Cancer genomics research aims to advance personalized oncology by finding and targeting specific genetic alterations associated with cancers. In genome-driven oncology, treatments are selected for ...individual patients on the basis of the findings of tumour genome sequencing. This personalized approach has prolonged the survival of subsets of patients with cancer. However, many patients do not respond to the predicted therapies based on the genomic profiles of their tumours. Furthermore, studies pairing genomic and proteomic analyses of samples from the same tumours have shown that the proteome contains novel information that cannot be discerned through genomic analysis alone. This observation has led to the concept of proteogenomics, in which both types of data are leveraged for a more complete view of tumour biology that might enable patients to be more successfully matched to effective treatments than they would using genomics alone. In this Perspective, we discuss the added value of proteogenomics over the current genome-driven approach to the clinical characterization of cancers and summarize current efforts to incorporate targeted proteomic measurements based on selected/multiple reaction monitoring (SRM/MRM) mass spectrometry into the clinical laboratory to facilitate clinical proteogenomics.
Targeted proteomics technique has emerged as a powerful protein quantification tool in systems biology, biomedical research, and increasing for clinical applications. The most widely used targeted ...proteomics approach, selected reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), can be used for quantification of cellular signaling networks and preclinical verification of candidate protein biomarkers. As an extension to our previous review on advances in SRM sensitivity (Shi et al., Proteomics, 12, 1074–1092, 2012) herein we review recent advances in the method and technology for further enhancing SRM sensitivity (from 2012 to present), and highlighting its broad biomedical applications in human bodily fluids, tissue and cell lines. Furthermore, we also review two recently introduced targeted proteomics approaches, parallel reaction monitoring (PRM) and data‐independent acquisition (DIA) with targeted data extraction on fast scanning high‐resolution accurate‐mass (HR/AM) instruments. Such HR/AM targeted quantification with monitoring all target product ions addresses SRM limitations effectively in specificity and multiplexing; whereas when compared to SRM, PRM and DIA are still in the infancy with a limited number of applications. Thus, for HR/AM targeted quantification we focus our discussion on method development, data processing and analysis, and its advantages and limitations in targeted proteomics. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large‐scale quantification of hundreds of target proteins are discussed.
Extracellular vesicles (EVs) are released by nearly all cell types as part of normal cell physiology, transporting biological cargo, including nucleic acids and proteins, across the cell membrane. In ...pathological states such as cancer, EV-derived cargo may mirror the altered state of the cell of origin. Exosomes are the smaller, 50–150 nanometer-sized EVs released from fusion of multivesicular endosomes with the plasma membrane. Exosomes play important roles in cell-cell communication and participate in multiple cancer processes, including invasion and metastasis. Therefore, proteomic analysis of exosomes is a promising approach to discover potential cancer biomarkers, even though it is still at an early stage. Herein, we critically review the advances in exosome isolation methods and their compatibility with mass spectrometry (MS)-based proteomic analysis, as well as studies of exosomes in pathogenesis and progression of prostate and bladder cancer, two common urologic cancers whose incidence rates continue to rise annually. As urological tumors, both urine and blood samples are feasible for noninvasive or minimally invasive analysis. A better understanding of the biological cargo and functions of exosomes via high-throughput proteomics will help provide new insights into complex alterations in cancer and provide potential therapeutic targets and personalized treatment for patients.
Through evaluating and optimizing boosting ratio and MS acquisition conditions (automatic gain control and ion injection time), the improved Boosting to Amplify Signal with Isobaric Labeling (iBASIL) ...strategy allows for precise and robust quantitative single-cell proteomics. A total of 2,622 proteins were identified and 1,452 proteins (58%) were quantified in more than 70% of the sample channels in the analysis of 104 FACS-isolated AML single cells, which recapitulates the key biological differences amongst three AML cell lines.
Display omitted
Highlights
•Higher AGC significantly improves quantitation quality in single-cell analysis.•The boosting-to-sample ratio should be carefully evaluated and optimized.•iBASIL allows for precise quantitation of 1,500 proteins from 104 AML single cells.•iBASIL recapitulates major biological differences in different AML single cells.
Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100×) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ∼2500 proteins and precise quantification of ∼1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.
The relationships of kinase levels and activity have been investigated using large, high quality proteomic and phosphoproteomic data sets from tumors. Results show that the protein levels of some ...kinases correlate with their activity and that activation of kinases is a complex process. This study provides the first analysis of kinase activity in cancer integrating proteomic and phosphoproteomic data.
Display omitted
Highlights
•Integration of proteomics and phosphoproteomics data to understand kinase activity.•The abundance of some kinases correlates with activity.•Kinase activity does not necessarily reflect phosphorylation of regulatory sites.•Correlation patterns can be used to extend kinase substrate repertoire.
Phosphorylation of proteins is a key way cells regulate function, both at the individual protein level and at the level of signaling pathways. Kinases are responsible for phosphorylation of substrates, generally on serine, threonine, or tyrosine residues. Though particular sequence patterns can be identified that dictate whether a residue will be phosphorylated by a specific kinase, these patterns are not highly predictive of phosphorylation. The availability of large scale proteomic and phosphoproteomic data sets generated using mass-spectrometry-based approaches provides an opportunity to study the important relationship between kinase activity, substrate specificity, and phosphorylation. In this study, we analyze relationships between protein abundance and phosphopeptide abundance across more than 150 tumor samples and show that phosphorylation at specific phosphosites is not well correlated with overall kinase abundance. However, individual kinases show a clear and statistically significant difference in correlation among known phosphosite targets for that kinase and randomly selected phosphosites. We further investigate relationships between phosphorylation of known activating or inhibitory sites on kinases and phosphorylation of their target phosphosites. Combined with motif-based analysis, this approach can predict novel kinase targets and show which subsets of a kinase's target repertoire are specifically active in one condition versus another.
