Evidence map›Paper›PMID 25502431›Full record

ReviewCurrent opinion in obstetrics & gynecology2015

Genomic profiling of breast cancers.

Christina Curtis

Abstract readReview
In one paragraph

Review in Current opinion in obstetrics & gynecology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–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

14 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. Review
  8. Review
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. 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

1 author.

Christina CurtisDepartments of Medicine and Genetics, Stanford University School of Medicine and Stanford Cancer Institute, Stanford, California, USA.

Funding

Integrated genomic analysis and multi-scale modeling of therapeutic resistanceR01CA182514 · NCI · STANFORD UNIVERSITY · PI CURTIS, CHRISTINA N · 2014 to 2018
$2.4M
NCI NIH HHS 1R01CA182514NCI NIH HHS R01 CA182514
6 · The paper itself

Abstract

purpose of reviewTo describe recent advances in the application of advanced genomic technologies towards the identification of biomarkers of prognosis and treatment response in breast cancer. RECENT

findingsAdvances in high-throughput genomic profiling such as massively parallel sequencing have enabled researchers to catalogue the spectrum of somatic alterations in breast cancers. These tools also hold promise for precision medicine through accurate patient prognostication, stratification, and the dynamic monitoring of treatment response. For example, recent efforts have defined robust molecular subgroups of breast cancer and novel subtype-specific oncogenes. In addition, previously unappreciated activating mutations in human epidermal growth factor receptor 2 have been reported, suggesting new therapeutic opportunities. Genomic profiling of cell-free tumor DNA and circulating tumor cells has been used to monitor disease burden and the emergence of resistance, and such 'liquid biopsy' approaches may facilitate the early, noninvasive detection of aggressive disease. Finally, single-cell genomics is coming of age and will contribute to an understanding of breast cancer evolutionary dynamics. SUMMARY: Here, we highlight recent studies that employ high-throughput genomic technologies in an effort to elucidate breast cancer biology, discover new therapeutic targets, improve prognostication and stratification, and discuss the implications for precision cancer medicine.

Indexed as

High-Throughput Nucleotide SequencingMolecular Targeted TherapySequence Analysis, DNABiomarkers, TumorBreast NeoplasmsFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansPredictive Value of TestsPrognosisBiomarkers, Tumor

Identifiers

PMID25502431
PMCPMC4497788

What OpenQuestion holds

Textmetadata
LicenceTDM
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.