Dataset Information

Construction and validation of a novel prognostic signature of microRNAs in lung adenocarcinoma.

ABSTRACT: MicroRNA (miRNA, miR) has been reported to be highly implicated in a wide range of biological processes in lung cancer (LC), and identification of differentially expressed miRNAs between normal and LC samples has been widely used in the discovery of prognostic factors for overall survival (OS) and response to therapy. The present study was designed to develop and evaluate a miRNA-based signature with prognostic value for the OS of lung adenocarcinoma (LUAD), a common histologic subtype of LC. In brief, the miRNA expression profiles and clinicopathological factors of 499 LUAD patients were collected from The Cancer Genome Atlas (TCGA) database. Kaplan-Meier (K-M) survival analysis showed significant correlations between differentially expressed miRNAs and LUAD survival outcomes. Afterward, 1,000 resample LUAD training matrices based on the training set was applied to identify the potential prognostic miRNAs. The least absolute shrinkage and selection operator (LASSO) cox regression analysis was used to constructed a six-miRNA based prognostic signature for LUAD patients. Samples with different risk scores displayed distinct OS in K-M analysis, indicating considerable predictive accuracy of this signature in both training and validation sets. Furthermore, time-dependent receiver operating characteristic (ROC) analysis demonstrated the nomogram achieved higher predictive accuracy than any other clinical variables after incorporating the clinical information (age, sex, stage, and recurrence). In the stratification analysis, the prognostic value of this classifier in LUAD patients was validated to be independent of other clinicopathological variables, such as age, gender, tumor recurrence, and early stage. Gene set annotation analyses were also conducted through the Hallmark gene set and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, indicating target genes of the six miRNAs were positively related to various molecular pathways of cancer, such as hallmark UV response, Wnt signaling pathway and mTOR signaling pathway. In addition, fresh cancer tissue samples and matched adjacent tissue samples from 12 LUAD patients were collected to verify the expression of miR-582's target genes in the model, further revealing the potential relationship between SOX9, RASA1, CEP55, MAP4K4 and LUAD tumorigenesis, and validating the predictive value of the model. Taken together, the present study identified a robust signature for the OS prediction of LUAD patients, which could potentially aid in the individualized selection of therapeutic approaches for LUAD patients.

SUBMITTER: Li W

PROVIDER: S-EPMC7798616 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Construction and validation of a novel prognostic signature of microRNAs in lung adenocarcinoma.

Li Wanzhen W Liu Shiqing S Su Shihong S Chen Yang Y Sun Gengyun G

PeerJ 20210108

MicroRNA (miRNA, miR) has been reported to be highly implicated in a wide range of biological processes in lung cancer (LC), and identification of differentially expressed miRNAs between normal and LC samples has been widely used in the discovery of prognostic factors for overall survival (OS) and response to therapy. The present study was designed to develop and evaluate a miRNA-based signature with prognostic value for the OS of lung adenocarcinoma (LUAD), a common histologic subtype of LC. In ...[more]

PMID: 33510968

Similar Datasets

Project description:Background: Long non-coding RNAs (lncRNAs) are drawing increasing attention as promising predictors of prognosis for lung adenocarcinoma (LUAD) patients. Necroptosis, a novel regulated mechanism of necrotic cell death, plays an important role in the biological process of cancer. The aim of this study was to identify the necroptosis-related lncRNAs (NRLRs) in a LUAD cohort and establish a necroptosis-related lncRNA signature (NRLSig) to stratify LUAD patients. Methods: NRLRs were identified in LUAD patients from The Cancer Genome Atlas (TCGA) database using Pearson correlation analysis between necroptosis-related genes and lncRNAs. Then the NRLSig was identified using univariate Cox regression analysis and LASSO regression analysis. Assessments of the signature were performed based on survival analysis, receiver operating characteristic (ROC) curve analysis and clustering analysis. Next, a nomogram containing the NRLSig and clinical information was developed through univariate and multivariate Cox regression analysis. Further, functional enrichment analysis of the selected lncRNAs in NRLSig and the association between NRLSig and the immune infiltration were also evaluated. Results: A 4-lncRNA signature, incorporating LINC00941, AP001453.2, AC026368.1, and AC236972.3, was identified to predict overall survival (OS) and stratify LUAD patients into different groups. Survival analysis, ROC curve analysis and clustering analysis showed good performance in the prognostic prediction of the lncRNA signature. Then, a nomogram containing the NRLSig was developed and showed satisfactory predictive accuracy, calibration and clinical usefulness. The co-expressed genes of selected NRLRs were enriched in several biological functions and signaling pathways. Finally, differences in the abundance of immune cells were investigated among the high-risk group and low-risk group divided by the NRLSig. Conclusion: The proposed NRLSig may provide promising therapeutic targets or prognostic predictors for LUAD patients.

