Evidence map›Paper›PMID 27605190›Full record

ReviewMicroarrays (Basel, Switzerland)2013

Improving Pathological Assessment of Breast Cancer by Employing Array-Based Transcriptome Analysis.

Zsuzsanna Mihály, Balázs Győrffy

Open access · goldAbstract readReview
In one paragraph

Review in Microarrays (Basel, Switzerland), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
0.9field-weighted citation impact, top 26% 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

21 citing papers in PubMed, 28 citations in OpenAlex.

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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

2 authors at 2 institutions in 1 country.

Zsuzsanna MihályDeptartment of Pediatrics, Semmelweis University, Budapest H-1083, Hungary. zsuzsannamihaly@gmail.com.
Balázs GyőrffyResearch Laboratory of Pediatrics and Nephrology, Hungarian Academy of Sciences, Budapest H-1083, Hungary. gyorffy@gyer1.sote.hu.
Hungarian Academy of Sciences · HUSemmelweis University · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer research has paved the way of personalized oncology with the introduction of hormonal therapy and the measurement of estrogen receptor as the first widely accepted clinical biomarker. The expression of another receptor-HER2/ERBB2/neu-was initially a sign of worse prognosis, but targeted therapy has granted improved outcome for these patients so that today HER2 positive patients have better prognosis than HER2 negative patients. Later, the introduction of multigene assays provided the pathologists with an unbiased assessment of the tumors' molecular fingerprint. The recent FDA approval of complete microarray pipelines has opened new possibilities for the objective classification of breast cancer samples. Here we review the applications of microarrays for determining ER and HER2 status, molecular subtypes as well as predicting prognosis and grade for breast cancer patients. An open question remains the role of single genes within such signatures. Openly available microarray datasets enable the execution of an independent cross-validation of new marker and signature candidates. In summary, we review the current state regarding clinical applications of microarrays in breast cancer molecular pathology.

Indexed as

biomarkerbreast cancermicroarraymolecular subtypepredictionprognosis

Identifiers

PMID27605190
PMCPMC5003464
OpenAlexW2048166083

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.