Dataset Information

Uncovering Potential Therapeutic Targets in Colorectal Cancer by Deciphering Mutational Status and Expression of Druggable Oncogenes.

ABSTRACT:

Background

Numerous driver mutations have been identified in colorectal cancer (CRC), but their relevance to the development of targeted therapies remains elusive. The secondary effects of pathogenic driver mutations on downstream signaling pathways offer a potential approach for the identification of therapeutic targets. We aimed to identify differentially expressed genes as potential drug targets linked to driver mutations.

Methods

Somatic mutations and the gene expression data of 582 CRC patients were utilized, incorporating the mutational status of 39,916 and the expression levels of 20,500 genes. To uncover candidate targets, the expression levels of various genes in wild-type and mutant cases for the most frequent disruptive mutations were compared with a Mann-Whitney test. A survival analysis was performed in 2100 patients with transcriptomic gene expression data. Up-regulated genes associated with worse survival were filtered for potentially actionable targets. The most significant hits were validated in an independent set of 171 CRC patients.

Results

Altogether, 426 disruptive mutation-associated upregulated genes were identified. Among these, 95 were linked to worse recurrence-free survival (RFS). Based on the druggability filter, 37 potentially actionable targets were revealed. We selected seven genes and validated their expression in 171 patient specimens. The best independently validated combinations were DUSP4 (p = 2.6 × 10^-12) in ACVR2A mutated (7.7%) patients; BMP4 (p = 1.6 × 10^-04) in SOX9 mutated (8.1%) patients; TRIB2 (p = 1.35 × 10^-14) in ACVR2A mutated patients; VSIG4 (p = 2.6 × 10^-05) in ANK3 mutated (7.6%) patients, and DUSP4 (p = 7.1 × 10^-04) in AMER1 mutated (8.2%) patients.

Conclusions

The results uncovered potentially druggable genes in colorectal cancer. The identified mutations could enable future patient stratification for targeted therapy.

SUBMITTER: Menyhart O

PROVIDER: S-EPMC6679198 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Uncovering Potential Therapeutic Targets in Colorectal Cancer by Deciphering Mutational Status and Expression of Druggable Oncogenes.

Menyhart Otília O Kakisaka Tatsuhiko T Pongor Lőrinc Sándor LS Uetake Hiroyuki H Goel Ajay A Győrffy Balázs B

Cancers 20190714 7

<h4>Background</h4>Numerous driver mutations have been identified in colorectal cancer (CRC), but their relevance to the development of targeted therapies remains elusive. The secondary effects of pathogenic driver mutations on downstream signaling pathways offer a potential approach for the identification of therapeutic targets. We aimed to identify differentially expressed genes as potential drug targets linked to driver mutations.<h4>Methods</h4>Somatic mutations and the gene expression data ...[more]

PMID: 31337155

Similar Datasets

Project description:The aim of the present study was to identify potential therapeutic targets for colorectal cancer (CRC). The gene expression profile GSE32323, containing 34 samples, including 17 specimens of CRC tissues and 17 of paired normal tissues from CRC patients, was downloaded from the Gene Expression Omnibus database. Following data preprocessing using the Affy and preprocessCore packages, the differentially-expressed genes (DEGs) between the two types of samples were identified with the Linear Models for Microarray Analysis package. Next, functional and pathway enrichment analysis of the DEGs was performed using the Database for Annotation Visualization and Integrated Discovery. The protein-protein interaction (PPI) network was established using the Search Tool for the Retrieval of Interacting Genes database. Utilizing WebGestalt, the potential microRNAs (miRNAs/miRs) of the DEGs were screened and the integrated miRNA-target network was built. A cohort of 1,347 DEGs was identified, the majority of which were mainly enriched in cell cycle-related biological processes and pathways. Cyclin-dependent kinase 1 (CDK1), cyclin B1 (CCNB1), MAD2 mitotic arrest deficient-like 1 (MAD2L1) and BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) were prominent in the PPI network, while the over-represented genes in the integrated miRNA-target network were SRY (sex determining region Y)-box 4 (SOX4; targeted by hsa-mir-129), v-myc avian myelocytomatosis viral oncogene homolog (MYC; targeted by hsa-let-7c and hsa-mir-145) and cyclin D1 (CCND1; targeted by hsa-let-7b). CDK1, CCNB1 and CCND1 were also associated with the p53 signaling pathway. Overall, several genes associated with the cell cycle and p53 pathway were identified as biomarkers for CRC. CDK1, CCNB1, MAD2L1, BUB1B, SOX4, collagen type I ?2 chain and MYC may play significant roles in CRC progression by affecting the cell cycle-related pathways, while CDK1, CCNB1 and CCND1 may serve as crucial regulators in the p53 signaling pathway. Furthermore, SOX4, MYC and CCND1 may be targets of miR-129, hsa-mir-145 and hsa-let-7c, respectively. However, further validation of these data is required.

Dataset Information

Uncovering Potential Therapeutic Targets in Colorectal Cancer by Deciphering Mutational Status and Expression of Druggable Oncogenes.

Background

Methods

Results

Conclusions

Publications

Uncovering Potential Therapeutic Targets in Colorectal Cancer by Deciphering Mutational Status and Expression of Druggable Oncogenes.

Similar Datasets

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