Spectrometry Studies. Int J Mol Sci 2021; 22:ijms222413605. [PMID: 34948404 PMCID: PMC8707426 DOI: 10.3390/ijms222413605] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 12/15/2021] [Accepted: 12/15/2021] [Indexed: 12/24/2022] Open
Abstract
Molecular diagnostics based on discovery research holds the promise of improving screening methods for prostate cancer (PCa). Furthermore, the congregated information prompts the question whether the urinary extracellular vesicles (uEV) proteome has been thoroughly explored, especially at the proteome level. In fact, most extracellular vesicles (EV) based biomarker studies have mainly targeted plasma or serum. Therefore, in this study, we aim to inquire about possible strategies for urinary biomarker discovery particularly focused on the proteome of urine EVs. Proteomics data deposited in the PRIDE archive were reanalyzed to target identifications of potential PCa markers. Network analysis of the markers proposed by different prostate cancer studies revealed moderate overlap. The recent throughput improvements in mass spectrometry together with the network analysis performed in this study, suggest that a larger standardized cohort may provide potential biomarkers that are able to fully characterize the heterogeneity of PCa. According to our analysis PCa studies based on urinary EV proteome presents higher protein coverage compared to plasma, plasma EV, and voided urine proteome. This together with a direct interaction of the prostate gland and urethra makes uEVs an attractive option for protein biomarker studies. In addition, urinary proteome based PCa studies must also evaluate samples from bladder and renal cancers to assess specificity for PCa.
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Affiliation(s)
- Rui Miguel Marques Bernardino
- Computational and Experimental Biology Group, Chronic Diseases Research Centre (CEDOC), NOVA Medical School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, 1169-056 Lisboa, Portugal;
- Urology Department, Centro Hospitalar e Universitário de Lisboa Central, 1169-050 Lisbon, Portugal;
- Correspondence: (R.M.M.B.); (R.M.); Tel.: +351-939218696 (R.M.M.B. & R.M.)
| | - Ricardo Leão
- Faculty of Medicine, University of Coimbra, 3000-370 Coimbra, Portugal;
| | - Rui Henrique
- Pathology Department, Instituto Português de Oncologia, 4200-072 Porto, Portugal;
| | - Luis Campos Pinheiro
- Urology Department, Centro Hospitalar e Universitário de Lisboa Central, 1169-050 Lisbon, Portugal;
| | - Prashant Kumar
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India;
- Somaiya Institute of Research and Consultancy (SIRAC), Somaiya Vidyavihar University (SVU), Vidyavihar, Mumbai 400077, India
| | - Prashanth Suravajhala
- Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham, Amritapuri Campus, Clappana P.O., Kollam 690525, India;
| | - Hans Christian Beck
- Centre for Clinical Proteomics, Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, 5000 Odense, Denmark;
| | - Ana Sofia Carvalho
- Computational and Experimental Biology Group, Chronic Diseases Research Centre (CEDOC), NOVA Medical School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, 1169-056 Lisboa, Portugal;
| | - Rune Matthiesen
- Computational and Experimental Biology Group, Chronic Diseases Research Centre (CEDOC), NOVA Medical School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, 1169-056 Lisboa, Portugal;
- Correspondence: (R.M.M.B.); (R.M.); Tel.: +351-939218696 (R.M.M.B. & R.M.)
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10
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Yan Y, Yeon SY, Qian C, You S, Yang W. On the Road to Accurate Protein Biomarkers in Prostate Cancer Diagnosis and Prognosis: Current Status and Future Advances. Int J Mol Sci 2021; 22:13537. [PMID: 34948334 PMCID: PMC8703658 DOI: 10.3390/ijms222413537] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 12/14/2021] [Indexed: 12/11/2022] Open
Abstract
Prostate cancer (PC) is a leading cause of morbidity and mortality among men worldwide. Molecular biomarkers work in conjunction with existing clinicopathologic tools to help physicians decide who to biopsy, re-biopsy, treat, or re-treat. The past decade has witnessed the commercialization of multiple PC protein biomarkers with improved performance, remarkable progress in proteomic technologies for global discovery and targeted validation of novel protein biomarkers from clinical specimens, and the emergence of novel, promising PC protein biomarkers. In this review, we summarize these advances and discuss the challenges and potential solutions for identifying and validating clinically useful protein biomarkers in PC diagnosis and prognosis. The identification of multi-protein biomarkers with high sensitivity and specificity, as well as their integration with clinicopathologic parameters, imaging, and other molecular biomarkers, bodes well for optimal personalized management of PC patients.
