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Zhuo L, Meng F, Sun K, Zhou M, Sun J. Integrated immuno-transcriptomic analysis of ovarian cancer identifies a four-chemokine-dominated subtype with antitumor immune-active phenotype and favorable prognosis. Br J Cancer 2024:10.1038/s41416-024-02803-7. [PMID: 39095528 DOI: 10.1038/s41416-024-02803-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 07/15/2024] [Accepted: 07/18/2024] [Indexed: 08/04/2024] Open
Abstract
BACKGROUND Ovarian cancer (OV) is a heterogeneous disease but has traditionally been treated as an immunologically cold malignancy. The relationship between the immune-active cancer phenotype typified by a T helper 1 (Th-1) immune response and clinical outcome in OV remains uncertain. METHODS A cohort-scale compendium of transcriptomic data from 2850 OV samples from 19 individual datasets was compiled for integrative immuno-transcriptomic analysis. The immunological constant of rejection was used as a metric to assess the Th-1/cytotoxic response orientation and investigate the clinical-biological significance of immune polarization towards a Th-1 immune response. Single-cell RNA sequencing data from 39 OV samples were analyzed to elucidate the variability of the immune microenvironment, and immunohistochemical validation was performed on 39 samples from the Harbin Medical University Cancer Hospital. RESULTS Our results demonstrated the prognostic significance of a Th-1/cytotoxic immune profile within the tumor microenvironment (TME) using the immunological constant of rejection classification to OV samples. Specifically, patients with tumors expressing high levels of ICR markers showed significantly improved survival. A gene panel consisting of four chemokines (CXCL9, CXCL10, CXCL11 and CXCL13) was identified as critical players in mediating the establishment of an active T-cell-inflamed antitumor phenotype. This 4-chemokine signature, which was extensively validated in external multicenter cohorts through transcriptomic profiling and in an independent in-house cohort through immunohistochemistry, introduced a novel immune classification in OV and identified a chemokine-dominated subtype associated with an active antitumor immune phenotype and favorable prognosis. Single-cell transcriptomic analysis revealed that chemokine-dominated tumors increase CXCR3 + NK and T cell recruitment to the TME primarily through the overexpression of macrophage-derived CXCL9/10/11. CONCLUSIONS This study provides new insights into understanding immune heterogeneity within the TME and paves the way for tailoring appropriate therapeutic interventions for patients with differing immune profiles.
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Affiliation(s)
- Lili Zhuo
- School of Biomedical Engineering, Eye Hospital, Wenzhou Medical University, Wenzhou, 325027, China
| | - Fanling Meng
- Department of Gynecology, Harbin Medical University Cancer Hospital, Harbin, 150081, China
| | - Kaidi Sun
- Department of Gynecology, Harbin Medical University Cancer Hospital, Harbin, 150081, China
| | - Meng Zhou
- School of Biomedical Engineering, Eye Hospital, Wenzhou Medical University, Wenzhou, 325027, China.
| | - Jie Sun
- School of Biomedical Engineering, Eye Hospital, Wenzhou Medical University, Wenzhou, 325027, China.
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2
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Hou Y, Zhang F, Zong J, Li T, Gan W, Lv S, Yan Z, Zeng Z, Yang L, Zhou M, Zhao W, Yang M. Integrated analysis reveals a novel 5-fluorouracil resistance-based prognostic signature with promising implications for predicting the efficacy of chemotherapy and immunotherapy in patients with colorectal cancer. Apoptosis 2024; 29:1126-1144. [PMID: 38824480 DOI: 10.1007/s10495-024-01981-2] [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] [Accepted: 05/14/2024] [Indexed: 06/03/2024]
Abstract
BACKGROUND 5-Fluorouracil (5-FU) has been used as a standard first-line treatment for colorectal cancer (CRC) patients. Although 5-FU-based chemotherapy and immune checkpoint blockade (ICB) have achieved success in treating CRC, drug resistance and low response rates remain substantial limitations. Thus, it is necessary to construct a 5-FU resistance-related signature (5-FRSig) to predict patient prognosis and identify ideal patients for chemotherapy and immunotherapy. METHODS Using bulk and single-cell RNA sequencing data, we established and validated a novel 5-FRSig model using stepwise regression and multiple CRC cohorts and evaluated its associations with the prognosis, clinical features, immune status, immunotherapy, neoadjuvant therapy, and drug sensitivity of CRC patients through various bioinformatics algorithms. Unsupervised consensus clustering was performed to categorize the 5-FU resistance-related molecular subtypes of CRC. The expression levels of 5-FRSig, immune checkpoints, and immunoregulators were determined using quantitative real-time polymerase chain reaction (RT‒qPCR). Potential small-molecule agents were identified via Connectivity Map (CMap) and molecular docking. RESULTS The 5-FRSig and cluster were confirmed as independent prognostic factors in CRC, as patients in the low-risk group and Cluster 1 had a better prognosis. Notably, 5-FRSig was significantly associated with 5-FU sensitivity, chemotherapy response, immune cell infiltration, immunoreactivity phenotype, immunotherapy efficiency, and drug selection. We predicted 10 potential compounds that bind to the core targets of 5-FRSig with the highest affinity. CONCLUSION We developed a valid 5-FRSig to predict the prognosis, chemotherapeutic response, and immune status of CRC patients, thus optimizing the therapeutic benefits of chemotherapy combined with immunotherapy, which can facilitate the development of personalized treatments and novel molecular targeted therapies for patients with CRC.
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Affiliation(s)
- Yufang Hou
- State Key Laboratory of Digestive Health, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 2 Nanwei Road, Beijing, 100050, China
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Fang Zhang
- State Key Laboratory of Digestive Health, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 2 Nanwei Road, Beijing, 100050, China
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Jinbao Zong
- Clinical Laboratory, The Affiliated Hospital of Qingdao University, Qingdao, 266000, China
- Qingdao Hospital of Traditional Chinese Medicine, The affiliated Qingdao Hiser Hospital of Qingdao University, Qingdao, 266033, China
| | - Tiegang Li
- State Key Laboratory of Digestive Health, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 2 Nanwei Road, Beijing, 100050, China
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Wenqiang Gan
- State Key Laboratory of Digestive Health, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 2 Nanwei Road, Beijing, 100050, China
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Silin Lv
- State Key Laboratory of Digestive Health, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 2 Nanwei Road, Beijing, 100050, China
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Zheng Yan
- State Key Laboratory of Digestive Health, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 2 Nanwei Road, Beijing, 100050, China
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Zifan Zeng
- State Key Laboratory of Digestive Health, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 2 Nanwei Road, Beijing, 100050, China
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Liu Yang
- State Key Laboratory of Digestive Health, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 2 Nanwei Road, Beijing, 100050, China
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Mingxuan Zhou
- State Key Laboratory of Digestive Health, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 2 Nanwei Road, Beijing, 100050, China
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Wenyi Zhao
- State Key Laboratory of Digestive Health, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 2 Nanwei Road, Beijing, 100050, China
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Min Yang
- State Key Laboratory of Digestive Health, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 2 Nanwei Road, Beijing, 100050, China.
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China.
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Tao B, Yi C, Ma Y, Li Y, Zhang B, Geng Y, Chen Z, Ma X, Chen J. A Novel TGF-β-Related Signature for Predicting Prognosis, Tumor Microenvironment, and Therapeutic Response in Colorectal Cancer. Biochem Genet 2024; 62:2999-3029. [PMID: 38062276 DOI: 10.1007/s10528-023-10591-7] [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: 07/03/2023] [Accepted: 11/07/2023] [Indexed: 07/31/2024]
Abstract
The transforming growth factor beta (TGF-β) signaling plays a critical role in immune evasion and tumor progression. However, its modulatory influences on prognosis, tumor microenvironment (TME), and therapeutic efficacy remain unknown in colorectal cancer (CRC). We summarized TGF-β-related genes and comprehensively estimated their expression pattern in 2142 CRC samples from 9 datasets. Two distinct cluster patterns were divided and biological characteristics of each pattern were further analyzed. Then, to quantify the TGF-β cluster pattern of individual CRC patient, we generated the TGF-β score (TGFBscore) model based on TGF-β cluster pattern-relevant differentially expressed genes (DEGs). Subsequently, we conducted correlation analysis for TGFBscore and clinical prognosis, consensus molecular subtypes (CMSs), TME characteristics, liver metastasis, drug response, and immunotherapeutic efficacy in CRC. We illustrated transcriptional and genetic alterations of TGF-β-relevant genes, which were closely linked with carcinogenic pathways. We identified two different TGF-β cluster patterns, characterized by a high and a low TGFBscore. The TGFBscore-high group was significantly linked with worse patient survival, epithelial-mesenchymal transition (EMT) activation, liver metastasis tendency, and the infiltration of immunosuppressive cells (regulatory T cells [Tregs], M2 macrophages, cancer-associated fibroblasts [CAFs], and myeloid-derived suppressor cells [MDSCs]), while the TGFBscore-low group was linked with a survival advantage, epithelial phenotype, early CRC staging, and the infiltration of immune-activated cells (B cell, CD4 T cell, natural killer T [NKT] cell, and T helper 1 [Th1] cell). In terms of predicting drug response, TGFBscore negatively correlated (sensitive to TGFBscore-high group) with drugs targeting PI3K/mTOR, JNK and p38, RTK signaling pathways, and positively correlated (sensitive to TGFBscore-low group) with drugs targeting EGFR signaling pathway. Also, TGFBscore could predict the efficacy of different anti-tumor therapies. TGFBscore-low patients might benefit more from anti-PDL1 immunotherapy, adjuvant chemotherapy (ACT), and ERBB targeted therapy, whereas TGFBscore-high patients might benefit more from antiangiogenic targeted therapy. Our study constructed a novel TGF-β scoring model that could predict prognosis, liver metastasis tendency, and TME characteristics for CRC patients. More importantly, this work emphasizes the potential clinical utility of TGFBscore in evaluating the efficacy of chemotherapy, targeted therapy, and immunotherapy, guiding individualized precision treatment in CRC.
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Affiliation(s)
- Baorui Tao
- Department of General Surgery, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, People's Republic of China
- Cancer Metastasis Institute, Fudan University, Shanghai, People's Republic of China
| | - Chenhe Yi
- Department of General Surgery, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, People's Republic of China
- Cancer Metastasis Institute, Fudan University, Shanghai, People's Republic of China
| | - Yue Ma
- Department of General Surgery, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, People's Republic of China
- Cancer Metastasis Institute, Fudan University, Shanghai, People's Republic of China
| | - Yitong Li
- Department of General Surgery, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, People's Republic of China
- Cancer Metastasis Institute, Fudan University, Shanghai, People's Republic of China
| | - Bo Zhang
- Department of General Surgery, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, People's Republic of China
- Cancer Metastasis Institute, Fudan University, Shanghai, People's Republic of China
| | - Yan Geng
- Department of General Surgery, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, People's Republic of China
- Cancer Metastasis Institute, Fudan University, Shanghai, People's Republic of China
| | - Zhenmei Chen
- Department of General Surgery, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, People's Republic of China
- Cancer Metastasis Institute, Fudan University, Shanghai, People's Republic of China
| | - Xiaochen Ma
- Department of General Surgery, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, People's Republic of China
- Cancer Metastasis Institute, Fudan University, Shanghai, People's Republic of China
| | - Jinhong Chen
- Department of General Surgery, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, People's Republic of China.
- Cancer Metastasis Institute, Fudan University, Shanghai, People's Republic of China.
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Li X, Liu D, Wu Z, Xu Y. Diffuse tumors: Molecular determinants shared by different cancer types. Comput Biol Med 2024; 178:108703. [PMID: 38850961 DOI: 10.1016/j.compbiomed.2024.108703] [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: 12/05/2023] [Revised: 05/02/2024] [Accepted: 06/01/2024] [Indexed: 06/10/2024]
Abstract
Most cancer types have both diffuse and non-diffuse subtypes, which have rather distinct morphologies, namely scattered tiny tumors vs. one solid tumor, and different levels of aggressiveness. However, the causes for forming such distinct subtypes remain largely unknown. Using the diffuse and non-diffuse gastric cancers (GCs) as the illustrative example, we present a computational study based on the transcriptomic data from the TCGA and GEO databases, to address the following questions: (i) What are the key molecular determinants that give rise to the distinct morphologies between diffuse and non-diffuse cancers? (ii) What are the main reasons for diffuse cancers to be generally more aggressive than non-diffuse ones of the same cancer type? (iii) What are the reasons for their distinct immunoactivities? And (iv) why do diffuse cancers on average tend to take place in younger patients? The study is conducted using the framework we have previously developed for elucidation of general drivers cancer formation and development. Our main discoveries are: (a) the level of (poly-) sialic acids deployed on the surface of cancer cells is a significant factor contributing to questions (i) and (ii); (b) poly-sialic acids synthesized by ST8SIA4 are the key to question (iii); and (c) the circulating growth factors specifically needed by the diffuse subtype dictate the answer to question (iv). All these predictions are substantiated by published experimental studies. Our further analyses on breast, prostate, lung, liver, and thyroid cancers reveal that these discoveries generally apply to the diffuse subtypes of these cancer types, hence indicating the generality of our discoveries.
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Affiliation(s)
- Xuan Li
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun, 130012, China; School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Dingyun Liu
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun, 130012, China
| | - Zhipeng Wu
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun, 130012, China
| | - Ying Xu
- School of Medicine, Southern University of Science and Technology, Shenzhen, China.
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Ju M, Zhang J, Deng Z, Wei M, Ma L, Chen T, Zhao L. Prophylactic IL-23 blockade uncouples efficacy and toxicity in dual CTLA-4 and PD-1 immunotherapy. J Immunother Cancer 2024; 12:e009345. [PMID: 39089739 PMCID: PMC11293404 DOI: 10.1136/jitc-2024-009345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/22/2024] [Indexed: 08/04/2024] Open
Abstract
BACKGROUND Immune-related adverse events (irAEs), characterized by targeted inflammation, occur in up to 60% of patients with melanoma treated with immune checkpoint inhibitors (ICIs). Evidence proved that the baseline peripheral blood profiles of patients at risk for severe irAEs development paralleled clinical autoimmunity. Interleukin (IL)-23 blockade with risankizumab is recommended for cases that are suffering from autoimmune disease, such as autoimmune colitis. However, currently, the role of IL-23 in irAEs onset and severity remains poorly understood. METHODS The pro-inflammatory cytokines most associated with severe irAEs onset were identified by retrospective analysis based on GSE186143 data set. To investigate the efficacy of prophylactic IL-23 blockade administration to prevent irAEs, refer to a previous study, we constructed two irAEs murine models, including dextran sulfate sodium salt (DSS)-induced colitis murine model and a combined-ICIs-induced irAEs murine model. To further explore the applicability of our findings, murine models with graft-versus-host disease were established, in which Rag2-/-Il2rg-/- mice were transferred with human peripheral blood mononuclear cells and received combined cytotoxic T-lymphocyte associated antigen 4 (CTLA-4) and programmed cell death protein-1 (PD-1) treatment. Human melanoma cells were xenografted into these mice concomitantly. RESULTS Here we show that IL-23 was upregulated in the serum of patients suffering from irAEs after dual anti-CTLA-4 and anti-PD-1 treatment, and increased as a function of irAEs severity. Additionally, Augmented CD4+ Tems may preferentially underlie irAEs onset. Treating mice with anti-mouse IL-23 antibody concomitantly with combined CTLA-4 and PD-1 immunotherapy ameliorates colitis and, in addition, preserves antitumor efficacy. Moreover, in xenografted murine models with irAEs, prophylactic blockade of human IL-23 using clinically available IL-23 inhibitor (risankizumab) ameliorated colitis, hepatitis and lung inflammation, and moreover, immunotherapeutic control of tumors was retained. Finally, we also provided a novel machine learning-based computational framework based on two blood-based features-IL-23 and CD4+ Tems-that may have predictive potential for severe irAEs and ICIs response. CONCLUSIONS Our study not only provides clinically feasible strategies to dissociate efficacy and toxicity in the use of combined ICIs for cancer immunotherapy, but also develops a blood-based biomarker that makes it possible to achieve a straightforward and non-invasive, detection assay for early prediction of irAEs onset.
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Affiliation(s)
- Mingyi Ju
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China
- Liaoning Key Laboratory of molecular targeted anti-tumor drug development and evaluation; Liaoning Cancer immune peptide drug Engineering Technology Research Center; Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang, China
| | - Jiaojiao Zhang
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China
- Liaoning Key Laboratory of molecular targeted anti-tumor drug development and evaluation; Liaoning Cancer immune peptide drug Engineering Technology Research Center; Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang, China
| | - Zhuoyuan Deng
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China
- Liaoning Key Laboratory of molecular targeted anti-tumor drug development and evaluation; Liaoning Cancer immune peptide drug Engineering Technology Research Center; Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang, China
| | - Minjie Wei
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China
- Liaoning Key Laboratory of molecular targeted anti-tumor drug development and evaluation; Liaoning Cancer immune peptide drug Engineering Technology Research Center; Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang, China
- Liaoning Medical Diagnosis and Treatment Center, Shenyang, China
| | - Lianghua Ma
- Department of Radiation Oncology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Ting Chen
- Department of Orthopedics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Lin Zhao
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China
- Liaoning Key Laboratory of molecular targeted anti-tumor drug development and evaluation; Liaoning Cancer immune peptide drug Engineering Technology Research Center; Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang, China
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Rao F, Cao J, Wang C, Xiang S, Wu K, Lin D, Lv J, Wang X, Wang M, Xiang L. Overexpression of miR-96 leads to retinal degeneration in mice. Biochem Biophys Res Commun 2024; 719:150048. [PMID: 38763044 DOI: 10.1016/j.bbrc.2024.150048] [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] [Accepted: 05/01/2024] [Indexed: 05/21/2024]
Abstract
Double knockout of miR-183 and miR-96 results in retinal degeneration in mice; however, single knockout of miR-96 leads to developmental delay but not substantial retinal degeneration. To further explore the role of miR-96, we overexpressed this miRNA in mouse retinas. Interestingly, we found that overexpression of miR-96 at a safe dose results in retinal degeneration in the mouse retina. The retinal photoreceptors dramatically degenerated in the miR-96-overexpressing group, as shown by OCT, ERG and cryosectioning at one month after subretinal injection. Degenerative features such as TUNEL signals and reactive gliosis were observed in the miR-96-overexpressing retina. RNA-seq data revealed that immune responses and microglial activation occurred in the degenerating retina. Further qRT‒PCR and immunostaining experiments verified the microglial activation. Moreover, the number of microglia in the miR-96-overexpressing retinas was significantly increased. Our findings demonstrate that appropriate miR-96 expression is required for mouse retinal homeostasis.
