The changing demographic landscape is causing a steady rise in the number of oncological, chronic-inflammatory and degenerative diseases. Despite a similarly growing number of therapeutic options, treating these diseases often proves unsatisfactory. Personalized therapy can bring about fundamental progress here. For this to work, the molecular basis of a disease first needs to be precisely determined and the case-specific disease progression and response to therapy has to be predicted. Ever since the human genome was sequenced in full in 2001, the decoding of disease-relevant genes has opened up new options for developing tailor-made approaches to therapy. Alongside evidence of changes in DNA patterns (e.g. mutations), the investigation of RNA gene expression patterns by means of transcriptome-wide sequencing is increasingly shifting into focus.
As part of the RIBOLUTION project, funded by the Fraunhofer Future Foundation, new biomarkers were identified for prostate cancer based on transcriptome-wide (RNA) sequencing together with microarray analyses. Biomarkers were identified here that can diagnose the disease and also predict the aggressiveness of the cancer.
In order to validate and subsequently use these biomarkers for diagnostic purposes, a manageable number of biomarkers is to be identified using a simple test. To do this, the RNA Biomarker Unit has come up with a workflow for detecting diagnostic biomarkers in the urine, using quantitative real-time PCR (qPCR). For optimization purposes, suitable reference and target regions as well as primers and probes were tested in depth and the reaction conditions were adapted, among other things. For the assessment, the selected biomarkers were investigated in close cooperation with the Bioinformatics Unit using a specially developed algorithm.
For the more complicated issue of predicting the cancer, the Next-Generation Diagnostics Unit developed a workflow based on RNA sequencing from FFPE biopsy material. The aim here was to identify a broad spectrum of potential biomarkers in clinically available samples. In the interests of reducing time and costs, sequencing was optimized in terms of sensitivity and robustness. Based on this established method, the transcriptome-wide sequencing of a large patient cohort (n>150) is currently being carried out to validate the identified biomarkers.
The workflows developed in this project are to be transferred to other indications in the future.