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Affiliation(s)
- Yiwu Yan
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; (Y.Y.); (S.Y.Y.); (C.Q.); (S.Y.)
| | - Su Yeon Yeon
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; (Y.Y.); (S.Y.Y.); (C.Q.); (S.Y.)
| | - Chen Qian
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; (Y.Y.); (S.Y.Y.); (C.Q.); (S.Y.)
| | - Sungyong You
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; (Y.Y.); (S.Y.Y.); (C.Q.); (S.Y.)
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Wei Yang
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; (Y.Y.); (S.Y.Y.); (C.Q.); (S.Y.)
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
- Department of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
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11
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Kischkel B, Boniche-Alfaro C, Menezes IDG, Rossi SA, Angeli CB, de Almeida SR, Palmisano G, Lopes-Bezerra L, Nosanchuk JD, Taborda CP. Immunoproteomic and Immunopeptidomic Analyses of Histoplasma capsulatum Reveal Promiscuous and Conserved Epitopes Among Fungi With Vaccine Potential. Front Immunol 2021; 12:764501. [PMID: 34880863 PMCID: PMC8645968 DOI: 10.3389/fimmu.2021.764501] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 10/29/2021] [Indexed: 12/27/2022] Open
Abstract
As there are more than 6 million human deaths due to mycoses each year, there is an urgent need to develop fungal vaccines. Moreover, given the similarities among pathogenic fungi, it may be possible to create a multi-fungi vaccine. In this study, we combined immunoproteomic and immunopeptidomic methods, for which we have adapted a technique based on co-immunoprecipitation (Co-IP) that made it possible to map Histoplasma capsulatum epitopes for the first time in a natural context using murine dendritic cells (DCs) and macrophages (Mφ). Although polysaccharide epitopes exist, this research focused on mapping protein epitopes as these are more immunogenic. We used different algorithms to screen proteins and peptides identified by two-dimensional electrophoresis (2-D) and Co-IP. Seventeen proteins were revealed by 2-D gels, and 45 and 24 peptides from distinct proteins were presented by DCs and Mφ, respectively. We then determined which epitopes were restricted to MHC-I and II from humans and mice and showed high promiscuity, but lacked identity with human proteins. The 4 most promising peptides were synthesized, and the peptides with and without incorporation into glucan particles induced CD4+ and CD8+ T cell proliferation and produced a Th1 and Th17 response marked by the secretion of high levels of IFN-γ, IL-17 and IL-2. These epitopes were from heat shock protein 60, enolase, and the ATP-dependent molecular chaperone HSC82, and they each have a high degree of identity with proteins expressed by other medically important pathogenic fungi. Thus, the epitopes described in this study have the potential for use in the development of vaccines that could result in cross-protection among fungal species.