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Affiliation(s)
- Fengqin Rao
- Department of Anesthesiology, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai 317000, China; Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China; College of Nursing, Wenzhou Medical University, Wenzhou 325035, China; School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, 325035, China
| | - Jianbin Cao
- Department of Anesthesiology, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai 317000, China
| | - Chenyu Wang
- Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Shengjin Xiang
- Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Kunchao Wu
- Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China; Department of Ophthalmology, The First People's Hospital of Guiyang, China
| | - Dan Lin
- Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Jineng Lv
- Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Xiaojie Wang
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, 325035, China.
| | - Mingcang Wang
- Department of Anesthesiology, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai 317000, China.
| | - Lue Xiang
- Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China.
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Zhou R, Jia X, Li Z, Huang S, Feng W, Zhu X. Identifying an immunosenescence-associated gene signature in gastric cancer by integrating bulk and single-cell sequencing data. Sci Rep 2024; 14:17055. [PMID: 39048596 PMCID: PMC11269723 DOI: 10.1038/s41598-024-68054-x] [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: 03/11/2024] [Accepted: 07/19/2024] [Indexed: 07/27/2024] Open
Abstract
It has been believed that immunosenescence plays a crucial role in tumorigenesis and cancer therapy. Nevertheless, there is still a lack of understanding regarding its role in determining clinical outcomes and therapy selection for gastric cancer patients, due to the lack of a feasible immunosenescence signature. Therefore, this research aims to develop a gene signature based on immunosenescence, which is used for stratification of gastric cancer. By integrative analysis of bulk transcriptome and single-cell data, we uncovered immunosenescence features in gastric cancer. Random forest algorithm was used to select hub genes and multivariate Cox algorithm was applied to construct a scoring system to evaluate the prognosis and the response to immunotherapy and chemotherapy. The Cancer Genome Atlas of Stomach Adenocarcinoma (TCGA-STAD) cohort was implemented as the training cohort and two independent cohorts from the Gene Expression Omnibus (GEO) database were used for validation. The model was further tested by our Fudan cohort. In this study, immunosenescence was identified as a hallmark of gastric cancer that is linked with transcriptomic features, genomic variations, and distinctive tumor microenvironment (TME). Four immunosenescence genes, including APOD, ADIPOR2, BRAF, and C3, were screened out to construct a gene signature for risk stratification. Higher risk scores indicated strong predictive power for poorer overall survival. Notably, the risk score signature could reliably predict response to chemotherapy and immunotherapy, with patients with high scores benefiting from immunotherapy and patients with low scores responding to chemotherapy. We report immunosenescence as a hitherto unheralded hallmark of gastric cancer that affects prognosis and treatment efficiency.
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Affiliation(s)
- Runye Zhou
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Hepatic Oncology, Zhongshan Hospital, Fudan University, Shanghai, China
- Shanghai Key Laboratory of Medical Epigenetics, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
- Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
| | - Xiya Jia
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
- Shanghai Key Laboratory of Medical Epigenetics, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
- Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
| | - Ziteng Li
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
- Shanghai Key Laboratory of Medical Epigenetics, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
- Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
| | - Shenglin Huang
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
- Shanghai Key Laboratory of Medical Epigenetics, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
- Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
| | - Wanjing Feng
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
- Shanghai Key Laboratory of Medical Epigenetics, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
- Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
| | - Xiaodong Zhu
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
- Shanghai Key Laboratory of Medical Epigenetics, Institutes of Biomedical Sciences, Fudan University, Shanghai, China.
- Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China.
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Huang X, Du G, Yang Y, Su P, Chen S, Cai C, Huang T, Zeng Y, Tao Y, Tian D, Zhang N. Advancing bladder cancer management: development of a prognostic model and personalized therapy. Front Immunol 2024; 15:1430792. [PMID: 39104534 PMCID: PMC11298345 DOI: 10.3389/fimmu.2024.1430792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Accepted: 07/08/2024] [Indexed: 08/07/2024] Open
Abstract
Background Bladder cancer (BLCA) was recognized as a significant public health challenge due to its high incidence and mortality rates. The influence of molecular subtypes on treatment outcomes was well-acknowledged, necessitating further exploration of their characterization and application. This study was aimed at enhancing the understanding of BLCA by mapping its molecular heterogeneity and developing a robust prognostic model using single-cell and bulk RNA sequencing data. Additionally, immunological characteristics and personalized treatment strategies were investigated through the risk score. Methods Single-cell RNA sequencing (scRNA-seq) data from GSE135337 and bulk RNA-seq data from several sources, including GSE13507, GSE31684, GSE32894, GSE69795, and TCGA-BLCA, were utilized. Molecular subtypes, particularly the basal-squamous (Ba/Sq) subtype associated with poor prognosis, were identified. A prognostic model was constructed using LASSO and Cox regression analyses focused on genes linked with the Ba/Sq subtype. this model was validated across internal and external datasets to ensure predictive accuracy. High- and low-risk groups based on the risk score derived from TCGA-BLCA data were analyzed to examine their immune-related molecular profiles and treatment responses. Results Six molecular subtypes were identified, with the Ba/Sq subtype being consistently associated with poor prognosis. The prognostic model, based on basal-squamous subtype-related genes (BSSRGs), was shown to have strong predictive performance across diverse clinical settings with AUC values at 1, 3, and 5 years indicating robust predictability in training, testing, and entire datasets. Analysis of the different risk groups revealed distinct immune infiltration and microenvironments. Generally higher tumor mutation burden (TMB) scores and lower tumor immune dysfunction and exclusion (TIDE) scores were exhibited by the low-risk group, suggesting varied potentials for systemic drug response between the groups. Finally, significant differences in potential systemic drug response rates were also observed between risk groups. Conclusions The study introduced and validated a new prognostic model for BLCA based on BSSRGs, which was proven effective in prognosis prediction. The potential for personalized therapy, optimized by patient stratification and immune profiling, was highlighted by our risk score, aiming to improve treatment efficacy. This approach was promised to offer significant advancements in managing BLCA, tailoring treatments based on detailed molecular and immunological insights.
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Affiliation(s)
- Xiang Huang
- Department of Urology, Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Guotu Du
- Department of Urology, Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Ying Yang
- Department of Pathology, Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Peng Su
- Department of Urology, Affiliated Hospital of Zunyi Medical University, Zunyi, China
- Department of Pathology, Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Shicheng Chen
- Department of Urology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Chongjiong Cai
- Department of Urology, Affiliated Hospital of Zunyi Medical University, Zunyi, China
- Department of Urology, Renhuai People’s Hospital, Zunyi, China
| | - Tianyu Huang
- Department of Nursing, Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Yu Zeng
- Department of Urology, Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Yonggang Tao
- Department of Urology, Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Demei Tian
- Department of Urology, Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Neng Zhang
- Department of Urology, Affiliated Hospital of Zunyi Medical University, Zunyi, China
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9
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Wang Y, Xie Y, Qian L, Ding R, Pang R, Chen P, Zhang Q, Zhang S. RAB42 overexpression correlates with poor prognosis, immune cell infiltration and chemoresistance. Front Pharmacol 2024; 15:1445170. [PMID: 39101146 PMCID: PMC11294155 DOI: 10.3389/fphar.2024.1445170] [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: 06/06/2024] [Accepted: 06/26/2024] [Indexed: 08/06/2024] Open
Abstract
Background RAB42 (Ras-related protein 42) is a new small GTPase that controls the vesicular trafficking from endosomes to trans-Golgi network in mammalian cells. However, the role of RAB42 in multiple cancers, especially in liver hepatocellular carcinoma (LIHC), has not been well investigated. Methods A variety of cancer-related databases and online tools, including TCGA, GTEx, TARGET, QUANTISEQ, EPIC, RNAactDrug, CTR-DB, TIMER algorithms and Sangerbox, were applied to explore the correlation of RAB42 expression with prognosis, immune microenvironment, immune regulatory network, RNA modification, pathway activation and drug sensitivity in pan-cancer. The prognostic, immunomodulatory and tumor-promoting effects of RAB42 were verified in various malignancies and determined by a series of in vitro cellular experiments. Results RAB42 is significantly overexpressed in most cancers with advanced pathological stages. Its overexpression is correlated with poor survival in pan-cancer. RAB42 overexpression has a high diagnostic accuracy of various cancers (AUC > 0.80). RAB42 overexpression not only correlates with distinct stromal immune infiltration and level of immune checkpoint molecules, but also associates with weak immune cell infiltration, immunomodulatory genes expression, and immunotherapeutic response to immune checkpoint inhibitors (ICIs). Additionally, RAB42 overexpression correlates with enhanced expression of m6A RNA methylation-related genes (MRGs) and its interactors. Moreover, overexpression of RAB42 serves as a drug-resistant marker to certain chemotherapies and acts as a potential biomarker for LIHC. Notably, RAB42 overexpression or activation promotes the cellular proliferation, migration and invasion of LIHC. Conclusion Overexpressed RAB42 serves as a potential prognostic biomarker and therapeutic target in pan-cancer, especially in LIHC.
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Affiliation(s)
- Yang Wang
- Department of Cell Biology, School of Medicine, Nankai University, Tianjin, China
| | - Youbang Xie
- Department of Hematology and Rheumatology, Qinghai Provincial People’s Hospital, Xining, Qinghai, China
| | - Luomeng Qian
- Department of Cell Biology, School of Medicine, Nankai University, Tianjin, China
| | - Ran Ding
- School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, China
| | - Rongqing Pang
- Basic Medical Laboratory, 920th Hospital of Joint Logistics Support Force, Kunming, Yunnan, China
| | - Ping Chen
- National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Qing Zhang
- National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Sihe Zhang
- Department of Cell Biology, School of Medicine, Nankai University, Tianjin, China
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10
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Fu D, Weng X, Su Y, Hong B, Zhao A, Lin J. Establishing a model composed of immune-related gene-modules to predict tumor immunotherapy response. Sci Rep 2024; 14:16630. [PMID: 39025898 PMCID: PMC11258235 DOI: 10.1038/s41598-024-67742-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: 01/31/2024] [Accepted: 07/15/2024] [Indexed: 07/20/2024] Open
Abstract
At present, tumor immunotherapy has been widely applied to treat various cancers. However, the accuracy of predicting treatment efficacy has not yet achieved a significant breakthrough. This study aimed to construct a prediction model based on the modified WGCNA algorithm to precisely judge the anti-tumor immune response. First, we used a murine colon cancer model to screen corresponding DEGs according to different groups. GSEA was used to analyze the potential mechanisms of the immune-related DEGs (irDEGs) in each group. Subsequently, the intersection of the irDEGs in every group was acquired, and 7 gene-modules were mapped. Finally, 4 gene-modules including cogenes, antiPD-1 immu-genes, chemo immu-genes and comb immu-genes, were selected for subsequent study. Furthermore, a clinical dataset of gastric cancer patients receiving immunotherapy was enrolled, and the irDEGs were identified. A total of 34 vital irDEGs were obtained from the intersections of the vital irDEGs and the four gene-modules. Next, the vital irDEGs were analyzed by the modified WGCNA algorithm, and the correlation coefficients between the 4 gene-modules and the response status to immunotherapy were calculated. Thus, a prediction model based on correlation coefficients was built, and the corresponding model scores were acquired. The AUC calculated according to the model score was 0.727, which was non-inferior to that of the ESTIMATE score and the TIDE score. Meanwhile, the AUC calculated according to the classification of the model scores was 0.705, which was non-inferior to that of the ESTIMATE classification and the TIDE classification. The prediction accuracy of the model was validated in clinical datasets of other cancers.
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Affiliation(s)
- Deqiang Fu
- Department of Oncology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Xiaoyuan Weng
- Thyroid and Breast Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
- Quanzhou Medical College, Quanzhou, China
| | - Yunxia Su
- Department of Oncology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Binhuang Hong
- Department of Oncology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Aiyue Zhao
- Department of Oncology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
| | - Jianqing Lin
- Thyroid and Breast Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
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11
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Liu T, Liu C, Li Q, Zheng X, Zou F. Adaptive Regularized Tri-Factor Non-Negative Matrix Factorization for Cell Type Deconvolution. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.07.570631. [PMID: 38106220 PMCID: PMC10723472 DOI: 10.1101/2023.12.07.570631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Accurate deconvolution of cell types from bulk gene expression is crucial for understanding cellular compositions and uncovering cell-type specific differential expression and physiological states of diseased tissues. Existing deconvolution methods have limitations, such as requiring complete cellular gene expression signatures or neglecting partial biological information. Moreover, these methods often overlook varying cell-type mRNA amounts, leading to biased proportion estimates. Additionally, they do not effectively utilize valuable reference information from external studies, such as means and ranges of population cell-type proportions. To address these challenges, we introduce an Adaptive Regularized Tri-factor non-negative matrix factorization approach for deconvolution (ARTdeConv). We rigorously establish the numerical convergence of our algorithm. Through benchmark simulations, we demonstrate the superior performance of ARTdeConv compared to state-of-the-art semi-reference-based and reference-free methods. In a real-world application, our method accurately estimates cell proportions, as evidenced by the nearly perfect Pearson's correlation between ARTdeConv estimates and flow cytometry measurements in a dataset from a trivalent influenza vaccine study. Moreover, our analysis of ARTdeConv estimates in COVID-19 patients reveals patterns consistent with important immunological phenomena observed in other studies. The proposed method, ARTdeConv, is implemented as an R package and can be accessed on GitHub for researchers and practitioners.
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12
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Li XP, Song JT, Dai YT, Zhang WN, Zhao BT, Mao JY, Gao Y, Jiang L, Liang Y. Integrative single-cell analysis of longitudinal t(8;21) AML reveals heterogeneous immune cell infiltration and prognostic signatures. Front Immunol 2024; 15:1424933. [PMID: 39086485 PMCID: PMC11288856 DOI: 10.3389/fimmu.2024.1424933] [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: 04/28/2024] [Accepted: 07/01/2024] [Indexed: 08/02/2024] Open
Abstract
Introduction Immunotherapies targeting T cells in solid cancers are revolutionizing clinical treatment. Novel immunotherapies have had extremely limited benefit for acute myeloid leukemia (AML). Here, we characterized the immune microenvironment of t(8;21) AML patients to determine how immune cell infiltration status influenced prognosis. Methods Through multi-omics studies of primary and longitudinal t(8;21) AML samples, we characterized the heterogeneous immune cell infiltration in the tumor microenvironment and their immune checkpoint gene expression. Further external cohorts were also included in this research. Results CD8+ T cells were enriched and HAVCR2 and TIGIT were upregulated in the CD34+CD117dim%-High group; these features are known to be associated with immune exhaustion. Data integration analysis of single-cell dynamics revealed that a subset of T cells (cluster_2) (highly expressing GZMB, NKG7, PRF1 and GNLY) evolved and expanded markedly in the drug-resistant stage after relapse. External cohort analysis confirmed that the cluster_2 T-cell signature could be utilized to stratify patients by overall survival outcome. Discussion In conclusion, we discovered a distinct T-cell signature by scRNA-seq that was correlated with disease progression and drug resistance. Our research provides a novel system for classifying patients based on their immune microenvironment.
