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Record W3126819005 · doi:10.1002/stem.3352

Protein kinase C-β-dependent changes in the glucose metabolism of bone marrow stromal cells of chronic lymphocytic leukemia

2021· article· en· W3126819005 on OpenAlexaff
Franziska von Heydebrand, Maximilian Fuchs, Meik Kunz, Simon Voelkl, Anita N. Kremer, Robert A.J. Oostendorp, Jochen Wilke, Michael Leitges, Alexander Egle, Andréas Mackensen, Gloria Lutzny‐Geier

Bibliographic record

VenueStem Cells · 2021
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsMemorial University of Newfoundland
FundersDeutsche ForschungsgemeinschaftBoettcher Foundation
KeywordsStromal cellBiologyChronic lymphocytic leukemiaCancer researchBone marrowProtein kinase CCell biologyTumor microenvironmentGlucose uptakeKinaseLeukemiaImmunologyEndocrinologyInsulin

Abstract

fetched live from OpenAlex

Survival of chronic lymphocytic leukemia (CLL) cells critically depends on the support of an adapted and therefore appropriate tumor microenvironment. Increasing evidence suggests that B-cell receptor-associated kinases such as protein kinase C-β (PKCβ) or Lyn kinase are essential for the formation of a microenvironment supporting leukemic growth. Here, we describe the impact of PKCβ on the glucose metabolism in bone marrow stromal cells (BMSC) upon CLL contact. BMSC get activated by CLL contact expressing stromal PKCβ that diminishes mitochondrial stress and apoptosis in CLL cells by stimulating glucose uptake. In BMSC, the upregulation of PKCβ results in increased mitochondrial depolarization and leads to a metabolic switch toward oxidative phosphorylation. In addition, PKCβ-deficient BMSC regulates the expression of Hnf1 promoting stromal insulin signaling after CLL contact. Our data suggest that targeting PKCβ and the glucose metabolism of the leukemic niche could be a potential therapeutic strategy to overcome stroma-mediated drug resistance.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.015
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.259
Teacher spread0.241 · 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 teacher head, 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".

Quick stats

Citations11
Published2021
Admission routes1
Has abstractyes

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