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Affiliation(s)
- Brenda Kischkel
- Department of Microbiology, Biomedical Sciences Institute, University of São Paulo, São Paulo, Brazil
| | - Camila Boniche-Alfaro
- Department of Microbiology, Biomedical Sciences Institute, University of São Paulo, São Paulo, Brazil
| | - Isabela de Godoy Menezes
- Department of Clinical and Toxicological Analysis, Faculty of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil
| | - Suelen Andreia Rossi
- Department of Microbiology, Biomedical Sciences Institute, University of São Paulo, São Paulo, Brazil.,Department of Dermatology, Tropical Medicine Institute, Faculty of Medicine, University of São Paulo, São Paulo, Brazil
| | - Claudia Blanes Angeli
- Department of Parasitology, Biomedical Sciences Institute, University of São Paulo, São Paulo, Brazil
| | - Sandro Rogério de Almeida
- Department of Clinical and Toxicological Analysis, Faculty of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil
| | - Giuseppe Palmisano
- Department of Parasitology, Biomedical Sciences Institute, University of São Paulo, São Paulo, Brazil
| | - Leila Lopes-Bezerra
- Department of Microbiology, Biomedical Sciences Institute, University of São Paulo, São Paulo, Brazil
| | - Joshua D Nosanchuk
- Division of Infectious Diseases, Department of Medicine, Albert Einstein College of Medicine, New York, NY, United States.,Department of Microbiology and Immunology, Albert Einstein College of Medicine, New York, NY, United States
| | - Carlos Pelleschi Taborda
- Department of Microbiology, Biomedical Sciences Institute, University of São Paulo, São Paulo, Brazil.,Department of Dermatology, Tropical Medicine Institute, Faculty of Medicine, University of São Paulo, São Paulo, Brazil
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12
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Luo L, Zhang LL, Tao W, Xia TL, Li LY. Prediction of potential prognostic biomarkers in metastatic prostate cancer based on a circular RNA-mediated competing endogenous RNA regulatory network. PLoS One 2021; 16:e0260983. [PMID: 34860853 PMCID: PMC8641895 DOI: 10.1371/journal.pone.0260983] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 11/19/2021] [Indexed: 11/18/2022] Open
Abstract
Recently, studies on competing endogenous RNA (ceRNA) networks have become prevalent, and circular RNAs (circRNAs) have crucial implications for the development and progression of carcinoma. However, studies relevant to metastatic prostate cancer (mPCa) are scant. This study aims to discover potential ceRNAs that may be related to the prognosis of mPCa. RNA-Seq data were obtained from the MiOncoCirc database and Gene Expression Omnibus (GEO). Differential expression patterns of RNAs were examined using R packages. Circular RNA Interactome, miRTarBase, miRDB and TargetScan were applied to predict the corresponding relation between circRNAs, miRNAs and mRNAs. The Gene Ontology (GO) annotations were performed to present related GO terms, and Gene Set Enrichment Analysis (GSEA) tools were applied for pathway annotations. Moreover, survival analysis was conducted for the hub genes. We found 820 circRNAs, 81 miRNAs and 179 mRNAs that were distinguishingly expressed between primary prostate cancer (PCa) and mPCa samples. A ceRNA network including 45 circRNAs, 24 miRNAs and 56 mRNAs was constructed. In addition, the protein–protein interaction (PPI) network was built, and 10 hub genes were selected by using the CytoHubba application. Among the 10 hub genes, survival analysis showed that ITGA1, LMOD1, MYH11, MYLK, SORBS1 and TGFBR3 were significantly connected with disease-free survival (DFS). The circRNA-mediated ceRNA network provides potential prognostic biomarkers for metastatic prostate cancer.
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Affiliation(s)
- Liang Luo
- Department of Urology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Department of Urology, Foshan First Municipal People’s Hospital, Foshan, China
| | - Lei-Lei Zhang
- Department of Urology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Department of Urology, Foshan First Municipal People’s Hospital, Foshan, China
| | - Wen Tao
- Department of Urology, Foshan First Municipal People’s Hospital, Foshan, China
| | - Tao-Lin Xia
- Department of Urology, Foshan First Municipal People’s Hospital, Foshan, China
| | - Liao-Yuan Li
- Department of Urology, Foshan First Municipal People’s Hospital, Foshan, China
- * E-mail:
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13
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Proteomic Landscape of Prostate Cancer: The View Provided by Quantitative Proteomics, Integrative Analyses, and Protein Interactomes. Cancers (Basel) 2021; 13:cancers13194829. [PMID: 34638309 PMCID: PMC8507874 DOI: 10.3390/cancers13194829] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 09/23/2021] [Accepted: 09/24/2021] [Indexed: 12/12/2022] Open
Abstract
Prostate cancer is the second most frequent cancer of men worldwide. While the genetic landscapes and heterogeneity of prostate cancer are relatively well-known already, methodological developments now allow for studying basic and dynamic proteomes on a large scale and in a quantitative fashion. This aids in revealing the functional output of cancer genomes. It has become evident that not all aberrations at the genetic and transcriptional level are translated to the proteome. In addition, the proteomic level contains heterogeneity, which increases as the cancer progresses from primary prostate cancer (PCa) to metastatic and castration-resistant prostate cancer (CRPC). While multiple aspects of prostate adenocarcinoma proteomes have been studied, less is known about proteomes of neuroendocrine prostate cancer (NEPC). In this review, we summarize recent developments in prostate cancer proteomics, concentrating on the proteomic landscapes of clinical prostate cancer, cell line and mouse model proteomes interrogating prostate cancer-relevant signaling and alterations, and key prostate cancer regulator interactomes, such as those of the androgen receptor (AR). Compared to genomic and transcriptomic analyses, the view provided by proteomics brings forward changes in prostate cancer metabolism, post-transcriptional RNA regulation, and post-translational protein regulatory pathways, requiring the full attention of studies in the future.
