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Risk Signature of Cancer-Associated Fibroblast–Secreted Cytokines Associates With Clinical Outcomes of Breast Cancer

医学 内科学 肿瘤科 癌症 癌相关成纤维细胞 基因签名 生物标志物
作者
Chunxiao Sun,Siwei Wang,Yuchen Zhang,Fan Yang,Tianyu Zeng,Fanchen Meng,Mengzhu Yang,Yiqi Yang,Yijia Hua,Ziyi Fu,Jun Li,Xiang Huang,Hao Wu,Yongmei Yin,Wei Li
出处
期刊:Frontiers in Oncology [Frontiers Media SA]
卷期号:11: 628677- 被引量:1
标识
DOI:10.3389/fonc.2021.628677
摘要

Cancer-associated fibroblasts (CAFs) are key components in tumor microenvironment (TME). The secreted products of CAFs play important roles in regulating tumor cells and further impacting clinical prognosis. This study aims to reveal the relationship between CAF-secreted cytokines and breast cancer (BC) by constructing the risk signature. We performed three algorithms to reveal CAF-related cytokines in the TCGA BC dataset and identified five prognosis-related cytokines. Then we used single-cell RNA sequencing (ScRNA-Seq) datasets of BC to confirm the expression level of these five cytokines in CAFs. METABRIC and other independent datasets were utilized to validate the findings in further analyses. Based on the identified five-cytokine signature derived from CAFs, BC patients with high-risk score (RS) had shorter overall survival than low-RS cases. Further analysis suggested that the high-RS level correlated with cell proliferation and mast cell infiltration in BCs of the Basal-like subtype. The results also indicated that the level of RS could discriminate the high-risk BC cases harboring driver mutations (i.e., PI3KCA, CDH1, and TP53). Additionally, the status of five-cytokine signature was associated with the frequency and molecular timing of whole genome duplication (WGD) events. Intratumor heterogeneity (ITH) analysis among BC samples indicated that the high-RS level was associated with the increase of tumor subclones. This work demonstrated that the prognostic signature based on CAF-secreted cytokines was associated with clinical outcome, tumor progression, and genetic alteration. Our findings may provide insights to develop novel strategies for early intervention and prognostic prediction of BC.
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