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Published on: March 28, 2021
Drug combinations identified by high-throughput screening promote cell cycle transition and upregulate Smad pathways
Tyler J Peat1, Snehal M Gaikwad2, Wendy Dubois2
1Laboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA; Department of Comparative Pathobiology, Purdue University, West Lafayette, IN, USA.
Abstract:
Drug resistance and disease progression are common in multiple myeloma (MM) patients, underscoring the need for new therapeutic combinations. A high-throughput drug screen in 47 MM cell lines and in silico Huber robust regression analysis of drug responses revealed 43 potentially synergistic combinations. We hypothesized that effective combinations would reduce MYC expression and enhance p16 activity. Six combinations cooperatively reduced MYC protein, frequently over-expressed in MM and also cooperatively increased p16 expression, frequently downregulated in MM. Synergistic reductions in viability were observed with top combinations in proteasome inhibitor-resistant and sensitive MM cell lines, while sparing fibroblasts. Three combinations significantly prolonged survival in a transplantable Ras-driven allograft model of advanced MM closely recapitulating high-risk/refractory myeloma in humans and reduced viability of ex vivo treated patient cells. Common genetic pathways similarly downregulated by these combinations promoted cell cycle transition, whereas pathways most upregulated were involved in TGFβ/SMAD signaling. These preclinical data identify potentially useful drug combinations for evaluation in drug-resistant MM and reveal potential mechanisms of combined drug sensitivity.
Insights
New drug combinations show promise for treating multiple myeloma (MM) by reducing MYC and enhancing p16 activity. These synergistic therapies effectively target drug-resistant MM cells and improve survival in preclinical models.
Area of Science:
- Oncology
- Pharmacology
- Genetics
Background:
- Drug resistance and disease progression are significant challenges in multiple myeloma (MM) treatment.
- There is a critical need for novel therapeutic strategies and drug combinations to overcome resistance.
Purpose of the Study:
- To identify and validate synergistic drug combinations for multiple myeloma (MM).
- To investigate the impact of these combinations on MYC expression and p16 activity.
- To evaluate the efficacy of promising combinations in preclinical MM models.
Main Methods:
- High-throughput drug screening across 47 MM cell lines.
- In silico Huber robust regression analysis for drug response prediction.
- Assessment of MYC protein and p16 expression levels.
- Evaluation in a transplantable mouse model of advanced MM.
- Ex vivo treatment of patient-derived cells.
Main Results:
- Identified 43 potentially synergistic drug combinations.
- Six combinations cooperatively reduced MYC and increased p16 expression.
- Top combinations showed synergistic viability reduction in resistant and sensitive MM cells, sparing fibroblasts.
- Three combinations prolonged survival in a preclinical MM model and reduced patient cell viability.
- Analysis revealed modulation of cell cycle and TGFβ/SMAD signaling pathways.
Conclusions:
- Preclinical data identify promising drug combinations for drug-resistant MM.
- These combinations demonstrate efficacy in reducing MM cell viability and improving survival.
- The study reveals potential mechanisms underlying combined drug sensitivity, including MYC/p16 modulation and TGFβ/SMAD signaling.
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