Selective genomic copy number imbalances and probability of recurrence in early-stage breast cancer

Patricia A. Thompson, Abenaa M. Brewster, Do Kim-Anh, Veerabhadran Baladandayuthapani, Bradley M. Broom, Mary E. Edgerton, Karin M. Hahn, James L. Murray, Aysegul Sahin, Spyros Tsavachidis, Yuker Wang, Li Zhang, Gabriel N. Hortobagyi, Gordon Mills, Melissa L. Bondy

Research output: Contribution to journalArticle

31 Citations (Scopus)

Abstract

A number of studies of copy number imbalances (CNIs) in breast tumors support associations between individual CNIs and patient outcomes. However, no pattern or signature of CNIs has emerged for clinical use. We determined copy number (CN) gains and losses using high-density molecular inversion probe (MIP) arrays for 971 stage I/II breast tumors and applied a boosting strategy to fit hazards models for CN and recurrence, treating chromosomal segments in a dose-specific fashion (-1 [loss], 0 [no change] and +1 [gain]). The concordance index (C-Index) was used to compare prognostic accuracy between a training (n = 728) and test (n = 243) set and across models. Twelve novel prognostic CNIs were identified: losses at 1p12, 12q13.13, 13q12.3, 22q11, and Xp21, and gains at 2p11.1, 3q13.12, 10p11.21, 10q23.1, 11p15, 14q13.2-q13.3, and 17q21.33. In addition, seven CNIs previously implicated as prognostic markers were selected: losses at 8p22 and 16p11.2 and gains at 10p13, 11q13.5, 12p13, 20q13, and Xq28. For all breast cancers combined, the final full model including 19 CNIs, clinical covariates, and tumor marker-approximated subtypes (estrogen receptor [ER], progesterone receptor, ERBB2 amplification, and Ki67) significantly outperformed a model containing only clinical covariates and tumor subtypes (C-Index full model, train[test] = 0.72[0.71] ± 0.02 vs. C-Index clinical + subtype model, train[test] = 0.62[0.62] ± 0.02; p<10 -6). In addition, the full model containing 19 CNIs significantly improved prognostication separately for ER-, HER2+, luminal B, and triple negative tumors over clinical variables alone. In summary, we show that a set of 19 CNIs discriminates risk of recurrence among early-stage breast tumors, independent of ER status. Further, our data suggest the presence of specific CNIs that promote and, in some cases, limit tumor spread.

Original languageEnglish (US)
Article numbere23543
JournalPLoS One
Volume6
Issue number8
DOIs
StatePublished - Aug 18 2011
Externally publishedYes

Fingerprint

breast neoplasms
Tumors
Estrogen Receptors
Breast Neoplasms
genomics
Recurrence
neoplasms
Molecular Probes
Neoplasms
Progesterone Receptors
Tumor Biomarkers
Proportional Hazards Models
Biomarkers
testing
Amplification
Hazards
dosage
estrogen receptors

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Cite this

Thompson, P. A., Brewster, A. M., Kim-Anh, D., Baladandayuthapani, V., Broom, B. M., Edgerton, M. E., ... Bondy, M. L. (2011). Selective genomic copy number imbalances and probability of recurrence in early-stage breast cancer. PLoS One, 6(8), [e23543]. https://doi.org/10.1371/journal.pone.0023543

Selective genomic copy number imbalances and probability of recurrence in early-stage breast cancer. / Thompson, Patricia A.; Brewster, Abenaa M.; Kim-Anh, Do; Baladandayuthapani, Veerabhadran; Broom, Bradley M.; Edgerton, Mary E.; Hahn, Karin M.; Murray, James L.; Sahin, Aysegul; Tsavachidis, Spyros; Wang, Yuker; Zhang, Li; Hortobagyi, Gabriel N.; Mills, Gordon; Bondy, Melissa L.

In: PLoS One, Vol. 6, No. 8, e23543, 18.08.2011.

