Page 172 - Read Online
P. 172

Page 536                                              Belizario et al. Cancer Drug Resist 2019;2:527-38  I  http://dx.doi.org/10.20517/cdr.2018.009

               DECLARATIONS
               Acknowledgments
               Maria Mitzi Brentani, Fiorita Mundim, Alda Wakamatsu, Venancio AF Alves (University of São Paulo
               School of Medicine Medicine) and Dr Victor Piana Andrade e Fernando Soares (AC Carmargo Cancer
               Center) for their help and fruitful discussions.


               Author’s contribution
               Study conception: Belizario JE, Loggulo AF
               Selection and critical review of the papers and manuscript preparation: Belizario JE, Loggulo AF
               Read and approved the final manuscript: Belizario JE, Loggulo AF


               Availability of data and materials
               Not applicable.


               Financial support and sponsorship
               JEB is supported by fellowship from “Conselho Nacional de Desenvolvimento Científico e Tecnológico”
               (CNPq proc 486048/2011; 312206/2016-0).


               Conflicts of interest
               Both authors declared that there are no conflicts of interest.


               Ethical approval and consent to participate
               Not applicable.


               Consent for publication
               Not applicable.


               Copyright
               © The Author(s) 2019.



               REFERENCES
               1.   Belizario JE. Cancer risks linked to the bad luck hypothesis and epigenomic mutational signatures. Epigenomes 2018;2:13.
               2.   Lawrence MS, Stojanov P, Mermel CH, Robinson JT, Garraway LA et al. Discovery and saturation analysis of cancer genes across 21
                   tumour types. Nature 2014;505:495-501.
               3.   Vasaikar SV, Straub P, Wang J, Zhang B. LinkedOmics: analyzing multi-omics data within and across 32 cancer types. Nucleic Acids
                   Res 2018;46:D956-63.
               4.   Kim YA, Cho DY, Przytycka TM. Understanding genotype - phenotype effects in cancer via network approaches. PLoS Comput Biol
                   2016;12:e1004747.
               5.   Barretina J, Caponigro G, Stransky N, Venkatesan K, Margolin AA, et al. The Cancer Cell Line Encyclopedia enables predictive
                   modeling of anticancer drug sensitivity. Nature 2012;483:603-7.
               6.   Garnett MJ, Edelman J, Heidorn SJ, Greenman CD, Dastur A, et al. Systematic identification of genomic markers of drug sensitivity
                   in cancer cells. Nature 2012;483:570-5.
               7.   Klijn C, Durinck S, Stawiski EW, Haverty PM, Jiang Z, et al. A comprehensive transcriptional portrait of human cancer cell lines. Nat
                   Biotechnol 2015;33:306-12.
               8.   Campbell J, Ryan CJ, Brough R, Bajrami I, Pemberton HN, et al. Large-scale profiling of kinase dependencies in cancer cell lines.
                   Cell Rep 2016;15:14:2490-501.
               9.   Polyak K, Haviv I, Campbell IG. Co-evolution of tumor cells and their microenvironment. Trends Genet 2008;25:30-8.
               10.   McGranahan N, Swanton C. Biological and therapeutic impact of intratumor heterogeneity in cancer evolution. Cancer Cell
                   2015;27:15-26.
               11.   Belizario JE, Sangiuliano BA, Perez-Sosa M, Neyra JM, Moreira DF. Using pharmacogenomic databases for discovering patient-
                   target genes and small molecule candidates to cancer therapy. Front Pharmacol 2016;7:312.
               12.   Feinberg AP, Koldobskiy MA, Göndör A. Epigenetic modulators, modifiers and mediators in cancer aetiology and progression. Nat
   167   168   169   170   171   172   173   174   175   176   177