A new approach to assess drug sensitivity in cells for novel drug discovery

References

• Scannell JW, Blanckley A, Boldon H, et al. Diagnosing the decline in pharmaceutical R&D efficiency. Nat Rev Drug Discov. 2012;11:191–200.
   PubMed Web of Science ®Google Scholar
• Moffat JG, Rudolph J, Bailey D. Phenotypic screening in cancer drug discovery: past, present and future. Nat Rev Drug Discov. 2014;13:588–602.
   PubMed Web of Science ®Google Scholar
• Scherer WF, Syverton JT, Gey GO. Studies on the propagation in vitro of poliomyelitis viruses. IV. Viral multiplication in a stable strain of human malignant epithelial cells (strain HeLa) derived from an epidermoid carcinoma of the cervix. J Exp Med. 1953;97:695–710.
   PubMed Web of Science ®Google Scholar
• Pampaloni F, Reynaud EG, Stelzer EHK. The third dimension bridges the gap between cell culture and live tissue. Nat Rev Mol Cell Biol. 2007;8:839–845.
   PubMed Web of Science ®Google Scholar
• Horvath P, Aulner N, Bickle M, et al. Screening out irrelevant cell-based models of disease. Nat Rev Drug Discov. 2016;15:751–769.
   PubMed Web of Science ®Google Scholar
• Shoemaker RH. The NCI60 human tumour cell line anticancer drug screen. Nat Rev Cancer. 2006;6:813–823.
   PubMed Web of Science ®Google Scholar
• Alley MC, Scudiero DA, Monks A, et al. Feasibility of drug screening with panels of human tumor cell lines using a microculture tetrazolium assay. Cancer Res. 1988;48:589–601.
   PubMed Web of Science ®Google Scholar
• McDermott U, Iafrate AJ, Gray NS, et al. Genomic alterations of anaplastic lymphoma kinase may sensitize tumors to anaplastic lymphoma kinase inhibitors. Cancer Res. 2008;68:3389LP–3395.
   Web of Science ®Google Scholar
• Tsai J, Lee JT, Wang W, et al. Discovery of a selective inhibitor of oncogenic B-Raf kinase with potent antimelanoma activity. Proc Natl Acad Sci. 2008;105:3041–3046.
   PubMed Web of Science ®Google Scholar
• Barretina J, Caponigro G, Stransky N, et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature. 2012;483:603–607.
   PubMed Web of Science ®Google Scholar
• Garnett MJ, Edelman EJ, Heidorn SJ, et al. Systematic identification of genomic markers of drug sensitivity in cancer cells. Nature. 2012;483:570–575.
   PubMed Web of Science ®Google Scholar
• Yang W, Soares J, Greninger P, et al. Genomics of drug sensitivity in cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells. Nucleic Acids Res. 2013;41:D955–D961.
   PubMed Web of Science ®Google Scholar
• Iorio F, Knijnenburg TA, Vis DJ, et al. A landscape of pharmacogenomic interactions in cancer. Cell. 2016;166:740–754.
   PubMed Web of Science ®Google Scholar
• Haverty PM, Lin E, Tan J, et al. Reproducible pharmacogenomic profiling of cancer cell line panels. Nature. 2016;533:333–337.
   PubMed Web of Science ®Google Scholar
• Zhang N, Wang H, Fang Y, et al. Predicting anticancer drug responses using a dual-layer integrated cell line-drug network model. PLoS Comput Biol. 2015;11:1–18.
   Web of Science ®Google Scholar
• Ammad-Ud-Din M, Georgii E, Gonen M, et al. Integrative and personalized QSAR analysis in cancer by kernelized Bayesian matrix factorization. J Chem Inf Model. 2014;54:2347–2359.
   PubMed Web of Science ®Google Scholar
• Menden MP, Iorio F, Garnett M, et al. Machine learning prediction of cancer cell sensitivity to drugs based on genomic and chemical properties. PLoS One. 2013;8:e61318.
   PubMed Web of Science ®Google Scholar
• Vidyasagar M. Identifying predictive features in drug response using machine learning: opportunities and challenges. Annu Rev Pharmacol Toxicol. 2015;55:15–34.
   PubMed Web of Science ®Google Scholar
• Geeleher P, Cox NJ, Huang RS. Clinical drug response can be predicted using baseline gene expression levels and in vitrodrug sensitivity in cell lines. Genome Biol. 2014;15:R47.