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MESH Headings
- Humans
- Leukemia, Myeloid, Acute/genetics
- Leukemia, Myeloid, Acute/immunology
- Leukemia, Myeloid, Acute/mortality
- Leukemia, Myeloid, Acute/therapy
- Single-Cell Analysis/methods
- Prognosis
- Tumor Microenvironment/immunology
- Tumor Microenvironment/genetics
- Chromosomes, Human, Pair 8/genetics
- Lymphocytes, Tumor-Infiltrating/immunology
- Lymphocytes, Tumor-Infiltrating/metabolism
- Male
- Female
- Translocation, Genetic
- Chromosomes, Human, Pair 21/genetics
- CD8-Positive T-Lymphocytes/immunology
- Adult
- Middle Aged
- Biomarkers, Tumor/genetics
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Affiliation(s)
- Xue-Ping Li
- Department of Hematologic Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Jiang-Tao Song
- Department of Hematologic Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Yu-Ting Dai
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wei-Na Zhang
- Department of Hematology, Guangzhou Women and Children’s Medical Center, Guangzhou, China
| | - Bai-Tian Zhao
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Jia-Ying Mao
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Yan Gao
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Lu Jiang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yang Liang
- Department of Hematologic Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China
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13
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He C, Zhang J, Bai X, Lu C, Zhang K. Lysine lactylation-based insight to understanding the characterization of cervical cancer. Biochim Biophys Acta Mol Basis Dis 2024; 1870:167356. [PMID: 39025375 DOI: 10.1016/j.bbadis.2024.167356] [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: 11/09/2023] [Revised: 06/28/2024] [Accepted: 07/10/2024] [Indexed: 07/20/2024]
Abstract
Lysine lactylation (Kla), a recently discovered post-translational modification (PTM), is not only present in histone proteins but also widely distributed among non-histone proteins in tumor cells and immunocytes. However, the precise characterization and functional implications of these non-histone Kla proteins remain to be explored. Herein, a comprehensive proteomic analysis of Kla was conducted in HeLa cells. As a result, a total of 3633 Kla sites on 1637 proteins were identified. Subsequently, the stable Kla substrates were obtained and sorted to investigate the characterization and function of Kla proteins. Moreover, we characterized the Kla-related features of cervical cancers through integrative analyses of multiple datasets with proteomes, transcriptomes and single-cell transcriptome profiling. Kla-related genes (KRGs) were used to stratify cervical cancers into two clusters (C1 and C2). C2 cluster display inhibition in glycosylation and increased oxidative phosphorylation activity with high survival rate. In addition, we constructed a prognostic model based on two lactate signature genes, namely ISY1 and PPP1R14B. Interestingly, our findings revealed a negative correlation between PPP1R14B expression and the infiltration of CD8+ T cells, as well as a lower survival rate. This observation was further validated at the single-cell resolution. Simultaneously, we found that K140R mutant of PPP1R14B resulted in the decrease of Kla level and enhanced the proliferation and migration capabilities of cervical cancer cell lines, suggesting PPP1R14B-K140la has an effect on tumor behaviors. Collectively, we provides a Kla-based insight to understanding the characterization of cervical cancer, offering a potential avenue for therapeutic approaches.
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Affiliation(s)
- Chaoran He
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Jianji Zhang
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Xue Bai
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Congcong Lu
- Frontiers Science Center for Cell Responses, Department of Biochemistry and Molecular Biology, College of Life Sciences, Nankai University, Tianjin 300071, China
| | - Kai Zhang
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China.
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14
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Wang H, Arulraj T, Ippolito A, Popel AS. From virtual patients to digital twins in immuno-oncology: lessons learned from mechanistic quantitative systems pharmacology modeling. NPJ Digit Med 2024; 7:189. [PMID: 39014005 PMCID: PMC11252162 DOI: 10.1038/s41746-024-01188-4] [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: 01/25/2024] [Accepted: 07/03/2024] [Indexed: 07/18/2024] Open
Abstract
Virtual patients and digital patients/twins are two similar concepts gaining increasing attention in health care with goals to accelerate drug development and improve patients' survival, but with their own limitations. Although methods have been proposed to generate virtual patient populations using mechanistic models, there are limited number of applications in immuno-oncology research. Furthermore, due to the stricter requirements of digital twins, they are often generated in a study-specific manner with models customized to particular clinical settings (e.g., treatment, cancer, and data types). Here, we discuss the challenges for virtual patient generation in immuno-oncology with our most recent experiences, initiatives to develop digital twins, and how research on these two concepts can inform each other.
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Affiliation(s)
- Hanwen Wang
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Theinmozhi Arulraj
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Alberto Ippolito
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Aleksander S Popel
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Departments of Medicine and Oncology, and the Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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15
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Liu W, Liu Y, Chen S, Hui J, He S. AURKB promotes immunogenicity and immune infiltration in clear cell renal cell carcinoma. Discov Oncol 2024; 15:286. [PMID: 39014265 PMCID: PMC11252114 DOI: 10.1007/s12672-024-01141-7] [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: 03/19/2024] [Accepted: 07/02/2024] [Indexed: 07/18/2024] Open
Abstract
BACKGROUND Chromatin regulators (CRs) are capable of causing epigenetic alterations, which are significant features of cancer. However, the function of CRs in controlling Clear Cell Renal Cell Carcinoma (ccRCC) is not well understood. This research aims to discover a CRs prognostic signature in ccRCC and to elucidate the roles of CRs-related genes in tumor microenvironment (TME). METHODS Expression profiles and relevant clinical annotations were retrieved from the Cancer Genome Atlas (TCGA) and UCSC Xena platform for progression-free survival (PFS) data. The R package "limma" was used to identify differentially expressed CRs. A predictive model based on five CRs was developed using LASSO-Cox analysis. The model's predictive power and applicability were validated using K-M curves, ROC curves, nomograms, comparisons with other models, stratified survival analyses, and validation with the ICGC cohort. GO and GSEA analyses were performed to investigate mechanisms differentiating low and high riskScore groups. Immunogenicity was assessed using Tumor Mutational Burden (TMB), immune cell infiltrations were inferred, and immunotherapy was evaluated using immunophenogram analysis and the expression patterns of human leukocyte antigen (HLA) and checkpoint genes. Differentially expressed CRs (DECRs) between low and high riskScore groups were identified using log2|FC|> 1 and FDR < 0.05. AURKB, one of the high-risk DECRs and a component of our prognostic model, was selected for further analysis. RESULTS We constructed a 5 CRs signature, which demonstrated a strong capacity to predict survival and greater applicability in ccRCC. Elevated immunogenicity and immune infiltration in the high riskScore group were associated with poor prognosis. Immunotherapy was more effective in the high riskScore group, and certain chemotherapy medications, including cisplatin, docetaxel, bleomycin, and axitinib, had lower IC50 values. Our research shows that AURKB is critical for the immunogenicity and immune infiltration of the high riskScore group. CONCLUSION Our study produced a reliable prognostic prediction model using only 5 CRs. We found that AURKB promotes immunogenicity and immune infiltration. This research provides crucial support for the development of prognostic biomarkers and treatment strategies for ccRCC.
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Affiliation(s)
- Weihao Liu
- Department of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Ying Liu
- Department of Oncology, Huadu District People's Hospital of Guangzhou, Guangzhou, 510810, Guangdong, China
| | - Shisheng Chen
- Department of Urology, Dongguan Tungwah Hospital, Dongguan, 523110, Guangdong, China
| | - Jialiang Hui
- Department of Organ Transplantation, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
| | - Shuhua He
- Department of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
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16
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Liu HX, Feng J, Jiang JJ, Shen WJ, Zheng Y, Liu G, Gao XY. Integrated single-cell and bulk RNA sequencing revealed an epigenetic signature predicts prognosis and tumor microenvironment colorectal cancer heterogeneity. World J Gastrointest Oncol 2024; 16:3032-3054. [PMID: 39072180 PMCID: PMC11271797 DOI: 10.4251/wjgo.v16.i7.3032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 04/23/2024] [Accepted: 05/07/2024] [Indexed: 07/12/2024] Open
Abstract
BACKGROUND Colorectal cancer (CRC) prognosis prediction is currently a major challenge. Epigenetic regulation has been widely reported for its role in cancer development. AIM To construct a robust prognostic signature, we used developed and validated across datasets. METHODS After constructing the signature, the prognostic value of the signature was evaluated in the TCGA cohort and six independent datasets (GSE17526, GSE17537, GSE33113, GSE37892, GSE39048 and GSE39582). The clinical, genomic and transcriptomic features related to the signature were identified. The correlations of the signature score with immune cell infiltration and cell-cell interactions were analyzed. The correlations between the signature score and the sensitivity to different drugs were also predicted. RESULTS In the TCGA cohort, patients in the low-risk group according to the signature score had longer survival than those in the high-risk group, and this finding was validated in the validation datasets. The signature was a prognostic factor independent of age and sex and was correlated with stage and PD-1/PD-L1 expression. Area under the receiving operating characteristic curve was 0.72. Genomic association analyses revealed that samples from high-risk patients exhibited chromosomal instability. Transcriptomic analyses revealed that the signature score was significantly associated with multiple cellular pathways. Bulk RNA-seq and single-cell sequencing data revealed that the signature reflected differences in infiltrating immune cell-tumor cell interactions, especially for macrophages. The signature also predicted the putative drug sensitivity of CRC samples. CONCLUSION The signature is a valuable biomarker for predicting CRC prognosis and reflects multiple features of CRC, especially macrophage infiltration in the microenvironment.
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Affiliation(s)
- Han-Xuan Liu
- Beijing Jinghua Anliang Technology, Beijing 102627, China
| | - Jie Feng
- Department of Clinical Laboratory, The First Medical Centre of Chinese PLA General Hospital, Beijing 100853, China
| | - Jing-Jing Jiang
- Clinical Biological Sample Center, Medical Innovation Research Division of Chinese PLA General Hospital, Beijing 100853, China
| | - Wan-Jun Shen
- Department of Nephrology, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
| | - Yu Zheng
- Institute of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Gang Liu
- Institute of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Xiang-Yang Gao
- The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing 100853, China
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17
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Lian P, Cai X, Wang C, Zhai H, Liu K, Yang X, Wu Y, Ma Z, Cao X, Xu Y. Identification and experimental validation of m7G-related molecular subtypes, immune signature, and feature genes in Alzheimer's disease. Heliyon 2024; 10:e33836. [PMID: 39027505 PMCID: PMC11255592 DOI: 10.1016/j.heliyon.2024.e33836] [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: 09/15/2023] [Revised: 06/01/2024] [Accepted: 06/27/2024] [Indexed: 07/20/2024] Open
Abstract
Background Studies has shown that N7-methylguanosine (m7G) modification plays a critical role in neurological diseases. However, the exact role and association of m7G with the immune microenvironment in Alzheimer's disease (AD) remain largely unknown and unexplored. Methods The study datasets comprised 667 AD samples and 503 control samples selected from eight datasets in the Gene Expression Omnibus database; m7G regulator genes were obtained from previous literature. The AD subtypes were identified by consensus clustering analysis according to m7G regulator genes. The clinical characteristics, immune infiltration, and biological functions of the AD subgroups were evaluated. A combination of different types of machine-learning algorithms were used for the identification of AD genes. We also assessed and validated the diagnostic performance of the identified genes via qRT-PCR, immunofluorescence, and immunohistochemical analyses. Results Two AD distinct subgroups, namely cluster A and cluster B, were identified. Cluster A had poor pathological progression and immune infiltration, representing a high-risk subgroup for AD. The differentially expressed genes of cluster A were enriched in immune and synapse-related pathways, suggesting that these genes probably contribute to AD progression by regulating immune-related pathways. Additionally, five feature genes (AEBP1, CARTPT, AK5, NPTX2, and COPG2IT1) were identified, which were used to construct a nomogram model with good ability to predict AD. The animal experiment analyses further confirmed that these feature genes were associated with AD development. Conclusion To the best of our knowledge, this is the first study to reveal close correlations among m7G RNA modification, the immune microenvironment, and the pathogenesis of AD. We also identified five feature genes associated with AD, further contributing to our understanding of the underlying mechanisms and potential therapeutic targets for AD.
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Affiliation(s)
- Piaopiao Lian
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xing Cai
- Department of Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Cailin Wang
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Heng Zhai
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ke Liu
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoman Yang
- Department of Neurology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Yi Wu
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhuoran Ma
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xuebing Cao
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan Xu
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Huang H, Zhu X, Yu Y, Li Z, Yang Y, Xia L, Lu S. EGFR mutations induce the suppression of CD8 + T cell and anti-PD-1 resistance via ERK1/2-p90RSK-TGF-β axis in non-small cell lung cancer. J Transl Med 2024; 22:653. [PMID: 39004699 PMCID: PMC11246587 DOI: 10.1186/s12967-024-05456-5] [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: 04/16/2024] [Accepted: 07/01/2024] [Indexed: 07/16/2024] Open
Abstract
BACKGROUND Non-small cell lung cancer (NSCLC) patients with EGFR mutations exhibit an unfavorable response to immune checkpoint inhibitor (ICI) monotherapy, and their tumor microenvironment (TME) is usually immunosuppressed. TGF-β plays an important role in immunosuppression; however, the effects of TGF-β on the TME and the efficacy of anti-PD-1 immunotherapy against EGFR-mutated tumors remain unclear. METHODS Corresponding in vitro studies used the TCGA database, clinical specimens, and self-constructed mouse cell lines with EGFR mutations. We utilized C57BL/6N and humanized M-NSG mouse models bearing EGFR-mutated NSCLC to investigate the effects of TGF-β on the TME and the combined efficacy of TGF-β blockade and anti-PD-1 therapy. The changes in immune cells were monitored by flow cytometry. The correlation between TGF-β and immunotherapy outcomes of EGFR-mutated NSCLC was verified by clinical samples. RESULTS We identified that TGF-β was upregulated in EGFR-mutated NSCLC by EGFR activation and subsequent ERK1/2-p90RSK phosphorylation. TGF-β directly inhibited CD8+ T cell infiltration, proliferation, and cytotoxicity both in vitro and in vivo, but blocking TGF-β did not suppress the growth of EGFR-mutated tumors in vivo. Anti-TGF-β antibody combined with anti-PD-1 antibody significantly inhibited the proliferation of recombinant EGFR-mutated tumors in C57BL/6N mice, which was superior to their monotherapy. Mechanistically, the combination of anti-TGF-β and anti-PD-1 antibodies significantly increased the infiltration of CD8+ T cells and enhanced the anti-tumor function of CD8+ T cells. Moreover, we found that the expression of TGF-β1 in EGFR-TKI resistant cell lines was significantly higher than that in parental cell lines. The combination of anti-TGF-β and nivolumab significantly inhibited the proliferation of EGFR-TKI resistant tumors in humanized M-NSG mice and prolonged their survival. CONCLUSIONS Our results reveal that TGF-β expression is upregulated in NSCLC with EGFR mutations through the EGFR-ERK1/2-p90RSK signaling pathway. High TGF-β expression inhibits the infiltration and anti-tumor function of CD8+ T cells, contributing to the "cold" TME of EGFR-mutated tumors. Blocking TGF-β can reshape the TME and enhance the therapeutic efficacy of anti-PD-1 in EGFR-mutated tumors, which provides a potential combination immunotherapy strategy for advanced NSCLC patients with EGFR mutations.
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Affiliation(s)
- Huayan Huang
- Department of Medical Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, West Huaihai Road 241, Shanghai, 200030, China
| | - Xiaokuan Zhu
- Department of Medical Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, West Huaihai Road 241, Shanghai, 200030, China
| | - Yongfeng Yu
- Department of Medical Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, West Huaihai Road 241, Shanghai, 200030, China
| | - Ziming Li
- Department of Medical Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, West Huaihai Road 241, Shanghai, 200030, China
| | - Yi Yang
- Department of Medical Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, West Huaihai Road 241, Shanghai, 200030, China
| | - Liliang Xia
- Department of Medical Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, West Huaihai Road 241, Shanghai, 200030, China.
| | - Shun Lu
- Department of Medical Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, West Huaihai Road 241, Shanghai, 200030, China.
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19
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Zhang S, Ta N, Zhang S, Li S, Zhu X, Kong L, Gong X, Guo M, Liu Y. Unraveling pancreatic ductal adenocarcinoma immune prognostic signature through a naive B cell gene set. Cancer Lett 2024; 594:216981. [PMID: 38795761 DOI: 10.1016/j.canlet.2024.216981] [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: 02/07/2024] [Revised: 05/14/2024] [Accepted: 05/17/2024] [Indexed: 05/28/2024]
Abstract
BACKGROUND Pancreatic ductal adenocarcinoma (PDAC), a leading cause of cancer mortality, has a complex pathogenesis involving various immune cells, including B cells and their subpopulations. Despite emerging research on the role of these cells within the tumor microenvironment (TME), the detailed molecular interactions with tumor-infiltrating immune cells (TIICs) are not fully understood. METHODS We applied CIBERSORT to quantify TIICs and naive B cells, which are prognostic for PDAC. Marker genes from scRNA-seq and modular genes from weighted gene co-expression network analysis (WGCNA) were integrated to identify naive B cell-related genes. A prognostic signature was constructed utilizing ten machine-learning algorithms, with validation in external cohorts. We further assessed the immune cell diversity, ESTIMATE scores, and immune checkpoint genes (ICGs) between patient groups stratified by risk to clarify the immune landscape in PDAC. RESULTS Our analysis identified 994 naive B cell-related genes across single-cell and bulk transcriptomes, with 247 linked to overall survival. We developed a 12-gene prognostic signature using Lasso and plsRcox algorithms, which was confirmed by 10-fold cross-validation and showed robust predictive power in training and real-world cohorts. Notably, we observed substantial differences in immune infiltration between patients with high and low risk. CONCLUSION Our study presents a robust prognostic signature that effectively maps the complex immune interactions in PDAC, emphasizing the critical function of naive B cells and suggesting new avenues for immunotherapeutic interventions. This signature has potential clinical applications in personalizing PDAC treatment, enhancing the understanding of immune dynamics, and guiding immunotherapy strategies.
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Affiliation(s)
- Shichen Zhang
- Software Engineering Institute, East China Normal University, Shanghai 200062, China
| | - Na Ta
- Department of Pathology, Changhai Hospital, Navy Medical University, Shanghai 200433, China
| | - Shihao Zhang
- National Key Laboratory of Immunity and Inflammation & Institute of Immunology, Navy Medical University, Shanghai 200433, China
| | - Senhao Li
- National Key Laboratory of Immunity and Inflammation & Institute of Immunology, Navy Medical University, Shanghai 200433, China
| | - Xinyu Zhu
- National Key Laboratory of Immunity and Inflammation & Institute of Immunology, Navy Medical University, Shanghai 200433, China
| | - Lingyun Kong
- National Key Laboratory of Immunity and Inflammation & Institute of Immunology, Navy Medical University, Shanghai 200433, China
| | - Xueqing Gong
- Software Engineering Institute, East China Normal University, Shanghai 200062, China.
| | - Meng Guo
- National Key Laboratory of Immunity and Inflammation & Institute of Immunology, Navy Medical University, Shanghai 200433, China.
| | - Yanfang Liu
- Department of Pathology, Changhai Hospital, Navy Medical University, Shanghai 200433, China; National Key Laboratory of Immunity and Inflammation & Institute of Immunology, Navy Medical University, Shanghai 200433, China.
