R Luo1,2, W Guo1,2, H Wang3,4. 1. Department of Colorectal Surgery, The Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510655, People's Republic of China. 2. Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510655, People's Republic of China. 3. Department of Colorectal Surgery, The Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510655, People's Republic of China. wang89@mail.sysu.edu.cn. 4. Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510655, People's Republic of China. wang89@mail.sysu.edu.cn.
Abstract
BACKGROUND: The development and progression of colon cancer are significantly affected by the tumor microenvironment, which has attracted much attention. The goal of our study was primarily to find out all possible tumor microenvironment-related genes in colon cancer. METHOD: This study quantified the immune and stromal landscape using the ESTIMATION algorithm using the gene expression matrix obtained from the UCSC Xena database. Dysregulated genes were harvested using the limma R package, and relevant pathways and biofunctions were identified using enrichment analysis. A least absolute shrinkage and selection operator (LASSO) regression was used to select the pivotal genes from the DEGs. Then, survival analysis was performed to determine the hub genes and a prognostic model was constructed by these hub genes with (or) TNM stage. Besides, associations between hub gene expressions and immune cell infiltration were assessed. RESULTS: A total of 725 DEGs were identified. Most of the results of the enrichment analysis were immune-related items. 13 genes were selected as the hub genes and a moderate-to-strong positive correlation between most hub genes and several immune cells were observed. Besides, the prognostic value of the hub genes were comparable to TNM staging. CONCLUSIONS: Our study provides a better understanding of how interactions between the 13 immune-prognostic hub genes and immune cells in the tumor microenvironment affect biological processes in colon cancer. These genes exhibit an equivalent ability to TNM staging in prognosis prediction. They are particularly expected to become novel prognostic biomarkers and targets of immunotherapies for colon cancer.
BACKGROUND: The development and progression of colon cancer are significantly affected by the tumor microenvironment, which has attracted much attention. The goal of our study was primarily to find out all possible tumor microenvironment-related genes in colon cancer. METHOD: This study quantified the immune and stromal landscape using the ESTIMATION algorithm using the gene expression matrix obtained from the UCSC Xena database. Dysregulated genes were harvested using the limma R package, and relevant pathways and biofunctions were identified using enrichment analysis. A least absolute shrinkage and selection operator (LASSO) regression was used to select the pivotal genes from the DEGs. Then, survival analysis was performed to determine the hub genes and a prognostic model was constructed by these hub genes with (or) TNM stage. Besides, associations between hub gene expressions and immune cell infiltration were assessed. RESULTS: A total of 725 DEGs were identified. Most of the results of the enrichment analysis were immune-related items. 13 genes were selected as the hub genes and a moderate-to-strong positive correlation between most hub genes and several immune cells were observed. Besides, the prognostic value of the hub genes were comparable to TNM staging. CONCLUSIONS: Our study provides a better understanding of how interactions between the 13 immune-prognostic hub genes and immune cells in the tumor microenvironment affect biological processes in colon cancer. These genes exhibit an equivalent ability to TNM staging in prognosis prediction. They are particularly expected to become novel prognostic biomarkers and targets of immunotherapies for colon cancer.
Authors: Mikhail Binnewies; Edward W Roberts; Kelly Kersten; Vincent Chan; Douglas F Fearon; Miriam Merad; Lisa M Coussens; Dmitry I Gabrilovich; Suzanne Ostrand-Rosenberg; Catherine C Hedrick; Robert H Vonderheide; Mikael J Pittet; Rakesh K Jain; Weiping Zou; T Kevin Howcroft; Elisa C Woodhouse; Robert A Weinberg; Matthew F Krummel Journal: Nat Med Date: 2018-04-23 Impact factor: 53.440
Authors: Shubha Vij; Heiner Kuhl; Inna S Kuznetsova; Aleksey Komissarov; Andrey A Yurchenko; Peter Van Heusden; Siddharth Singh; Natascha M Thevasagayam; Sai Rama Sridatta Prakki; Kathiresan Purushothaman; Jolly M Saju; Junhui Jiang; Stanley Kimbung Mbandi; Mario Jonas; Amy Hin Yan Tong; Sarah Mwangi; Doreen Lau; Si Yan Ngoh; Woei Chang Liew; Xueyan Shen; Lawrence S Hon; James P Drake; Matthew Boitano; Richard Hall; Chen-Shan Chin; Ramkumar Lachumanan; Jonas Korlach; Vladimir Trifonov; Marsel Kabilov; Alexey Tupikin; Darrell Green; Simon Moxon; Tyler Garvin; Fritz J Sedlazeck; Gregory W Vurture; Gopikrishna Gopalapillai; Vinaya Kumar Katneni; Tansyn H Noble; Vinod Scaria; Sridhar Sivasubbu; Dean R Jerry; Stephen J O'Brien; Michael C Schatz; Tamás Dalmay; Stephen W Turner; Si Lok; Alan Christoffels; László Orbán Journal: PLoS Genet Date: 2016-12-09 Impact factor: 5.917
Authors: Weiwen Deng; Victor Lira; Thomas E Hudson; Edward E Lemmens; William G Hanson; Ruben Flores; Gonzalo Barajas; George E Katibah; Anthony L Desbien; Peter Lauer; Meredith L Leong; Daniel A Portnoy; Thomas W Dubensky Journal: Proc Natl Acad Sci U S A Date: 2018-07-23 Impact factor: 11.205