Construction of Prognostic Risk Prediction Model of Oral Squamous Cell Carcinoma Based on Nine Survival-Associated Metabolic Genes

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.

Development of a lncRNA‐based prognostic signature for oral squamous cell carcinoma

“…However, both studies lack validation from external cohorts. A nomogram incorporating a nine-metabolic-gene signature and several clinical characteristics performs well in discriminating patients with different outcomes with a C-index of 0.7, 19 which is comparable to the performance of the present model.…”

Molecular Subtypes Based on Cell Differentiation Trajectories in Head and Neck Squamous Cell Carcinoma: Differential Prognosis and Immunotherapeutic Responses

“…In recent years, studies on metabolic reprogramming of HNSCC during immune escape have shown that cancer cells can evolve and develop compensatory metabolic changes to escape death. In light of this, systemic manipulations to direct the tumor cell metabolic status to the normal cell status may reduce the malignancy (39)(40)(41). Studies have shown that metabolic therapy for certain metabolic processes provides an alternative for chemotherapy-resistant patients.…”

Lipid Metabolism in Cancer: The Role of Acylglycerolphosphate Acyltransferases (AGPATs)

“…Consequently, the upregulation of AGPAT4 in CRC cells most likely results in the decrease of T-cell activation and suppression of antitumor immunity. Microarray analysis studies of genes regulating lipid metabolism have further shown that AGPAT4 expression is upregulated in melanoma [ 98 ] and oral squamous cell carcinoma (OSCC) [ 99 ].…”