Development and validation of a robust epithelial-mesenchymal transition (EMT)-related prognostic signature for hepatocellular carcinoma

Association of mitochondrial phosphoenolpyruvate carboxykinase with prognosis and immune regulation in hepatocellular carcinoma

Mitochondrial phosphoenolpyruvate carboxykinase (PCK2), a mitochondrial isoenzyme, supports the growth of cancer cells under glucose deficiency conditions in vitro. This study investigated the role and potential mechanism of PCK2 in the occurrence and development of Hepatocellular carcinoma (HCC). The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and other databases distinguish the expression of PCK2 and verified by qRT-PCR and Western blotting. Kaplan-Meier was conducted to assess PCK2 survival in HCC. The potential biological function of PCK2 was verified by enrichment analysis and gene set enrichment analysis (GSEA). The correlation between PCK2 expression and immune invasion and checkpoint was found by utilizing Tumor Immune Estimation Resource (TIMER). Lastly, the effects of PCK2 on the proliferation and metastasis of hepatocellular carcinoma cells were evaluated by cell tests, and the expressions of Epithelial mesenchymal transformation (EMT) and apoptosis related proteins were detected. PCK2 is down-regulated in HCC, indicating a poor prognosis. PCK2 gene mutation accounted for 1.3% of HCC. Functional enrichment analysis indicated the potential of PCK2 as a metabolism-related therapeutic target. Subsequently, we identified several signaling pathways related to the biological function of PCK2. The involvement of PCK2 in immune regulation was verified and key immune checkpoints were predicted. Ultimately, after PCK2 knockdown, cell proliferation and migration were significantly increased, and N-cadherin and vimentin expression were increased. PCK2 has been implicated in immune regulation, proliferation, and metastasis of hepatocellular carcinoma, and is emerging as a novel predictive biomarker and metabolic-related clinical target.

Development and validation of robust metabolism-related gene signature in the prognostic prediction of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant tumours worldwide. Given metabolic reprogramming in tumours was a crucial hallmark, several studies have demonstrated its value in the diagnostics and surveillance of malignant tumours. The present study aimed to identify a cluster of metabolism-related genes to construct a prediction model for the prognosis of HCC. Multiple cohorts of HCC cases (466 cases) from public datasets were included in the present analysis. (GEO cohort) After identifying a list of metabolism-related genes associated with prognosis, a risk score based on metabolism-related genes was formulated via the LASSO-Cox and LASSO-pcvl algorithms. According to the risk score, patients were stratified into low- and high-risk groups, and further analysis and validation were accordingly conducted. The results revealed that high-risk patients had a significantly worse 5-year overall survival (OS) than low-risk patients in the GEO cohort. (30.0% vs. 57.8%; hazard ratio [HR], 0.411; 95% confidence interval [95% CI], 0.302-0.651; p < 0.001) This observation was confirmed in the external TCGA-LIHC cohort. (34.5% vs. 54.4%; HR 0.452; 95% CI, 0.299-0.681; p < 0.001) To promote the predictive ability of the model, risk score, age, gender and tumour stage were integrated into a nomogram. According to the results of receiver operating characteristic curves and decision curves analysis, the nomogram score possessed a superior predictive ability than conventional factors, which indicate that the risk score combined with clinicopathological features was able to achieve a robust prediction for OS and improve the individualized clinical decision making of HCC patients. In conclusion, the metabolic genes related to OS were identified and developed a metabolism-based predictive model for HCC. Through a series of bioinformatics and statistical analyses, the predictive ability of the model was approved.

EMT-Related Genes Have No Prognostic Relevance in Metastatic Colorectal Cancer as Opposed to Stage II/III: Analysis of the Randomised, Phase III Trial FIRE-3 (AIO KRK 0306; FIRE-3)

INTRODUCTION

There is no standard treatment after resection of colorectal liver metastases and the role of systemic therapy remains controversial. To avoid over- or undertreatment, proper risk stratification with regard to postoperative treatment strategy is highly needed. We recently demonstrated the prognostic relevance of EMT-related (epithelial-mesenchymal transition) genes in stage II/III CRC. As EMT is a major step in CRC progression, we now aimed to analyse the prognostic relevance of EMT-related genes in stage IV CRC using the study cohort of the FIRE-3 trial, an open-label multi-centre randomised controlled phase III trial of patients with metastatic CRC.

METHODS

Overall and progression free survival were considered as endpoints (n = 350). To investigate the prognostic relevance of EMT-related genes on either endpoint, we compared predictive performance of different models using clinical data only to models using gene data in addition to clinical data, expecting better predictive performance if EMT-related genes have prognostic value. In addition to baseline models (Kaplan Meier (KM), (regularised) Cox), Random Survival Forest (RSF), and gradient boosted trees (GBT) were fit to the data. Repeated, nested five-fold cross-validation was used for hyperparameter optimisation and performance evaluation. Predictive performance was measured by the integrated Brier score (IBS).

RESULTS

The baseline KM model showed the best performance (OS: 0.250, PFS: 0.251). None of the other models were able to outperform the KM when using clinical data only according to the IBS scores (OS: 0.253 (Cox), 0.256 (RSF), 0.284 (GBT); PFS: 0.254 (Cox), 0.256 (RSF), 0.276 (GBT)). When adding gene data, performance of GBT improved slightly (OS: 0.262 vs. 0.284; PFS: 0.268 vs. 0.276), however, none of the models performed better than the KM baseline.

