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Liu S, Wang Z, Hu L, Ye C, Zhang X, Zhu Z, Li J, Shen Q. Pan-cancer analysis of super-enhancer-induced LINC00862 and validation as a SIRT1-promoting factor in cervical cancer and gastric cancer. Transl Oncol 2024; 45:101982. [PMID: 38718436 PMCID: PMC11097084 DOI: 10.1016/j.tranon.2024.101982] [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: 02/17/2024] [Revised: 04/18/2024] [Accepted: 04/30/2024] [Indexed: 05/19/2024] Open
Abstract
Immune checkpoints inhibitors are effective but it needs more precise biomarkers for patient selection. We explored the biological significance of LINC00862 in pan-cancer by bioinformatics. And we studied its regulatory mechanisms using chromatin immunoprecipitation and RNA immunoprecipitation assays etc. TCGA and single-cell sequencing data analysis indicated that LINC00862 was overexpressed in the majority of tumor and stromal cells, which was related with poor prognosis. LINC00862 expression was related with immune cell infiltration and immune checkpoints expression, and had a high predictive value for immunotherapy efficacy. Mechanistically, LINC00862 competitively bound to miR-29c-3p to unleash SIRT1's tumor-promoting function. SIRT1 inhibitor-EX527 were screened by virtual screening and verified by in vitro and vivo assays. Notably, acetyltransferase P300-mediated super-enhancer activity stimulated LINC00862 transcription. Collectively, LINC00862 could be a diagnostic and prognostic biomarker. LINC00862 could also be a predictive biomarker for immunotherapy efficacy. Super-enhancer activity is the driver for LINC00862 overexpression in cervical cancer and gastric cancer.
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Affiliation(s)
- Shaojun Liu
- Department of General Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui, China
| | - Zhaohui Wang
- Department of Pathology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui, China
| | - Lei Hu
- Department of General Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui, China
| | - Chao Ye
- Department of Gastroenterology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui, China
| | - Xubin Zhang
- Department of General Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui, China
| | - Zhiqiang Zhu
- Department of General Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui, China
| | - Jiaqiu Li
- Clinical Research Center, Affiliated Hospital of Shandong Second Medical University, Shandong Second Medical University, Weifang 261031, Shandong, China.
| | - Qi Shen
- Department of Radiation Oncology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui, China.
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Liu WS, Wu BS, Yang L, Chen SD, Zhang YR, Deng YT, Wu XR, He XY, Yang J, Feng JF, Cheng W, Xu YM, Yu JT. Whole exome sequencing analyses reveal novel genes in telomere length and their biomedical implications. GeroScience 2024:10.1007/s11357-024-01203-2. [PMID: 38837026 DOI: 10.1007/s11357-024-01203-2] [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: 12/29/2023] [Accepted: 05/11/2024] [Indexed: 06/06/2024] Open
Abstract
Telomere length is a putative biomarker of aging and is associated with multiple age-related diseases. There are limited data on the landscape of rare genetic variations in telomere length. Here, we systematically characterize the rare variant associations with leukocyte telomere length (LTL) through exome-wide association study (ExWAS) among 390,231 individuals in the UK Biobank. We identified 18 robust rare-variant genes for LTL, most of which estimated effects on LTL were significant (> 0.2 standard deviation per allele). The biological functions of the rare-variant genes were associated with telomere maintenance and capping and several genes were specifically expressed in the testis. Three novel genes (ASXL1, CFAP58, and TET2) associated with LTL were identified. Phenotypic association analyses indicated significant associations of ASXL1 and TET2 with cancers, age-related diseases, blood assays, and cardiovascular traits. Survival analyses suggested that carriers of ASXL1 or TET2 variants were at increased risk for cancers; diseases of the circulatory, respiratory, and genitourinary systems; and all-cause and cause-specific deaths. The CFAP58 carriers were at elevated risk of deaths due to cancers. Collectively, the present whole exome sequencing study provides novel insights into the genetic landscape of LTL, identifying novel genes associated with LTL and their implications on human health and facilitating a better understanding of aging, thus pinpointing the genetic relevance of LTL with clonal hematopoiesis, biomedical traits, and health-related outcomes.
