Abstract PO-021: Targeting the mitochondrial pyruvate complex to alter metabolic programming in pancreatic cancer
Bibliographic record
Abstract
Abstract Pancreatic ductal adenocarcinoma (PDAC) can be stratified into distinct transcriptome subtypes, with the ‘basal-like’ or ‘squamous’ subtype being associated with worse prognosis, compared to the ‘classical’ subtype. Our group recently demonstrated that PDAC tumors have unique metabolic transcriptome profiles, and that genes involved in glycolysis and cholesterol synthesis pathways are positively correlated with basal-like and classical gene expression patterns, respectively. The mitochondrial pyruvate complex (MPC) mediates the transport of pyruvate into the mitochondria which attenuates the effect of glycolysis on tumor progression. The mitochondrial pyruvate carrier 1 (MPC1) gene, which encodes one of two subunits of MPC, is deleted in over 60% of metastatic PDAC and PDAC glycolytic tumors have lowest levels of MPC1 expression. Using PDAC tissue microarrays, we also found that reduced MPC1 protein expression correlates with reduced survival in patients. We hypothesized that targeting MPC1 will alter metabolic reprogramming and may modulate tumor aggressiveness and therapeutic vulnerability in PDAC tumor cells. Genomically and clinically annotated patient-derived tumor organoids (PDOs) were generated from metastatic biopsies from patients enrolled in the PanGen study (NCT02869802). PDOs from both basal and classical tumors were used in the study. In order to investigate glycolysis in PDOs, we adapted the Seahorse Glycolytic Stress Test. Glycolysis, glycolytic capacity and reserve were analyzed in PDOs under basal and treated conditions. To alter MPC1 activity, PDOs were treated for 48 hours with 5uM of UK-5099, an MPC1 inhibitor, or 2.5-5uM SRT1720. SRT1720 is an activator of sirtuin 1 (SIRT1) and the transcriptional coactivator peroxisome proliferator-activated receptor γ coactivator-1α (PGC1-α), which regulates the expression of MPC1. An unpaired t-test with an alpha of 0.05 was used for all statistical analysis. Glycolysis analysis revealed distinct glycolytic profiles in PDOs with differences in glycolytic capacity and reserves trending with different tumor subtypes. Treatment with UK-5099 resulted in an increase in both glycolytic rate and reserve in PDOs from basal and classical tumors. Treatment with SRT1720 resulted in significantly reduced glycolytic rate and capacity. These data suggest that PDAC PDOs exhibit distinct metabolic profiles and that targeting MPC1 can modulate glycolysis in PDOs. Our ongoing efforts aim to further characterize the subtype-specific effect of MPC1 modulators on glycolysis and chemotherapy response in PDAC PDOs. Citation Format: Hassan A. Ali, Andrew Metcalfe, James T. Topham, Cassia S. Warren, Joanna M. Karasinska, David F. Schaeffer, Daniel J. Renouf. Targeting the mitochondrial pyruvate complex to alter metabolic programming in pancreatic cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PO-021.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".