   PubMed Web of Science ®Google Scholar
• Falgreen S, Dybkær K, Young KH, et al. Predicting response to multidrug regimens in cancer patients using cell line experiments and regularised regression models. BMC Cancer. 2015;15:235.
   PubMed Web of Science ®Google Scholar
• Mpindi JP, Yadav B, Östling P, et al. Consistency in drug response profiling. Nature. 2016;540:E5–E6.
   PubMed Web of Science ®Google Scholar
• Yadav B, Pemovska T, Szwajda A, et al. Quantitative scoring of differential drug sensitivity for individually optimized anticancer therapies. Sci Rep. 2014;4:5193.
   PubMed Web of Science ®Google Scholar
• Greshock J, Bachman KE, Degenhardt YY, et al. Molecular target class is predictive of in vitro response profile. Cancer Res. 2010;70:3677–3687.
   PubMed Web of Science ®Google Scholar
• Seashore-Ludlow B, Rees MG, Cheah JH, et al. Harnessing connectivity in a large-scale small-molecule sensitivity dataset. Cancer Discov. 2015;5:1210LP–1223.
   Web of Science ®Google Scholar
• Haibe-Kains B, El-Hachem N, Birkbak NJ, et al. Inconsistency in large pharmacogenomic studies. Nature. 2013;504:389–393.
   PubMed Web of Science ®Google Scholar
• Cancer Cell Line Encyclopedia Consortium T, Genomics of Drug Sensitivity in Cancer Consortium T. Pharmacogenomic agreement between two cancer cell line data sets. Nature. 2015; 528:84–87.
   PubMed Web of Science ®Google Scholar
• He Y, Zhu Q, Chen M, et al. The changing 50% inhibitory concentration (IC(50)) of cisplatin: a pilot study on the artifacts of the MTT assay and the precise measurement of density-dependent chemoresistance in ovarian cancer. Oncotarget. 2016;7:70803–70821.
   PubMedGoogle Scholar
• Montero J, Sarosiek KA, DeAngelo JD, et al. Drug-induced death signaling strategy rapidly predicts cancer response to chemotherapy. Cell. 2015;160:977–989.
   PubMed Web of Science ®Google Scholar
• Williams SP, McDermott U. The pursuit of therapeutic biomarkers with high-throughput cancer cell drug screens. Cell Chem Biol. 2017;24(9):1066–1074.
   PubMed Web of Science ®Google Scholar
• Harris LA, Frick PL, Garbett SP, et al. An unbiased metric of antiproliferative drug effect in vitro. Nat Meth. 2016;13:497–500.
   PubMed Web of Science ®Google Scholar
• Hafner M, Niepel M, Chung M, et al. Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs. Nat Meth. 2016;13:521–527.
   PubMed Web of Science ®Google Scholar
• Popovici-Muller J, Saunders JO, Salituro FG, et al. Discovery of the first potent inhibitors of mutant IDH1 that lower tumor 2-HG in vivo. ACS Med Chem Lett. 2012;3:850–855.
   PubMed Web of Science ®Google Scholar
• Daigle SR, Olhava EJ, Therkelsen CA, et al. Selective killing of mixed lineage leukemia cells by a potent small-molecule DOT1L inhibitor. Cancer Cell. 2011;20:53–65.
   PubMed Web of Science ®Google Scholar
• Mohammad HP, Smitheman KN, Kamat CD, et al. A DNA hypomethylation signature predicts antitumor activity of LSD1 inhibitors in SCLC. Cancer Cell. 2015;28:57–69.
   PubMed Web of Science ®Google Scholar
• Chomienne C, Ballerini P, Balitrand N, et al. All-trans retinoic acid in acute promyelocytic leukemias. II. In vitro studies: structure-function relationship. Blood. 1990;76:1710–1717.
   PubMed Web of Science ®Google Scholar
• Lacroix M, Leclercq G. Relevance of breast cancer cell lines as models for breast tumours: an update. Breast Cancer Res Treat. 2004;83:249–289.
   PubMed Web of Science ®Google Scholar
• Sachs N, Clevers H. Organoid cultures for the analysis of cancer phenotypes. Curr Opin Genet Dev. 2014;24:68–73.
