Dissecting order amidst chaos of programmed cell deaths: construction of a diagnostic model for KIRC using transcriptomic information in blood-derived exosomes and single-cell multi-omics data in tumor microenvironment - Wang, Chengbang; He, Yuan; Zheng, Jie; Wang, Xiang; Chen, Shaohua (Frontiers in Immunology, 2023)
Abstract Background: Kidney renal clear cell carcinoma (KIRC) is the most frequently diagnosed subtype of renal cell carcinoma (RCC); however, the pathogenesis and diagnostic approaches for KIRC remain elusive. Using single-cell transcriptomic information of KIRC, we constructed a diagnostic model de-picting the landscape of programmed cell death (PCD)-associated genes, namely cell death-related genes (CDRGs). Methods: In this study, six CDRGs categories, including apoptosis, necroptosis, autophagy, pyroptosis, ferroptosis, and cuproptosis, were collected. RNA sequencing (RNA-seq) data of blood-derived exo-somes from exoRBase database, RNA-seq data of tissues from TCGA combined with control samples from GTEx databases, and single-cell RNA sequencing (scRNA-seq) data from GEO database were downloaded. Next, we intersected the differentially expressed genes (DEGs) of the KIRC cohort from exoRBase, and the TCGA databases with CDRGs and DEGs obtained from single-cell datasets, fur-ther screening out the candidate biomarker genes using clinical indicators and machine learning meth-ods, thus constructing a diagnostic model for KIRC. Finally, we investigated the underlying mecha-nisms of key genes and their roles in the tumor microenvironment (TME) using scRNA-seq, single-cell assays for transposase-accessible chromatin sequencing (scATAC-seq) and spatial transcriptomics se-quencing (stRNA-seq) data of KIRC provided by GEO database. Result: We obtained 1428 samples and 216,155 single cells. After the rational screening, we con-structed a 13-gene diagnostic model for KIRC, which had high diagnostic efficacy in the exoRBase KIRC cohort (training set: AUC = 1; testing set: AUC = 0.965) and TCGA KIRC cohort (training set: AUC = 1; testing set: AUC = 0.982) with an additional validation cohort from GEO databases pre-senting AUC value of 0.914. Subsequent analysis revealed a specific tumor epithelial cell of TRIB3high subset. Mechanical analysis showed the relatively elevated chromatin accessibility of TRIB3 in tumor epithelial cells in the scATAC data, while the stRNA-seq verified that TRIB3 was predominantly ex-pressed in cancer tissues. Conclusions: The 13-gene diagnostic model yielded high accuracy in KIRC screening, and TRIB3high tumor epithelial cells could be a promising therapeutic target for the KIRC.