Jiarong Zheng, Dalong Shu, Rongwei Xu, Yucheng Zheng, Pei Lin, Yunfan Lin, Xinyuan Zhao, Li Cui, Xin Liao and Bing Guo* Pages 1 - 19 ( 19 )
Aim: This study seeks to develop a prognostic risk signature for head and neck squamous cell carcinoma (HNSCC) based on cholesterol-related genes (CholRG), aiming to enhance prognostic accuracy in clinical practice.
Background: HNSCC poses significant challenges due to its aggressive behavior and limited response to standard treatments, resulting in elevated morbidity and mortality rates.In order to improve prognostic prediction in HNSCC, our study is inspired by the realization that cholesterol metabolism plays a critical role in accelerating the progression of cancer. To this end, we are developing a unique risk signature using CholRG.
Objective: The aim of this study was to create a CholRG-based risk signature to predict HNSCC prognosis, aiding in clinical decision-making accurately.
Method: The TCGA HNSCC dataset, along with GSE41613 and GSE65858, was obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, respectively. A CholRG-based risk signature was then developed and validated across various independent HNSCC cohorts. Moreover, a nomogram model incorporating CholRG-based risk signature was established. Additionally, functional enrichment analysis was conducted, and the immune landscapes of the high- and low-risk groups were compared. Finally, in vitro experiments were performed using lipid-based transfection to deliver siRNAs targeting ACAT1 to SCC1 and SCC23 cell lines, further examining the effects of ACAT1 knockdown on these cells.
Results: Utilizing RNA-seq, microarray, and clinical data from public databases, we constructed and validated a CholRG-based risk signature that includes key genes such as ACAT1, CYP19A1, CYP27A1, FAXDC2, INSIG2, PRKAA2, and SEC14L2, which can effectively predict the clinical outcome of HNSCC. Additionally, our findings were reinforced by a nomogram model that integrates the risk score with clinical variables for more clinically practical prognostic assessment. In addition, patients at high risk show hypoxia and increased oncogenic pathways such as mTORC1 signaling, as well as a suppressed immune microenvironment marked by a reduction in the infiltration of important immune cells. Notably, in vitro experiments showed that ACAT1 depletion significantly suppressed the proliferation, colony formation, and invasion capabilities of HNSCC cells, confirming ACAT1's role in promoting malignancy.
Conclusion: Collectively, our study not only underscores the importance of cholesterol metabolism in HNSCC pathogenesis but also highlights the CholRG-based risk signature as a promising tool for enhancing prognostic accuracy and personalizing therapeutic strategies.
HNSCC, cholesterol, risk signature, prognostic prediction, immune infiltration.