   PubMed Web of Science ®Google Scholar
• Liu X, Ory V, Chapman S, et al. ROCK inhibitor and feeder cells induce the conditional reprogramming of epithelial cells. Am J Pathol. 2012;180:599–607.
   PubMed Web of Science ®Google Scholar
• Nestor CE, Ottaviano R, Reinhardt D, et al. Rapid reprogramming of epigenetic and transcriptional profiles in mammalian culture systems. Genome Biol. 2015;16:11.
   PubMed Web of Science ®Google Scholar
• Nestor CE, Ottaviano R, Reddington J, et al. Tissue type is a major modifier of the 5-hydroxymethylcytosine content of human genes. Genome Res. 2012;22:467–477.
   PubMed Web of Science ®Google Scholar
• Merkle FT, Ghosh S, Kamitaki N, et al. Human pluripotent stem cells recurrently acquire and expand dominant negative P53 mutations. Nature. 2017;545:229–233.
   PubMed Web of Science ®Google Scholar
• Esquenet M, Swinnen JV, Heyns W, et al. LNCaP prostatic adenocarcinoma cells derived from low and high passage numbers display divergent responses not only to androgens but also to retinoids. J Steroid Biochem Mol Biol. 1997;62:391–399.
   PubMed Web of Science ®Google Scholar
• Briske-Anderson MJ, Finley JW, Newman SM. The influence of culture time and passage number on the morphological and physiological development of Caco-2 cells. Proc Soc Exp Biol Med. 1997;214:248–257.
   PubMed Web of Science ®Google Scholar
• Yu H, Cook TJ, Sinko PJ. Evidence for diminished functional expression of intestinal transporters in Caco-2 cell monolayers at high passages. Pharm Res. 1997;14:757–762.
   PubMed Web of Science ®Google Scholar
• Chang-Liu CM, Woloschak GE. Effect of passage number on cellular response to DNA-damaging agents: cell survival and gene expression. Cancer Lett. 1997;113:77–86.
   PubMed Web of Science ®Google Scholar
• Wenger SL, Senft JR, Sargent LM, et al. Comparison of established cell lines at different passages by karyotype and comparative genomic hybridization. Biosci Rep. 2004;24:631–639.
   PubMed Web of Science ®Google Scholar
• Ben-David U, Ha G, Tseng -Y-Y, et al. Patient-derived xenografts undergo mouse-specific tumor evolution. Nat Genet. 2017;49:1567–1575.
   PubMed Web of Science ®Google Scholar
• ATCC. ATCC’s use of passage number and population doubling level (PDL) [Internet]. ATCC FAQ. 2012. Available from: https://www.lgcstandards-atcc.org/Global/FAQs/2/F/ATCCs use of passage number and population doubling level PDL-110.aspx?geo_country=it.
   Google Scholar
• Miller TE, Liau BB, Wallace LC, et al. Transcription elongation factors represent in vivo cancer dependencies in glioblastoma. Nature. 2017;547:355–359.
   PubMed Web of Science ®Google Scholar
• Birsoy K, Possemato R, Lorbeer FK, et al. Metabolic determinants of cancer cell sensitivity to glucose limitation and biguanides. Nature. 2014;508:108–112.
   PubMed Web of Science ®Google Scholar
• Tardito S, Oudin A, Ahmed SU, et al. Glutamine synthetase activity fuels nucleotide biosynthesis and supports growth of glutamine-restricted glioblastoma. Nat Cell Biol. 2015;17:1556–1568.
   PubMed Web of Science ®Google Scholar
• Palm W, Thompson CB. Review nutrient acquisition strategies of mammalian cells. Nat Publ Gr. 2017;546:234–242.
   Google Scholar
• McMurtrey RJ. Roles of diffusion dynamics in stem cell signaling and three-dimensional tissue development. Stem Cells Dev. 2017;26(18):1293–1303.
   PubMed Web of Science ®Google Scholar
• Ito K, Suda T. Metabolic requirements for the maintenance of self-renewing stem cells. Nat Rev Mol Cell Biol. 2014;15:243–256.
   PubMed Web of Science ®Google Scholar
• Sancho P, Barneda D, Heeschen C. Hallmarks of cancer stem cell metabolism. Br J Cancer. 2016;114(12):1305–1312. Cancer Research, UK.