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20
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Wei C, Wang W, Hu Z, Huang Z, Lu Y, Zhou W, Liu X, Jin X, Yin J, Li G. Predicting prognosis and immunotherapy response in colorectal cancer by pericytes insights from single-cell RNA sequencing. Hum Mol Genet 2024; 33:1215-1228. [PMID: 38652261 DOI: 10.1093/hmg/ddae064] [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: 01/12/2024] [Revised: 02/28/2024] [Accepted: 03/26/2024] [Indexed: 04/25/2024] Open
Abstract
Immunotherapy has revolutionized the treatment of tumors, but there are still a large number of patients who do not benefit from immunotherapy. Pericytes play an important role in remodeling the immune microenvironment. However, how pericytes affect the prognosis and treatment resistance of tumors is still unknown. This study jointly analyzed single-cell RNA sequencing (scRNA-seq) data and bulk RNA sequencing data of multiple cancers to reveal pericyte function in the colorectal cancer microenvironment. Analyzing over 800 000 cells, it was found that colorectal cancer had more pericyte enrichment in tumor tissues than other cancers. We then combined the TCGA database with multiple public datasets and enrolled more than 1000 samples, finding that pericyte may be closely related to poor prognosis due to the higher epithelial-mesenchymal transition (EMT) and hypoxic characteristics. At the same time, patients with more pericytes have higher immune checkpoint molecule expressions and lower immune cell infiltration. Finally, the contributions of pericyte in poor treatment response have been demonstrated in multiple immunotherapy datasets (n = 453). All of these observations suggest that pericyte can be used as a potential biomarker to predict patient disease progression and immunotherapy response.
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Affiliation(s)
- Chen Wei
- College of Life Sciences, University of Chinese Academy of Sciences, Yuquan Road, Shijingshan District, Beijing 100049, China
- BGI Research, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Weikai Wang
- College of Life Sciences, University of Chinese Academy of Sciences, Yuquan Road, Shijingshan District, Beijing 100049, China
- BGI Research, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Zhihao Hu
- College of Life Sciences, University of Chinese Academy of Sciences, Yuquan Road, Shijingshan District, Beijing 100049, China
- BGI Research, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Zhuoli Huang
- College of Life Sciences, University of Chinese Academy of Sciences, Yuquan Road, Shijingshan District, Beijing 100049, China
- BGI Research, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Ye Lu
- College of Life Sciences, University of Chinese Academy of Sciences, Yuquan Road, Shijingshan District, Beijing 100049, China
| | - Wenwen Zhou
- BGI Research, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Xiaoying Liu
- BGI Research, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Xin Jin
- College of Life Sciences, University of Chinese Academy of Sciences, Yuquan Road, Shijingshan District, Beijing 100049, China
- BGI Research, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Jianhua Yin
- BGI Research, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Guibo Li
- BGI Research, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
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Ge J, Tao M, Zhang G, Cai J, Li D, Tao L. New HCC Subtypes Based on CD8 Tex-Related lncRNA Signature Could Predict Prognosis, Immunological and Drug Sensitivity Characteristics of Hepatocellular Carcinoma. J Hepatocell Carcinoma 2024; 11:1331-1355. [PMID: 38983937 PMCID: PMC11232885 DOI: 10.2147/jhc.s459150] [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: 02/23/2024] [Accepted: 06/28/2024] [Indexed: 07/11/2024] Open
Abstract
Purpose Hepatocellular carcinoma has become one of the severe diseases threatening human health. T cell exhaustion is deemed as a reason for immunotherapy resistance. However, little is known about the roles of CD8 Tex-related lncRNAs in HCC. Materials and Methods We processed single-cell RNA sequencing to identify CD8 Tex-related genes. CD8 Tex-related lncRNAs were identified based on their correlations with mRNAs. Unsupervised clustering approach was used to identify molecular clusters of CD8 Tex-related lncRNAs. Differences in prognosis and immune infiltration between the clusters were explored. Machine learning algorithms were used to construct a prognostic signature. Samples were classified as low- and high-risk groups based on their risk scores. We identified prognosis-related lncRNAs and constructed a ceRNA network. In vitro experiments were conducted to investigate the impacts of CD8 Tex-related lncRNAs on proliferation and apoptosis of HCC cells. Results We clarified cell types within two HCC single-cell datasets. We identified specific markers of CD8 Tex cells and analyzed their potential functions. Twenty-eight lncRNAs were identified as CD8 Tex-related. Based on CD8 Tex-related lncRNAs, samples were categorized into two distinct clusters, which exhibited significant differences in survival rates and immune infiltration. Ninety-six algorithm combinations were employed to establish a prognostic signature. RSF emerged as the one with the highest C-index. Patients in high- and low-risk groups exhibited marked differences in prognosis, enriched pathways, mutations and drug sensitivities. MCM3AP-AS1, MAPKAPK5-AS1 and PART1 were regarded as prognosis-related lncRNAs. A ceRNA network was constructed based on CD8 Tex-related lncRNAs and mRNAs. Experiments on cell lines and organoids indicated that downregulation of MCM3AP-AS1, MAPKAPK5-AS1 and PART1 suppressed cell proliferation and induced apoptosis. Conclusion CD8 Tex-related lncRNAs played crucial roles in HCC progression. Our findings provided new insights into the regulatory mechanisms of CD8 Tex-related lncRNAs in HCC.
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Affiliation(s)
- Jiachen Ge
- Department of Hepatobiliary Surgery, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, People's Republic of China
| | - Ming Tao
- Department of General Surgery, Peking University Third Hospital, Beijing, People's Republic of China
| | - Gaolei Zhang
- Department of Hepatobiliary Surgery, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, People's Republic of China
| | - Jianping Cai
- Department of Hepatobiliary Surgery, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, People's Republic of China
| | - Deyu Li
- Department of Hepatobiliary Surgery, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, People's Republic of China
| | - Lianyuan Tao
- Department of Hepatobiliary Surgery, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, People's Republic of China
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22
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Pan S, Yin R, Zhu H, Shen S, Li Z, Liu B. Prostate cancer cancer-associated fibroblasts with stable markers post-androgen deprivation therapy associated with tumor progression and castration resistant prostate cancer. Cancer Sci 2024. [PMID: 38970292 DOI: 10.1111/cas.16267] [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: 03/28/2024] [Revised: 05/30/2024] [Accepted: 06/18/2024] [Indexed: 07/08/2024] Open
Abstract
The specificity and clinical relevance of cancer-associated fibroblasts (CAFs) in prostate cancer (PCa), as well as the effect of androgen deprivation therapy (ADT) on CAFs, remain to be fully elucidated. Using cell lineage diversity and weighted gene co-expression network analysis (WGCNA), we pinpointed a unique CAF signature exclusive to PCa. The specificity of this CAF signature was validated through single-cell RNA sequencing (scRNA-seq), cell line RNA sequencing, and immunohistochemistry. This signature associates CAFs with tumor progression, elevated Gleason scores, and the emergence of castration resistant prostate cancer (CRPC). Using scRNA-seq on collected samples, we demonstrated that the CAF-specific signature is not altered by ADT, maintaining its peak signal output. Identifying a PCa-specific CAF signature and observing signaling changes in CAFs after ADT lay essential groundwork for further PCa studies.
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Affiliation(s)
- Shen Pan
- Department of Nuclear Medicine, Shengjing Hospital of China Medical University, Shenyang, China
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Rui Yin
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Hehe Zhu
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Siang Shen
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Zhenhua Li
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Bitian Liu
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China
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23
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Görtler F, Mensching-Buhr M, Skaar Ø, Schrod S, Sterr T, Schäfer A, Beißbarth T, Joshi A, Zacharias HU, Grellscheid SN, Altenbuchinger M. Adaptive digital tissue deconvolution. Bioinformatics 2024; 40:i100-i109. [PMID: 38940181 PMCID: PMC11256946 DOI: 10.1093/bioinformatics/btae263] [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: 06/29/2024] Open
Abstract
MOTIVATION The inference of cellular compositions from bulk and spatial transcriptomics data increasingly complements data analyses. Multiple computational approaches were suggested and recently, machine learning techniques were developed to systematically improve estimates. Such approaches allow to infer additional, less abundant cell types. However, they rely on training data which do not capture the full biological diversity encountered in transcriptomics analyses; data can contain cellular contributions not seen in the training data and as such, analyses can be biased or blurred. Thus, computational approaches have to deal with unknown, hidden contributions. Moreover, most methods are based on cellular archetypes which serve as a reference; e.g. a generic T-cell profile is used to infer the proportion of T-cells. It is well known that cells adapt their molecular phenotype to the environment and that pre-specified cell archetypes can distort the inference of cellular compositions. RESULTS We propose Adaptive Digital Tissue Deconvolution (ADTD) to estimate cellular proportions of pre-selected cell types together with possibly unknown and hidden background contributions. Moreover, ADTD adapts prototypic reference profiles to the molecular environment of the cells, which further resolves cell-type specific gene regulation from bulk transcriptomics data. We verify this in simulation studies and demonstrate that ADTD improves existing approaches in estimating cellular compositions. In an application to bulk transcriptomics data from breast cancer patients, we demonstrate that ADTD provides insights into cell-type specific molecular differences between breast cancer subtypes. AVAILABILITY AND IMPLEMENTATION A python implementation of ADTD and a tutorial are available at Gitlab and zenodo (doi:10.5281/zenodo.7548362).
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Affiliation(s)
- Franziska Görtler
- Computational Biology Unit, Department of Biological Sciences, University of Bergen, N-5008 Bergen, Norway
- Department of Oncology and Medical Physics, Haukeland University Hospital, 5021 Bergen, Norway
| | - Malte Mensching-Buhr
- Department of Medical Bioinformatics, University Medical Center Göttingen, 37075 Göttingen, Germany
| | - Ørjan Skaar
- Department of Informatics, Computational Biology Unit, University of Bergen, N-5008 Bergen, Norway
| | - Stefan Schrod
- Department of Medical Bioinformatics, University Medical Center Göttingen, 37075 Göttingen, Germany
| | - Thomas Sterr
- Institute of Theoretical Physics, University of Regensburg, 93053 Regensburg, Germany
| | - Andreas Schäfer
- Institute of Theoretical Physics, University of Regensburg, 93053 Regensburg, Germany
| | - Tim Beißbarth
- Department of Medical Bioinformatics, University Medical Center Göttingen, 37075 Göttingen, Germany
| | - Anagha Joshi
- Department of Clinical Science, Computational Biology Unit, University of Bergen, N-5008 Bergen, Norway
| | - Helena U Zacharias
- Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Hannover Medical School, 30625 Hannover, Germany
| | | | - Michael Altenbuchinger
- Department of Medical Bioinformatics, University Medical Center Göttingen, 37075 Göttingen, Germany
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24
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Zhou M, Li T, Lv S, Gan W, Zhang F, Che Y, Yang L, Hou Y, Yan Z, Zeng Z, Zhao W, Yang M. Identification of immune-related genes and small-molecule drugs in hypertension-induced left ventricular hypertrophy based on machine learning algorithms and molecular docking. Front Immunol 2024; 15:1351945. [PMID: 38994368 PMCID: PMC11236603 DOI: 10.3389/fimmu.2024.1351945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 06/04/2024] [Indexed: 07/13/2024] Open
Abstract
Background Left ventricular hypertrophy (LVH) is a common consequence of hypertension and can lead to heart failure. The immune response plays an important role in hypertensive LVH; however, there is no comprehensive method to investigate the mechanistic relationships between immune response and hypertensive LVH or to find novel therapeutic targets. This study aimed to screen hub immune-related genes involved in hypertensive LVH as well as to explore immune target-based therapeutic drugs. Materials and methods RNA-sequencing data from a mouse model generated by angiotensin II infusion were subjected to weighted gene co-expression network analysis (WGCNA) to identify core expression modules. Machine learning algorithms were applied to screen immune-related LVH characteristic genes. Heart structures were evaluated by echocardiography and cardiac magnetic resonance imaging (CMRI). Validation of hub genes was conducted by RT-qPCR and western blot. Using the Connectivity Map database and molecular docking, potential small-molecule drugs were explored. Results A total of 1215 differentially expressed genes were obtained, most of which were significantly enriched in immunoregulation and collagen synthesis. WGCNA and multiple machine learning strategies uncovered six hub immune-related genes (Ankrd1, Birc5, Nuf2, C1qtnf6, Fcgr3, and Cdca3) that may accurately predict hypertensive LVH diagnosis. Immune analysis revealed that fibroblasts and macrophages were closely correlated with hypertensive LVH, and hub gene expression was significantly associated with these immune cells. A regulatory network of transcription factor-mRNA and a ceRNA network of miRNA-lncRNA was established. Notably, six hub immune-related genes were significantly increased in the hypertensive LVH model, which were positively linked to left ventricle wall thickness. Finally, 12 small-molecule compounds with the potential to reverse the high expression of hub genes were ruled out as potential therapeutic agents for hypertensive LVH. Conclusion This study identified and validated six hub immune-related genes that may play essential roles in hypertensive LVH, providing new insights into the potential pathogenesis of cardiac remodeling and novel targets for medical interventions.
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Affiliation(s)
- Mingxuan Zhou
- State Key Laboratory of Bioactive Substances and Function of Natural Medicine, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Tiegang Li
- State Key Laboratory of Bioactive Substances and Function of Natural Medicine, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Silin Lv
- State Key Laboratory of Bioactive Substances and Function of Natural Medicine, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wenqiang Gan
- State Key Laboratory of Bioactive Substances and Function of Natural Medicine, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fang Zhang
- State Key Laboratory of Bioactive Substances and Function of Natural Medicine, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yuexia Che
- State Key Laboratory of Bioactive Substances and Function of Natural Medicine, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- School of Pharmacy, Minzu University of China, Beijing, China
| | - Liu Yang
- State Key Laboratory of Bioactive Substances and Function of Natural Medicine, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yufang Hou
- State Key Laboratory of Bioactive Substances and Function of Natural Medicine, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zheng Yan
- State Key Laboratory of Bioactive Substances and Function of Natural Medicine, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zifan Zeng
- State Key Laboratory of Bioactive Substances and Function of Natural Medicine, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wenyi Zhao
- State Key Laboratory of Bioactive Substances and Function of Natural Medicine, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Min Yang
- State Key Laboratory of Bioactive Substances and Function of Natural Medicine, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Wang K, Yang C, Xie J, Zhang X, Wei T, Yan Z. Long non-coding RNAs in ferroptosis and cuproptosis impact on prognosis and treatment in hepatocellular carcinoma. Clin Exp Med 2024; 24:135. [PMID: 38907744 PMCID: PMC11193701 DOI: 10.1007/s10238-024-01397-x] [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: 04/18/2024] [Accepted: 06/08/2024] [Indexed: 06/24/2024]
Abstract
Ferroptosis and cuproptosis are recently discovered forms of cell death that have gained interest as potential cancer treatments, particularly for hepatocellular carcinoma. Long non-coding RNAs (lncRNAs) influence cancer cell activity by interacting with various nucleic acids and proteins. However, the role of ferroptosis and cuproptosis-related lncRNAs (FCRLs) in cancer remains underexplored. Ferroptosis and cuproptosis scores for each sample were assessed using Gene Set Variation Analysis (GSVA). Weighted correlation network analysis identified the FCRLs most relevant to our study. A risk model based on FCRLs was developed to categorize patients into high-risk and low-risk groups. We then compared overall survival (OS), tumor immune microenvironment, and clinical characteristics between these groups. The IPS score and ImmuCellAI webpage were used to predict the association between FCRL-related signatures and immunotherapy response. Finally, we validated the accuracy of FCRLs in hepatocellular carcinoma cell lines using induction agents (elesclomol and erastin). Patients in different risk subgroups showed significant differences in OS, immune cell infiltration, pathway activity, and clinical characteristics. Cellular assays revealed significant changes in the expression of AC019080.5, AC145207.5, MIR210HG, and LINC01063 in HCC cell lines following the addition of ferroptosis and cuproptosis inducers. We created a signature of four FCRLs that accurately predicted survival in HCC patients, laid the foundation for basic research related to ferroptosis and cuproptosis in hepatocellular carcinoma, and provided therapeutic recommendations for HCC patients.
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Affiliation(s)
- Kun Wang
- Department of Gastroenterology, The First People's Hospital of Lianyungang, Lianyungang, China
| | - Chunqian Yang
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Jingen Xie
- Department of General Medicine, Huai'an Cancer Hospital, Huai'an, China
| | - Xiao Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
| | - Ting Wei
- Department of Gastroenterology, The First People's Hospital of Lianyungang, Lianyungang, China.
| | - Zhu Yan
- Emergency Medicine Department, Huai'an Hospital Affiliated to Yangzhou University (The Fifth People's Hospital of Huai'an), Huaian, China.
