Alternative splicing associated with cancer stemness in kidney renal clear cell carcinoma

作者：Lixing Xiao, Guoying Zou, Rui Cheng, Pingping Wang, Kexin Ma, Huimin Cao, Wenyang Zhou, Xiyun Jin, Zhaochun Xu, Yan Huang, Xiaoyu Lin, Huan Nie, Qinghua Jiang · 发表于：BMC Cancer · 年份：2021 · DOI：10.1186/s12885-021-08470-8 · 被引用次数：37 · 研究领域：Single-cell and spatial transcriptomics、Ferroptosis and cancer prognosis、Renal cell carcinoma treatment

BACKGROUD: Cancer stemness is associated with metastases in kidney renal clear cell carcinoma (KIRC) and negatively correlates with immune infiltrates. Recent stemness evaluation methods based on the absolute expression have been proposed to reveal the relationship between stemness and cancer. However, we found that existing methods do not perform well in assessing the stemness of KIRC patients, and they overlooked the impact of alternative splicing. Alternative splicing not only progresses during the differentiation of stem cells, but also changes during the acquisition of the stemness features of cancer stem cells. There is an urgent need for a new method to predict KIRC-specific stemness more accurately, so as to provide help in selecting treatment options. METHODS: The corresponding RNA-Seq data were obtained from the The Cancer Genome Atlas (TCGA) data portal. We also downloaded stem cell RNA sequence data from the Progenitor Cell Biology Consortium (PCBC) Synapse Portal. Independent validation sets with large sample size and common clinic pathological characteristics were obtained from the Gene Expression Omnibus (GEO) database. we constructed a KIRC-specific stemness prediction model using an algorithm called one-class logistic regression based on the expression and alternative splicing data to predict stemness indices of KIRC patients, and the model was externally validated. We identify stemness-associated alternative splicing events (SASEs) by analyzing different alt...