The increasing incidence of endometrial cancer (EC) requires an extensive search for novel preventive tools and early intervention approaches. However, the establishment of reliable predictive models is impossible without knowledge of genetic changes prior to diagnosis. In 3 this work, we aimed to establish whether known EC risk factors influence peripheral blood gene expression in a prospective design. First, we selected variables (parity status, lifetime number of years of menstruation, coffee consumption, BMI, age of menopause, use of oral contraceptives) that were shown to have an impact on EC risk in a big prospective cohort (165,000 women). Next, using BeadChip microarray technology, we tested the association between these variables and changes in gene expression profiles in blood in a nested case-control study (79 case-control pairs) of women from the NOWAC postgenome cohort. Lastly, we undertook a gene set enrichment analysis (GSEA). At overall gene expression level, we found no difference between the EC cases and controls. The introduction of parity status into the statistical model, revealed changes in the expression of 1,379 genes in the controls, while we did not observe any expression changes in the cases. Twenty-seven genes were associated with BMI increase in the controls, whereas there was no association observed between changes in BMI and gene expression in women with EC. In GSEA, 2407 significantly enriched gene sets were attributed to a parity increase among cancer-free women. In this study, we found that an increased number of parities have a life-long effect on the gene expression profile in the peripheral blood of women who never developed cancer, while neither multiparity nor elevated BMI changed the gene expression in women diagnosed with EC later in life.
Gavriluk et al. (Fri,) studied this question.