In oncology, the concept of ‘precision medicine’ relates to a match between specific forms of treatment and points of biological vulnerability in cancer cells. Discovery research in this area is often focussed on identification of novel treatment targets. At the point of translation, robust predictive biomarkers are needed to identify individuals who may benefit from targeted treatments. Rapid progress in this area has come from high-throughput genomics and transcriptomics research and there is now enormous potential for cancer tissue proteomics to further advance the field.
ProCan is a major cancer research program aiming to complete a large-scale survey of the cancer tissue proteome over a 5-7 year timeframe. The overall goal is to assemble a comprehensive proteomics knowledge-base that, in combination with clinical and other ‘omic data, will support both discovery research and the development of biomarkers for clinical use. ProCan is largely based on Data-Independent Analysis Mass Spectrometry (DIA-MS) of highly characterised cancer tissue samples, coupled with ‘big data’ analytics. A key challenge is to establish a systematic approach that will allow results from a large number of samples, analysed over a long period of time to be compared. This combination of high sample throughput and analytical validity is critical for cancer tissue proteomics to make an impact on clinical practice.