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14
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Brady L, Kriner M, Coleman I, Morrissey C, Roudier M, True LD, Gulati R, Plymate SR, Zhou Z, Birditt B, Meredith R, Geiss G, Hoang M, Beechem J, Nelson PS. Inter- and intra-tumor heterogeneity of metastatic prostate cancer determined by digital spatial gene expression profiling. Nat Commun 2021; 12:1426. [PMID: 33658518 PMCID: PMC7930198 DOI: 10.1038/s41467-021-21615-4] [Citation(s) in RCA: 133] [Impact Index Per Article: 44.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 02/04/2021] [Indexed: 02/08/2023] Open
Abstract
Metastatic prostate cancer (mPC) comprises a spectrum of diverse phenotypes. However, the extent of inter- and intra-tumor heterogeneity is not established. Here we use digital spatial profiling (DSP) technology to quantitate transcript and protein abundance in spatially-distinct regions of mPCs. By assessing multiple discrete areas across multiple metastases, we find a high level of intra-patient homogeneity with respect to tumor phenotype. However, there are notable exceptions including tumors comprised of regions with high and low androgen receptor (AR) and neuroendocrine activity. While the vast majority of metastases examined are devoid of significant inflammatory infiltrates and lack PD1, PD-L1 and CTLA4, the B7-H3/CD276 immune checkpoint protein is highly expressed, particularly in mPCs with high AR activity. Our results demonstrate the utility of DSP for accurately classifying tumor phenotype, assessing tumor heterogeneity, and identifying aspects of tumor biology involving the immunological composition of metastases. The inter- and intra-tumor heterogeneity of metastatic prostate cancer (mPC) is underexplored. Here the authors use Digital Spatial Profiling to study gene and protein expression heterogeneity in 27 mPC patients, finding variation in associated pathways and potential immunotherapy targets.
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Affiliation(s)
- Lauren Brady
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | | | - Ilsa Coleman
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | | | | | | | - Roman Gulati
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Stephen R Plymate
- University of Washington, Seattle, WA, USA.,VAPSHCS-GRECC, Seattle, WA, USA
| | - Zoey Zhou
- NanoString Technologies, Inc., Seattle, WA, USA
| | | | | | - Gary Geiss
- NanoString Technologies, Inc., Seattle, WA, USA
| | | | | | - Peter S Nelson
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA. .,University of Washington, Seattle, WA, USA.