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Kumar M, Leekha A, Nandy S, Kulkarni R, Martinez-Paniagua M, Rahman Sefat KMS, Willson RC, Varadarajan N. Enzymatic depletion of circulating glutamine is immunosuppressive in cancers. iScience 2024; 27:109817. [PMID: 38770139 PMCID: PMC11103382 DOI: 10.1016/j.isci.2024.109817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 03/13/2024] [Accepted: 04/24/2024] [Indexed: 05/22/2024] Open
Abstract
Although glutamine addiction in cancer cells is extensively reported, there is controversy on the impact of glutamine metabolism on the immune cells within the tumor microenvironment (TME). To address the role of extracellular glutamine, we enzymatically depleted circulating glutamine using PEGylated Helicobacter pylori gamma-glutamyl transferase (PEG-GGT) in syngeneic mouse models of breast and colon cancers. PEG-GGT treatment inhibits growth of cancer cells in vitro, but in vivo it increases myeloid-derived suppressor cells (MDSCs) and has no significant impact on tumor growth. By deriving a glutamine depletion signature, we analyze diverse human cancers within the TCGA and illustrate that glutamine depletion is not associated with favorable clinical outcomes and correlates with accumulation of MDSC. Broadly, our results help clarify the integrated impact of glutamine depletion within the TME and advance PEG-GGT as an enzymatic tool for the systemic and selective depletion (no asparaginase activity) of circulating glutamine in live animals.
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Affiliation(s)
- Monish Kumar
- William A. Brookshire Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX 77204, USA
| | - Ankita Leekha
- William A. Brookshire Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX 77204, USA
| | - Suman Nandy
- William A. Brookshire Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX 77204, USA
| | - Rohan Kulkarni
- William A. Brookshire Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX 77204, USA
| | - Melisa Martinez-Paniagua
- William A. Brookshire Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX 77204, USA
| | - K. M. Samiur Rahman Sefat
- William A. Brookshire Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX 77204, USA
| | - Richard C. Willson
- William A. Brookshire Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX 77204, USA
| | - Navin Varadarajan
- William A. Brookshire Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX 77204, USA
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27
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Liu Y, Jiang W, Huang J, Zhong L. Bioinformatic analysis combined with immune infiltration to explore osteoarthritis biomarkers and drug prediction. Medicine (Baltimore) 2024; 103:e38430. [PMID: 38905428 PMCID: PMC11191918 DOI: 10.1097/md.0000000000038430] [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: 04/17/2024] [Accepted: 05/10/2024] [Indexed: 06/23/2024] Open
Abstract
Along with global aging, osteoarthritis (OA) appears to have a high incidence and disability rate, which seriously affects the quality of life of patients, making age a major risk factor. However, the pathology of OA is under-researched, and there is no obvious and effective treatment. Research has demonstrated the importance of aging, inflammation, and immunology in the onset and course of OA. This study aims to anticipate therapeutic drugs based on critical genes associated with OA and to elucidate the roles of genes and possible biomarkers associated with inflammation, immunology, and cellular senescence in OA. The OA gene expression matrix was first obtained from the Gene Expression Omnibus database. Screening for OA significant differentially expressed genes by bioinformatics identification. Specific biological processes and related signaling pathways of the differential genes were enriched. Then elucidate the status of immune cell involvement in OA based on immune infiltration analysis. Finally predict therapeutic agents based on pivotal genes. A total of 198 differentially expressed genes were identified in OA, and TP53, EGFR, TGFB1, LEP, CD4, MAPK8, SCARB1, ADIPOQ, JAK2, and SERPINE1 were further identified as important hub genes. The enrichment results showed that the development of arthritis was mainly related to immune cell differentiation, amino acid metabolism and cellular senescence process. The validation of immune infiltration results indicated that NK_cells, CD4_Tcells, Macrophages, Monocytic_lineage, Dendritic_cells, Basophils, CD8+_naive_T-cells may play an important role in the immune process of OA. Key Drug Prediction of Hub Genes found that Halicin, Ruxolitinib, Tofacitinib, Clenoliximab, Baricitinib may be a key drug or component in the treatment of OA.
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Affiliation(s)
- Yan Liu
- Gerontology Medicine Department, The Affiliated Hospital of Southwest Medical University, Southwest Medical University, Luzhou, China
| | - Wei Jiang
- Rehabilitation Medicine Department, The Affiliated Hospital of Southwest Medical University, Southwest Medical University, Luzhou, China
| | - Juan Huang
- Rehabilitation Medicine Department, The Affiliated Hospital of Southwest Medical University, Southwest Medical University, Luzhou, China
| | - Li Zhong
- Gerontology Medicine Department, The Affiliated Hospital of Southwest Medical University, Southwest Medical University, Luzhou, China
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28
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Van Arsdale A, Turker L, Chang YC, Gould J, Harmon B, Maggi EC, Meshcheryakova O, Brown MP, Luong D, Van Doorslaer K, Einstein MH, Kuo DYS, Zheng D, Haas BJ, Lenz J, Montagna C. Structure and transcription of integrated HPV DNA in vulvar carcinomas. NPJ Genom Med 2024; 9:35. [PMID: 38898085 PMCID: PMC11187145 DOI: 10.1038/s41525-024-00418-8] [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: 08/11/2023] [Accepted: 05/02/2024] [Indexed: 06/21/2024] Open
Abstract
HPV infections are associated with a fraction of vulvar cancers. Through hybridization capture and DNA sequencing, HPV DNA was detected in five of thirteen vulvar cancers. HPV16 DNA was integrated into human DNA in three of the five. The insertions were in introns of human NCKAP1, C5orf67, and LRP1B. Integrations in NCKAP1 and C5orf67 were flanked by short direct repeats in the human DNA, consistent with HPV DNA insertions at sites of abortive, staggered, endonucleolytic incisions. The insertion in C5orf67 was present as a 36 kbp, human-HPV-hetero-catemeric DNA as either an extrachromosomal circle or a tandem repeat within the human genome. The human circularization/repeat junction was defined at single nucleotide resolution. The integrated viral DNA segments all retained an intact upstream regulatory region and the adjacent viral E6 and E7 oncogenes. RNA sequencing revealed that the only HPV genes consistently transcribed from the integrated viral DNAs were E7 and E6*I. The other two HPV DNA+ tumors had coinfections, but no evidence for integration. HPV-positive and HPV-negative vulvar cancers exhibited contrasting human, global gene expression patterns partially overlapping with previously observed differences between HPV-positive and HPV-negative cervical and oropharyngeal cancers. A substantial fraction of the differentially expressed genes involved immune system function. Thus, transcription and HPV DNA integration in vulvar cancers resemble those in other HPV-positive cancers. This study emphasizes the power of hybridization capture coupled with DNA and RNA sequencing to identify a broad spectrum of HPV types, determine human genome integration status of viral DNAs, and elucidate their structures.
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Affiliation(s)
- Anne Van Arsdale
- Department of Obstetrics Gynecology and Women's Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Lauren Turker
- Department of Obstetrics Gynecology and Women's Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
- Lankenau Medical Center, Wynnewood, PA, 19096, USA
| | - Yoke-Chen Chang
- Rutgers Cancer Institute of New Jersey, 195 Little Albany St., New Brunswick, NJ, 08901, USA
| | - Joshua Gould
- Broad Institute, Cambridge, MA, 02142, USA
- Cellarity, Cambridge, MA, 02140, USA
| | - Bryan Harmon
- Department of Pathology, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Elaine C Maggi
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
- Twist Biosciences, South San Francisco, CA, 94080, USA
| | - Olga Meshcheryakova
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Maxwell P Brown
- Broad Institute, Cambridge, MA, 02142, USA
- Verve Therapeutics, Boston, MA, 02215, USA
| | - Dana Luong
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Koenraad Van Doorslaer
- School of Animal and Comparative Biomedical Sciences, College of Agriculture and Life Sciences BIO5 Institute, University of Arizona, Tucson, AZ, 85721, USA
| | - Mark H Einstein
- Department of Obstetrics, Gynecology, and Women's Health, Rutgers New Jersey Medical School, Newark, NJ, 07102, USA
| | - Dennis Y S Kuo
- Department of Obstetrics Gynecology and Women's Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Deyou Zheng
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | | | - Jack Lenz
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Cristina Montagna
- Department of Obstetrics Gynecology and Women's Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA.
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA.
- Rutgers Cancer Institute of New Jersey, 195 Little Albany St., New Brunswick, NJ, 08901, USA.
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29
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Jin YW, Hu P, Liu Q. NNICE: a deep quantile neural network algorithm for expression deconvolution. Sci Rep 2024; 14:14040. [PMID: 38890415 PMCID: PMC11189483 DOI: 10.1038/s41598-024-65053-w] [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: 01/06/2024] [Accepted: 06/17/2024] [Indexed: 06/20/2024] Open
Abstract
The composition of cell-type is a key indicator of health. Advancements in bulk gene expression data curation, single cell RNA-sequencing technologies, and computational deconvolution approaches offer a new perspective to learn about the composition of different cell types in a quick and affordable way. In this study, we developed a quantile regression and deep learning-based method called Neural Network Immune Contexture Estimator (NNICE) to estimate the cell type abundance and its uncertainty by automatically deconvolving bulk RNA-seq data. The proposed NNICE model was able to successfully recover ground-truth cell type fraction values given unseen bulk mixture gene expression profiles from the same dataset it was trained on. Compared with baseline methods, NNICE achieved better performance on deconvolve both pseudo-bulk gene expressions (Pearson correlation R = 0.9) and real bulk gene expression data (Pearson correlation R = 0.9) across all cell types. In conclusion, NNICE combines statistic inference with deep learning to provide accurate and interpretable cell type deconvolution from bulk gene expression.
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Affiliation(s)
- Yong Won Jin
- Department of Biochemistry & Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, R3E 0J9, Canada
| | - Pingzhao Hu
- Department of Biochemistry & Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, R3E 0J9, Canada
- Department of Biochemistry, Schulich School of Medicine & Dentistry, Western University, London, ON, N6A 5C1, Canada
| | - Qian Liu
- Department of Applied Computer Science, University of Winnipeg, Winnipeg, MB, R3B 2E9, Canada.
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Horwitz SM, Nirmal AJ, Rahman J, Xu R, Drill E, Galasso N, Ganesan N, Davey T, Hancock H, Perez L, Maccaro C, Bahgat A, Marzouk E, Cathcart E, Moskowitz A, Noy A, Kumar A, Jacobsen E, Fisher DC, Mehta-Shah N, Kim YH, Khodadoust M, Kotlov N, Nikitina A, Kudryashova O, Zubareva V, Zornikova K, Shin N, Sorokina M, Degryse S, Postovalova E, Bagaev A, Hosszu K, McAvoy D, Boelens JJ, Wu W, Ciantra Z, Appelt JW, Trevisani C, Amaka S, Weinstock DM, Vardhana SA. Duvelisib plus romidepsin in relapsed/refractory T cell lymphomas: a phase 1b/2a trial. Nat Med 2024:10.1038/s41591-024-03076-6. [PMID: 38886623 DOI: 10.1038/s41591-024-03076-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Accepted: 05/17/2024] [Indexed: 06/20/2024]
Abstract
PI3K-δ inhibitors have shown impressive activity in lymphoid malignancies but have been hampered by autoimmune and infectious toxicities, leading to market withdrawals. We previously demonstrated activity of the PI3K-δγ inhibitor duvelisib in T cell lymphomas (TCLs) that was associated with inflammatory adverse events. As reported here, we conducted a phase 1b/2a study of duvelisib in combination with either romidepsin (n = 66) or bortezomib (n = 32) in patients with relapsed/refractory TCL and found that the addition of romidepsin, but not bortezomib, appeared to increase efficacy while attenuating PI3K inhibitor-driven toxicity. The primary endpoint of the study was to determine the safety and maximum tolerated dose of duvelisib, which was 75 mg twice daily when combined with romidepsin versus 25 mg twice daily when combined with bortezomib. The most common adverse events were neutropenia (42%, 25/59) and fatigue (37%, 22/59) in patients treated with duvelisib and romidepsin and diarrhea (48%, 11/23) and neutropenia (30%, 7/23) in patients treated with duvelisib and bortezomib. Duvelisib and romidepsin resulted in less grade 3/4 hepatotoxicity (14%, 8/59) compared to 40% (14/35) in our previous study with duvelisib monotherapy. This was associated with reductions in circulating inflammatory mediators and myeloid cell inflammatory gene expression. Secondary endpoints of overall and complete response rates were 55% (35/64) and 34% (22/64) for patients treated with duvelisib and romidepsin and 34% (11/32) and 13% (4/32) for patients treated with duvelisib and bortezomib. Among patients with peripheral T cell lymphomas (PTCLs), overall and complete response rates of duvelisib and romidepsin were 56% (27/48) and 44% (21/48), respectively, with exploratory analyses showing increased response rates in patients with a follicular helper T cell subtype. These findings support further development of combined PI3K and histone deacetylase (HDAC) inhibition in TCLs and suggest a unique strategy to enable PI3K inhibitor-based combinations for additional patient populations. ClinicalTrials.gov identifier: NCT02783625 .
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Affiliation(s)
- Steven M Horwitz
- Lymphoma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- New York Presbyterian Hospital-Weill Cornell Medical College, New York, NY, USA.
| | - Ajit J Nirmal
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Jahan Rahman
- Department of Biostatistics and Epidemiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ran Xu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Esther Drill
- Department of Biostatistics and Epidemiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Natasha Galasso
- Lymphoma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Nivetha Ganesan
- Lymphoma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Theresa Davey
- Lymphoma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Helen Hancock
- Lymphoma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Leslie Perez
- Lymphoma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Catherine Maccaro
- Lymphoma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Alexandra Bahgat
- Lymphoma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Evan Marzouk
- Lymphoma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Elizabeth Cathcart
- Lymphoma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Alison Moskowitz
- Lymphoma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ariela Noy
- Lymphoma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Anita Kumar
- Lymphoma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Eric Jacobsen
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - David C Fisher
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Neha Mehta-Shah
- Department of Medicine, Division of Oncology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Youn H Kim
- Division of Oncology, Stanford University, Stanford, CA, USA
- Department of Dermatology, Stanford University, Stanford, CA, USA
| | - Michael Khodadoust
- Division of Oncology, Stanford University, Stanford, CA, USA
- Department of Dermatology, Stanford University, Stanford, CA, USA
| | | | | | | | | | | | - Nara Shin
- BostonGene Corporation, Boston, MA, USA
| | | | | | | | | | - Kinga Hosszu
- Department of Pediatrics and Immune Discovery & Modeling Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Devin McAvoy
- Department of Pediatrics and Immune Discovery & Modeling Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jaap J Boelens
- Department of Pediatrics and Immune Discovery & Modeling Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Stem Cell Transplantation and Cellular Therapies, MSK Kids, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Wenchao Wu
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Zoe Ciantra
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Jackson W Appelt
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | | | - Sam Amaka
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - David M Weinstock
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Merck and Co., Rahway, NJ, USA
| | - Santosha A Vardhana
- Lymphoma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- New York Presbyterian Hospital-Weill Cornell Medical College, New York, NY, USA.
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
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31
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Ur Rehman A, Wang Z, Qin Q, Zhang X, Akhtar A, Liu H, Mao B, Khan N, Tang L, Li X. Enhancing antitumor immunity and achieving tumor eradication with IL11RA mRNA immunotherapy. Int Immunopharmacol 2024; 134:112205. [PMID: 38718659 DOI: 10.1016/j.intimp.2024.112205] [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: 02/15/2024] [Revised: 04/30/2024] [Accepted: 05/02/2024] [Indexed: 06/03/2024]
Abstract
Current methods for delivering genes to target tumors face significant challenges, including off-target effects and immune responses against delivery vectors. In this study, we developed a novel approach using messenger RNA (mRNA) to encode IL11RA for local immunotherapy, aiming to harness the immune system to combat tumors. Our research uncovered a compelling correlation between IL11RA expression and CD8 + T cell levels across multiple tumor types, with elevated IL11RA expression correlating with improved overall survival. Examination of the Pan-Cancer Atlas dataset showed a significant reduction in IL11RA expression in various cancer types compared to normal tissue, raising questions about its potential role in tumorigenesis. To achieve efficient in vivo expression of IL11RA, we synthesized two mRNA sequences mimicking the wild-type protein. These mRNA sequences were formulated and capped to ensure effective delivery, resulting in robust expression within tumor sites. Our investigation into IL11RA mRNA therapy demonstrated its effectiveness in controlling tumor growth when administered both intratumorally and intravenously in mouse models. Additionally, IL11RA mRNA treatment significantly stimulated the expansion of CD8 + T cells within tumors, draining lymph nodes, and the spleen. Transcriptome analysis revealed distinct transcriptional patterns associated with T cell functions. Using multiple deconvolution algorithms, we found substantial infiltration of CD8 + T cells following IL11RA mRNA treatment, highlighting its immunomodulatory effects within the tumor microenvironment. In conclusion, IL11RA mRNA therapy presents a promising strategy for tumor regression with potential immunomodulatory effects and clinical implications for improved survival outcomes.
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Affiliation(s)
- Adeel Ur Rehman
- Clinical Molecular Medicine Testing Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; Key Laboratory of Major Brain Disease and Aging Research (Ministry of Education), Institute for Brain Science and Disease, Chongqing Medical University, Chongqing 400016, China.
| | - Zhihuai Wang
- Department of General Surgery, Changzhou No.2 People's Hospital Affiliated with Nanjing Medical University, Changzhou, Jiangsu, 213000, China
| | - Qianshan Qin
- Suzhou Abogen Biosciences Co., Ltd., Suzhou, Jiangsu, 215123, China
| | - Xiaojing Zhang
- Suzhou Abogen Biosciences Co., Ltd., Suzhou, Jiangsu, 215123, China
| | - Aleena Akhtar
- Clinical Molecular Medicine Testing Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Hanyang Liu
- Charité‑University Medical Center, Department of Hematology, Oncology and Tumor Immunology, Virchow Campus, and Molecular Cancer Research Center, D‑13353 Berlin, Germany
| | - Binli Mao
- Clinical Molecular Medicine Testing Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Naveed Khan
- Graduate School of Green-Bio Science, Kyung Hee University, Yongin 17104, Korea
| | - Liming Tang
- Department of General Surgery, Changzhou No.2 People's Hospital Affiliated with Nanjing Medical University, Changzhou, Jiangsu, 213000, China
| | - Xiaosong Li
- Clinical Molecular Medicine Testing Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China; Key Laboratory of Major Brain Disease and Aging Research (Ministry of Education), Institute for Brain Science and Disease, Chongqing Medical University, Chongqing 400016, China.
