Dataset Information

Prognostic Profiling of the EMT-Associated and Immunity-Related LncRNAs in Lung Squamous Cell Carcinomas.

ABSTRACT: Lung squamous cell carcinoma (Lung SCC) is associated with metastatic disease, resulting in poor clinical prognosis and a low survival rate. The aberrant epithelial-mesenchymal transition (EMT) and long non-coding RNA (LncRNA) are critical attributors to tumor metastasis and invasiveness in Lung SCC. The present study divided lncRNAs into two subtypes, C1 and C2 (Cluster 1 and Cluster 2), according to the correlation of EMT activity within the public TCGA and GEO databases. Subsequently, the differential clinical characteristics, mutations, molecular pathways and immune cell deconvolution between C1 and C2 were evaluated. Lastly, we further identified three key lncRNAs (DNM3OS, MAGI2-AS3 and LINC01094) that were associated with EMT and, at the same time, prognostic for the clinical outcomes of Lung SCC patients. Our study may provide a new paradigm of metastasis-associated biomarkers for predicting the prognosis of Lung SCC.

SUBMITTER: Sun Q

PROVIDER: S-EPMC9497331 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Prognostic Profiling of the EMT-Associated and Immunity-Related LncRNAs in Lung Squamous Cell Carcinomas.

Sun Qifeng Q Gao Yan Y Zhang Yehui Y Cao Hongmei H Liu Jiajia J Neo Shi-Yong SY Chen Keguang K Bi Yanping Y Wu Jing J

Cells 20220915 18

Lung squamous cell carcinoma (Lung SCC) is associated with metastatic disease, resulting in poor clinical prognosis and a low survival rate. The aberrant epithelial-mesenchymal transition (EMT) and long non-coding RNA (LncRNA) are critical attributors to tumor metastasis and invasiveness in Lung SCC. The present study divided lncRNAs into two subtypes, C1 and C2 (Cluster 1 and Cluster 2), according to the correlation of EMT activity within the public TCGA and GEO databases. Subsequently, the dif ...[more]

PMID: 36139456

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Project description:Purpose: This study aimed to develop a prognostic indicator based on epithelial-mesenchymal transition (EMT)-related long noncoding RNAs (lncRNAs) and explore the function of EMT-related lncRNAs in malignant progression in lung adenocarcinoma (LUAD). Materials and methods: A LUAD dataset was acquired from The Cancer Genome Atlas (TCGA) to identify prognostic EMT-related lncRNAs via differential expression analysis and univariate Cox regression analysis. Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis was utilized for variable selection and model construction. The EMT-related prognostic index (ERPI) was calculated according to the model and served as a classifier to divide LUAD individuals into high-ERPI and low-ERPI groups. A nomogram incorporating ERPI and clinicopathological variables was constructed. TCGA-LUAD, GSE50081, and GSE31210 were used to test the predictive capacity of the ERPI and nomogram. The characteristics of the tumor microenvironment (TME) were evaluated via the ESTIMATE, TIMER, and ssGSEA algorithms. Gene set variation analysis (GSVA) and ssGSEA were used to annotate the functions of the high-ERPI and low-ERPI groups. CCK8, transwell assay, wound-healing assay, and clone formation assay were conducted to clarify the biological functions of prognostic EMT-related lncRNAs. Results: Ninety-seven differentially expressed EMT-related lncRNAs were identified, 15 of which were related to overall survival (OS). A prognostic signature was constructed based on 14 prognostic EMT-related lncRNAs to calculate the ERPI of each patient, and the predictive ability of ERPI was verified in TCGA, GSE50081, and GSE31210. The low-ERPI group survived longer and had a lower percentage of patients in advanced stage than the high-ERPI group. The nomogram had the highest predictive accuracy, followed by ERPI and stage. Patients with low ERPI had higher infiltration degree of immune cells and stronger immune responses than those with high ERPI. A series of in vitro experiments demonstrated that knockdown of LINC01138 dampened variability, proliferation, and motility of A549 and H460 cells. Conclusion: Our study developed a prognostic classifier with robust prognostic performance and clarified the biological functions of LINC01138 in LUAD, aiding in making individual treatments for patients with LUAD and dissecting the mechanism of oncogenesis.

Project description:BackgroundEMT is an important biological process in the mechanism of tumor invasion and metastasis. However, there are still many unknowns about the specific mechanism of EMT in tumor. At present, a comprehensive analysis of EMT-related genes in colorectal cancer (CRC) is still lacking.MethodsAll the data were downloaded from public databases including TCGA database (488 tumor samples and 52 normal samples) as the training set and the GEO database (GSE40967 including 566 tumor samples and 19 normal samples, GSE12945 including 62 tumor samples, GSE17536 including 177 tumor samples, GSE17537 including 55 tumor samples) as the validation sets. One hundred and sixty-six EMT-related genes (EMT-RDGs) were selected from the Molecular Signatures Database. Bioinformatics methods were used to analyze the correlation between EMT-RDGs and CRC prognosis, metastasis, drug efficacy, and immunity.ResultsWe finally obtained nine prognostic-related EMT-RDGs (FGF8, NOG, PHLDB2, SIX2, SNAI1, TBX5, TIAM1, TWIST1, TCF15) through differential expression analysis, Unicox and Lasso regression analysis, and then constructed a risk prognosis model. There were significant differences in clinical characteristics, 22 immune cells, and immune functions between the high-risk and low-risk groups and the different states of the nine prognostic-related EMT-RDGs. The methylation level and mutation status of nine prognostic-related EMT-RDGs all affect their regulation of EMT. The Cox proportional hazards regression model was also constructed by the methylation sites of nine prognostic-related EMT-RDGs. In addition, the expression of FGF8, PHLDB2, SIX2, and SNAIL was higher and the expression level of NOG and TWIST1 was lower in the non-metastasis CRC group. Nine prognostic-related EMT-RDGs also affected the drug treatment response of CRC.ConclusionsTargeting these nine prognostic-related EMT-RDGs can regulate CRC metastasis and immune, which is beneficial for the prognosis of CRC patients, improve drug sensitivity in CRC patients.

Dataset Information

Prognostic Profiling of the EMT-Associated and Immunity-Related LncRNAs in Lung Squamous Cell Carcinomas.

Publications

Prognostic Profiling of the EMT-Associated and Immunity-Related LncRNAs in Lung Squamous Cell Carcinomas.

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