Integration of scRNA and bulk RNA-sequence to construct the 5-gene molecular prognostic model based on the heterogeneity of thyroid carcinoma endothelial cell

Abstract

Thyroid cancer (TC) is a kind of cancer with high heterogeneity, which leads to significant difference in prognosis. The prognostic molecular processes are not well understood. Cancer cells and tumor microenvironment (TME) cells jointly determine the heterogeneity. However, quite a little attention was paid to cells in the TME in the past years. In this study, we not only reveal that endothelial cells (ECs) are strongly associated with the progress of papillary thyroid cancer (PTC) using single-cell RNA-seq (scRNA-seq) data downloaded from Gene Expression Omnibus (GEO) and WGCNA, but also screen 5 crucial genes of ECs: CLDN5, ABCG2, NOTCH4, PLAT, and TMEM47. Furthermore, the 5-gene molecular prognostic model is constructed, which can predict how well a patient will do on PD-L1 blockade immunotherapy for TC and evaluate prognosis. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis demonstrates that PLAT is decreased in TC and the increase of PLAT can restrain the migratory capacity of TC cells. Meanwhile, in TC cells, PLAT suppresses VEGFa/VEGFR2-mediated human umbilical vascular endothelial cell (HUVEC) proliferation and tube formation. Totally, we construct the 5-gene molecular prognostic model from the perspective of EC and provide a new idea for immunotherapy of TC.

Keywords

• thyroid cancer
• single-cell RNA-seq
• biomarker
• prognosis module