   PubMed Web of Science ®Google Scholar
• De Angelis ML, Zeuner A, Policicchio E, et al. Cancer stem cell-based models of colorectal cancer reveal molecular determinants of therapy resistance. Stem Cells Transl Med. 2016;5:511–523.
   PubMed Web of Science ®Google Scholar
• Charafe-Jauffret E, Ginestier C, Iovino F, et al. Breast cancer cell lines contain functional cancer stem cells with metastatic capacity and a distinct molecular signature. Cancer Res. 2009;69:1302LP–1313.
   Web of Science ®Google Scholar
• Petersen OW, Ronnov-Jessen L, Howlett AR, et al. Interaction with basement membrane serves to rapidly distinguish growth and differentiation pattern of normal and malignant human breast epithelial cells. Proc Natl Acad Sci U S A. 1992;89:9064–9068.
   PubMed Web of Science ®Google Scholar
• Weaver VM, Petersen OW, Wang F, et al. Reversion of the malignant phenotype of human breast cells in three-dimensional culture and in vivo by integrin blocking antibodies. J Cell Biol. 1997;137:231–245.
   PubMed Web of Science ®Google Scholar
• Paszek MJ, Zahir N, Johnson KR, et al. Tensional homeostasis and the malignant phenotype. Cancer Cell. 2005;8:241–254.
   PubMed Web of Science ®Google Scholar
• Ghosh S, Spagnoli GC, Martin I, et al. Three-dimensional culture of melanoma cells profoundly affects gene expression profile: a high density oligonucleotide array study. J Cell Physiol. 2005;204:522–531.
   PubMed Web of Science ®Google Scholar
• Kenny PA, Lee GY, Myers CA, et al. The morphologies of breast cancer cell lines in three-dimensional assays correlate with their profiles of gene expression. Mol Oncol. 2007;1:84–96.
   PubMed Web of Science ®Google Scholar
• Gomez-Roman N, Stevenson K, Gilmour L, et al. A novel 3D human glioblastoma cell culture system for modeling drug and radiation responses. Neuro Oncol. 2017;19:229–241.
   PubMed Web of Science ®Google Scholar
• Jiang L, Shestov AA, Swain P, et al. Reductive carboxylation supports redox homeostasis during anchorage-independent growth. Nature. 2016;532:255–258.
   PubMed Web of Science ®Google Scholar
• Cox MC, Reese LM, Bickford LR, et al. Toward the broad adoption of 3D tumor models in the cancer drug pipeline. ACS Biomater Sci Eng. 2015;1:877–894.
   PubMed Web of Science ®Google Scholar
• Clark AK, Taubenberger AV, Taylor RA, et al. A bioengineered microenvironment to quantitatively measure the tumorigenic properties of cancer-associated fibroblasts in human prostate cancer. Biomaterials. 2013;34:4777–4785.
   PubMed Web of Science ®Google Scholar
• Vaira V, Fedele G, Pyne S, et al. Preclinical model of organotypic culture for pharmacodynamic profiling of human tumors. Proc Natl Acad Sci U S A. 2010;107:8352–8356.
   PubMed Web of Science ®Google Scholar
• Majumder B, Baraneedharan U, Thiyagarajan S, et al. Predicting clinical response to anticancer drugs using an ex vivo platform that captures tumour heterogeneity. Nat Commun. 2015;6:6169.
   PubMed Web of Science ®Google Scholar
• Anastasov N, Hofig I, Radulovic V, et al. A 3D-microtissue-based phenotypic screening of radiation resistant tumor cells with synchronized chemotherapeutic treatment. BMC Cancer. 2015;15:466.
   PubMed Web of Science ®Google Scholar
• Krausz E, De Hoogt R, Gustin E, et al. Translation of a tumor microenvironment mimicking 3D tumor growth co-culture assay platform to high-content screening. J Biomol Screen. 2013;18:54–66.
   PubMed Web of Science ®Google Scholar
• Sato T, Vries RG, Snippert HJ, et al. Single Lgr5 stem cells build crypt-villus structures in vitro without a mesenchymal niche. Nature. 2009;459:262–265.
   PubMed Web of Science ®Google Scholar
• Fatehullah A, Tan SH, Barker N. Organoids as an in vitro model of human development and disease. Nat Cell Biol. 2016;18:246–254.