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Affiliation(s)
- Wei-Shi Liu
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Liu Yang
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Shi-Dong Chen
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Ya-Ru Zhang
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Yue-Ting Deng
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Xin-Rui Wu
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Xiao-Yu He
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Jing Yang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, 1St Eastern Jianshe Road, Zhengzhou, 450000, China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, Zhengzhou, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry, UK
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry, UK
| | - Yu-Ming Xu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, 1St Eastern Jianshe Road, Zhengzhou, 450000, China.
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, Zhengzhou, China.
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China.
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Jiang F, Tao Z, Zhang Y, Xie X, Bao Y, Hu Y, Ding J, Wu C. Machine learning combined with single-cell analysis reveals predictive capacity and immunotherapy response of T cell exhaustion-associated lncRNAs in uterine corpus endometrial carcinoma. Cell Signal 2024; 117:111077. [PMID: 38311301 DOI: 10.1016/j.cellsig.2024.111077] [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: 09/16/2023] [Revised: 12/24/2023] [Accepted: 02/01/2024] [Indexed: 02/10/2024]
Abstract
BACKGROUND The exhaustion of T-cells is a primary factor contributing to immune dysfunction in cancer. Long non-coding RNAs (lncRNAs) play a significant role in the advancement, survival, and treatment of Uterine Corpus Endometrial Carcinoma (UCEC). Nevertheless, there has been no investigation into the involvement of lncRNAs associated with T-cell exhaustion (TEXLs) in UCEC. The goal of this work is to establish predictive models for TEXLs in UCEC and study their related immune features. METHODS Using transcriptome and single-cell sequencing data from The Cancer Genome Atlas and Gene Expression Omnibus databases, we employed co-expression analysis and univariate Cox regression to identify prognostic-associated TEXLs (pTEXLs). The prognostic model was developed using the Least Absolute Contraction and Selection Operator. The immunotherapy characteristics of the prognostic model risk score were studied. Then molecular subgroups were identified through non-negative Matrix Factorization based on pTEXLs. The identification of co-expressed genes was done using a weighted correlation network analysis. Subsequently, a diagnostic model for UCEC was created. In-depth investigations, both in vitro and in vivo, were carried out to elucidate the molecular mechanism of the key gene within the diagnostic model. RESULTS Receiver operating characteristic curve, calibration curve, and decision curve analysis proved the validity of the predictive models established according to pTEXLs. The subgroup with lower risk scores in the prognostic model has better responses to blocking immune checkpoint therapy. Single-cell analysis suggests that the expression level of MIEN1 is relatively high in immune cells among diagnostic genes. Furthermore, the targeted suppression of MIEN1 via sh-MIEN1 diminishes the proliferative, migratory, and invasive capacities of UCEC cells, potentially associated with CD8+ T cell exhaustion. CONCLUSIONS The association between TEXLs and UCEC was methodically elucidated by our investigation. A stable pTEXLs risk prediction model and a diagnosis model for UCEC were also established.
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Affiliation(s)
- Feng Jiang
- Department of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
| | - Ziyu Tao
- Department of Ultrasound, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
| | - Yun Zhang
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiaoyan Xie
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yunlei Bao
- Department of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
| | - Yifang Hu
- Department of Geriatric Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
| | - Jingxin Ding
- Department of Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China; Shanghai Key Laboratory of Female Reproductive Endocrine-Related Disease, Shanghai, China.
