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Song N, Wang Z, Shi P, Cui K, Fan Y, Zeng L, Di W, Li J, Su W, Wang H. Comprehensive analysis of signaling lymphocyte activation molecule family as a prognostic biomarker and correlation with immune infiltration in clear cell renal cell carcinoma. Oncol Lett 2024; 28:354. [PMID: 38881710 PMCID: PMC11176890 DOI: 10.3892/ol.2024.14487] [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: 11/01/2023] [Accepted: 04/17/2024] [Indexed: 06/18/2024] Open
Abstract
Clear cell renal cell carcinoma (ccRCC) is a common type of kidney cancer and accounts for 2-3% of all cancer cases. Furthermore, a growing number of immunotherapy approaches are being used in antitumor treatment. Signaling lymphocyte activation molecule family (SLAMF) members have been well studied in several cancers, whereas their roles in ccRCC have not been investigated. The present study comprehensively assessed the molecular mechanisms of SLAMF members in ccRCC, performed using The Cancer Genome Atlas database, with analysis of gene transcription, prognosis, biological function, clinical features, tumor-associated immune cells and the correlation with programmed cell death protein 1/programmed death-ligand 1 immune checkpoints. Simultaneously, the Tumor Immune Dysfunction and Exclusion algorithm was used to predict the efficacy of immune checkpoint blockade (ICB) therapy in patients with high and low SLAMF expression levels. The results demonstrated that all SLAMF members were highly expressed in ccRCC, and patients with high expression levels of SLAMF1, 4, 7 and 8 had a worse prognosis that those with low expression. SLAMF members were not only highly associated with immune activation but also with immunosuppressive agents. The level of immune cell infiltration was associated with the prognosis of patients with ccRCC with high SLAMF expression. Moreover, high ICB response rates were observed in patients with high expression levels of SMALF1 and 4. In summary, SLAMF members may serve as future potential biomarkers for predicting the prognosis of ccRCC and emerge as a novel immunotherapy target.
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Affiliation(s)
- Na Song
- Department of Pathology, Xinxiang Key Laboratory of Tumor Precision Medicine, The First Affiliated Hospital of Xinxiang Medical University, Weihui, Henan 453100, P.R. China
- Department of Pathology, School of Basic Medical Sciences, Xinxiang Medical University, Xinxiang, Henan 453000, P.R. China
| | - Ziwei Wang
- Department of Pathology, School of Basic Medical Sciences, Xinxiang Medical University, Xinxiang, Henan 453000, P.R. China
| | - Pingyu Shi
- Department of Pathology, School of Basic Medical Sciences, Xinxiang Medical University, Xinxiang, Henan 453000, P.R. China
| | - Kai Cui
- Department of Pathology, School of Basic Medical Sciences, Xinxiang Medical University, Xinxiang, Henan 453000, P.R. China
| | - Yanwu Fan
- Department of Pathology, School of Basic Medical Sciences, Xinxiang Medical University, Xinxiang, Henan 453000, P.R. China
| | - Liqun Zeng
- Department of Pathology, School of Basic Medical Sciences, Xinxiang Medical University, Xinxiang, Henan 453000, P.R. China
| | - Wenyu Di
- Department of Pathology, Xinxiang Key Laboratory of Tumor Precision Medicine, The First Affiliated Hospital of Xinxiang Medical University, Weihui, Henan 453100, P.R. China
| | - Jinsong Li
- Department of Pathology, Xinxiang Key Laboratory of Tumor Precision Medicine, The First Affiliated Hospital of Xinxiang Medical University, Weihui, Henan 453100, P.R. China
| | - Wei Su
- Department of Pathology, Xinxiang Key Laboratory of Tumor Precision Medicine, The First Affiliated Hospital of Xinxiang Medical University, Weihui, Henan 453100, P.R. China
| | - Haijun Wang
- Department of Pathology, Xinxiang Key Laboratory of Tumor Precision Medicine, The First Affiliated Hospital of Xinxiang Medical University, Weihui, Henan 453100, P.R. China
- Department of Pathology, School of Basic Medical Sciences, Xinxiang Medical University, Xinxiang, Henan 453000, P.R. China
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Ullah A, Chen Y, Singla RK, Cao D, Shen B. Pro-inflammatory cytokines and CXC chemokines as game-changer in age-associated prostate cancer and ovarian cancer: Insights from preclinical and clinical studies' outcomes. Pharmacol Res 2024; 204:107213. [PMID: 38750677 DOI: 10.1016/j.phrs.2024.107213] [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: 01/29/2024] [Revised: 04/15/2024] [Accepted: 05/09/2024] [Indexed: 06/01/2024]
