Dataset Information

Comprehensive analysis of partial epithelial mesenchymal transition-related genes in hepatocellular carcinoma.

ABSTRACT: Increasing evidence has revealed that cancer cells undergoing an intermediate state, partial epithelial mesenchymal transition (p-EMT), tend to metastasize rather than complete EMT. We performed a comprehensive analysis of E-cadherin and 25 p-EMT-related genes in HCC to explore the roles and regulatory mechanisms of them in HCC. We analysed E-cadherin and 25 p-EMT-related genes in HCC and constructed an mRNA-miRNA-lncRNA ceRNA subnetwork containing p-EMT-related genes by bioinformatic approaches. IHC was used to identify the protein expression of key p-EMT-related genes, P4HA2, ITGA5, MMP9, MT1X and SPP1. Complete EMT is not necessary for HCC progression. Overexpression of P4HA2, ITGA5, MMP9, SPP1 and down-regulation of MT1X were found in HCC tissues, which were significantly associated with poor prognosis of HCC patients. By means of stepwise reverse prediction and validation from mRNA to lncRNA, an mRNA-miRNA-lncRNA ceRNA subnetwork correlated with HCC prognosis was identified by expression and survival analysis. This study implied that key p-EMT-related genes P4HA2, ITGA5, MMP9, MT1X, SPP1 could be prognostic biomarkers and potential targets of therapy for HCC patients. We constructed an mRNA-miRNA-lncRNA subnetwork containing p-EMT-related genes successfully, among which each component might be utilized as a prognostic biomarker of HCC.

SUBMITTER: Lei Y

PROVIDER: S-EPMC7810929 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Comprehensive analysis of partial epithelial mesenchymal transition-related genes in hepatocellular carcinoma.

Lei Yu Y Yan Wei W Lin Zhuoying Z Liu Jingmei J Tian Dean D Han Ping P

Journal of cellular and molecular medicine 20201120 1

Increasing evidence has revealed that cancer cells undergoing an intermediate state, partial epithelial mesenchymal transition (p-EMT), tend to metastasize rather than complete EMT. We performed a comprehensive analysis of E-cadherin and 25 p-EMT-related genes in HCC to explore the roles and regulatory mechanisms of them in HCC. We analysed E-cadherin and 25 p-EMT-related genes in HCC and constructed an mRNA-miRNA-lncRNA ceRNA subnetwork containing p-EMT-related genes by bioinformatic approaches ...[more]

PMID: 33215860

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Project description:Background: Hepatocellular carcinoma (HCC) is a highly heterogeneous disease with the high rates of the morbidity and mortality due to the lack of the effective prognostic model for prediction. Aim: To construct a risk model composed of the epithelial-mesenchymal transition (EMT)-related immune genes for the assessment of the prognosis, immune infiltration status, and chemosensitivity. Methods: We obtained the transcriptome and clinical data of the HCC samples from The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC) databases. The Pearson correlation analysis was applied to identify the differentially expressed EMT-related immune genes (DE-EMTri-genes). Subsequently, the univariate Cox regression was introduced to screen out the prognostic gene sets and a risk model was constructed based on the least absolute shrinkage and selection operator-penalized Cox regression. Additionally, the receiver operating characteristic (ROC) curves were plotted to compare the prognostic value of the newly established model compared with the previous model. Furthermore, the correlation between the risk model and survival probability, immune characteristic, and efficacy of the chemotherapeutics were analyzed by the bioinformatics methods. Results: Six DE-EMTri-genes were ultimately selected to construct the prognostic model. The area under the curve (AUC) values for 1-, 2-, and 3- year were 0.773, 0.721, and 0.673, respectively. Stratified survival analysis suggested that the prognosis of the low-score group was superior to the high-score group. Moreover, the univariate and multivariate analysis indicated that risk score [hazard ratio (HR) 5.071, 95% CI 3.050, 8.432; HR 4.396, 95% CI 2.624, 7.366; p < 0.001] and stage (HR 2.500, 95% CI 1.721, 3.632; HR 2.111, 95% CI 1.443, 3.089; p < 0.001) served as an independent predictive factors in HCC. In addition, the macrophages, natural killer (NK) cells, and regulatory T (Treg) cells were significantly enriched in the high-risk group. Finally, the patients with the high-risk score might be more sensitive to cisplatin, doxorubicin, etoposide, gemcitabine, and mitomycin C. Conclusion: We established a reliable EMTri-genes-based prognostic signature, which may hold promise for the clinical prediction.

Project description:AbstractReliable biomarkers are of great significance for the treatment and diagnosis of hepatocellular carcinoma (HCC). This study identified potential prognostic epithelial-mesenchymal transition related lncRNAs (ERLs) by the cancer genome atlas (TCGA) database and bioinformatics.The differential expression of long noncoding RNA (lncRNA) was obtained by analyzing the lncRNA data of 370 HCC samples in TCGA. Then, Pearson correlation analysis was carried out with EMT related genes (ERGs) from molecular signatures database. Combined with the univariate Cox expression analysis of the total survival rate of hepatocellular carcinoma (HCC) patients, the prognostic ERLs were obtained. Then use "step" function to select the optimal combination of constructing multivariate Cox expression model. The expression levels of ERLs in HCC samples were verified by real-time quantitative polymerase chain reaction.Finally, we identified 5 prognostic ERLs (AC023157.3, AC099850.3, AL031985.3, AL365203.2, CYTOR). The model showed that these prognostic markers were reliable independent predictors of risk factors (P value <.0001, hazard ratio [HR] = 2.400, 95% confidence interval [CI] = 1.667-3.454 for OS). In the time-dependent receiver operating characteristic analysis, this prognostic marker is a good predictor of HCC survival (area under the curve of 1 year, 2 years, 3 years, and 5 years are 0.754, 0.720, 0.704, and 0.662 respectively). We analyzed the correlation of clinical characteristics of these prognostic markers, and the results show that this prognostic marker is an independent factor that can predict the prognosis of HCC more accurately. In addition, by matching with the Molecular Signatures Database, we obtained 18 ERLs, and then constructed the HCC prognosis model and clinical feature correlation analysis using 5 prognostic ERLs. The results show that these prognostic markers have reliable independent predictive value. Bioinformatics analysis showed that these prognostic markers were involved in the regulation of EMT and related functions of tumor occurrence and migration.Five prognostic types of ERLs identified in this study can be used as potential biomarkers to predict the prognosis of HCC.

Project description:Immunotherapy has yielded encouraging results in the treatment of advanced hepatocellular carcinoma (HCC). However, the relationship between epithelial-mesenchymal transition (EMT) and immunotherapy for HCC has not been adequately explained. In this study, we comprehensively analyzed a bulk RNA sequence dataset of 365 HCC patients in The Cancer Genome Atlas (TCGA) dataset. Subsequently, we constructed a prognostic signature based on 6 EMT-related genes and divided 365 HCC patients into high- and low-risk groups. The predictive efficacy of the signature was well validated in different clinical subgroups and in two independent external datasets. We further explored the relationship between prognostic signature and immunotherapy response in terms of immune cell infiltration, somatic mutations, tumor mutation burden (TMB), microsatellite instability (MSI), immune checkpoint-associated gene expression, single-nucleotide variants (SNV) neoantigens, cancer testicular antigens (CTA) scores, and tumor immune dysfunction and exclusion (TIDE) scores. We validated the predictive efficacy of prognostic signature for immunotherapy response using external independent immunotherapy data. Real-time quantitative polymerase chain reaction (qRT-PCR) was used to validate EMT-related gene overexpression in HCC tissue samples. Prognostic signature was an independent risk factor affecting the prognosis of HCC patients and has shown superiority in predicting patient survival compared to other clinical factors. Compared with the low-risk group, the proportion of Activated_CD4_T_cell, Type_2_T_helper_cel, and macrophages were higher in the tumor microenvironment of HCC patients in the high-risk group, while the Activated_CD8_T_cell and CD56bright_natural_killer_cell proportions were lower. The prognostic signature was positively correlated with TMB scores, MSI scores, SNV neoantigens scores, expression levels of immune checkpoint-related genes, and TIDE scores, and patients in the high-risk group were more suitable for immunotherapy. qRT-PCR confirms overexpression of 6 EMT-related genes in HCC tissues for the construction of prognostic signature. Our novel prognostic signature can effectively predict the prognosis and immunotherapy response of HCC patients. In the future, it will be an effective tool for physicians to screen suitable immunotherapy populations and improve response rates and overall survival (OS).

Project description:BackgroundTumor metastasis is one of the leading reasons of the dismal prognosis of hepatocellular carcinoma (HCC). Epithelial-mesenchymal transition (EMT) is closely associated with tumor metastasis including HCC. The purpose of this study is to construct and validate an EMT-related gene signature for predicting the prognosis of HCC patients.MethodsGene expression data of HCC patients was downloaded from The Cancer Genome Atlas (TCGA) database. Gene set enrichment analysis (GSEA) was performed to found the EMT-related gene sets which were obviously distinct between normal samples and paired HCC samples. Cox regression analysis was used to develop an EMT-related prognostic signature, and the performance of the signature was evaluated by Kaplan-Meier curves and time-dependent receiver operating characteristic (ROC) curves. A nomogram incorporating the independent predictors was established. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression levels of the hub genes in HCC cell lines, and the role of PDCD6 in the metastasis of HCC was determined by functional experiments.ResultsAn EMT-related 5-gene signature (PDCD6, TCOF1, TRIM28, EZH2 and FAM83D) was constructed using univariate and multivariate Cox regression analysis. Based on the signature, the HCC patients were classified into high- and low-risk groups, and patients in high-risk group had a poor prognosis. Time-dependent ROC and Cox regression analyses suggested that the signature could predict HCC prognosis exactly and independently. The predictive capacity of the signature was also validated in two external cohorts. GSEA results showed that many cancer-related signaling pathways such as PI3K/Akt/mTOR pathway and TGF-β/SMAD pathway were enriched in high-risk group. The result of qRT-PCR revealed that PDCD6, TCOF1 and FAM83D were highly expressed in HCC cancer cells. Among them, PDCD6 were found to promote cell migration and invasion.ConclusionThe EMT-related 5-gene signature can serve as a promising prognostic biomarker for HCC patients and may provide a novel mechanism of HCC metastasis.

Dataset Information

Comprehensive analysis of partial epithelial mesenchymal transition-related genes in hepatocellular carcinoma.

Publications

Comprehensive analysis of partial epithelial mesenchymal transition-related genes in hepatocellular carcinoma.

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