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Zhang M, Wang X, Yang N, Zhu X, Lu Z, Cai Y, Li B, Zhu Y, Li X, Wei Y, Zhang S, Tian J, Miao X. Prioritization of risk genes in colorectal cancer by integrative analysis of multi-omics data and gene networks. SCIENCE CHINA. LIFE SCIENCES 2024; 67:132-148. [PMID: 37747674 DOI: 10.1007/s11427-023-2439-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 08/26/2023] [Indexed: 09/26/2023]
Abstract
Genome-wide association studies (GWASs) have identified over 140 colorectal cancer (CRC)-associated loci; however, target genes at the majority of loci and underlying molecular mechanisms are poorly understood. Here, we utilized a Bayesian approach, integrative risk gene selector (iRIGS), to prioritize risk genes at CRC GWAS loci by integrating multi-omics data. As a result, a total of 105 high-confidence risk genes (HRGs) were identified, which exhibited strong gene dependencies for CRC and enrichment in the biological processes implicated in CRC. Among the 105 HRGs, CEBPB, located at the 20q13.13 locus, acted as a transcription factor playing critical roles in cancer. Our subsequent assays indicated the tumor promoter function of CEBPB that facilitated CRC cell proliferation by regulating multiple oncogenic pathways such as MAPK, PI3K-Akt, and Ras signaling. Next, by integrating a fine-mapping analysis and three independent case-control studies in Chinese populations consisting of 8,039 cases and 12,775 controls, we elucidated that rs1810503, a putative functional variant regulating CEBPB, was associated with CRC risk (OR=0.90, 95%CI=0.86-0.93, P=1.07×10-7). The association between rs1810503 and CRC risk was further validated in three additional multi-ancestry populations consisting of 24,254 cases and 58,741 controls. Mechanistically, the rs1810503 A to T allele change weakened the enhancer activity in an allele-specific manner to decrease CEBPB expression via long-range promoter-enhancer interactions, mediated by the transcription factor, REST, and thus decreased CRC risk. In summary, our study provides a genetic resource and a generalizable strategy for CRC etiology investigation, and highlights the biological implications of CEBPB in CRC tumorigenesis, shedding new light on the etiology of CRC.
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Affiliation(s)
- Ming Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
- Research Center of Public Health, Renmin hospital of Wuhan University, Wuhan University, Wuhan, 430060, China
| | - Xiaoyang Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, 450008, China
| | - Nan Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
- Research Center of Public Health, Renmin hospital of Wuhan University, Wuhan University, Wuhan, 430060, China
| | - Xu Zhu
- Department of Gastrointestinal Surgery, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
| | - Bin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
| | - Xiangpan Li
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, Wuhan, 430060, China
| | - Yongchang Wei
- Department of Gastrointestinal Oncology, Hubei Cancer Clinical Study Center, Zhongnan Hospital of Wuhan University, Wuhan, 430062, China
| | - Shaokai Zhang
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, 450008, China.
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China.
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China.
- Research Center of Public Health, Renmin hospital of Wuhan University, Wuhan University, Wuhan, 430060, China.
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan, 430071, China.
- Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
- Department of Radiation Oncology, Renmin Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China.
- Research Center of Public Health, Renmin hospital of Wuhan University, Wuhan University, Wuhan, 430060, China.
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430073, China.
- Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, 211166, China.
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Wu Y, Xu J, Tan B, Yi T, Liu S, Yang G, Li K, Zhao X. SMAD7 gene polymorphisms and their influence on patients with colorectal cancer. Cell Cycle 2023; 22:2424-2435. [PMID: 38146644 PMCID: PMC10802200 DOI: 10.1080/15384101.2023.2296210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 12/13/2023] [Indexed: 12/27/2023] Open
Abstract
Colorectal cancer (CRC) is a prevalent malignant tumor, and its pathogenesis is still not fully understood. Studies have shown that SMAD7 gene polymorphisms can affect CRC susceptibility, but the results have been inconsistent and require additional confirmation. Our study aimed to evaluate the effect of SMAD7 variants on the risk of CRC in the Chinese Han population. A total of five single nucleotide polymorphisms (SNPs) in SMAD7 were genotyped among 696 CRC patients and 696 healthy participants using the MassARRAY iPLEX platform. SNPs were evaluated for their associations with CRC using logistic regression analysis under multiple genetic models. The false-positive report probability (FPRP) analysis was used to validate the positive findings. Our study indicated that rs11874392 showed an increased association with CRC risk (odds ratio, 1.31; 95% confidence interval, 1.04-1.67; p = 0.024). Stratified analysis showed that rs11874392 might increase the risk of CRC in females (OR = 1.70, p = 0.028), individuals with smoking (OR = 1.87, p = 0.026), and drinking (OR = 1.38, p = 0.027). The rs11874392 was found to be related to an elevated risk of rectal cancer (OR = 1.73, p = 0.003), but not with colon cancer. FPRP analysis demonstrated that all of these associations were statistically significant (FPRP <0.2). Additionally, rs11874392 was the strongest predictive model for CRC. This study provides evidence that the SMAD7 rs11874392 is related to an increased susceptibility to CRC.
