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Splicing annotation of endometrial cancer GWAS risk loci reveals potentially causal variants and supports a role for NF1 and SKAP1 as susceptibility genes

Canson, D. M.; O'Mara, T. A.; Spurdle, A. B.; Glubb, D. M.

2022-12-16 oncology
10.1101/2022.12.15.22283542 medRxiv
Show abstract

Alternative splicing contributes to cancer development. Indeed, splicing analysis of cancer genome-wide association study (GWAS) risk variants has revealed likely causal variants. To systematically assess GWAS variants for splicing effects, we developed a prioritization workflow using a combination of splicing prediction tools, alternative transcript isoform and splicing quantitative trait locus (sQTL) annotations. Application of this workflow to candidate causal variants from 16 endometrial cancer GWAS risk loci highlighted single nucleotide polymorphisms (SNPs) that were predicted to upregulate alternative transcripts. For two variants, sQTL data supported the predicted impact on splicing. At the 17q11.2 locus, the protective allele for rs7502834 was associated with increased splicing of an exon in NF1 alternative transcript encoding a truncated protein in adipose tissue and is consistent with an endometrial cancer transcriptome-wide association study (TWAS) finding in adipose tissue. Notably, NF1 haploinsufficiency is protective for obesity, a well-established risk factor for endometrial cancer. At the 17q21.32 locus, the rs2278868 risk allele was predicted to upregulate a SKAP1 transcript that is subject to nonsense mediated decay, concordant with a corresponding sQTL in lymphocytes. This is consistent with a TWAS finding that indicates decreased SKAP1 expression in blood increases endometrial cancer risk. As SKAP1 is involved in T-cell immune responses, decreased SKAP1 expression may impact endometrial tumor immunosurveillance. In summary, our analysis has identified potentially causal endometrial cancer GWAS risk variants with plausible biological mechanisms and provides a splicing annotation workflow to aid interpretation of other GWAS datasets.

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