Personalized Cancer Models for Target Discovery and Precision Medicine

Ocana, 2010, Preclinical development of molecular-targeted agents for cancer, Nat. Rev. Clin. Oncol., 8, 200, 10.1038/nrclinonc.2010.194 DiMasi, 2013, Clinical approval success rates for investigational cancer drugs, Clin. Pharmacol. Ther., 94, 329, 10.1038/clpt.2013.117 Gould, 2015, Translational value of mouse models in oncology drug development, Nat. Med., 21, 431, 10.1038/nm.3853 Gengenbacher, 2017, Preclinical mouse solid tumour models: status quo, challenges and perspectives, Nat. Rev. Cancer, 17, 751, 10.1038/nrc.2017.92 Barretina, 2012, The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity, Nature, 483, 603, 10.1038/nature11003 Iorio, 2016, A landscape of pharmacogenomic interactions in cancer, Cell, 166, 740, 10.1016/j.cell.2016.06.017 Johnson, 2001, Relationships between drug activity in NCI preclinical in vitro and in vivo models and early clinical trials, Br. J. Cancer, 84, 1424, 10.1054/bjoc.2001.1796 Sharma, 2010, Cell line-based platforms to evaluate the therapeutic efficacy of candidate anticancer agents, Nat. Rev. Cancer, 10, 241, 10.1038/nrc2820 Sharpless, 2006, The mighty mouse: genetically engineered mouse models in cancer drug development, Nat. Rev. Drug Discov., 5, 741, 10.1038/nrd2110 Letai, 2017, Functional precision cancer medicine-moving beyond pure genomics, Nat. Med., 23, 1028, 10.1038/nm.4389 Tannock, 2016, Limits to personalized cancer medicine, N. Engl. J. Med., 375, 1289, 10.1056/NEJMsb1607705 Hutter, 2018, The Cancer Genome Atlas: creating lasting value beyond Its data, Cell, 173, 283, 10.1016/j.cell.2018.03.042 Sanchez-Vega, 2018, Oncogenic signaling pathways in The Cancer Genome Atlas, Cell, 173, 321, 10.1016/j.cell.2018.03.035 Way, 2018, Machine learning detects pan-cancer ras pathway activation in The Cancer Genome Atlas, Cell Rep., 23, 172, 10.1016/j.celrep.2018.03.046 Schaub, 2018, Pan-cancer alterations of the MYC oncogene and its proximal network across the Cancer Genome Atlas, Cell Syst., 6, 282, 10.1016/j.cels.2018.03.003 Druker, 1996, Effects of a selective inhibitor of the Abl tyrosine kinase on the growth of Bcr-Abl positive cells, Nat. Med., 2, 561, 10.1038/nm0596-561 Druker, 2006, Five-year follow-up of patients receiving imatinib for chronic myeloid leukemia, N. Engl. J. Med., 355, 2408, 10.1056/NEJMoa062867 O’Brien, 2003, Imatinib compared with interferon and low-dose cytarabine for newly diagnosed chronic-phase chronic myeloid leukemia, N. Engl. J. Med., 348, 994, 10.1056/NEJMoa022457 Camidge, 2012, Activity and safety of crizotinib in patients with ALK-positive non-small-cell lung cancer: updated results from a phase 1 study, Lancet Oncol., 13, 1011, 10.1016/S1470-2045(12)70344-3 Shaw, 2013, Crizotinib versus chemotherapy in advanced ALK-positive lung cancer, N. Engl. J. Med., 368, 2385, 10.1056/NEJMoa1214886 Katayama, 2015, Therapeutic targeting of anaplastic lymphoma kinase in lung cancer: a paradigm for precision cancer medicine, Clin. Cancer Res., 21, 2227, 10.1158/1078-0432.CCR-14-2791 Prior, 2012, A comprehensive survey of Ras mutations in cancer, Cancer Res., 72, 2457, 10.1158/0008-5472.CAN-11-2612 Leroy, 2014, TP53 mutations in human cancer: database reassessment and prospects for the next decade, Hum. Mutat., 35, 672, 10.1002/humu.22552 Pauli, 2017, Personalized in vitro and in vivo cancer models to guide precision medicine, Cancer Discov., 7, 462, 10.1158/2159-8290.CD-16-1154 Chakravarty, 2017, OncoKB: A precision oncology knowledge base, JCO Precis. Oncol., 10.1200/PO.17.00011 Schram, 2017, Quantifying the benefits of genome-driven oncology, Cancer Discov., 7, 552, 10.1158/2159-8290.CD-17-0380 Chae, 