Exploring immune gene expression and potential regulatory mechanisms in anaplastic thyroid carcinoma using a combination of single-cell and bulk RNA sequencing data.
Kehui Zhou, Shijia Zhang, Jinbiao Shang, Xiabin Lan
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引用次数: 0
Abstract
Thyroid cancer includes papillary thyroid carcinoma (PTC) and anaplastic thyroid carcinoma (ATC). While PTC has an excellent prognosis, ATC has a dismal prognosis, necessitating the identification of novel targets in ATC to aid in ATC diagnosis and treatment. Therefore, we analyzed ATC single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq) data from the Gene Expression Omnibus (GEO), retrieved immune-related genes from the ImmPort database, and identified differentially expressed immune genes within single-cell subgroups. The AUCell package in R was used to calculate activity scores for single-cell subgroups and identify active cell populations. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed on differentially expressed genes (DEGs) in active cell populations. Then, we integrated thyroid-cancer scRNA-seq and bulk RNA-seq data to identify overlapping DEGs. Relevant transcription factors (TFs) were retrieved from the TRRUST database. A protein-protein interaction (PPI) network for key TFs was created using the STRING database. Simultaneously, drugs associated with key TFs were obtained from DGIdb. ScRNA-seq cluster analysis showed that T/natural killer (NK) cells were more distributed in ATC and that thyrocytes cells were more distributed in PTC. We obtained 264 differential immune genes (DIGs) from the IMMPORT database and integrated scRNA-seq cluster analysis to identify the active cell T/NK cells and myeloid cells. Integrated bulk RNA-seq analysis obtained common immune genes (CIGs) such as TMSB4X, NFKB1, TNFRSF1B, and B2M. The nine CIG-related TFs (CEBPB, SPI1, NFKB1, RUNX1, NFE2L2, REL, CIITA, KLF6, and CEBPD) in myeloid cells and three TFs (NFKB1, FOXO1, and NR3C1) in T/NK cells were obtained from the TRRUST database. The key genes we identified represent potential targets for treating ATC.