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

通过解读突变状态和可药物靶向癌基因的表达来发现结直肠癌的潜在治疗靶点

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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.

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