ArticleHeliyon2023
Identification of potential key genes of TGF-beta signaling associated with the immune response and prognosis of ovarian cancer based on bioinformatics analysis.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 12 citations in OpenAlex.
- Piezo-type mechanosensitive ion channel component 1: a mechano-bioenergetic transducer in the tumour microenvironment.Annals of medicine · 2026Review
- mBiochemical genetics · 2026Article
- Mechanistic insights into c-Met rs368750834 mutation and a bifunctional CAR-T strategy for serous ovarian carcinoma.Journal of ovarian research · 2025Article
- Epithelial membrane protein 1 drives hepatic stellate cell activation via the TLN1/FAK cascade in MASLD donor liver transplantation.Molecular biomedicine · 2025Article
- SORCS2 serves as a tumor suppressor and associates with immune infiltration in ovarian cancer.Journal of ovarian research · 2025Article
- Construction and validation of a prognostic model of angiogenesis-related genes in multiple myeloma.BMC cancer · 2024Article
- Potential shared gene signatures and molecular mechanisms between recurrent pregnancy loss and ovarian cancer.Frontiers in oncology · 2024Article
- SLC38A5 promotes glutamine metabolism and inhibits cisplatin chemosensitivity in breast cancer.Breast cancer (Tokyo, Japan) · 2024Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: TGF-beta signaling is a key regulator of immunity and multiple cellular behaviors in cancer. However, the prognostic and therapeutic role of TGF-beta signaling-related genes in ovarian cancer (OV) remains unexplored. Methods: Data of OV used in the current study were sourced from TCGA and GEO databases. Consensus clustering was applied to classify OV patients into different clusters using TGF-beta signaling-related genes. Differentially expressed genes (DEGs) between different clusters were screened by the "limma" R package. Prognostic genes were screened from DEGs by univariate Cox regression, followed by the construction of the TGF-beta signaling-related score. The prognostic value of TGF-beta signaling-related score was evaluated in both training and testing OV cohorts. Moreover, the immune status, GSEA and therapeutic response between low- and high-score groups were performed to further reveal the potential mechanisms. Results: By consensus clustering, OV patients were classified into two clusters with different tumor immune environments. After differential expression and univariate Cox regression analyses, GMPR, PIEZO1, EMP1, CXCL13, GADD45B, SORCS2, FOSL2, PODN, LYNX1 and SLC38A5 were selected as prognostic genes. Using PCA algorithm, the TGF-beta signaling-related score of OV patients was calculated based on prognostic genes. Then OV patients were divided into low- and high-TGF-beta signaling-related score groups. We observed that the two score groups had significantly different survivals, tumor immune environments and expressions of immune checkpoints. In addition, GSEA results showed that immune-related pathways and biological processes, like chemokine signaling pathway, TNF signaling pathway and T cell migration were significantly enriched in the low-score group. Moreover, patients in the low- and high-score groups had remarkably different sensitivity to chemo- and immunotherapy. Conclusion: For the first time, our study identified ten prognostic genes associated with TGF-beta signaling, constructed a prognostic TGF-beta signaling-related score and investigated the effect of TGF-beta signaling-related score on OV immunity and therapy. These findings may enrich our knowledge of the TGF-beta signaling in OV prognosis and help to improve the prognosis prediction and treatment strategies in OV.
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