CTNNB1, PIK3CA, EIF1AX, and PTEN polymorphisms found in aggressive types of differentiated thyroid cancer.

Dauren Adilbay, G. Adilbayev, Madina Orazgaliyeva, Viktoria Shipilova, Gulzhan Kidirbayeva, N. Sloneva, Aizhan Amandosova, S. Ossikbayeva

2020

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DOI 10.1200/jco.2020.38.15_suppl.e18578
Data confidence 70 medium
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Abstract

e18578 Background: Thyroid cancer incidence is rapidly increasing in all developing and developed nations. Despite the benign nature of most thyroid cases, there are aggressively behaving subgroups that need proper attention and tailored treatment. As of today, thyroid cancers stratified using the latest AJCC 8th edition staging system, which dramatically changed the staging system. Despite the implementation of the new system, there is still a need for better stratification of patients to groups that will benefit from extensive treatment. Methods: Retrospective analysis of 23 patients with papillary and follicular thyroid cancer treated in a tertiary cancer center in 2012 and 2013. All patients underwent different types of surgical treatment, FFPE blocks are obtained from pathology archives and additionally reviewed by two independent pathologists. DNA extracted from 20 patients FFPE blocks; 3 cases excluded. DNA analyzed by NGS on the MiniSeq Illumina platform using a custom panel of 14 genes and 200 SNPs associated with thyroid cancers. Results: All identified polymorphisms were selected based on the COSMIC registry. After excluding all types filtered based on frequency, 1329 polymorphisms identified. Fifty-two types are pathologic based on ClinVar database. All benign cases based on Polyphen and Clinvar excluded from the analysis. In patients with aggressive types of papillary and follicular thyroid cancer NRAS and HRAS identified in 8.33% cases, EIF1AX in 25% cases, PIK3CA in 58.33% cases, KRAS in 41.66 cases, TSHR in 33.3% cases and BRAF in 50% cases. Conclusions: We identified mutations in genes probably associated with the aggressive behavior of differentiated thyroid cancer. These mutations can be used as stratification criteria in the future after more data and trials confirm the results.