Abstract
Prostate cancer (PC) and Ovarian cancer (OC) are two of the most common types of cancer that affect the reproductive systems of older men and women. These cancers are associated with a poor quality of life among the aged population. Therefore, finding new and innovative ways to detect, treat, and prevent these cancers in older patients is essential. Finding biomarkers for these malignancies will increase the chance of early detection and effective treatment, subsequently improving the survival rate. Studies have shown that the prevalence and health of some illnesses are linked to an impaired immune system. However, the age-associated changes in the immune system during malignancies such as PC and OC are poorly understood. Recent research has suggested that the excessive production of inflammatory immune mediators, such as interleukin-6 (IL-6), interleukin-8 (IL-8), transforming growth factor (TGF), tumor necrosis factor (TNF), CXC motif chemokine ligand 1 (CXCL1), CXC motif chemokine ligand 12 (CXCL12), and CXC motif chemokine ligand 13 (CXCL13), etc., significantly impact the development of PC and OC in elderly patients. Our review focuses on the latest functional studies of pro-inflammatory cytokines (interleukins) and CXC chemokines, which serve as biomarkers in elderly patients with PC and OC. Thus, we aim to shed light on how these biomarkers affect the development of PC and OC in elderly patients. We also examine the current status and future perspective of cytokines (interleukins) and CXC chemokines-based therapeutic targets in OC and PC treatment for elderly patients.
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Affiliation(s)
- Amin Ullah
- Department of Abdominal Oncology, Cancer Center of West China Hospital and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Yongxiu Chen
- Gynecology Department, Guangdong Women and Children Hospital, No. 521, Xingnan Road, Panyu District, Guangzhou 511442, China
| | - Rajeev K Singla
- Department of Abdominal Oncology, Cancer Center of West China Hospital and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China; School of Pharmaceutical Sciences, Lovely Professional University, Phagwara, Punjab 144411, India
| | - Dan Cao
- Department of Abdominal Oncology, Cancer Center of West China Hospital and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Bairong Shen
- Department of Abdominal Oncology, Cancer Center of West China Hospital and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China.
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Mares-Quiñones MD, Galán-Vásquez E, Pérez-Rueda E, Pérez-Ishiwara DG, Medel-Flores MO, Gómez-García MDC. Identification of modules and key genes associated with breast cancer subtypes through network analysis. Sci Rep 2024; 14:12350. [PMID: 38811600 PMCID: PMC11137066 DOI: 10.1038/s41598-024-61908-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 05/10/2024] [Indexed: 05/31/2024] Open
Abstract
Breast cancer is the most common malignancy in women around the world. Intratumor and intertumoral heterogeneity persist in mammary tumors. Therefore, the identification of biomarkers is essential for the treatment of this malignancy. This study analyzed 28,143 genes expressed in 49 breast cancer cell lines using a Weighted Gene Co-expression Network Analysis to determine specific target proteins for Basal A, Basal B, Luminal A, Luminal B, and HER2 ampl breast cancer subtypes. Sixty-five modules were identified, of which five were characterized as having a high correlation with breast cancer subtypes. Genes overexpressed in the tumor were found to participate in the following mechanisms: regulation of the apoptotic process, transcriptional regulation, angiogenesis, signaling, and cellular survival. In particular, we identified the following genes, considered as hubs: IFIT3, an inhibitor of viral and cellular processes; ETS1, a transcription factor involved in cell death and tumorigenesis; ENSG00000259723 lncRNA, expressed in cancers; AL033519.3, a hypothetical gene; and TMEM86A, important for regulating keratinocyte membrane properties, considered as a key in Basal A, Basal B, Luminal A, Luminal B, and HER2 ampl breast cancer subtypes, respectively. The modules and genes identified in this work can be used to identify possible biomarkers or therapeutic targets in different breast cancer subtypes.
