Xiangcheng Zhang, Ce Liang, Bingchuan Zhou, Liming Pang
{"title":"基于线粒体能量代谢途径相关基因的结肠癌预后模型的构建及其临床意义。","authors":"Xiangcheng Zhang, Ce Liang, Bingchuan Zhou, Liming Pang","doi":"10.1002/jmr.3044","DOIUrl":null,"url":null,"abstract":"<p>Mitochondria are the main sites of oxidative metabolism and energy release of sugars, fats and amino acids in the body. According to studies, malignant tumor occurrence and development have been linked to abnormal mitochondrial energy metabolism (MEM). However, the feasible role of abnormal MEM in colon adenocarcinoma (COAD) is poorly understood. In this work, we obtained COAD patient data from The Cancer Genome Atlas (TCGA) as the training set, and GSE103479 from Gene Expression Omnibus (GEO) as the validation set. Combined with the mitochondrial energy metabolic pathway (MEMP)-related genes in Kyoto Encyclopedia of Genes and Genomes (KEGG) database, a risk prognostic model was constructed by utilizing Cox regression analysis to identify 6 feature genes (CYP4A11, PGM2, PKLR, PPARGC1A, CPT2 and ACAT2) that were significantly associated with MEMP in COAD. By stratifying the samples based on riskscore, two distinct groups, namely the high- and low-risk groups, were identified. The model demonstrated accurate assessment of the prognosis risk in COAD patients and exhibited independent prognostic capability, as evidenced by the survival curve and receiver operating characteristic (ROC) curve analysis. A nomogram was plotted based on clinical information and riskscore. We proved it could predict the survival time of COAD patients effectively combined with the calibration curve of risk prediction. Subsequently, based on the immune evaluation and mutation frequency analysis performed on COAD patients, patients in high-risk group had observably higher immune scores, immune activity and PDCD1 expression level than low-risk group. In general, the prognostic model developed using MEMP-related genes served as a valuable biomarker for forecasting the prognosis of COAD patients, which offered a reference for the prognosis evaluation and clinical cure of COAD patients.</p>","PeriodicalId":16531,"journal":{"name":"Journal of Molecular Recognition","volume":"36 8","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Construction of a prognostic model based on genes associated with mitochondrial energy metabolic pathway in colon adenocarcinoma and its clinical significance\",\"authors\":\"Xiangcheng Zhang, Ce Liang, Bingchuan Zhou, Liming Pang\",\"doi\":\"10.1002/jmr.3044\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Mitochondria are the main sites of oxidative metabolism and energy release of sugars, fats and amino acids in the body. According to studies, malignant tumor occurrence and development have been linked to abnormal mitochondrial energy metabolism (MEM). However, the feasible role of abnormal MEM in colon adenocarcinoma (COAD) is poorly understood. In this work, we obtained COAD patient data from The Cancer Genome Atlas (TCGA) as the training set, and GSE103479 from Gene Expression Omnibus (GEO) as the validation set. Combined with the mitochondrial energy metabolic pathway (MEMP)-related genes in Kyoto Encyclopedia of Genes and Genomes (KEGG) database, a risk prognostic model was constructed by utilizing Cox regression analysis to identify 6 feature genes (CYP4A11, PGM2, PKLR, PPARGC1A, CPT2 and ACAT2) that were significantly associated with MEMP in COAD. By stratifying the samples based on riskscore, two distinct groups, namely the high- and low-risk groups, were identified. The model demonstrated accurate assessment of the prognosis risk in COAD patients and exhibited independent prognostic capability, as evidenced by the survival curve and receiver operating characteristic (ROC) curve analysis. A nomogram was plotted based on clinical information and riskscore. We proved it could predict the survival time of COAD patients effectively combined with the calibration curve of risk prediction. Subsequently, based on the immune evaluation and mutation frequency analysis performed on COAD patients, patients in high-risk group had observably higher immune scores, immune activity and PDCD1 expression level than low-risk group. In general, the prognostic model developed using MEMP-related genes served as a valuable biomarker for forecasting the prognosis of COAD patients, which offered a reference for the prognosis evaluation and clinical cure of COAD patients.</p>\",\"PeriodicalId\":16531,\"journal\":{\"name\":\"Journal of Molecular Recognition\",\"volume\":\"36 8\",\"pages\":\"\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2023-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Molecular Recognition\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/jmr.3044\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Molecular Recognition","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/jmr.3044","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Construction of a prognostic model based on genes associated with mitochondrial energy metabolic pathway in colon adenocarcinoma and its clinical significance
Mitochondria are the main sites of oxidative metabolism and energy release of sugars, fats and amino acids in the body. According to studies, malignant tumor occurrence and development have been linked to abnormal mitochondrial energy metabolism (MEM). However, the feasible role of abnormal MEM in colon adenocarcinoma (COAD) is poorly understood. In this work, we obtained COAD patient data from The Cancer Genome Atlas (TCGA) as the training set, and GSE103479 from Gene Expression Omnibus (GEO) as the validation set. Combined with the mitochondrial energy metabolic pathway (MEMP)-related genes in Kyoto Encyclopedia of Genes and Genomes (KEGG) database, a risk prognostic model was constructed by utilizing Cox regression analysis to identify 6 feature genes (CYP4A11, PGM2, PKLR, PPARGC1A, CPT2 and ACAT2) that were significantly associated with MEMP in COAD. By stratifying the samples based on riskscore, two distinct groups, namely the high- and low-risk groups, were identified. The model demonstrated accurate assessment of the prognosis risk in COAD patients and exhibited independent prognostic capability, as evidenced by the survival curve and receiver operating characteristic (ROC) curve analysis. A nomogram was plotted based on clinical information and riskscore. We proved it could predict the survival time of COAD patients effectively combined with the calibration curve of risk prediction. Subsequently, based on the immune evaluation and mutation frequency analysis performed on COAD patients, patients in high-risk group had observably higher immune scores, immune activity and PDCD1 expression level than low-risk group. In general, the prognostic model developed using MEMP-related genes served as a valuable biomarker for forecasting the prognosis of COAD patients, which offered a reference for the prognosis evaluation and clinical cure of COAD patients.
期刊介绍:
Journal of Molecular Recognition (JMR) publishes original research papers and reviews describing substantial advances in our understanding of molecular recognition phenomena in life sciences, covering all aspects from biochemistry, molecular biology, medicine, and biophysics. The research may employ experimental, theoretical and/or computational approaches.
The focus of the journal is on recognition phenomena involving biomolecules and their biological / biochemical partners rather than on the recognition of metal ions or inorganic compounds. Molecular recognition involves non-covalent specific interactions between two or more biological molecules, molecular aggregates, cellular modules or organelles, as exemplified by receptor-ligand, antigen-antibody, nucleic acid-protein, sugar-lectin, to mention just a few of the possible interactions. The journal invites manuscripts that aim to achieve a complete description of molecular recognition mechanisms between well-characterized biomolecules in terms of structure, dynamics and biological activity. Such studies may help the future development of new drugs and vaccines, although the experimental testing of new drugs and vaccines falls outside the scope of the journal. Manuscripts that describe the application of standard approaches and techniques to design or model new molecular entities or to describe interactions between biomolecules, but do not provide new insights into molecular recognition processes will not be considered. Similarly, manuscripts involving biomolecules uncharacterized at the sequence level (e.g. calf thymus DNA) will not be considered.