Pre-Clinical Evaluation of a Small Molecule Inhibitor of CDK1 as Potential Therapy for MYC Expressing Mutiple Myeloma Tumors
Bibliographic record
Abstract
Abstract Through the recent elucidation of molecular and cellular processes in multiple myeloma (MM) pathogenesis that effect well-defined proliferative and survival pathways, a number of molecular targets for anti-cancer agents have emerged. This includes proteins involved in cell cycle regulation. A recent model of early MM pathogenesis proposes that at least one of the cyclin D genes is dysregulated in all myeloma tumors facilitating activation of cyclin dependent kinase (CDK)4 (or CDK6), and transition from G1 to S phase. It is hypothesized that this renders myeloma cells more responsive to bone marrow (BM) derived proliferative stimuli including IL-6 that upregulates MYC expression in MM cells and cooperates with cyclin D to promote transit to S-phase. In addition, recent studies have established a causative role of MYC dysreguation in progression from monoclonal gammopathy to myeloma. Thus an approach targeting deregulated cell cycle progression and MYC may prove effective MM therapy. Purvalanol is a potent and selective inhibitor of CDK1, an important regulator of cell cycle progression and has been reported to induce MYC-dependent apoptosis. Activity of purvalanol against a panel of 14 standardized, annotated myeloma cell lines was measured in a 48 hour MTT viability assay. IC50-s of all 14 cell lines ranged between 5 uM to 7.5 uM. Western blot and real-time PCR analysis revealed variability of MYC protein and mRNA levels between the 14 myeloma cell lines. We compared potential therapeutic activity of purvalanol against 3 myeloma cell lines (U266, H929, KMS12PE) with low, intermediate, and high levels of c-MYC expression, respectively. All three cell lines demonstrated G2-M growth arrest however marked apoptosis as determined by PI/annexin V staining was observed only in the cell lines with the highest level of MYC expression. Exposure of MM patient-derived BM mononuclear cells to purvalanol preferentially induced apoptosis of CD138+ MM cells. In contrast, purvalanol was minimally cytotoxic to the non-myeloma cell fraction and to non-transformed fibroblast cell lines (MRC5, IMR90 and W138) and failed to inhibit normal bone marrow-derived CD34 colony formation. Recent studies have demonstrated that the BM microenvironment offers protection of myeloma cells from chemotherapeutic agents by common mechanisms. Myeloma cell lines were cultured in 3 different conditions to mimic the tumor’s protective microenvironment. Soluble factors produced by the BM, IL6 and IGF-1 induced a modest degree of resistance to purvalanol while co-culture on BM stroma cells was completely protective. Studies evaluating the in vivo efficacy of purvalanol in a novel Vk*myc transgenic mouse model that spontaneously develops myeloma with a low proliferative index are ongoing and will be presented. The CDK1 inhibitor, purvalanol demonstrates broad single agent activity against myeloma cells with enhanced activity against MYC overexpressing cells. However, the strong protective effect of the BM microenvironment suggest that combination with agents that can reverse cell-adhesion mediated drug resistance may prove beneficial in optimizing the efficacy of this class of drugs for the treatment of MM.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".