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Affiliation(s)
- María Daniela Mares-Quiñones
- Laboratorio de Biomedicina Molecular, Programa de Doctorado en Biotecnología, Escuela Nacional de Medicina y Homeopatía, Instituto Politécnico Nacional, Ciudad de México, Mexico
| | - Edgardo Galán-Vásquez
- Departamento de Ingeniería de Sistemas Computacionales y Automatización, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Ciudad Universitaria, Ciudad de México, Mexico
| | - Ernesto Pérez-Rueda
- Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Unidad Académica del Estado de Yucatán, Mérida, Mexico
| | - D Guillermo Pérez-Ishiwara
- Laboratorio de Biomedicina Molecular, Programa de Doctorado en Biotecnología, Escuela Nacional de Medicina y Homeopatía, Instituto Politécnico Nacional, Ciudad de México, Mexico
| | - María Olivia Medel-Flores
- Laboratorio de Biomedicina Molecular, Programa de Doctorado en Biotecnología, Escuela Nacional de Medicina y Homeopatía, Instituto Politécnico Nacional, Ciudad de México, Mexico
| | - María Del Consuelo Gómez-García
- Laboratorio de Biomedicina Molecular, Programa de Doctorado en Biotecnología, Escuela Nacional de Medicina y Homeopatía, Instituto Politécnico Nacional, Ciudad de México, Mexico.
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Gunes M, Rosen ST, Shachar I, Gunes EG. Signaling lymphocytic activation molecule family receptors as potential immune therapeutic targets in solid tumors. Front Immunol 2024; 15:1297473. [PMID: 38476238 PMCID: PMC10927787 DOI: 10.3389/fimmu.2024.1297473] [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: 09/20/2023] [Accepted: 02/05/2024] [Indexed: 03/14/2024] Open
Abstract
Recently, cancer immunotherapy has revolutionized cancer treatment. Various forms of immunotherapy have a manageable safety profile and result in prolongation of overall survival in patients with solid tumors, but only in a proportion of patients. Various factors in the tumor microenvironment play critical roles and may be responsible for this lack of therapeutic response. Signaling lymphocytic activation molecule family (SLAMF) members are increasingly being studied as factors impacting the tumor immune microenvironment. SLAMF members consist of nine receptors mainly expressed in immune cells. However, SLAMF receptors have also been detected in cancer cells, and they may be involved in a spectrum of anti-tumor immune responses. Here, we review the current knowledge of the expression of SLAMF receptors in solid tumors and tumor-infiltrating immune cells and their association with patient outcomes. Furthermore, we discuss the therapeutic potential of targeting SLAMF receptors to improve outcomes of cancer therapy in solid tumors. We believe the research on SLAMF receptor-targeted strategies may enhance anti-cancer immunity in patients with solid tumors and improve clinical outcomes.
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Affiliation(s)
- Metin Gunes
- Department of Hematology and Hematopoietic Cell Transplantation, Beckman Research Institute, City of Hope, Los Angeles, CA, United States
| | - Steven T. Rosen
- Department of Hematology and Hematopoietic Cell Transplantation, Beckman Research Institute, City of Hope, Los Angeles, CA, United States
- Judy and Bernard Briskin Center for Multiple Myeloma Research, City of Hope, Los Angeles, CA, United States
| | - Idit Shachar
- Department of System Immunology, Weizmann Institute of Science, Rehovot, Israel
| | - E. Gulsen Gunes
- Department of Hematology and Hematopoietic Cell Transplantation, Beckman Research Institute, City of Hope, Los Angeles, CA, United States
- Judy and Bernard Briskin Center for Multiple Myeloma Research, City of Hope, Los Angeles, CA, United States
- Toni Stephenson Lymphoma Center, City of Hope, Los Angeles, CA, United States
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Fei H, Han X, Wang Y, Li S. Novel immune-related gene signature for risk stratification and prognosis prediction in ovarian cancer. J Ovarian Res 2023; 16:205. [PMID: 37858138 PMCID: PMC10585734 DOI: 10.1186/s13048-023-01289-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: 09/27/2021] [Accepted: 09/28/2023] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND The immune system played a multifaceted role in ovarian cancer (OC) and was a significant mediator of ovarian carcinogenesis. Various immune cells and immune gene products played an integrated role in ovarian cancer (OC) progression, proved the significance of the immune microenvironment in prognosis. Therefore, we aimed to establish and validate an immune gene prognostic signature for OC patients' prognosis prediction. METHODS Differently expressed Immune-related genes (DEIRGs) were identified in 428 OC and 77 normal ovary tissue specimens from 9 independent GEO datasets. The Cancer Genome Atlas (TCGA) cohort was used as a training cohort, Univariate Cox analysis was used to identify prognostic DEIRGs in TCGA cohort. Then, an immune gene-based risk model for prognosis prediction was constructed using the LASSO regression analysis, and validated the accuracy and stability of the model in 374 and 93 OC patients in TCGA training cohort and International Cancer Genome Consortium (ICGC) validation cohort respectively. Finally, the correlation among risk score model, clinicopathological parameters, and immune cell infiltration were analyzed. RESULTS Five DEIRGs were identified to establish the immune gene signature and divided OC patients into the low- and high-risk groups. In TCGA and ICGC datasets, patients in the low-risk group showed a substantially higher survival rate than high-risk group. Receiver operating characteristic (ROC) curves, t-distributed stochastic neighbor embedding (t-SNE) analysis and principal component analysis (PCA) showed the good performance of the risk model. Clinicopathological correlation analysis proved the risk score model could serve as an independent prognostic factor in 2 independent datasets. CONCLUSIONS The prognostic model based on immune-related genes can function as a superior prognostic indicator for OC patients, which could provide evidence for individualized treatment and clinical decision making.
