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Interactive Verification Analysis of Multiple Sequencing Data for Identifying Potential Biomarker of Lung Adenocarcinoma.

ABSTRACT: Background:Lung adenocarcinoma (LUAD) comprises around 40% of all lung cancers, and in about 70% of patients, it has spread locally or systemically when first detected leading to a worse prognosis. Methods:We filtered out differentially expressed genes (DEGs) based on the RNA sequencing data in the Gene Expression Omnibus database and verified and deeply analyzed screened DEGs using a combined bioinformatics approach. Results:Expressions of 11,143 genes in 694 nontumor lung tissues and LUAD cases from 8 independent laboratories were analyzed; 188 mRNAs were identified as differentially expressed genes (DEGs). A PPI network constructed with 188 DEGs screened out 8 hub DEGs (CDH5, PECAM1, VWF, CLDN5, COL1A1, MMP9, SPP1, and IL6) which highly interconnected with other nodes. The expression levels of 8 hub genes in LUAD and control were assessed in the Oncomine database, and the results were consistent. The survival curves of 8 hub genes showed that their expressions are significantly related to the prognosis of lung cancer and LUAD patients except for IL6. Since the expression of IL6 is nonspecific and highly sensitive, we choose the other 7 hub genes we had verified to do the next analysis. Mutual exclusivity or cooccurrence analysis of 7 hub genes identified a tendency towards cooccurrence between CDH5, PECAM1, and VWF in LUAD. The coexpression profiles of CDH5 in LUAD were identified, and we found that PECAM1 and VWF coexpressed with CDH5. Immunohistochemistry and RT-PCR analysis showed that higher levels of CDH5, PECAM1, and VWF were expressed in normal lung tissues but a low or undetectable level was found in LUAD tissues. Conclusions:Taken together, we speculate that CDH5, PECAM1, and VWF played an important role in LUAD.

SUBMITTER: Fei H

PROVIDER: S-EPMC7547331 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Interactive Verification Analysis of Multiple Sequencing Data for Identifying Potential Biomarker of Lung Adenocarcinoma.

Fei Hongjun H Chen Songchang S Xu Chenming C

BioMed research international 20201001

<h4>Background</h4>Lung adenocarcinoma (LUAD) comprises around 40% of all lung cancers, and in about 70% of patients, it has spread locally or systemically when first detected leading to a worse prognosis.<h4>Methods</h4>We filtered out differentially expressed genes (DEGs) based on the RNA sequencing data in the Gene Expression Omnibus database and verified and deeply analyzed screened DEGs using a combined bioinformatics approach.<h4>Results</h4>Expressions of 11,143 genes in 694 nontumor lung ...[more]

PMID: 33062704

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Project description:BackgroundAbnormal expression of protein tyrosine kinase 6 (PTK6) has been proven to be involved in the development of gynecological tumors. However, its immune-related carcinogenic mechanism in other tumors remains unclear.ObjectiveThe aim of this study was to identify PTK6 as a novel prognostic biomarker in pan-cancer, especially in lung adenocarcinoma (LUAD), which is correlated with immune infiltration, and to clarify its clinicopathological and prognostic significance.MethodsThe prognostic value and immune relevance of PTK6 were investigated by using bio-informatics in this study. PTK6 expression was validated in vitro experiments (lung cancer cell lines PC9, NCI-H1975, and HCC827; human normal lung epithelial cells BEAS-2B). Western blot (WB) revealed the PTK6 protein expression in lung cancer cell lines. PTK6 expression was inhibited by Tilfrinib. Colony formation and the Cell Counting Kit-8 (CCK-8) assay were used to detect cell proliferation. The wound healing and trans-well were performed to analyze the cell migration capacity. Then flow cytometry was conducted to evaluate the cell apoptosis. Eventually, the relationship between PTK6 and immune checkpoints was examined. WB was used to estimate the PD-L1 expression at different Tilfrinib doses.ResultsPTK6 was an independent predictive factor for LUAD and was substantially expressed in LUAD. Pathological stage was significantly correlated with increased PTK6 expression. In accordance with survival analysis, poor survival rate in LUAD was associated with a high expression level of PTK6. Functional enrichment of the cell cycle and TGF-β signaling pathway was demonstrated by KEGG and GSEA analysis. Moreover, PTK6 expression considerably associated with immune infiltration in LUAD, as determined by immune analysis. Thus, the result of vitro experiments indicated that cell proliferation and migration were inhibited by the elimination of PTK6. Additionally, PTK6 suppression induced cell apoptosis. Obviously, PD-L1 protein expression level up-regulated while PTK6 was suppressed.ConclusionPTK6 has predictive value for LUAD prognosis, and could up regulated PD-L1.

