Endocrine Abstracts

Differentiated thyroid cancer (DTC) has a high survival rate and is usually treated with surgery followed by treatment with radioactive iodine (RAI). However, some patients are refractory to RAI (RAI-R DTC) and show decreased survival. This leads to progression of the disease, and the only approved treatment for those patients are multikinase inhibitors, lenvatinib being the most widely used. However, patients end up developing resistance to MKIs. Here we aim to study the mechanisms of resistance to lenvatinib to identify potential biomarkers of response, as well as potential therapeutic targets. We used the TPC-1 cell line, derived from a papillary thyroid carcinoma, and established a cell line resistant to lenvatinib (TPC-1 LR) by treating the cells with gradually increasing doses of lenvatinib for 6 months. To better understand the mechanisms by which drug resistance arises, we analysed the transcriptome using single-cell RNA-sequencing (scRNA-seq) for two controls (parental TPC-1 and TPC-1 treated with DMSO) and two time points along the process of generation of drug-resistant cells (TPC-1 LR5 and TPC-1 LR8.6 cultured at 5 µM —intermediate point— and 8.6 µM —final point—, respectively). ScRNA-seq data was obtained using 10x Genomics and CellRanger, and analysed using the R package Seurat. Results showed that sensitive (controls) and resistant cells clustered separately, indicating that lenvatinib significantly affects the transcriptome. We found no differences between controls (identified as the same cluster), while resistant cells were divided in different clusters. We identified 220 and 551 overexpressed genes (logFC>1, adj pval<0.05) in TPC-1 LR5 and TPC-1 LR8.6 cells when compared to control cells, respectively, with 74 common genes among those. We performed a gene ontology analysis and found overexpressed genes in TPC-1 LR5 associated with negative regulation of the hippo signalling pathway and cell adhesion and migration, while overexpressed genes in TPC-1 LR8.6 cells were associated with different metabolic pathways. These results were also validated in bulk RNA-seq data. Based on these data and publicly available datasets of thyroid cancer patients, we selected some differentially expressed genes to further study their role in lenvatinib resistance in vitro. In conclusion, we have identified potential candidate genes involved in lenvatinib resistance, which could lead to a novel combination drug therapy for RAI-R DTC patients.