A clinically relevant gene signature in triple negative and basal-like breast cancer

  • Introduction: Current prognostic gene expression profiles for breast cancer mainly reflect proliferation status and are most useful in ER-positive cancers. Triple negative breast cancers (TNBC) are clinically heterogeneous and prognostic markers and biology-based therapies are needed to better treat this disease. Methods: We assembled Affymetrix gene expression data for 579 TNBC and performed unsupervised analysis to define metagenes that distinguish molecular subsets within TNBC. We used n = 394 cases for discovery and n = 185 cases for validation. Sixteen metagenes emerged that identified basal-like, apocrine and claudin-low molecular subtypes, or reflected various non-neoplastic cell populations, including immune cells, blood, adipocytes, stroma, angiogenesis and inflammation within the cancer. The expressions of these metagenes were correlated with survival and multivariate analysis was performed, including routine clinical and pathological variables. Results: Seventy-three percent of TNBC displayed basal-like molecular subtype that correlated with high histological grade and younger age. Survival of basal-like TNBC was not different from non basal-like TNBC. High expression of immune cell metagenes was associated with good and high expression of inflammation and angiogenesis-related metagenes were associated with poor prognosis. A ratio of high B-cell and low IL-8 metagenes identified 32% of TNBC with good prognosis (hazard ratio (HR) 0.37, 95% CI 0.22 to 0.61; P < 0.001) and was the only significant predictor in multivariate analysis including routine clinicopathological variables. Conclusions: We describe a ratio of high B-cell presence and low IL-8 activity as a powerful new prognostic marker for TNBC. Inhibition of the IL-8 pathway also represents an attractive novel therapeutic target for this disease.

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  • Additional file 1: Supplementary Figures S1 to S15. An Adobe file containing 15 supplementary figures (S1 to S15).

  • Additional file 2: Supplementary Tables S1 to S7. An Adobe file containing seven supplementary tables (S1 to S7).

  • Additional file 3: Supplementary Tables S8. An file containing a supplementary table (S8) containing lists of probesets and corresponding information from the supervised analysis by SAM.

  • Additional file 4: Supplementary Methods. An Adobe file containing supplementary information on methodology and six additional supplementary figures (S16 to S21), which are referred to within this supplementary methods.

  • Additional file 5: Supplementary R files. A zipped package containing an R script file of the analysis with respective links to the complete dataset files in GEO and a text file of the metagene probesets used in the R analysis.

  • 3262210.epubeng

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Author:Achim Rody, Thomas Karn, Cornelia Liedtke, Lajos Pusztai, Eugen Ruckhäberle, Lars Hanker, Regine Gätje, Christine Solbach, André Ahr, Dirk Metzler, Marcus Schmidt, Volkmar MüllerORCiDGND, Uwe Holtrich, Manfred KaufmannGND
Pubmed Id:https://pubmed.ncbi.nlm.nih.gov/21978456
Parent Title (English):Breast cancer research
Publisher:BioMed Central
Place of publication:London
Document Type:Article
Date of Publication (online):2012/11/16
Year of first Publication:2011
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2012/11/16
Issue:5, Art. R97
Page Number:12
First Page:1
Last Page:12
© 2011 Rody et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Institutes:Medizin / Medizin
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Licence (German):License LogoCreative Commons - Namensnennung 2.0