Dataset Information

The autophagy-related marker LC3 can predict prognosis in human hepatocellular carcinoma.

ABSTRACT:

Background

Defects of autophagy and endoplasmic reticulum (ER) stress are related to many diseases and tumors. However, only a few studies have examined hepatocellular carcinoma (HCC) as related to these processes. Therefore, in this study, we investigated the expression and extent of autophagy and ER stress-related markers in HCC and their influence on clinical characteristics and prognosis for each protein.

Methodology

The expression of autophagy-related markers (LC3 and Beclin-1) and ER stress-related markers (GRP78 and CHOP) was analyzed by immunohistochemistry on tissues from completely resected specimens of 190 HCC patients. Their influence on clinicopathologic features and prognosis were evaluated using the chi-square test and Kaplan-Meier analysis. Correlations of each protein were determined by Spearman's correlation analysis.

Principal findings

LC3 expression was not correlated with TNM, BCLC stage, or Edmonson-Steiner grading, whereas it was correlated with longer overall survival (OS) (p = 0.039) and tended to be related with longer time to recurrence (TTR) (p=0.068) although it did not show statistical significance. Multivariate analysis indicated that LC3 expression was a significantly independent prognostic factor of OS (HR, 0.42; 95% CI, 0.22-0.80; p-value=0.009) and TTR (HR, 0.54; 95% CI, 0.33-0.90; p=0.017). Expression of LC3 in advanced stages of TNM (III) (p=0.045) and Edmonson-Steiner Grades (III and IV) (p=0.043) was correlated with longer survival, but not in the early stages. A positive correlation was not observed between the expression of autophagy-related markers and ER stress-related markers.

Conclusion

Our results suggest that the expression and extent of LC3 might be a strong prognostic factor of HCC, especially in patients with surgical resection.

SUBMITTER: Lee YJ

PROVIDER: S-EPMC3839913 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Publications

The autophagy-related marker LC3 can predict prognosis in human hepatocellular carcinoma.

Lee Yoo Jin YJ Hah Yu Jin YJ Kang Yu Na YN Kang Koo Jeong KJ Hwang Jae Seok JS Chung Woo Jin WJ Cho Kwang Bum KB Park Kyung Sik KS Kim Eun Soo ES Seo Hye-Young HY Kim Mi-Kyung MK Park Keun-Gyu KG Jang Byoung Kuk BK

PloS one 20131125 11

<h4>Background</h4>Defects of autophagy and endoplasmic reticulum (ER) stress are related to many diseases and tumors. However, only a few studies have examined hepatocellular carcinoma (HCC) as related to these processes. Therefore, in this study, we investigated the expression and extent of autophagy and ER stress-related markers in HCC and their influence on clinical characteristics and prognosis for each protein.<h4>Methodology</h4>The expression of autophagy-related markers (LC3 and Beclin- ...[more]

PMID: 24282606

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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:BackgroundTumor-related macrophages (TAMs) have emerged as an essential part of the immune regulatory network in hepatocellular carcinoma (HCC). Constructing a TAM-related signature is significant for evaluating prognosis and immunotherapeutic response of HCC patients.MethodsInformative single-cell RNA sequencing (scRNA-seq) dataset was obtained from the Gene Expression Omnibus (GEO) database, and diverse cell subpopulations were identified by clustering dimension reduction. Moreover, we determined molecular subtypes with the best clustering efficacy by calculating the cumulative distribution function (CDF). The ESTIMATE method, CIBERSORT (cell-type identification by estimating relative subsets of RNA transcripts) algorithm and publicly available tumor immune dysfunction and exclusion (TIDE) tools were used to characterize the immune landscape and tumor immune escape status. A TAM-related gene risk model was constructed through Cox regression and verified in multiple datasets and dimensions. We also performed functional enrichment analysis to detect potential signaling pathways related to TAM marker genes.ResultsIn total, 10 subpopulations and 165 TAM-related marker genes were obtained from the scRNA-seq dataset (GSE149614). After clustering 3 molecular subtypes based on TAM-related marker genes, we found significantly different prognostic survival and immune signatures among the three subtypes. Subsequently, a 9-gene predictive signature (TPP1, FTL, CXCL8, CD68, ATP6V1F, CSTB, YBX1, LGALS3, and APLP2) was identified as an independent prognostic factor for HCC patients. Those patients with high RiskScore had a lower survival rate and benefited less from immunotherapy than those with low RiskScore. Moreover, more samples of the Cluster C subtype were enriched in the high-risk group, with higher tumor immune escape incidence.ConclusionsWe constructed a TAM-related signature with excellent efficacy for predicting prognostic survival and immunotherapeutic responses in HCC patients.

Dataset Information

The autophagy-related marker LC3 can predict prognosis in human hepatocellular carcinoma.

Background

Methodology

Principal findings

Conclusion

Publications

The autophagy-related marker LC3 can predict prognosis in human hepatocellular carcinoma.

Similar Datasets

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