Functional annotation with expression validation identifies novel metastasis-relevant genes from post-GWAS risk loci in sporadic colorectal carcinomas

Author:

Thean Lai Fun,Wong Michelle,Lo Michelle,Tan Iain,Wong Evelyn,Gao Fei,Tan Emile,Tang Choong Leong,Cheah Peh YeanORCID

Abstract

AbstractColorectal cancer (CRC) is the third highest incidence cancer and leading cause of cancer mortality worldwide. Metastasis to distal organ is the major cause of cancer mortality. However, the underlying genetic factors are unclear. This study aims to identify metastasis-relevant genes and pathways for better management of metastasis-prone patients. Multiple lines of evidence have indicated that germline variants play important role in shaping the somatic (tumor) genome. A case-case genome-wide association study comprising 2677 sporadic Chinese CRC cases (1282 metastasis-positive vs 1395 metastasis-negative) was performed using the Human SNP6 microarray platform and analyzed with the correlation/trend test based on the additive model. Single nucleotide polymorphism (SNP) variants with association testing -log10p-value ≥ 5 were imported into Functional Mapping and Annotation (FUMA) for functional annotation which uncovered glycolysis as the top hallmark geneset. Transcripts from two of the five genes profiled, HAX1 and HMMR, were significantly down-regulated in the metastasis-positive tumors. In contrast to disease-risk variants with minimal impact on survival, HAX1 appeared to act synergistically with HMMR in significantly impacting metastasis-free survival. Furthermore, examining the subtype datasets with FUMA and Ingenuity Pathway identified distinct pathways demonstrating sexual dimorphism in CRC metastasis. Combining genome-wide association testing with in silico functional annotation and wet-bench validation identified metastasis-relevant genes that could serve as features to develop subtype-specific metastasis-risk signatures for tailored management of Stage I-III CRC patients.

Publisher

Cold Spring Harbor Laboratory

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