Sensitive detection of low-abundance proteins in complex biological samples has typically been achieved by immunoassays that use antibodies specific to target proteins; however, de novo development ...of antibodies is associated with high costs, long development lead times, and high failure rates. To address these challenges, we developed an antibody-free strategy that involves PRISM (high-pressure, high-resolution separations coupled with intelligent selection and multiplexing) for sensitive selected reaction monitoring (SRM)–based targeted protein quantification. The strategy capitalizes on high-resolution reversed-phase liquid chromatographic separations for analyte enrichment, intelligent selection of target fractions via on-line SRM monitoring of internal standards, and fraction multiplexing before nano–liquid chromatography-SRM quantification. Application of this strategy to human plasma/serum demonstrated accurate and reproducible quantification of proteins at concentrations in the 50–100 pg/mL range, which represents a major advance in the sensitivity of targeted protein quantification without the need for specific-affinity reagents. Application to a set of clinical serum samples illustrated an excellent correlation between the results obtained from the PRISM-SRM assay and those from clinical immunoassay for the prostate-specific antigen level.
In the past decade, there has been an increasing interest in applying proteomics to assist in understanding the pathogenesis of ovarian cancer, elucidating the mechanism of drug resistance, and in ...the development of biomarkers for early detection of ovarian cancer. Although ovarian cancer is a spectrum of different diseases, the strategies for diagnosis and treatment with surgery and adjuvant therapy are similar across ovarian cancer types, increasing the general applicability of discoveries made through proteomics research. While proteomic experiments face many difficulties which slow the pace of clinical applications, recent advances in proteomic technology contribute significantly to the identification of aberrant proteins and networks which can serve as targets for biomarker development and individualized therapies. This review provides a summary of the literature on proteomics’ contributions to ovarian cancer research and highlights the current issues, future directions, and challenges. We propose that protein-level characterization of primary lesion in ovarian cancer can decipher the mystery of this disease, improve diagnostic tools, and lead to more effective screening programs.
Interleukin-1 receptor-associated kinase 1 (IRAK1), an essential mediator of innate immunity and inflammatory responses, is constitutively active in multiple cancers. We evaluated the role of IRAK1 ...in acute myeloid leukemia (AML) and assessed the inhibitory activity of multikinase inhibitor pacritinib on IRAK1 in AML. We demonstrated that IRAK1 is overexpressed in AML and provides a survival signal to AML cells. Genetic knockdown of IRAK1 in primary AML samples and xenograft model showed a significant reduction in leukemia burden. Kinase profiling indicated pacritinib has potent inhibitory activity against IRAK1. Computational modeling combined with site-directed mutagenesis demonstrated high-affinity binding of pacritinib to the IRAK1 kinase domain. Pacritinib exposure reduced IRAK1 phosphorylation in AML cells. A higher percentage of primary AML samples showed robust sensitivity to pacritinib, which inhibits FLT3, JAK2, and IRAK1, relative to FLT3 inhibitor quizartinib or JAK1/2 inhibitor ruxolitinib, demonstrating the importance of IRAK1 inhibition. Pacritinib inhibited the growth of AML cells harboring a variety of genetic abnormalities not limited to FLT3 and JAK2. Pacritinib treatment reduced AML progenitors in vitro and the leukemia burden in AML xenograft model. Overall, IRAK1 contributes to the survival of leukemic cells, and the suppression of IRAK1 may be beneficial among heterogeneous AML subtypes.
Comprehensive phosphoproteomic analysis of small populations of cells remains a daunting task due primarily to the insufficient MS signal intensity from low concentrations of enriched ...phosphopeptides. Isobaric labeling has a unique multiplexing feature where the “total” peptide signal from all channels (or samples) triggers MS/MS fragmentation for peptide identification, while the reporter ions provide quantitative information. In light of this feature, we tested the concept of using a “boosting” sample (e.g., a biological sample mimicking the study samples but available in a much larger quantity) in multiplexed analysis to enable sensitive and comprehensive quantitative phosphoproteomic measurements with <100 000 cells. This simple boosting to amplify signal with isobaric labeling (BASIL) strategy increased the overall number of quantifiable phosphorylation sites more than 4-fold. Good reproducibility in quantification was demonstrated with a median CV of 15.3% and Pearson correlation coefficient of 0.95 from biological replicates. A proof-of-concept experiment demonstrated the ability of BASIL to distinguish acute myeloid leukemia cells based on the phosphoproteome data. Moreover, in a pilot application, this strategy enabled quantitative analysis of over 20 000 phosphorylation sites from human pancreatic islets treated with interleukin-1β and interferon-γ. Together, this signal boosting strategy provides an attractive solution for comprehensive and quantitative phosphoproteome profiling of relatively small populations of cells where traditional phosphoproteomic workflows lack sufficient sensitivity.
PDF
