Genes associated with histopathologic features of triple negative breast tumors predict molecular subtypes

Kristen S Purrington^{1

2}, Daniel W Visscher³, Chen Wang², Drakoulis Yannoukakos⁴, Ute Hamann⁵, Heli Nevanlinna⁶, Angela Cox⁷, Graham G Giles⁸, Jeanette E Eckel-Passow², Sotiris Lakis⁹, Vassiliki Kotoula⁹, George Fountzilas⁹, Maria Kabisch⁵, Thomas Rüdiger¹⁰, Päivi Heikkilä¹¹, Carl Blomqvist¹², Simon S Cross¹³, Melissa C Southey¹⁴, Janet E Olson², Judy Gilbert³, Sandra Deming-Halverson¹⁵, Veli-Matti Kosma^{16

17}, Christine Clarke¹⁸, Rodney Scott¹⁹, J Louise Jones²⁰, Wei Zheng¹⁵, Arto Mannermaa^{16

17}; Jane Carpenter for ABCTC Investigators; Diana M Eccles²¹, Celine M Vachon², Fergus J Couch^{22

23}

Affiliations

¹ Department of Oncology, Wayne State University School of Medicine and Karmanos Cancer Institute, Detroit, USA.
² Department of Health Sciences Research, Mayo Clinic, Stabile 2-42, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
³ Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, USA.
⁴ Molecular Diagnostics Laboratory INRASTES, National Centre for Scientific Research "Demokritos", Athens, Greece.
⁵ Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany.
⁶ Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland.
⁷ Department of Oncology, University of Sheffield, Sheffield, UK.
⁸ Cancer Epidemiology Centre, The Cancer Council Victoria, Melbourne, Australia.
⁹ Laboratory of Molecular Oncology, Hellenic Foundation for Cancer Research, Aristotle University of Thessaloniki School of Medicine, Thessaloniki, Greece.
¹⁰ Institute of Pathology, Städtisches Klinikum Karlsruhe, Karlsruhe, Germany.
¹¹ Department of Pathology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland.
¹² Department of Oncology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland.
¹³ Department of Neuroscience, University of Sheffield, Sheffield, UK.
¹⁴ Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Melbourne, Australia.
¹⁵ Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, USA.
¹⁶ Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Kuopio, Finland.
¹⁷ School of Medicine, Institute of Clinical Medicine, Pathology and Forensic Medicine, Biocenter Kuopio, Cancer Center of Eastern Finland, University of Eastern Finland, Kuopio, Finland.
¹⁸ Centre for Cancer Research, University of Sydney at the Westmead Millennium Institute, Westmead, Australia.
¹⁹ Division of Genetics, Hunter Area Pathology Service and University of Newcastle, Newcastle, Australia.
²⁰ Barts Cancer Research Institute, Queen Mary University of London, London, UK.
²¹ Faculty of Medicine and NIHR/CRUK Clinical Trials Unit, University of Southampton, Southampton, UK.
²² Department of Health Sciences Research, Mayo Clinic, Stabile 2-42, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA. couch.fergus@mayo.edu.
²³ Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, USA. couch.fergus@mayo.edu.

PMID: 27083182
PMCID: PMC5400013
DOI: 10.1007/s10549-016-3775-2

Genes associated with histopathologic features of triple negative breast tumors predict molecular subtypes

Kristen S Purrington et al. Breast Cancer Res Treat. 2016 May.

. 2016 May;157(1):117-31.

doi: 10.1007/s10549-016-3775-2. Epub 2016 Apr 15.

Authors

Affiliations

¹ Department of Oncology, Wayne State University School of Medicine and Karmanos Cancer Institute, Detroit, USA.
² Department of Health Sciences Research, Mayo Clinic, Stabile 2-42, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
³ Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, USA.
⁴ Molecular Diagnostics Laboratory INRASTES, National Centre for Scientific Research "Demokritos", Athens, Greece.
⁵ Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany.
⁶ Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland.
⁷ Department of Oncology, University of Sheffield, Sheffield, UK.
⁸ Cancer Epidemiology Centre, The Cancer Council Victoria, Melbourne, Australia.
⁹ Laboratory of Molecular Oncology, Hellenic Foundation for Cancer Research, Aristotle University of Thessaloniki School of Medicine, Thessaloniki, Greece.
¹⁰ Institute of Pathology, Städtisches Klinikum Karlsruhe, Karlsruhe, Germany.
¹¹ Department of Pathology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland.
¹² Department of Oncology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland.
¹³ Department of Neuroscience, University of Sheffield, Sheffield, UK.
¹⁴ Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Melbourne, Australia.
¹⁵ Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, USA.
¹⁶ Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Kuopio, Finland.
¹⁷ School of Medicine, Institute of Clinical Medicine, Pathology and Forensic Medicine, Biocenter Kuopio, Cancer Center of Eastern Finland, University of Eastern Finland, Kuopio, Finland.
¹⁸ Centre for Cancer Research, University of Sydney at the Westmead Millennium Institute, Westmead, Australia.
¹⁹ Division of Genetics, Hunter Area Pathology Service and University of Newcastle, Newcastle, Australia.
²⁰ Barts Cancer Research Institute, Queen Mary University of London, London, UK.
²¹ Faculty of Medicine and NIHR/CRUK Clinical Trials Unit, University of Southampton, Southampton, UK.
²² Department of Health Sciences Research, Mayo Clinic, Stabile 2-42, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA. couch.fergus@mayo.edu.
²³ Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, USA. couch.fergus@mayo.edu.