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Affiliation(s)
- Yongsheng Wu
- Department of Oncology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
- The Second Ward of Oncology and Hematology Department, The People’s Hospital of XiangXiang, Xiangxiang, China
| | - Jue Xu
- Department of Intrarenal Rheumatology and Immunology, The People’s Hospital of XiangXiang, Xiangxiang, China
| | - Biaobin Tan
- The Second Ward of Oncology and Hematology Department, The People’s Hospital of XiangXiang, Xiangxiang, China
| | - Ting Yi
- The Second Ward of Oncology and Hematology Department, The People’s Hospital of XiangXiang, Xiangxiang, China
| | - Su Liu
- The Second Ward of Oncology and Hematology Department, The People’s Hospital of XiangXiang, Xiangxiang, China
| | - Guang Yang
- The Second Ward of Oncology and Hematology Department, The People’s Hospital of XiangXiang, Xiangxiang, China
| | - Kai Li
- The Second Ward of Oncology and Hematology Department, The People’s Hospital of XiangXiang, Xiangxiang, China
| | - Xinhan Zhao
- Department of Oncology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
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Chen X, Han M, Li Y, Li X, Zhang J, Zhu Y. Identification of functional gene modules by integrating multi-omics data and known molecular interactions. Front Genet 2023; 14:1082032. [PMID: 36760999 PMCID: PMC9902936 DOI: 10.3389/fgene.2023.1082032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 01/11/2023] [Indexed: 01/25/2023] Open
Abstract
Multi-omics data integration has emerged as a promising approach to identify patient subgroups. However, in terms of grouping genes (or gene products) into co-expression modules, data integration methods suffer from two main drawbacks. First, most existing methods only consider genes or samples measured in all different datasets. Second, known molecular interactions (e.g., transcriptional regulatory interactions, protein-protein interactions and biological pathways) cannot be utilized to assist in module detection. Herein, we present a novel data integration framework, Correlation-based Local Approximation of Membership (CLAM), which provides two methodological innovations to address these limitations: 1) constructing a trans-omics neighborhood matrix by integrating multi-omics datasets and known molecular interactions, and 2) using a local approximation procedure to define gene modules from the matrix. Applying Correlation-based Local Approximation of Membership to human colorectal cancer (CRC) and mouse B-cell differentiation multi-omics data obtained from The Cancer Genome Atlas (TCGA), Clinical Proteomics Tumor Analysis Consortium (CPTAC), Gene Expression Omnibus (GEO) and ProteomeXchange database, we demonstrated its superior ability to recover biologically relevant modules and gene ontology (GO) terms. Further investigation of the colorectal cancer modules revealed numerous transcription factors and KEGG pathways that played crucial roles in colorectal cancer progression. Module-based survival analysis constructed four survival-related networks in which pairwise gene correlations were significantly correlated with colorectal cancer patient survival. Overall, the series of evaluations demonstrated the great potential of Correlation-based Local Approximation of Membership for identifying modular biomarkers for complex diseases. We implemented Correlation-based Local Approximation of Membership as a user-friendly application available at https://github.com/free1234hm/CLAM.
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Affiliation(s)
- Xiaoqing Chen
- Basic Medical School, Anhui Medical University, Hefei, China,National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing, China
| | - Mingfei Han
- National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing, China
| | - Yingxing Li
- Central Research Laboratory, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiao Li
- National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing, China
| | - Jiaqi Zhang
- National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing, China
| | - Yunping Zhu
- Basic Medical School, Anhui Medical University, Hefei, China,National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing, China,*Correspondence: Yunping Zhu,
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