Xi Xu1, Chaoju Gong2, Yunfeng Wang3, Yanyan Hu4, Hong Liu5,6, Zejun Fang4,7. 1. Department of Pathology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China. 2. Central Laboratory, The Municipal Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221106, PR China. 3. Institute for Integrative Biology of the Cell, UMR 9198, CNRS, Commissariat à l'Energie Atomique et aux Énergies Alternatives (CEA), Université Paris-Sud, 91198 Gif-sur-Yvette, Palaiseau, 91120, France. 4. Central Laboratory, Sanmen People's Hospital of Zhejiang Province, Sanmen, 317100, PR China. 5. Zhejiang Normal University - Jinhua People's Hospital Joint Center for Biomedical Research, Jinhua, 321004, PR China. 6. The Affiliated Hospital of Jinhua Polytechnic College, Jinhua, 321000, PR China. 7. Central Laboratory, Sanmenwan Branch, The First Affiliated Hospital, College of Medicine, Zhejiang University, Sanmen, 317100, PR China.
Abstract
Aim: We aim to identify driving genes of colorectal cancer (CRC) through multi-omics analysis. Materials & methods: We downloaded multi-omics data of CRC from The Cancer Genome Atlas dataset. Integrative analysis of single-nucleotide variants, copy number variations, DNA methylation and differentially expressed genes identified candidate genes that carry CRC risk. Kernal genes were extracted from the weighted gene co-expression network analysis. A competing endogenous RNA network composed of CRC-related genes was constructed. Biological roles of genes were further investigated in vitro. Results: We identified LRRC26 and REP15 as novel prognosis-related driving genes for CRC. LRRC26 hindered tumorigenesis of CRC in vitro. Conclusion: Our study identified novel driving genes and may provide new insights into the molecular mechanisms of CRC.
Aim: We aim to identify driving genes of colorectal cancer (CRC) through multi-omics analysis. Materials & methods: We downloaded multi-omics data of CRC from The Cancer Genome Atlas dataset. Integrative analysis of single-nucleotide variants, copy number variations, DNA methylation and differentially expressed genes identified candidate genes that carry CRC risk. Kernal genes were extracted from the weighted gene co-expression network analysis. A competing endogenous RNA network composed of CRC-related genes was constructed. Biological roles of genes were further investigated in vitro. Results: We identified LRRC26 and REP15 as novel prognosis-related driving genes for CRC. LRRC26 hindered tumorigenesis of CRC in vitro. Conclusion: Our study identified novel driving genes and may provide new insights into the molecular mechanisms of CRC.
Authors: Amrita Rai; Anurag K Singh; Nathalie Bleimling; Guido Posern; Ingrid R Vetter; Roger S Goody Journal: Nat Commun Date: 2022-07-23 Impact factor: 17.694