DNA and RNA sequencing are now standard tools in cancer research but are not yet widely implemented in the clinical setting. Translation of sequencing-based molecular phenotyping to the clinic holds the promise to provide a quantitative and more detailed basis for diagnosis and prognosis compared to conventional pathology, and thus lead to improved patient outcomes.

In this talk I will present results from the ClinSeq (Clinical Sequencing of Cancer in Sweden) breast cancer study. ClinSeq aims to develop and evaluate infrastructure, bioinformatic methods and statistical models to bring sequencing-based cancer diagnostics to the clinic. Using multivariate prediction modelling we assess to what extent DNA and RNA sequencing-based molecular profiling of primary breast cancer tumours can replace, and potentially augment, current routine pathology, including immunohistochemical markers and histological grade. Our results, based on a retrospective study including DNA and RNA sequencing of ~300 primary breast cancer tumours, indicate a high degree of concordance between conventional markers and predictions from models based on sequencing data, while also providing additional treatment relevant information. Around 8% of cases are reclassified by sequencing-based models and these cases also have an increased probability of reclassification under pathological re-examination.