Dataset Information

Overexpression of Paxillin Correlates with Tumor Progression and Predicts Poor Survival in Glioblastoma.

ABSTRACT: AIMS:To explore the prognostic and clinicopathological features of glioma with Paxillin (PXN) expression based on a large number of samples. METHODS:RNA sequencing data of 325 glioma samples from Chinese Glioma Genome Atlas (CGGA) database were obtained as discovery set. Three additional datasets were further obtained as validation sets. The protein expression pattern of PXN in glioma was measured by IHC. Kaplan-Meier survival and multivariate Cox analysis were used to estimate the survival distributions. Moreover, the functional annotation of PXN was also analyzed. RESULTS:In the discovery set, PXN overexpression was significantly associated with high-grade glioma as well as the higher mortality in survival analysis (log-rank test, P < 0.01). The results of the other validation datasets showed similar findings. PXN also served as an independent prognostic biomarker in glioblastoma patients. Functional assays showed that PXN contributed to glioma cell proliferation and invasion. CONCLUSION:PXN plays as an oncogene in glioma progression and suggests a new potential biotarget for therapy.

SUBMITTER: Sun LH

PROVIDER: S-EPMC6492676 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Overexpression of Paxillin Correlates with Tumor Progression and Predicts Poor Survival in Glioblastoma.

Sun Li-Hua LH Yang Fu-Qiang FQ Zhang Chuan-Bao CB Wu Yi-Ping YP Liang Jing-Shan JS Jin Shuai S Wang Zheng Z Wang Hong-Jun HJ Bao Zhao-Shi ZS Yang Zheng-Xiang ZX Jiang Tao T

CNS neuroscience & therapeutics 20160917 1

<h4>Aims</h4>To explore the prognostic and clinicopathological features of glioma with Paxillin (PXN) expression based on a large number of samples.<h4>Methods</h4>RNA sequencing data of 325 glioma samples from Chinese Glioma Genome Atlas (CGGA) database were obtained as discovery set. Three additional datasets were further obtained as validation sets. The protein expression pattern of PXN in glioma was measured by IHC. Kaplan-Meier survival and multivariate Cox analysis were used to estimate th ...[more]

PMID: 27637748

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Project description:Background: Semaphorin 6b (SEMA6B) is a member of the semaphorin axon-guidance family and has been demonstrated to both induce and inhibit tumor progression. However, the role of SEMA6B in colorectal cancer (CRC) has remained unclear. This study sought to explore the promising prognostic biomarker for CRC and to understand the expression pattern, clinical significance, immune effects, and biological functions of SEMA6B. Methods: SEMA6B expression in CRC was evaluated via multiple gene and protein expression databases and we identified its prognostic value through The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Correlations between SEMA6B expression and components of the tumor immune microenvironment were analyzed by packages implemented in R, Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), and Tumor-Immune System Interactions database (TISIDB). RNA interference was performed to silence the expression of SEMA6B to explore its biological roles in the colon cancer cell lines HCT116 and LoVo. Results: The messenger RNA (mRNA) level of SEMA6B and the protein expression were higher in CRC tissues than adjacent normal tissues from multiple CRC datasets. High SEMA6B expression was significantly associated with dismal survival. Multivariate Cox regression analysis demonstrated that SEMA6B was an independent prognostic factor for progression-free survival (PFS). The nomogram showed a favorable predictive ability in PFS. Functional enrichment analysis and the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm revealed that the gene cluster associated with the high SEMA6B group were prominently involved in immune responses and inflammatory activities. Notably, SEMA6B expression was positively correlated with infiltrating levels of CD4+ T cells, macrophages, myeloid-derived suppressor cells (MDSCs), regulatory T cells (Tregs), neutrophils, and dendritic cells. Moreover, SEMA6B expression displayed strong correlations with diverse marker sets of immunosuppressive cells in CRC. Integrative analysis revealed that immunosuppressive molecules and immune checkpoints were markedly upregulated in CRC samples with high SEMA6B expression. Furthermore, knockdown of SMEA6B in colon cancer cells significantly inhibited cell proliferation, migration, invasion and reduced the mRNA levels of immunosuppressive molecules. Conclusion: Our findings provide evidence that high SEMA6B expression correlated with adverse prognosis and the tumor immunosuppressive microenvironment in CRC patients. Therefore, SEMA6B may serve as a novel prognostic biomarker for CRC, which offers further insights into developing CRC-targeted immunotherapies.

Project description:PurposeOur research was aimed to identify the expression, clinical value and biological significance of GINS complex subunit 4 (GINS4) in hepatocellular carcinoma (HCC).Materials and methodsGINS4 was initially screened through weighted gene co-expression network analysis (WGCNA). The TCGA, GEO, and TIMER databases were applied for analyzing the GINS4 mRNA expression in HCC. GINS4 protein levels were detected via immunohistochemistry (IHC). Receiver operating characteristic (ROC) curve was applied for estimating the diagnostic significance of GINS4 in HCC. Kaplan-Meier plots, Cox model, and nomogram were used to assess the prognostic performance of GINS4 in HCC. Nomogram validation was conducted through time-dependent ROC and decision curve analysis (DCA). The Wanderer, UALCAN, and DiseaseMeth databases were utilized to identify GINS4 methylation levels in HCC. Genes co-expressed with GINS4 in HCC were estimated through the TCGA, cBioPortal, and GEPIA. GO, KEGG, and GSEA unraveled the possible biological mechanisms of GINS4 in HCC.ResultsWGCNA confirmed that GINS4 was one of hub genes significantly associated with histological grade of HCC. Multiple databases confirmed the significant upregulation of GINS4 in HCC tissues compared with non-tumor controls. IHC analysis of 35 HCC patients demonstrated that overexpressed GINS4 positively correlated with advanced TNM stage and poor pathological differentiation. GINS4 could effectively differentiate HCC cases from healthy individuals, with an AUC of 0.865. Increased GINS4 expression predicted unsatisfactory prognosis in HCC patients, especially in age >60 years, histological grade 1, HBV infection-negative, and occurring relapse subgroup. Nomogram incorporating GINS4 level and TNM stage displayed satisfactory predictive accuracy and clinical utility in predicting HCC prognosis. Upregulated GINS4 exhibited hypomethylated levels in HCC. Functional analysis indicated that GINS4 potentially positively modulated cell cycle and PI3K/AKT/mTOR pathway.ConclusionGINS4 is overexpressed in HCC and is correlated with undesirable survival of HCC patients.

Dataset Information

Overexpression of Paxillin Correlates with Tumor Progression and Predicts Poor Survival in Glioblastoma.

Publications

Overexpression of Paxillin Correlates with Tumor Progression and Predicts Poor Survival in Glioblastoma.

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