Prediction of EVT6-NTRK3-Dependent Papillary Thyroid Cancer Using Minor Expression Profile.

Abstract

Solid tumors resulting from oncogenic stimulation of neurotrophin receptors (TRK) by chimeric proteins are a group of rare tumors of various localization that respond to therapy with targeted drugs entrectinib and larotrectinib. The standard method for detecting chimeric TRK genes in tumor samples today is considered to be next generation sequencing with the determination of the prime structure of the chimeric transcripts. We hypothesized that expression of the chimeric tyrosine kinase proteins in tumors can determine the specific transcriptomic profile of tumor cells. We detected differentially expressed genes allowing distinguishing between TRK-dependent tumors papillary thyroid cancer (TC) from other molecular variants of tumors of this type. Using PCR with reverse transcription (RT-PCR), we identified 7 samples of papillary TC carrying a EVT6-NTRK3 rearrangement (7/215, 3.26%). Using machine learning and the data extracted from TCGA, we developed of a recognition function for predicting the presence of rearrangement in NTRK genes based on the expression of 10 key genes: AUTS2, DTNA, ERBB4, HDAC1, IGF1, KDR, NTRK1, PASK, PPP2R5B, and PRSS1. The recognition function was used to analyze the expression data of the above genes in 7 TRK-dependent and 10 TRK-independent thyroid tumors obtained by RT-PCR. On the test samples from TCGA, the sensitivity was 72.7%, the specificity - 99.6%. On our independent validation samples tested by RT-PCR, sensitivity was 100%, specificity - 70%. We proposed an mRNA profile of ten genes that can classify TC in relation to the presence of driver NTRK-chimeric TRK genes with acceptable sensitivity and specificity.