Analysis of gene expression in blood before diagnosis of ovarian cancer - Different statistical methods

The analyses in this note are based on a dataset with gene expression in blood before diagnosis of ovarian cancer. The dataset consists of case‐control pairs that are matched on birth year and time of blood sampling, and the data for a pair is the log2 difference in gene expression between the case and control. For each case‐ control pair the gene expression is measured once before diagnosis. As the blood samples of the different case‐controls pairs are measured at different points in time before diagnosis, we have used the dataset for examining whether the gene expression profile varies with time. We have also used the dataset for examining whether the gene expression profile varies between cases and controls, or between cases with and without spread (metastases), and for predicting whether a case has ovarian cancer with or without spread. We have used and adapted a method based on hypothesis testing using randomization, that is able to identify small changes that are varying slowly in time and/or among strata, by using a large number of genes in each hypothesis test and predictor. Even though the signals in the data are weak, we concluded that the gene expression profile varies in time, between cases and controls and between cases with and without spread (metastases). The results indicated that there is an increasing variation in the gene expression profiles when approaching the time of diagnosis, while the gene expression profiles far from diagnosis are more stable. The dataset is quite small, with only 59 case‐control pairs with spread and 28 without spread that are distributed over a seven year period before diagnosis. We can therefore not draw any firm conclusion about whether the predictive power of the method used for predicting the metastasis status of the cases is sufficiently good (p‐value 0.28, Fisher’s test). The best predictive power was observed in a two‐year period around year 5 before diagnosis (p‐value 0.12, Fisher’s test).