2017, Path toward precision oncology: review of targeted therapy studies and tools to aid in defining ‘actionability’ of a molecular lesion and patient management support, Mol. Cancer Ther., 16, 2645, 10.1158/1535-7163.MCT-17-0597 Meric-Bernstam, 2015, Feasibility of large-scale genomic testing to facilitate enrollment onto genomically matched clinical trials, J. Clin. Oncol., 33, 2753, 10.1200/JCO.2014.60.4165 Pezo, 2018, Impact of multi-gene mutational profiling on clinical trial outcomes in metastatic breast cancer, Breast Cancer Res. Treat., 168, 159, 10.1007/s10549-017-4580-2 Biankin, 2015, Patient-centric trials for therapeutic development in precision oncology, Nature, 526, 361, 10.1038/nature15819 Kumar-Sinha, 2018, Precision oncology in the age of integrative genomics, Nat. Biotechnol., 36, 46, 10.1038/nbt.4017 Hyman, 2017, Implementing genome-driven oncology, Cell, 168, 584, 10.1016/j.cell.2016.12.015 Wright, 1984, Cancer chemotherapy: past, present, and future–Part I, J. Natl. Med. Assoc., 76, 773 Wright, 1984, Cancer chemotherapy: past, present, and future–Part II, J. Natl. Med. Assoc., 76, 865 Drost, 2018, Organoids in cancer research, Nat. Rev. Cancer, 18, 407, 10.1038/s41568-018-0007-6 Pemovska, 2013, Individualized systems medicine strategy to tailor treatments for patients with chemorefractory acute myeloid leukemia, Cancer Discov., 3, 1416, 10.1158/2159-8290.CD-13-0350 Friedman, 2015, Precision medicine for cancer with next-generation functional diagnostics, Nat. Rev. Cancer, 15, 747, 10.1038/nrc4015 Maheswaran, 2015, Ex vivo culture of CTCs: an emerging resource to guide cancer therapy, Cancer Res., 75, 2411, 10.1158/0008-5472.CAN-15-0145 Baker, 2016, Modeling pancreatic cancer with organoids, Trends Cancer, 2, 176, 10.1016/j.trecan.2016.03.004 Vlachogiannis, 2018, Patient-derived organoids model treatment response of metastatic gastrointestinal cancers, Science, 359, 920, 10.1126/science.aao2774 van de Wetering, 2015, Prospective derivation of a living organoid biobank of colorectal cancer patients, Cell, 161, 933, 10.1016/j.cell.2015.03.053 Sachs, 2018, A living biobank of breast cancer organoids captures disease heterogeneity, Cell, 172, 10.1016/j.cell.2017.11.010 Ince, 2015, Characterization of twenty-five ovarian tumour cell lines that phenocopy primary tumours, Nat. Commun., 6, 10.1038/ncomms8419 Broutier, 2017, Human primary liver cancer-derived organoid cultures for disease modeling and drug screening, Nat. Med., 23, 1424, 10.1038/nm.4438 Lee, 2018, Tumor evolution and drug response in patient-derived organoid models of bladder cancer, Cell, 173, 10.1016/j.cell.2018.03.017 Echeverri, 2006, High-throughput RNAi screening in cultured cells: a user’s guide, Nat. Rev. Genet., 7, 373, 10.1038/nrg1836 Xu, 2018, Functional precision medicine identifies novel druggable targets and therapeutic options in head and neck cancer, Clin. Cancer Res., 24, 2828, 10.1158/1078-0432.CCR-17-1339 Kurtz, 2017, Molecularly targeted drug combinations demonstrate selective effectiveness for myeloid- and lymphoid-derived hematologic malignancies, Proc. Natl. Acad. Sci. U. S. A., 114, E7554, 10.1073/pnas.1703094114 Chia, 2017, Phenotype-driven precision oncology as a guide for clinical decisions one patient at a time, Nat. Commun., 8, 10.1038/s41467-017-00451-5 Puca, 2018, Patient derived organoids to model rare prostate cancer phenotypes, Nat. Commun., 9, 10.1038/s41467-018-04495-z Santos, 2017, A comprehensive map of molecular drug targets, Nat. Rev. Drug Discov., 16, 19, 10.1038/nrd.2016.230 Yaffe, 2013, The scientific drunk and the lamppost: massive sequencing efforts in cancer discovery and treatment, Sci. Signal., 6, 10.1126/scisignal.2003684 