Literature DB >> 15331079

Predicting drug response based on gene expression.

Jacques Robert1, Antoine Vekris, Philippe Pourquier, Jacques Bonnet.   

Abstract

Predicting drug response is a challenging problem in oncology. In the 1975-1985 decade, important efforts were devoted to the generation of cellular assays able to predict, on an individual basis, the in vitro response of tumour cells to chemotherapeutic agents, but such methods could not be adopted in routine. Numerous mechanisms of resistance to anticancer agents have been identified in cultured cell lines selected for growth in the presence of infratoxic, increasing doses of anticancer agents. They mainly concern drug transport, drug activation or detoxification, target quantitative or qualitative alterations, DNA repair efficiency, and alterations in signalling and/or execution of cell death programmes. New molecular biology techniques have been developed in order to identify the genes involved in drug resistance; they mainly involve differential expression techniques, but functional approaches may also prove informative. The availability of techniques of gene expression profiling has allowed to establish correlations between gene expression and drug sensitivity of tumour cells or human cancers. This type of approach has been initiated on in vitro systems by the National Cancer Institute (NCI) in the USA and is pursued by a growing number of public and private laboratories around the world. In the clinical setting, a number of genes or proteins have been identified as potential predictive markers of drug activity and their use could be progressively implemented for drug selection in patients receiving chemotherapy, allowing thus more rational and individualised treatments.

Entities:  

Mesh:

Substances:

Year:  2004        PMID: 15331079     DOI: 10.1016/j.critrevonc.2004.06.002

Source DB:  PubMed          Journal:  Crit Rev Oncol Hematol        ISSN: 1040-8428            Impact factor:   6.312


  11 in total

1.  Drug discovery in a multidimensional world: systems, patterns, and networks.

Authors:  Joel T Dudley; Eric Schadt; Marina Sirota; Atul J Butte; Euan Ashley
Journal:  J Cardiovasc Transl Res       Date:  2010-07-31       Impact factor: 4.132

2.  The role of drug profiles as similarity metrics: applications to repurposing, adverse effects detection and drug-drug interactions.

Authors:  Santiago Vilar; George Hripcsak
Journal:  Brief Bioinform       Date:  2017-07-01       Impact factor: 11.622

3.  Discovery and preclinical validation of drug indications using compendia of public gene expression data.

Authors:  Marina Sirota; Joel T Dudley; Jeewon Kim; Annie P Chiang; Alex A Morgan; Alejandro Sweet-Cordero; Julien Sage; Atul J Butte
Journal:  Sci Transl Med       Date:  2011-08-17       Impact factor: 17.956

4.  Analyzing illumina gene expression microarray data from different tissues: methodological aspects of data analysis in the metaxpress consortium.

Authors:  Claudia Schurmann; Katharina Heim; Arne Schillert; Stefan Blankenberg; Maren Carstensen; Marcus Dörr; Karlhans Endlich; Stephan B Felix; Christian Gieger; Harald Grallert; Christian Herder; Wolfgang Hoffmann; Georg Homuth; Thomas Illig; Jochen Kruppa; Thomas Meitinger; Christian Müller; Matthias Nauck; Annette Peters; Rainer Rettig; Michael Roden; Konstantin Strauch; Uwe Völker; Henry Völzke; Simone Wahl; Henri Wallaschofski; Philipp S Wild; Tanja Zeller; Alexander Teumer; Holger Prokisch; Andreas Ziegler
Journal:  PLoS One       Date:  2012-12-07       Impact factor: 3.240

5.  Identification of gene polymorphisms of human DNA topoisomerase I in the National Cancer Institute panel of human tumour cell lines.

Authors:  F Moisan; M Longy; J Robert; V Le Morvan
Journal:  Br J Cancer       Date:  2006-09-19       Impact factor: 7.640

6.  Knowledge-guided gene prioritization reveals new insights into the mechanisms of chemoresistance.

Authors:  Amin Emad; Junmei Cairns; Krishna R Kalari; Liewei Wang; Saurabh Sinha
Journal:  Genome Biol       Date:  2017-08-11       Impact factor: 13.583

7.  Genetic Signatures of Acute Asthma Exacerbation Related With Ineffective Response to Corticosteroid.

Authors:  Min Gyu Kang; Hyun Seung Lee; Kelan G Tantisira; Heung Woo Park
Journal:  Allergy Asthma Immunol Res       Date:  2020-07       Impact factor: 5.764

8.  Functional DNA repair signature of cancer cell lines exposed to a set of cytotoxic anticancer drugs using a multiplexed enzymatic repair assay on biochip.

Authors:  Anne Forestier; Fanny Sarrazy; Sylvain Caillat; Yves Vandenbrouck; Sylvie Sauvaigo
Journal:  PLoS One       Date:  2012-12-31       Impact factor: 3.240

9.  Comparison of selected gene expression profiles in sensitive and resistant cancer cells treated with doxorubicin and Selol.

Authors:  Jadwiga Dudkiewicz-Wilczyńska; Agnieszka Grabowska; Iza Książek; Karolina Sitarz; Piotr Suchocki; Elżbieta Anuszewska
Journal:  Contemp Oncol (Pozn)       Date:  2014-06-03

10.  Computational discovery of transcription factors associated with drug response.

Authors:  C Hanson; J Cairns; L Wang; S Sinha
Journal:  Pharmacogenomics J       Date:  2015-10-27       Impact factor: 3.550

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.