Effect of hypoxic status on survival and therapeutic responses in gastric cancer.

Abstract

e16003 Background: As a significant factor of tumor microenvironment (TME), hypoxia is closely related to cancer metastasis, immune escape and drug resistance. The potential prognosis of hypoxia, as well as its influence on the TME, and therapeutic response have not yet been comprehensively studied in gastric cancer (GC). Here, we developed a prognosis risk assessment model (hypoxia_pred model) based on genes related to hypoxia, and further explored the exact role an impact of hypoxia in GC. Methods: Clinical information and gene expression profile were obtained from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). 375 patients from TCGA-STAD cohort were used as training set. A 21-hypoxic genes expression dataset from TCGA-STAD was performed an unsupervised clustering analysis for different molecular subtypes of GC. Genes associated prognosis were screened by univariate Cox analysis with a cutoff of pvalue＜0.05. The prognostic risk model based on 9-genes transcriptome data of both hypoxia and prognosis related genes was constructed by Least Absolute Shrinkage and Selection Operator regression analysis. Another two gene expression datasets including 409 patients from GEO (GSE62254 and GSE26901) were employed for verifying the forecast performance of this model. In addition, we used ESTATE and single sample Gene Set Enrichment Analysis (ssGSEA) to explore tumor immune infiltration and potential molecular mechanism of hypoxia in GC. We also evaluated the influence of hypoxia on the prognosis, targeted therapy and immunotherapy of GC patients by survival analysis, targeted drug sensitivity analysis and the assessments of the Cancer Immunome Atlas database. Results: We found hypoxia_pred model is a valuable predictor for the survival of GC in validation cohort (AUC > 0.7). AUC for 1- and 3-year overall survival of GC patients in the TCGA cohort were 0.71 and 0.73. In GC, it was supposed that the aggravation of hypoxia was accompanied by the increase of immune rejection phenotype and the infiltration of immunosuppressive cells. In the validation set, patients predicted high risk by the model have worse immunotherapeutic response and prognosis, and may profit from drugs that inhibit cell cycle signaling pathways. In addition, the outcomes by hypoxia_pred for changes in TME, efficacy of immunotherapy and drug sensitivity were quite hypoxia_pred. targeted drug sensitivity, immune microenvironment, biological function, immunotherapeutic response, and immune cell infiltration were found to be significantly different in those molecular subtypes and risk groups. Conclusions: The model based on hypoxic environment provides theoretical foundation for predicting tumor prognosis and clinical treatment, and may improve the prognosis of GC patients by recommending personalized immunotherapy.