Evidence map›Paper›PMID 28351365›Full record

ArticleBMC medical genomics2017

Basal-like breast cancer: molecular profiles, clinical features and survival outcomes.

Heloisa H Milioli, Inna Tishchenko, Carlos Riveros, Regina Berretta, Pablo Moscato

Abstract read
In one paragraph

Article in BMC medical genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 1 pooled it
–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

54 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Integrating multi-omics data: Methods and applications in human complex diseases.Biotechnology reports (Amsterdam, Netherlands) · 2025
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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

5 authors.

Heloisa H MilioliCentre for Bioinformatics, Biomarker Discovery and Information-Based Medicine, Hunter Medical Research Institute, Lot 1, Kookaburra Circuit, New Lambton Heights, 2305, Australia.
Inna TishchenkoCentre for Bioinformatics, Biomarker Discovery and Information-Based Medicine, Hunter Medical Research Institute, Lot 1, Kookaburra Circuit, New Lambton Heights, 2305, Australia.
Carlos RiverosCReDITSS Unit, Hunter Medical Research Institute, Lot 1, Kookaburra Circuit, New Lambton Heights, 2305, Australia.
Regina BerrettaCentre for Bioinformatics, Biomarker Discovery and Information-Based Medicine, Hunter Medical Research Institute, Lot 1, Kookaburra Circuit, New Lambton Heights, 2305, Australia.
Pablo MoscatoCentre for Bioinformatics, Biomarker Discovery and Information-Based Medicine, Hunter Medical Research Institute, Lot 1, Kookaburra Circuit, New Lambton Heights, 2305, Australia. Pablo.Moscato@newcastle.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBasal-like constitutes an important molecular subtype of breast cancer characterised by an aggressive behaviour and a limited therapy response. The outcome of patients within this subtype is, however, divergent. Some individuals show an increased risk of dying in the first five years, and others a long-term survival of over ten years after the diagnosis. In this study, we aim at identifying markers associated with basal-like patients' survival and characterising subgroups with distinct disease outcome.

methodsWe explored the genomic and transcriptomic profiles of 351 basal-like samples from the METABRIC and ROCK data sets. Two selection methods, labelled Differential and Survival filters, were employed to determine genes/probes that are differentially expressed in tumour and control samples, and are associated with overall survival. These probes were further used to define molecular subgroups, which vary at the microRNA level and in DNA copy number.

resultsWe identified the expression signature of 80 probes that distinguishes between two basal-like subgroups with distinct clinical features and survival outcomes. Genes included in this list have been mainly linked to cancer immune response, epithelial-mesenchymal transition and cell cycle. In particular, high levels of CXCR6, HCST, C3AR1 and FPR3 were found in Basal I; whereas HJURP, RRP12 and DNMT3B appeared over-expressed in Basal II. These genes exhibited the highest betweenness centrality and node degree values and play a key role in the basal-like breast cancer differentiation. Further molecular analysis revealed 17 miRNAs correlated to the subgroups, including hsa-miR-342-5p, -150, -155, -200c and -17. Additionally, increased percentages of gains/amplifications were detected on chromosomes 1q, 3q, 8q, 10p and 17q, and losses/deletions on 4q, 5q, 8p and X, associated with reduced survival.

conclusionsThe proposed signature supports the existence of at least two subgroups of basal-like breast cancers with distinct disease outcome. The identification of patients at a low risk may impact the clinical decisions-making by reducing the prescription of high-dose chemotherapy and, consequently, avoiding adverse effects. The recognition of other aggressive features within this subtype may be also critical for improving individual care and for delineating more effective therapies for patients at high risk.

Indexed as

Computational BiologyBreast NeoplasmsDNA Copy Number VariationsGene Expression ProfilingHumansMicroRNAsOligonucleotide Array Sequence AnalysisSurvival AnalysisMicroRNAsBasal-likeBreast cancerCopy number aberrationGene expressionIntrinsic subtypesMicroRNAMolecular profileSignatureSurvival outcomeTriple-negative

Identifiers

PMID28351365
PMCPMC5370447

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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.