Deciphering tranSNPs: functional genetic variants shaping protein output and cancer-related phenotypes

This study investigates the impact of genetic diversity, in the form of single-nucleotide polymorphisms (SNPs), on the post-transcriptional control of gene expression, to identify a novel class of functional SNPs, named tranSNPs, with potential applications as biomarkers for cancer diagnosis, prognosis, or targeted therapy; tranSNPs are defined as SNPs whose allelic fraction is significantly imbalanced across polysome-bound and total mRNAs. We provide a comprehensive characterization of tranSNPs and their implications by exploring their cell line and cancer-type specificity, as well as their mechanistic insights focusing on the rs1053639 tranSNP (T/A) on DDIT4 3’UTR. This example demonstrated that a 3’UTR SNP can significantly affect mRNA localization, modification, and polysomal recruitment through allele-specific interaction with the trans-factor RBMX, eventually causing allele-specific differences in protein levels and downstream phenotypes related to cancer. Indeed, autophagy, cell competition, and in vivo xenotransplantation were significantly affected across TT and AA clones homozygous for the SNP. Furthermore, analysis of TCGA colorectal cancer data revealed that rs1053639 alleles are prognostic for disease-free interval (DFI), and we uncovered allele-specific sensitivities to a number of compounds. When further explored, tranSNPs could become an uncharted source of SNPs to be used as biomarkers for cancer prognosis and to guide treatments based on SNP genotype in the context of personalized medicine.