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Integrating Metabolic Profiling Of Pancreatic Juice With Transcriptomic Analysis Of Pancreatic Cancer Tissue Identifies Distinct Clinical Subgroups.

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Integrating Metabolic Profiling Of Pancreatic Juice With Transcriptomic Analysis Of Pancreatic Cancer Tissue Identifies Distinct Clinical Subgroups.

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Integrating metabolic profiling of pancreatic juice with transcriptomic analysis of pancreatic cancer tissue

Alessandra Pulvirenti^1,2, Marialuisa Barbagallo³, Anna Rita Putignano³

¹Section of Pancreatic Surgery, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Humanitas Research Hospital, Rozzano, Italy.

Frontiers in Oncology

|July 11, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

Pancreatic juice (PJ) metabolic profiles reveal distinct pancreatic ductal adenocarcinoma (PDAC) subtypes and immune microenvironments. This finding highlights PJ as a potential biomarker for personalized PDAC therapy.

Keywords:

metabolism pancreatic cancer profiling transcriptomics tumor infiltrating lymphocytes

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Area of Science:

Oncology
Metabolomics
Immunology

Background:

Metabolic reprogramming is a key characteristic of pancreatic ductal adenocarcinoma (PDAC).
Pancreatic juice (PJ) metabolic signatures show prognostic value for PDAC outcomes.
Integrating PJ profiling with tumor microenvironment analysis can identify PDAC vulnerabilities.

Purpose of the Study:

To investigate the association between PJ metabolic profiles and PDAC molecular subtypes.
To characterize the tumor immune microenvironment in relation to metabolic clusters.
To explore the potential of PJ as a source for PDAC biomarkers.

Main Methods:

Transcriptomic analysis of 26 PDAC samples categorized into 3 metabolic clusters (M_CL) based on PJ profiles.
Analysis of molecular subtypes and transcriptional differences.

Validation using multidimensional imaging and immunofluorescence on tumor slides.

Main Results:

PJ metabolic profiling correlated significantly with PDAC molecular subtypes (p=0.004).
M_CL1 tumors, associated with longer survival, displayed a non-squamous phenotype and enriched immune genes/pathways compared to M_CL2.
Immune signature analysis confirmed decreased immunity in M_CL2, enabling patient stratification by survival.

Conclusions:

PJ metabolic fingerprints accurately reflect PDAC molecular subtypes and the tumor immune microenvironment.
PJ serves as a promising source for developing biomarkers for personalized PDAC therapy.