Inhibiting BCKDK in triple negative breast cancer suppresses protein translation, impairs mitochondrial function, and potentiates doxorubicin cytotoxicity
Bibliographic record
Abstract
Triple-negative breast cancers (TNBCs) are characterized by poor survival, prognosis, and gradual resistance to cytotoxic chemotherapeutics, like doxorubicin (DOX). The clinical utility of DOX is limited by its cardiotoxic and chemoresistant effects that manifest over time. To induce chemoresistance, TNBC rewires oncogenic gene expression and cell signaling pathways. Recent studies have demonstrated that reprogramming of branched-chain amino acids (BCAAs) metabolism facilitates tumor growth and survival. Branched-chain ketoacid dehydrogenase kinase (BCKDK), a regulatory kinase of the rate-limiting enzyme of the BCAA catabolic pathway, is reported to activate RAS/RAF/MEK/ERK signaling to promote tumor cell proliferation. However, it remains unexplored if BCKDK action remodels TNBC proliferation and survival per se and influences susceptibility to DOX-induced genotoxic stress. TNBC cells treated with DOX exhibited reduced BCKDK expression and intracellular BCKAs. Genetic and pharmacological inhibition of BCKDK in TNBC cell lines also showed a similar reduction in intracellular and secreted BCKAs. BCKDK silencing in TNBC cells downregulated mitochondrial metabolism genes, reduced electron complex protein expression, oxygen consumption, and ATP production. Transcriptome analysis of BCKDK silenced cells confirmed dysregulation of mitochondrial metabolic networks and upregulation of the apoptotic signaling pathway. Furthermore, BCKDK inhibition with concurrent DOX treatment exacerbated apoptosis, caspase activity, and loss of TNBC proliferation. Inhibition of BCKDK in TNBC also upregulated sestrin 2 and concurrently decreased mTORC1 signaling and protein synthesis. Overall, loss of BCKDK action in TNBC remodels BCAA flux, reduces protein translation triggering cell death, ATP insufficiency, and susceptibility to genotoxic stress.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".