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Affiliation(s)
- Hongjun Fei
- Department of Reproductive Genetics, International Peace Maternity and Child Health Hospital, Shanghai Key Laboratory of Embryo Original Diseases, Shanghai Municipal Key Clinical Specialty, Shanghai Jiao Tong University School of Medicine, No.910, Hengshan Road, Shanghai, 200030, China.
| | - Xu Han
- Department of Reproductive Genetics, International Peace Maternity and Child Health Hospital, Shanghai Key Laboratory of Embryo Original Diseases, Shanghai Municipal Key Clinical Specialty, Shanghai Jiao Tong University School of Medicine, No.910, Hengshan Road, Shanghai, 200030, China
| | - Yanlin Wang
- Department of Reproductive Genetics, International Peace Maternity and Child Health Hospital, Shanghai Key Laboratory of Embryo Original Diseases, Shanghai Municipal Key Clinical Specialty, Shanghai Jiao Tong University School of Medicine, No.910, Hengshan Road, Shanghai, 200030, China
| | - Shuyuan Li
- Department of Reproductive Genetics, International Peace Maternity and Child Health Hospital, Shanghai Key Laboratory of Embryo Original Diseases, Shanghai Municipal Key Clinical Specialty, Shanghai Jiao Tong University School of Medicine, No.910, Hengshan Road, Shanghai, 200030, China.
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Liang L, Zhu Y, Li J, Zeng J, Yuan G, Wu L. Immune Subtypes and Immune Landscape Analysis of Endometrial Carcinoma. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2022; 209:1606-1614. [PMID: 36096644 PMCID: PMC9527207 DOI: 10.4049/jimmunol.2200329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 08/15/2022] [Indexed: 01/04/2023]
Abstract
Some patients with endometrial cancer (EC) suffer from limited survival benefits after immunotherapy, suggesting that there may be a specific pattern associated with immunotherapy. Immune-related genes were extracted from The Cancer Genome Atlas databases. We analyzed the differences among immune subtypes (ISs) in the distribution of the tumor mutational burden, chemotherapy-induced immune response markers, immune checkpoint-related genes, immunotherapy, and chemotherapy. We applied dimensionality reduction and defined the immune landscape of EC. Then, we used the Weighted Gene Co-Expression Network Analysis package to identify the coexpression modules of these immune genes. Finally, hub genes were selected and detected by quantitative PCR and immunohistochemistry. We obtained three ISs. There were differences in the distribution of the tumor mutational burden, chemotherapy-induced immune response markers, and immune checkpoint-related genes among the ISs. Regarding immunotherapy and chemotherapy, the IS2 subtypes were more sensitive to programmed cell death protein 1 inhibitors. In addition, different positions in the immune landscape map exhibited different prognostic characteristics, providing further evidence of the ISs. The IS2 subtypes were significantly positively correlated with yellow module gene list, indicating a good prognosis with high score. SIRPG and SLAMF1 were identified as the final characteristic genes. The quantitative PCR and immunohistochemistry results showed that the expression levels of SIRPG and SLAMF1 were low in human EC tissue. In this study, we identified three reproducible ISs of EC. The immune landscape analysis further revealed the intraclass heterogeneity of the ISs. SIRPG and SLAMF1 were identified to be associated with progression, suggesting that they may be novel immune-related biomarkers of EC.
