Biomarker studies

Disease screening based on genomic biomarkers (RNA and DNA biomarkers)

Recent developments in genomic research and in the field of non-coding RNAs such as microRNAs offer new approaches to disease screening based on genetic biomarkers. bdc supported case-control studies examining genomic as well as transcriptional changes in patients compared to healthy probands enable the development of diagnostic biomarker signatures. The goal of this joint screening program is to detect human diseases such as cancer at an early stage and optimize treatment with personalized patient care.

Proper study and experimental design coupled with the correct data analysis approach are critical components of successful biomarker discovery, and the bdc offers the opportunity to benefit from standardized approaches and consolidated knowledge. The bdc supports comprehensive studies and offers guidance through study design, experimental workflow and the biostatistical analysis of the results.

Moreover, in an effort to make most use of valuable data, the bdc develops and administrates a „microRNA Expression Database“ where miRNA biomarker data of different studies can be stored. This database is still in development but holds great promise to be a valuable tool for biomarker researchers. miRNA biomarker expression data generated in clinical studies could easily be uploaded by participating researchers including a brief description of submitter, study layout and experimental strategy. In turn, biomarker expression patterns could be browsed, extracted and interpreted for any disease of interest.

Especially microarray-based techniques used in biomarker research generate vast quantities of data. Thorough analysis is required to sort through these data to select the most robust candidate biomarkers and to develop disease-specific signatures. Biomarkers that have been identified and validated are subject to biostatistical analysis and, in the microRNA Expression Database, can be compared to data generated in other studies. That way more information can be integrated and a greater statistical reliability can be achieved. Predictive or diagnostic biomarker signatures, based on the minimum number of significantly deregulated miRNAs that is necessary to distinguish patients from controls, can be generated and allow for accurate classification of each investigated patient group. Cross-comparisons not only to healthy probands but also to other diseases make study results all the more meaningful and statistically significant.

Further supporting the discovery of biomarkers beyond miRNAs and their target genes, the febit technology applied in bdc studies facilitates the analysis of genomic biomarkers based on targeted resequencing. The HybSelect™ Sequence Capture strategy allows for targeted enrichment of biomarker relevant sequences and genomic loci of interest in order to perform deep sequencing on Next Generation Sequencing platforms, like ABIs SOLiD 3 Sequencer. Accurate, massively parallel Next Generation Sequencing enables high throughput targeted resequencing to be conducted more rapidly and cost effectively than previously possible, which is essential for large scale biomarker studies.