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Zou Y, Sun H, Guo Y, Shi Y, Jiang Z, Huang J, Li L, Jiang F, Lin Z, Wu J, Zhou R, Liu Y, Ao L. Integrative Pan-Cancer Analysis Reveals Decreased Melatonergic Gene Expression in Carcinogenesis and RORA as a Prognostic Marker for Hepatocellular Carcinoma. Front Oncol 2021; 11:643983. [PMID: 33842355 PMCID: PMC8029983 DOI: 10.3389/fonc.2021.643983] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 03/02/2021] [Indexed: 12/13/2022] Open
Abstract
Background Melatonin has been shown to play a protective role in the development and progression of cancer. However, the relationship between alterations in the melatonergic microenvironment and cancer development has remained unclear. Methods We performed a comprehensive investigation on 12 melatonergic genes and their relevance to cancer occurrence, progression and survival by integrating multi-omics data from microarray analysis and RNA sequencing across 11 cancer types. Specifically, the 12 melatonergic genes that we investigated, which reflect the melatonergic microenvironment, included three membrane receptor genes, three nuclear receptor genes, two intracellular receptor genes, one synthetic gene, and three metabolic genes. Results Widely coherent underexpression of nuclear receptor genes, intracellular receptor genes, and metabolic genes was observed in cancerous samples from multiple cancer types compared to that in normal samples. Furthermore, genomic and/or epigenetic alterations partially contributed to these abnormal expression patterns in cancerous samples. Moreover, the majority of melatonergic genes had significant prognostic effects in predicting overall survival. Nevertheless, few corresponding alterations in expression were observed during cancer progression, and alterations in expression patterns varied greatly across cancer types. However, the association of melatonergic genes with one specific cancer type, hepatocellular carcinoma, identified RORA as a tumor suppressor and a prognostic marker for patients with hepatocellular carcinoma. Conclusions Overall, our study revealed decreased melatonergic gene expression in various cancers, which may help to better elucidate the relationship between melatonin and cancer development. Taken together, our findings highlight the potential prognostic significance of melatonergic genes in various cancers.
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Affiliation(s)
- Yi Zou
- Department of Automation and Key Laboratory of China MOE for System Control and Information Processing, Shanghai Jiao Tong University, Shanghai, China.,Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Huaqin Sun
- Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Yating Guo
- Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Yidan Shi
- Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Zhiyu Jiang
- Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Jingxuan Huang
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Li Li
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.,Department of Cell Biology and Genetics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Fengle Jiang
- Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Zeman Lin
- Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Junling Wu
- Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Ruixiang Zhou
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.,Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Yuncai Liu
- Department of Automation and Key Laboratory of China MOE for System Control and Information Processing, Shanghai Jiao Tong University, Shanghai, China
| | - Lu Ao
- Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.,Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
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