| | - Chuyan Wu
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
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Chang F, Liu H, Wan J, Gao Y, Wang Z, Zhang L, Feng Q. Construction and Validation of a Prognostic Risk Prediction Model for Lactate Metabolism-Related lncRNA in Endometrial Cancer. Biochem Genet 2024; 62:741-760. [PMID: 37423972 DOI: 10.1007/s10528-023-10443-4] [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: 03/08/2023] [Accepted: 06/29/2023] [Indexed: 07/11/2023]
Abstract
Endometrial cancer (EC) is a common group of malignant epithelial tumors that mainly occur in the female endometrium. Lactate is a key regulator of signal pathways in normal and malignant tissues. However, there is still no research on lactate metabolism-related lncRNA in EC. Here, we intended to establish a prognostic risk model for EC based on lactate metabolism-related lncRNA to forecast the prognosis of EC patients. First, we found that 38 lactate metabolism-associated lncRNAs were significantly overall survival through univariate Cox regression analysis. Using minimum absolute contraction and selection operator (LASSO) regression analysis and multivariate Cox regression analysis, six lactate metabolism-related lncRNAs were established as independent predictor in EC patients and were used to establish a prognostic risk signature. We next used multifactorial COX regression analysis and receiver operating characteristic (ROC) curve analysis to confirm that risk score was an independent prognostic factor of overall patient survival. The survival time of patients with EC in different high-risk populations was obviously related to clinicopathological factors. In addition, lactate metabolism-related lncRNA in high-risk population participated in multiple aspects of EC malignant progress through Gene Set Enrichment Analysis, Genomes pathway and Kyoto Encyclopedia of Genes and Gene Ontology. And risk scores were strongly associated with tumor mutation burden, immunotherapy response and microsatellite instability. Finally, we chose a lncRNA SRP14-AS1 to validate the model we have constructed. Interestingly, we observed that the expression degree of SRP14-AS1 was lower in tumor tissues of EC patients than in normal tissues, which was consistent with our findings in the TCGA database. In conclusion, our study constructed a prognostic risk model through lactate metabolism-related lncRNA and validated the model, confirming that the model can be used to predict the prognosis of EC patients and providing a molecular analysis of potential prognostic lncRNA for EC.
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Affiliation(s)
- Fenghua Chang
- Department of Obstetrics and Gynecology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China
| | - Hongyang Liu
- Department of Obstetrics and Gynecology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China
| | - Junhu Wan
- Department of Clinical Laboratory, Key Clinical Laboratory of Henan Province, First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China
| | - Ya Gao
- Department of Obstetrics and Gynecology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China
| | - Zhiting Wang
- Department of Obstetrics and Gynecology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China
| | - Lindong Zhang
- Department of Obstetrics and Gynecology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China
| | - Quanling Feng
- Department of Obstetrics and Gynecology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
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Ren H, Zheng J, Zhu Y, Wang L, Liu J, Xu H, Dong J, Zhang S. Comprehensive analysis of cuproptosis-related long non-coding RNAs in prognosis, immune microenvironment infiltration and chemotherapy response of hepatocellular carcinoma. Medicine (Baltimore) 2023; 102:e36611. [PMID: 38115286 PMCID: PMC10727658 DOI: 10.1097/md.0000000000036611] [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: 07/15/2023] [Revised: 11/17/2023] [Accepted: 11/21/2023] [Indexed: 12/21/2023] Open
Abstract
The objective of this study is to explore the relationship between cuproptosis-related long noncoding RNAs (lncRNAs) in hepatocellular carcinoma (HCC). RNA-seq data, including lncRNAs and related clinical information of HCC patients, were downloaded from The Cancer Genome Atlas database. A signature composed 3 cuproptosis-related lncRNAs was constructed by LASSO analysis, and HCC patients were classified into high- and low-risk groups. Patients in the high-risk group had a poorer prognosis compared with the low-risk group. Univariate Cox and multivariate Cox regression analyses confirmed that the signature model was an independent risk factor compared to other clinical biomarkers. Furthermore, gene set enrichment analysis indicated that metabolism-related pathways were enriched in low-risk group, including drug metabolism, and fatty acid metabolism. Further research demonstrated that there were markedly differences in drug response between the high- and low-risk group. Immune related analysis showed that the most type of immune cells and immunological function in the high-risk group were different with the risk-group. Finally, TP53 mutation rate and the tumor mutational burden in the high-risk group were higher compared with the low-risk group. In conclusion, we constructed a prognostic signature based on the expression of cuproptosis-related lncRNAs to predict HCC patients' prognosis, drug response and immune microenvironment, and further research will be conducted to uncover the mechanisms.
