Genome-Wide Association and Transcriptome-Wide Association Studies Identify Novel Susceptibility Genes Contributing to Colorectal Cancer

Prioritization of risk genes in colorectal cancer by integrative analysis of multi-omics data and gene networks

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.

SMAD7 gene polymorphisms and their influence on patients with colorectal cancer

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.

Identification of functional gene modules by integrating multi-omics data and known molecular interactions

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.

Evaluation of the Synergistic Potential of Simultaneous Pan- or Isoform-Specific BET and SYK Inhibition in B-Cell Lymphoma: An In Vitro Approach

Simple Summary

B-cell lymphomas represent the majority of non-Hodgkin lymphomas and are the most common lymphoid malignancies in the Western world. Genetic alterations or epigenetic modulations can lead to tumor initiation and tumor progression. Aside from standard care, targeted, individualized therapies can be highly effective. Here, we evaluated the impact of simultaneous specific inhibition of two key regulators involved in B lymphoid tumor progression. Spleen tyrosine kinase (SYK) is a B-cell receptor-associated kinase acting as a proto-oncogene in B-cell malignancies, while bromodomain and extra-terminal domain (BET) proteins are epigenetic reader proteins involved in histone recognition and transcription regulation. The simultaneous inhibition of SYK and BET showed enhanced anti-proliferative effects, as well as inducing a distinct combination-specific gene expression profile, suggesting SYK and BET inhibition as a promising combination in the treatment of B-cell lymphoma.

Abstract

Background: Both bromodomain and extra-terminal domain (BET) proteins and spleen tyrosine kinase (SYK) represent promising targets in diffuse large B-cell (DLBCL) and Burkitt’s lymphoma (BL). We evaluated the anti-lymphoma activity of the isoform-specific bivalent BET inhibitor AZD5153 (AZD) and the pan-BET inhibitor I-BET151 (I-BET) as single agents and in combination with SYK inhibitor Entospletinib (Ento) in vitro. Methods: The effect of the single agents on cell proliferation and metabolic activity was evaluated in two DLBCL and two BL cell lines. Proliferation, metabolic activity, apoptosis, cell cycle and morphology were further investigated after a combined treatment of AZD or I-BET and Ento. RNAseq profiling of combined AZD+Ento treatment was performed in SU-DHL-4 cells. Results: Both BET inhibitors reduced cell proliferation and metabolic activity in a dose- and time-dependent manner. Combined BET and SYK inhibition enhanced the anti-proliferative effect and induced a G0/G1 cell cycle arrest. SU-DHL-4 demonstrated a pronounced modulation of gene expression by AZD, which was markedly increased by additional SYK inhibition. Functional enrichment analyses identified combination-specific GO terms related to DNA replication and cell division. Genes such as ADGRA2, MYB, TNFRSF11A, S100A10, PLEKHH3, DHRS2 and FOXP1-AS1 were identified as possible key regulators. Conclusion: Simultaneous inhibition of BET and SYK enhanced the anti-proliferative effects, and induced a combination-specific gene expression signature.