Evidence map›Paper›PMID 39664194›Full record

ArticleFrontiers in oncology2024

Unveiling the role of TGF-β signaling pathway in breast cancer prognosis and immunotherapy.

Yifan Zheng, Li Li, Wenqian Cai, Lin Li, Rongxin Zhang, Wenbin Huang, Yulun Cao

Abstract read
In one paragraph

Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yifan Zheng *Department of General Surgery I, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, Guangdong, China.
Li Li *Guangdong Provincial Key Laboratory for Biotechnology Drug Candidates, Institute of Basic Medical Sciences and Department of Biotechnology, School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, China.
Wenqian CaiGuangdong Provincial Key Laboratory for Biotechnology Drug Candidates, Institute of Basic Medical Sciences and Department of Biotechnology, School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, China.
Lin LiDepartment of General Surgery I, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, Guangdong, China.
Rongxin ZhangGuangdong Provincial Key Laboratory for Biotechnology Drug Candidates, Institute of Basic Medical Sciences and Department of Biotechnology, School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, China.
Wenbin HuangDepartment of General Surgery I, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, Guangdong, China.
Yulun CaoDepartment of General Surgery I, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The TGF-β signaling pathway (TSP) is pivotal in tumor progression. Nonetheless, the connection between genes associated with the TSP and the clinical outcomes of breast cancer, as well as their impact on the tumor microenvironment and immunotherapeutic responses, remains elusive. Methods: Breast cancer transcriptomic and single-cell sequencing data were obtained from the The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. We identified 54 genes associated with the TSP from the Molecular Signatures Database (MSigDB) and analyzed both data types to evaluate TSP activity. Using weighted gene co-expression network analysis (WGCNA), we identified modules linked to TSP activity. To assess patient risk, we used 101 machine learning algorithms to develop an optimal TGF-β pathway-related prognostic signature (TSPRS). We then examined immune activity and response to immune checkpoint inhibitors and chemotherapy in these groups. Finally, we validated ZMAT3 expression levels clinically and confirmed its relevance in breast cancer using CCK-8 and migration assays. Results: At the single-cell level, TSP activity was most notable in endothelial cells, with higher activity in normal tissues compared to tumors. TSPRS was developed. This signature's accuracy was confirmed through internal and external validations. A nomogram incorporating the TSPRS was created to improve prediction accuracy. Further studies showed that breast cancer patients categorized as low-risk by the TSPRS had higher immune phenotype scores and more immune cell infiltration, leading to better prognosis and enhanced immunotherapy response. Additionally, a strong link was found between the TSPRS risk score and the effectiveness of anti-tumor agents. Silencing the ZMAT3 gene in the TSPRS significantly reduced the proliferation and invasiveness of breast cancer cells. Discussion: Our study developed a TSPRS, which emerges as a potent predictive instrument for the prognosis of breast cancer, offering novel perspectives on the immunotherapeutic approach to the disease.

Indexed as

breast cancerimmunotherapyprognostic signatureTGF-βtumor microenvironment

Identifiers

PMID39664194
PMCPMC11631921

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