Dobbelstein, 2014, Targeting tumour-supportive cellular machineries in anticancer drug development, Nat. Rev. Drug Discov., 13, 179, 10.1038/nrd4201 Byrd, 2014, Ibrutinib versus ofatumumab in previously treated chronic lymphoid leukemia, N. Engl. J. Med., 371, 213, 10.1056/NEJMoa1400376 Lord, 2017, PARP inhibitors: Synthetic lethality in the clinic, Science, 355, 1152, 10.1126/science.aam7344 Ison, 2018, FDA approval summary: Niraparib for the maintenance treatment of patients with recurrent ovarian cancer in response to platinum-based chemotherapy, Clin. Cancer Res., 10.1158/1078-0432.CCR-18-0042 Knijnenburg, 2018, Genomic and molecular landscape of DNA damage repair deficiency across The Cancer Genome Atlas, Cell Rep., 23, 10.1016/j.celrep.2018.03.076 Cancer Target, 2016, Transforming big data into cancer-relevant insight: an initial, multi-tier approach to assess reproducibility and relevance, Mol. Cancer Res., 14, 675, 10.1158/1541-7786.MCR-16-0090 Iorns, 2007, Utilizing RNA interference to enhance cancer drug discovery, Nat. Rev. Drug Discov., 6, 556, 10.1038/nrd2355 Boehm, 2011, Towards systematic functional characterization of cancer genomes, Nat. Rev. Genet., 12, 487, 10.1038/nrg3013 Scott, 2018, How CRISPR is transforming drug discovery, Nature, 555, S10, 10.1038/d41586-018-02477-1 Ratan, 2018, CRISPR-Cas9: a promising genetic engineering approach in cancer research, Ther. Adv. Med. Oncol., 10, 10.1177/1758834018755089 Cermelli, 2014, Synthetic lethal screens as a means to understand and treat MYC-driven cancers, Cold Spring Harb. Perspect. Med., 4, 10.1101/cshperspect.a014209 Collins, 2006, A small interfering RNA screen for modulators of tumor cell motility identifies MAP4K4 as a promigratory kinase, Proc. Natl. Acad. Sci. U. S. A., 103, 3775, 10.1073/pnas.0600040103 Toyoshima, 2012, Functional genomics identifies therapeutic targets for MYC-driven cancer, Proc. Natl. Acad. Sci. U. S. A., 109, 9545, 10.1073/pnas.1121119109 Conrad, 2013, FAM129B is a novel regulator of Wnt/beta-catenin signal transduction in melanoma cells, F1000Research, 2, 134, 10.12688/f1000research.2-134.v2 Grandori, 2012, A high throughput siRNA screening platform to identify MYC synthetic lethal genes as candidate therapeutic targets, Methods Mol. Biol., 1012, 187, 10.1007/978-1-62703-429-6_12 Moser, 2014, Functional kinomics identifies candidate therapeutic targets in head and neck cancer, Clin. Cancer Res., 20, 4274, 10.1158/1078-0432.CCR-13-2858 Kessler, 2012, A SUMOylation-dependent transcriptional subprogram is required for Myc-driven tumorigenesis, Science, 335, 348, 10.1126/science.1212728 Liu, 2012, Deregulated MYC expression induces dependence upon AMPK-related kinase 5, Nature, 483, 608, 10.1038/nature10927 Campbell, 2016, Large-scale profiling of kinase dependencies in cancer cell lines, Cell Rep., 14, 2490, 10.1016/j.celrep.2016.02.023 Picco, 2017, A road map for precision cancer medicine using personalized models, Cancer Discov., 7, 456, 10.1158/2159-8290.CD-17-0268 Siegel, 2018, Cancer statistics, 2018, CA Cancer J. Clin., 68, 7, 10.3322/caac.21442 Aarts, 2012, Forced mitotic entry of S-phase cells as a therapeutic strategy induced by inhibition of WEE1, Cancer Discov., 2, 524, 10.1158/2159-8290.CD-11-0320 Hirai, 2009, Small-molecule inhibition of Wee1 kinase by MK-1775 selectively sensitizes p53-deficient tumor cells to DNA-damaging agents, Mol. Cancer Ther., 8, 2992, 10.1158/1535-7163.MCT-09-0463 Mendez, 2018, A Phase I clinical trial of AZD1775 in combination with neoadjuvant weekly docetaxel and cisplatin before definitive therapy in head and neck squamous cell carcinoma, Clin. Cancer Res., 24, 2740, 10.1158/1078-0432.CCR-17-3796