Prioritization of drug targets for thyroid cancer: a multi-omics Mendelian randomization study

Objectives: Recurrence or tumor metastasis and drug resistance remain the major challenge in the treatment of thyroid cancer. It is needed to identify novel drug targets for thyroid cancer.

Methods: Summary data-based Mendelian randomization (SMR) and colocalization analysis were performed to evaluate the associations between gene methylation, expression, protein levels with thyroid cancer. We additionally performed protein-protein interaction (PPI) network, gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analyses to further explore the potential roles of identified genes in thyroid cancer.

Results: SDCCAG8 and VCAM1 genes were associated with risk of thyroid cancer with tier 1 evidence, while TCN2 gene was with tier 3 evidence. SDCCAG8 gene was associated with risk of papillary thyroid cancer with tier 1 evidence. At the level of circulating proteins, genetically predicted higher levels of SDCCAG8 (OR = 0.46, 95% CI 0.34-0.64) and VCAM1 (OR = 0.21, 95% CI 0.10-0.45) were inversely associated with thyroid cancer risk; higher level of TCN2 was associated with an increased risk of thyroid cancer (OR = 1.30, 95% CI 1.15-1.47); and the higher level of SDCCAG8 (OR = 0.40, 95% CI 0.28-0.58) was associated with a decreased risk of papillary thyroid cancer. The bioinformatics analysis showed that SDCCAG8, VCAM1 and TCN2 might play roles in immune-related pathways.

Conclusion: SDCCAG8, VCAM1 and TCN2 genes were associated with thyroid cancer risk with evidence at multi-omics levels. There were potential roles of SDCCAG8, VCAM1 and TCN2 in immune-related pathways. Our findings might improve the understanding of the pathogenesis of thyroid cancer and discovery of novel potential drug targets for this disease.