ArticleJournal of oncology2022
A TRP Family Based Signature for Prognosis Prediction in Head and Neck Squamous Cell Carcinoma.
Article in Journal of oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Development and validation of transient receptor potential channel-related signature for predicting prognosis in patients with lung adenocarcinoma.Oncology letters · 2025Article
- Article
- A comprehensive analysis of TRP-related gene signature, and immune infiltration in patients with colorectal cancer.Discover oncology · 2024Article
- Transient receptor potential-related risk model predicts prognosis of hepatocellular carcinoma patients.World journal of gastrointestinal oncology · 2023Article
- 'Toxic Masculinity': What Is Known about the Role of Androgen Receptors in Head and Neck Squamous Cell Carcinoma.International journal of molecular sciences · 2023Review
- FAM family gene prediction model reveals heterogeneity, stemness and immune microenvironment of UCEC.Frontiers in molecular biosciences · 2023Article
- Comprehensive Analysis of TRP Channel-Related Genes for Estimating the Immune Microenvironment, Prognosis, and Therapeutic Effect in Patients With Esophageal Squamous Cell Carcinoma.Frontiers in cell and developmental biology · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
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Abstract
purposeHead and neck squamous cell carcinoma (HNSCC) is a classical type of head and neck cancers, with heterogeneous clinical outcome. This project is set out to create a robust risk signature based on TRP family genes (TFGs) for prognosis evaluation in HNSCC.
methodsBased on the HNSCC sample data from the TCGA website, we integrated expression profile of TFGs for 490 HNSCC cases. We explore the interactions among TFGs using STRING tool. The TFGs-based signature (TFBS) was created by Cox relative analyses. In addition, we conducted GSEA to identify the underlying signaling pathways of the specific TFGs in HNSCC. The immune landscape of HNSCC patients was analyzed by CIBERSORT and ssGSEA algorithms.
resultsA total of 6 TFGs (TRPC1, TRPC3, TRPC6, TRPV2, TRPV4, and TRPM8) closely associated with prognosis of HNSCC cases were screened to create TFBS. TFBS predicted that the TFBS-high group presented dismal patient outcome. Cox regression revealed the favorable independent value of TFBS. ROC analysis showed the robust power of TFBS for prognosis forecasting. GSEA determined several crucial pathways related with HNSCC, which are the p53 pathway, TNF-alpha signaling via NFKB, and hypoxia. Moreover, immune-related analysis showed that patients in the TFBS-high group were more likely in immunosuppressive status.
conclusionOur proposed TFBS could serve as a favorable indicator to forecast the survival outcome of HNSCC cases and offer prominent therapy guidance.
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Registered trials
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