Evidence map›Paper›PMID 20701793›Full record

ArticleGenome medicine2010

Predictive biomarker discovery through the parallel integration of clinical trial and functional genomics datasets.

Charles Swanton, James M Larkin, Marco Gerlinger, Aron C Eklund, Michael Howell, Gordon Stamp, Julian Downward, Martin Gore, P Andrew Futreal, Bernard Escudier and 13 more

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
7.0field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 43 citations in OpenAlex.

  1. Article
  2. Journal of thoracic disease · 2022
    Article
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  7. Individualising treatment choices in a crowded treatment algorithm.EJC supplements : EJC : official journal of EORTC, European Organization for Research and Treatment of Cancer ... [et al.] · 2013
    Review
  8. Tumour heterogeneity and immune-modulation.Current opinion in pharmacology · 2013
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

23 authors at 11 institutions in 5 countries.

Charles SwantonCancer Research UK London Research Institute, 44 Lincoln's Inn Fields, London, WC2A 3PX, UK. charles.swanton@cancer.org.uk.
James M Larkin
Marco Gerlinger
Aron C Eklund
Michael Howell
Gordon Stamp
Julian Downward
Martin Gore
P Andrew Futreal
Bernard Escudier
Fabrice Andre
Laurence Albiges
Benoit Beuselinck
Stephane Oudard
Jens Hoffmann
Balázs Gyorffy
Chris J Torrance
Karen A Boehme
Hansjuergen Volkmer
Luisella Toschi
Barbara Nicke
Marlene Beck
Zoltan Szallasi
Cancer Research UK · GBInstitut Gustave Roussy · FRTechnical University of Denmark · DKBayer (Germany) · DENatural and Medical Sciences Institute · DERoyal Marsden NHS Foundation Trust · GBHôpital Européen · FRHôpital Européen Georges-Pompidou · FRHorizon Discovery Group (United Kingdom) · GBSemmelweis University · HUWellcome Sanger Institute · GB

Funding

Medical Research Council G0902275
6 · The paper itself

Abstract

The European Union multi-disciplinary Personalised RNA interference to Enhance the Delivery of Individualised Cytotoxic and Targeted therapeutics (PREDICT) consortium has recently initiated a framework to accelerate the development of predictive biomarkers of individual patient response to anti-cancer agents. The consortium focuses on the identification of reliable predictive biomarkers to approved agents with anti-angiogenic activity for which no reliable predictive biomarkers exist: sunitinib, a multi-targeted tyrosine kinase inhibitor and everolimus, a mammalian target of rapamycin (mTOR) pathway inhibitor. Through the analysis of tumor tissue derived from pre-operative renal cell carcinoma (RCC) clinical trials, the PREDICT consortium will use established and novel methods to integrate comprehensive tumor-derived genomic data with personalized tumor-derived small hairpin RNA and high-throughput small interfering RNA screens to identify and validate functionally important genomic or transcriptomic predictive biomarkers of individual drug response in patients. PREDICT's approach to predictive biomarker discovery differs from conventional associative learning approaches, which can be susceptible to the detection of chance associations that lead to overestimation of true clinical accuracy. These methods will identify molecular pathways important for survival and growth of RCC cells and particular targets suitable for therapeutic development. Importantly, our results may enable individualized treatment of RCC, reducing ineffective therapy in drug-resistant disease, leading to improved quality of life and higher cost efficiency, which in turn should broaden patient access to beneficial therapeutics, thereby enhancing clinical outcome and cancer survival. The consortium will also establish and consolidate a European network providing the technological and clinical platform for large-scale functional genomic biomarker discovery. Here we review our current understanding of molecular mechanisms driving resistance to anti-angiogenesis agents, the current limitations of laboratory and clinical trial strategies and how the PREDICT consortium will endeavor to identify a new generation of predictive biomarkers.

Identifiers

PMID20701793
PMCPMC2945010
OpenAlexW2165086913

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.