Evidence map›Paper›PMID 20576095›Full record

ArticleBreast cancer research : BCR2010

Genomic subtypes of breast cancer identified by array-comparative genomic hybridization display distinct molecular and clinical characteristics.

Göran Jönsson, Johan Staaf, Johan Vallon-Christersson, Markus Ringnér, Karolina Holm, Cecilia Hegardt, Haukur Gunnarsson, Rainer Fagerholm, Carina Strand, Bjarni A Agnarsson and 13 more

Open access · goldAbstract read
In one paragraph

Article in Breast cancer research : BCR, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 103 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
103citing papers in PubMed, 2 pooled it
14.2field-weighted citation impact, top 1% 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

103 citing papers in PubMed, 2 syntheses or guidelines pooled it, 194 citations in OpenAlex.

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  11. NETWORK DIFFERENTIAL CONNECTIVITY ANALYSIS.The annals of applied statistics · 2022
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  13. Landscape ofAnnals of translational medicine · 2022
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43 more citing papers are in PubMed but not listed here.

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

23 authors at 3 institutions in 3 countries.

Göran JönssonDepartment of Oncology, Clinical Sciences, Lund University and Skåne University Hospital, Barngatan 2B, 5 Lund, Sweden. goran_b.jonsson@med.lu.se
Johan Staaf
Johan Vallon-Christersson
Markus Ringnér
Karolina Holm
Cecilia Hegardt
Haukur Gunnarsson
Rainer Fagerholm
Carina Strand
Bjarni A Agnarsson
Outi Kilpivaara
Lena Luts
Päivi Heikkilä
Kristiina Aittomäki
Carl Blomqvist
Niklas Loman
Per Malmström
Håkan Olsson
Oskar Th Johannsson
Adalgeir Arason
Heli Nevanlinna
Rosa B Barkardottir
Ake Borg
Lund University · SEHelsinki University Hospital · FIReykjavík University · IS

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionBreast cancer is a profoundly heterogeneous disease with respect to biologic and clinical behavior. Gene-expression profiling has been used to dissect this complexity and to stratify tumors into intrinsic gene-expression subtypes, associated with distinct biology, patient outcome, and genomic alterations. Additionally, breast tumors occurring in individuals with germline BRCA1 or BRCA2 mutations typically fall into distinct subtypes.

methodsWe applied global DNA copy number and gene-expression profiling in 359 breast tumors. All tumors were classified according to intrinsic gene-expression subtypes and included cases from genetically predisposed women. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was used to identify significant DNA copy-number aberrations and genomic subgroups of breast cancer.

resultsWe identified 31 genomic regions that were highly amplified in > 1% of the 359 breast tumors. Several amplicons were found to co-occur, the 8p12 and 11q13.3 regions being the most frequent combination besides amplicons on the same chromosomal arm. Unsupervised hierarchical clustering with 133 significant GISTIC regions revealed six genomic subtypes, termed 17q12, basal-complex, luminal-simple, luminal-complex, amplifier, and mixed subtypes. Four of them had striking similarity to intrinsic gene-expression subtypes and showed associations to conventional tumor biomarkers and clinical outcome. However, luminal A-classified tumors were distributed in two main genomic subtypes, luminal-simple and luminal-complex, the former group having a better prognosis, whereas the latter group included also luminal B and the majority of BRCA2-mutated tumors. The basal-complex subtype displayed extensive genomic homogeneity and harbored the majority of BRCA1-mutated tumors. The 17q12 subtype comprised mostly HER2-amplified and HER2-enriched subtype tumors and had the worst prognosis. The amplifier and mixed subtypes contained tumors from all gene-expression subtypes, the former being enriched for 8p12-amplified cases, whereas the mixed subtype included many tumors with predominantly DNA copy-number losses and poor prognosis.

conclusionsGlobal DNA copy-number analysis integrated with gene-expression data can be used to dissect the complexity of breast cancer. This revealed six genomic subtypes with different clinical behavior and a striking concordance to the intrinsic subtypes. These genomic subtypes may prove useful for understanding the mechanisms of tumor development and for prognostic and treatment prediction purposes.

Indexed as

Comparative Genomic HybridizationGene Expression ProfilingAdultAgedAged, 80 and overBiomarkers, TumorBRCA1 ProteinBRCA2 ProteinBreast NeoplasmsFemaleFollow-Up StudiesGenetic Predisposition to DiseaseHumansMiddle AgedMutationNeoplasms, Basal CellBiomarkers, TumorBRCA1 ProteinBRCA2 Protein

Identifiers

PMID20576095
PMCPMC2917037
OpenAlexW2143186560

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.