C4orf46 is a Potential Prognostic Biomarker for Liver Hepatocellular Carcinoma
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Chromosome 4 includes genetic factors involved in various cancers, such as liver hepatocellular carcinoma (LIHC), and those related to the diagnostic biomarkers of human diseases. However, chromosome 4 open-reading frame 46 (C4orf46), a part of chromosome 4, has not yet been evaluated as an LIHC biomarker. In this study, we investigated the potential of C4orf46 as a prognostic biomarker for LIHC and analyzed its correlations with immune cells and molecular functions. Data analysis using open online databases, including the Tumor Immune Estimation Resource, University of ALabama at Birmingham CANcer, Kaplan-Meier plotter, LinkedOmics, and Gene Expression Profiling Interactive Analysis version 2, revealed that C4orf46 was highly expressed in LIHC tissues than in normal tissues. Moreover, survival rate analyses, such as disease-specific, overall, progression-free, and relapse-free survival analyses, revealed that high expression of C4orf46 was associated with a poor prognosis in LIHC. C4orf46 expression was positively correlated with various tumorinfiltrating immune cells, including B cells, CD4 + T cells, CD8 + T cells, neutrophils, macrophages, and dendritic cells. C4orf46 was also involved in chromosome segregation, DNA replication, cell cycle G2/M phase transition, and microtubule cytoskeleton organization during mitosis, mitotic cell cycle phase transition, and cell cycle checkpoints. In conclusion, C4orf46 is a potential prognostic biomarker that is correlated with immune infiltration in LIHC.
Abstract
Chromosome 4 includes genetic factors involved in various cancers, such as liver hepatocellular carcinoma (LIHC), and those related to the diagnostic biomarkers of human diseases. However, chromosome 4 open-reading frame 46 (C4orf46), a part of chromosome 4, has not yet been evaluated as an LIHC biomarker. In this study, we investigated the potential of C4orf46 as a prognostic biomarker for LIHC and analyzed its correlations with immune cells and molecular functions. Data analysis using open online databases, including the Tumor Immune Estimation Resource, University of ALabama at Birmingham CANcer, Kaplan-Meier plotter, LinkedOmics, and Gene Expression Profiling Interactive Analysis version 2, revealed that C4orf46 was highly expressed in LIHC tissues than in normal tissues. Moreover, survival rate analyses, such as disease-specific, overall, progression-free, and relapse-free survival analyses, revealed that high expression of C4orf46 was associated with a poor prognosis in LIHC. C4orf46 expression was positively correlated with various tumorinfiltrating immune cells, including B cells, CD4 + T cells, CD8 + T cells, neutrophils, macrophages, and dendritic cells. C4orf46 was also involved in chromosome segregation, DNA replication, cell cycle G2/M phase transition, and microtubule cytoskeleton organization during mitosis, mitotic cell cycle phase transition, and cell cycle checkpoints. In conclusion, C4orf46 is a potential prognostic biomarker that is correlated with immune infiltration in LIHC.
