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01-08-2010 | Preclinical study

Analysis of breast cancer related gene expression using natural splines and the Cox proportional hazard model to identify prognostic associations

Authors: Bas Kreike, Guus Hart, Harry Bartelink, Marc J. van de Vijver

Published in: Breast Cancer Research and Treatment | Issue 3/2010

Abstract

Many studies correlating gene expression data to clinical parameters assume a linear increase or decrease of the clinical parameter under investigation with the expression of a gene. We have studied genes encoding important breast cancer-related proteins using a model for survival-type data that is based on natural splines and the Cox proportional hazard model, thereby removing the linearity assumption. Expression data of 16 genes were studied in relation to metastasis-free probability in a cohort of 295 consecutive breast cancer patients treated at The Netherlands Cancer Institute. The independent predictive power for disease outcome of the 16 individual genes was tested in a multivariable model with known clinical and pathological risk factors. There is a linear relationship between increasing expression and a higher or lower hazard for distant metastasis for ESR1, ERBB4, VEGF, CCNE2, EZH2, and UPA; for ERBB2, ERBB3, CCND1, CCNE1, EED, CXCR4, CCR7, SDF1, and PAI1 there is no clear increase or decrease; and for EGFR there seems to be a non-linear relation. Multivariable analysis showed that the 70-gene prognosis profile outperforms all the other variables in the model (hazard-rate 5.4, 95% CI 2.5–11.7; P = 0.000018). EGFR-expression seems to have a non-linear relation with disease outcome, indicating that lower but also higher expression of EGFR are associated with worse outcome compared to intermediate expression levels; the other genes show no or a linear relation.

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Title: Analysis of breast cancer related gene expression using natural splines and the Cox proportional hazard model to identify prognostic associations
Authors: Bas Kreike
Guus Hart
Harry Bartelink
Marc J. van de Vijver
Publication date: 01-08-2010
Publisher: Springer US
Published in: Breast Cancer Research and Treatment / Issue 3/2010
Print ISSN: 0167-6806
Electronic ISSN: 1573-7217
DOI: https://doi.org/10.1007/s10549-009-0588-6

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