Evidence map›Paper›PMID 26597277›Full record

ArticleBMC medical genomics2015

Gene-expression signature functional annotation of breast cancer tumours in function of age.

Pascal Jézéquel, Zein Sharif, Hamza Lasla, Wilfried Gouraud, Catherine Guérin-Charbonnel, Loïc Campion, Stéphane Chrétien, Mario Campone

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 43% 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

3 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
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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

8 authors at 3 institutions in 1 country.

Pascal JézéquelBioinfomics unit, Integrated Centre for Oncology - René Gauducheau, Bd J. Monod, Nantes, Saint Herblain Cedex, 44805, France. pascal.jezequel@ico.unicancer.fr.
Zein SharifDépartemental de Vendée - site de Montaigu, Polyvalent medicine service, Centre Hospitalier, 54, rue Saint Jacques, BP 259, Montaigu, 85602, France. zein.sharif@chd-vendee.fr.
Hamza LaslaBioinfomics unit, Integrated Centre for Oncology - René Gauducheau, Bd J. Monod, Nantes, Saint Herblain Cedex, 44805, France. Hamza.lasla@ico.unicancer.fr.
Wilfried GouraudBioinfomics unit, Integrated Centre for Oncology - René Gauducheau, Bd J. Monod, Nantes, Saint Herblain Cedex, 44805, France. Wilfried.gouraud@ico.unicancer.fr.
Catherine Guérin-CharbonnelBioinfomics unit, Integrated Centre for Oncology - René Gauducheau, Bd J. Monod, Nantes, Saint Herblain Cedex, 44805, France. Catherine.guerin@ico.unicancer.fr.
Loïc CampionINSERM U892, IRT-UN, 8 quai Moncousu, Nantes Cedex, 44007, France. Loic.campion@ico.unicancer.fr.
Stéphane ChrétienMathematics laboratory, UMR CNRS 6623 et Université de Franche Comté, 16 route de Gray, Besançon Cedex, 25030, France. Stephane.chretien@univ-fcomte.fr.
Mario CamponeBioinfomics unit, Integrated Centre for Oncology - René Gauducheau, Bd J. Monod, Nantes, Saint Herblain Cedex, 44805, France. Mario.campone@ico.unicancer.fr.
Inserm · FRCentre Hospitalier Départemental Vendée · FRUniversité de franche-comté · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast cancer biological characteristics change as age advances. Today, there is a lack of knowledge regarding age-specific molecular alterations that characterize breast tumours, notably in elderly patients. The vast majority of studies that aimed at exploring breast cancer in function of age are based on clinico-pathological data. Gene-expression signatures (GES), which in some ways capture biological information in a non-reductionist manner, represent powerful tools able to explore tumour heterogeneity.

methodsTwenty-five GES were used for functional annotation of breast tumours in function of age: five for molecular subtyping, seven for immune response, three for metabolism, seven for critical pathways in cancer and three for prognosis. Affymetrix® genomics datasets were exclusively used to avoid cross-platform normalization issues. Available corresponding clinico-pathological data were also retrieved and analysed.

resultsFifteen publicly available datasets were pooled for a total of 2378 breast cancer patients (whole cohort), out of whom 1413 were of Caucasian origin. Three age groups were defined: ≤ 40 years (AG1), > 40 to < 70 years (AG2) and ≥ 70 years (AG3). We confirmed that age influenced the incidence of molecular subtypes. We found a significant growing incidence of luminal B and a decreasing kinetics for basal-like in function of age. We showed that AG3 luminal B tumours were less aggressive than AG1 luminal B tumours based on different GES (iron metabolism, mitochondrial oxidative phosphorylation and reactive stroma), recurrence score prognostic GES and histological grade (SBR). Contrary to tumours of young patients, tumours of elderly patients concentrated favourable GES scores: high oestrogen receptor and mitochondrial oxidative phosphorylation, low proliferation, basal-like, glycolysis, chromosomal instability and iron metabolism, and low GES prognostic scores (van't Veer 70-GES, genomic grade index and recurrence score).

conclusionsFunctional annotation of breast tumours by means of 25 GES demonstrated a decreasing aggressiveness of breast tumours in function of age. This strategy, which can be strengthened by increasing the number of representative GES to gain more insight into biological systems involved in this disease, provides a framework to develop rational therapeutic strategies in function of age.

Indexed as

Gene Expression ProfilingMolecular Sequence AnnotationAdultAgedAgingBreast NeoplasmsFemaleHumansMiddle AgedPrognosis

Identifiers

PMID26597277
PMCPMC4657228
OpenAlexW2177819111

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.