Literature DB >> 12716460

Prediction of sensitivity to STI571 among chronic myeloid leukemia patients by genome-wide cDNA microarray analysis.

Yasuyuki Kaneta1, Yoshitoyo Kagami, Toyomasa Katagiri, Tatsuhiko Tsunoda, Itsuro Jin-nai, Hirokuni Taguchi, Hisamaru Hirai, Kazunori Ohnishi, Takanori Ueda, Nobuhiko Emi, Akihiro Tomida, Takashi Tsuruo, Yusuke Nakamura, Ryuzo Ohno.   

Abstract

One of the most critical issues to be solved in regard to cancer chemotherapy is the establishment of ways to predict the efficacy of anti-cancer drugs for individual patients. To develop a prediction system based on expression of specific genes, we analyzed expression profiles of mononuclear cells from 18 chronic myeloid leukemia (CML) patients who were treated with the tyrosine kinase inhibitor STI571. cDNA microarrays representing 23 040 genes identified 79 genes that were expressed differentially between responders and non-responders to STI571. On the basis of the expression patterns of 15 or 30 of these genes among the patients, we developed a "Prediction Score" system that could clearly separate the responder group from the non-responder group. Verification of this system using four additional ("test") cases succeeded in predicting the response of each of those four patients to the drug. These results provide the first evidence that gene-expression profiles can predict sensitivity of CML cells to STI571, and may eventually lead to the achievement of "personalized therapy" for this disease.

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Year:  2002        PMID: 12716460      PMCID: PMC5927114          DOI: 10.1111/j.1349-7006.2002.tb01328.x

Source DB:  PubMed          Journal:  Jpn J Cancer Res        ISSN: 0910-5050


  16 in total

1.  Targeting the BCR-ABL tyrosine kinase in chronic myeloid leukemia.

Authors:  J M Goldman; J V Melo
Journal:  N Engl J Med       Date:  2001-04-05       Impact factor: 91.245

Review 2.  The biology of chronic myeloid leukemia.

Authors:  S Faderl; M Talpaz; Z Estrov; S O'Brien; R Kurzrock; H M Kantarjian
Journal:  N Engl J Med       Date:  1999-07-15       Impact factor: 91.245

Review 3.  Bcr-Abl inhibition as a modality of CML therapeutics.

Authors:  E Buchdunger; A Matter; B J Druker
Journal:  Biochim Biophys Acta       Date:  2001-08-31

4.  Chronic myeloid leukemia: current treatment options.

Authors:  J M Goldman; B J Druker
Journal:  Blood       Date:  2001-10-01       Impact factor: 22.113

5.  Expression profiling of medulloblastoma: PDGFRA and the RAS/MAPK pathway as therapeutic targets for metastatic disease.

Authors:  T J MacDonald; K M Brown; B LaFleur; K Peterson; C Lawlor; Y Chen; R J Packer; P Cogen; D A Stephan
Journal:  Nat Genet       Date:  2001-10       Impact factor: 38.330

6.  Identification by cDNA microarray of genes involved in ovarian carcinogenesis.

Authors:  K Ono; T Tanaka; T Tsunoda; O Kitahara; C Kihara; A Okamoto; K Ochiai; T Takagi; Y Nakamura
Journal:  Cancer Res       Date:  2000-09-15       Impact factor: 12.701

Review 7.  Going APE over ref-1.

Authors:  A R Evans; M Limp-Foster; M R Kelley
Journal:  Mutat Res       Date:  2000-10-16       Impact factor: 2.433

8.  Apurinic/apyrimidinic endonuclease activity is elevated in human adult gliomas.

Authors:  M S Bobola; A Blank; M S Berger; B A Stevens; J R Silber
Journal:  Clin Cancer Res       Date:  2001-11       Impact factor: 12.531

9.  Genome-wide analysis of gene expression in human hepatocellular carcinomas using cDNA microarray: identification of genes involved in viral carcinogenesis and tumor progression.

Authors:  H Okabe; S Satoh; T Kato; O Kitahara; R Yanagawa; Y Yamaoka; T Tsunoda; Y Furukawa; Y Nakamura
Journal:  Cancer Res       Date:  2001-03-01       Impact factor: 12.701

10.  Efficacy and safety of a specific inhibitor of the BCR-ABL tyrosine kinase in chronic myeloid leukemia.

Authors:  B J Druker; M Talpaz; D J Resta; B Peng; E Buchdunger; J M Ford; N B Lydon; H Kantarjian; R Capdeville; S Ohno-Jones; C L Sawyers
Journal:  N Engl J Med       Date:  2001-04-05       Impact factor: 91.245

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  7 in total

1.  Gene expression signature that predicts early molecular response failure in chronic-phase CML patients on frontline imatinib.

Authors:  Chung H Kok; David T Yeung; Liu Lu; Dale B Watkins; Tamara M Leclercq; Phuong Dang; Verity A Saunders; John Reynolds; Deborah L White; Timothy P Hughes
Journal:  Blood Adv       Date:  2019-05-28

Review 2.  c-Cbl and Cbl-b ubiquitin ligases: substrate diversity and the negative regulation of signalling responses.

Authors:  Christine B F Thien; Wallace Y Langdon
Journal:  Biochem J       Date:  2005-10-15       Impact factor: 3.857

3.  A gene expression signature of CD34+ cells to predict major cytogenetic response in chronic-phase chronic myeloid leukemia patients treated with imatinib.

Authors:  Shannon K McWeeney; Lucy C Pemberton; Marc M Loriaux; Kristina Vartanian; Stephanie G Willis; Gregory Yochum; Beth Wilmot; Yaron Turpaz; Raji Pillai; Brian J Druker; Jennifer L Snead; Mary MacPartlin; Stephen G O'Brien; Junia V Melo; Thoralf Lange; Christina A Harrington; Michael W N Deininger
Journal:  Blood       Date:  2009-10-16       Impact factor: 22.113

4.  Efficacy and safety of imatinib mesylate for patients in the first chronic phase of chronic myeloid leukemia: results of a Japanese phase II clinical study.

Authors:  Yasuo Morishima; Michinori Ogura; Miki Nishimura; Fumiharu Yazaki; Masami Bessho; Hideaki Mizoguchi; Shigeru Chiba; Hisamaru Hirai; Tetsuzo Tauchi; Akio Urabe; Masatomo Takahashi; Kazunori Ohnishi; Toshiya Yokozawa; Nobuhiko Emi; Masami Hirano; Chihiro Shimazaki; Shinji Nakao; Yasukazu Kawai; Masahiro Fujimoto; Hirokuni Taguchi; Itsuro Jinnai; Ryuzo Ohno
Journal:  Int J Hematol       Date:  2004-10       Impact factor: 2.490

5.  Network-based de-noising improves prediction from microarray data.

Authors:  Tsuyoshi Kato; Yukio Murata; Koh Miura; Kiyoshi Asai; Paul B Horton; Tsuda Koji; Wataru Fujibuchi
Journal:  BMC Bioinformatics       Date:  2006-03-20       Impact factor: 3.169

Review 6.  Integrating genetic and epigenetic factors in chronic myeloid leukemia risk assessment: toward gene expression-based biomarkers.

Authors:  Vaidehi Krishnan; Dennis Dong Hwan Kim; Timothy P Hughes; Susan Branford; S Tiong Ong
Journal:  Haematologica       Date:  2022-02-01       Impact factor: 9.941

7.  Confirming microarray data--is it really necessary?

Authors:  John C Rockett; Gary M Hellmann
Journal:  Genomics       Date:  2004-04       Impact factor: 5.736

  7 in total

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