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Series GSE81540 Query DataSets for GSE81540
Status Public on Mar 12, 2018
Title Clinical Value of RNA Sequencing–Based Classifiers for Prediction of the Five Conventional Breast Cancer Biomarkers: A Report From the Population-Based Multicenter Sweden Cancerome Analysis Network—Breast Initiative [superseries]
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Summary This SuperSeries is composed of the SubSeries GSE81538 [cohort 405] and GSE96058 [cohort 3273] linked to below.

PURPOSE
In early breast cancer (BC), five conventional biomarkers—estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), Ki67, and Nottingham histologic grade (NHG)—are used to determine prognosis and treatment. We aimed to develop classifiers for these biomarkers that were based on tumor mRNA sequencing (RNA-seq), compare classification performance, and test whether such predictors could add value for risk stratification.

METHODS
In total, 3,678 patients with BC were studied. For 405 tumors, a comprehensive multi-rater histopathologic evaluation was performed. Using RNA-seq data, single-gene classifiers and multigene classifiers (MGCs) were trained on consensus histopathology labels. Trained classifiers were tested on a prospective population-based series of 3,273 BCs that included a median follow-up of 52 months (Sweden Cancerome Analysis Network—Breast [SCAN-B], ClinicalTrials.gov identifier: NCT02306096), and results were evaluated by agreement statistics and Kaplan-Meier and Cox survival analyses.

RESULTS
Pathologist concordance was high for ER, PgR, and HER2 (average κ, 0.920, 0.891, and 0.899, respectively) but moderate for Ki67 and NHG (average κ, 0.734 and 0.581). Concordance between RNA-seq classifiers and histopathology for the independent cohort of 3,273 was similar to interpathologist concordance. Patients with discordant classifications, predicted as hormone responsive by histopathology but non–hormone responsive by MGC, had significantly inferior overall survival compared with patients who had concordant results. This extended to patients who received no adjuvant therapy (hazard ratio [HR], 3.19; 95% CI, 1.19 to 8.57), or endocrine therapy alone (HR, 2.64; 95% CI, 1.55 to 4.51). For cases identified as hormone responsive by histopathology and who received endocrine therapy alone, the MGC hormone-responsive classifier remained significant after multivariable adjustment (HR, 2.45; 95% CI, 1.39 to 4.34).

CONCLUSION
Classification error rates for RNA-seq–based classifiers for the five key BC biomarkers generally were equivalent to conventional histopathology. However, RNA-seq classifiers provided added clinical value in particular for tumors determined by histopathology to be hormone responsive but by RNA-seq to be hormone insensitive.
 
Overall design Refer to individual Series.
 
Citation(s) 32913985, 32926574, 33937624, 35304506
Christian Brueffer, Johan Vallon-Christersson, Dorthe Grabau, Anna Ehinger, Jari Häkkinen, Cecilia Hegardt, Janne Malina, Yilun Chen, Pär-Ola Bendahl, Jonas Manjer, Martin Malmberg, Christer Larsson, Niklas Loman, Lisa Rydén, Åke Borg, and Lao H. Saal. Clinical Value of RNA Sequencing-Based Classifiers for Prediction of the Five Conventional Breast Cancer Biomarkers: A Report From the Population-Based Multicenter Sweden Cancerome Analysis Network—Breast Initiative. JCO Precision Oncology 2018;2:1-18. DOI: 10.1200/PO.17.00135
Submission date May 17, 2016
Last update date May 04, 2022
Contact name Lao H Saal
E-mail(s) lao.saal@med.lu.se
Organization name Lund University
Department Department of Oncology and Pathology
Lab Translational Oncogenomics Unit
Street address Scheelevägen 2, MV404B2
City Lund
ZIP/Postal code 22391
Country Sweden
 
Platforms (2)
GPL11154 Illumina HiSeq 2000 (Homo sapiens)
GPL18573 Illumina NextSeq 500 (Homo sapiens)
Samples (3814)
GSM2155558 T1
GSM2155559 T2
GSM2155560 T3
This SuperSeries is composed of the following SubSeries:
GSE81538 Clinical Value of RNA Sequencing–Based Classifiers for Prediction of the Five Conventional Breast Cancer Biomarkers: A Report From the Population-Based Multicenter Sweden Cancerome Analysis Network—Breast Initiative [cohort 405]
GSE96058 Clinical Value of RNA Sequencing–Based Classifiers for Prediction of the Five Conventional Breast Cancer Biomarkers: A Report From the Population-Based Multicenter Sweden Cancerome Analysis Network—Breast Initiative [cohort 3273]
Relations
BioProject PRJNA321906

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