Heme promotes venetoclax resistance in multiple myeloma through MEK-ERK signaling and purine biosynthesis
Bibliographic record
Abstract
ABSTRACT: We previously demonstrated that reduced intrinsic electron transport chain (ETC) activity predicts and promotes sensitivity to the B-cell lymphoma 2 (BCL-2) antagonist, venetoclax (Ven), in multiple myeloma (MM). Heme, an iron-containing prosthetic group and metabolite, is fundamental to maintaining ETC activity. Interrogation of the cyclin D1 group 2 subgroup of MM from the Relating Clinical Outcomes in MM to Personal Assessment of Genetic Profile (CoMMpass) trial (NCT01454297), which can be used as a proxy for Ven-sensitive MM (VS MM), shows reduced expression of the conserved heme biosynthesis pathway gene signature. Consistent with this, we identified that VS MM exhibits reduced heme biosynthesis and curiously elevated hemin (oxidized heme) uptake. Supplementation with hemin or protoporphyrin IX (heme lacking iron) promotes Ven resistance, whereas targeting ferrochetalase, the penultimate enzyme involved in heme biosynthesis, increases Ven sensitivity in cell lines and primary MM cells. Mechanistically, heme-mediated activation of prosurvival rapidly accelerated fibrosarcoma-rat sarcoma virus-mitogen-activated protein kinase (MEK) signaling and metabolic rewiring, increasing de novo purine synthesis, were found to contribute to heme-induced Ven resistance. Cotargeting BCL-2 and myeloid cell leukemia-1 suppresses heme-induced Ven resistance. Interrogation of the Multiple Myeloma Research Foundation CoMMpass study of patients shows increased purine and pyrimidine biosynthesis to corelate with poor progression-free survival and overall survival. Elevated heme and purine biosynthesis gene signatures were also observed in matched relapse refractory MM, underscoring the relevance of heme metabolism in therapy-refractory MM. Overall, our findings reveal, for the first time, a role for extrinsic heme, a physiologically relevant metabolite, in modulating proximity to the apoptotic threshold with translational implications for BCL-2 antagonism in MM therapy.
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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) | 0.002 | 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".