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ATG101-related signature predicts prognosis and therapeutic option in hepatocellular carcinoma.

ABSTRACT: Autophagy plays a critical role in tumor pathogenesis. However, autophagy-related signature in Hepatocellular carcinoma (HCC) has not been revealed yet. We quantified the levels of various cancer hallmarks and identified ATG101 as the major risk factor for overall survival in HCC. A robust ATG101-related gene signature (ATS) for prognosis was constructed using a combination of bioinformatic and statistical approaches. Additionally, genetic and immunological properties were measured between ATS-high and ATS-low groups. The ATS signature was associated with shortened overall survival in HCC patients independently of clinicopathological characteristics. ATS status defines an inflamed yet exhausted tumor microenvironment, in which the activities of the exhausted CD8+ or CD4+ T cells were strongly associated with ATS. The ATS signature predicts the drug resistance to the immunotherapy, thus a combination of targeted therapy and immunotherapy might be suitable for ATS-high patients. This work shed light on the function of ATG101-related genes in HCC and revealed that the ATS signature may be a useful prognostic biomarker for differentiating molecular and immunological features and predicting probable response to the therapy.

SUBMITTER: Wang B

PROVIDER: S-EPMC9613769 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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ATG101-related signature predicts prognosis and therapeutic option in hepatocellular carcinoma.

Wang Bin B Fu Jiantao J Lin Yuanji Y Lou Yi Y Lu Anqian A Yang Jin J

Scientific reports 20221027 1

Autophagy plays a critical role in tumor pathogenesis. However, autophagy-related signature in Hepatocellular carcinoma (HCC) has not been revealed yet. We quantified the levels of various cancer hallmarks and identified ATG101 as the major risk factor for overall survival in HCC. A robust ATG101-related gene signature (ATS) for prognosis was constructed using a combination of bioinformatic and statistical approaches. Additionally, genetic and immunological properties were measured between ATS-h ...[more]

PMID: 36302799

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Project description:Objective: Hepatocellular carcinoma (HCC) is a genetically and phenotypically heterogeneous tumor, and the prediction of its prognosis remains a challenge. In the past decade, studies elucidating the mechanisms that induce tumor cell pyroptosis has rapidly increased. The elucidation of their mechanisms is essential for the clinical development optimal application of anti-hepatocellular carcinoma therapeutics. Methods: Based on the different expression profiles of pyroptosis-related genes in HCC, we constructed a LASSO Cox regression pyroptosis-related genes signature that could more accurately predict the prognosis of HCC patients. Results: We identified seven pyroptosis-related genes signature (BAK1, CHMP4B, GSDMC, NLRP6, NOD2, PLCG1, SCAF11) in predicting the prognosis of HCC patients. Kaplan Meier survival analysis showed that the pyroptosis-related high-risk gene signature was associated with poor prognosis HCC patients. Moreover, the pyroptosis-related genes signature performed well in the survival analysis and ICGC validation group. The hybrid nomogram and calibration curve further demonstrated their feasibility and accuracy for predicting the prognosis of HCC patients. Meanwhile, the evaluation revealed that our novel signature predicted the prognosis of HCC patients more accurately than traditional clinicopathological features. GSEA analysis further revealed the novel signature associated mechanisms of immunity response in high-risk groups. Moreover, analysis of immune cell subsets with relevant functions revealed significant differences in aDCs, APC co-stimulation, CCR, check-point, iDCs, Macrophages, MHC class-I, Treg, and type II INF response between high- and low-risk groups. Finally, the expression of Immune checkpoints was enhanced in high-risk group, and m6A-related modifications were expressed differently between low- and high-risk groups. Conclusion: The novel pyroptosis-related genes signature can predict the prognosis of patients with HCC and insight into new cell death targeted therapies.

Project description:BackgroundHepatocellular carcinoma (HCC) is a global health burden with poor prognosis. Anoikis, a novel programmed cell death, has a close interaction with metastasis and progression of cancer. In this study, we aimed to construct a novel bioinformatics model for evaluating the prognosis of HCC based on anoikis-related gene signatures as well as exploring the potential mechanisms.Materials and methodsWe downloaded the RNA expression profiles and clinical data of liver hepatocellular carcinoma from TCGA database, ICGC database and GEO database. DEG analysis was performed using TCGA and verified in the GEO database. The anoikis-related risk score was developed via univariate Cox regression, LASSO Cox regression and multivariate Cox regression, which was then used to categorize patients into high- and low-risk groups. Then GO and KEGG enrichment analyses were performed to investigate the function between the two groups. CIBERSORT was used for determining the fractions of 22 immune cell types, while the ssGSEA analyses was used to estimate the differential immune cell infiltrations and related pathways. The "pRRophetic" R package was applied to predict the sensitivity of administering chemotherapeutic and targeted drugs.ResultsA total of 49 anoikis-related DEGs in HCC were detected and 3 genes (EZH2, KIF18A and NQO1) were selected out to build a prognostic model. Furthermore, GO and KEGG functional enrichment analyses indicated that the difference in overall survival between risk groups was closely related to cell cycle pathway. Notably, further analyses found the frequency of tumor mutations, immune infiltration level and expression of immune checkpoints were significantly different between the two risk groups, and the results of the immunotherapy cohort showed that patients in the high-risk group have a better immune response. Additionally, the high-risk group was found to have higher sensitivity to 5-fluorouracil, doxorubicin and gemcitabine.ConclusionThe novel signature of 3 anoikis-related genes (EZH2, KIF18A and NQO1) can predict the prognosis of patients with HCC, and provide a revealing insight into personalized treatments in HCC.

Dataset Information

ATG101-related signature predicts prognosis and therapeutic option in hepatocellular carcinoma.

Publications

ATG101-related signature predicts prognosis and therapeutic option in hepatocellular carcinoma.

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