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 (P < 0.05) based on the training set. To further clarify, validation sets showed a significant difference between the high-risk group with a worse prognosis and the low-risk group (P < 0.05). Independent prognostic analysis based on the training set and validation set indicated that the risk score was superior as an independent prognostic factor compared to other clinical characteristics. We conducted Gene Set Enrichment Analysis (GSEA) among high-risk and low-risk patients to identify metabolism-related biological pathways. Finally, nomogram incorporating some clinical characteristics and risk score was constructed to predict 1-, 2-, and 3-year survival rates (C-index = 0.7). The proposed nine metabolic gene prognostic model may contribute to a more accurate and individualized prediction for the prognosis of newly diagnosed OSCC patients, and provide advice for clinical treatment and follow-up observations.
Highlights
Among head and neck squamous carcinoma worldwide, > 90% patients suffered from oral squamous cell carcinoma (OSCC) (Marur and Forastiere, 2016; Henley et al, 2020), which was a life-threatening disease with high morbidity and mortality
A matrix consisting of 1,723 metabolic gene signatures based on Kyoto Encyclopedia of Genes and Genomes (KEGG) and their expression values in 422 samples was obtained. 452 metabolism-related genes with | log2 fold change (FC)| > 0.5 and false discovery rate (FDR) < 0.05 were thought to be primary differentially expressed genes (DEGs), including 209 down-regulated genes and 243 up-regulated genes
195 randomly obtained sample sets were defined as training sets, while 390 samples constituted validation set for testing sets
Summary
Among head and neck squamous carcinoma worldwide, > 90% patients suffered from oral squamous cell carcinoma (OSCC) (Marur and Forastiere, 2016; Henley et al, 2020), which was a life-threatening disease with high morbidity and mortality. Prognostic Prediction Model for OSCC was the most common type of oral malignancy, with half a million new cases diagnosed each year in India (Gupta et al, 2016). Relevant study showed that metabolic phenotypes provide information on patient prognosis and the treatment of cancer (Vander Heiden and DeBerardinis, 2017). The abnormal activity of these pathways, as one of the most significant events in cancer, accelerated the development of tumor and arouses great interest in tumor metabolism (Vander Heiden and DeBerardinis, 2017; Fakhri et al, 2020). The specific mechanism between cancer and metabolic reprogramming has been widely studied, but as far as OSCC was concerned, the specific mechanism is not well understood
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