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ITGAV overexpression predicts poor prognosis in gastric cancer
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Abstract
To explore Integrin alpha V (ITGAV) expression and its potential impact on gastric cancer (GC). The TCGA database was used to acquire the clinical information of GC patients. GEPIA and Ualcan were employed to investigate the ITGAV expression in GC. Immunohistochemistry (IHC) and Quantitative real-time PCR(qRT-PCR)validated the expression level of ITGAV. A nomogram was established to evaluate the predictive function of ITGAV in GC. The concordance index (C-index) together with calibration plot assisted in assessing the model predictive performance. The decision curve analysis (DCA) served for the clinical value evaluation. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to investigate the biological functions and signaling pathways. Bioinformatic data indicated ITGAV was significantly upregulated in GC (P < 0.05). IHC and qRT-PCR validated the result. ITGAV upregulation is closely associated with poor survival in GC (P < 0.05). Univariate and multivariate analysis revealed ITGAV was a risk factor for GC. Nomogram was developed and validated for GC patients, which revealed a good application prospect. ITGAV might serve as a predictive biomarker for GC and assist clinicians in decision-making.
Title: ITGAV overexpression predicts poor prognosis in gastric cancer
Description:
Abstract
To explore Integrin alpha V (ITGAV) expression and its potential impact on gastric cancer (GC).
The TCGA database was used to acquire the clinical information of GC patients.
GEPIA and Ualcan were employed to investigate the ITGAV expression in GC.
Immunohistochemistry (IHC) and Quantitative real-time PCR(qRT-PCR)validated the expression level of ITGAV.
A nomogram was established to evaluate the predictive function of ITGAV in GC.
The concordance index (C-index) together with calibration plot assisted in assessing the model predictive performance.
The decision curve analysis (DCA) served for the clinical value evaluation.
Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to investigate the biological functions and signaling pathways.
Bioinformatic data indicated ITGAV was significantly upregulated in GC (P < 0.
05).
IHC and qRT-PCR validated the result.
ITGAV upregulation is closely associated with poor survival in GC (P < 0.
05).
Univariate and multivariate analysis revealed ITGAV was a risk factor for GC.
Nomogram was developed and validated for GC patients, which revealed a good application prospect.
ITGAV might serve as a predictive biomarker for GC and assist clinicians in decision-making.
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