Research output: Contribution to journalArticle

Thompson, PA, Brewster, AM, Kim-Anh, D, Baladandayuthapani, V, Broom, BM, Edgerton, ME, Hahn, KM, Murray, JL, Sahin, A, Tsavachidis, S, Wang, Y, Zhang, L, Hortobagyi, GN, Mills, G & Bondy, ML 2011, 'Selective genomic copy number imbalances and probability of recurrence in early-stage breast cancer', PLoS One, vol. 6, no. 8, e23543. https://doi.org/10.1371/journal.pone.0023543
Thompson PA, Brewster AM, Kim-Anh D, Baladandayuthapani V, Broom BM, Edgerton ME et al. Selective genomic copy number imbalances and probability of recurrence in early-stage breast cancer. PLoS One. 2011 Aug 18;6(8). e23543. https://doi.org/10.1371/journal.pone.0023543
Thompson, Patricia A. ; Brewster, Abenaa M. ; Kim-Anh, Do ; Baladandayuthapani, Veerabhadran ; Broom, Bradley M. ; Edgerton, Mary E. ; Hahn, Karin M. ; Murray, James L. ; Sahin, Aysegul ; Tsavachidis, Spyros ; Wang, Yuker ; Zhang, Li ; Hortobagyi, Gabriel N. ; Mills, Gordon ; Bondy, Melissa L. / Selective genomic copy number imbalances and probability of recurrence in early-stage breast cancer. In: PLoS One. 2011 ; Vol. 6, No. 8.
@article{991c365809a345eb8de9d483638aa9b0,
title = "Selective genomic copy number imbalances and probability of recurrence in early-stage breast cancer",
abstract = "A number of studies of copy number imbalances (CNIs) in breast tumors support associations between individual CNIs and patient outcomes. However, no pattern or signature of CNIs has emerged for clinical use. We determined copy number (CN) gains and losses using high-density molecular inversion probe (MIP) arrays for 971 stage I/II breast tumors and applied a boosting strategy to fit hazards models for CN and recurrence, treating chromosomal segments in a dose-specific fashion (-1 [loss], 0 [no change] and +1 [gain]). The concordance index (C-Index) was used to compare prognostic accuracy between a training (n = 728) and test (n = 243) set and across models. Twelve novel prognostic CNIs were identified: losses at 1p12, 12q13.13, 13q12.3, 22q11, and Xp21, and gains at 2p11.1, 3q13.12, 10p11.21, 10q23.1, 11p15, 14q13.2-q13.3, and 17q21.33. In addition, seven CNIs previously implicated as prognostic markers were selected: losses at 8p22 and 16p11.2 and gains at 10p13, 11q13.5, 12p13, 20q13, and Xq28. For all breast cancers combined, the final full model including 19 CNIs, clinical covariates, and tumor marker-approximated subtypes (estrogen receptor [ER], progesterone receptor, ERBB2 amplification, and Ki67) significantly outperformed a model containing only clinical covariates and tumor subtypes (C-Index full model, train[test] = 0.72[0.71] ± 0.02 vs. C-Index clinical + subtype model, train[test] = 0.62[0.62] ± 0.02; p<10 -6). In addition, the full model containing 19 CNIs significantly improved prognostication separately for ER-, HER2+, luminal B, and triple negative tumors over clinical variables alone. In summary, we show that a set of 19 CNIs discriminates risk of recurrence among early-stage breast tumors, independent of ER status. Further, our data suggest the presence of specific CNIs that promote and, in some cases, limit tumor spread.",
author = "Thompson, {Patricia A.} and Brewster, {Abenaa M.} and Do Kim-Anh and Veerabhadran Baladandayuthapani and Broom, {Bradley M.} and Edgerton, {Mary E.} and Hahn, {Karin M.} and Murray, {James L.} and Aysegul Sahin and Spyros Tsavachidis and Yuker Wang and Li Zhang and Hortobagyi, {Gabriel N.} and Gordon Mills and Bondy, {Melissa L.}",
year = "2011",
month = "8",
day = "18",
doi = "10.1371/journal.pone.0023543",
language = "English (US)",
volume = "6",
journal = "PLoS One",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "8",

}

TY - JOUR

T1 - Selective genomic copy number imbalances and probability of recurrence in early-stage breast cancer

AU - Thompson, Patricia A.

AU - Brewster, Abenaa M.

AU - Kim-Anh, Do

AU - Baladandayuthapani, Veerabhadran

AU - Broom, Bradley M.

AU - Edgerton, Mary E.

AU - Hahn, Karin M.

AU - Murray, James L.

