Novel patterns of genome rearrangement and their association with survival in breast cancer

  1. James Hicks1,10,
  2. Alexander Krasnitz1,
  3. B. Lakshmi1,
  4. Nicholas E. Navin1,2,
  5. Michael Riggs1,
  6. Evan Leibu1,
  7. Diane Esposito1,
  8. Joan Alexander1,
  9. Jen Troge1,
  10. Vladimir Grubor1,
  11. Seungtai Yoon1,
  12. Michael Wigler1,
  13. Kenny Ye9,
  14. Anne-Lise Børresen-Dale3,4,
  15. Bjørn Naume5,
  16. Ellen Schlicting6,
  17. Larry Norton7,
  18. Torsten Hägerström8,
  19. Lambert Skoog8,
  20. Gert Auer8,
  21. Susanne Månér8,
  22. Pär Lundin8, and
  23. Anders Zetterberg8
  1. 1 Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA;
  2. 2 Watson School of Biological Sciences, Cold Spring Harbor, New York 11724, USA;
  3. 3 Department of Genetics, Institute for Cancer Research, Rikshospitalet-Radiumhospitalet Medical Center, 0310 Oslo, Norway;
  4. 4 Faculty of Medicine, University of Oslo, 0316 Oslo, Norway;
  5. 5 The Cancer Clinic, Rikshospitalet-Radiumhospitalet Medical Center, 0310 Oslo, Norway;
  6. 6 Department of Surgery, Ullevål Univ. Hospital, 0407 Oslo, Norway;
  7. 7 Memorial Sloan-Kettering Cancer Center, New York, New York 10021, USA;
  8. 8 Karolinska Institutet, Department of Oncology-Pathology, 171 76 Stockholm, Sweden;
  9. 9 Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York 10461, USA

Abstract

Representational Oligonucleotide Microarray Analysis (ROMA) detects genomic amplifications and deletions with boundaries defined at a resolution of ∼50 kb. We have used this technique to examine 243 breast tumors from two separate studies for which detailed clinical data were available. The very high resolution of this technology has enabled us to identify three characteristic patterns of genomic copy number variation in diploid tumors and to measure correlations with patient survival. One of these patterns is characterized by multiple closely spaced amplicons, or “firestorms,” limited to single chromosome arms. These multiple amplifications are highly correlated with aggressive disease and poor survival even when the rest of the genome is relatively quiet. Analysis of a selected subset of clinical material suggests that a simple genomic calculation, based on the number and proximity of genomic alterations, correlates with life-table estimates of the probability of overall survival in patients with primary breast cancer. Based on this sample, we generate the working hypothesis that copy number profiling might provide information useful in making clinical decisions, especially regarding the use or not of systemic therapies (hormonal therapy, chemotherapy), in the management of operable primary breast cancer with ostensibly good prognosis, for example, small, node-negative, hormone-receptor-positive diploid cases.

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