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

ABSTRACT: 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.

SUBMITTER: Sun C

PROVIDER: S-EPMC8356635 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Cancer-associated fibroblasts (CAFs) are actively involved in cancer progression through generating extracellular matrix and orchestrating the crosstalk within the tumor microenvironment (TME). This study aimed to develop and validate a CAF-derived lncRNA (long non-coding RNA) (CAFDL) signature for predicting clinical outcomes in colorectal cancer (CRC). Clinical data and transcriptomic profiles of 2,320 patients with CRC from The Cancer Genome Atlas (TCGA)-COAD and TCGA-READ datasets and 16 Gene Expression Omnibus datasets were included in this study. CAFDLs were identified using weighted gene co-expression network analysis. The CAFDL signature was constructed using the least absolute shrinkage and selection operator analysis in the TCGA-CRC training set. Multiple CRC cohorts and pan-cancer cohorts were used to validated the CAFDL signature. Patients with high CAFDL scores had significantly worse overall survival and disease-free survival than patients with low CAFDL scores in all CRC cohorts. In addition, non-responders to fluorouracil, leucovorin, and oxaliplatin (FOLFOX)/fluorouracil, leucovorin, and irinotecan (FOLFIRI) chemotherapy, chemoradiotherapy, bevacizumab, and immune checkpoint inhibitors had significantly higher CAFDL scores compared with responders. Pan-cancer analysis showed that CAFDL had prognostic predictive power in multiple cancers such as lung adenocarcinoma, breast invasive carcinoma, stomach adenocarcinoma, and thyroid carcinoma. The CAFDL signature was positively correlated with transforming growth factor-beta (TGF-β) signaling, epithelial-mesenchymal transition, and angiogenesis pathways but negatively correlated with the expression of immune checkpoints such as PDCD1, CD274, and CTLA4. The CAFDL signature reflects CAF properties from a lncRNA perspective and effectively predicts clinical outcomes in CRC and across pan-cancer. The CAFDL signature can serve as a useful tool for risk stratification and provide new insights into the underlying mechanisms of CAFs in cancer immunity.

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

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