Inhibiting BCKDK in triple negative breast cancer suppress protein translation, impair mitochondrial function, and potentiate doxorubicin cytotoxicity
Bibliographic record
Abstract
Abstract Triple-negative breast cancers (TNBCs) are characterized by poor survival, prognosis and gradual resistance to cytotoxic chemotherapeutics, like doxorubicin (DOX), which is limited by its cardiotoxic and chemoresistant effects that manifest over time. TNBC growth and survival are fuelled by reprogramming branched-chain amino acids (BCAAs) metabolism, which rewires oncogenic gene expression and cell signaling pathways. A regulatory kinase of the rate-limiting enzyme of the BCAA catabolic pathway, branched-chain ketoacid dehydrogenase kinase (BCKDK), have recently been implicated in driving tumor cell proliferation and conferring drug resistance by activating RAS/RAF/MEK/ERK signaling. However it remains unexplored if BCKDK remodels TNBC proliferation, survival and susceptibility to DOX-induced genotoxic stress. TNBC cell lines exhibited reduced BCKDK expression in response to DOX. Genetic and pharmacological inhibition of BCKDK in TNBC cell lines displayed reduced intracellular and secreted BCKAs. Moreover, BCKDK inhibition with concurrent DOX treatment exacerbated apoptosis, caspase activity and loss of TNBC proliferation. Transcriptome analysis of BCKDK silenced cells confirmed a marked upregulation of the apoptotic signaling pathway with increased protein ubiquitylation and compromised mitochondrial metabolism. BCKDK silencing in TNBC downregulated mitochondrial metabolism genes, reduced electron complex protein expression, oxygen consumption and ATP production. Silencing BCKDK in TNBC upregulated sestrin 2 and concurrently decreased protein synthesis and mTORC1 signaling. Inhibiting BCKDK in TNBC remodel BCAA flux, reduces protein translation triggering cell death, ATP insufficiency and susceptibility to genotoxic stress. Graphical abstract
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".