Literature DB >> 15335284

Using microarrays to predict resistance to chemotherapy in cancer patients.

Chung-Hae Lee1, Pascale F Macgregor.   

Abstract

Chemotherapy resistance remains a major obstacle to successful treatment and better outcome in cancer patients. The advent of whole genome experimental strategies, such as DNA microarrays, has transformed the way researchers approach cancer research. There is considerable hope that microarray technology will lead to the identification of new targets for therapeutic intervention, a better understanding of the disease process, and, ultimately, to higher survival rates and more personalized medicine. The question at hand is what is the best approach to apply these new technologies to the study of anticancer drug resistance, and how can the results obtained in the laboratory be quickly moved to a clinical setting? This review offers an overview of the microarray technology, including its recently associated strategies, such as array comparative genomic hybridization and promoter arrays. It also highlights some recent examples of microarray studies, which represent a first step toward a better understanding of drug resistance in cancer and, ultimately, personalized medicine.

Entities:  

Mesh:

Substances:

Year:  2004        PMID: 15335284     DOI: 10.1517/14622416.5.6.611

Source DB:  PubMed          Journal:  Pharmacogenomics        ISSN: 1462-2416            Impact factor:   2.533


  5 in total

1.  Effect of ketoprofen and indomethacin on methotrexate pharmacokinetics in mice plasma and tumor tissues.

Authors:  Yasmine M Elmorsi; Sahar M El-Haggar; Osama M Ibrahim; Mokhtar M Mabrouk
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2012-11-17       Impact factor: 2.441

2.  Prediction of anticancer drug potency from expression of genes involved in growth factor signaling.

Authors:  Zunyan Dai; Catalin Barbacioru; Ying Huang; Wolfgang Sadée
Journal:  Pharm Res       Date:  2006-01-26       Impact factor: 4.200

3.  MIMAS: an innovative tool for network-based high density oligonucleotide microarray data management and annotation.

Authors:  Leandro Hermida; Olivier Schaad; Philippe Demougin; Patrick Descombes; Michael Primig
Journal:  BMC Bioinformatics       Date:  2006-04-05       Impact factor: 3.169

4.  Gene Expression Profiles - What the Clinician Needs to Know.

Authors:  Koraljka Gall-Troselj
Journal:  EJIFCC       Date:  2005-05-17

5.  Modulation of gene expression in drug resistant Leishmania is associated with gene amplification, gene deletion and chromosome aneuploidy.

Authors:  Jean-Michel Ubeda; Danielle Légaré; Frédéric Raymond; Amin Ahmed Ouameur; Sébastien Boisvert; Philippe Rigault; Jacques Corbeil; Michel J Tremblay; Martin Olivier; Barbara Papadopoulou; Marc Ouellette
Journal:  Genome Biol       Date:  2008-07-18       Impact factor: 13.583

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.