Study of cellular oncometabolism via multidimensional protein identification technology

Abstract

Cellular proteomics is becoming a widespread clinical application, matching the definition of bench-to-bedside translation. Among various fields of investigation, this approach can be applied to the study of the metabolic alterations that accompany oncogenesis and tumor progression, which are globally referred to as oncometabolism. Here, we describe a multidimensional protein identification technology (MuDPIT)-based strategy that can be employed to study the cellular proteome of malignant cells and tissues. This method has previously been shown to be compatible with the reproducible, in-depth analysis of up to a thousand proteins in clinical samples. The possibility to employ this technique to study clinical specimens demonstrates its robustness. MuDPIT is advantageous as compared to other approaches because it is direct, highly sensitive, and reproducible, it provides high resolution with ultra-high mass accuracy, it allows for relative quantifications, and it is compatible with multiplexing (thus limiting costs).This method enables the direct assessment of the proteomic profile of neoplastic cells and tissues and could be employed in the near future as a high-throughput, rapid, quantitative, and cost-effective screening platform for clinical samples. © 2014 Elsevier Inc. All rights reserved.