Marcks Peptide Inhibitor Displays Synergistic Cytotoxicity with Bortezomib in Drug Resistant Multiple Myeloma Cells but Enhances Autophagic Effect
Bibliographic record
Abstract
Abstract Myristoylated alanine-rich C kinase substrate (MARCKS) is a protein which has recently been connected to the progression of multiple cancer types including multiple myeloma (MM). MARCKS can be phosphorylated and then activated by several PKCs in its phosphorylation site domain (PSD). All known biological functions of MARCKS including its oncogenic effects are conducted by its phosphorylated form. Although in an earlier study we have shown that MARCKS knocking down could lead to cell cycle arrest and apoptosis in drug resistant MM cell lines, whether it is possible to antagonize drug resistance of MM cells by inhibitors of MARCKS phosphorylation is still unclear. Here we investigated the anti-myeloma activity of MARCKS inhibitors in MM cells by applying MARCKS PSD peptide inhibitor (MPS), a validated 25-amino-acid peptide targeting the MARCKS PSD. Two drug resistant MM cell lines MM1R and 8226R5 as well as normal peripheral blood mononuclear cells (PBMCs) derived from three healthy volunteers were exposed to MPS for 48 hours. Compared with its mutated (inactive) form, treatment of this inhibitor led to a dose dependent cytotoxic effect on drug resistant MM cells, while it did not affect cell viability of normal PBMCs. Furthermore, MPS treatment significantly sensitized MM1R and 8226R5 cells to bortezomib exposure after 48 hrs. Co-treatment of these two agents exhibited synergistic effect on both of the above resistant MM cell lines (on 8226R5, the combination index (CI) = 0.79; on MM1R, CI=0.88). We next investigated the mechanisms by which MPS may induce cell death and overcome bortezomib resistance. Following MPS treatment, accumulation of p27Kip1as well as dampened phosphorylation of Akt1 were identified both in MM1R and 8226R5 MM cell lines, indicating that MPS treatment may lead to cell cycle arrest and growth suppression. Interestingly, the level of LC3BII, a marker of autophagy, was also significantly upregulated, which suggested an enhancement of autophagic activity after MARCKS inhibition. To confirm the correlation between MARCKS inhibition and autophagy induction, we knocked down MARCKS by transfecting shRNA lentiviral vectors into above drug resistant MM cells. Western blots showed a significantly upregulated LC3BII in both cell lines with MARCKS silencing, compared with cells transfected by scrambled shRNA. Accumulation of lysosomes as well as autophagosomes was also observed separately via cellular staining with acridine orange and florescence-labeled LC3BII antibody. Upregulation of autophagy has been tightly related to the induction of drug resistance in cancer cells. Thus, drug resistant MM cells with impaired MARCKS activity may become more dependent on the pro-survival outcome of autophagy when exposed to anti-tumor drugs like bortezomib. To examine this hypothesis, both MARCKS-silenced MM1R and 8226R5 cells as well as negative control cells expressing scramble shRNA were co-treated with bortezomib and autophagy inhibitor chloroquine (CQ) for 48hrs. MTT assays showed that the combination of CQ and bortezomib resulted in more cell death in MARCKS-silenced drug resistant MM cells than negative control cells (~40% and ~30% more cell death in MM1R (p<0.01) and 8226R5 (p<0.05) cell lines, respectively). In MARCKS-silenced cells, synergistic effects of CQ and bortezomib were also more significant than in negative control cells. Hence depletion of MARCKS activity makes MM cells more vulnerable to bortezomib when cellular autophagic activity is intercepted. We are currently examining the in vivo activity of MPS using xenograft mice models. Taken together, our results indicate that MPS peptide is effective in killing myeloma cells by inhibition of phosphorylation of MARCKS but also enhances autophagic response. This previously unappreciated correlation between MARCKS suppression and autophagy enhancement suggests that the combination of bortezomib, MARCKS inhibitor, as well as autophagy antagonists like chloroquine may contribute to the development of novel MM therapies. Disclosures No relevant conflicts of interest to declare.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".