A Targeted Quantitative Proteomics Strategy for Global Kinome Profiling of Cancer Cells and Tissues |
| |
Authors: | Yongsheng Xiao Lei Guo Yinsheng Wang |
| |
Institution: | From the ‡Department of Chemistry and ;§Environmental Toxicology Graduate Program, University of California, Riverside, CA 92521-0403 |
| |
Abstract: | Kinases are among the most intensively pursued enzyme superfamilies as targets for anti-cancer drugs. Large data sets on inhibitor potency and selectivity for more than 400 human kinases became available recently, offering the opportunity to design rationally novel kinase-based anti-cancer therapies. However, the expression levels and activities of kinases are highly heterogeneous among different types of cancer and even among different stages of the same cancer. The lack of effective strategy for profiling the global kinome hampers the development of kinase-targeted cancer chemotherapy. Here, we introduced a novel global kinome profiling method, based on our recently developed isotope-coded ATP-affinity probe and a targeted proteomic method using multiple-reaction monitoring (MRM), for assessing simultaneously the expression of more than 300 kinases in human cells and tissues. This MRM-based assay displayed much better sensitivity, reproducibility, and accuracy than the discovery-based shotgun proteomic method. Approximately 250 kinases could be routinely detected in the lysate of a single cell line. Additionally, the incorporation of iRT into MRM kinome library rendered our MRM kinome assay easily transferrable across different instrument platforms and laboratories. We further employed this approach for profiling kinase expression in two melanoma cell lines, which revealed substantial kinome reprogramming during cancer progression and demonstrated an excellent correlation between the anti-proliferative effects of kinase inhibitors and the expression levels of their target kinases. Therefore, this facile and accurate kinome profiling assay, together with the kinome-inhibitor interaction map, could provide invaluable knowledge to predict the effectiveness of kinase inhibitor drugs and offer the opportunity for individualized cancer chemotherapy.Protein phosphorylation, one of the most important types of post-translational modifications (PTMs)1, is catalyzed by protein kinases (collectively referred to as the kinome), which are encoded by over 500 genes in higher eukaryotes (1). Aberrant expression and/or activation/deactivation of kinases have been implicated as among the major mechanisms through which cancer cells escape normal physiological constraints of cell growth and survival (2). Additionally, dynamic kinome reprogramming has been found to be closely associated with resistance toward cancer chemotherapy (3). Owing to their crucial roles in cancer development, kinases have become one of the most intensively pursued enzyme superfamilies as drug targets for cancer chemotherapy and more than 130 distinct kinase inhibitors have been developed for phase 1–3 clinical trials (4). Recently, inhibitor potency and selectivity for more than 400 kinases have been reported, which provided a comprehensive target-inhibition profile for the majority of the human kinome (5–7). Therefore, the kinome-inhibitor interaction networks coupled with comprehensive profiling of global kinome expression and activity associated with certain types of cancer could be invaluable for understanding the mechanisms of carcinogenesis and for designing rationally novel kinase-directed anti-cancer chemotherapies.Unfortunately, currently there is no optimal strategy for profiling the expression levels of the entire kinome at the protein level. Traditional methods for measuring kinase expression rely primarily on antibody-based immunoassays because of their high specificity and sensitivity (8). The immunoassays, however, are limited by the availability of high-quality antibodies; therefore, these methods are only useful for assessing a small number of kinases in low-throughput. Recent advances in MS instrumentation and bioinformatic tools enable the identification and quantification of a significant portion of the human proteome from complex samples (9). However, proteomic studies of global kinome by MS are still very challenging, which is largely attributed to the fact that, similar as other regulatory enzymes, protein kinases are generally expressed at low levels in cells (10). This analytical challenge is further aggravated in shotgun proteomics approach where even more complex mixtures of peptides instead of proteins from whole cell or tissue extracts are analyzed (11). Therefore, selective enrichment of protein kinases from cellular extracts is essential for the comprehensive identification and quantification of the global kinome.Affinity columns immobilized with kinase inhibitors have been employed as capture ligands for the enrichment of kinases, and ∼200 protein kinases could be identified and quantified by subsequent LC-MS/MS analyses (3, 10, 12). Recently, we and others reported the application of biotin-conjugated acyl nucleotide probes for the enrichment and identification of kinases from complex protein mixtures (13–17). This enrichment technique, in combination with multi-dimensional LC-MS platform, facilitates the identification of ∼200 protein kinases (15). Despite these advances, such large-scale kinome studies are often performed in the data-dependent acquisition (DDA) mode, where typically 10–20 most abundant ions found in MS are subsequently selected for fragmentation in MS/MS to enable peptide identification (18). Although this discovery-mode (or shotgun) proteomic approach provides the potential to uncover novel protein targets, sample complexity, together with inherent variation in automated peak selection, results in compromised sensitivity and reproducibility for protein quantification. As a result, only partially overlapping sets of proteins can be identified even from substantially similar samples (11). The inadequate sensitivity and reproducibility of these kinome detection strategies hamper their utility in biomarker discovery and clinical studies.Targeted proteomics technique, which relies on multiple-reaction monitoring (MRM) on triple quadrupole mass spectrometers, has become increasingly used in quantitative proteomics studies (19). In the MRM mode, mass filtering of both the precursor and product ions is employed to provide high specificity for the quantification of target proteins. Additionally, this MRM-based targeted MS analysis permits rapid and continuous monitoring of specific ions of interest, which enhances the sensitivity for peptide detection by up to 100-fold relative to MS analysis in DDA-based discovery mode (20). Therefore, the MRM-based targeted proteomic approach may enable global kinome profiling with high specificity, sensitivity, throughput, and reproducibility.Here, we developed the first MRM-based platform to support the multiplexed, reproducible, and sensitive quantification of ∼300 protein kinases in the human kinome. Aside from conventional MRM-based assay design, we selectively label and enrich kinases from complex human proteome prior to MRM analysis with the use of desthiobiotin-based isotope-coded ATP-affinity probe (ICAP) (21) to attain high specificity and sensitivity. We demonstrated that this MRM-based kinome detection strategy coupled with ICAP reagent is applicable for clinical samples that are not amenable to metabolic labeling. Additionally, this MRM-based kinome assay is easily transferable between instruments and laboratories, rendering it a facile and universal strategy for global kinome detection. |
| |
Keywords: | |
本文献已被 ScienceDirect 等数据库收录! |
|