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Autophagy-related genes prognosis signature as potential predictive markers for immunotherapy in hepatocellular carcinoma.

ABSTRACT: Autophagy-related genes (ATGs) depress tumorigenesis. However, in tumor tissue, it promotes tumor progression. Here, we demonstrated that 63 ATGs were differentially expressed in normal tissues and tumor tissues of hepatocellular carcinoma (HCC), and seven prognostic-related genes were chosen to establish prognostic risk signatures. It is not just an independent prognostic factor for HCC, but also closely related to the degree of malignancy of HCC. Further, the hallmarks of PI3K-AKT-mTOR signaling was significantly enriched in the high-risk group. Moreover, AKT-pS473 and mTOR-pS2448 expression was down-regulated and correlated with patient prognosis in high-risk group. Finally, we demonstrate that the prognosis signature of ATGs is closely related to immune cell infiltration and PD-L1 expression. In conclusion, ATGs are a crucial factor in the malignant progression of HCC and will be a new prognostic marker for diagnosis and treatment. ATGs prognostic signatures are potentially useful for predicting PD-L1 therapeutic effects.

SUBMITTER: Mao D

PROVIDER: S-EPMC6970541 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Autophagy-related genes prognosis signature as potential predictive markers for immunotherapy in hepatocellular carcinoma.

Mao Deli D Zhang Zhe Z Zhao Xin X Dong Xiaoqiang X

PeerJ 20200117

Autophagy-related genes (ATGs) depress tumorigenesis. However, in tumor tissue, it promotes tumor progression. Here, we demonstrated that 63 ATGs were differentially expressed in normal tissues and tumor tissues of hepatocellular carcinoma (HCC), and seven prognostic-related genes were chosen to establish prognostic risk signatures. It is not just an independent prognostic factor for HCC, but also closely related to the degree of malignancy of HCC. Further, the hallmarks of PI3K-AKT-mTOR signali ...[more]

PMID: 31988807

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Project description:Hepatocellular carcinoma (HCC) has been recognized as the third leading cause of cancer-related deaths worldwide. There is increasing evidence that the abnormal expression of autophagy-related genes plays an important role in the occurrence and development of HCC. Therefore, the study of autophagy-related genes can further elucidate the genetic drivers of cancer and provide valuable therapeutic targets for clinical treatment. In this study, we used 232 autophagy-related genes extracted from the Human Autophagy Database (HADb) and Molecular Signatures Database (MSigDB) to construct 1884 autophagy-related gene pairs. On this basis, we developed a prognostic model based on autophagy-related gene pairs using least absolute shrinkage and selection operator (LASSO) Cox regression to evaluate the prognosis of patients after liver cancer resection. We then used 845 liver cancer samples from three different databases to test the reliability of the risk signature through survival analysis, receiver operating characteristic (ROC) curve analysis, univariate and multivariate analysis. To further explore the underlying biological mechanisms, we conducted an enrichment analysis of autophagy-related genes. Finally, we combined the signature with independent prognostic factors to construct a nomogram. Based on the autophagy-related gene pair (ARGP) signature, we can divide patients into high- or low-risk groups. Survival analysis and ROC curve analysis verified the validity of the signature (AUC: 0.786-0.828). Multivariate Cox regression showed that the risk score can be used as an independent predictor of the clinical outcomes of liver cancer patients. Notably, this model has a more accurate predictive effect than most prognostic models for hepatocellular carcinoma. Moreover, our model is a powerful supplement to the HCC staging indicator, and a nomogram comprising both indicators can provide a better prognostic effect. Based on pairs of multiple autophagy-related genes, we proposed a prognostic model for predicting the overall survival rate of HCC patients after surgery, which is a promising prognostic indicator. This study confirms the importance of autophagy in the occurrence and development of HCC, and also provides potential biomarkers for targeted treatments.