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32
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Huang XW, Li Y, Jiang LN, Zhao BK, Liu YS, Chen C, Zhao D, Zhang XL, Li ML, Jiang YY, Liu SH, Zhu L, Zhao JM. Comprehensive pan-cancer investigation of carnosine dipeptidase 1 and its prospective prognostic significance in hepatocellular carcinoma. Open Med (Wars) 2024; 19:20240982. [PMID: 38883336 PMCID: PMC11179385 DOI: 10.1515/med-2024-0982] [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: 04/15/2024] [Revised: 05/18/2024] [Accepted: 05/21/2024] [Indexed: 06/18/2024] Open
Abstract
Carnosine dipeptidase 1 (CNDP1), an enzyme integral to the hydrolysis of dipeptides containing histidine, plays an indispensable role in myriad physiological processes, including hydrolysis of proteins, maturation of specific biochemical functionalities within proteins, tissue regeneration, and regulation of cell cycle. However, the implications of CNDP1 in oncogenesis and its prognostic value are not yet fully elucidated. Initially, we procured the GSE40367 dataset from the Gene Expression Omnibus and established a protein-protein interaction network. Thereafter, we conducted functional and pathway enrichment analyses utilizing GO, KEGG, and GSEA. Moreover, we undertook an association analysis concerning the expression of CNDP1 with immune infiltration, along with survival analysis across various cancers and specifically in hepatocellular carcinoma (HCC). Our study uncovered a total of 2,248 differentially expressed genes, with a down-regulation of CNDP1 in HCC and other cancers. Our explorations into the relationship between CNDP1 and immune infiltration disclosed a negative correlation between CNDP1 expression and the presence of immune cells in HCC. Survival analyses revealed that diminished expression of CNDP1 correlates with an adverse prognosis in HCC and several other types of cancer. These observations intimate that CNDP1 holds promise as a novel prognostic biomarker for both pan-cancer and HCC.
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Affiliation(s)
- Xiao-Wen Huang
- Medical School of Chinese PLA, Beijing, China
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100039, China
| | - Yan Li
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100039, China
| | - Li-Na Jiang
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100039, China
| | - Bo-Kang Zhao
- Department of Hepatology, Center of Infectious Diseases and Pathogen Biology, The First Hospital of Jilin University, Changchun, China
| | - Yi-Si Liu
- First Department of Liver Disease Center, Beijing Youan Hospital, Capital Medical University, Beijing, China
| | - Chun Chen
- Senior Department of Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Dan Zhao
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100039, China
| | - Xue-Li Zhang
- Medical School of Chinese PLA, Beijing, China
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100039, China
| | - Mei-Ling Li
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100039, China
| | - Yi-Yun Jiang
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100039, China
| | - Shu-Hong Liu
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100039, China
| | - Li Zhu
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100039, China
| | - Jing-Min Zhao
- Medical School of Chinese PLA, Beijing, China
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100039, China
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Zhao N, Wang J, Huang S, Zhang J, Bao J, Ni H, Gao X, Zhang C. The landscape of programmed cell death-related lncRNAs in Alzheimer's disease and Parkinson's disease. Apoptosis 2024:10.1007/s10495-024-01984-z. [PMID: 38853201 DOI: 10.1007/s10495-024-01984-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/23/2024] [Indexed: 06/11/2024]
Abstract
This study delivers a thorough analysis of long non-coding RNAs (lncRNAs) in regulating programmed cell death (PCD), vital for neurodegenerative diseases like Alzheimer's disease (AD) and Parkinson's disease (PD). We propose a new framework PCDLnc, and identified 20 significant lncRNAs, including HEIH, SNHG15, and SNHG5, associated with PCD gene sets, which were known for roles in proliferation and apoptosis in neurodegenerative diseases. By using GREAT software, we identified regulatory functions of top lncRNAs in different neurodegenerative diseases. Moreover, lncRNAs cis-regulated mRNAs linked to neurodegeneration, including JAK2, AKT1, EGFR, CDC42, SNCA, and ADIPOQ, highlighting their therapeutic potential in neurodegenerative diseases. A further exploration into the differential expression of mRNA identified by PCDLnc revealed a role in apoptosis, ferroptosis and autophagy. Additionally, protein-protein interaction (PPI) network analysis exposed abnormal interactions among key genes, despite their consistent expression levels between disease and normal samples. The randomforest model effectively distinguished between disease samples, indicating a high level of accuracy. Shared gene subsets in AD and PD might serve as potential biomarkers, along with disease-specific gene sets. Besides, we also found the strong relationship between AD and immune infiltration. This research highlights the role of lncRNAs and their associated genes in PCD in neurodegenerative diseases, offering potential therapeutic targets and diagnostic markers for future study and clinical application.
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Affiliation(s)
- Ning Zhao
- College of Computer and Control Engineering, Northeast Forestry University, Harbin, Heilongjiang, China
| | - Junyi Wang
- College of Computer and Control Engineering, Northeast Forestry University, Harbin, Heilongjiang, China
| | - Shan Huang
- The Second Affiliated Hospital, Harbin Medical University, Harbin, Heilongjiang, China
| | - Jingyu Zhang
- The Fourth Affiliated Hospital, Harbin Medical University, Harbin, Heilongjiang, China
| | - Jin Bao
- College of Computer and Control Engineering, Northeast Forestry University, Harbin, Heilongjiang, China
| | - Haisen Ni
- College of Computer and Control Engineering, Northeast Forestry University, Harbin, Heilongjiang, China
| | - Xinhang Gao
- College of Computer and Control Engineering, Northeast Forestry University, Harbin, Heilongjiang, China
| | - Chunlong Zhang
- College of Computer and Control Engineering, Northeast Forestry University, Harbin, Heilongjiang, China.
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34
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Yang Q, Li X, Zhu W. Identification of a unique stress response state of T cells-related gene signature in patients with gastric cancer. Aging (Albany NY) 2024; 16:9709-9726. [PMID: 38848147 PMCID: PMC11210248 DOI: 10.18632/aging.205895] [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: 11/09/2023] [Accepted: 04/25/2024] [Indexed: 06/09/2024]
Abstract
Gastric cancer (GC), the third most lethal cancer worldwide, is often diagnosed at an advanced stage, leaving limited therapeutic options. Given the diverse outcomes among GC patients with similar AJCC/UICC-TNM characteristics, there is a pressing need for more reliable prognostic tools. Recent advances in targeted therapy and immunotherapy have underscored this necessity. In this context, our study focused on a novel stress response state of T cells, termed TSTR, identified across multiple cancers, which is associated with resistance to immunotherapy. We aimed to develop a predictive gene signature for the TSTR phenotype within the tumor microenvironment (TME) of GC patients. By categorizing GC patients into high and low TSTR groups based on the infiltration states of TME TSTR cells, we observed significant differences in clinical prognosis and characteristics between the groups. Through a multi-step bioinformatics approach, we established an eight-gene signature based on genes differentially expressed between these groups. We conducted functional validations for the signature gene PDGFRL in GC cells. This gene signature effectively stratifies GC patients into high and low-risk categories, demonstrating robustness in predicting clinical outcomes. Furthermore, these risk groups exhibited distinct immune profiles, somatic mutations, and drug susceptibilities, highlighting the potential of our gene signature to enhance personalized treatment strategies in clinical practice.
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Affiliation(s)
- Qin Yang
- Puai Medical College, Shaoyang University, The First Affiliated Hospital of Shaoyang University, Shaoyang, Hunan, China
| | - Xin Li
- Department of Immunology, School of Basic Medicine, Central South University, Changsha, Hunan, China
| | - Weiyuan Zhu
- Puai Medical College, Shaoyang University, The First Affiliated Hospital of Shaoyang University, Shaoyang, Hunan, China
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Luo L, Jiang M, Wu H, Liu Y, Wang H, Zhou C, Ren S, Chen X, Jiang T, Xu C. SIRPG expression positively associates with an inflamed tumor microenvironment and response to PD-1 blockade. Cancer Immunol Immunother 2024; 73:147. [PMID: 38833156 PMCID: PMC11150346 DOI: 10.1007/s00262-024-03737-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: 03/21/2024] [Accepted: 05/15/2024] [Indexed: 06/06/2024]
Abstract
BACKGROUND This study aimed to investigate the relationship between signal regulatory protein gamma (SIRPG) and tumor immune microenvironment phenotypes or T cell mediated-adaptive antitumor immunity, and its predictive value for response to PD-1 blockade in cancers. METHODS Pan-cancer analysis of SIRPG expression and immune deconvolution was performed using transcriptomic data across 33 tumor types. Transcriptomic and clinical data from 157 patients with non-small-cell lung cancer (NSCLC) and melanoma received PD-1 blockade were analyzed. Expression characteristics of SIRPG were investigated using single-cell RNA sequencing (scRNA-seq) data of 103,599 cells. The effect of SIRPG expression was evaluated via SIRPG knockdown or overexpression in Jurkat T cells. RESULTS The results showed that most cancers with high SIRPG expression had significantly higher abundance of T cells, B cells, NK cells, M1 macrophages and cytotoxic lymphocytes and increased expression level of immunomodulatory factors regulating immune cell recruitment, antigen presentation, T cell activation and cytotoxicity, but markedly lower abundance of neutrophils, M2 macrophages, and myeloid-derived suppressor cells. High SIRPG expression was associated with favorable response to PD-1 blockade in both NSCLC and melanoma. scRNA-seq data suggested SIRPG was mainly expressed in CD8+ exhausted T and CD4+ regulatory T cells, and positively associated with immune checkpoint expression including PDCD1 and CTLA4. In vitro test showed SIRPG expression in T cells could facilitate expression of PDCD1 and CTLA4. CONCLUSION High SIRPG expression is associated with an inflamed immune phenotype in cancers and favorable response to PD-1 blockade, suggesting it would be a promising predictive biomarker for PD-1 blockade and novel immunotherapeutic target.
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Affiliation(s)
- Libo Luo
- Department of Medical Oncology, Shanghai Pulmonary Hospital and Thoracic Cancer Institute, Tongji University School of Medicine, No. 507 Zhengmin Road, Shanghai, 200433, China
| | - Minlin Jiang
- Department of Medical Oncology, Shanghai Pulmonary Hospital and Thoracic Cancer Institute, Tongji University School of Medicine, No. 507 Zhengmin Road, Shanghai, 200433, China
| | - Hong Wu
- Department of Oncology and Cancer Institute, Department of Laboratory Medicine and Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, No. 32 1st Ring Road, Chengdu, 610072, China
| | - Yiqiang Liu
- Department of Oncology and Cancer Institute, Department of Laboratory Medicine and Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, No. 32 1st Ring Road, Chengdu, 610072, China
| | - Haowei Wang
- Department of Medical Oncology, Shanghai Pulmonary Hospital and Thoracic Cancer Institute, Tongji University School of Medicine, No. 507 Zhengmin Road, Shanghai, 200433, China
| | - Caicun Zhou
- Department of Medical Oncology, Shanghai Pulmonary Hospital and Thoracic Cancer Institute, Tongji University School of Medicine, No. 507 Zhengmin Road, Shanghai, 200433, China
| | - Shengxiang Ren
- Department of Medical Oncology, Shanghai Pulmonary Hospital and Thoracic Cancer Institute, Tongji University School of Medicine, No. 507 Zhengmin Road, Shanghai, 200433, China
| | - Xiaoxia Chen
- Department of Medical Oncology, Shanghai Pulmonary Hospital and Thoracic Cancer Institute, Tongji University School of Medicine, No. 507 Zhengmin Road, Shanghai, 200433, China.
| | - Tao Jiang
- Department of Medical Oncology, Shanghai Pulmonary Hospital and Thoracic Cancer Institute, Tongji University School of Medicine, No. 507 Zhengmin Road, Shanghai, 200433, China.
| | - Chuan Xu
- Department of Oncology and Cancer Institute, Department of Laboratory Medicine and Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, No. 32 1st Ring Road, Chengdu, 610072, China.
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Wu R, Horimoto Y, Oshi M, Benesch MGK, Khoury T, Takabe K, Ishikawa T. Emerging measurements for tumor-infiltrating lymphocytes in breast cancer. Jpn J Clin Oncol 2024; 54:620-629. [PMID: 38521965 PMCID: PMC11144297 DOI: 10.1093/jjco/hyae033] [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: 12/18/2023] [Accepted: 03/01/2024] [Indexed: 03/25/2024] Open
Abstract
Tumor-infiltrating lymphocytes are a general term for lymphocytes or immune cells infiltrating the tumor microenvironment. Numerous studies have demonstrated tumor-infiltrating lymphocytes to be robust prognostic and predictive biomarkers in breast cancer. Recently, immune checkpoint inhibitors, which directly target tumor-infiltrating lymphocytes, have become part of standard of care treatment for triple-negative breast cancer. Surprisingly, tumor-infiltrating lymphocytes quantified by conventional methods do not predict response to immune checkpoint inhibitors, which highlights the heterogeneity of tumor-infiltrating lymphocytes and the complexity of the immune network in the tumor microenvironment. Tumor-infiltrating lymphocytes are composed of diverse immune cell populations, including cytotoxic CD8-positive T lymphocytes, B cells and myeloid cells. Traditionally, tumor-infiltrating lymphocytes in tumor stroma have been evaluated by histology. However, the standardization of this approach is limited, necessitating the use of various novel technologies to elucidate the heterogeneity in the tumor microenvironment. This review outlines the evaluation methods for tumor-infiltrating lymphocytes from conventional pathological approaches that evaluate intratumoral and stromal tumor-infiltrating lymphocytes such as immunohistochemistry, to the more recent advancements in computer tissue imaging using artificial intelligence, flow cytometry sorting and multi-omics analyses using high-throughput assays to estimate tumor-infiltrating lymphocytes from bulk tumor using immune signatures or deconvolution tools. We also discuss higher resolution technologies that enable the analysis of tumor-infiltrating lymphocytes heterogeneity such as single-cell analysis and spatial transcriptomics. As we approach the era of personalized medicine, it is important for clinicians to understand these technologies.
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Affiliation(s)
- Rongrong Wu
- Department of Breast Surgery and Oncology, Tokyo Medical University, Tokyo, Japan
- Department of Surgical Oncology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Yoshiya Horimoto
- Department of Breast Surgery and Oncology, Tokyo Medical University, Tokyo, Japan
- Department of Breast Oncology, Juntendo University Hospital, Tokyo, Japan
| | - Masanori Oshi
- Department of Surgical Oncology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
- Department of Gastroenterological Surgery, Yokohama City University Graduate School of Medicine, Yokohama, Japan
| | - Matthew G K Benesch
- Department of Surgical Oncology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Thaer Khoury
- Department of Pathology & Laboratory Medicine, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Kazuaki Takabe
- Department of Breast Surgery and Oncology, Tokyo Medical University, Tokyo, Japan
- Department of Surgical Oncology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
- Department of Gastroenterological Surgery, Yokohama City University Graduate School of Medicine, Yokohama, Japan
- Department of Surgery, University at Buffalo Jacobs School of Medicine and Biomedical Sciences, The State University of New York, Buffalo, NY, USA
- Department of Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
- Department of Breast Surgery, Fukushima Medical University, Fukushima, Japan
| | - Takashi Ishikawa
- Department of Breast Surgery and Oncology, Tokyo Medical University, Tokyo, Japan
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Lian P, Cai X, Yang X, Ma Z, Wang C, Liu K, Wu Y, Cao X, Xu Y. Analysis and experimental validation of necroptosis-related molecular classification, immune signature and feature genes in Alzheimer's disease. Apoptosis 2024; 29:726-742. [PMID: 38478169 PMCID: PMC11055779 DOI: 10.1007/s10495-024-01943-8] [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] [Accepted: 02/04/2024] [Indexed: 04/28/2024]
Abstract
Necroptosis, a programmed cell death pathway, has been demonstrated to be activated in Alzheimer's disease (AD). However, the precise role of necroptosis and its correlation with immune cell infiltration in AD remains unclear. In this study, we conducted non-negative matrix factorization clustering analysis to identify three subtypes of AD based on necroptosis-relevant genes. Notably, these subtypes exhibited varying necroptosis scores, clinical characteristics and immune infiltration signatures. Cluster B, characterized by high necroptosis scores, showed higher immune cell infiltration and was associated with a more severe pathology, potentially representing a high-risk subgroup. To identify potential biomarkers for AD within cluster B, we employed two machine learning algorithms: the least absolute shrinkage and selection operator regression and Random Forest. Subsequently, we identified eight feature genes (CARTPT, KLHL35, NRN1, NT5DC3, PCYOX1L, RHOQ, SLC6A12, and SLC38A2) that were utilized to develop a diagnosis model with remarkable predictive capacity for AD. Moreover, we conducted validation using bulk RNA-seq, single-nucleus RNA-seq, and in vivo experiments to confirm the expression of these feature genes. In summary, our study identified a novel necroptosis-related subtype of AD and eight diagnostic biomarkers, explored the roles of necroptosis in AD progression and shed new light for the clinical diagnosis and treatment of this disease.
