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Annals of Surgical Oncology

, Volume 26, Issue 10, pp 3344–3353 | Cite as

Clinicopathological Features of Triple-Negative Breast Cancer Epigenetic Subtypes

  • Maggie L. DiNome
  • Javier I. J. Orozco
  • Chikako Matsuba
  • Ayla O. Manughian-Peter
  • Miquel Ensenyat-Mendez
  • Shu-Ching Chang
  • John R. Jalas
  • Matthew P. Salomon
  • Diego M. MarzeseEmail author
Breast Oncology
  • 143 Downloads

Abstract

Background/Objective

Triple-negative breast cancer (TNBC) is a heterogeneous collection of breast tumors with numerous differences including morphological characteristics, genetic makeup, immune-cell infiltration, and response to systemic therapy. DNA methylation profiling is a robust tool to accurately identify disease-specific subtypes. We aimed to generate an epigenetic subclassification of TNBC tumors (epitypes) with utility for clinical decision-making.

Methods

Genome-wide DNA methylation profiles from TNBC patients generated in the Cancer Genome Atlas project were used to build machine learning-based epigenetic classifiers. Clinical and demographic variables, as well as gene expression and gene mutation data from the same cohort, were integrated to further refine the TNBC epitypes.

Results

This analysis indicated the existence of four TNBC epitypes, named as Epi-CL-A, Epi-CL-B, Epi-CL-C, and Epi-CL-D. Patients with Epi-CL-B tumors showed significantly shorter disease-free survival and overall survival [log rank; P = 0.01; hazard ratio (HR) 3.89, 95% confidence interval (CI) 1.3–11.63 and P = 0.003; HR 5.29, 95% CI 1.55–18.18, respectively]. Significant gene expression and mutation differences among the TNBC epitypes suggested alternative pathway activation that could be used as ancillary therapeutic targets. These epigenetic subtypes showed complementarity with the recently described TNBC transcriptomic subtypes.

Conclusions

TNBC epigenetic subtypes exhibit significant clinical and molecular differences. The links between genetic make-up, gene expression programs, and epigenetic subtypes open new avenues in the development of laboratory tests to more efficiently stratify TNBC patients, helping optimize tailored treatment approaches.

Notes

Acknowledgment

This work was supported by the Associates for Breast and Prostate Cancer Studies (ABCs) Foundation, the Fashion Footwear Association of New York (FFANY) Foundation, and the John Wayne Cancer Institute Translational Research Fund.

Disclosure

None of the authors have any financial disclosures. The authors declare no competing interests.

Supplementary material

10434_2019_7565_MOESM1_ESM.pdf (276 kb)
Supplementary material 1 (PDF 276 kb)
10434_2019_7565_MOESM2_ESM.pdf (299 kb)
Supplementary material 2 (PDF 299 kb)
10434_2019_7565_MOESM3_ESM.pdf (276 kb)
Supplementary material 3 (PDF 275 kb)

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Copyright information

© Society of Surgical Oncology 2019

Authors and Affiliations

  • Maggie L. DiNome
    • 1
  • Javier I. J. Orozco
    • 2
  • Chikako Matsuba
    • 3
  • Ayla O. Manughian-Peter
    • 2
  • Miquel Ensenyat-Mendez
    • 4
  • Shu-Ching Chang
    • 5
  • John R. Jalas
    • 6
  • Matthew P. Salomon
    • 3
  • Diego M. Marzese
    • 2
    Email author
  1. 1.Department of Surgery, David Geffen School of MedicineUniversity California Los Angeles (UCLA)Los AngelesUSA
  2. 2.Cancer Epigenetics LaboratoryJohn Wayne Cancer Institute at Providence Saint John’s Health CenterSanta MonicaUSA
  3. 3.Computational Biology LaboratoryJohn Wayne Cancer Institute at Providence St. John’s Health CenterSanta MonicaUSA
  4. 4.Cancer Cell Biology GroupBalearic Islands Health Research Institute (IdISBa)PalmaSpain
  5. 5.Medical Data Research CenterProvidence Saint Joseph HealthPortlandUSA
  6. 6.Department of PathologyProvidence Saint John’s Health CenterSanta MonicaUSA

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