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      A curative combination cancer therapy achieves high fractional cell killing through low cross-resistance and drug additivity

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          Abstract

          Curative cancer therapies are uncommon and nearly always involve multi-drug combinations developed by experimentation in humans; unfortunately, the mechanistic basis for the success of such combinations has rarely been investigated in detail, obscuring lessons learned. Here, we use isobologram analysis to score pharmacological interaction, and clone tracing and CRISPR screening to measure cross-resistance among the five drugs comprising R-CHOP, a combination therapy that frequently cures Diffuse Large B-Cell Lymphomas. We find that drugs in R-CHOP exhibit very low cross-resistance but not synergistic interaction: together they achieve a greater fractional kill according to the null hypothesis for both the Loewe dose-additivity model and the Bliss effect-independence model. These data provide direct evidence for the 50 year old hypothesis that a curative cancer therapy can be constructed on the basis of independently effective drugs having non-overlapping mechanisms of resistance, without synergistic interaction, which has immediate significance for the design of new drug combinations.

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          Glutathione metabolism in cancer progression and treatment resistance

          Bansal and Simon discuss strategies to block glutathione synthesis and utilization pathways to inhibit tumor propagation and treatment resistance.
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            Rituximab: mechanism of action.

            Rituximab is a mainstay in the therapy for a broad variety of B-cell malignancies. Despite its undeniable therapeutic value, we still do not fully understand the mechanisms of action responsible for rituximab's anti-tumor effects. Direct signaling, complement-mediated cytotoxicity (CMC), and antibody-dependent cellular cytotoxicity (ADCC) all appear to play a role in rituximab efficacy. In vitro, animal model and clinical data addressing each of these mechanisms of action are reviewed, as are data speaking to the complexity of interactions between these mechanisms. Taken together, these data suggest different mechanisms are likely important in different scenarios. Study of the complex mechanisms of action that contribute to the clinical efficacy of rituximab have led to novel clinical trials including novel combinations, schedules, and generation of additional antibodies designed to have even greater effect. Such studies need to be accompanied by rigorous correlative analysis if we are to understand the importance of various mechanisms of action of rituximab and use that information to improve on what is already an indispensable component of therapy.
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              Evolutionary dynamics of cancer in response to targeted combination therapy

              In solid tumors, targeted treatments can lead to dramatic regressions, but responses are often short-lived because resistant cancer cells arise. The major strategy proposed for overcoming resistance is combination therapy. We present a mathematical model describing the evolutionary dynamics of lesions in response to treatment. We first studied 20 melanoma patients receiving vemurafenib. We then applied our model to an independent set of pancreatic, colorectal, and melanoma cancer patients with metastatic disease. We find that dual therapy results in long-term disease control for most patients, if there are no single mutations that cause cross-resistance to both drugs; in patients with large disease burden, triple therapy is needed. We also find that simultaneous therapy with two drugs is much more effective than sequential therapy. Our results provide realistic expectations for the efficacy of new drug combinations and inform the design of trials for new cancer therapeutics. DOI: http://dx.doi.org/10.7554/eLife.00747.001
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                19 November 2019
                2019
                : 8
                : e50036
                Affiliations
                [1 ]Laboratory of Systems Pharmacology, Harvard Medical School BostonUnited States
                [2 ]deptDepartment of Systems Biology Harvard Medical School BostonUnited States
                Memorial Sloan Kettering Cancer Center United States
                McGill University Canada
                Memorial Sloan Kettering Cancer Center United States
                Author notes
                [‡]

                Department of Pharmacology, Computational Medicine Program, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, United States.

                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0001-5028-7028
                http://orcid.org/0000-0002-8212-3148
                https://orcid.org/0000-0002-3364-1838
                Article
                50036
                10.7554/eLife.50036
                6897534
                31742555
                edb4bfa9-eb0e-4698-bb8a-85d8d3a68639
                © 2019, Palmer et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 09 July 2019
                : 18 November 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: P50-GM107618
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: U54-CA225088
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Award ID: 1072965
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000913, James S. McDonnell Foundation;
                Award ID: 2012036
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Cancer Biology
                Computational and Systems Biology
                Custom metadata
                Drugs in a curative chemotherapy regimen are independently effective and resisted by different mechanisms, so cancer cells have little chance of surviving all drugs, and this benefit occurs without synergistic interactions.

                Life sciences
                cancer,combination therapy,drug resistance,tumor heterogeneity,human
                Life sciences
                cancer, combination therapy, drug resistance, tumor heterogeneity, human

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