BRIDGES · Bioinformatic approaches to identify and detect both disease- and drug-related genomic alterations in breast cancer patients

Bioinformatic approaches to identify and detect both disease- and drug-related genomic alterations in breast cancer patients

With more than 400,000 new cases in 2012, breast cancer is the most common cancer among European women. Present clinical management causes overtreatment in more than 50% of patients, with implications on both patients’ quality of life and healthcare costs sustainability. At the same time, intrinsic or acquired tumour resistance to treatment leads to disease progression towards incurable metastatic disease in a significant proportion of patients. Advances in cancer genomics highlighted a high inter- and intra-tumour genetic heterogeneity of breast cancer, reinforcing the need for a personalized treatment and a way to non-invasively monitor an evolving disease. Although examples of targeted therapies have been developed in breast cancer (e.g. hormone therapy in estrogen receptor positive tumours or HER2 targeting in HER2 amplified tumours), a still unmet challenge is the implementation of a real personalized treatment and parallel development of companion biomarkers for patients’ stratification and early detection of resistance. Accordingly, the aims of this project were: 1) to develop new bioinformatics approaches to analyse and exploit large set of genomic and transcriptomic data from clinical specimens, liquid biopsy and pre-clinical models; 2) to identify candidate predictive biomarkers associated with response to treatment and enable their non-invasive assessment in a liquid biopsy. In the time frame of the action three computational approaches have been developed, respectively able: 1) to identify somatic mutations in cancer with higher sensitivity and specificity, 2) to distinguish human and mouse reads in sequencing data from patient-derived tumour xenografts (PDTX) and 3) to analyse amplicon based sequencing data from FFPE and plasma samples. These approaches are either published or submitted for publication in peer-reviewed international journals. At the same time, the integrative analysis of genomic and transcriptomic data from a clinical cohort and a PDTX cohort has identified several molecular signatures associated with drug response in breast cancer. Results obtained from the integrative analysis have been presented at the AACR Annual Meeting 2017 and will be submitted for publication in the near future. Molecular and drug response data from the PDTX cohort have been made available through a user-friendly graphical interface at http://caldaslab.cruk.cam.ac.uk/bcape/.

Data: CORDIS, © European Union