Evidence map›Paper›PMID 24074785›Full record

ReviewBreast (Edinburgh, Scotland)2013

Mutational analysis of breast cancer: guiding personalized treatments.

Matthew J Ellis

Open access · hybridAbstract readReview
In one paragraph

Review in Breast (Edinburgh, Scotland), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

8 citing papers in PubMed, 21 citations in OpenAlex.

  1. 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

1 author at 1 institution in 1 country.

Matthew J EllisDivision of Medical Oncology, Section of Breast Oncology, Washington University School of Medicine, Siteman Cancer Center, 660 South Euclid Ave, CB 8069, St Louis, MO 63110, USA. Electronic address: mellis@dom.wustl.edu.
Washington University in St. Louis · US

Funding

Washington University Center for Cellular ImagingP30CA091842 · NCI · WASHINGTON UNIVERSITY · PI TIMOTHY J. EBERLEIN · 2001 to 2026
$128.0M
Cancer Proteome Center at Washington Univ, Univ of North Carolina & Boise StateU24CA160035 · NCI · WASHINGTON UNIVERSITY · PI CHEN, XIAN, ELLIS, MATTHEW J · 2011 to 2016
$11.8M
NOVEL BIOMARKERS FOR AROMATASE INHIBITOR THERAPYR01CA095614 · NCI · WASHINGTON UNIVERSITY · PI ELLIS, MATTHEW J, LUO, JINGQIN · 2003 to 2013
$5.6M
WUSM CANCER AND LEUKEMIA GROUP BU10CA077440 · NCI · WASHINGTON UNIVERSITY · PI BARTLETT, NANCY L · 1998 to 2013
$4.4M
NCI NIH HHS P30 CA091842NCI NIH HHS P30 CA91842NCI NIH HHS R01 CA095614NCI NIH HHS U10 CA077440NCI NIH HHS U24 CA160035
6 · The paper itself

Abstract

The application of high throughput techniques to profile DNA, RNA and protein in breast cancer samples from hundreds of patients has profoundly increased our knowledge of the disease. However there remain many knowledge gaps that will require a long process of extended clinical correlation studies, deeper integrated 'omic analysis and functional annotation to address. This article reviews conclusions from recent breast cancer 'omics profiling' papers and considers pathways forward for extracting medically valuable information from large dimension data sets.

Indexed as

Genetic Predisposition to DiseaseAdultAgedAntineoplastic Agents, HormonalBreast NeoplasmsCombined Modality TherapyDNA Mutational AnalysisFemaleGene Expression ProfilingGenes, erbB-2GenomicsHumansMastectomyMiddle AgedPrecision MedicinePrognosisAntineoplastic Agents, HormonalBreast cancerGenomicsSomatic mutationTherapeutic road mapWhole genome sequencing

Identifiers

PMID24074785
PMCPMC3787523
OpenAlexW1968836535

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.