Dataset Information

Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts.

ABSTRACT:

Introduction

Adjuvant breast cancer therapy significantly improves survival, but overtreatment and undertreatment are major problems. Breast cancer expression profiling has so far mainly been used to identify women with a poor prognosis as candidates for adjuvant therapy but without demonstrated value for therapy prediction.

Methods

We obtained the gene expression profiles of 159 population-derived breast cancer patients, and used hierarchical clustering to identify the signature associated with prognosis and impact of adjuvant therapies, defined as distant metastasis or death within 5 years. Independent datasets of 76 treated population-derived Swedish patients, 135 untreated population-derived Swedish patients and 78 Dutch patients were used for validation. The inclusion and exclusion criteria for the studies of population-derived Swedish patients were defined.

Results

Among the 159 patients, a subset of 64 genes was found to give an optimal separation of patients with good and poor outcomes. Hierarchical clustering revealed three subgroups: patients who did well with therapy, patients who did well without therapy, and patients that failed to benefit from given therapy. The expression profile gave significantly better prognostication (odds ratio, 4.19; P = 0.007) (breast cancer end-points odds ratio, 10.64) compared with the Elston-Ellis histological grading (odds ratio of grade 2 vs 1 and grade 3 vs 1, 2.81 and 3.32 respectively; P = 0.24 and 0.16), tumor stage (odds ratio of stage 2 vs 1 and stage 3 vs 1, 1.11 and 1.28; P = 0.83 and 0.68) and age (odds ratio, 0.11; P = 0.55). The risk groups were consistent and validated in the independent Swedish and Dutch data sets used with 211 and 78 patients, respectively.

Conclusion

We have identified discriminatory gene expression signatures working both on untreated and systematically treated primary breast cancer patients with the potential to spare them from adjuvant therapy.

SUBMITTER: Pawitan Y

PROVIDER: S-EPMC1410752 | biostudies-literature | 2005

REPOSITORIES: biostudies-literature

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Publications

Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts.

Pawitan Yudi Y Bjöhle Judith J Amler Lukas L Borg Anna-Lena AL Egyhazi Suzanne S Hall Per P Han Xia X Holmberg Lars L Huang Fei F Klaar Sigrid S Liu Edison T ET Miller Lance L Nordgren Hans H Ploner Alexander A Sandelin Kerstin K Shaw Peter M PM Smeds Johanna J Skoog Lambert L Wedrén Sara S Bergh Jonas J

Breast cancer research : BCR 20051003 6

<h4>Introduction</h4>Adjuvant breast cancer therapy significantly improves survival, but overtreatment and undertreatment are major problems. Breast cancer expression profiling has so far mainly been used to identify women with a poor prognosis as candidates for adjuvant therapy but without demonstrated value for therapy prediction.<h4>Methods</h4>We obtained the gene expression profiles of 159 population-derived breast cancer patients, and used hierarchical clustering to identify the signature ...[more]

PMID: 16280042

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Dataset Information

Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts.

Introduction

Methods

Results

Conclusion

Publications

Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts.

Similar Datasets

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