Unraveling the potential mechanism and prognostic value of pentose phosphate pathway in hepatocellular carcinoma: a...

Hepatocellular carcinoma (HCC) remains a malignant and life-threatening tumor with an extremely poor prognosis, posing a significant global health challenge. Despite the continuous emergence of novel therapeutic agents, patients exhibit substantial heterogeneity in their responses to anti-tumor drugs and overall prognosis. The pentose phosphate pathway (PPP) is highly activated in various tumor cells and plays a pivotal role in tumor metabolic reprogramming. This study aimed to construct a model based on PPP-related Genes for risk assessment and prognosis prediction in HCC patients. We integrated RNA-seq and microarray data from TCGA, GEO, and ICGC databases, along with single-cell RNA sequencing (scRNA-seq) data obtained from HCC patients via GEO. Based on the "Seurat" R package, we identified distinct gene clusters related to the PPP within the scRNA-seq data. Using a penalized Cox regression model with least absolute shrinkage and selection operator (LASSO) penalties, we constructed a risk prognosis model. The validity of our risk prognosis model was further confirmed in external cohorts. Additionally, we developed a nomogram capable of accurately predicting overall survival in HCC patients. Furthermore, we explored the predictive potential of our risk model within the immune microenvironment and assessed its relevance to biological function, particularly in the context of immunotherapy. Subsequently, we performed in vitro functional validation of the key genes (ATAD2 and SPP1) in our model. A ten-gene signature associated with the PPP was formulated to enhance the prediction of HCC prognosis and anti-tumor treatment response. Following this, the ROC curve, nomogram, and calibration curve outcomes corroborated the model's robust clinical predictive capability. Functional enrichment analysis unveiled the engagement of the immune system and notable variances in the immune infiltration landscape across the high and low-risk groups. Additionally, tumor mutation frequencies were observed to be elevated in the high-risk group. Based on our analyses, the IC50 values of most identified anticancer agents demonstrated a correlation with the RiskScore. Additionally, the high-risk and low-risk groups exhibited differential sensitivity to various drugs. Cytological experiments revealed that silencing ATAD2 or SPP1 suppresses malignant phenotypes, including viability and migration, in liver cancer cells. In this study, a novel gene signature related to the PPP was developed, demonstrating favorable predictive performance. This signature holds significant guiding value for assessing the prognosis of HCC patients and directing individualized treatment strategies.