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15
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Kawahara R, Recuero S, Srougi M, Leite KRM, Thaysen-Andersen M, Palmisano G. The Complexity and Dynamics of the Tissue Glycoproteome Associated With Prostate Cancer Progression. Mol Cell Proteomics 2021; 20:100026. [PMID: 33127837 PMCID: PMC8010466 DOI: 10.1074/mcp.ra120.002320] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 10/19/2020] [Accepted: 10/30/2020] [Indexed: 12/30/2022] Open
Abstract
The complexity and dynamics of the immensely heterogeneous glycoproteome of the prostate cancer (PCa) tumor microenvironment remain incompletely mapped, a knowledge gap that impedes our molecular-level understanding of the disease. To this end, we have used sensitive glycomics and glycoproteomics to map the protein-, cell-, and tumor grade-specific N- and O-glycosylation in surgically removed PCa tissues spanning five histological grades (n = 10/grade) and tissues from patients with benign prostatic hyperplasia (n = 5). Quantitative glycomics revealed PCa grade-specific alterations of the oligomannosidic-, paucimannosidic-, and branched sialylated complex-type N-glycans, and dynamic remodeling of the sialylated core 1- and core 2-type O-glycome. Deep quantitative glycoproteomics identified ∼7400 unique N-glycopeptides from 500 N-glycoproteins and ∼500 unique O-glycopeptides from nearly 200 O-glycoproteins. With reference to a recent Tissue and Blood Atlas, our data indicate that paucimannosidic glycans of the PCa tissues arise mainly from immune cell-derived glycoproteins. Furthermore, the grade-specific PCa glycosylation arises primarily from dynamics in the cellular makeup of the PCa tumor microenvironment across grades involving increased oligomannosylation of prostate-derived glycoproteins and decreased bisecting GlcNAcylation of N-glycans carried by the extracellular matrix proteins. Furthermore, elevated expression of several oligosaccharyltransferase subunits and enhanced N-glycoprotein site occupancy were observed associated with PCa progression. Finally, correlations between the protein-specific glycosylation and PCa progression were observed including increased site-specific core 2-type O-glycosylation of collagen VI. In conclusion, integrated glycomics and glycoproteomics have enabled new insight into the complexity and dynamics of the tissue glycoproteome associated with PCa progression generating an important resource to explore the underpinning disease mechanisms.
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Affiliation(s)
- Rebeca Kawahara
- Departamento de Parasitologia, Instituto de Ciências Biomédicas, Universidade de São Paulo, USP, São Paulo, Brazil; Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia; Biomolecular Discovery Research Centre, Macquarie University, Sydney, NSW, Australia
| | - Saulo Recuero
- Laboratório de Investigação Médica da Disciplina de Urologia da Faculdade de Medicina da USP, São Paulo, Brazil
| | - Miguel Srougi
- Laboratório de Investigação Médica da Disciplina de Urologia da Faculdade de Medicina da USP, São Paulo, Brazil
| | - Katia R M Leite
- Laboratório de Investigação Médica da Disciplina de Urologia da Faculdade de Medicina da USP, São Paulo, Brazil
| | - Morten Thaysen-Andersen
- Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia; Biomolecular Discovery Research Centre, Macquarie University, Sydney, NSW, Australia.
| | - Giuseppe Palmisano
- Departamento de Parasitologia, Instituto de Ciências Biomédicas, Universidade de São Paulo, USP, São Paulo, Brazil.
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16
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Tonry C, Finn S, Armstrong J, Pennington SR. Clinical proteomics for prostate cancer: understanding prostate cancer pathology and protein biomarkers for improved disease management. Clin Proteomics 2020; 17:41. [PMID: 33292167 PMCID: PMC7678104 DOI: 10.1186/s12014-020-09305-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Accepted: 11/11/2020] [Indexed: 12/12/2022] Open
Abstract
Following the introduction of routine Prostate Specific Antigen (PSA) screening in the early 1990's, Prostate Cancer (PCa) is often detected at an early stage. There are also a growing number of treatment options available and so the associated mortality rate is generally low. However, PCa is an extremely complex and heterogenous disease and many patients suffer disease recurrence following initial therapy. Disease recurrence commonly results in metastasis and metastatic PCa has an average survival rate of just 3-5 years. A significant problem in the clinical management of PCa is being able to differentiate between patients who will respond to standard therapies and those who may benefit from more aggressive intervention at an earlier stage. It is also acknowledged that for many men the disease is not life threatenting. Hence, there is a growing desire to identify patients who can be spared the significant side effects associated with PCa treatment until such time (if ever) their disease progresses to the point where treatment is required. To these important clinical needs, current biomarkers and clinical methods for patient stratification and personlised treatment are insufficient. This review provides a comprehensive overview of the complexities of PCa pathology and disease management. In this context it is possible to review current biomarkers and proteomic technologies that will support development of biomarker-driven decision tools to meet current important clinical needs. With such an in-depth understanding of disease pathology, the development of novel clinical biomarkers can proceed in an efficient and effective manner, such that they have a better chance of improving patient outcomes.
