Literature DB >> 23230185

Lineage-specific biomarkers predict response to FGFR inhibition.

David C Loch1, Pamela M Pollock.   

Abstract

In this issue of Cancer Discovery, Guagnano and colleagues use a large and diverse annotated collection of cancer cell lines, the Cancer Cell Line Encyclopedia, to correlate whole-genome expression and genomic alteration datasets with cell line sensitivity data to the novel pan-fibroblast growth factor receptor (FGFR) inhibitor NVP-BGJ398. Their findings underscore not only the preclinical use of such cell line panels in identifying predictive biomarkers, but also the emergence of the FGFRs as valid therapeutic targets, across an increasingly broad range of malignancies. ©2012 AACR.

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Year:  2012        PMID: 23230185      PMCID: PMC4300517          DOI: 10.1158/2159-8290.CD-12-0486

Source DB:  PubMed          Journal:  Cancer Discov        ISSN: 2159-8274            Impact factor:   39.397


  11 in total

1.  AZD4547: an orally bioavailable, potent, and selective inhibitor of the fibroblast growth factor receptor tyrosine kinase family.

Authors:  Paul R Gavine; Lorraine Mooney; Elaine Kilgour; Andrew P Thomas; Katherine Al-Kadhimi; Sarah Beck; Claire Rooney; Tanya Coleman; Dawn Baker; Martine J Mellor; A Nigel Brooks; Teresa Klinowska
Journal:  Cancer Res       Date:  2012-02-27       Impact factor: 12.701

Review 2.  Molecular pathways: fibroblast growth factor signaling: a new therapeutic opportunity in cancer.

Authors:  A Nigel Brooks; Elaine Kilgour; Paul D Smith
Journal:  Clin Cancer Res       Date:  2012-03-02       Impact factor: 12.531

3.  Exploiting genetic complexity in cancer to improve therapeutic strategies.

Authors:  Mathew J Garnett; Ultan McDermott
Journal:  Drug Discov Today       Date:  2012-02-08       Impact factor: 7.851

4.  Potent, selective inhibitors of fibroblast growth factor receptor define fibroblast growth factor dependence in preclinical cancer models.

Authors:  Matthew Squires; George Ward; Gordan Saxty; Valerio Berdini; Anne Cleasby; Peter King; Patrick Angibaud; Tim Perera; Lynsey Fazal; Douglas Ross; Charlotte Griffiths Jones; Andrew Madin; Rajdeep K Benning; Emma Vickerstaffe; Alistair O'Brien; Martyn Frederickson; Michael Reader; Christopher Hamlett; Michael A Batey; Sharna Rich; Maria Carr; Darcey Miller; Ruth Feltell; Abarna Thiru; Susanne Bethell; Lindsay A Devine; Brent L Graham; Andrew Pike; Jose Cosme; Edward J Lewis; Eddy Freyne; John Lyons; Julie Irving; Christopher Murray; David R Newell; Neil T Thompson
Journal:  Mol Cancer Ther       Date:  2011-07-15       Impact factor: 6.261

Review 5.  Targeting mutant fibroblast growth factor receptors in cancer.

Authors:  Heidi Greulich; Pamela M Pollock
Journal:  Trends Mol Med       Date:  2011-03-01       Impact factor: 11.951

6.  A novel, selective inhibitor of fibroblast growth factor receptors that shows a potent broad spectrum of antitumor activity in several tumor xenograft models.

Authors:  Genshi Zhao; Wei-Ying Li; Daohong Chen; James R Henry; Hong-Yu Li; Zhaogen Chen; Mohammad Zia-Ebrahimi; Laura Bloem; Yan Zhai; Karen Huss; Sheng-Bin Peng; Denis J McCann
Journal:  Mol Cancer Ther       Date:  2011-09-07       Impact factor: 6.261

7.  Ponatinib (AP24534), a multitargeted pan-FGFR inhibitor with activity in multiple FGFR-amplified or mutated cancer models.

Authors:  Joseph M Gozgit; Matthew J Wong; Lauren Moran; Scott Wardwell; Qurish K Mohemmad; Narayana I Narasimhan; William C Shakespeare; Frank Wang; Tim Clackson; Victor M Rivera
Journal:  Mol Cancer Ther       Date:  2012-01-11       Impact factor: 6.261

8.  Molecular target class is predictive of in vitro response profile.

Authors:  Joel Greshock; Kurtis E Bachman; Yan Y Degenhardt; Junping Jing; Yuan H Wen; Stephen Eastman; Elizabeth McNeil; Christopher Moy; Ronald Wegrzyn; Kurt Auger; Mary Ann Hardwicke; Richard Wooster
Journal:  Cancer Res       Date:  2010-04-20       Impact factor: 12.701

Review 9.  Exploiting the cancer genome: strategies for the discovery and clinical development of targeted molecular therapeutics.

Authors:  Timothy A Yap; Paul Workman
Journal:  Annu Rev Pharmacol Toxicol       Date:  2012       Impact factor: 13.820

10.  The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity.

Authors:  Jordi Barretina; Giordano Caponigro; Nicolas Stransky; Kavitha Venkatesan; Adam A Margolin; Sungjoon Kim; Christopher J Wilson; Joseph Lehár; Gregory V Kryukov; Dmitriy Sonkin; Anupama Reddy; Manway Liu; Lauren Murray; Michael F Berger; John E Monahan; Paula Morais; Jodi Meltzer; Adam Korejwa; Judit Jané-Valbuena; Felipa A Mapa; Joseph Thibault; Eva Bric-Furlong; Pichai Raman; Aaron Shipway; Ingo H Engels; Jill Cheng; Guoying K Yu; Jianjun Yu; Peter Aspesi; Melanie de Silva; Kalpana Jagtap; Michael D Jones; Li Wang; Charles Hatton; Emanuele Palescandolo; Supriya Gupta; Scott Mahan; Carrie Sougnez; Robert C Onofrio; Ted Liefeld; Laura MacConaill; Wendy Winckler; Michael Reich; Nanxin Li; Jill P Mesirov; Stacey B Gabriel; Gad Getz; Kristin Ardlie; Vivien Chan; Vic E Myer; Barbara L Weber; Jeff Porter; Markus Warmuth; Peter Finan; Jennifer L Harris; Matthew Meyerson; Todd R Golub; Michael P Morrissey; William R Sellers; Robert Schlegel; Levi A Garraway
Journal:  Nature       Date:  2012-03-28       Impact factor: 49.962

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