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Abstract A021: Nutrient competition in the tumor microenvironment alters NK cell metabolism in Pancreatic Cancer

2023· article· en· W4389244788 on OpenAlexaboutno aff
Kamiya Mehla

Bibliographic record

VenueCancer Immunology Research · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsnot available
Fundersnot available
KeywordsGlycogenTumor microenvironmentPancreatic cancerBiologyCancer researchCytotoxic T cellCell cultureCancer cellOrganoidCell biologyImmune systemEndocrinologyInternal medicineCancerImmunologyBiochemistryIn vitroMedicine

Abstract

fetched live from OpenAlex

Abstract Tumor cells present constant nutritional demand of macronutrients and micronutrients for their rapid growth needs. Often this nutrient limitation hampers the function of anti-tumor immune cells, which need basal energy levels to execute cytotoxic effects against malignant cells. Hence, we investigated nutrient limitation-induced metabolic alterations in NK cells that regulate the anti-tumor activity of NK cells. Using 2D cultures and PDAC organoid models, we demonstrate that pancreatic tumor cells exhaust vitamin B6 (VB6) in the co-culture milieu, causing reduced killing activity of NK cells. Additionally, we demonstrate that PDAC patients have significantly reduced plasma VB6 as compared to the healthy counterparts. This data aligns with the epidemiological studies showing that VB6 intake reduces the risk of pancreatic cancer incidence. Moreover, we noted a significant reduction in circulating VB6 in the pancreatic tumor-bearing mice as compared to healthy counterparts. Utilizing mass spectrometry-based metabolomics we noted that limitation of the VB6 prevents glycogen breakdown in NK cells. This was validated by follow up electron microscopy-based studies that demonstrated glycogen depots in NK cells that were very prominent upon inhibiting glycogenolysis. Metabolic tracing studies demonstrated that NK cells require VB6 for intracellular glycogen breakdown. Correspondingly, knocking down glycogen phosphorylase, a key enzyme involved in glycogen breakdown abrogated anti-tumoral NK cell function. Notably, supplementation of co-cultures in 2D and organoid models and in vivo orthotopic mouse models, with VB6 restored NK cell function against pancreatic tumor cells. In parallel, we observed dependence of tumor cell metabolism on VB6 for sustaining growth. Accordingly, we observed that tumor cells actively deplete VB6 in tumor microenvironments, as observed by comparing VB6 levels in circulation and in tumor interstitial fluids. Finally, we observed that VB6 supplementation in combination with inhibitors targeting VB6-driven metabolic pathway dependencies in tumor cells effectively enhances NK cell frequency and diminishes tumor burden in vivo. These studies demonstrate a novel role of glycogen breakdown as a critical energy source for activated NK cells and demonstrate, for the first time a key role of glycogenolysis in NK cell cytotoxic activities. Our results expand the understanding of the critical role of micronutrients (vitamin B6) in regulating cancer progression and anti-tumor immunity and open new avenues for developing NK cell-based immunotherapies for PDAC patients. Citation Format: Kamiya Mehla. Nutrient competition in the tumor microenvironment alters NK cell metabolism in Pancreatic Cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr A021.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.029
GPT teacher head0.321
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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