Introduction: Precision oncology is becoming a standard approach in cancer patients care, with cancer molecular characterisation through genome sequencing being the major focus. In addition, there is growing evidence showing that patients transcriptome profiling can contribute to our knowledge of individual cancers by revealing additional layers to the disease biology. In this work we develop a pipeline for using cancer patient’s RNA sequencing (RNA-seq) data to complement genome-based findings and aid therapeutic targets prioritisation.
Method: We use bcbio-nextgen RNA-seq pipeline to process the RNA-seq read data from patient’s tumour, followed by gene fusions prioritisation, per-gene read count data normalisation and transformation into standard scores to address challenges associated with analysing data from a single-subject. In addition, we build an internal reference cohort using a set of in-house high-quality tumour samples to assure input material and data processing compatibility. Finally, we integrate transcriptome data with genome-based findings from patient’s whole-genome sequencing (WGS) data and annotate results using public knowledge bases to provide additional evidence for dysregulation of mutated genes, as well as genes located within detected structural variants or copy-number altered regions.
Results: We developed a pipeline capable to process and analyse RNA-seq data from an individual patient’s tumour. In addition, the inclusion of an internal reference set assures the input material and data compatibility. The results are visualised in an approachable html-based interactive report with searchable tables and plots, providing variant curators with a tool to verify and prioritise genome-based findings.
Discussion: RNA-seq technology holds great promise for the clinical applicability in molecular diagnostic standpoint. However, it is not straight forward to translate this technology into clinical practice, mainly due to its single-subject setting. We developed a pipeline for integrating information from both WGS and RNA sequencing approaches to provide additional clinically relevant information that can help prioritise variants for therapeutic intervention.