Project description:BackgroundLung adenocarcinoma (LUAD) is the leading cause of cancer-related death. This study aimed to develop and validate reliable prognostic biomarkers and signature.MethodsDifferentially expressed genes were identified based on three Gene Expression Omnibus (GEO) datasets. Based on 1052 samples' data from our cohort, GEO and The Cancer Genome Atlas, we explored the relationship of clinicopathological features and NEIL3 expression to determine clinical effect of NEIL3 in LUAD. Western blotting (22 pairs of tumor and normal tissues), Real-time quantitative PCR (19 pairs of tumor and normal tissues), and immunohistochemical analyses (406-tumor tissues subjected to microarray) were conducted. TIMER and ImmuCellAI analyzed relationship between NEIL3 expression and the abundance of tumor-infiltrating immune cells in LUAD. The co-expressed-gene prognostic signature was established based on the Cox regression analysis.ResultsThis study identified 502 common differentially expressed genes and confirmed that NEIL3 was significantly overexpressed in LUAD samples (P < 0.001). Increased NEIL3 expression was related to advanced stage, larger tumor size and poor overall survival (p < 0.001) in three LUAD cohorts. The proportions of natural T regulatory cells and induced T regulatory cells increased in the high NEIL3 group, whereas those of B cells, Th17 cells and dendritic cells decreased. Gene set enrichment analysis indicated that NEIL3 may activate cell cycle progression and P53 signaling pathway, leading to poor outcomes. We identified nine prognosis-associated hub genes among 370 genes co-expressed with NEIL3. A 10-gene prognostic signature including NEIL3 and nine key co-expressed genes was constructed. Higher risk-score was correlated with more advanced stage, larger tumor size and worse outcome (p < 0.05). Finally, the signature was verified in test cohort (GSE50081) with superior diagnostic accuracy.ConclusionsThis study suggested that NEIL3 has the potential to be an immune-related therapeutic target and an independent predictor of LUAD prognosis. We also developed a prognostic signature for LUAD with a precise diagnostic accuracy.

Project description:BACKGROUND: Lung adenocarcinoma is a heterogernous disease that creates challenges for classification and management. The purpose of this study is to identify specific miRNA markers closely associated with the survival of LUAD patients from a large dataset of significantly altered miRNAs, and to assess the prognostic value of this miRNA expression profile for OS in patients with LUAD. METHODS: We obtained miRNA expression profiles and corresponding clinical information for 372 LUAD patients from The Cancer Genome Atlas (TCGA), and identified the most significantly altered miRNAs between tumor and normal samples. Using survival analysis and supervised principal components method, we identified an eight-miRNA signature for the prediction of overall survival (OS) of LUAD patients. The relationship between OS and the identified miRNA signature was self-validated in the TCGA cohort (randomly classified into two subgroups: n?=?186 for the training set and n?=?186 for the testing set). Survival receiver operating characteristic (ROC) analysis was used to assess the performance of survival prediction. The biological relevance of putative miRNA targets was also analyzed using bioinformatics. RESULTS: Sixteen of the 111 most significantly altered miRNAs were associated with OS across different clinical subclasses of the TCGA-derived LUAD cohort. A linear prognostic model of eight miRNAs (miR-31, miR-196b, miR-766, miR-519a-1, miR-375, miR-187, miR-331 and miR-101-1) was constructed and weighted by the importance scores from the supervised principal component method to divide patients into high- and low-risk groups. Patients assigned to the high-risk group exhibited poor OS compared with patients in the low-risk group (hazard ratio [HR]?=?1.99, P <0.001). The eight-miRNA signature is an independent prognostic marker of OS of LUAD patients and demonstrates good performance for predicting 5-year OS (Area Under the respective ROC Curves [AUC]?=?0.626, P?=?0.003), especially for non-smokers (AUC?=?0.686, P?=?0.023). CONCLUSIONS: We identified an eight-miRNA signature that is prognostic of LUAD. The miRNA signature, if validated in other prospective studies, may have important implications in clinical practice, in particular identifying a subgroup of patients with LUAD who are at high risk of mortality.

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Interactive Verification Analysis of Multiple Sequencing Data for Identifying Potential Biomarker of Lung Adenocarcinoma.

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Interactive Verification Analysis of Multiple Sequencing Data for Identifying Potential Biomarker of Lung Adenocarcinoma.

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