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Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome

Overview of attention for article published in Breast Cancer Research, March 2017
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  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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7 tweeters

Citations

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71 Dimensions

Readers on

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112 Mendeley
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Title
Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome
Published in
Breast Cancer Research, March 2017
DOI 10.1186/s13058-017-0812-y
Pubmed ID
Authors

Miriam Ragle Aure, Valeria Vitelli, Sandra Jernström, Surendra Kumar, Marit Krohn, Eldri U. Due, Tonje Husby Haukaas, Suvi-Katri Leivonen, Hans Kristian Moen Vollan, Torben Lüders, Einar Rødland, Charles J. Vaske, Wei Zhao, Elen K. Møller, Silje Nord, Guro F. Giskeødegård, Tone Frost Bathen, Carlos Caldas, Trine Tramm, Jan Alsner, Jens Overgaard, Jürgen Geisler, Ida R. K. Bukholm, Bjørn Naume, Ellen Schlichting, Torill Sauer, Gordon B. Mills, Rolf Kåresen, Gunhild M. Mælandsmo, Ole Christian Lingjærde, Arnoldo Frigessi, Vessela N. Kristensen, Anne-Lise Børresen-Dale, Kristine K. Sahlberg

Abstract

Breast cancer is a heterogeneous disease at the clinical and molecular level. In this study we integrate classifications extracted from five different molecular levels in order to identify integrated subtypes. Tumor tissue from 425 patients with primary breast cancer from the Oslo2 study was cut and blended, and divided into fractions for DNA, RNA and protein isolation and metabolomics, allowing the acquisition of representative and comparable molecular data. Patients were stratified into groups based on their tumor characteristics from five different molecular levels, using various clustering methods. Finally, all previously identified and newly determined subgroups were combined in a multilevel classification using a "cluster-of-clusters" approach with consensus clustering. Based on DNA copy number data, tumors were categorized into three groups according to the complex arm aberration index. mRNA expression profiles divided tumors into five molecular subgroups according to PAM50 subtyping, and clustering based on microRNA expression revealed four subgroups. Reverse-phase protein array data divided tumors into five subgroups. Hierarchical clustering of tumor metabolic profiles revealed three clusters. Combining DNA copy number and mRNA expression classified tumors into seven clusters based on pathway activity levels, and tumors were classified into ten subtypes using integrative clustering. The final consensus clustering that incorporated all aforementioned subtypes revealed six major groups. Five corresponded well with the mRNA subtypes, while a sixth group resulted from a split of the luminal A subtype; these tumors belonged to distinct microRNA clusters. Gain-of-function studies using MCF-7 cells showed that microRNAs differentially expressed between the luminal A clusters were important for cancer cell survival. These microRNAs were used to validate the split in luminal A tumors in four independent breast cancer cohorts. In two cohorts the microRNAs divided tumors into subgroups with significantly different outcomes, and in another a trend was observed. The six integrated subtypes identified confirm the heterogeneity of breast cancer and show that finer subdivisions of subtypes are evident. Increasing knowledge of the heterogeneity of the luminal A subtype may add pivotal information to guide therapeutic choices, evidently bringing us closer to improved treatment for this largest subgroup of breast cancer.

Twitter Demographics

The data shown below were collected from the profiles of 7 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 112 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 22%
Researcher 17 15%
Student > Master 17 15%
Student > Bachelor 7 6%
Student > Doctoral Student 6 5%
Other 18 16%
Unknown 22 20%
Readers by discipline Count As %
Medicine and Dentistry 24 21%
Biochemistry, Genetics and Molecular Biology 21 19%
Agricultural and Biological Sciences 17 15%
Computer Science 9 8%
Chemistry 4 4%
Other 11 10%
Unknown 26 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 October 2017.
All research outputs
#3,351,070
of 11,923,653 outputs
Outputs from Breast Cancer Research
#492
of 1,360 outputs
Outputs of similar age
#92,048
of 265,750 outputs
Outputs of similar age from Breast Cancer Research
#11
of 20 outputs
Altmetric has tracked 11,923,653 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 1,360 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.9. This one has gotten more attention than average, scoring higher than 63% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 265,750 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.