Endocrine Abstracts

Immortalized human thyroid follicular epithelial cell lines represent a valuable tool for the investigation of thyroid physiology in vitro. While there is an extensive selection of human thyroid carcinoma cell lines, the number of healthy follicular epithelial cell lines is limited. The vast majority of studies on thyroid physiology is based on the human immortalized cell line Nthy-ori 3-1, leading to comprehensive characterization of this cell line. However, in 2021 Hopperstad et al. generated four novel immortalized cell line variants derived from normal human thyroid tissue (CI-huThyrEC clone 1-4). In order to verify, if results obtained from the different cell lines are comparable, we decided to characterize and to compare the transcriptomic profile of each cell line. For this, we chose a novel approach that focusses on RNA sequencing of particularly low cell numbers. We prepared RNA sequencing libraries from one cell, four cells and ten cells derived from the different cell lines, which then underwent Illumina Next Sequencing. Overall, we obtained high quality sequencing data with minor variability depending on the method of cell separation. Further, gene detection and mapping statistics are comparable. On average 10k – 12k genes were detected with 80 % – 90 % uniquely mapped reads independent of the input number of cells. Downstream principal component analysis (PCA) revealed that sequencing data generated from samples containing ten Nthy ori 3-1 cells cluster closer than data from lower cell numbers, pointing to a high transcriptional similarity and reproducibility at this cell number. The CI-huThyrEC clones 1-4 show a greater variability in the PCA plot indicating that the four cell line variants differ in their transcriptional profile. Comparing the transcriptomic profile of the cell lines it is noticeable that CI-huThyrEC show a significant upregulation of NKX2-1 gene expression that encodes the thyroid transcription factor-1 (TTF-1). Having established RNA sequencing of ultra-low cell numbers enables us to transfer this method to further questions. Next, we aim to transcriptionally characterize single neoplastic cells derived from fine needle aspiration biopsies of high-risk thyroid nodules. This might lead to the identification of new potential oncogenes or tumor suppressor genes, which might serve as potential biomarkers in the context of thyroid cancer and tumor stage assessment.