CONCLUSION

Overall, the results suggest that the prognostic relevance of EMT-related genes may be stage-dependent and that EMT-related genes have no prognostic relevance in stage IV CRC.

The association between several autophagy-related genes and their prognostic values in hepatocellular carcinoma: a study on the foundation of TCGA, GEPIA and HPA databases

BACKGROUND

The purpose of this study was to investigate the relationship between the expression of autophagy-related genes and prognosis in hepatocellular carcinoma (HCC).

METHODS AND RESULTS

We selected three autophagy-related genes (ATG3, ATG7, and ATG9A) from gene expression data of liver cancer patients in The Cancer Genome Atlas (TCGA) database by Kaplan-Meier survival analysis, univariate and multivariate Cox regression analysis, and Gene Set Enrichment Analysis (GSEA). Human Protein Atlas (HPA) and Gene Expression Profiling Interactive Analysis (GEPIA) databases were applied to testify the credibility of our results. The expression levels of ATG3, ATG7, and ATG9A were verified by real-time quantitative PCR (RT-qPCR) in normal liver cells (L02) and three HCC cell lines (HepG2, Hep3b, and Li-7). Data analysis results from TCGA showed high ATG3, ATG7, ATG9A expression in HCC tumor tissues. Kaplan-Meier survival analysis showed that the survival rate of the high expression group of ATG3, ATG7, and ATG9A was all significantly lower than the low expression group. GSEA analysis showed that many signaling pathways (such as the regulation of autophagy, glycine serine and threonine metabolism, pathways in cancer, mitogen-activated protein kinase (MAPK) signaling pathway, mammalian target of rapamycin (mTOR) signaling pathway, as well as P53 signaling pathway) were differentially enriched in HCCs with ATG3, ATG7, and ATG9A expression. GEPIA and RT-qPCR also identified that the mRNA expression level of ATG3, ATG7, and ATG9A in normal liver cells were significantly lower than in HCC cells. High protein expression of ATG3, ATG7, and ATG9A was displayed in HCCs from the HPA database.

CONCLUSIONS

The ATG3, ATG7, ATG9A might be utilized as prognostic biomarkers for liver cancer.

Risk characteristics with seven epithelial-mesenchymal transition-related genes are used to predict the prognosis of patients with hepatocellular carcinoma

Background

Epithelial-mesenchymal transition (EMT)-related genes (ERGs) have been shown to play an important role in cancer invasion, tumor resistance, and tumor metastasis of hepatocellular carcinoma. This study sought to examine the prognostic value of ERGs and other pre-hepatoma genes.

Methods

Relevant data from The Cancer Genome Atlas (TCGA) were analyzed and synthesized. Specifically, 1,014 ERGs were downloaded and subject to a gene set enrichment analysis; 318 different EAG expressions were found, and the possible molecular mechanism of EAG was predicted by GO analysis and KEGG analysis. To determine the prediction of ERGS, a Cox regression model was used to establish a risk hypothesis. Based on risk patterns, patients were divided into high- or low-risk groups. Kaplan-Meier and receiver operating characteristic (ROC) curves confirmed the predictive value of the model.

Results

Seven prognostically relevant ERGs (i.e., ECT2, EZH2, MYCN, ROR2, SPP1, SQSTM1, and STC2) were identified. Using Cox's regression analysis method, appropriate cases were selected to establish a new risk prediction model. Under the risk model, the overall survival rate of the low-risk group samples was higher than that of the high-risk group samples (P<0.00001).

Conclusions

In short, we developed a risk model for liver cancer based on ERGs terminology. This model improve the postpartum treatment of patients with liver cancer.

A Novel Expression Signature from the Perspective of Mesenchymal-Epithelial Transition for Hepatocellular Carcinoma with Regard to Prognosis, Clinicopathological Features, Immune Cell Infiltration, Chemotherapeutic Efficacy, and Immunosuppressive Molecules

Purpose

Mesenchymal-epithelial transition (MET), a reverse biological process to epithelial-mesenchymal transition (EMT), is involved in tumor metastasis and invasion. However, the role of MET-related genes (MRGs) in hepatocellular carcinoma (HCC) prognosis remains unclear.

Methods

In this research, we obtained MRGs data and clinical information from public databases. In the TCGA dataset, a prognostic signature for HCC was constructed by the least absolute shrinkage and selection operator (LASSO) method and externally verified using the ICGC dataset.

Results

There were 148 differentially expressed MRGs (DEMRGs), out of which 37 MRGs were found associated with overall survival (OS) in the univariate Cox analysis. A novel signature integrating of 5 MRGs was constructed, which split patients into high- and low-risk groups. Kaplan-Meier analysis revealed that high-risk patients had unfavorable OS than those low-risk counterparts. Receiver operating characteristic curve (ROC) showed great performance of this signature in predictive ability. Multivariate Cox analysis confirmed that this signature could independently predict HCC prognosis. The analysis of immune cell infiltration demonstrated that immune status varied differently between high- and low-risk groups. The analysis of clinicopathological characteristics suggested that tumor grade, clinical stage, and T stage were different between risk groups. The analysis between this signature and chemotherapeutic efficacy and immunosuppressive molecules indicated that this signature could serve as a promising predictor.

Conclusions

In conclusion, we constructed and verified a novel signature from the perspective of MET, which was significantly associated with HCC prognosis, clinicopathological features, immune status, chemotherapeutic efficacy, and immunosuppressive biomarkers.