Literature DB >> 17185464

Gene expression profiling and correlation with outcome in clinical trials of the proteasome inhibitor bortezomib.

George Mulligan1, Constantine Mitsiades, Barb Bryant, Fenghuang Zhan, Wee J Chng, Steven Roels, Erik Koenig, Andrew Fergus, Yongsheng Huang, Paul Richardson, William L Trepicchio, Annemiek Broyl, Pieter Sonneveld, John D Shaughnessy, P Leif Bergsagel, David Schenkein, Dixie-Lee Esseltine, Anthony Boral, Kenneth C Anderson.   

Abstract

The aims of this study were to assess the feasibility of prospective pharmacogenomics research in multicenter international clinical trials of bortezomib in multiple myeloma and to develop predictive classifiers of response and survival with bortezomib. Patients with relapsed myeloma enrolled in phase 2 and phase 3 clinical trials of bortezomib and consented to genomic analyses of pretreatment tumor samples. Bone marrow aspirates were subject to a negative-selection procedure to enrich for tumor cells, and these samples were used for gene expression profiling using DNA microarrays. Data quality and correlations with trial outcomes were assessed by multiple groups. Gene expression in this dataset was consistent with data published from a single-center study of newly diagnosed multiple myeloma. Response and survival classifiers were developed and shown to be significantly associated with outcome via testing on independent data. The survival classifier improved on the risk stratification provided by the International Staging System. Predictive models and biologic correlates of response show some specificity for bortezomib rather than dexamethasone. Informative gene expression data and genomic classifiers that predict clinical outcome can be derived from prospective clinical trials of new anticancer agents.

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Year:  2006        PMID: 17185464     DOI: 10.1182/blood-2006-09-044974

Source DB:  PubMed          Journal:  Blood        ISSN: 0006-4971            Impact factor:   22.113


  168 in total

1.  KLF9 is a novel transcriptional regulator of bortezomib- and LBH589-induced apoptosis in multiple myeloma cells.

Authors:  Sudha Mannava; DaZhong Zhuang; Jayakumar R Nair; Rajat Bansal; Joseph A Wawrzyniak; Shoshanna N Zucker; Emily E Fink; Kalyana C Moparthy; Qiang Hu; Song Liu; Lawrence H Boise; Kelvin P Lee; Mikhail A Nikiforov
Journal:  Blood       Date:  2011-12-05       Impact factor: 22.113

2.  Principled sure independence screening for Cox models with ultra-high-dimensional covariates.

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Journal:  J Multivar Anal       Date:  2012-02-01       Impact factor: 1.473

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Journal:  Haematologica       Date:  2012-07-06       Impact factor: 9.941

4.  PI3K/p110{delta} is a novel therapeutic target in multiple myeloma.

Authors:  Hiroshi Ikeda; Teru Hideshima; Mariateresa Fulciniti; Giulia Perrone; Naoya Miura; Hiroshi Yasui; Yutaka Okawa; Tanyel Kiziltepe; Loredana Santo; Sonia Vallet; Diana Cristea; Elisabetta Calabrese; Gullu Gorgun; Noopur S Raje; Paul Richardson; Nikhil C Munshi; Brian J Lannutti; Kamal D Puri; Neill A Giese; Kenneth C Anderson
Journal:  Blood       Date:  2010-05-26       Impact factor: 22.113

5.  Xbp1s-negative tumor B cells and pre-plasmablasts mediate therapeutic proteasome inhibitor resistance in multiple myeloma.

Authors:  Chungyee Leung-Hagesteijn; Natalie Erdmann; Grace Cheung; Jonathan J Keats; A Keith Stewart; Donna E Reece; Kim Chan Chung; Rodger E Tiedemann
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Review 6.  The use of molecular-based risk stratification and pharmacogenomics for outcome prediction and personalized therapeutic management of multiple myeloma.

Authors:  Sarah K Johnson; Christoph J Heuck; Anthony P Albino; Pingping Qu; Qing Zhang; Bart Barlogie; John D Shaughnessy
Journal:  Int J Hematol       Date:  2011-10-15       Impact factor: 2.490

7.  Metabolic signature identifies novel targets for drug resistance in multiple myeloma.

Authors:  Patricia Maiso; Daisy Huynh; Michele Moschetta; Antonio Sacco; Yosra Aljawai; Yuji Mishima; John M Asara; Aldo M Roccaro; Alec C Kimmelman; Irene M Ghobrial
Journal:  Cancer Res       Date:  2015-03-13       Impact factor: 12.701

8.  Histone deacetylase inhibitor panobinostat induces calcineurin degradation in multiple myeloma.

Authors:  Yoichi Imai; Eri Ohta; Shu Takeda; Satoko Sunamura; Mariko Ishibashi; Hideto Tamura; Yan-Hua Wang; Atsuko Deguchi; Junji Tanaka; Yoshiro Maru; Toshiko Motoji
Journal:  JCI Insight       Date:  2016-04-21

9.  CRM1 inhibition induces tumor cell cytotoxicity and impairs osteoclastogenesis in multiple myeloma: molecular mechanisms and therapeutic implications.

Authors:  Y-T Tai; Y Landesman; C Acharya; Y Calle; M Y Zhong; M Cea; D Tannenbaum; A Cagnetta; M Reagan; A A Munshi; W Senapedis; J R Saint-Martin; T Kashyap; S Shacham; M Kauffman; Y Gu; L Wu; I Ghobrial; F Zhan; A L Kung; S A Schey; P Richardson; N C Munshi; K C Anderson
Journal:  Leukemia       Date:  2013-04-16       Impact factor: 11.528

10.  Profiling bortezomib resistance identifies secondary therapies in a mouse myeloma model.

Authors:  Holly A F Stessman; Linda B Baughn; Aaron Sarver; Tian Xia; Raamesh Deshpande; Aatif Mansoor; Susan A Walsh; John J Sunderland; Nathan G Dolloff; Michael A Linden; Fenghuang Zhan; Siegfried Janz; Chad L Myers; Brian G Van Ness
Journal:  Mol Cancer Ther       Date:  2013-03-27       Impact factor: 6.261

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