참고문헌 (27)
- Villanueva A, "Hepatocellular carcinoma", N Engl J Med, 380, pp.1450~1462 (2019)
- Paul C, "Hepatitis C virus core protein interacts with cellular metastasis suppressor Nm23-H1and promotes cell migration and invasion", Arch Virol, 164, pp.1271~1285 (2019)
- Singal AG, "Hepatocellular carcinoma from epidemiology to prevention : Translating knowledge into practice", Clin Gastroenterol Hepatol, 13, pp.2140~2151 (2015)
- Zheng X, "Progression on the roles and mechanisms of tumor-infiltrating T lymphocytes in patients with hepatocellular carcinoma", Front Immunol, 12, pp.729705~ (2021)
- Lee YT, "Risk stratification and early detection biomarkers for precision LIHC screening", Hepatology, 78, pp.319~362 (2023)
- Gentles AJ, "The prognostic landscape of genes and infiltrating immune cells across human cancers", Nat Med, 21, pp.938~945 (2015)
- Angell HK, "PD-L1 and immune infiltrates are differentially expressed in distinct subgroups of gastric cancer", Oncoimmunology, 8, pp.e1544442~ (2018)
- Harding JJ, "Biomarkers : What role do they play(if any)for diagnosis, prognosis and tumor response prediction for hepatocellular carcinoma?", Dig Dis Sci, 64, pp.918~927 (2019)
- Chen LC, "Decoding the disease-associated proteins encoded in the human chromosome 4", J Proteome Res, 12, pp.33~44 (2013)
- 김혜란, "C4orf47 is a Novel Prognostic Biomarker and Correlates with Infiltrating Immune Cells in Hepatocellular Carcinoma", 대한의생명과학회지, 29(1), pp.11~25 (2023), 대한의생명과학회
- Li T, "TIMER : A web server for comprehensive analysis of tumor-infiltrating immune cells", Cancer Res, 77, pp.e108~e110 (2017)
- Chandrashekar DS, "UALCAN : A portal for facilitating tumor subgroup gene expression and survival analyses", Neoplasia, 19, pp.649~658 (2017)
- Györffy B, "An online survival analysis tool to rapidly assess the effect of 22, 277 genes on breast cancer prognosis using microarray data of 1, 809 patients", Breast Cancer Res Treat, 123, pp.725~731 (2010)
- Vasaikar SV, "LinkedOmics : Analyzing multi-omics data within and across 32 cancer types", Nucleic Acids Res, 46, pp.D956~D963 (2018)
- Tang Z, "GEPIA : A web server for cancer and normal gene expression profiling and interactive analyses", Nucleic Acids Res, 45, pp.W98~W102 (2017)
- Kulik L, "Epidemiology and management of hepato-cellular carcinoma", Gastroenterology, 156, pp.477~491 (2019)
- Wallace MC, "The evolving epidemiology of hepatocellular carcinoma : A global perspective", Expert Rev Gastroenterol Hepatol, 9, pp.765~779 (2015)
- Goswami KK, "Tumor promoting role of anti-tumor macrophages in tumor microenvironment", Cell Immunol, 316, pp.1~10 (2017)
- Bremnes RM, "The role of tumor-infiltrating immune cells and chronic inflammation at the tumor site on cancer development, progression, and prognosis: emphasis on non-small cell lung cancer", J Thorac Oncol, 6, pp.824~833 (2011)
- Harding JJ, "Biomarkers : What role do they play(if any)for diagnosis, prognosis and tumor response prediction for hepatocellular carcinoma?", Dig Dis Sci, 64, pp.918~927 (2019)
- Ma LJ, "Clinical significance of PD-1", PD-Ls gene amplification and overexpression in patients with hepatocellular carcinoma, 2018, pp.8, 5690~5702
- Sun H, "Human CD96 correlates to natural killer cell exhaustion and predicts the prognosis of human hepatocellular carcinoma", Hepatology, 70, pp.168~183 (2019)
- Tian MX, "Tissue-infiltrating lymphocytes signature predicts survival in patients with early", intermediate stage hepatocellular carcinoma, 2019, pp.17, 106~
- Murata Y, "ECT2 amplification and overexpression as a new prognostic biomarker for early-stage lung adenocarcinoma", Cancer Sci, 105, pp.490~497 (2014)
- Wu Z, "Identification of KIF23 as a prognostic biomarker associated with progression of clear cell renal cell carcinoma", Front Cell Dev Biol, 10, pp.839821~ (2022)
- Hu C, "PLK4 is a potential biomarker for abnormal tumor proliferation, immune infiltration, and prognosis in ccRCC", Comput Math Methods Med, 2022, pp.6302234~ (2022)
- He R-Q, "Prognosis prediction ability and prospective biological mechanisms of WDHD1 in hepatocellular carcinoma tissues", Electron J Biotechnol, 55, pp.78~90 (2022)