Tumor microenvironment phenotyping guides precision therapy in unresectable pancreatic cancer

Abstract

Treatment of locally advanced unresectable pancreatic cancer remains a major clinical challenge due to pronounced heterogeneity and resistance to standard regimens. Increasing evidence highlights the critical role of the tumor microenvironment (TME) in shaping therapeutic response and driving drug resistance. In this minireview, we summarize recent advances in TME phenotyping and its potential to guide precision therapy. A four-dimensional framework integrating stromal, immune, genomic, and metabolic features has been proposed to better characterize TME heterogeneity. Preclinical and clinical studies indicate that strategies targeting the stroma, modulating immunity, or exploiting genomic vulnerabilities such as homologous recombination deficiency may enhance the efficacy of chemotherapy, immunotherapy, and targeted agents. Dynamic biomarkers, including circulating tumor DNA and carbohydrate antigen 19-9, also show promise for real-time therapy adaptation, although their clinical application remains limited. By synthesizing current evidence, we emphasize the importance of individualized treatment strategies that account for TME complexity. While encouraging, the translation of multiomics phenotyping and biomarker monitoring into routine clinical practice requires standardization, prospective validation, and integration of novel technologies. Future research should focus on establishing reproducible TME-guided models to enable dynamic and personalized therapy for patients with unresectable pancreatic cancer.

Keywords: Locally advanced unresectable pancreatic cancer; Gemcitabine; Nano-albumin paclitaxel; Tumor microenvironmental resistance; Combination therapy

Core Tip: This review highlights the importance of tumor microenvironment (TME) heterogeneity in treatment resistance for unresectable locally advanced pancreatic cancer. We propose a novel four-dimensional TME phenotyping framework integrating fibrosis, immunity, genomics, and metabolism to guide precision therapy. This approach enables dynamic, individualized treatment strategies and offers new prospects for improving patient outcomes.