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Affiliation(s)
- Leilei Liang
- Department of Gynecologic Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yunshu Zhu
- Department of Gynecologic Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jian Li
- Department of Gynecologic Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jia Zeng
- Department of Gynecologic Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Guangwen Yuan
- Department of Gynecologic Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lingying Wu
- Department of Gynecologic Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Lin L, Zeng X, Liang S, Wang Y, Dai X, Sun Y, Wu Z. Construction of a co-expression network and prediction of metastasis markers in colorectal cancer patients with liver metastasis. J Gastrointest Oncol 2022; 13:2426-2438. [PMID: 36388701 PMCID: PMC9660078 DOI: 10.21037/jgo-22-965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 10/18/2022] [Indexed: 01/24/2023] Open
Abstract
BACKGROUND Colorectal cancer (CRC) is a common global malignancy associated with high invasiveness, high metastasis, and poor prognosis. CRC commonly metastasizes to the liver, where the treatment of metastasis is both difficult and an important topic in current CRC management. METHODS Microarrays data of human CRC with liver metastasis (CRCLM) were downloaded from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database to identify potential key genes. Differentially expressed (DE) genes (DEGs) and DEmiRNAs of primary CRC tumor tissues and metastatic liver tissues were identified. Microenvironment Cell Populations (MCP)-counter was used to estimate the abundance of immune cells in the tumor micro-environment (TME), and weighted gene correlation network analysis (WGCNA) was used to construct the co-expression network analysis. Gene Ontology and Kyoto Encyclopaedia of Gene and Genome (KEGG) pathway enrichment analyses were conducted, and the protein-protein interaction (PPI) network for the DEGs were constructed and gene modules were screened. RESULTS Thirty-five pairs of matched colorectal primary cancer and liver metastatic gene expression profiles were screened, and 610 DEGs (265 up-regulated and 345 down-regulated) and 284 DEmiRNAs were identified. The DEGs were mainly enriched in the complement and coagulation cascade pathways and renin secretion. Immune infiltrating cells including neutrophils, monocytic lineage, and cancer-associated fibroblasts (CAFs) differed significantly between primary tumor tissues and metastatic liver tissues. WGCN analysis obtained 12 modules and identified 62 genes with significant interactions which were mainly related to complement and coagulation cascade and the focal adhesion pathway. The best subset regression analysis and backward stepwise regression analysis were performed, and eight genes were determined, including F10, FGG, KNG1, MBL2, PROC, SERPINA1, CAV1, and SPP1. Further analysis showed four genes, including FGG, KNG1, CAV1, and SPP1 were significantly associated with CRCLM. CONCLUSIONS Our study implies complement and coagulation cascade and the focal adhesion pathway play a significant role in the development and progression of CRCLM, and FGG, KNG1, CAV1, and SPP1 may be metastatic markers for its early diagnosis.
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Affiliation(s)
- Lihong Lin
- Department of Anorectal Surgery, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China
| | - Xiuxiu Zeng
- Department of Anorectal Surgery, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China
| | - Shanyan Liang
- Department of Anorectal Surgery, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China
| | - Yunzhi Wang
- School of Health Sciences, University of Sydney, Lidcombe, NSW, Australia
| | - Xiaoyu Dai
- Department of Anorectal Surgery, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China
| | - Yuechao Sun
- Department of Anorectal Surgery, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China;,Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, China
| | - Zhou Wu
- Department of Anorectal Surgery, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, China
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Tang L, Yu S, Zhang Q, Cai Y, Li W, Yao S, Cheng H. Identification of hub genes related to CD4 + memory T cell infiltration with gene co-expression network predicts prognosis and immunotherapy effect in colon adenocarcinoma. Front Genet 2022; 13:915282. [PMID: 36105107 PMCID: PMC9465611 DOI: 10.3389/fgene.2022.915282] [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: 04/07/2022] [Accepted: 07/25/2022] [Indexed: 11/29/2022] Open
Abstract
Background: CD4+ memory T cells (CD4+ MTCs), as an important part of the microenvironment affecting tumorigenesis and progression, have rarely been systematically analyzed. Our purpose was to comprehensively analyze the effect of CD4+ MTC infiltration on the prognosis of colon adenocarcinoma (COAD). Methods: Based on RNA-Seq data, weighted gene co-expression network analysis (WGCNA) was used to screen the CD4+ MTC infiltration genes most associated with colon cancer and then identify hub genes and construct a prognostic model using the least absolute shrinkage and selection operator algorithm (LASSO). Finally, survival analysis, immune efficacy analysis, and drug sensitivity analysis were performed to evaluate the role of the prognostic model in COAD. Results: We identified 929 differentially expressed genes (DEGs) associated with CD4+ MTCs and constructed a prognosis model based on five hub genes (F2RL2, TGFB2, DTNA, S1PR5, and MPP2) to predict overall survival (OS) in COAD. Kaplan-Meier analysis showed poor prognosis in the high-risk group, and the analysis of the hub gene showed that overexpression of TGFB2, DTNA, S1PR5, or MPP2 was associated with poor prognosis. Clinical prediction nomograms combining CD4+ MTC-related DEGs and clinical features were constructed to accurately predict OS and had high clinical application value. Immune efficacy and drug sensitivity analysis provide new insights for individualized treatment. Conclusion: We constructed a prognostic risk model to predict OS in COAD and analyzed the effects of risk score on immunotherapy efficacy or drug sensitivity. These studies have important clinical significance for individualized targeted therapy and prognosis.
