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A Platform for Rapid, Quantitative Assessment of Multiple Drug Combinations Simultaneously in Solid Tumors In Vivo.

ABSTRACT: While advances in high-throughput screening have resulted in increased ability to identify synergistic anti-cancer drug combinations, validation of drug synergy in the in vivo setting and prioritization of combinations for clinical development remain low-throughput and resource intensive. Furthermore, there is currently no viable method for prospectively assessing drug synergy directly in human patients in order to potentially tailor therapies. To address these issues we have employed the previously described CIVO platform and developed a quantitative approach for investigating multiple combination hypotheses simultaneously in single living tumors. This platform provides a rapid, quantitative and cost effective approach to compare and prioritize drug combinations based on evidence of synergistic tumor cell killing in the live tumor context. Using a gemcitabine resistant model of pancreatic cancer, we efficiently investigated nine rationally selected Abraxane-based combinations employing only 19 xenografted mice. Among the drugs tested, the BCL2/BCLxL inhibitor ABT-263 was identified as the one agent that synergized with Abraxane® to enhance acute induction of localized apoptosis in this model of human pancreatic cancer. Importantly, results obtained with CIVO accurately predicted the outcome of systemic dosing studies in the same model where superior tumor regression induced by the Abraxane/ABT-263 combination was observed compared to that induced by either single agent. This supports expanded use of CIVO as an in vivo platform for expedited in vivo drug combination validation and sets the stage for performing toxicity-sparing drug combination studies directly in cancer patients with solid malignancies.

SUBMITTER: Dey J

PROVIDER: S-EPMC4928803 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:With rapid advances in our understanding of cancer, there is an expanding number of potential novel combination therapies, including novel-novel combinations. Identifying which combinations are appropriate and in which subpopulations are among the most difficult questions in medical research. We conducted a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-guided systematic review of trials of novel-novel combination therapies involving immunotherapies or molecular targeted therapies in advanced solid tumors. A MEDLINE search was conducted using a modified Cochrane Highly Sensitive Search Strategy for published clinical trials between July 1, 2017, and June 30, 2020, in the top-ranked medical and oncology journals. Trials were evaluated according to a criterion adapted from previously published Food and Drug Administration guidance and other key considerations in designing trials of combinations. This included the presence of a strong biological rationale, the use of a new established or emerging predictive biomarker prospectively incorporated into the clinical trial design, appropriate comparator arms of monotherapy or supportive external data sources and a primary endpoint demonstrating a clinically meaningful benefit. Of 32 identified trials, there were 11 (34%) trials of the novel-novel combination of anti-programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) and anti-cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) therapy, and 10 (31%) trials of anti-PD-1/PD-L1 and anti-vascular endothelial growth factor (VEGF) combination therapy. 20 (62.5%) trials were phase II trials, while 12 (37.5%) were phase III trials. Most (72%) trials lacked significant preclinical evidence supporting the development of the combination in the given indication. A majority of trials (69%) were conducted in biomarker unselected populations or used pre-existing biomarkers within the given indication for patient selection. Most studies (66%) were considered to have appropriate comparator arms or had supportive external data sources such as prior studies of monotherapy. All studies were evaluated as selecting a clinically meaningful primary endpoint. In conclusion, designing trials to evaluate novel-novel combination therapies presents numerous challenges to demonstrate efficacy in a comprehensive manner. A greater understanding of biological rationale for combinations and incorporating predictive biomarkers may improve effective evaluation of combination therapies. Innovative statistical methods and increasing use of external data to support combination approaches are potential strategies that may improve the efficiency of trial design. Designing trials to evaluate novel-novel combination therapies presents numerous challenges to demonstrate efficacy in a comprehensive manner. A greater understanding of biological rationale for combinations and incorporating predictive biomarkers may improve effective evaluation of combination therapies. Innovative statistical methods and increasing use of external data to support combination approaches are potential strategies that may improve the efficiency of trial design.

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A Platform for Rapid, Quantitative Assessment of Multiple Drug Combinations Simultaneously in Solid Tumors In Vivo.

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