Evidence map›Paper›PMID 25081647›Full record

ArticleMolecular oncology2014

Evaluation of the ability of adjuvant tamoxifen-benefit gene signatures to predict outcome of hormone-naive estrogen receptor-positive breast cancer patients treated with tamoxifen in the advanced setting.

Anieta M Sieuwerts, Maria B Lyng, Marion E Meijer-van Gelder, Vanja de Weerd, Fred C G J Sweep, John A Foekens, Paul N Span, John W M Martens, Henrik J Ditzel

Open access · bronzeAbstract read
In one paragraph

Article in Molecular oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

13 citing papers in PubMed, 19 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

9 authors at 3 institutions in 2 countries.

Anieta M SieuwertsDepartment of Medical Oncology, Erasmus MC Cancer Institute, Erasmus University Medical Center and Cancer Genomics Netherlands, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands. Electronic address: a.sieuwerts@erasmusmc.nl.
Maria B LyngInstitute of Molecular Medicine, University of Southern Denmark, Odense, Denmark.
Marion E Meijer-van GelderDepartment of Medical Oncology, Erasmus MC Cancer Institute, Erasmus University Medical Center and Cancer Genomics Netherlands, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands.
Vanja de WeerdDepartment of Medical Oncology, Erasmus MC Cancer Institute, Erasmus University Medical Center and Cancer Genomics Netherlands, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands.
Fred C G J SweepDepartment of Laboratory Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.
John A FoekensDepartment of Medical Oncology, Erasmus MC Cancer Institute, Erasmus University Medical Center and Cancer Genomics Netherlands, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands.
Paul N SpanDepartment of Radiation Oncology, Radboud University Medical Center, Nijmegen, The Netherlands.
John W M MartensDepartment of Medical Oncology, Erasmus MC Cancer Institute, Erasmus University Medical Center and Cancer Genomics Netherlands, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands.
Henrik J DitzelInstitute of Molecular Medicine, University of Southern Denmark, Odense, Denmark; Department of Oncology, Odense University Hospital, Odense, Denmark.
Erasmus MC · NLRadboud University Nijmegen · NLUniversity of Southern Denmark · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To identify molecular markers indicative of response to tamoxifen and easily implemented in the routine setting, we recently reported three gene signatures that could stratify post-menopausal tamoxifen-treated, estrogen receptor-positive (ER+) patients according to outcome in the adjuvant setting. Here, we evaluated the predictive potential of the total of 14 genes included in the 3 gene signatures using 2 hormone-naïve Dutch ER+ cohorts of a total of 285 recurrent breast cancer patients treated with first-line tamoxifen. mRNA levels were measured by reverse transcriptase quantitative PCR (RT-qPCR) and the length of progression-free survival (PFS) was used as the primary endpoint. A Mann-Whitney U test was used to select for differentially expressed genes between tumors of patients who showed or did not show progressive disease within 6 months after start of tamoxifen treatment. Cox univariate and multivariate regression analysis for PFS were used to further assess their (independent) predictive potential. Five (BCAR3, BCL2, ESR1, IGF1R, and NCOA1) of the 14 genes analyzed showed significantly higher mRNA levels in tumors of patients who showed no disease progression within 6 months. Only BCAR3, BCL2 and NAT1 were significantly associated with a favorable PFS in multivariate analysis that included the traditional predictive factors: age, dominant relapse site, disease-free interval, ER and progesterone receptor (PGR), and adjuvant chemotherapy. This study shows that BCAR3, BCL2 and NAT1 in particular exhibit predictive promise regarding the efficacy of tamoxifen treatment in recurrent disease, in addition to the previously shown favorable outcome in the adjuvant setting.

Indexed as

Adaptor Proteins, Signal TransducingArylamine N-AcetyltransferaseBreast NeoplasmsDisease-Free SurvivalFemaleGuanine Nucleotide Exchange FactorsHumansIsoenzymesMiddle AgedReceptors, EstrogenRetrospective StudiesTamoxifenAdaptor Proteins, Signal TransducingArylamine N-AcetyltransferaseBCAR3 protein, humanGuanine Nucleotide Exchange FactorsIsoenzymesN-acetyltransferase 1Receptors, EstrogenTamoxifenBreast cancerEndocrine therapyGene expressionProgression-free survivalTamoxifen

Identifiers

PMID25081647
PMCPMC5528606
OpenAlexW2133599188

What OpenQuestion holds

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Registered trials

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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.