PT  - JOURNAL ARTICLE
AU  - Weida Wang
AU  - Jinyuan Xu
AU  - Shuyuan Wang
AU  - Peng Xia
AU  - Li Zhang
AU  - Lei Yu
AU  - Jie Wu
AU  - Qian Song
AU  - Bo Zhang
AU  - Chaohan Xu
AU  - Yun Xiao
TI  - Single-cell RNA-seq data reveals TNBC tumor heterogeneity through characterizing subclone compositions and proportions
AID  - 10.1101/858290
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 858290
4099  - http://biorxiv.org/content/early/2019/11/28/858290.short
4100  - http://biorxiv.org/content/early/2019/11/28/858290.full
AB  - Understanding subclonal architecture and their biological functions poses one of the key challenges to deeply portray and investigative the cause of triple-negative breast cancer (TNBC). Here we combine single-cell and bulk sequencing data to analyze tumor heterogeneity through characterizing subclone compositions and proportions. Based on sing-cell RNA-seq data (GSE118389) we identified five distinct cell subpopulations and characterized their biological functions based on their gene markers. It is worth noting that C1 and C2 relate to immune functions, while C5 relates to programmed cell death. Then based on subclonal basis gene expression matrix, we applied CBS deconvolution algorithm on TCGA tissue RNA-seq data, and found that patients with low and high C1 proportions have different immune microenvironment; and high C5 proportions would led to poor survival outcome, p-value and HR [95%CI] for five years overall survival in TCGA dataset were 0.0326 and 1.664 [1.038-2.667], and in GSE96058 dataset were 0.0158 and 2.557 [1.160-5.636]. Collectively, our analysis reveals the both intra-tumor and inter-tumor heterogeneity and their association with subclonal microenvironment in TNBC (subclone compositions and proportions), and uncovers the organic combination of subclones dictating poor outcomes in this disease.