   PubMed Web of Science ®Google Scholar
• Simian M, Bissell MJ. Organoids: a historical perspective of thinking in three dimensions. J Cell Biol. 2017;262(81):31–40.
   Google Scholar
• van de Wetering M, Francies HE, Francis JM, et al. Prospective derivation of a living organoid biobank of colorectal cancer patients. Cell. 2015;161:933–945.
   PubMed Web of Science ®Google Scholar
• Sato T, Stange DE, Ferrante M, et al. Long-term expansion of epithelial organoids from human colon, adenoma, adenocarcinoma, and Barrett’s epithelium. Gastroenterology. 2011;141:1762–1772.
   PubMed Web of Science ®Google Scholar
• Boj SF, Hwang C-I, Baker LA, et al. Organoid models of human and mouse ductal pancreatic cancer. Cell. 2017;160:324–338.
   Web of Science ®Google Scholar
• Karthaus WR, Iaquinta PJ, Drost J, et al. Identification of multipotent luminal progenitor cells in human prostate organoid cultures. Cell. 2017;159:163–175.
   Google Scholar
• Gao D, Vela I, Sboner A, et al. Organoid cultures derived from patients with advanced prostate cancer. Cell. 2017;159:176–187.
   Google Scholar
• Weeber F, Ooft SN, Dijkstra KK, et al. Tumor organoids as a pre-clinical cancer model for drug discovery. Cell Chem Biol. 2017;24(9):1092-1100.
   PubMed Web of Science ®Google Scholar
• Schütte M, Risch T, Abdavi-Azar N, et al. Molecular dissection of colorectal cancer in pre-clinical models identifies biomarkers predicting sensitivity to EGFR inhibitors. Nat Commun. 2017;8:14262.
   PubMed Web of Science ®Google Scholar
• Pauli C, Hopkins BD, Prandi D, et al. Personalized in vitro and in vivo cancer models to guide precision medicine. Cancer Discov. 2017;7(5):462–477.
   PubMed Web of Science ®Google Scholar
• Pece S, Tosoni D, Confalonieri S, et al. Biological and molecular heterogeneity of breast cancers correlates with their cancer stem cell content. Cell. 2010;140:62–73.
   PubMed Web of Science ®Google Scholar
• Dontu G, Abdallah WM, Foley JM, et al. In vitro propagation and transcriptional profiling of human mammary stem/progenitor cells. Genes Dev. 2003;17:1253–1270.
   PubMed Web of Science ®Google Scholar
• Weeber F, Van De Wetering M, Hoogstraat M, et al. Preserved genetic diversity in organoids cultured from biopsies of human colorectal cancer metastases. Proc Natl Acad Sci. 2015;112:13308–13311.
   PubMed Web of Science ®Google Scholar
• Li X, Nadauld L, Ootani A, et al. Oncogenic transformation of diverse gastrointestinal tissues in primary organoid culture. Nat Med. 2014;20:769–777.
   PubMed Web of Science ®Google Scholar
• Mehta P, Novak C, Raghavan S, et al. Self-renewal and CSCs in vitro enrichment: growth as floating spheres. Methods Mol Biol. 2018;1692:61–75.
   PubMedGoogle Scholar
• Van Duinen V, Trietsch SJ, Joore J, et al. Microfluidic 3D cell culture: from tools to tissue models. Curr Opin Biotechnol. 2015;35:118–126.
   PubMed Web of Science ®Google Scholar
• Sart S, Tomasi RF-X, Amselem G, et al. Multiscale cytometry and regulation of 3D cell cultures on a chip. Nat Commun. 2017;8:469.
   PubMed Web of Science ®Google Scholar
• Chwalek K, Bray LJ, Werner C. Tissue-engineered 3D tumor angiogenesis models : potential technologies for anti-cancer drug discovery. Adv Drug Deliv Rev. 2014;79–80:30–39.
   PubMed Web of Science ®Google Scholar
• Black M, Barsoum IB, Truesdell P, et al. Activation of the PD-1/PD-L1 immune checkpoint confers tumor cell chemoresistance associated with increased metastasis. Oncotarget. 2016;7:10557–10567.
   PubMedGoogle Scholar
• Patel SJ, Sanjana NE, Kishton RJ, et al. Identification of essential genes for cancer immunotherapy. Nature. 2017;548:537–542.