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Affiliation(s)
- Huili Ren
- Department of Pharmacy, Traditional Chinese and Western Medicine Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jianglin Zheng
- Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Zhu
- Department of Pharmacy, Traditional Chinese and Western Medicine Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Leiyun Wang
- Department of Pharmacy, Traditional Chinese and Western Medicine Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jianmin Liu
- Department of Pharmacy, Traditional Chinese and Western Medicine Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongfeng Xu
- Department of Pharmacy, Traditional Chinese and Western Medicine Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Junli Dong
- Department of Pharmacy, Traditional Chinese and Western Medicine Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shaohui Zhang
- Department of Pharmacy, Traditional Chinese and Western Medicine Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Andersen MS, Leikfoss IS, Brorson IS, Cappelletti C, Bettencourt C, Toft M, Pihlstrøm L. Epigenome-wide association study of peripheral immune cell populations in Parkinson's disease. NPJ Parkinsons Dis 2023; 9:149. [PMID: 37903812 PMCID: PMC10616224 DOI: 10.1038/s41531-023-00594-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 10/19/2023] [Indexed: 11/01/2023] Open
Abstract
Understanding the contribution of immune mechanisms to Parkinson's disease pathogenesis is an important challenge, potentially of major therapeutic implications. To further elucidate the involvement of peripheral immune cells, we studied epigenome-wide DNA methylation in isolated populations of CD14+ monocytes, CD19+ B cells, CD4+ T cells, and CD8+ T cells from Parkinson's disease patients and healthy control participants. We included 25 patients with a maximum five years of disease duration and 25 controls, and isolated four immune cell populations from each fresh blood sample. Epigenome-wide DNA methylation profiles were generated from 186 samples using the Illumina MethylationEpic array and association with disease status was tested using linear regression models. We identified six differentially methylated CpGs in CD14+ monocytes and one in CD8 + T cells. Four differentially methylated regions were identified in monocytes, including a region upstream of RAB32, a gene that has been linked to LRRK2. Methylation upstream of RAB32 correlated negatively with mRNA expression, and RAB32 expression was upregulated in Parkinson's disease both in our samples and in summary statistics from a previous study. Our epigenome-wide association study of early Parkinson's disease provides evidence for methylation changes across different peripheral immune cell types, highlighting monocytes and the RAB32 locus. The findings were predominantly cell-type-specific, demonstrating the value of isolating purified cell populations for genomic studies.
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Affiliation(s)
- Maren Stolp Andersen
- Department of Neurology, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | | | | | | | - Conceicao Bettencourt
- Department of Neurodegenerative Disease and Queen Square Brain Bank for Neurological Disorders, Queen Square Institute of Neurology, University College London, London, UK
| | - Mathias Toft
- Department of Neurology, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Lasse Pihlstrøm
- Department of Neurology, Oslo University Hospital, Oslo, Norway.
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Deng Y, Li Z, Pan M, Wu H, Ni B, Han X. Implications of inflammatory cell death-related IFNG and co-expressed RNAs (AC006369.1 and CCR7) in breast carcinoma prognosis, and anti-tumor immunity. Front Genet 2023; 14:1112251. [PMID: 37408777 PMCID: PMC10318797 DOI: 10.3389/fgene.2023.1112251] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 04/14/2023] [Indexed: 07/07/2023] Open
Abstract
Objective: Interferon-γ (IFN-γ) encoded by IFNG gene is a pleiotropic molecule linked with inflammatory cell death mechanisms. This work aimed to determine and characterize IFNG and co-expressed genes, and to define their implications in breast carcinoma (BRCA). Methods: Transcriptome profiles of BRCA were retrospectively acquired from public datasets. Combination of differential expression analysis with WGCNA was conducted for selecting IFNG-co-expressed genes. A prognostic signature was generated through Cox regression approaches. The tumor microenvironment populations were inferred utilizing CIBERSORT. Epigenetic and epitranscriptomic mechanisms were also probed. Results: IFNG was overexpressed in BRCA, and connected with prolonged overall survival and recurrence-free survival. Two IFNG-co-expressed RNAs (AC006369.1, and CCR7) constituted a prognostic model that acted as an independent risk factor. The nomogram composed of the model, TNM, stage, and new event owned the satisfying efficacy in BRCA prognostication. IFNG, AC006369.1, and CCR7 were closely linked with the tumor microenvironment components (e.g., macrophages, CD4/CD8 T cells, NK cells), and immune checkpoints (notably PD1/PD-L1). Somatic mutation frequencies were 6%, and 3% for CCR7, and IFNG, and high amplification potentially resulted in their overexpression in BRCA. Hypomethylated cg05224770 and cg07388018 were connected with IFNG and CCR7 upregulation, respectively. Additionally, transcription factors, RNA-binding proteins, and non-coding RNAs possibly regulated IFNG and co-expressed genes at the transcriptional and post-transcriptional levels. Conclusion: Collectively, our work identifies IFNG and co-expressed genes as prognostic markers for BRCA, and as possible therapeutic targets for improving the efficacy of immunotherapy.
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