Faculty Collaboration Database

Transcriptomic-Based Microenvironment Classification Reveals Precision Medicine Strategies for Pancreatic Ductal Adenocarcinoma. Gastroenterology 2024 May;166(5):859-871.e3

Date

01/28/2024

Pubmed ID

38280684

DOI

10.1053/j.gastro.2024.01.028

Scopus ID

2-s2.0-85188891214 (requires institutional sign-in at Scopus site)

Abstract

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.

Author List

George B, Kudryashova O, Kravets A, Thalji S, Malarkannan S, Kurzrock R, Chernyavskaya E, Gusakova M, Kravchenko D, Tychinin D, Savin E, Alekseeva L, Butusova A, Bagaev A, Shin N, Brown JH, Sethi I, Wang D, Taylor B, McFall T, Kamgar M, Hall WA, Erickson B, Christians KK, Evans DB, Tsai S

Authors

Beth A. Erickson MD Professor in the Radiation Oncology department at Medical College of Wisconsin
Douglas B. Evans MD Chair, Professor in the Surgery department at Medical College of Wisconsin
Ben George MD Professor in the Medicine department at Medical College of Wisconsin
William Adrian Hall MD Professor in the Radiation Oncology department at Medical College of Wisconsin
Mandana Kamgar MD Assistant Professor in the Medicine department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Aged
Biomarkers, Tumor
Carcinoma, Pancreatic Ductal
Databases, Genetic
Female
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Humans
Immunotherapy
Liver Neoplasms
Lung Neoplasms
Male
Middle Aged
Neoadjuvant Therapy
Pancreatic Neoplasms
Precision Medicine
Predictive Value of Tests
Prognosis
Transcriptome
Tumor Microenvironment