Lina Wen1,2, Zongqiang Han3, Yanlin Du4. 1. Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China. 2. Department of Oncology, Capital Medical University; Beijing Institute of Integrated Chinese and Western Medicine Oncology, Beijing, China. 3. Department of Laboratory Medicine, Beijing Xiaotangshan Hospital, Beijing, China. 4. Department of Oncology, Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Abstract
BACKGROUND: Compared with colon cancer, the increase of morbidity is more significant for rectal cancer. The current study set out to identify novel and critical biomarkers or features that may be used as promising targets for early diagnosis and treatment monitoring of rectal cancer. METHODS: Microarray datasets of rectal cancer with a minimum sample size of 30 and RNA-sequencing datasets of rectal adenocarcinoma (READ) were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database. The method of robust rank aggregation was utilized to integrate differentially expressed genes (DEGs). The protein-protein interaction (PPI) network of the DEGs was structured using the STRING platform, and hub genes were identified using the Cytoscape plugin cytoHubba and an UpSet diagram. R software was employed to perform functional enrichment analysis. Receiver operating characteristic (ROC) curves based on the GEO data and Kaplan-Meier curves based on the TCGA data were drawn to assess the diagnostic and prognostic values of the hub genes. Immune cell infiltration analysis was conducted with CIBERSORT, and the diagnostic value and correlations between prognostic genes and infiltrated immune cells were analyzed by principal component analysis (PCA), ROC curves, and correlation scatter plots. RESULTS: A total of 137 robust DEGs were obtained by integrating datasets in GEO. Twenty-four hub genes, including CHGA, TTR, SAA1, SPP1, MMP1, TGFBI, COL1A1, and PCK1, were identified as a diagnostic gene biomarker group for rectal cancer, and SAA1, SPP1, and SI were identified as potential novel prognostic biomarkers. Functionally, the hub genes were mainly involved in the rectal cancer related interleukin (IL)-17 and proximal tubule bicarbonate reclamation pathways. Twelve sensitive infiltrated immune cells were identified, and were correlated with prognostic genes. CONCLUSIONS: The integrated gene biomarker group combined with immune cell infiltration can effectively indicate rectal cancer. 2021 Journal of Gastrointestinal Oncology. All rights reserved.
BACKGROUND: Compared with colon cancer, the increase of morbidity is more significant for rectal cancer. The current study set out to identify novel and critical biomarkers or features that may be used as promising targets for early diagnosis and treatment monitoring of rectal cancer. METHODS: Microarray datasets of rectal cancer with a minimum sample size of 30 and RNA-sequencing datasets of rectal adenocarcinoma (READ) were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database. The method of robust rank aggregation was utilized to integrate differentially expressed genes (DEGs). The protein-protein interaction (PPI) network of the DEGs was structured using the STRING platform, and hub genes were identified using the Cytoscape plugin cytoHubba and an UpSet diagram. R software was employed to perform functional enrichment analysis. Receiver operating characteristic (ROC) curves based on the GEO data and Kaplan-Meier curves based on the TCGA data were drawn to assess the diagnostic and prognostic values of the hub genes. Immune cell infiltration analysis was conducted with CIBERSORT, and the diagnostic value and correlations between prognostic genes and infiltrated immune cells were analyzed by principal component analysis (PCA), ROC curves, and correlation scatter plots. RESULTS: A total of 137 robust DEGs were obtained by integrating datasets in GEO. Twenty-four hub genes, including CHGA, TTR, SAA1, SPP1, MMP1, TGFBI, COL1A1, and PCK1, were identified as a diagnostic gene biomarker group for rectal cancer, and SAA1, SPP1, and SI were identified as potential novel prognostic biomarkers. Functionally, the hub genes were mainly involved in the rectal cancer related interleukin (IL)-17 and proximal tubule bicarbonate reclamation pathways. Twelve sensitive infiltrated immune cells were identified, and were correlated with prognostic genes. CONCLUSIONS: The integrated gene biomarker group combined with immune cell infiltration can effectively indicate rectal cancer. 2021 Journal of Gastrointestinal Oncology. All rights reserved.
Authors: Christina E Bailey; Chung-Yuan Hu; Y Nancy You; Brian K Bednarski; Miguel A Rodriguez-Bigas; John M Skibber; Scott B Cantor; George J Chang Journal: JAMA Surg Date: 2015-01 Impact factor: 14.766
Authors: Norihiro Yamaguchi; Ethan M Weinberg; Alexander Nguyen; Maria V Liberti; Hani Goodarzi; Yelena Y Janjigian; Philip B Paty; Leonard B Saltz; T Peter Kingham; Jia Min Loo; Elisa de Stanchina; Sohail F Tavazoie Journal: Elife Date: 2019-12-16 Impact factor: 8.140