Metabolic Characteristics of Pancreatic Ductal Adenocarcinoma (PDAC) Subtypes

Background

Pancreatic Ductal Adenocarcinoma (PDAC) is a highly aggressive cancer with a five-year survival rate of only 13%, making it the third leading cause of cancer-related deaths. The aggressiveness and chemoresistance of PDAC are closely linked to its complex metabolic reprogramming, particularly in the tumor microenvironment, where cancer cells adapt to changes in nutrient and oxygen availability. In recent years, transcriptome-based classification of PDAC subtypes (e.g., “basal-like” and “classical” subtypes) has been shown to correlate with prognosis, with the basal-like subtype associated with poorer outcomes. However, the metabolic differences between these subtypes and their functional relevance remain incompletely understood. Therefore, this study aimed to investigate the metabolic characteristics of basal-like and classical PDAC subtypes using patient-derived organoid (PDO) models and explore potential metabolic targets.

Source of the Paper

This paper was co-authored by Hassan A. Ali, Joanna M. Karasinska, and others, with the research team affiliated with the Pancreas Centre BC at the University of British Columbia and other institutions. The study was published in 2024 in the journal Cancer & Metabolism, titled “Pancreatic cancer tumor organoids exhibit subtype-specific differences in metabolic profiles.”

Research Process and Results

1. Establishment and Culture of Patient-Derived Organoids (PDOs)

The research team established PDO models from tumor biopsy samples of metastatic PDAC patients, including three basal-like and five classical tumor-derived PDOs. The PDOs were cultured using a protocol previously described by the Tuveson lab. The specific steps included: - Sample Processing: Tumor tissues from liver metastases were obtained, necrotic regions and blood vessels were excised, and the tissues were minced and incubated in digestion medium for 12–16 hours. - Cell Seeding: Dissociated cells were seeded into Matrigel and cultured in Complete Growth Medium (CGM). - Passaging: Organoids were passaged when they reached 80% Matrigel confluence.

2. Metabolic Analysis

To explore the metabolic characteristics of PDOs, the research team conducted several metabolic assays: - Glycolysis and Mitochondrial Stress Tests: The Seahorse XFe96 Analyzer was used to measure the Extracellular Acidification Rate (ECAR) and Oxygen Consumption Rate (OCR), assessing glycolysis and oxidative phosphorylation (OXPHOS) activity, respectively. - 13C-Glucose Metabolite Tracing: Stable isotope-labeled 13C-glucose was used to trace metabolite generation, analyzing changes in glycolysis and the tricarboxylic acid (TCA) cycle. - MPC1 Inhibitor Treatment: PDOs were treated with the MPC1 inhibitor UK-5099 to investigate the impact of mitochondrial pyruvate transport on metabolic differences.

3. Whole Genome and Transcriptome Sequencing

The research team performed whole genome and transcriptome sequencing on PDOs to analyze gene expression differences. Sequencing data were aligned using tools such as BWA-MEM and STAR, and differential expression analysis was conducted using DESeq2. Additionally, Gene Set Enrichment Analysis (GSEA) was performed to identify metabolic pathways associated with basal-like and classical subtypes.

4. Tissue Microarray (TMA) and Proteomics Analysis

To validate the prognostic value of MPC1, the research team conducted immunohistochemical analysis on a tissue microarray (TMA) of 252 resectable PDAC cases and performed mass spectrometry-based proteomics to analyze MPC1 and MPC2 protein levels in 45 metastatic PDAC cases.

Key Findings

1. Metabolic Differences Between Basal-like and Classical PDOs

The study found that basal-like PDOs exhibited lower baseline glycolysis activity but higher glycolytic reserves and oxygen consumption rates (OCR), indicating that basal-like tumor cells can more flexibly regulate glycolysis and oxidative phosphorylation under metabolic stress. Additionally, basal-like PDOs were more sensitive to the MPC1 inhibitor UK-5099, suggesting their reliance on glycolysis-derived pyruvate to sustain mitochondrial respiration.

2. Prognostic Value of MPC1

Through TMA and proteomics analysis, the research team found that low MPC1 expression was associated with aggressive clinicopathological features of PDAC, such as high tumor grade, lymphovascular invasion, and perineural invasion. Basal-like tumors had significantly lower MPC1 protein levels than classical tumors, further supporting the prognostic importance of MPC1 in PDAC.

3. 13C-Glucose Metabolite Tracing

In the 13C-glucose metabolite tracing experiment, basal-like PDOs showed lower fractions of M+2 metabolites (e.g., citrate and malate) but were more sensitive to UK-5099-mediated reduction in M+2 metabolites. This suggests that basal-like tumor cells rely more on glycolysis-derived pyruvate to sustain the TCA cycle.

4. Differential Gene Expression Analysis

Through differential gene expression analysis, the research team identified upregulated genes in basal-like PDOs associated with RNA translation, epithelial-mesenchymal transition (EMT), and KRAS signaling pathways, while downregulated genes were linked to monocarboxylate transport and bile acid metabolism. High expression of genes such as BAG3, DUSP14, and LYPD3 was associated with poorer prognosis.

Conclusions and Significance

This study, using PDO models, revealed significant metabolic differences between basal-like and classical PDAC subtypes, particularly the reliance of basal-like tumor cells on mitochondrial pyruvate transport. These findings provide new insights into subtype-specific metabolic targeting for PDAC treatment. Additionally, low MPC1 expression was associated with aggressive features of PDAC, further supporting its potential as a prognostic marker.

Research Highlights

1. Subtype-Specific Metabolic Characteristics: For the first time, the study systematically revealed differences in glycolysis and oxidative phosphorylation between basal-like and classical PDAC tumors using PDO models.
2. Prognostic Value of MPC1: The prognostic importance of MPC1 in PDAC was validated through large-scale clinical samples, providing a basis for future targeted therapies.
3. 13C-Glucose Metabolite Tracing: Stable isotope labeling technology was used to deeply analyze the metabolic reprogramming mechanisms of PDAC tumor cells.

Additional Valuable Information

The study’s limitations include a small sample size, and future validation through larger multicenter studies is needed. Additionally, the research team suggests that future studies should explore the roles of other metabolic pathways (e.g., lipid and amino acid metabolism) in PDAC subtypes.

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Through this research, we have deepened our understanding of the metabolic heterogeneity of PDAC and provided important scientific evidence for developing personalized treatment strategies tailored to different subtypes.