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Affiliation(s)
- Lingxue Tang
- Department of Oncology, the Second Affiliated Hospital of Anhui Medical University, Hefei, China
- Department of Oncology, Anhui Medical University, Hefei, China
| | - Sheng Yu
- Department of Oncology, the Second Affiliated Hospital of Anhui Medical University, Hefei, China
- Department of Oncology, Anhui Medical University, Hefei, China
| | - Qianqian Zhang
- Department of Oncology, the Second Affiliated Hospital of Anhui Medical University, Hefei, China
- Department of Oncology, Anhui Medical University, Hefei, China
| | - Yinlian Cai
- Department of Oncology, the Second Affiliated Hospital of Anhui Medical University, Hefei, China
- Department of Oncology, Anhui Medical University, Hefei, China
| | - Wen Li
- Department of Oncology, the Second Affiliated Hospital of Anhui Medical University, Hefei, China
- Department of Oncology, Anhui Medical University, Hefei, China
| | - Senbang Yao
- Department of Oncology, the Second Affiliated Hospital of Anhui Medical University, Hefei, China
- Department of Oncology, Anhui Medical University, Hefei, China
| | - Huaidong Cheng
- Department of Oncology, the Second Affiliated Hospital of Anhui Medical University, Hefei, China
- Department of Oncology, Anhui Medical University, Hefei, China
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ASPN Is a Potential Biomarker and Associated with Immune Infiltration in Endometriosis. Genes (Basel) 2022; 13:genes13081352. [PMID: 36011263 PMCID: PMC9407481 DOI: 10.3390/genes13081352] [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: 06/25/2022] [Revised: 07/20/2022] [Accepted: 07/25/2022] [Indexed: 11/16/2022] Open
Abstract
Objective: Endometriosis is a benign gynecological disease characterized by distant metastasis. Previous studies have discovered abnormal numbers and function of immune cells in endometriotic lesions. We aimed to find potential biomarkers of endometriosis and to explore the relationship between ASPN and the immune microenvironment of endometriosis. Methods: We obtained the GSE141549 and GSE7305 datasets containing endometriosis and normal endometrial samples from the Gene Expression Omnibus database (GEO). In the GSE141549 dataset, differentially expressed genes (DEGs) were found. The Least Absolute Shrinkage and Selection Operator (Lasso) regression and generalized linear models (GLMs) were used to screen new biomarkers. The expression levels and diagnostic utility of biomarkers were assessed in GSE7305, and biomarker expression levels were further validated using qRT-PCR and western blot. We identified DEGs between high and low expression groups of key biomarkers. Enrichment analysis was carried out to discover the target gene’s biological function. We analyzed the relationship between key biomarker expression and patient clinical features. Finally, the immune cells that infiltrate endometriosis were assessed using the Microenvironment Cell Population-Counter (MCP-counter), and the correlation of biomarker expression with immune cell infiltration and immune checkpoints genes was studied. Results: There were a total of 38 DEGs discovered. Two machine learning techniques were used to identify 10 genes. Six biomarkers (SCG2, ASPN, SLIT2, GEM, EGR1, and FOS) had good diagnostic efficiency (AUC > 0.7) by internal and external validation. We excluded previously reported related genes (SLIT2, EGR1, and FOS). ASPN was the most significantly differentially expressed biomarker between normal and ectopic endometrial tissues, as verified by qPCR. The western blot assay revealed a significant upregulation of ASPN expression in endometriotic tissues. The investigation for DEGs in the ASPN high- and low-expression groups revealed that the DEGs were particularly enriched in extracellular matrix tissue, vascular smooth muscle contraction, cytokine interactions, the calcium signaling pathway, and the chemokine signaling pathway. High ASPN expression was related to r-AFS stage (p = 0.006), age (p = 0.03), and lesion location (p < 0.001). Univariate and multivariate logistic regression analysis showed that ASPN expression was an independent influencing factor in patients with endometriosis. Immune cell infiltration analysis revealed a significant increase in T-cell, B-cell, and fibroblast infiltration in endometriosis lesions; cytotoxic lymphocyte, NK-cell, and endothelial cell infiltration were reduced. Additionally, the percentage of T cells, B cells, fibroblasts, and endothelial cells was favorably connected with ASPN expression, while the percentage of cytotoxic lymphocytes and NK cells was negatively correlated. Immune checkpoint gene (CTLA4, LAG3, CD27, CD40, and ICOS) expression and ASPN expression were positively associated. Conclusions: Increased expression of ASPN is associated with immune infiltration in endometriosis, and ASPN can be used as a diagnostic biomarker as well as a potential immunotherapeutic target in endometriosis.