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Affiliation(s)
- Claire Tonry
- UCD Conway Institute, University College Dublin, Dublin, Ireland
| | - Stephen Finn
- Department of Histopathology and Morbid Anatomy, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin 8, Ireland
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17
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Zhang M, Wang X, Chen X, Guo F, Hong J. Prognostic Value of a Stemness Index-Associated Signature in Primary Lower-Grade Glioma. Front Genet 2020; 11:441. [PMID: 32431729 PMCID: PMC7216823 DOI: 10.3389/fgene.2020.00441] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Accepted: 04/09/2020] [Indexed: 12/20/2022] Open
Abstract
Objective As a prevalent and infiltrative cancer type of the central nervous system, the prognosis of lower-grade glioma (LGG) in adults is highly heterogeneous. Recent evidence has demonstrated the prognostic value of the mRNA expression-based stemness index (mRNAsi) in LGG. Our aim was to develop a stemness index-based signature (SI-signature) for risk stratification and survival prediction. Methods Differentially expressed genes (DEGs) between LGG in the Cancer Genome Atlas (TCGA) and normal brain tissue samples from the Genotype-Tissue Expression (GTEx) project were screened out, and the weighted gene correlation network analysis (WGCNA) was employed to identify the mRNAsi-related gene sets. Meanwhile, the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed for the functional annotation of the key genes. ESTIMATE was used to calculate tumor purity for acquiring the correct mRNAsi. Differences in overall survival (OS) between the high and low mRNAsi (corrected mRNAsi) groups were compared using the Kaplan Meier analysis. By combining the Lasso regression with univariate and multivariate Cox regression, the SI-signature was constructed and validated using the Chinese Glioma Genome Atlas (CGGA). Results There was a significant difference in OS between the high and low mRNAsi groups, which was also observed in the two corrected mRNAsi groups. Based on threshold limits, 86 DEGs were most significantly associated with mRNAsi via WGCNA. Seven genes (ADAP2, ALOX5AP, APOBEC3C, FCGRT, GNG5, LRRC25, and SP100) were selected to establish a risk signature for primary LGG. The ROC curves showed a fair performance in survival prediction in both the TCGA and the CGGA validation cohorts. Univariate and multivariate Cox regression revealed that the risk group was an independent prognostic factor in primary LGG. The nomogram was developed based on clinical parameters integrated with the risk signature, and its accuracy for predicting 3- and 5-years survival was assessed by the concordance index, the area under the curve of the time-dependent receiver operating characteristics curve, and calibration curves. Conclusion The SI-signature with seven genes could serve as an independent predictor, and suggests the importance of stemness features in risk stratification and survival prediction in primary LGG.
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Affiliation(s)
- Mingwei Zhang
- Department of Radiation Oncology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.,Institute of Immunotherapy, Fujian Medical University, Fuzhou, China.,Key Laboratory of Radiation Biology (Fujian Medical University), Fujian Province University, Fuzhou, China.,Fujian Key Laboratory of Individualized Active Immunotherapy, Fuzhou, China.,Fujian Medical University Union Hospital, Fuzhou, China
| | - Xuezhen Wang
- Department of Radiation Oncology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Xiaoping Chen
- Department of Statistics, College of Mathematics and Informatics & FJKLMAA, Fujian Normal University, Fuzhou, China
| | - Feibao Guo
- Department of Radiation Oncology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Jinsheng Hong
- Department of Radiation Oncology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.,Key Laboratory of Radiation Biology (Fujian Medical University), Fujian Province University, Fuzhou, China.,Fujian Key Laboratory of Individualized Active Immunotherapy, Fuzhou, China
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18
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Lenčo J, Khalikova MA, Švec F. Dissolving Peptides in 0.1% Formic Acid Brings Risk of Artificial Formylation. J Proteome Res 2020; 19:993-999. [DOI: 10.1021/acs.jproteome.9b00823] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Affiliation(s)
- Juraj Lenčo
- Department of Analytical Chemistry, Faculty of Pharmacy, Charles University, Heyrovského 1203/8, 500 05 Hradec Králové, Czech Republic
| | - Maria A. Khalikova
- Department of Analytical Chemistry, Faculty of Pharmacy, Charles University, Heyrovského 1203/8, 500 05 Hradec Králové, Czech Republic
| | - František Švec
- Department of Analytical Chemistry, Faculty of Pharmacy, Charles University, Heyrovského 1203/8, 500 05 Hradec Králové, Czech Republic
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