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Affiliation(s)
- Piaopiao Lian
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xing Cai
- Department of Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoman Yang
- Department of Neurology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zhuoran Ma
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Cailin Wang
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ke Liu
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Wu
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xuebing Cao
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan Xu
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Han J, Wang Q, Li S, Yang J, Qiu Z, Fu W. Comprehensive analysis of basement membrane-related gene based on single-cell and bulk RNA sequencing data to predict prognosis and evaluate immune characteristics in colorectal cancer. ENVIRONMENTAL TOXICOLOGY 2024; 39:3367-3380. [PMID: 38445432 DOI: 10.1002/tox.24211] [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: 01/09/2024] [Revised: 02/05/2024] [Accepted: 02/15/2024] [Indexed: 03/07/2024]
Abstract
AIMS Basement membrane-related genes (BMs) participate in regulating cell polarity, invasion, metastasis, and survival across different tumor types. Nevertheless, the specific functions of BMs in colorectal cancer (CRC) remain uncertain. METHODS To investigate the clinical relevance of BMs in CRC, we retrieved both gene expression and clinical data from The Cancer Genome Atlas (TCGA) datasets for subsequent analysis. The Kaplan-Meier (K-M) survival curve was employed to evaluate prognosis in high- and low-risk groups. Furthermore, additional analyses, including nomogram construction, functional enrichment, examination of the tumor immune microenvironment, prediction of small-molecule drugs, and more, were conducted to delve into the significance of BM-related signatures in CRC. Single-cell data from seven CRC patients were obtained from the TISCH2 database, and expression validation and cell source exploration of BM-related signatures were performed. Lastly, the expression and function of TIMP1, a key gene in BMs that may play a role in the progression of CRC, was validated in vitro through a series of basic experiments. RESULTS We constructed a seven BMs-based model to categorize CRC patients into high-risk and low-risk groups. K-M survival analysis indicated a poorer prognosis for high-risk CRC patients. Cox regression analysis further identified the risk score as an independent prognostic factor for CRC patients. The nomogram model exhibited superior discrimination and calibration abilities of CRC patients. Based on the results from GO/KEGG and GSEA, genes in the high-risk subgroup were implicated in immune-related pathways and exhibited a positive correlation with immune checkpoints. In single-cell data, we found that TIMP1 is highly expressed in many cells, especially in malignant tumor cells. We also observed up-regulation of TIMP1 in CRC cell lines, promoting cancer invasion and migration in vitro. CONCLUSIONS Our study has discovered a novel prognostic index derived from BM-related genes in CRC patients. Specifically, the new model enables patient stratification, improving the selection of individuals likely to benefit from immunotherapy.
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Affiliation(s)
- Jing Han
- Xuzhou Medical University, Xuzhou, Jiangsu Province, China
- Department of General Surgery, Shuyang Hospital of TCM, Shuyang, Jiangsu Province, China
| | - Qipeng Wang
- Department of General Surgery, Shuyang Hospital of TCM, Shuyang, Jiangsu Province, China
| | - Shangshang Li
- Department of General Surgery, Shuyang Hospital of TCM, Shuyang, Jiangsu Province, China
| | - Jie Yang
- Department of General Surgery, Shuyang Hospital of TCM, Shuyang, Jiangsu Province, China
| | - Zhengcai Qiu
- Department of General Surgery, Shuyang Hospital of TCM, Shuyang, Jiangsu Province, China
| | - Wei Fu
- Xuzhou Medical University, Xuzhou, Jiangsu Province, China
- Department of General Surgery, Second Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu Province, China
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Wang SY, Yang XQ, Wang YX, Shen A, Liang CC, Huang RJ, Cheng UH, Jian R, An N, Xiao YL, Wang LS, Zhao Y, Lin C, Wang CP, Yuan ZP, Yuan SQ. Overexpression of COX7A1 Promotes the Resistance of Gastric Cancer to Oxaliplatin and Weakens the Efficacy of Immunotherapy. J Transl Med 2024; 104:102090. [PMID: 38830579 DOI: 10.1016/j.labinv.2024.102090] [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: 12/19/2023] [Revised: 05/09/2024] [Accepted: 05/28/2024] [Indexed: 06/05/2024] Open
Abstract
Gastric cancer (GC) is one of the most common clinical malignant tumors worldwide, with high morbidity and mortality. Presently, the overall response rate to immunotherapy is low, and current methods for predicting the prognosis of GC are not optimal. Therefore, novel biomarkers with accuracy, efficiency, stability, performance ratio, and wide clinical application are needed. Based on public data sets, the chemotherapy cohort and immunotherapy cohort from Sun Yat-sen University Cancer Center, a series of bioinformatics analyses, such as differential expression analysis, survival analysis, drug sensitivity prediction, enrichment analysis, tumor immune dysfunction and exclusion analysis, single-sample gene set enrichment analysis, stemness index calculation, and immune cell infiltration analysis, were performed for screening and preliminary exploration. Immunohistochemical staining and in vitro experiments were performed for further verification. Overexpression of COX7A1 promoted the resistance of GC cells to Oxaliplatin. COX7A1 may induce immune escape by regulating the number of fibroblasts and their cellular communication with immune cells. In summary, measuring the expression levels of COX7A1 in the clinic may be useful in predicting the prognosis of GC patients, the degree of chemotherapy resistance, and the efficacy of immunotherapy.
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Affiliation(s)
- Si-Yu Wang
- Department of Oncology, The First People's Hospital of Yibin, Yibin, China
| | - Xian-Qi Yang
- Department of Gastric Surgery, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Yu-Xin Wang
- Department of Nuclear Medicine, The First Hospital of Jilin University, Changchun, China
| | - Ao Shen
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Cheng-Cai Liang
- Department of Gastric Surgery, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Run-Jie Huang
- Department of Medical Oncology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Un Hio Cheng
- Department of Urology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Rui Jian
- Department of Gastric Surgery, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Nan An
- Department of Gastric Surgery, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Yu-Long Xiao
- Department of Gastric Surgery, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Li-Shuai Wang
- Department of Oncology, The First People's Hospital of Yibin, Yibin, China
| | - Yin Zhao
- Department of Oncology, The First People's Hospital of Yibin, Yibin, China
| | - Chuan Lin
- Department of Oncology, The First People's Hospital of Yibin, Yibin, China
| | - Chang-Ping Wang
- Department of Oncology, The First People's Hospital of Yibin, Yibin, China
| | - Zhi-Ping Yuan
- Department of Oncology, The First People's Hospital of Yibin, Yibin, China
| | - Shu-Qiang Yuan
- Department of Gastric Surgery, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
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Navasardyan I, Zaravinos A, Bonavida B. Therapeutic Implications of Targeting YY1 in Glioblastoma. Cancers (Basel) 2024; 16:2074. [PMID: 38893192 PMCID: PMC11171050 DOI: 10.3390/cancers16112074] [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: 04/25/2024] [Revised: 05/26/2024] [Accepted: 05/27/2024] [Indexed: 06/21/2024] Open
Abstract
The transcription factor Yin Yang 1 (YY1) plays a pivotal role in the pathogenesis of glioblastoma multiforme (GBM), an aggressive form of brain tumor. This review systematically explores the diverse roles of YY1 overexpression and activities in GBM, including its impact on the tumor microenvironment (TME) and immune evasion mechanisms. Due to the poor response of GBM to current therapies, various findings of YY1-associated pathways in the literature provide valuable insights into novel potential targeted therapeutic strategies. Moreover, YY1 acts as a significant regulator of immune checkpoint molecules and, thus, is a candidate therapeutic target in combination with immune checkpoint inhibitors. Different therapeutic implications targeting YY1 in GBM and its inherent associated challenges encompass the use of nanoparticles, YY1 inhibitors, targeted gene therapy, and exosome-based delivery systems. Despite the inherent complexities of such methods, the successful targeting of YY1 emerges as a promising avenue for reshaping GBM treatment strategies, presenting opportunities for innovative therapeutic approaches and enhanced patient outcomes.
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Affiliation(s)
- Inesa Navasardyan
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA;
- Department of Microbiology, Immunology & Molecular Genetics, University of California at Los Angeles, Los Angeles, CA 90095, USA
| | - Apostolos Zaravinos
- Cancer Genetics, Genomics and Systems Biology Laboratory, Basic and Translational Cancer Research Center (BTCRC), 1516 Nicosia, Cyprus;
- Department of Life Sciences, School of Sciences, European University Cyprus, 1516 Nicosia, Cyprus
| | - Benjamin Bonavida
- Department of Microbiology, Immunology & Molecular Genetics, University of California at Los Angeles, Los Angeles, CA 90095, USA
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Peng X, Liu C, Zhang L, Chen Y, Mao L, Gao S, Shi X, Zuo L. IL4I1: a novel molecular biomarker represents an inflamed tumor microenvironment and precisely predicts the molecular subtype and immunotherapy response of bladder cancer. Front Pharmacol 2024; 15:1365683. [PMID: 38873416 PMCID: PMC11169701 DOI: 10.3389/fphar.2024.1365683] [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: 01/04/2024] [Accepted: 05/09/2024] [Indexed: 06/15/2024] Open
Abstract
Introduction: IL4I1, also known as Interleukin-4-induced gene 1, is an enzyme that can modulate the immune system by acting as a L-amino acid oxidase. Nevertheless, a precise understanding of the correlation of IL4I1 with immunological features and immunotherapy efficacy in bladder cancer (BLCA) remains incomplete. Methods: We analyzed RNA sequencing data from the Cancer Genome Atlas (TCGA) to investigate the immune function and prognostic importance of IL4I1 across different cancer types. We further examined the TCGA-BLCA cohort for correlations between IL4I1 and various immunological characteristics of tumor microenvironment (TME), such as cancer immune cycle, immune cell infiltration, immune checkpoint expression and T cell inflamed score. Validation was conducted using two independent cohort, GSE48075 and E-MTAB-4321. Finally, RNA sequencing data from the IMvigor210 cohort and immunohistochemistry assays were employed to validate the predictive value of IL4I1 for the TME and immunotherapy efficacy. Results: In our findings, a positive correlation was observed between IL4I1 expression and immunomodulators expression, immune cell infiltration, the cancer immune cycle, and T cell inflamed score in BLCA, suggesting a significant link to the inflamed TME. In addition, studies have shown that IL4I1 elevated levels of individuals tend to be more performance for basal subtype and exhibit enhanced response rates to diverse treatment modalities, specifically immunotherapy. Clinical data from the IMvigor 210 cohort confirmed a higher rate of response to immunotherapy and better survival benefits in patients with high IL4I1 expression. Discussion: To summarize, our research showed that elevated IL4I1 levels are indicative of an inflamed TME, the basal subtype, and a more favorable response to various treatment methods, especially immune checkpoint blockade therapy in BLCA.
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Affiliation(s)
- Xiangrong Peng
- Department of Urology, ChangZhou No.2 people’s Hospital, Nanjing Medical University, Changzhou, Jiangsu, China
- Laboratory of Urology, ChangZhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu, China
| | - Chuan Liu
- Department of Urology, ChangZhou No.2 people’s Hospital, Nanjing Medical University, Changzhou, Jiangsu, China
- Laboratory of Urology, ChangZhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu, China
| | - Li Zhang
- Department of Urology, ChangZhou No.2 people’s Hospital, Nanjing Medical University, Changzhou, Jiangsu, China
- Laboratory of Urology, ChangZhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu, China
| | - Yin Chen
- Department of Urology, ChangZhou No.2 people’s Hospital, Nanjing Medical University, Changzhou, Jiangsu, China
- Laboratory of Urology, ChangZhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu, China
| | - Lixin Mao
- Department of Urology, ChangZhou No.2 people’s Hospital, Nanjing Medical University, Changzhou, Jiangsu, China
- Laboratory of Urology, ChangZhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu, China
| | - Shenglin Gao
- Department of Urology, ChangZhou No.2 people’s Hospital, Nanjing Medical University, Changzhou, Jiangsu, China
- Laboratory of Urology, ChangZhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu, China
- Department of Urology, Gonghe County Hospital of Traditional Chinese Medicine, Hainan Tibetan Autonomous Prefecture, Qinghai, China
| | - Xiaokai Shi
- Department of Urology, ChangZhou No.2 people’s Hospital, Nanjing Medical University, Changzhou, Jiangsu, China
- Laboratory of Urology, ChangZhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu, China
| | - Li Zuo
- Department of Urology, ChangZhou No.2 people’s Hospital, Nanjing Medical University, Changzhou, Jiangsu, China
- Laboratory of Urology, ChangZhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu, China
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Shi W, Dong J, Zhong B, Hu X, Zhao C. Predicting the Prognosis of Bladder Cancer Patients Through Integrated Multi-omics Exploration of Chemotherapy-Related Hypoxia Genes. Mol Biotechnol 2024:10.1007/s12033-024-01203-9. [PMID: 38806990 DOI: 10.1007/s12033-024-01203-9] [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: 01/10/2024] [Accepted: 05/14/2024] [Indexed: 05/30/2024]
Abstract
Bladder cancer is a prevalent malignancy with high mortality rates worldwide. Hypoxia is a critical factor in the development and progression of cancers. However, whether and how hypoxia-related genes (HRGs) could affect the development and the chemotherapy response of bladder cancer is still largely unexplored. This study comprehensively explored the complex molecular landscape associated with hypoxia in bladder cancer by analyzing 260 hypoxia genes based on transcriptomic and genomic data in 411 samples. Employing the 109 dysregulated hypoxia genes for consensus clustering, we delineated two distinct bladder cancer clusters characterized by disparate survival outcomes and distinct oncogenic roles. We defined a HPscore that was correlated with a variety of clinical features, including TNM stages and pathologic grades. Tumor immune landscape analysis identified three immune clusters and close interactions between hypoxia genes and the various immune cells. Utilizing a network-based method, we defined 129 HRGs exerting influence on apoptotic processes and critical signaling pathways in cancer. Further analysis of chemotherapy drug sensitivity identified potential drug-target HRGs. We developed a Risk Score model that was related to the overall survival of bladder cancer patients based on doxorubicin-target HRGs: ACTG2, MYC, PDGFRB, DHRS2, and KLRD1. This study not only enhanced our understanding of bladder cancer at the molecular level but also provided promising avenues for the development of targeted therapies, representing a significant step toward the identification of effective treatments and addressing the urgent need for advancements in bladder cancer management.
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Affiliation(s)
- Wensheng Shi
- Hunan Key Laboratory of Skin Cancer and Psoriasis, Department of Dermatology, Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
- National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Central South University, Changsha, 410008, Hunan, China
- Furong Laboratory, Changsha, 410008, Hunan, China
- Department of Urology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Jiaming Dong
- Department of Radiation, Cangzhou Central Hospital, Hebei, 061000, China
| | - Bowen Zhong
- Hunan Key Laboratory of Skin Cancer and Psoriasis, Department of Dermatology, Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
- National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Central South University, Changsha, 410008, Hunan, China
- Furong Laboratory, Changsha, 410008, Hunan, China
- Department of Urology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Xiheng Hu
- Hunan Key Laboratory of Skin Cancer and Psoriasis, Department of Dermatology, Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
- National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Central South University, Changsha, 410008, Hunan, China
- Furong Laboratory, Changsha, 410008, Hunan, China
- Department of Urology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Chunguang Zhao
- Department of Critical Care Medicine, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China.
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Azuma I, Mizuno T, Kusuhara H. GLDADec: marker-gene guided LDA modeling for bulk gene expression deconvolution. Brief Bioinform 2024; 25:bbae315. [PMID: 38982642 PMCID: PMC11233176 DOI: 10.1093/bib/bbae315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 05/21/2024] [Accepted: 06/14/2024] [Indexed: 07/11/2024] Open
Abstract
Inferring cell type proportions from bulk transcriptome data is crucial in immunology and oncology. Here, we introduce guided LDA deconvolution (GLDADec), a bulk deconvolution method that guides topics using cell type-specific marker gene names to estimate topic distributions for each sample. Through benchmarking using blood-derived datasets, we demonstrate its high estimation performance and robustness. Moreover, we apply GLDADec to heterogeneous tissue bulk data and perform comprehensive cell type analysis in a data-driven manner. We show that GLDADec outperforms existing methods in estimation performance and evaluate its biological interpretability by examining enrichment of biological processes for topics. Finally, we apply GLDADec to The Cancer Genome Atlas tumor samples, enabling subtype stratification and survival analysis based on estimated cell type proportions, thus proving its practical utility in clinical settings. This approach, utilizing marker gene names as partial prior information, can be applied to various scenarios for bulk data deconvolution. GLDADec is available as an open-source Python package at https://github.com/mizuno-group/GLDADec.
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Affiliation(s)
- Iori Azuma
- Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1, Bunkyo-ku 113-0033, Japan
| | - Tadahaya Mizuno
- Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1, Bunkyo-ku 113-0033, Japan
| | - Hiroyuki Kusuhara
- Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1, Bunkyo-ku 113-0033, Japan
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Sun J, Guo H, Zhang S, Nie Y, Zhou S, Zeng Y, Sun Y. Machine learning-based integration develops an immunogenic cell death-derived lncRNA signature for predicting prognosis and immunotherapy response in lung adenocarcinoma. Sci Rep 2024; 14:11724. [PMID: 38778157 PMCID: PMC11111459 DOI: 10.1038/s41598-024-62569-z] [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: 04/27/2023] [Accepted: 05/19/2024] [Indexed: 05/25/2024] Open
Abstract
Accumulating evidence demonstrates that lncRNAs are involved in the regulation of the immune microenvironment and early tumor development. Immunogenic cell death occurs mainly through the release or increase of tumor-associated antigen and tumor-specific antigen, exposing "danger signals" to stimulate the body's immune response. Given the recent development of immunotherapy in lung adenocarcinoma, we explored the role of tumor immunogenic cell death-related lncRNAs in lung adenocarcinoma for prognosis and immunotherapy benefit, which has never been uncovered yet. Based on the lung adenocarcinoma cohorts from the TCGA database and GEO database, the study developed the immunogenic cell death index signature by several machine learning algorithms and then validated the signature for prognosis and immunotherapy benefit of lung adenocarcinoma patients, which had a more stable performance compared with published signatures in predicting the prognosis, and demonstrated predictive value for benefiting from immunotherapy in multiple cohorts of multiple cancers, and also guided the utilization of chemotherapy drugs.