PMID: 27083182
PMCID: PMC5400013
DOI: 10.1007/s10549-016-3775-2

Abstract

Distinct subtypes of triple negative (TN) breast cancer have been identified by tumor expression profiling. However, little is known about the relationship between histopathologic features of TN tumors, which reflect aspects of both tumor behavior and tumor microenvironment, and molecular TN subtypes. The histopathologic features of TN tumors were assessed by central review and 593 TN tumors were subjected to whole genome expression profiling using the Illumina Whole Genome DASL array. TN molecular subtypes were defined based on gene expression data associated with histopathologic features of TN tumors. Gene expression analysis yielded signatures for four TN subtypes (basal-like, androgen receptor positive, immune, and stromal) consistent with previous studies. Expression analysis also identified genes significantly associated with the 12 histological features of TN tumors. Development of signatures using these markers of histopathological features resulted in six distinct TN subtype signatures, including an additional basal-like and stromal signature. The additional basal-like subtype was distinguished by elevated expression of cell motility and glucose metabolism genes and reduced expression of immune signaling genes, whereas the additional stromal subtype was distinguished by elevated expression of immunomodulatory pathway genes. Histopathologic features that reflect heterogeneity in tumor architecture, cell structure, and tumor microenvironment are related to TN subtype. Accounting for histopathologic features in the development of gene expression signatures, six major subtypes of TN breast cancer were identified.

Keywords: Breast cancer; Gene expression; Germline mutation; Pathology; Tumor biology.

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Figures

**Figure 1. Clustering robustness using 2,158 agnostic probes**
a) A plot of Hartigan score values from the Engelman-Hartigan test for two through ten clusters. The yellow highlighted area indicates the threshold below which additional clusters should not be added. b) The consensus cumulative distribution functions (CDF) for each solution from two to ten clusters. c) The delta area, or the relative change in the area under the consensus CDF curve for each solution from two to ten clusters.

**Figure 2. Agnostic TN subtypes**
A heat map of the 177 genes that were significantly different across four agnostic TN subtypes. Red indicates up-regulated genes; green represents down-regulated genes compared to the mean. Each of the four subtypes is clustered as shown by the dendogram and samples are color coded by subtype: black=BL, red=LAR, green=IM, blue=STR. Enriched ontologies by GSEA corresponding to each of the four subtypes are listed next to the genes that were significantly up-regulated in clusters.

**Figure 3. Clustering robustness using 2,776 pathology-based probes**
a) A plot of Hartigan score values from the Engelman-Hartigan test for two through ten clusters. The yellow highlighted area indicates the threshold below which additional clusters should not be added. b) The consensus cumulative distribution functions (CDF) for each solution from two to ten clusters. c) The delta area, or the relative change in the area under the consensus CDF curve for each solution from two to ten clusters.

**Figure 4. Phenotype-driven TN subtypes**
A heat map of the 185 genes that were significantly different across the six phenotype-driven TN subtypes. Red indicates up-regulated genes; green represents down-regulated genes compared to the mean. Each of the six subtypes is clustered as shown by the dendogram and samples are color coded by subtype: black=P-BL1, red=P-BL2, green=P-LAR, blue=P-IM, cyan=P-STR1, purple=P-STR2. Enriched ontologies by GSEA corresponding to each of the six subtypes are listed next to the group of genes that were significantly up-regulated in clusters.

See this image and copyright information in PMC

References

1. Foulkes WD, Smith IE, Reis-Filho JS. Triple-negative breast cancer. N Engl J Med. 2010;363(20):1938–1948. doi:10.1056/NEJMra1001389. - PubMed
1. American Cancer Society . Breast Cancer Facts & Figures, 2011-2012. American Cancer Society; Atlanta, GA: 2012.
1. Perou CM. Molecular stratification of triple-negative breast cancers. Oncologist. 2010;15(Suppl 5):39–48. doi:15/suppl_5/39 [pii] 10.1634/theoncologist.2010-S5-39. - PubMed
1. Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, Pollack JR, Ross DT, Johnsen H, Akslen LA, Fluge O, Pergamenschikov A, Williams C, Zhu SX, Lonning PE, Borresen-Dale AL, Brown PO, Botstein D. Molecular portraits of human breast tumours. Nature. 2000;406(6797):747–752. doi:10.1038/35021093. - PubMed
1. Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS, Thorsen T, Quist H, Matese JC, Brown PO, Botstein D, Eystein Lonning P, Borresen-Dale AL. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A. 2001;98(19):10869–10874. doi:10.1073/pnas.191367098 98/19/10869 [pii] - PMC - PubMed

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Genes associated with histopathologic features of triple negative breast tumors predict molecular subtypes

Affiliations

Genes associated with histopathologic features of triple negative breast tumors predict molecular subtypes

Authors

Affiliations

Abstract

Figures

References

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MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

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