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Development of epithelial-mesenchymal transition-related lncRNA signature for predicting survival and immune microenvironment in pancreatic cancerwithexperiment validation.

ABSTRACT: Long non-coding RNAs (LncRNAs) have crucial function in epithelial-mesenchymal transition (EMT) in pancreatic cancer. It is necessary to comprehensively analyze the potential role of EMT-related lncRNA in pancreatic cancer. In the present study, genomic data of pancreatic cancer from the TCGA database were downloaded and we found 368 EMT-related lncRNAs. According to the expression characteristics of prognostic-related lncRNAs, all samples could be divided into two clusters with different clinical outcomes and different tumor microenvironments. Moreover, an eleven EMT-related lncRNAs signature was established and verified. Patients with pancreatic cancer in the high-risk group had a shorter overall survival than those in the low-risk group and the signature could act as an independent prognostic factor. Further analysis suggested that the EMT-related lncRNAs might affect the prognosis of patients through immune mechanisms. All findings indicated that the signature and eleven lncRNAs might serve as potential prognostic biomarkers and therapeutic targets in the treatment of pancreatic cancer.

SUBMITTER: Gao Y

PROVIDER: S-EPMC8809919 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Development of epithelial-mesenchymal transition-related lncRNA signature for predicting survival and immune microenvironment in pancreatic cancerwithexperiment validation.

Gao Yong Y Liu Jinhui J Cai Baobao B Chen Qun Q Wang Guangfu G Lu Zipeng Z Jiang Kuirong K Miao Yi Y

Bioengineered 20211201 2

Long non-coding RNAs (LncRNAs) have crucial function in epithelial-mesenchymal transition (EMT) in pancreatic cancer. It is necessary to comprehensively analyze the potential role of EMT-related lncRNA in pancreatic cancer. In the present study, genomic data of pancreatic cancer from the TCGA database were downloaded and we found 368 EMT-related lncRNAs. According to the expression characteristics of prognostic-related lncRNAs, all samples could be divided into two clusters with different clinic ...[more]

PMID: 34854360

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Project description:BackgroundBreast cancer (BRCA) has become the most diagnosed cancer worldwide for female and seriously endanger female health. The epithelial-mesenchymal transition (EMT) process is associated with metastasis and drug resistance in BRCA patients. However, the prognostic value of EMT-related lncRNA in BRCA still needs to be revealed. The aim of this study is to construct an EMT-related lncRNA (ERL) signature with accuracy predictive ability for the prognosis of BRCA patients.MethodsRNA-seq expression data and Clinical characteristics obtained from the TCGA (The Cancer Genome Atlas) were used in the study. First, we identified the EMT-related lncRNA by the Pearson correlation analysis. An EMT-related lncRNAs prognostic risk signature was constructed using univariate Cox regression and Lasso-penalized Cox regression analyses. The model's performance was validated using Kaplan-Meier (KM) survival analysis, ROC curve and C-index. Finally, a nomogram was constructed for clinical practice in evaluating the patients with BRCA and validated by calibration curve and decision curve analysis (DCA). We also evaluated the drug sensitivity of signature lncRNA and the tumor immune cell infiltration in breast cancer.ResultsWe constructed a 10-lncRNA risk score signature based on the lncRNAs associated with the EMT process. We could assign BRCA patients to the high- and low-risk group according to the median risk score. The prognostic risk signature showed excellent accuracy and demonstrated sufficient independence from other clinical characteristics. The immune cell infiltration analysis showed that the prognostic risk signature was related to the infiltration of the immune cell subtype. Drug sensitivity analysis proved ERLs signature could effectively predict the sensitivity of patients to common chemotherapy drugs in BRCA and provide guidance for chemotherapy drugs for high-risk and low-risk patients.ConclusionOur ERL signature and nomogram have excellent prognostic value and could become reliable tools for clinical guidance.

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.

Project description:BackgroundCuproptosis is a novel form of cell death referred to as copper-dependent cytotoxicity. The regulation of proptosis is becoming an increasingly popular cancer treatment modality. To date, few studies have attempted to identify the cuproptosis-related long non-coding RNAs (CRLs). In this study, we sought to investigate the CRLs and construct a novel prognostic model for colorectal cancer (CRC).MethodsThe RNA-sequencing data of CRC patients were obtained from The Cancer Genome Atlas database. An analysis was conducted to identify the differentially expressed long non-coding RNAs, and a correlation analysis was performed to identify the CRLs. A univariate Cox analysis was conducted to select the prognostic CRLs. Based on a least absolute shrinkage and selection operator regression analysis, a prognostic signature comprising the 22 identified CRLs was constructed. A survival receiver operating characteristic curve analysis was conducted to evaluate the performance of the signature. Finally, an in vitro analysis was performed to investigate the function of lncRNA AC090116.1 in the CRC cells.ResultsA signature comprising 22 CRLs was developed. The patients in the training and validation sets were divided into the low- and high-risk groups and had significantly different survival probabilities. This signature had outstanding prognostic accuracy in predicting the 5-year overall survival of patients [training set, area under the curve (AUC) =0.820; validation set, AUC =0.810]. The pathway enrichment analysis showed that the differential genes between low and high groups were enriched in several important oncogenic- and metastatic-associated processes and pathways. Finally, the in vitro experiments showed that AC090116.1 silencing promoted the cuproptosis processes and suppressed cell proliferation.ConclusionsOur findings provided promising insights into the CRLs involved in CRC. The signature based on CRLs has been successfully devised to prognosticate the clinical outcomes and treatment responses in patients.

Dataset Information

Development of epithelial-mesenchymal transition-related lncRNA signature for predicting survival and immune microenvironment in pancreatic cancerwithexperiment validation.

Publications

Development of epithelial-mesenchymal transition-related lncRNA signature for predicting survival and immune microenvironment in pancreatic cancerwithexperiment validation.

Similar Datasets

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