Cited by 64Breast Cancer Treatment StudiesCancer-related Molecular PathwaysEstrogen and related hormone effects

Distinct p53 gene signatures are needed to predict prognosis and response to chemotherapy in ER-positive and ER-negative breast cancers

Coutant, Charles, Rouzier, Roman, Qi, Yuan, Lehmann-Che, Jacqueline, Bianchini, Giampaolo, Iwamoto, Takayuki, Hortobagyi, Gabriel N., Symmans, W. Fraser +4 more·2011·Clinical Cancer Research

Published version of a preprint

Abstract

Purpose Estrogen receptor-positive (ER+) and -negative (ER) breast cancers are molecularly distinct diseases. We hypothesized that p53 mutations may lead to different transcriptional changes and carry different prognostic value in these two different types of cancers. Experimental design We developed a 39-gene p53 signature derived from 213 ER+ and a separate 30-gene signature from 38 ER- cancers with known mutation status and tested their prognostic and chemotherapy response predictive values in ER+ and ER- cancers, respectively. Results External validation to predict p53 status (n = 103) showed sensitivity and specificity of 89% and 54% for the 39-gene signature, and 82% and 61% for the 30-gene signature. The 39-gene signature was predictive of worse distant metastasis free survival in ER+ cancers in two separate prognostic data sets (n = 255, HR: 2.3, P = 0.005 and n = 198, HR: 2.17, P = 0.09). It also predicted for poor prognosis even with adjuvant tamoxifen therapy (n = 277, HR = 2.43, P Conclusions P53 dysfunction is prognostically most relevant in ER+ cancers and supports the hypothesis that different predictive or prognostic markers will be needed for different molecular subsets of breast cancer.

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Crossref · 10.1158/1078-0432.ccr-10-1045

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Authors
Coutant, C., Rouzier, R., Qi, Y., Lehmann-Che, J., Bianchini, G., Iwamoto, T., Hortobagyi, G. N., Symmans, W. F., Uzan, S., Andre, F., de Thé, H., & Pusztai, L.
Affiliations
  • The University of Texas MD Anderson Cancer Center (US)
  • Authors' Affiliations: Departments of 1Breast Medical Oncology, 2Bioinformatics, and 3Pathology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas; 4Department of Gynecology and Obstetrics, University Pierre et Marie Curie, Paris 6 and UPRES EA 4053, Tenon Hospital, Assistance Publique des Hôpitaux de Paris; 5Department of Biochemistry and INSERM U944 University Rene Diderot, Paris 7, Saint Louis Hospital, Assistance Publique Hôpitaux de Paris, Paris, France; 6Division of Medical Oncology, Fondazione IRCCS Istituto Tumori di Milano, Milan, Italy; 7Department of Gastroenterological Surgery and Surgical Oncology, Okayama, University Graduate School of Medicine and Dentistry, Okayama, Japan; and 8The Translational Research Unit, Institut Gustave Roussy, Villejuif, France
Venue
Clinical Cancer Research
Published
2011-04-14
Volume
17
Issue
8
Pages
2591-2601
ISSN
  • 1078-0432 (ISSN-L)
  • 1557-3265
OpenAlex
W2118949116
Cited by
64
References
0
Citations by year
2026: 1 · 2025: 3 · 2024: 2 · 2023: 8 · 2022: 4 · 2021: 3 · 2020: 5 · 2019: 2 · 2018: 3 · 2017: 2 · 2016: 1 · 2015: 4 · 2014: 4 · 2013: 5 · 2012: 13
FWCI
2.70
Type
journal article
Language
en
Open access
closed
Locations
  • Clinical Cancer Research (publishedVersion)
  • PubMed (publishedVersion)
Funders
Fondation de France
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
  • Health Sciences › Medicine › Oncology › Cancer-related Molecular Pathways
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Estrogen and related hormone effects
Keywords
TP53 mutation, gene expression signatures, estrogen receptor-positive breast cancer, estrogen receptor-negative breast cancer, prognosis, chemotherapy response prediction, distant metastasis-free survival, tamoxifen, gene expression changes, molecular subtypes
MeSH terms
Adult, Aged, Aged, 80 and over, Breast Neoplasms, Female, Humans, Middle Aged, Mutation, Predictive Value of Tests, Prognosis, Receptors, Estrogen, Multivariate Analysis, Survival Analysis, Tumor Suppressor Protein p53, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling

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