Overexpression of RHEB is associated with metastasis and poor prognosis in hepatocellular carcinoma

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

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.

Identification of an autophagy-related gene signature that can improve prognosis of hepatocellular carcinoma patients

Background

Autophagy is a programmed cell degradation mechanism that has been associated with several physiological and pathophysiological processes, including malignancy. Improper induction of autophagy has been proposed to play a pivotal role in the progression of hepatocellular carcinoma (HCC).

Methods

Univariate Cox regression analysis of overall survival (OS) was performed to identify risk-associated autophagy-related genes (ARGs) in HCC data set from The Cancer Genome Atlas (TCGA). Multivariate cox regression was then performed to develop a risk prediction model for the prognosis of 370 HCC patients. The multi-target receiver operating characteristic (ROC) curve was used to determine the model’s accuracy. Besides, the relationship between drug sensitivity and ARGs expression was also examined.

Results

A total of 62 differentially expressed ARGs were identified in HCC patients. Univariate and multivariate regression identified five risk-associated ARGs (HDAC1, RHEB, ATIC, SPNS1 and SQSTM1) that were correlated with OS in HCC patients. Of importance, the risk-associated ARGs were independent risk factors in the multivariate risk model including clinical parameters such as malignant stage (HR = 1.433, 95% CI = 1.293–1.589, P < 0.001). In addition, the area under curve for the prognostic risk model was 0.747, which indicates the high accuracy of the model in prediction of HCC outcomes. Interestingly, the risk-associated ARGs were also correlated with drug sensitivity in HCC cell lines.

Conclusion

We developed a novel prognostic risk model by integrating the molecular signature and clinical parameters of HCC, which can effectively predict the outcomes of HCC patients.

Construction of a prognosis-predicting model based on autophagy-related genes for hepatocellular carcinoma (HCC) patients

Background: Autophagy, a highly conserved cellular catabolic process by which the eukaryotic cells deliver autophagosomes engulfing cellular proteins and organelles to lysosomes for degradation, is critical for maintaining cellular homeostasis in response to various signals and nutrient stresses. The dysregulation of autophagy has been noted in the pathogenesis of cancers. Our study aims to investigate the prognosis-predicting value of autophagy-related genes (ARG) in hepatocellular carcinoma (HCC).

Results: The signature was constructed based on eight ARGs, which stratified HCC patients into high- and low-risk groups in terms of overall survival (OS) (Hazard Ratio, HR=4.641, 95% Confidential Interval, CI, 3.365-5.917, P=0.000). The ARG signature is an independent prognostic indicator for HCC patients (HR = 1.286, 95% CI, 1.194-1.385; P < 0.001). The area under the receiver operating characteristic (ROC) curve (AUC) for 5-year survival is 0.765.

Conclusion: This study provides a potential prognostic signature for predicting the prognosis of HCC patients and molecular insights into the significance of autophagy in HCC.

Methods: Sixty-two differentially expressed ARGs and the clinical characteristics and basic information of the 369 enrolled HCC patients were retrieved from The Cancer Genome Atlas (TCGA) database. the Cox proportional hazard regression analysis was adopted to identify survival-related ARGs, based on which a prognosis predicting signature was constructed.

Prognostic value of ATAD3 gene cluster expression in hepatocellular carcinoma

ATPase family AAA domain-containing protein 3 (ATAD3) is a mitochondrial membrane-bound ATPase that is involved in a number of cellular processes and is linked with the progression of various types of malignancies. In primates, the ATAD3 gene cluster contains ATAD3A, ATAD3B and ATAD3C. The association between ATAD3 gene cluster expression and hepatocellular carcinoma (HCC) remains unknown. Therefore, the present study examined the prognostic significance of ATAD3 gene cluster expression in patients with HCC. Box plots of expression differences between HCC and normal liver tissues for the ATAD3 family genes were obtained from the online tool Gene Expression Profiling Interactive Analysis. Data from 360 patients with HCC in The Cancer Genome Atlas database were analyzed. Kaplan-Meier analysis and a Cox regression model were used to calculate median survival time (MST) and overall survival (OS). ATAD3A and ATAD3B expression levels were higher in HCC compared with normal liver tissues (P<0.05). However, ATAD3C expression was significantly decreased in HCC tissues compared with normal liver tissues (P<0.05). ATAD3A [P=0.017, hazard ratio (HR)=1.54, 95% confidence interval (CI)=1.08-2.20; adjusted P=0.032; adjusted HR=1.52; 95% CI=1.04-2.22] and ATAD3B (P=0.026, HR=1.49, 95% CI=1.05-2.13; adjusted P=0.031, adjusted HR=1.52, 95% CI=1.04-2.21) expression levels were significantly associated with OS. A joint-effects analysis revealed that patients with high ATAD3A and ATAD3B expression had reduced OS rates compared with patients with low ATAD3A and ATAD3B expression (P=0.007, HR=1.77, 95% CI=1.16-2.69; adjusted P=0.013, adjusted HR=1.76, 95% CI=1.13-2.75). In conclusion, ATAD3A and ATAD3B may serve as potential prognostic biomarkers for patients with HCC.