Literature DB >> 23498875

Cancer gene expression signatures - the rise and fall?

Frederic Chibon1.   

Abstract

A 'gene expression signature' can be defined as a single or a combined gene expression alteration with validated specificity in terms of diagnosis, prognosis or prediction of therapeutic response. Since the publication of the first signature in the late 90s, high-throughput gene expression analysis has revolutionised genetics over the last 15 years. The scientific community has used this new technology to find responses to these fundamental questions; from understanding tumour biology, to prediction of progression, and treatments to which it will respond. Nevertheless, legitimate excitement about the attractiveness of molecular technologies and the promise of discovery-based research should not overlook adherence to the rules of evidence, otherwise it may result in claims that are not meaningful and lead to disappointment. This review will thus focus on the approaches developed to answer these three fundamental questions and the results evidenced both at biological and clinical level. On looking at this huge amount of data that have become increasingly minute, and at times contradictory, we discuss how gene expression signature improve our understanding of cancer biology, our ability to predict progression and response, and finally, our capacity to treat cancers more efficiently.
Copyright © 2013 Elsevier Ltd. All rights reserved.

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Year:  2013        PMID: 23498875     DOI: 10.1016/j.ejca.2013.02.021

Source DB:  PubMed          Journal:  Eur J Cancer        ISSN: 0959-8049            Impact factor:   9.162


  69 in total

1.  A Prognostic Signature for Lower Grade Gliomas Based on Expression of Long Non-Coding RNAs.

Authors:  Manjari Kiran; Ajay Chatrath; Xiwei Tang; Daniel Macrae Keenan; Anindya Dutta
Journal:  Mol Neurobiol       Date:  2018-11-03       Impact factor: 5.590

2.  MCM2: An alternative to Ki-67 for measuring breast cancer cell proliferation.

Authors:  Einas M Yousef; Daniela Furrer; David L Laperriere; Muhammad R Tahir; Sylvie Mader; Caroline Diorio; Louis A Gaboury
Journal:  Mod Pathol       Date:  2017-01-13       Impact factor: 7.842

3.  Biomarker identification for statin sensitivity of cancer cell lines.

Authors:  Vineet K Raghu; Colin H Beckwitt; Katsuhiko Warita; Alan Wells; Panayiotis V Benos; Zoltán N Oltvai
Journal:  Biochem Biophys Res Commun       Date:  2017-11-14       Impact factor: 3.575

Review 4.  Hypoxia gene expression signatures as predictive biomarkers for personalising radiotherapy.

Authors:  Lingjian Yang; Catharine Ml West
Journal:  Br J Radiol       Date:  2018-03-20       Impact factor: 3.039

5.  Personalized disease signatures through information-theoretic compaction of big cancer data.

Authors:  Swetha Vasudevan; Efrat Flashner-Abramson; F Remacle; R D Levine; Nataly Kravchenko-Balasha
Journal:  Proc Natl Acad Sci U S A       Date:  2018-07-05       Impact factor: 11.205

6.  A high-resolution transcriptome map of cell cycle reveals novel connections between periodic genes and cancer.

Authors:  Daniel Dominguez; Yi-Hsuan Tsai; Nicholas Gomez; Deepak Kumar Jha; Ian Davis; Zefeng Wang
Journal:  Cell Res       Date:  2016-07-01       Impact factor: 25.617

Review 7.  The value of genomics in dissecting the RAS-network and in guiding therapeutics for RAS-driven cancers.

Authors:  Gajendra Shrestha; Shelley M MacNeil; Jasmine A McQuerry; David F Jenkins; Sunil Sharma; Andrea H Bild
Journal:  Semin Cell Dev Biol       Date:  2016-06-20       Impact factor: 7.727

8.  Lean Big Data integration in systems biology and systems pharmacology.

Authors:  Avi Ma'ayan; Andrew D Rouillard; Neil R Clark; Zichen Wang; Qiaonan Duan; Yan Kou
Journal:  Trends Pharmacol Sci       Date:  2014-08-07       Impact factor: 14.819

Review 9.  Defining actionable mutations for oncology therapeutic development.

Authors:  T Hedley Carr; Robert McEwen; Brian Dougherty; Justin H Johnson; Jonathan R Dry; Zhongwu Lai; Zara Ghazoui; Naomi M Laing; Darren R Hodgson; Francisco Cruzalegui; Simon J Hollingsworth; J Carl Barrett
Journal:  Nat Rev Cancer       Date:  2016-04-26       Impact factor: 60.716

10.  Gene Expression Signatures and Immunohistochemical Subtypes Add Prognostic Value to Each Other in Breast Cancer Cohorts.

Authors:  Arian Lundberg; Linda S Lindström; J Chuck Harrell; Claudette Falato; Joseph W Carlson; Paul K Wright; Theodoros Foukakis; Charles M Perou; Kamila Czene; Jonas Bergh; Nicholas P Tobin
Journal:  Clin Cancer Res       Date:  2017-09-29       Impact factor: 12.531

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