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Evaluation of ITGB1 expression as a predictor of the therapeutic effects of immune checkpoint inhibitors in gastric cancer
BACKGROUND: Gastric cancer (CC) is a disease with high incidence and mortality rate. Immunotherapy is an important method for gastric cancer while lack of effective predictor. Integrins play an important role in the development. We aimed to explore the predictive value of β1 integrin (ITGB1) as a pr...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10478479/ https://www.ncbi.nlm.nih.gov/pubmed/37667169 http://dx.doi.org/10.1186/s12876-023-02930-0 |
Sumario: | BACKGROUND: Gastric cancer (CC) is a disease with high incidence and mortality rate. Immunotherapy is an important method for gastric cancer while lack of effective predictor. Integrins play an important role in the development. We aimed to explore the predictive value of β1 integrin (ITGB1) as a predictor of immunnotherapy in gastric cancer. METHODS: Differential expression analysis was conducted using the Gene Expression Profiling Interactive Analysis (GEPIA) 2.0 and GEO databases. GEPIA data were used to evaluate the prognostic value of ITGB1 in gastric cancer (GC). Transcriptomic and clinical data of GC and normal tissues were downloaded from The Cancer Genome Atlas database, and the TIMER database was used to evaluate the association between ITGB1 and immune infiltration. Time-dependent receiver operating characteristic (ROC) curve analysis was used to determine the prognostic value of ITGB1. To verify ITGB1 expression at the protein level, immunohistochemical staining was conducted. In addition, to analyze the correlation of ITGB1 with PD-1 and PD-L1, we examined levels of PD-1 and PD-L1 by IHC and determined the predictive value of ITGB1 for anti-PD-1 therapy in GC by ROC curve analysis. RESULTS: Compared with normal tissues, analysis of GEPIA and data at protein levels showed significantly higher expression of ITGB1 in GC. In addition, higher expression of ITGB1 was associated with worse pathological G-staging and tumor T-staging, which suggested that ITGB1 is a risk factor for poor prognosis in GC. The level of ITGB1 expression was positively correlated with CD8 + T cells, neutrophils, macrophages, and dendritic cells. ITGB1 expression was also correlated with PD-L1 expression, and this was further verified at the protein level by immunohistochemical analysis. The area under the ROC curve was 0.808. CONCLUSION: ITGB1 may be a promising prognostic biomarker and effective predictor for anti-PD-1 therapy in GC. TRIAL REGISTRATION: Retrospectively registered. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12876-023-02930-0. |
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