Analysis of breast cancer related gene expression using natural splines and the Cox proportional hazard model to identify prognostic associations.
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.
Division of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 121, Amsterdam 1066 CX, The Netherlands.
Bas
B
Kreike
Guus
G
Hart
Harry
H
Bartelink
Marc J
MJ
van de Vijver
D014408:Biomarkers, Tumor / Q000235:genetics*; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000235:genetics* / Q000556:secondary; D015331:Cohort Studies; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D008875:Middle Aged; D009426:Netherlands; D020411:Oligonucleotide Array Sequence Analysis; D011379:Prognosis; D016016:Proportional Hazards Models; D012044:Regression Analysis
D014408:Biomarkers, Tumor