ArticleFrontiers in physiology2021
Construction of Prognostic Risk Prediction Model of Oral Squamous Cell Carcinoma Based on Nine Survival-Associated Metabolic Genes.
Article in Frontiers in physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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Who cites it
10 citing papers in PubMed, 17 citations in OpenAlex.
- Pairwise analysis of gene expression for oral squamous cell carcinoma via a large-scale transcriptome integration.Journal of cellular and molecular medicine · 2024Article
- Exploring the prognostic landscape of oral squamous cell carcinoma through mitochondrial damage-related genes.BMC medical genomics · 2024Article
- Characterization of the mScientific reports · 2023Article
- Systematic establishment and verification of an epithelial-mesenchymal transition gene signature for predicting prognosis of oral squamous cell carcinoma.Frontiers in genetics · 2023Article
- Abnormal expression of HADH, an enzyme of fatty acid oxidation, affects tumor development and prognosis (Review).Molecular medicine reports · 2022Review
- Lipid Metabolism in Cancer: The Role of Acylglycerolphosphate Acyltransferases (AGPATs).Cancers · 2022Review
- Hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit beta gene as a tumour suppressor in stomach adenocarcinoma.Frontiers in oncology · 2022Article
- Risk Stratification in Oral Cancer: A Novel Approach.Frontiers in oncology · 2022Article
- Low Expression of AGPAT5 Is Associated With Clinical Stage and Poor Prognosis in Colorectal Cancer and Contributes to Tumour Progression.Clinical Medicine Insights. Oncology · 2022Article
- Molecular Subtypes Based on Cell Differentiation Trajectories in Head and Neck Squamous Cell Carcinoma: Differential Prognosis and Immunotherapeutic Responses.Frontiers in immunology · 2021Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim was to investigate the independent prognostic factors and construct a prognostic risk prediction model to facilitate the formulation of oral squamous cell carcinoma (OSCC) clinical treatment plan. We constructed a prognostic model using univariate COX, Lasso, and multivariate COX regression analysis and conducted statistical analysis. In this study, 195 randomly obtained sample sets were defined as training set, while 390 samples constituted validation set for testing. A prognostic model was constructed using regression analysis based on nine survival-associated metabolic genes, among which PIP5K1B, NAGK, and HADHB significantly down-regulated, while MINPP1, PYGL, AGPAT4, ENTPD1, CA12, and CA9 significantly up-regulated. Statistical analysis used to evaluate the prognostic model showed a significant different between the high and low risk groups and a poor prognosis in the high risk group (
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Registered trials
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