   PubMed Web of Science ®Google Scholar
• Khandelwal N, Breinig M, Speck T, et al. A high-throughput RNAi screen for detection of immune-checkpoint molecules that mediate tumor resistance to cytotoxic T lymphocytes. EMBO Mol Med. 2015;7:450–463.
   PubMed Web of Science ®Google Scholar
• Hirt C, Papadimitropoulos A, Mele V, et al. “In vitro” 3D models of tumor-immune system interaction. Adv Drug Deliv Rev. 2014;79–80:145–154.
   PubMed Web of Science ®Google Scholar
• Sutherland RM, MacDonald HR, Howell RL. Multicellular spheroids: a new model target for in vitro studies of immunity to solid tumor allografts: brief communication. JNCI J Natl Cancer Inst. 1977;58:1849–1853.
   Web of Science ®Google Scholar
• Sacks PG, Taylor DL, Racz T, et al. A multicellular tumor spheroid model of cellular immunity against head and neck cancer. Cancer Immunol Immunother. 1990;32:195–200.
   PubMed Web of Science ®Google Scholar
• Mahoney KM, Rennert PD, Freeman GJ. Combination cancer immunotherapy and new immunomodulatory targets. Nat Rev Drug Discov. 2015;14:561–584.
   PubMed Web of Science ®Google Scholar
• Fischer K, Hoffmann P, Voelkl S, et al. Inhibitory effect of tumor cell-derived lactic acid on human T cells. Blood. 2007;109:3812–3820.
   PubMed Web of Science ®Google Scholar
• Ghosh S, Rosenthal R, Zajac P, et al. Culture of melanoma cells in 3-dimensional architectures results in impaired immunorecognition by cytotoxic T lymphocytes specific for Melan-A/MART-1 tumor-associated antigen. Ann Surg. 2005;242:851–858.
   PubMed Web of Science ®Google Scholar
• Dangles-Marie V, Richon S, El Behi M, et al. A three-dimensional tumor cell defect in activating autologous CTLs is associated with inefficient antigen presentation correlated with heat shock protein-70 down-regulation. Cancer Res. 2003;63:3682LP–3687.
   Web of Science ®Google Scholar
• Holmes TD, El-Sherbiny YM, Davison A, et al. A human NK cell activation/inhibition threshold allows small changes in the target cell surface phenotype to dramatically alter susceptibility to NK cells. J Immunol. 2011;186:1538LP–1545.
   Web of Science ®Google Scholar
• Giannattasio A, Weil S, Kloess S, et al. Cytotoxicity and infiltration of human NK cells in in vivo-like tumor spheroids. BMC Cancer. 2015;15:351.
   PubMed Web of Science ®Google Scholar
• Dietl K, Renner K, Dettmer K, et al. Lactic acid and acidification inhibit TNF secretion and glycolysis of human monocytes. J Immunol. 2010;184:1200–1209.
   PubMed Web of Science ®Google Scholar
• Hauptmann S, Zwadlo-Klarwasser G, Jansen M, et al. Macrophages and multicellular tumor spheroids in co-culture: a three-dimensional model to study tumor-host interactions. Evidence for macrophage-mediated tumor cell proliferation and migration. Am J Pathol. 1993;143:1406–1415.
   PubMed Web of Science ®Google Scholar
• Gottfried E, Kunz-Schughart LA, Ebner S, et al. Tumor-derived lactic acid modulates dendritic cell activation and antigen expression. Blood. 2006;107:2013–2022.
   PubMed Web of Science ®Google Scholar
• Mina M, Raynaud F, Tavernari D, et al. Conditional selection of genomic alterations dictates cancer evolution and oncogenic dependencies. Cancer Cell. 2017;32:155–168.e6.
   PubMed Web of Science ®Google Scholar
• Chio IIC, Jafarnejad SM, Ponz-Sarvise M, et al. NRF2 promotes tumor maintenance by modulating mRNA translation in pancreatic cancer. Cell. 2017;166:963–976.
   Web of Science ®Google Scholar
• Feng Y, LoGrasso PV, Defert O, et al. Rho kinase (ROCK) inhibitors and their therapeutic potential. J Med Chem. 2016;59:2269–2300.
   PubMed Web of Science ®Google Scholar