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Transcriptomic-Based Microenvironment Classification Reveals Precision Medicine Strategies for Pancreatic Ductal
Ben George1, Olga Kudryashova2, Andrey Kravets2
1LaBahn Pancreatic Cancer Program, Division of Hematology and Oncology, Medical College of Wisconsin (MCW), Milwaukee, Wisconsin.
Background & Aims:
The complex tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) has hindered the development of reliable predictive biomarkers for targeted therapy and immunomodulatory strategies. A comprehensive characterization of the TME is necessary to advance precision therapeutics in PDAC.
Methods:
A transcriptomic profiling platform for TME classification based on functional gene signatures was applied to 14 publicly available PDAC datasets (n = 1657) and validated in a clinically annotated independent cohort of patients with PDAC (n = 79). Four distinct subtypes were identified using unsupervised clustering and assessed to evaluate predictive and prognostic utility.
Results:
TME classification using transcriptomic profiling identified 4 biologically distinct subtypes based on their TME immune composition: immune enriched (IE); immune enriched, fibrotic (IE/F); fibrotic (F); and immune depleted (D). The IE and IE/F subtypes demonstrated a more favorable prognosis and potential for response to immunotherapy compared with the F and D subtypes. Most lung metastases and liver metastases were subtypes IE and D, respectively, indicating the role of clonal phenotype and immune milieu in developing personalized therapeutic strategies. In addition, distinct TMEs with potential therapeutic implications were identified in treatment-naive primary tumors compared with tumors that underwent neoadjuvant therapy.
Conclusions:
This novel approach defines a distinct subgroup of PADC patients that may benefit from immunotherapeutic strategies based on their TME subtype and provides a framework to select patients for prospective clinical trials investigating precision immunotherapy in PDAC. Further, the predictive utility and real-world clinical applicability espoused by this transcriptomic-based TME classification approach will accelerate the advancement of precision medicine in PDAC.
Insights
Researchers identified four pancreatic ductal adenocarcinoma (PDAC) subtypes based on tumor microenvironment (TME) characteristics. This classification helps predict immunotherapy response and advance precision medicine for PDAC patients.
Area of Science:
- Oncology
- Immunology
- Genomics
Background:
- The tumor microenvironment (TME) in pancreatic ductal adenocarcinoma (PDAC) presents challenges for developing predictive biomarkers for targeted therapies and immunomodulation.
- Comprehensive TME characterization is crucial for advancing precision therapeutics in PDAC.
Purpose of the Study:
- To classify PDAC subtypes based on TME characteristics using transcriptomic profiling.
- To evaluate the predictive and prognostic utility of identified TME subtypes for immunotherapy response.
Main Methods:
- Applied a transcriptomic profiling platform to 14 public PDAC datasets (n=1657) and validated in an independent cohort (n=79).
- Utilized unsupervised clustering to identify distinct TME subtypes based on functional gene signatures.
- Assessed the predictive and prognostic value of TME subtypes.
Main Results:
- Identified four distinct TME subtypes: immune enriched (IE), immune enriched/fibrotic (IE/F), fibrotic (F), and immune depleted (D).
- IE and IE/F subtypes showed a more favorable prognosis and potential for immunotherapy response compared to F and D subtypes.
- Observed distinct TME profiles in treatment-naive versus neoadjuvant-treated tumors, suggesting therapeutic implications.
Conclusions:
- This transcriptomic-based TME classification defines PDAC patient subgroups who may benefit from immunotherapy.
- Provides a framework for selecting patients for precision immunotherapy clinical trials in PDAC.
- Accelerates the advancement of precision medicine in PDAC through predictive utility and clinical applicability.
