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Transcriptomic-Based Microenvironment Classification Reveals Precision Medicine Strategies for Pancreatic Ductal Adenocarcinoma.
George, Ben; Kudryashova, Olga; Kravets, Andrey; Thalji, Samih; Malarkannan, Subramaniam; Kurzrock, Razelle; Chernyavskaya, Ekatherina; Gusakova, Mariia; Kravchenko, Dmitry; Tychinin, Dmitry; Savin, Egor; Alekseeva, Lolita; Butusova, Anna; Bagaev, Aleksander; Shin, Nara; Brown, Jessica H; Sethi, Isha; Wang, Dandan; Taylor, Bradley; McFall, Thomas; Kamgar, Mandana; Hall, William A; Erickson, Beth; Christians, Kathleen K; Evans, Douglas B; Tsai, Susan.
Afiliação
  • George B; LaBahn Pancreatic Cancer Program, Division of Hematology and Oncology, Medical College of Wisconsin (MCW), Milwaukee, Wisconsin. Electronic address: bgeorge@mcw.edu.
  • Kudryashova O; BostonGene Corporation, Waltham, Massachusetts.
  • Kravets A; BostonGene Corporation, Waltham, Massachusetts.
  • Thalji S; LaBahn Pancreatic Cancer Program, Department of Surgery, Medical College of Wisconsin (MCW), Milwaukee, Wisconsin.
  • Malarkannan S; Versiti Blood Research Institute, Department of Medicine, Microbiology & Molecular Genetics, Medical College of Wisconsin (MCW), Milwaukee, Wisconsin.
  • Kurzrock R; Linda T. and John A. Mellowes Center for Genomic Sciences and Precision Medicine, Division of Hematology and Oncology, Medical College of Wisconsin (MCW), Milwaukee, Wisconsin.
  • Chernyavskaya E; BostonGene Corporation, Waltham, Massachusetts.
  • Gusakova M; BostonGene Corporation, Waltham, Massachusetts.
  • Kravchenko D; BostonGene Corporation, Waltham, Massachusetts.
  • Tychinin D; BostonGene Corporation, Waltham, Massachusetts.
  • Savin E; BostonGene Corporation, Waltham, Massachusetts.
  • Alekseeva L; BostonGene Corporation, Waltham, Massachusetts.
  • Butusova A; BostonGene Corporation, Waltham, Massachusetts.
  • Bagaev A; BostonGene Corporation, Waltham, Massachusetts.
  • Shin N; BostonGene Corporation, Waltham, Massachusetts.
  • Brown JH; BostonGene Corporation, Waltham, Massachusetts.
  • Sethi I; BostonGene Corporation, Waltham, Massachusetts.
  • Wang D; Versiti Blood Research Institute, Department of Medicine, Microbiology & Molecular Genetics, Medical College of Wisconsin (MCW), Milwaukee, Wisconsin.
  • Taylor B; Clinical and Translational Science Institute, Medical College of Wisconsin (MCW), Milwaukee, Wisconsin.
  • McFall T; LaBahn Pancreatic Cancer Program, Department of Biochemistry, Medical College of Wisconsin (MCW), Milwaukee, Wisconsin.
  • Kamgar M; LaBahn Pancreatic Cancer Program, Division of Hematology and Oncology, Medical College of Wisconsin (MCW), Milwaukee, Wisconsin.
  • Hall WA; LaBahn Pancreatic Cancer Program, Department of Radiation Oncology, Medical College of Wisconsin (MCW), Milwaukee, Wisconsin.
  • Erickson B; LaBahn Pancreatic Cancer Program, Department of Radiation Oncology, Medical College of Wisconsin (MCW), Milwaukee, Wisconsin.
  • Christians KK; LaBahn Pancreatic Cancer Program, Department of Surgery, Medical College of Wisconsin (MCW), Milwaukee, Wisconsin.
  • Evans DB; LaBahn Pancreatic Cancer Program, Department of Surgery, Medical College of Wisconsin (MCW), Milwaukee, Wisconsin.
  • Tsai S; LaBahn Pancreatic Cancer Program, Department of Surgery, Medical College of Wisconsin (MCW), Milwaukee, Wisconsin.
Gastroenterology ; 166(5): 859-871.e3, 2024 05.
Article em En | MEDLINE | ID: mdl-38280684
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Pancreáticas / Biomarcadores Tumorais / Perfilação da Expressão Gênica / Carcinoma Ductal Pancreático / Medicina de Precisão / Microambiente Tumoral / Transcriptoma Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Pancreáticas / Biomarcadores Tumorais / Perfilação da Expressão Gênica / Carcinoma Ductal Pancreático / Medicina de Precisão / Microambiente Tumoral / Transcriptoma Idioma: En Ano de publicação: 2024 Tipo de documento: Article