AI Article Synopsis

  • * The study used data from The Cancer Genome Atlas and the International Cancer Genome Consortium, resulting in a model containing 6 key genes that effectively predicts overall survival and serves as an independent prognostic factor.
  • * Analysis showed that patients in the low-risk group benefitted from greater immune-related activity, and the gene LY6D emerged as a promising predictor for PAC outcomes, assisting in evaluating responses to therapies like immunotherapy and chemoradiotherapy.

Article Abstract

Pancreatic cancer (PAC) is a highly fatal and aggressive type of cancer. Hypoxia is a common feature of PAC. The aim of this study was to develop a hypoxia status-related prognostic model for predicting the survival outcomes in PAC. The data sets of PAC from The Cancer Genome Atlas and the International Cancer Genome Consortium were used to construct and validate the signature. A 6 hypoxia status-related differential expression genes prognostic model for predicting the survival outcomes was established. The Kaplan-Meier analysis and Received operating characteristic curve indicated the good performance of the signature at predicting overall survival. Univariate and Multivariate Cox regression revealed that the signature was an independent prognostic factor in PAC. Weighted Gene Co-expression Network Analysis and immune infiltration analysis indicated that Immune-related pathways and immune cell infiltration was mostly enriched in the low-risk group, which presented a better prognosis. We also evaluated the predictive of the signature for immunotherapy and chemoradiotherapy. Risk gene LY6D may be a potential prognostic predictor of PAC. This model can be used as an independent prognostic factor for predicting clinical outcomes and a possible classifier for response to chemotherapy.

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Source
http://dx.doi.org/10.1007/s12033-023-00807-xDOI Listing

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