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Drown MK, Crawford DL, Oleksiak MF. Transcriptomic analysis provides insights into molecular mechanisms of thermal physiology. BMC Genomics 2022; 23:421. [PMID: 35659182 PMCID: PMC9167525 DOI: 10.1186/s12864-022-08653-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 05/18/2022] [Indexed: 11/15/2022] Open
Abstract
Physiological trait variation underlies health, responses to global climate change, and ecological performance. Yet, most physiological traits are complex, and we have little understanding of the genes and genomic architectures that define their variation. To provide insight into the genetic architecture of physiological processes, we related physiological traits to heart and brain mRNA expression using a weighted gene co-expression network analysis. mRNA expression was used to explain variation in six physiological traits (whole animal metabolism (WAM), critical thermal maximum (CTmax), and four substrate specific cardiac metabolic rates (CaM)) under 12 °C and 28 °C acclimation conditions. Notably, the physiological trait variations among the three geographically close (within 15 km) and genetically similar F. heteroclitus populations are similar to those found among 77 aquatic species spanning 15–20° of latitude (~ 2,000 km). These large physiological trait variations among genetically similar individuals provide a powerful approach to determine the relationship between mRNA expression and heritable fitness related traits unconfounded by interspecific differences. Expression patterns explained up to 82% of metabolic trait variation and were enriched for multiple signaling pathways known to impact metabolic and thermal tolerance (e.g., AMPK, PPAR, mTOR, FoxO, and MAPK) but also contained several unexpected pathways (e.g., apoptosis, cellular senescence), suggesting that physiological trait variation is affected by many diverse genes.
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Fan X, Zhang L, Huang J, Zhong Y, Fan Y, Zhou T, Lu M. An Integrated Immune-Related Bioinformatics Analysis in Glioma: Prognostic Signature’s Identification and Multi-Omics Mechanisms’ Exploration. Front Genet 2022; 13:889629. [PMID: 35601497 PMCID: PMC9114310 DOI: 10.3389/fgene.2022.889629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 04/18/2022] [Indexed: 12/05/2022] Open
Abstract
As the traditional treatment for glioma, the most common central nervous system malignancy with poor prognosis, the efficacy of high-intensity surgery combined with radiotherapy and chemotherapy is not satisfactory. The development of individualized scientific treatment strategy urgently requires the guidance of signature with clinical predictive value. In this study, five prognosis-related differentially expressed immune-related genes (PR-DE-IRGs) (CCNA2, HMGB2, CASP3, APOBEC3C, and BMP2) highly associated with glioma were identified for a prognostic model through weighted gene co-expression network analysis, univariate Cox and lasso regression. Kaplan-Meier survival curves, receiver operating characteristic curves and other methods have shown that the model has good performance in predicting the glioma patients’ prognosis. Further combined nomogram provided better predictive performance. The signature’s guiding value in clinical treatment has also been verified by multiple analysis results. We also constructed a comprehensive competing endogenous RNA (ceRNA) regulatory network based on the protective factor BMP2 to further explore its potential role in glioma progression. Numerous immune-related biological functions and pathways were enriched in a high-risk population. Further multi-omics integrative analysis revealed a strong correlation between tumor immunosuppressive environment/IDH1 mutation and signature, suggesting that their cooperation plays an important role in glioma progression.
