Relative Prognostic and Predictive Value of Gene Signature and Histologic Grade in Estrogen Receptor-Positive, HER2-Negative Breast Cancer

Takayuki Iwamoto, Catherine Kelly, Taeko Mizoo, Tomohiro Nogami, Takayuki Motoki, Tadahiko Shien, Naruto Taira, Naoki Hayashi, Naoki Niikura, Toshiyoshi Fujiwara, Hiroyoshi Doihara, Junji Matsuoka

Research output: Contribution to journalArticle

Abstract

Background: In estrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer, first-generation genomic signatures serve predominately as prognostic biomarkers and secondarily as predictors of response to chemotherapy. We compared both the prognostic and predictive value of histologic grades and genomic markers. Methods: We retrieved publicly available cDNA microarray data from 1373 primary ER+/HER2- breast cancers and developed a genomic signature simulated from Recurrence Online (http://www.recurrenceonline.com/) to calculate the recurrence score and risk using predefined sets of genes in the cDNA microarray. We then compared the prognostic and predictive information provided by histologic grade and genomic signature. Results: Based on genomic signatures, 55%, 28%, and 17% of breast cancers were classified as low, intermediate, and high risk, respectively, whereas the histologic grades were I, II, and III in 22%, 59%, and 19% of breast cancers, respectively. Univariate analysis in the untreated cohort revealed that both histologic grade (overall P = .007) and genomic signature (P <.001) could predict prognosis. Results were similar using the genomic signature, with pathologic complete response rates of 4.6%, 5.7%, and 16.5% for low-, intermediate-, and high-risk cancers, respectively. Neither biomarker was statistically significant in multivariate analysis for predictive response to neoadjuvant chemotherapy (NAC). Conclusion: Genomic signature was better at identifying low-risk cases compared to histologic grade alone, but both markers had similar predictive values for NAC response. Better predictive biomarkers for NAC response are still needed.

Original languageEnglish
JournalClinical Breast Cancer
DOIs
Publication statusAccepted/In press - Jul 29 2015

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Estrogen Receptors
Breast Neoplasms
Drug Therapy
Biomarkers
Oligonucleotide Array Sequence Analysis
Genes
Recurrence
Multivariate Analysis
human ERBB2 protein
Neoplasms

Keywords

  • Breast cancer
  • Chemotherapy response
  • Genomic marker
  • Grade
  • Predictive marker

ASJC Scopus subject areas

  • Cancer Research
  • Oncology

Cite this

@article{3f8f1af7113946f9acc62d533cd8191d,
title = "Relative Prognostic and Predictive Value of Gene Signature and Histologic Grade in Estrogen Receptor-Positive, HER2-Negative Breast Cancer",
abstract = "Background: In estrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer, first-generation genomic signatures serve predominately as prognostic biomarkers and secondarily as predictors of response to chemotherapy. We compared both the prognostic and predictive value of histologic grades and genomic markers. Methods: We retrieved publicly available cDNA microarray data from 1373 primary ER+/HER2- breast cancers and developed a genomic signature simulated from Recurrence Online (http://www.recurrenceonline.com/) to calculate the recurrence score and risk using predefined sets of genes in the cDNA microarray. We then compared the prognostic and predictive information provided by histologic grade and genomic signature. Results: Based on genomic signatures, 55{\%}, 28{\%}, and 17{\%} of breast cancers were classified as low, intermediate, and high risk, respectively, whereas the histologic grades were I, II, and III in 22{\%}, 59{\%}, and 19{\%} of breast cancers, respectively. Univariate analysis in the untreated cohort revealed that both histologic grade (overall P = .007) and genomic signature (P <.001) could predict prognosis. Results were similar using the genomic signature, with pathologic complete response rates of 4.6{\%}, 5.7{\%}, and 16.5{\%} for low-, intermediate-, and high-risk cancers, respectively. Neither biomarker was statistically significant in multivariate analysis for predictive response to neoadjuvant chemotherapy (NAC). Conclusion: Genomic signature was better at identifying low-risk cases compared to histologic grade alone, but both markers had similar predictive values for NAC response. Better predictive biomarkers for NAC response are still needed.",
keywords = "Breast cancer, Chemotherapy response, Genomic marker, Grade, Predictive marker",
author = "Takayuki Iwamoto and Catherine Kelly and Taeko Mizoo and Tomohiro Nogami and Takayuki Motoki and Tadahiko Shien and Naruto Taira and Naoki Hayashi and Naoki Niikura and Toshiyoshi Fujiwara and Hiroyoshi Doihara and Junji Matsuoka",
year = "2015",
month = "7",
day = "29",
doi = "10.1016/j.clbc.2015.10.004",
language = "English",
journal = "Clinical Breast Cancer",
issn = "1526-8209",
publisher = "Elsevier",