AU - Sahin, Aysegul

AU - Tsavachidis, Spyros

AU - Wang, Yuker

AU - Zhang, Li

AU - Hortobagyi, Gabriel N.

AU - Mills, Gordon

AU - Bondy, Melissa L.

PY - 2011/8/18

Y1 - 2011/8/18

N2 - A number of studies of copy number imbalances (CNIs) in breast tumors support associations between individual CNIs and patient outcomes. However, no pattern or signature of CNIs has emerged for clinical use. We determined copy number (CN) gains and losses using high-density molecular inversion probe (MIP) arrays for 971 stage I/II breast tumors and applied a boosting strategy to fit hazards models for CN and recurrence, treating chromosomal segments in a dose-specific fashion (-1 [loss], 0 [no change] and +1 [gain]). The concordance index (C-Index) was used to compare prognostic accuracy between a training (n = 728) and test (n = 243) set and across models. Twelve novel prognostic CNIs were identified: losses at 1p12, 12q13.13, 13q12.3, 22q11, and Xp21, and gains at 2p11.1, 3q13.12, 10p11.21, 10q23.1, 11p15, 14q13.2-q13.3, and 17q21.33. In addition, seven CNIs previously implicated as prognostic markers were selected: losses at 8p22 and 16p11.2 and gains at 10p13, 11q13.5, 12p13, 20q13, and Xq28. For all breast cancers combined, the final full model including 19 CNIs, clinical covariates, and tumor marker-approximated subtypes (estrogen receptor [ER], progesterone receptor, ERBB2 amplification, and Ki67) significantly outperformed a model containing only clinical covariates and tumor subtypes (C-Index full model, train[test] = 0.72[0.71] ± 0.02 vs. C-Index clinical + subtype model, train[test] = 0.62[0.62] ± 0.02; p<10 -6). In addition, the full model containing 19 CNIs significantly improved prognostication separately for ER-, HER2+, luminal B, and triple negative tumors over clinical variables alone. In summary, we show that a set of 19 CNIs discriminates risk of recurrence among early-stage breast tumors, independent of ER status. Further, our data suggest the presence of specific CNIs that promote and, in some cases, limit tumor spread.

AB - A number of studies of copy number imbalances (CNIs) in breast tumors support associations between individual CNIs and patient outcomes. However, no pattern or signature of CNIs has emerged for clinical use. We determined copy number (CN) gains and losses using high-density molecular inversion probe (MIP) arrays for 971 stage I/II breast tumors and applied a boosting strategy to fit hazards models for CN and recurrence, treating chromosomal segments in a dose-specific fashion (-1 [loss], 0 [no change] and +1 [gain]). The concordance index (C-Index) was used to compare prognostic accuracy between a training (n = 728) and test (n = 243) set and across models. Twelve novel prognostic CNIs were identified: losses at 1p12, 12q13.13, 13q12.3, 22q11, and Xp21, and gains at 2p11.1, 3q13.12, 10p11.21, 10q23.1, 11p15, 14q13.2-q13.3, and 17q21.33. In addition, seven CNIs previously implicated as prognostic markers were selected: losses at 8p22 and 16p11.2 and gains at 10p13, 11q13.5, 12p13, 20q13, and Xq28. For all breast cancers combined, the final full model including 19 CNIs, clinical covariates, and tumor marker-approximated subtypes (estrogen receptor [ER], progesterone receptor, ERBB2 amplification, and Ki67) significantly outperformed a model containing only clinical covariates and tumor subtypes (C-Index full model, train[test] = 0.72[0.71] ± 0.02 vs. C-Index clinical + subtype model, train[test] = 0.62[0.62] ± 0.02; p<10 -6). In addition, the full model containing 19 CNIs significantly improved prognostication separately for ER-, HER2+, luminal B, and triple negative tumors over clinical variables alone. In summary, we show that a set of 19 CNIs discriminates risk of recurrence among early-stage breast tumors, independent of ER status. Further, our data suggest the presence of specific CNIs that promote and, in some cases, limit tumor spread.

UR - http://www.scopus.com/inward/record.url?scp=80051660868&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80051660868&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0023543

DO - 10.1371/journal.pone.0023543

M3 - Article

C2 - 21858162

AN - SCOPUS:80051660868

VL - 6

JO - PLoS One

JF - PLoS One

SN - 1932-6203

IS - 8

M1 - e23543

ER -