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Affiliation(s)
- Xin Fan
- Department of Emergency Medicine, Shangrao Hospital Affiliated to Nanchang University, Shangrao People’s Hospital, Shangrao, China
- Department of Otolaryngology-Head and Neck Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Lingling Zhang
- School of Stomatology, Nanchang University, Nanchang, China
| | - Junwen Huang
- The First Clinical Medical College of Nanchang University, Nanchang, China
| | - Yun Zhong
- The First Clinical Medical College of Nanchang University, Nanchang, China
| | - Yanting Fan
- The First Clinical Medical College of Nanchang University, Nanchang, China
| | - Tong Zhou
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Min Lu
- Department of Emergency Medicine, Shangrao Hospital Affiliated to Nanchang University, Shangrao People’s Hospital, Shangrao, China
- *Correspondence: Min Lu,
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Xiaowei W, Tong L, Yanjun Q, Lili F. PTH2R is related to cell proliferation and migration in ovarian cancer: a multi-omics analysis of bioinformatics and experiments. Cancer Cell Int 2022; 22:148. [PMID: 35410353 PMCID: PMC8996580 DOI: 10.1186/s12935-022-02566-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 03/30/2022] [Indexed: 12/23/2022] Open
Abstract
Background Ovarian cancer is a common gynecological disease and seriously endangers women's health. Currently, there is still a lack of effective molecular markers for the diagnosis and treatment of ovarian cancer. The present study aimed to investigate the molecular markers associated with ovarian cancer. Methods The molecular and gene related to ovarian cancer were extracted from GEO database and TCGA database by bioinformatics, and the related genes and functions were further analyzed. The results were verified by qPCR, WB, CCK-8 and Transwell experiments. Results Data analysis showed that PTH2R gene was highly expressed in tumors, and 51 HUB genes were obtained. Finally, experimental verification showed that PTH2R gene was highly expressed in ovarian cancer, and PTH2R gene was involved in the proliferation, invasion and metastasis of ovarian cancer cells. Conclusions After experimental verification, we found that knocking down the expression of PTH2R can inhibit the proliferation, invasion and migration of tumor cells.PTH2R is expected to become a new molecular marker for ovarian cancer. Supplementary Information The online version contains supplementary material available at 10.1186/s12935-022-02566-2.
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Affiliation(s)
- Wang Xiaowei
- Department of Ultrasnography in Gynecology and Obstetrics, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Lu Tong
- Department of Thoracic Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Qu Yanjun
- Department of Ultrasnography in Gynecology and Obstetrics, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Fan Lili
- Department of Children's and Adolescent Health, Public Health College, Harbin Medical University, Harbin, China.
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Glycosylation-Related Genes Predict the Prognosis and Immune Fraction of Ovarian Cancer Patients Based on Weighted Gene Coexpression Network Analysis (WGCNA) and Machine Learning. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2022; 2022:3665617. [PMID: 35281472 PMCID: PMC8916863 DOI: 10.1155/2022/3665617] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 02/10/2022] [Accepted: 02/21/2022] [Indexed: 12/24/2022]
Abstract
Background Ovarian cancer (OC) is a malignancy exhibiting high mortality in female tumors. Glycosylation is a posttranslational modification of proteins but research has failed to demonstrate a systematic link between glycosylation-related signatures and tumor environment of OC. Purpose This study is aimed at developing a novel model with glycosylation-related messenger RNAs (GRmRNAs) to predict the prognosis and immune function in OC patients. Methods The transcriptional profiles and clinical phenotypes of OC patients were collected from the Gene Expression Omnibus and The Cancer Genome Atlas databases. A weighted gene coexpression network analysis and machine learning were performed to find the optimal survival-related GRmRNAs. Least absolute shrinkage and selection operator regression (LASSO) and Cox regression were carried out to calculate the coefficients of each GRmRNA and compute the risk score of each patient as well as develop a prognostic model. A nomogram model was constructed, and several algorithms were used to investigate the relationship between risk subtypes and immune-infiltrating levels. Results A total of four signatures (ALG8, DCTN4, DCTN6, and UBB) were determined to calculate the risk scores, classifying patients into the high-and low-risk groups. High-risk patients exhibited significantly poorer survival outcomes, and the established nomogram model had a promising prediction for OC patients' prognosis. Tumor purity and tumor mutation burden were negatively correlated with risk scores. In addition, risk scores held statistical associations with pathway signatures such as Wnt, Hippo, and reactive oxygen species, and nonsynonymous mutation counts. Conclusion The currently established risk scores based on GRmRNAs can accurately predict the prognosis, the immune microenvironment, and the immunotherapeutic efficacy of OC patients.
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