Project description:Hepatocellular carcinoma (HCC) is one of the common malignant tumors. The prognosis and five-year survival rate of HCC are not promising due to tumor recurrence and metastasis. Exploring markers that contribute to the early diagnosis of HCC, markers for prognostic evaluation of HCC patients, and effective targets for treating HCC patients are in the spotlight of HCC therapy. Zinc Finger CCHC-Type Containing 17 (ZCCHC17) encodes the RNA binding protein ZCCHC17, but its role in HCC is still unclear. Here, 90 paraffin-embedded specimens combined with bioinformatics were used to comprehensively clarify the value of ZCCHC17 in the diagnosis and prognosis of HCC and its potential functions. Paraffin-embedded specimens were used to assess ZCCHC17 protein expression and its correlation with prognosis in 90 HCC patients. the public data sets of HCC patients from TCGA, ICG, and GEO databases were also used for further analysis. It was found that protein and mRNA levels of ZCCHC17 in HCC tissues were significantly higher than those in normal tissues. The abnormally high expression may be related to the abnormal DNA methylation of ZCCHC17 in tumor tissues. The high expression of ZCCHC17 is related to AFP, histologic grade, tumor status, vascular invasion, and pathological stage. Multi-data set analysis showed that patients with high ZCCHC17 expression had a worse prognosis, and multivariate cox regression analysis showed an independent prognostic significance of ZCCHC17. The results of functional analysis, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA), indicate that ZCCHC17 is mainly involved in immune regulation. Subsequently, further single-sample gene set enrichment analysis (ssGSEA) showed that the expression of ZCCHC17 was related to the infiltration of immune cells. Importantly, we also analyzed the relationship between ZCCHC17 and immune checkpoint genes, tumor mutation burden (TMB), microsatellite instability (MSI) and TP53 status in HCC patients and evaluated the role of ZCCHC17 in cancer immunotherapy. In summary, ZCCHC17 is a novel marker for the diagnosis and prognostic evaluation of HCC. Concurrently, it regulates immune cells in the tumor microenvironment (TME) of HCC patients, which has a specific reference value for the immunotherapy of HCC.

Project description:Background: Pyroptosis, a newly discovered type of programmed cell death, has both anti-tumor and tumor-promoting effects on carcinogenesis. In hepatocellular carcinoma (HCC), however, the associations between pyroptosis-regulated genes and prognosis, immune microenvironment, and immunotherapy response remain unclear. Samples and methods: Sequencing data were collected from The Cancer Genome Atlas database, The International Cancer Genome Consortium (ICGC), and The Integrative Molecular Database of Hepatocellular Carcinoma (HCCDB). First, we investigated the expression levels and copy number variations (CNVs) of 56 pyroptosis genes in HCC and pan-cancer. Next, we identified 614 genes related to 56 pyroptosis-associated genes at the expression, mutation, and CNVs levels. Pathway enrichment analysis of 614 genes in the Hallmark, KEGG, and Reactome databases yielded a total of 253 significant signaling pathways. The pyroptosis-regulated genes (PRGs) comprised 108 genes that were derived from the top 20 signaling pathways, of which 57 genes had prognostic value in HCC. The least absolute shrinkage and selection operator (LASSO) analysis was performed to screen for PRGs with prognostic values. Ultimately, we constructed a risk score model with seven PRGs to predict HCC prognosis and validated its predictive value in three independent HCC cohorts. Risk scores were used to illustrate receiver operating characteristic (ROC) curves predicting 1, 3, and 5-years overall survival (OS). Single-sample gene set enrichment analysis (ssGSEA), was performed to study 28 types of immune cells infiltrated in HCC. The relationship between the risk signature and six immune checkpoint genes and immunotherapy was analyzed. Results: A total of seven PRGs were obtained following multiple screening steps. The risk score model containing seven PRGs was found to correlate significantly with the HCC prognosis of the training group. In addition, we validated the risk score model in two additional HCC cohorts. The risk score significantly correlated with infiltrating immune cells (i. e. CD4+ T cells, etc.), ICB key molecules (i. e. HAVCR2, etc.), and ICB response. Conclusions: This study demonstrated a vital role of PRGs in predicting the prognosis and immunotherapy response of HCC patients. The risk model could pave the way for drugs targeting pyroptosis and immune checkpoints in HCC.

Dataset Information

Autophagy-related genes prognosis signature as potential predictive markers for immunotherapy in hepatocellular carcinoma.

Publications

Autophagy-related genes prognosis signature as potential predictive markers for immunotherapy in hepatocellular carcinoma.

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