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      Independent Drug Action in Combination Therapy: Implications for Precision Oncology

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          Abstract

          Combination therapies are superior to monotherapy for many cancers. This advantage was historically ascribed to the ability of combinations to address tumor heterogeneity, but synergistic interaction is now a common explanation as well as a design criterion for new combinations. We review evidence that independent drug action, described in 1961, explains the efficacy of many practice-changing combination therapies: it provides populations of patients with heterogeneous drug sensitivities multiple chances of benefit from at least one drug. Understanding response heterogeneity could reveal predictive or pharmacodynamic biomarkers for more precise use of existing drugs and realize the benefits of additivity or synergy.

          Significance:

          The model of independent drug action represents an effective means to predict the magnitude of benefit likely to be observed in new clinical trials for combination therapies. The “bet-hedging” strategy implicit in independent action suggests that individual patients often benefit from only a subset—sometimes one—of the drugs in a combination. Personalized, targeted combination therapy, consisting of agents likely to be active in a particular patient, will increase, perhaps substantially, the magnitude of therapeutic benefit. Precision approaches of this type will require a better understanding of variability in drug response and new biomarkers, which will entail preclinical research on diverse panels of cancer models rather than studying drug synergy in unusually sensitive models.

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          Most cited references138

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          Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq.

          To explore the distinct genotypic and phenotypic states of melanoma tumors, we applied single-cell RNA sequencing (RNA-seq) to 4645 single cells isolated from 19 patients, profiling malignant, immune, stromal, and endothelial cells. Malignant cells within the same tumor displayed transcriptional heterogeneity associated with the cell cycle, spatial context, and a drug-resistance program. In particular, all tumors harbored malignant cells from two distinct transcriptional cell states, such that tumors characterized by high levels of the MITF transcription factor also contained cells with low MITF and elevated levels of the AXL kinase. Single-cell analyses suggested distinct tumor microenvironmental patterns, including cell-to-cell interactions. Analysis of tumor-infiltrating T cells revealed exhaustion programs, their connection to T cell activation and clonal expansion, and their variability across patients. Overall, we begin to unravel the cellular ecosystem of tumors and how single-cell genomics offers insights with implications for both targeted and immune therapies.
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            Five-Year Survival with Combined Nivolumab and Ipilimumab in Advanced Melanoma

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              Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma.

              Human cancers are complex ecosystems composed of cells with distinct phenotypes, genotypes, and epigenetic states, but current models do not adequately reflect tumor composition in patients. We used single-cell RNA sequencing (RNA-seq) to profile 430 cells from five primary glioblastomas, which we found to be inherently variable in their expression of diverse transcriptional programs related to oncogenic signaling, proliferation, complement/immune response, and hypoxia. We also observed a continuum of stemness-related expression states that enabled us to identify putative regulators of stemness in vivo. Finally, we show that established glioblastoma subtype classifiers are variably expressed across individual cells within a tumor and demonstrate the potential prognostic implications of such intratumoral heterogeneity. Thus, we reveal previously unappreciated heterogeneity in diverse regulatory programs central to glioblastoma biology, prognosis, and therapy. Copyright © 2014, American Association for the Advancement of Science.
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                Author and article information

                Journal
                Cancer Discov
                Cancer Discov
                Cancer Discovery
                American Association for Cancer Research
                2159-8274
                2159-8290
                01 March 2022
                08 March 2022
                : 12
                : 3
                : 606-624
                Affiliations
                [1 ]Laboratory of Systems Pharmacology and the Department of Systems Biology, Harvard Medical School, Boston, Massachusetts.
                [2 ]Harvard-MIT Division of Health Sciences and Technology, Cambridge, Massachusetts.
                [3 ]Department of Pharmacology, Computational Medicine Program, UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
                Author notes
                [#]

                D. Plana and A.C. Palmer contributed equally to this article.

                [* ] Corresponding Authors: Peter K. Sorger, Systems Biology, Harvard Medical School, Warren Alpert 440, Boston, MA 02115. Phone: 617-432-6901; Fax: 617-432-6990; E-mail: peter_sorgerhms.harvard.edu (cc: sorger_admin@ 123456hms.harvard.edu) ; and Adam C. Palmer, University of North Carolina at Chapel Hill, 116 Manning Drive, Mary Ellen Jones Building, Room 11-202A, CB# 1045, Chapel Hill, NC 27599. Phone: 857-234-7964; E-mail: palmer@ 123456unc.edu
                Author information
                https://orcid.org/0000-0002-4218-1693
                https://orcid.org/0000-0001-5028-7028
                https://orcid.org/0000-0002-3364-1838
                Article
                CD-21-0212
                10.1158/2159-8290.CD-21-0212
                8904281
                34983746
                a2bdc74c-98df-4b9b-a13a-9226bd7f5e9b
                ©2022 The Authors; Published by the American Association for Cancer Research

                This open access article is distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license.

                History
                : 12 February 2021
                : 02 September 2021
                : 10 November 2021
                Page count
                Pages: 19
                Funding
                Funded by: NIH, DOI http://dx.doi.org/10.13039/100000002, NCI, DOI http://dx.doi.org/10.13039/100000054;
                Award ID: U54-CA225088
                Funded by: NIGMS grant, DOI http://dx.doi.org/10.13039/100000057;
                Award ID: T32-GM007753
                Funded by: NCI grant, DOI http://dx.doi.org/10.13039/100000054;
                Award ID: F30-CA260780
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