Integration RNA bulk and single cell RNA sequencing to explore the change of BCAA metabolism-related immune microenvironment and construct prognostic signature in HNSCC

Background Several studies have demonstrated that impaired metabolism of branched chain amino acids (BCAAs) is related to cancer progression. However, the specific mechanisms underlying BCAA metabolism in head and neck squamous cell carcinoma (HNSCC) remain to be explored. The aim of this study was to identify prognostic genes associated with BCAA metabolism in HNSCC and to elucidate their functional mechanisms. Methods The HNSCC related datasets (TCGA-HNSCC, GSE65858 and GSE140042) were enrolled in this study. Candidate genes were acquired by overlapping differentially expressed genes form differential expression analysis and key module genes connected with BCAA-metabolism related genes (BCAA-MRGs) scores from weighted gene co-expression network analysis. Subsequently, prognostic genes were obtained to construct the risk model through univariate Cox regression analysis, proportional hazards hypothesis test, and least absolute shrinkage and selection operator regression analysis selected in sequence. Afterwards, independent prognostic analysis, enrichment analysis and immune microenvironment analysis were performed. Furthermore, the expression changes of prognostic genes at the cellular level were assessed through single-cell RNA sequencing (scRNA-seq) data analysis and pseudo-time analysis. Additionally, RT-qPCR was used to confirm the expression levels of prognostic genes in HNSCC tissues. Results SMS, PRDX6, GSTO1, and ADA were determined as prognostic genes to create the risk model. The HNSCC samples were divided into high-risk group (HRG) and low-risk group (LRG), with LRG demonstrating significantly higher survival rates compared to the HRG. Furthermore, the nomogram model constructed using risk score and age had an excellent predictive ability for HNSCC patients. Enrichment analysis revealed that ‘pentose phosphate pathway’ and ‘fructose and mannose metabolism’ were significantly associated with HNSCC progression. At the same time, we also found that the level of infiltration of 20 immune cells (plasmacytoid dendritic cells, mast cells, and T follicle helper cells) and the expression of 10 immune checkpoints (CD276, CD27, and CD40) differed between the HRG and the LRG. Additionally, epithelial cells were selected as key cells due to higher expression of prognostic genes. Importantly, the trend of prognostic gene expression varied with different stages of cell differentiation. Through RT-qPCR experiment, SMS, GSTO1, and ADA all expressed highly in the tumor group, but PRDX6 had not remarkably difference between tumor and normal groups. Conclusion In summary, we pinpointed four genes-SMS, PRDX6, GSTO1, and ADA-linked to the prognosis of HNSCC within the context of BCAA metabolism. Subsequently, we developed a risk model. This model offers a novel reference for prognostic assessment and treatment strategies tailored to HNSCC patients.