Dataset Information

Characterization of cancer-associated fibroblasts (CAFs) and development of a CAF-based risk model for triple-negative breast cancer.

ABSTRACT: Triple-negative breast Cancer (TNBC) is a highly malignant cancer with unclear pathogenesis. Within the tumor microenvironment (TME), cancer-associated fibroblasts (CAFs) vitally influence tumor onset and progression. Thus, this research aimed to identify distinct subgroups of CAF using single-cell and TNBC-related information from the GEO and TCGA databases, respectively. The primary aim was to establish a novel predictive model based on the CAF features and their clinical relevance. Moreover, the CAFs were analyzed for their immune characteristics, response to immunotherapy, and sensitivity to different drugs. The developed predictive model demonstrated significant effectiveness in determining the prognosis of patients with TNBC, TME, and the immune landscape of the tumor. Of note, the expression of GPR34 was significantly higher in TNBC tissues compared to that in other breast cancer (non-TNBC) tissues, indicating that GPR34 plays a crucial role in the onset and progression of TNBC. In summary, this research has yielded a novel predictive model for TNBC that holds promise for the accurate prediction of prognosis and response to immunotherapy in patients with TNBC.

SUBMITTER: Wang G

PROVIDER: S-EPMC10676599 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Characterization of cancer-associated fibroblasts (CAFs) and development of a CAF-based risk model for triple-negative breast cancer.

Wang Ganggang G Zhang Hao H Shen Xiaowei X Jin Wenzhi W Wang Xiaoliang X Zhou Zhijie Z

Cancer cell international 20231125 1

Triple-negative breast Cancer (TNBC) is a highly malignant cancer with unclear pathogenesis. Within the tumor microenvironment (TME), cancer-associated fibroblasts (CAFs) vitally influence tumor onset and progression. Thus, this research aimed to identify distinct subgroups of CAF using single-cell and TNBC-related information from the GEO and TCGA databases, respectively. The primary aim was to establish a novel predictive model based on the CAF features and their clinical relevance. Moreover, ...[more]

PMID: 38007443

Similar Datasets

Project description:Cancer-associated fibroblasts (CAFs) are one of the most abundant stromal cells in the tumor microenvironment which mediate desmoplastic response and are the primary driver for an immunosuppressive microenvironment, leading to the failure of triple-negative breast cancer (TNBC) immunotherapy. Therefore, depleting CAFs may enhance the effect of immunotherapy (such as PD-L1 antibody). Relaxin (RLN) has been demonstrated to significantly improve transforming growth factor-β (TGF-β) induced CAFs activation and tumor immunosuppressive microenvironment. However, the short half-life and systemic vasodilation of RLN limit its in vivo efficacy. Here, plasmid encoding relaxin (pRLN) to locally express RLN was delivered with a new positively charged polymer named polymeric metformin (PolyMet), which could increase gene transfer efficiency significantly and have low toxicity that have been certified by our lab before. In order to improve the stability of pRLN in vivo, this complex was further formed lipid poly-γ-glutamic acid (PGA)/PolyMet-pRLN nanoparticle (LPPR). The particle size of LPPR was 205.5 ± 2.9 nm, and the zeta potential was +55.4 ± 1.6 mV. LPPR displayed excellent tumor penetrating efficacy and weaken proliferation of CAFs in 4T1luc/CAFs tumor spheres in vitro. In vivo, it could reverse aberrantly activated CAFs by decreasing the expression of profibrogenic cytokine and remove the physical barrier to reshape the tumor stromal microenvironment, which enabled a 2.2-fold increase in cytotoxic T cell infiltration within the tumor and a decrease in immunosuppressive cells infiltration. Thus, LPPR was observed retarded tumor growth by itself in the 4T1 tumor bearing-mouse, and the reshaped immune microenvironment further led to facilitate antitumor effect when it combined with PD-L1 antibody (aPD-L1). Altogether, this study presented a novel therapeutic approach against tumor stroma using LPPR to achieve a combination regimen with immune checkpoint blockade therapy against the desmoplastic TNBC model.

Dataset Information

Characterization of cancer-associated fibroblasts (CAFs) and development of a CAF-based risk model for triple-negative breast cancer.

Publications

Characterization of cancer-associated fibroblasts (CAFs) and development of a CAF-based risk model for triple-negative breast cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets