Non-Apoptotic Programmed Cell Death-Related Gene Signature Correlates With Stemness and Immune Status and Predicts the Responsiveness of Transarterial Chemoembolization in Hepatocellular Carcinoma

Abstract

Background: Non-apoptotic programmed cell death, including autophagy, ferroptosis, and pyroptosis, newly discovered in recent years, plays an important role in hepatocellular carcinoma (HCC). So, this study attempted to explore the relationship between non-apoptotic programmed cell death-related genes and the molecular characteristics, tumor microenvironment, and prognosis in HCC patients.Methods: The transcriptomic and clinical data of HCC samples were downloaded from various public datasets, followed by acquiring non-apoptotic programmed cell death-related genes from the database. A gene signature model was then constructed using univariate and multivariate Cox regression analyses and validated in other cohorts as well as our institution sequencing data. Kaplan–Meier survival curves and time-dependent receiver operating characteristic curves were generated to evaluate the model’s predictive capability. Furthermore, the relationships among the gene signature, TP53 mutation, stemness, immune status, and responsiveness of transarterial chemoembolization (TACE) were analyzed.Results: The gene signature model was constructed based on five autophagy-, three ferroptosis-, and two pyroptosis-related differentially expressed genes. The model accurately predicted that patients classified as low risk would have better overall survival than high-risk patients, which was robustly consistent with data from other cohorts as well as our institution sequencing data. The comprehensive results indicated that a high-risk index was correlated with a high TP53 mutation rate, high cancer cell stemness, high infiltration of immunosuppressive cells and low immunophenoscore, and low TACE responsiveness of HCC patients.Conclusion: Collectively, the established non-apoptotic programmed cell death-related gene signature was shown to accurately predict prognosis, associated with the TP53 mutation and liver cancer cell stemness, reflect the tumor immune microenvironment, and predict TACE responsiveness in HCC patients.

Leveraging diverse cell-death patterns to predict the clinical outcome of immune checkpoint therapy in lung adenocarcinoma: Based on muti-omics analysis and vitro assay

“…Previous investigations have exhibited that the expression of genes related to apoptosis serves as a promising biomarker for forecasting prognosis across various cancer types, such as breast cancer and gastric cancer [ 21 , 22 ]. Moreover, studies have evidenced that the programmed cell death pathway plays a crucial role in chemotherapy resistance in cancerous cells [ 23 ]. Our study expands upon these previous findings by presenting a distinct PCD signature that may serve as a prognostic indicator and possible predictor of drug sensitivity in LUAD.…”

A novel defined programmed cell death related gene signature for predicting the prognosis of serous ovarian cancer

“…Initially, we collected 268 programmed cell death genes (PCD genes) from existing literature sources [ 24 , 25 ]. Using scRNA-seq datasets, we identified 3,000 cell Differential genes (cellDiffgenes) intersecting with PCD genes to obtain our target gene.…”