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Series GSE80999 Query DataSets for GSE80999
Status Public on Mar 01, 2017
Title Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome
Organism Homo sapiens
Experiment type Expression profiling by array
Summary Background: 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.

Methods: Tumor tissue from 425 primary breast cancer patients of the Oslo2 study was cut and blended before being divided into fractions for DNA-, RNA- and protein isolation, and metabolomics, allowing for 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.

Results: Based on DNA copy number data, tumors were scored 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 using integrative clustering, tumors were classified into ten subtypes. The final consensus clustering incorporating all the 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 where 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 significant different outcome, and in another a trend was observed.

Conclusions: The herein identified six integrated subtypes confirm the heterogeneity of breast cancer and show that finer subdivisions of subtypes are evident. Increasing the knowledge of the luminal A subtype heterogeneity may add pivotal information guiding therapeutic choices, evidently bringing us closer to more personalized treatment for this largest subgroup of breast cancer.

 
Overall design The mRNA expression profiling of breast cancer samples was performed using the SurePrint G3 Human GE 8x60K one-color microarrays from Agilent (Agilent Technologies, Santa Clara, CA, USA) according to the manufacturer’s protocol (One-Color Microarray-Based Gene Expression Analysis, Low Input Quick Amp Labeling, v.6.5, May 2010). For each sample, 100 ng of RNA was amplified and hybridized on the array. Scanning was performed with Agilent Scanner G2565A, using AgilentG3_GX_1Color as profile. Signals were extracted using FE v.10.7.3.1 and protocol GE1_107_Sep09 (Agilent Technologies). Arrays were log2-transformed, quantile normalized and hospital-adjusted by subtracting from each probe value the mean probe value among samples from the same hospital.
 
Contributor(s) Aure MR, Vitelli V, Jernström S, Krohn M, Due EU, Haukaas TH, Leivonen S, Vollan HK, Kumar S, Lüders T, Rødland E, Vaske CJ, Zhao W, Møller EK, Nord S, Giskeødegård GF, Bathen TF, Caldas C, Tramm T, Alsner J, Overgaard J, Geisler J, Bukholm IR, Naume B, Schlichting E, Sauer T, Mills GB, Kåresen R, Mælandsmo GM, Lingjærde OC, Frigessi A, Kristensen VN, Børresen-Dale A, Sahlberg KK
Citation(s) 28356166, 31992741, 32242091
Submission date May 02, 2016
Last update date Apr 13, 2020
Contact name Miriam Ragle Aure
E-mail(s) mirrag@rr-research.no
Phone +47 22781363
Organization name Oslo University Hospital Radiumhospitalet
Department Dept. of Cancer Genetics
Street address Ullernchauséen 70
City Oslo
ZIP/Postal code 0310
Country Norway
 
Platforms (1)
GPL14550 Agilent-028004 SurePrint G3 Human GE 8x60K Microarray (Probe Name Version)
Samples (381)
GSM1403625 BreastTumor_OSL2U-0477T1
GSM1403626 BreastTumor_OSL2U-0252T1
GSM1403627 BreastTumor_OSL2U-0442T1
This SubSeries is part of SuperSeries:
GSE81002 Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome
Relations
BioProject PRJNA320292

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE80999_RAW.tar 4.5 Gb (http)(custom) TAR (of TXT)
Processed data included within Sample table

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