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Affiliation(s)
- Jiazheng Sun
- Department of Respiratory Medicine, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hehua Guo
- Department of Respiratory Medicine, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Respiratory Medicine, The First People's Hospital of Jiangxia District, Wuhan, China
| | - Siyu Zhang
- Department of Respiratory Medicine, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yalan Nie
- Department of Respiratory Medicine, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Sirui Zhou
- Department of Respiratory Medicine, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yulan Zeng
- Department of Respiratory Medicine, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Yalu Sun
- Department of Rehabilitation Medicine, Affiliated Hospital of Jining Medical University, Jining, China.
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Nguyen H, Nguyen H, Tran D, Draghici S, Nguyen T. Fourteen years of cellular deconvolution: methodology, applications, technical evaluation and outstanding challenges. Nucleic Acids Res 2024; 52:4761-4783. [PMID: 38619038 PMCID: PMC11109966 DOI: 10.1093/nar/gkae267] [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: 10/26/2023] [Revised: 03/01/2024] [Accepted: 04/02/2024] [Indexed: 04/16/2024] Open
Abstract
Single-cell RNA sequencing (scRNA-Seq) is a recent technology that allows for the measurement of the expression of all genes in each individual cell contained in a sample. Information at the single-cell level has been shown to be extremely useful in many areas. However, performing single-cell experiments is expensive. Although cellular deconvolution cannot provide the same comprehensive information as single-cell experiments, it can extract cell-type information from bulk RNA data, and therefore it allows researchers to conduct studies at cell-type resolution from existing bulk datasets. For these reasons, a great effort has been made to develop such methods for cellular deconvolution. The large number of methods available, the requirement of coding skills, inadequate documentation, and lack of performance assessment all make it extremely difficult for life scientists to choose a suitable method for their experiment. This paper aims to fill this gap by providing a comprehensive review of 53 deconvolution methods regarding their methodology, applications, performance, and outstanding challenges. More importantly, the article presents a benchmarking of all these 53 methods using 283 cell types from 30 tissues of 63 individuals. We also provide an R package named DeconBenchmark that allows readers to execute and benchmark the reviewed methods (https://github.com/tinnlab/DeconBenchmark).
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Affiliation(s)
- Hung Nguyen
- Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, USA
| | - Ha Nguyen
- Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, USA
| | - Duc Tran
- Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Sorin Draghici
- Department of Computer Science, Wayne State University, Detroit, MI, USA
- Advaita Bioinformatics, Ann Arbor, MI, USA
| | - Tin Nguyen
- Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, USA
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46
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Li Y, Gu F, Huang X, Huang W, Xiang J, Yue J, Wang Y, Chen R. FRZB: a potential prognostic marker for head and neck squamous cell carcinoma. Braz J Med Biol Res 2024; 57:e13368. [PMID: 38775547 PMCID: PMC11101165 DOI: 10.1590/1414-431x2024e13368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 04/08/2024] [Indexed: 05/25/2024] Open
Abstract
Head and neck squamous cell carcinoma (HNSCC) is the sixth most common malignancy worldwide, with approximately 600,000 new cases each year. A small number of HNSCCs are caused by human papillomavirus (HPV) infection. Frizzled related protein (FRZB) has been reported in many inflammatory diseases and cancers, but it is yet unclear how FRZB affects HNSCC, as well as its role and underlying mechanism. TIMER2 database was utilized to evaluate FRZB expression in cancer tissues, and FRZB expression in HNSCC tissues was confirmed by samples obtained from Gene Expression Omnibus. To identify whether FRZB could be used as a prognostic predictor, we performed univariate and multivariate Cox regression analyses. FRZB co-expression profile was explored using the LinkedOmics database, then Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analyses were performed for these FRZB-related genes in HNSCC samples. Lasso regression analysis was subsequently used to screen for prognostic variables, and we determined the infiltration of immune cells in HNSCC patients to clarify the influence of FRZB on tumor immune microenvironment. At last, we assessed the association between FRZB expression and immune checkpoint gene, and compared the sensitivity of common chemotherapeutic agents. In this study, we found that FRZB was dysregulated in HNSCC tumor tissues and had a relationship with clinical parameters. The reliability and independence of FRZB as a factor in determining a patient's prognosis for HNSCC was also established. Additional investigation revealed that FRZB was linked to common immune checkpoint genes and may be implicated in immune infiltration.
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Affiliation(s)
- Yunshan Li
- College & Hospital of Stomatology, Anhui Medical University,
Key Laboratory of Oral Diseases Research of Anhui Province, Hefei, China
| | - Feihan Gu
- College & Hospital of Stomatology, Anhui Medical University,
Key Laboratory of Oral Diseases Research of Anhui Province, Hefei, China
| | - Xu Huang
- College & Hospital of Stomatology, Anhui Medical University,
Key Laboratory of Oral Diseases Research of Anhui Province, Hefei, China
| | - Wenkai Huang
- College & Hospital of Stomatology, Anhui Medical University,
Key Laboratory of Oral Diseases Research of Anhui Province, Hefei, China
| | - Junwei Xiang
- College & Hospital of Stomatology, Anhui Medical University,
Key Laboratory of Oral Diseases Research of Anhui Province, Hefei, China
| | - Jiayuan Yue
- College & Hospital of Stomatology, Anhui Medical University,
Key Laboratory of Oral Diseases Research of Anhui Province, Hefei, China
| | - Yuanyin Wang
- College & Hospital of Stomatology, Anhui Medical University,
Key Laboratory of Oral Diseases Research of Anhui Province, Hefei, China
| | - Ran Chen
- College & Hospital of Stomatology, Anhui Medical University,
Key Laboratory of Oral Diseases Research of Anhui Province, Hefei, China
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47
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Lin Z, Wang Q, Zheng Z, Zhang B, Zhou S, Zheng D, Chen Z, Zheng S, Zhu S, Zhang X, Lan E, Zhang Y, Lin X, Zhuang Q, Qian H, Hu X, Zhuang Y, Jin Z, Jiang S, Ma Y. Identification and validation of a platelet-related signature for predicting survival and drug sensitivity in multiple myeloma. Front Pharmacol 2024; 15:1377370. [PMID: 38818376 PMCID: PMC11137312 DOI: 10.3389/fphar.2024.1377370] [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: 01/27/2024] [Accepted: 04/29/2024] [Indexed: 06/01/2024] Open
Abstract
Background: Significant progress has been achieved in the management of multiple myeloma (MM) by implementing high-dose therapy and stem cell transplantation. Moreover, the prognosis of patients has been enhanced due to the introduction of novel immunomodulatory drugs and the emergence of new targeted therapies. However, predicting the survival rates of patients with multiple myeloma is still tricky. According to recent researches, platelets have a significant impact in affecting the biological activity of tumors and are essential parts of the tumor microenvironment. Nonetheless, it is still unclear how platelet-related genes (PRGs) connect to the prognosis of multiple myeloma. Methods: We analyzed the expression of platelet-related genes and their prognostic value in multiple myeloma patients in this study. We also created a nomogram combining clinical metrics. Furthermore, we investigated disparities in the biological characteristics, immunological microenvironment, and reaction to immunotherapy, along with analyzing the drug susceptibility within diverse risk groups. Results: By using the platelet-related risk model, we were able to predict patients' prognosis more accurately. Subjects in the high-risk cohort exhibited inferior survival outcomes, both in the training and validation datasets, as compared to those in the low-risk cohort (p < 0.05). Moreover, there were differences in the immunological microenvironments, biological processes, clinical features, and chemotherapeutic drug sensitivity between the groups at high and low risk. Using multivariable Cox regression analyses, platelet-related risk score was shown to be an independent prognostic influence in MM (p < 0.001, hazard ratio (HR) = 2.001%, 95% confidence interval (CI): 1.467-2.730). Furthermore, the capacity to predict survival was further improved when a combined nomogram was utilized. In training cohort, this outperformed the predictive value of International staging system (ISS) alone from a 5-years area under curve (AUC) = 0.668 (95% CI: 0.611-0.725) to an AUC = 0.721 (95% CI: 0.665-0.778). Conclusion: Our study revealed the potential benefits of PRGs in terms of survival prognosis of MM patients. Furthermore, we verified its potential as a drug target for MM patients. These findings open up novel possibilities for prognostic evaluation and treatment choices for MM.
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Affiliation(s)
- Zhili Lin
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Quanqiang Wang
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Ziwei Zheng
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Bingxin Zhang
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Shujuan Zhou
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Dong Zheng
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Zixing Chen
- Department of Hepatobiliary Surgery, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, China
| | - Sisi Zheng
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Shuxia Zhu
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xinyi Zhang
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Enqing Lan
- Department of Hepatobiliary Surgery, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yu Zhang
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xuanru Lin
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Qiang Zhuang
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Honglan Qian
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xudong Hu
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yan Zhuang
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Zhouxiang Jin
- Department of Hepatobiliary Surgery, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, China
| | - Songfu Jiang
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yongyong Ma
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
- Key Laboratory of Intelligent Treatment and Life Support for Critical Diseases of Zhejiang Province, Wenzhou, China
- Zhejiang Engineering Research Center for Hospital Emergency and Process Digitization, Wenzhou, China
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48
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Yang XL, Zeng Z, Wang C, Wang GY, Zhang FQ. Prognostic model incorporating immune checkpoint genes to predict the immunotherapy efficacy for lung adenocarcinoma: a cohort study integrating machine learning algorithms. Immunol Res 2024:10.1007/s12026-024-09492-7. [PMID: 38755433 DOI: 10.1007/s12026-024-09492-7] [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: 12/03/2023] [Accepted: 05/09/2024] [Indexed: 05/18/2024]
Abstract
This study aimed to develop and validate a nomogram based on immune checkpoint genes (ICGs) for predicting prognosis and immune checkpoint blockade (ICB) efficacy in lung adenocarcinoma (LUAD) patients. A total of 385 LUAD patients from the TCGA database and 269 LUAD patients in the combined dataset (GSE41272 + GSE50081) were divided into training and validation cohorts, respectively. Three different machine learning algorithms including random forest (RF), least absolute shrinkage and selection operator (LASSO) logistic regression analysis, and support vector machine (SVM) were employed to select the predictive markers from 82 ICGs to construct the prognostic nomogram. The X-tile software was used to stratify patients into high- and low-risk subgroups based on the nomogram-derived risk scores. Differences in functional enrichment and immune infiltration between the two subgroups were assessed using gene set variation analysis (GSVA) and various algorithms. Additionally, three lung cancer cohorts receiving ICB therapy were utilized to evaluate the ability of the model to predict ICB efficacy in the real world. Five ICGs were identified as predictive markers across all three machine learning algorithms, leading to the construction of a nomogram with strong potential for prognosis prediction in both the training and validation cohorts (all AUC values close to 0.800). The patients were divided into high- (risk score ≥ 185.0) and low-risk subgroups (risk score < 185.0). Compared to the high-risk subgroup, the low-risk subgroup exhibited enrichment in immune activation pathways and increased infiltration of activated immune cells, such as CD8 + T cells and M1 macrophages (P < 0.05). Furthermore, the low-risk subgroup had a greater likelihood of benefiting from ICB therapy and longer progression-free survival (PFS) than did the high-risk subgroup (P < 0.05) in the two cohorts receiving ICB therapy. A nomogram based on ICGs was constructed and validated to aid in predicting prognosis and ICB treatment efficacy in LUAD patients.
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Affiliation(s)
- Xi-Lin Yang
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China
| | - Zheng Zeng
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China
| | - Chen Wang
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China
| | - Guang-Yu Wang
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China
| | - Fu-Quan Zhang
- Department of Radiation Oncology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China.
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49
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Zhu Z, Dong S, Qin S, Gu K, Zhou Y. ANOS1 accelerates the progression of esophageal cancer identified by multi-omic approaches. Am J Cancer Res 2024; 14:2343-2370. [PMID: 38859828 PMCID: PMC11162658 DOI: 10.62347/spcp3536] [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: 12/19/2023] [Accepted: 04/27/2024] [Indexed: 06/12/2024] Open
Abstract
To assess the role of ANOS1 in esophageal cancer (ESCA) progression, multi-omic analysis and experimental validation were employed. It was revealed that ANOS1 expression is significantly enhanced in ESCA patients and cell lines. The expression level of ANOS1 in ESCA patients can distinguish the malignancy from normal tissue with an area under curve (AUC) >0.75. Moreover, increased expression of ANOS1 is associated with advanced T stage and worse disease-free survival of ESCA patients. Therefore, a clinically applicable nomogram with ANOS1 was established with strong predictive power. Furthermore, high expression of ANOS1 in ESCA is correlated with (i) the enrichment of epithelial-mesenchymal transition by gene set enrichment analysis, (ii) the involvement in hypoxia, angiogenesis, WNT signaling pathway, and TGFβ signaling pathway by gene set variation analysis, (iii) the presence of the small insertion and deletion mutational signature ID9, associated with chromothripsis, in the single-nucleotide polymorphism analysis, (iv) the amplification of 11q13.3 in the copy number variants analysis, (v) the enrichment of cancer-associated fibroblasts and mesenchymal stromal cells in the tumor microenvironment. All the results from multi-omic analysis indicate that ANOS1 plays a pivotal role in accelerating the progression of ESCA. Results from in vivo and in vitro experiments show that the knockdown of ANOS1 hampers the proliferation of ESCA cells, further validating the oncogenic role of ANOS1 in ESCA. Additionally, potential chemotherapeutics with sensitivity were identified in the high-ANOS1 group. In conclusion, ANOS1 accelerates the progression of ESCA.
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Affiliation(s)
- Zuoquan Zhu
- Department of Radiotherapy and Oncology, The Affiliated Hospital of Jiangnan UniversityWuxi 214000, Jiangsu, China
| | - Shikun Dong
- Department of Otorhinolaryngology, Zhongda Hospital, Southeast UniversityNanjing 210009, Jiangsu, China
| | - Shaolei Qin
- Jiangnan UniversityWuxi 214000, Jiangsu, China
| | - Ke Gu
- Department of Radiotherapy and Oncology, The Affiliated Hospital of Jiangnan UniversityWuxi 214000, Jiangsu, China
| | - Yanjun Zhou
- Department of Radiotherapy and Oncology, The Affiliated Hospital of Jiangnan UniversityWuxi 214000, Jiangsu, China
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50
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Lin J, Huang C, Diao W, Liu H, Lu H, Huang S, Wang J. CPE correlates with poor prognosis in gastric cancer by promoting tumourigenesis. Heliyon 2024; 10:e29901. [PMID: 38694095 PMCID: PMC11058891 DOI: 10.1016/j.heliyon.2024.e29901] [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: 12/04/2023] [Revised: 04/16/2024] [Accepted: 04/17/2024] [Indexed: 05/03/2024] Open
Abstract
Aims To investigate the potential functions and mechanisms of tumourigenesis in carboxypeptidase E (CPE) and its prognostic value in gastric cancer, and to develop a predictive model for prognosis based on CPE. Results Transcriptome level variation and the prognostic value of CPE in different types of cancers were investigated using bioinformatics analyses. The association between CPE and clinicopathological characteristics was specifically explored in gastric cancer. Elevated CPE expression was associated with poor survival and recurrence prognosis and was found in cases with a later clinical stage of gastric cancer. The CPE was considered an independent prognostic factor, as assessed using Cox regression analysis. The prognostic value of CPE was further verified through immunohistochemistry and haematoxylin staining. Enrichment analysis provided a preliminary confirmation of the potential functions and mechanisms of CPE. Immune cell infiltration analysis revealed a significant correlation between CPE and macrophage infiltration. Eventually, a prognosis prediction nomogram model based on CPE was developed. Conclusion CPE was identified as an independent biomarker associated with poor prognosis in gastric cancer. This suggests that CPE overexpression promoted epithelial-mesenchymal transition via the activation of the Erk/Wnt pathways, leading to proliferation, invasion, and metastasis. Targeted therapeutic strategies for gastric cancer may benefit from these findings.
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Affiliation(s)
- Jiarui Lin
- Department of Gastrointestinal Surgery, Department of General Surgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Chengzhi Huang
- Department of Gastrointestinal Surgery, Department of General Surgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Department of General Surgery, Guangdong Provincial People's Hospital Ganzhou Hospital (Ganzhou Municipal Hospital), Ganzhou, 341000, China
- School of Medicine, South China University of Technology, Guangzhou, 510006, China
| | - Wenfei Diao
- Department of Gastrointestinal Surgery, Department of General Surgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Shantou University Medical College, Shantou, 515000, China
| | - Haoming Liu
- Department of Gastrointestinal Surgery, Department of General Surgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Hesong Lu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080, China
| | - Shengchao Huang
- Department of Gastrointestinal Surgery, Department of General Surgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Junjiang Wang
- Department of Gastrointestinal Surgery, Department of General Surgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
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