ArticleJournal of personalized medicine2021
A Transcriptomic Analysis of Head and Neck Squamous Cell Carcinomas for Prognostic Indications.
Article in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- The tumor-suppressive function of the unique H domain of FCGBP and its potential as a therapeutic target in colorectal cancer.BMC cancer · 2026Article
- A dynamic co-expression approach reveals Gins2 as a potential upstream modulator of HNSCC metastasis.Scientific reports · 2025Article
- FCGBP functions as a tumor suppressor gene in head and neck squamous cell carcinoma.Discover oncology · 2024Article
- Fc fragment of IgG binding protein is correlated with immune infiltration levels in hepatocellular carcinoma.Biomolecules & biomedicine · 2023Article
- Article
- Chondroitin Sulfate Proteoglycan 4 as a Marker for Aggressive Squamous Cell Carcinoma.Cancers · 2022Review
- Prognostic signature related to the immune environment of oral squamous cell carcinoma.Open life sciences · 2022Article
- Role of the mucin-like glycoprotein FCGBP in mucosal immunity and cancer.Frontiers in immunology · 2022Review
- Expanding the Genetic Blueprint of Wilms Tumor: An Account of 71 Novel Variants across 16 Genes with Novel Implications for Wilms Tumor Pathogenesis.Journal of Indian Association of Pediatric SurgeonsArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Survival analysis of the Cancer Genome Atlas (TCGA) dataset is a well-known method for discovering gene expression-based prognostic biomarkers of head and neck squamous cell carcinoma (HNSCC). A cutoff point is usually used in survival analysis for patient dichotomization when using continuous gene expression values. There is some optimization software for cutoff determination. However, the software's predetermined cutoffs are usually set at the medians or quantiles of gene expression values. There are also few clinicopathological features available in pre-processed datasets. We applied an in-house workflow, including data retrieving and pre-processing, feature selection, sliding-window cutoff selection, Kaplan-Meier survival analysis, and Cox proportional hazard modeling for biomarker discovery. In our approach for the TCGA HNSCC cohort, we scanned human protein-coding genes to find optimal cutoff values. After adjustments with confounders, clinical tumor stage and surgical margin involvement were found to be independent risk factors for prognosis. According to the results tables that show hazard ratios with Bonferroni-adjusted
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.