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Leveraging Human Genetics to Guide Cancer Drug Development

Leveraging Human Genetics to Guide Cancer Drug Development Purpose: The high attrition rate of cancer drug development programs is a barrier to realizing the promise of precision oncology. We have examined whether the genetic insights from genome-wide association studies of cancer can guide drug development and repurposing in oncology. Materials and Methods: Across 37 cancers, we identified 955 genetic risk variants from the National Human Genome Research Institute-European Bioinformatics Institute genome-wide association study catalog. We linked these variants to target genes using strategies that were based on linkage disequilibrium, DNA three-dimensional structure, and integration of predicted gene function and expression. With the use of the Informa Pharmaprojects database, we identified genes that are targets of unique drugs and assessed the level of enrichment that would be afforded by incorporation of genetic information in preclinical and phase II studies. For targets not under development, we implemented machine learning approaches to assess druggability. Results: For all preclinical targets incorporating genetic information, a 2.00-fold enrichment of a drug being successfully approved could be achieved (95% CI, 1.14- to 3.48-fold; P = .02). For phase II targets, a 2.75-fold enrichment could be achieved (95% CI, 1.42- to 5.35-fold; P < .001). Application of genetic information suggests potential repurposing of 15 approved nononcology drugs. Conclusion: The findings illustrate the value of using insights from the genetics of inherited cancer susceptibility discovery projects as part of a data-driven strategy to inform drug discovery. Support for cancer germline genetic information for prospective targets is available online from the Institute of Cancer Research. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JCO Clinical Cancer Informatics Wolters Kluwer Health

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  • K. Michailidou, S. Lindström, J. Dennis, J. Beesley, Shirley Hui, S. Kar, Audrey Lemaçon, P. Soucy, Dylan Glubb, Asha Rostamianfar, M. Bolla, Qin Wang, J. Tyrer, E. Dicks, Andrew Lee, Zhaoming Wang, Jamie Allen, R. Keeman, U. Eilber, J. French, Xiao Chen, L. Fachal, K. McCue, A. Reed, M. Ghoussaini, J. Carroll, Xia Jiang, H. Finucane, Marcia Adams, M. Adank, H. Ahsan, K. Aittomäki, H. Anton-Culver, N. Antonenkova, V. Arndt, K. Aronson, B. Arun, P. Auer, F. Bacot, Myrto Barrdahl, C. Baynes, M. Beckmann, S. Behrens, J. Benítez, M. Bermisheva, L. Bernstein, C. Blomqvist, N. Bogdanova, S. Bojesen, B. Bonanni, A. Børresen-Dale, Judith Brand, H. Brauch, P. Brennan, H. Brenner, L. Brinton, P. Broberg, I. Brock, A. Broeks, A. Brooks-Wilson, S. Brucker, T. Brüning, B. Burwinkel, Katja Butterbach, Q. Cai, H. Cai, T. Caldés, F. Canzian, Á. Carracedo, B. Carter, J. Castelao, T. Chan, T. Cheng, K. Chia, Ji-Yeob Choi, H. Christiansen, C. Clarke, Margriet Collee, Don Conroy, E. Cordina-Duverger, S. Cornelissen, D. Cox, A. Cox, S. Cross, J. Cunningham, K. Czene, M. Daly, P. Devilee, K. Doheny, T. Dörk, I. dos-Santos-Silva, M. Dumont, L. Durcan, M. Dwek, D. Eccles, A. Ekici, A. Eliassen, Carolina Ellberg, Mingajeva Elvira, C. Engel, M. Eriksson, P. Fasching, J. Figueroa, D. Flesch-Janys, O. Fletcher, H. Flyger, L. Fritschi, V. Gaborieau, M. Gabrielson, M. Gago-Domínguez, Yu-Tang Gao, S. Gapstur, J. García-Saenz, M. Gaudet, V. Georgoulias, G. Giles, G. Glendon, M. Goldberg, D. Goldgar, A. González-Neira, Grethe Alnæs, Mervi Grip, J. Gronwald, Anne Grundy, P. Guénel, L. Haeberle, E. Hahnen, C. Haiman, N. Håkansson, U. Hamann, Nathalie Hamel, S. Hankinson, P. Harrington, S. Hart, J. Hartikainen, M. Hartman, A. Hein, J. Heyworth, B. Hicks, P. Hillemanns, Dona Ho, A. Hollestelle, M. Hooning, R. Hoover, J. Hopper, M. Hou, Chia-Ni Hsiung, Guanmengqian Huang, K. Humphreys, J. Ishiguro, Hidemi Ito, M. Iwasaki, H. Iwata, A. Jakubowska, W. Janni, E. John, N. Johnson, K. Jones, Michael Jones, A. Jukkola-Vuorinen, R. Kaaks, M. Kabisch, K. Kaczmarek, D. Kang, Y. Kasuga, M. Kerin, Sofia Khan, E. Khusnutdinova, J. Kiiski, Sung-Won Kim, J. Knight, V. Kosma, V. Kristensen, Ute Krüger, A. Kwong, D. Lambrechts, L. Marchand, Eunjung Lee, M. Lee, Jong Lee, C. Lee, F. Lejbkowicz, Jingmei Li, J. Lilyquist, A. Lindblom, J. Lissowska, W. Lo, S. Loibl, J. Long, A. Lophatananon, J. Lubiński, C. Luccarini, M. Lux, E. Ma, R. MacInnis, T. Maishman, E. Makalic, K. Malone, I. Kostovska, A. Mannermaa, S. Manoukian, J. Manson, S. Margolin, S. Mariapun, M. Martínez, K. Matsuo, D. Mavroudis, J. Mckay, C. Mclean, H. Meijers-Heijboer, A. Meindl, P. Menéndez, U. Menon, Jeffery Meyer, H. Miao, N. Miller, N. Taib, K. Muir, A. Mulligan, C. Mulot, S. Neuhausen, H. Nevanlinna, P. Neven, S. Nielsen, D. Noh, B. Nordestgaard, A. Norman, O. Olopade, J. Olson, H. Olsson, Curtis Olswold, N. Orr, V. Pankratz, Sue-Kyung Park, T. Park-Simon, R. Lloyd, J. Peŕez, P. Peterlongo, J. Peto, K. Phillips, M. Pinchev, D. Plaseska‐Karanfilska, R. Prentice, N. Presneau, D. Prokofieva, E. Pugh, K. Pylkäs, B. Rack, P. Radice, N. Rahman, G. Rennert, H. Rennert, V. Rhenius, A. Romero, Jane Romm, K. Ruddy, T. Rüdiger, A. Rudolph, M. Ruebner, E. Rutgers, E. Saloustros, D. Sandler, S. Sangrajrang, E. Sawyer, D. Schmidt, R. Schmutzler, A. Schneeweiss, M. Schoemaker, F. Schumacher, P. Schürmann, R. Scott, Christopher Scott, S. Seal, C. Seynaeve, M. Shah, P. Sharma, Chen-Yang Shen, Grace Sheng, M. Sherman, M. Shrubsole, X. Shu, A. Smeets, C. Sohn, M. Southey, J. Spinelli, C. Stegmaier, S. Stewart-Brown, J. Stone, D. Stram, H. Surowy, A. Swerdlow, R. Tamimi, Jack Taylor, M. Tengström, S. Teo, M. Terry, D. Tessier, Somchai Thanasitthichai, K. Thöne, R. Tollenaar, I. Tomlinson, L. Tong, Diana Torres, Thérèse Truong, C. Tseng, S. Tsugane, H. Ulmer, G. Ursin, M. Untch, C. Vachon, C. Asperen, D. Berg, A. Ouweland, L. Kolk, R. Luijt, Daniel Vincent, Jason Vollenweider, Q. Waisfisz, S. Wang-gohrke, C. Weinberg, Camilla Wendt, A. Whittemore, H. Wildiers, W. Willett, R. Winqvist, A. Wolk, A. Wu, Lucy Xia, T. Yamaji, Xiaohong Yang, C. Yip, K. Yoo, Jyh‐cherng Yu, W. Zheng, Ying Zheng, B. Zhu, A. Ziogas, E. Ziv, S. Lakhani, A. Antoniou, A. Droit, I. Andrulis, C. Amos, F. Couch, P. Pharoah, J. Chang-Claude, P. Hall, D. Hunter, R. Milne, M. García-Closas, M. Schmidt, S. Chanock, A. Dunning, S. Edwards, Gary Bader, G. Chenevix-Trench, J. Simard, P. Kraft, D. Easton (2017)