}

TY - JOUR

T1 - Relative Prognostic and Predictive Value of Gene Signature and Histologic Grade in Estrogen Receptor-Positive, HER2-Negative Breast Cancer

AU - Iwamoto, Takayuki

AU - Kelly, Catherine

AU - Mizoo, Taeko

AU - Nogami, Tomohiro

AU - Motoki, Takayuki

AU - Shien, Tadahiko

AU - Taira, Naruto

AU - Hayashi, Naoki

AU - Niikura, Naoki

AU - Fujiwara, Toshiyoshi

AU - Doihara, Hiroyoshi

AU - Matsuoka, Junji

PY - 2015/7/29

Y1 - 2015/7/29

N2 - Background: In estrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer, first-generation genomic signatures serve predominately as prognostic biomarkers and secondarily as predictors of response to chemotherapy. We compared both the prognostic and predictive value of histologic grades and genomic markers. Methods: We retrieved publicly available cDNA microarray data from 1373 primary ER+/HER2- breast cancers and developed a genomic signature simulated from Recurrence Online (http://www.recurrenceonline.com/) to calculate the recurrence score and risk using predefined sets of genes in the cDNA microarray. We then compared the prognostic and predictive information provided by histologic grade and genomic signature. Results: Based on genomic signatures, 55%, 28%, and 17% of breast cancers were classified as low, intermediate, and high risk, respectively, whereas the histologic grades were I, II, and III in 22%, 59%, and 19% of breast cancers, respectively. Univariate analysis in the untreated cohort revealed that both histologic grade (overall P = .007) and genomic signature (P <.001) could predict prognosis. Results were similar using the genomic signature, with pathologic complete response rates of 4.6%, 5.7%, and 16.5% for low-, intermediate-, and high-risk cancers, respectively. Neither biomarker was statistically significant in multivariate analysis for predictive response to neoadjuvant chemotherapy (NAC). Conclusion: Genomic signature was better at identifying low-risk cases compared to histologic grade alone, but both markers had similar predictive values for NAC response. Better predictive biomarkers for NAC response are still needed.

AB - Background: In estrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer, first-generation genomic signatures serve predominately as prognostic biomarkers and secondarily as predictors of response to chemotherapy. We compared both the prognostic and predictive value of histologic grades and genomic markers. Methods: We retrieved publicly available cDNA microarray data from 1373 primary ER+/HER2- breast cancers and developed a genomic signature simulated from Recurrence Online (http://www.recurrenceonline.com/) to calculate the recurrence score and risk using predefined sets of genes in the cDNA microarray. We then compared the prognostic and predictive information provided by histologic grade and genomic signature. Results: Based on genomic signatures, 55%, 28%, and 17% of breast cancers were classified as low, intermediate, and high risk, respectively, whereas the histologic grades were I, II, and III in 22%, 59%, and 19% of breast cancers, respectively. Univariate analysis in the untreated cohort revealed that both histologic grade (overall P = .007) and genomic signature (P <.001) could predict prognosis. Results were similar using the genomic signature, with pathologic complete response rates of 4.6%, 5.7%, and 16.5% for low-, intermediate-, and high-risk cancers, respectively. Neither biomarker was statistically significant in multivariate analysis for predictive response to neoadjuvant chemotherapy (NAC). Conclusion: Genomic signature was better at identifying low-risk cases compared to histologic grade alone, but both markers had similar predictive values for NAC response. Better predictive biomarkers for NAC response are still needed.

KW - Breast cancer

KW - Chemotherapy response

KW - Genomic marker

KW - Grade

KW - Predictive marker

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DO - 10.1016/j.clbc.2015.10.004

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JO - Clinical Breast Cancer

JF - Clinical Breast Cancer

SN - 1526-8209

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