Proteomics and Metabolomics in Cancer Diagnosis and Therapy

Abstract

Cancer apparently seems to be incurable but a deeper introspection reveals other story. Cancer survival rate can be increased significantly with early detection and proper therapeutic intervention. It can be vividly justified by the fact that breast cancer survival rates in high-income countries have reached over 80% while it is nearly 50% or even below in poorer countries. The reason for such contrasting picture can be understood as effective therapeutic facilities are available in above 90% of the developed countries as compared to treatment availability in below 30% of poorer countries. Proper diagnostic facilities are also lacking as only 26% of poorer countries can offer public sector pathology services according to 2017 WHO data. Conventional diagnostic approaches usually rely up on the clinical manifestation of aberration symptoms for disease diagnosis which is associated with significant delay in onset of therapeutic intervention. This is fatal, particularly for cancer as it urges earliest detection, preferably before metastasis for effective treatment outcome. State-of-the-art high-throughput proteomics and metabolomics techniques can offer solution as they identify the disease-associated molecular signatures much earlier than the traditional methods. Further, high resolution, single-cell or even organelle level penetration, extreme sensitivity, considerable reliability, and automation render them as potential platforms for identification of novel therapeutic targets as well which can facilitate development of extremely precise target-specific drugs to overcome the systemic side effects of traditional cancer chemotherapeutics. Separation-based chromatographic and electrophoretic methods such as liquid or gas chromatography (LC/GC) or capillary electrophoresis (CE) coupled with mass spectrometry (MS), Fluorescence-based methods, Raman-based methods, nuclear magnetic resonance (NMR), direct mass spectrometry imaging (MSI) are the mainstay of currently available proteomics and metabolomics analytical platforms. Although the spatiotemporal analyte dynamicity; generation, handling, and meaningful interpretation of the large data in biological context; dearth of universal standardized analytical protocols and specialized databases are posing limitations but continuous efforts from several stakeholders throughout the world is progressively alleviating the hurdles for transition of these high-end techniques from research arena to the field of routine clinical cancer diagnosis and therapy. Relentless progress in sample handling methods, instrumentation, computational software and data analyses programs ensure intense prospect of the techniques in oncology arena.