Jul 2026· Visual Information Expert Workshop· 0 citations· 33 references
TL;DR
A novel AIGScore model with significant prognostic utility for PDAC is proposed, which may provide insights into TME characteristics and offer a potential framework for optimizing immunotherapeutic strategies in patients with PDAC.
Abstract
Immunotherapy has emerged as a pivotal approach in cancer treatment, yet its efficacy is influenced by the interactions within the tumor microenvironment (TME). Angiogenesis, the formation of new blood vessels, is a hallmark feature of the TME, particularly in aggressive malignancies such as pancreatic ductal adenocarcinoma (PDAC). This study aims to elucidate angiogenesis patterns in PDAC and investigate their associations with clinical characteristics, TME features, and the response to immunotherapy. By analyzing 40 angiogenesis‐related genes, 28 angiogenesis‐associated immune genes (AIGs) were identified, enabling classification of PDAC patients into two subclusters with distinct clinical and TME profiles. Afterwards, we constructed an AIGScore risk model using least absolute shrinkage and selection operator regression in PDAC, and its reliable predictive ability was confirmed in both training and validation sets. Functional analyses suggested that a high AIGScore may be associated with worse prognosis, reduced tumor immune cycle activity, elevated immune and stromal scores, and diminished response to anti‐PD‐1 immunotherapy. Pan‐cancer analyses further indicated a potential correlation between the seven AIGs and tumor progression, as well as patient outcomes across other malignancies. In summary, this study proposes a novel AIGScore model with significant prognostic utility for PDAC. The findings may provide insights into TME characteristics and offer a potential framework for optimizing immunotherapeutic strategies in patients with PDAC.
BACKGROUND
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