    Association analysis identifies 65 new breast cancer risk loci

    Nature, 551

  • C. Finan, A. Gaulton, Felix Kruger, R. Lumbers, T. Shah, J. Engmann, L. Galver, Ryan Kelley, Anneli Karlsson, Rita Santos, John Overington, A. Hingorani, J. Casas (2016)

    The druggable genome and support for target identification and validation in drug development

    Science Translational Medicine, 9

Publisher
Wolters Kluwer Health
Copyright
(C) 2018 by Lippincott Williams & Wilkins, Inc.
ISSN
2473-4276
DOI
10.1200/CCI.18.00077
Publisher site
See Article on Publisher Site

Abstract

Purpose: The high attrition rate of cancer drug development programs is a barrier to realizing the promise of precision oncology. We have examined whether the genetic insights from genome-wide association studies of cancer can guide drug development and repurposing in oncology. Materials and Methods: Across 37 cancers, we identified 955 genetic risk variants from the National Human Genome Research Institute-European Bioinformatics Institute genome-wide association study catalog. We linked these variants to target genes using strategies that were based on linkage disequilibrium, DNA three-dimensional structure, and integration of predicted gene function and expression. With the use of the Informa Pharmaprojects database, we identified genes that are targets of unique drugs and assessed the level of enrichment that would be afforded by incorporation of genetic information in preclinical and phase II studies. For targets not under development, we implemented machine learning approaches to assess druggability. Results: For all preclinical targets incorporating genetic information, a 2.00-fold enrichment of a drug being successfully approved could be achieved (95% CI, 1.14- to 3.48-fold; P = .02). For phase II targets, a 2.75-fold enrichment could be achieved (95% CI, 1.42- to 5.35-fold; P < .001). Application of genetic information suggests potential repurposing of 15 approved nononcology drugs. Conclusion: The findings illustrate the value of using insights from the genetics of inherited cancer susceptibility discovery projects as part of a data-driven strategy to inform drug discovery. Support for cancer germline genetic information for prospective targets is available online from the Institute of Cancer Research.

Journal

JCO Clinical Cancer InformaticsWolters Kluwer Health

Published: Nov 21, 2018

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