The effective implementation of personalised cancer therapeutic regimens depends on the successful identification and translation of informative biomarkers to aid clinical decision making. The utility and importance of cancer biomarkers has been recognised by substantial public and private funding, and biomarker discovery efforts are now commonplace in both academic and industrial settings. Advances in omic technologies, especially transcriptomics and proteomics, have led to a proliferation of potential cancer biomarkers. However, the pace of biomarker validation has not kept up with the extensive strides made in discovery. Key to successful translation of biomarkers into clinical settings is the establishment of robust, reproducible and informative assays. Antibody-based proteomics occupies a pivotal space in the cancer biomarker discovery and validation pipeline, facilitating the high-throughput evaluation of candidate markers. Although the clinical utility of such approaches remains to be established, the traditional use of antibodies as affinity reagents in clinical diagnostic and predictive assays suggests that rapid translation is an achievable goal. Furthermore, in combination with, or as alternatives to, genomic and transcriptomic methods for patient stratification, antibody-based proteomics approaches offer the promise of additional insight into cancer disease states. In this presentation, the current status of antibody-based proteomics will be covered, as will its contribution to the development of new assays that are crucial for the realisation of individualised cancer therapy. Moreover, the utility of digital pathology, particularly pertaining to automated assessment of tissue-derived biomarker expression, will also be described. The presentation will also provide a more general perspective of the advent of molecular diagnostics within the oncology arena, as well as touch upon several large-scale collaborative cancer research projects which are taking place at the international level that are addressing key issues in this space.
Research And Development
3D Cell Model
Clinical Laboratory Scientist33%
Medical Laboratory Technician33%
Manufacturer - Other25%