Marcks Inhibition By a Peptide Inhibitor, MPS, Cooperates with Bortezomib to Effectively Eliminate Drug Resistance in Multiple Myeloma
Bibliographic record
Abstract
Abstract Overexpression of myristoylated alanine-rich C kinase substrate (MARCKS) has been implicated in the progression of multiple cancer types including multiple myeloma (MM). Our previous study showed that overexpression of MARCKS in MM cells plays an important role in drug resistance. However; the mechanism(s) underlying MARCKS overexpression and its association with drug resistance in MM remain undefined. Using miRNA target scan algorithms, we identified miR-34a as a regulator of MARCKS, which is underexpressed in drug-resistant MM cells (8226-R5 and MM1R) in comparison to parental cells (8226 and MM1S, respectively). Using luciferase assays, we demonstrated direct targeting of MARCKS by miR-34a. Notably, targeting of MARCKS by miR-34a overexpression re-sensitized the resistant cells to anti-myeloma drugs. Moreover, since all known biological functions of MARCKS including its oncogenic effects are conducted by its phosphorylated form, we investigated whether inhibitor of MARCKS phosphorylation could antagonize drug resistance in MM cells. We showed that a MARCKS PSD peptide inhibitor (MPS) had a dose dependent cytotoxic effect on drug resistant MM cells in comparison to its mutated (inactive) form, but minimal cytotoxicity on normal peripheral blood mononuclear cells (PBMCs). Furthermore, MPS treatment sensitized drug-resistant MM cells to bortezomib (BTZ), a first line proteasome inhibitor that is widely used in the treatment of MM. We further investigated the effect of MPS on tumorigenesis in mouse xenograft models of MM resistant cells. Combination of BTZ plus MPS significantly suppressed tumor growth and prolonged overall survival as compared with MPS alone, BTZ alone or vehicle treated controls. IHC analysis of xenograft tumor sections revealed that combination treatment of MPS and BTZ resulted in decreased proliferation (Ki67) and increased apoptosis (TUNEL), compared to either BTZ or MPS alone. These results support that targeting of phospho-MARCKS by MPS contributes to drug sensitivity in MM resistant cells. Furthermore, we investigated the mechanisms by which MPS induces cell death and overcome bortezomib resistance. Following MPS treatment, PUMA was accumulated both in MM1R and 8226R5 MM cell lines, indicating that MPS treatment may lead to apoptosis. Interestingly, the level of LC3BII, a marker of autophagy, was also significantly upregulated, suggesting enhanced autophagic flux after MARCKS inhibition. The significant upregulation of LC3BII observed in both MM1R and 8226R5 MM cell lines after MARCKS silencing further confirmed the correlation between MARCKS inhibition and autophagy induction. Remarkably, MARCKS-silenced drug resistant MM cells were more vulnerable than negative control cells to the autophagy inhibitor chloroquine (CQ). More significant cytotoxicity of the BTZ plus CQ combo was also detected in MARCKS-inhibited MM cells than in negative control cells. Mechanistically, co-immuno-precipitation assays revealed increased interactions of PUMA with both Mcl-1 and Bcl-xL in MARCKS-silenced 8226R5 cells, while the interaction between Beclin-1 and Bcl-xL in MARCKS silenced 8226R5 cells was dampened. These results suggest that PUMA upregulation after MRCKS inhibition enhances the initiation of autophagic response by sequestering Bcl-2 family proteins like Bcl-xL from Beclin-1/Vps34 complexes. Taken together, our results demonstrate that the MPS peptide can sensitize drug resistant MM cell to anti-myeloma drugs by inhibiting MARCKS phosphorylation in vitro and in vivo. These findings underscore the importance of MARCKS suppression in antagonizing adaptive BTZ resistance and provide novel venues to treat MM. Disclosures No relevant conflicts of interest to declare.
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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) | 0.001 | 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".