Evidence map›Paper›PMID 21878891›Full record

ArticleNature reviews. Clinical oncology2011

Challenges translating breast cancer gene signatures into the clinic.

Britta Weigelt, Lajos Pusztai, Alan Ashworth, Jorge S Reis-Filho

Abstract read
PubMed Publisher
In one paragraph

Article in Nature reviews. Clinical oncology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

55 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. General Assessment of Humoral Activity in Healthy Humans.Molecular & cellular proteomics : MCP · 2016
    Article
  17. Article
  18. Article
  19. Article
  20. Article
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

4 authors.

Britta WeigeltSignal Transduction Laboratory, Cancer Research UK London Research Institute, 44 Lincoln's Inn Fields, London WC2A 3LY, UK.
Lajos Pusztai
Alan Ashworth
Jorge S Reis-Filho

Funding

Breast Cancer Now BREAST CANCER NOW RESEARCH CENTRECancer Research UK
6 · The paper itself

Abstract

The advent of microarray-based gene-expression profiling a decade ago raised high expectations for rapid advances in breast cancer classification, prognostication and prediction. Despite the development of molecular classifications, and prognostic and predictive gene-expression signatures, microarray-based studies have not yielded definitive answers to many of the questions that remain germane for the successful implementation of personalized medicine. There are a lack of robust signatures to predict benefit from specific therapeutic agents and it is still not possible to predict prognosis or chemotherapy treatment response in specific disease subsets accurately, such as triple-negative breast cancer. We discuss the hurdles in the development and validation of molecular classification systems, and prognostic and predictive signatures based on microarray gene-expression profiling. We suggest that similar challenges are likely to be encountered in translating next-generation sequencing data into clinically useful information. Finally we highlight strategies for the development of clinically useful molecular predictors in the future.

Indexed as

Gene Expression ProfilingTranslational Research, BiomedicalBiological AssayBiomarkers, TumorBiomedical ResearchBreast NeoplasmsFemaleHumansBiomarkers, Tumor

Identifiers

What OpenQuestion holds

Textmetadata
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.