Project description:Previous literatures have suggested the importance of inflammatory response during lung adenocarcinoma (LUAD) development. This study aimed at exploring the inflammation-related genes and developing a prognostic signature for predicting the prognosis of LUAD. Survival‑associated inflammation-related genes were identified by univariate Cox regression analysis in the dataset of The Cancer Genome Atlas (TCGA). The least absolute shrinkage and selection operator (LASSO) penalized Cox regression model was used to derive a risk signature which is significantly negatively correlated with OS and divide samples into high-, medium- and low-risk group. Univariate and multivariate Cox analyses suggested that the level of risk group was an independent prognostic factor of the overall survival (OS). Time-dependent receiver operating characteristic (ROC) curve indicated the AUC of 1-, 3- and 5-years of the risk signature was 0.715, 0.719, 0.699 respectively. A prognostic nomogram was constructed by integrating risk group and clinical features. The independent dataset GSE30219 of Gene Expression Omnibus (GEO) was used for verification. We further explored the differences among risk groups in Gene set enrichment analysis (GSEA), tumor mutation and tumor microenvironment. Furthermore, Single Sample Gene Set Enrichment Analysis (ssGSEA) and the results of Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) suggested the status of immune cell infiltration was highly associated with risk groups. We demonstrated the prediction effect of CTLA-4 and PD-1/PD-L1 inhibitors in the low-risk group was better than that in the high-risk group using two methods of immune score include immunophenoscore from The Cancer Immunome Atlas (TCIA) and TIDE score from Tumor Immune Dysfunction and Exclusion (TIDE). In addition, partial targeted drugs and chemotherapy drugs for lung cancer had higher drug sensitivity in the high-risk group. Our findings provide a foundation for future research targeting inflammation-related genes to predictive prognosis and some reference significance for the selection of immunotherapy and drug regimen for lung adenocarcinoma.

Project description:BackgroundCuproptosis is a novel form of copper-induced cell death that targets lipoylated tricarboxylic acid (TCA) cycle proteins. However, its prognostic role in lung adenocarcinoma (LUAD) remains unclear. This study aimed to establish a cuproptosis-related prognostic signature for patients with LUAD.MethodsTranscriptome data of LUAD samples were extracted from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The prognostic value of cuproptosis-related genes (CRGs) was investigated using Cox regression analysis to develop a cuproptosis-related prognostic model. Kyoto Encyclopedia of Genes and Genomes (KEGG), gene ontology (GO) and gene set variation analysis (GSVA) were conducted to characterize different biological activities or pathways between high- or low-CRG groups. The expression pattern and prognostic values of CRGs were validated in 37 paired tumor-normal samples using quantitative PCR. Furthermore, in vitro experiments were performed to investigate the relationship between cuproptosis and CRG expression and to explore the function of target genes in cuproptosis.ResultsAmong the 36 CRGs, 17 genes were upregulated, and 3 genes were downregulated in LUAD. A total of 385 CRGs were identified using Pearson correlation analysis. A cuproptosis-related signature was constructed using least absolute shrinkage and selection operator (LASSO) analysis. The prognostic value of the cuproptosis-related signature was validated in six external validation cohorts and in LUAD specimens from our facility. Patients in the high-risk group based on the CRG signature score had shorter overall survival than those in the low-risk group in both the datasets and clinical specimens. In vitro experiments revealed that the expression of BARX1, GFRA3, and KHDRBS2 was upregulated after cuproptosis was induced by elesclomol-CuCL2, whereas the upregulation was suppressed on pretreatment with tetrathiomolybdate (TTM), a chelator of copper. Further, the cell proliferation assay revealed that the BARX1 and GFRA3 deficiency facilities the cuproptosis induced by elesclomol-CuCL2.ConclusionThis study established a new CRG signature that can be used to predict the OS of LUAD patients. Moreover, the knockdown of BARX1 and GFRA3 could increase the sensitivity of LUAD cells to the cuproptosis.

Project description:BackgroundCuproptosis, a newly identified form of programmed cell death, is thought to play a role in tumorigenesis. Long non-coding RNAs (lncRNAs) are reported to be associated with tumor progression and prognosis in colon adenocarcinoma (COAD). However, the role and prognostic value of cuproptosis-related lncRNAs in COAD remains unknown. This study is devoted to constructing and validating a cuproptosis-related lncRNA signature that can predict COAD patient outcomes using bioinformatics methods.MethodsThe COAD mRNA and lncRNA expression profiles and corresponding clinical data were downloaded from The Cancer Genome Atlas (TCGA) database and 2,567 cuproptosis-related lncRNAs were obtained. A 10 cuproptosis-related-lncRNA prognostic signature was then constructed using the least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression model and patients were divided into high- and low-risk groups. Kaplan-Meier analysis, receiver operating characteristic (ROC) curve, and a nomogram were employed to evaluate the predictive power of the signature. The immune characteristics and drug sensitivity were also investigated based on the signature. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to verify the risk model. In vitro experiments were conducted to validate the expression of the ten lncRNAs during cuproptosis.ResultsThe high-risk group was associated with shorter overall survival (OS) time in COAD patients (p<0.001). Multivariate Cox regression indicated that a high-risk score was an independent risk factor for poor prognosis (p<0.001). ROC curve analysis was performed to confirm the validity of the signature (area under the curve (AUC) at 3 years: 0.879). Gene Ontology (GO) enrichment analysis revealed that the signature was highly correlated with the immune response in biological processes. The immune function, the score of the immune cells, and the expression of immune checkpoints were significantly different between the two risk groups. Three drugs, LAQ824, FH535, YM155, were found to be more sensitive in the high-risk group. Finally, the expression levels of the ten lncRNAs comprising the signature were tested by qRT-PCR.ConclusionA ten-cuproptosis-related lncRNA signature was constructed that provided promising insights into personalized prognosis and drug selection among COAD patients.

Dataset Information

Construction and validation of a novel prognostic signature of microRNAs in lung adenocarcinoma.

Publications

Construction and validation of a novel prognostic signature of microRNAs in lung adenocarcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets