A novel epithelial–mesenchymal transition gene signature for the immune status and prognosis of hepatocellular carcinoma

Abstract

Background This study clarified whether EMT-related genes can predict immunotherapy efficacy and overall survival in patients with HCC. Methods The RNA-sequencing profiles and patient information of 370 samples were derived from the Cancer Genome Atlas (TCGA) dataset, and EMT-related genes were obtained from the Molecular Signatures database. The signature model was constructed using the least absolute shrinkage and selection operator Cox regression analysis in TCGA cohort. Validation data were obtained from the International Cancer Genome Consortium (ICGC) dataset of patients with HCC. Kaplan–Meier analysis and multivariate Cox analyses were employed to estimate the prognostic value. Immune status and tumor microenvironment were estimated using a single-sample gene set enrichment analysis (ssGSEA). The expression of prognostic genes was verified using qRT-PCR analysis of HCC cell lines. Results A signature model was constructed using EMT-related genes to determine HCC prognosis, based on which patients were divided into high-risk and low-risk groups. The risk score, as an independent factor, was related to tumor stage, grade, and immune cells infiltration. The results indicated that the most prognostic genes were highly expressed in the HCC cell lines, but GADD45B was down-regulated. Enrichment analysis suggested that immunoglobulin receptor binding and material metabolism were essential in the prognostic signature. Conclusion Our novel prognostic signature model has a vital impact on immune status and prognosis, significantly helping the decision-making related to the diagnosis and treatment of patients with HCC.

Construction and validation of a novel signature based on epithelial-mesenchymal transition–related genes to predict prognosis and immunotherapy response in hepatocellular carcinoma by comprehensive analysis of the tumor microenvironment

“…To further verify the superiority of the prognostic signature, we compare the ROC curve of our prognostic signature with the ROC curve of the prognostic signature constructed by Shi et al (Shi et al 2022 ) based on EMT-related genes. It is found that not only the AUC of our prognostic signature in the TCGA training set (AUC of 1 year: 0.785, AUC of 3 years: 0.698) and ICGC verification set (AUC of 1 year: 0.754, AUC of 3 years: 0.676) are better than those of the prognostic signature constructed by Shi et al (TCGA: AUC of 1 year: 0.767, AUC of 3 years: 0.680; ICGC: AUC of 1 year: 0.677, AUC of 3 years: 0.689).…”

“…Shi et al (Shi et al 2022) based on EMT-related genes. It is found that not only the AUC of our prognostic signature in the TCGA training set (AUC of 1 year: 0.785, AUC of 3 years: 0.698) and ICGC verification set (AUC of 1 year: 0.754, AUC of 3 years: 0.676) are better than those of the prognostic signature constructed byShi et al …”

A Novel Risk Model for lncRNAs Associated with Oxidative Stress Predicts Prognosis of Bladder Cancer

“…First, we used R and statistical analysis to develop prognostic risk models for eight DEOSlncRNAs using public databases. Although these approaches have been used and proved in numerous studies [52,53] and some of the eight DEOSlncR-NAs have been studied to some extent [35][36][37][38][39][40][41], further research is needed to reveal the association between eight DEOSlncRNAs and OS. And more, in-depth studies are needed including their functions and molecular mechanisms.…”

Dual-region-based computed tomography radiomics analysis for the non-invasive prediction of telomerase reverse transcriptase status and clinical prognosis in liver cancer

“…The current gold standard for liver cancer prognostic evaluation is the Barcelona Clinic Liver Cancer (BCLC) prognosis and treatment strategy [2]. However, high-level heterogeneity, along with the aggressive nature of HCC, results in poor prognosis, and the 5-year HCC survival rate is 18% [3][4][5]. In most studies, tumor samples were collected during resection and a correlation was checked between the patient prognosis and pathological ndings; however, the study ndings were not representative of the condition of unoperated patients.…”

“…Telomerase reverse transcriptase (TERT) can directly regulate various hallmarks of cancer, including sustaining proliferative signaling, evading growth suppressors, inducing angiogenesis, resisting cell death, activating invasion and metastasis, promoting tumor in ammation, and enabling replicative immortality [5]. Currently, the determination process of TERT is expensive, complicated, and lacks sensitivity, thereby limiting its clinical application [9][10][11][12].…”