scholarly journals Kinome Profiling of Primary Endometrial Tumors Using Multiplexed Inhibitor Beads and Mass Spectrometry Identifies SRPK1 As Candidate Therapeutic Target

2020 ◽  
Author(s):  
Katherine J. Johnson ◽  
Vikas Kumar ◽  
Alison M. Kurimchak ◽  
Nishi Srivastava ◽  
Suraj Peri ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Quantitative Proteomics ◽  
Drug Target ◽  
Drug Targets ◽  
Large Scale ◽  
Poor Survival ◽  
Cancer Treatments ◽  
Chemical Proteomics ◽  
Protein Levels ◽  
Tumor Tissues

ABSTRACTProtein kinases (collectively, termed the kinome) represent one of the most tractable drug targets in the pursuit of new and effective cancer treatments. However, less than 20% of the kinome is currently being explored as primary targets for cancer therapy, leaving the majority of the kinome untargeted for drug therapy. Chemical proteomics approaches such as Multiplexed Inhibitor Beads and Mass Spectrometry (MIB-MS) have been developed that measure the abundance of a significant portion of the kinome, providing a strategy to interrogate kinome landscapes and dynamics. Kinome profiling of cancer cell lines using MIB-MS has been extensively characterized, however, application of this method to measure tissue kinome(s) has not been thoroughly explored. Here, we present a quantitative proteomics workflow specifically designed for kinome profiling of tissues that pairs MIB-MS with a newly designed super-SILAC kinome standard. Using this workflow, we mapped the kinome landscape of endometrial carcinoma (EC) tumors and normal endometrial (NE) tissues and identified several kinases overexpressed in EC tumors, including Serine/Arginine-Rich Splicing Factor kinase, (SRPK1). Immunohistochemical (IHC) analysis of EC tumor TMAs confirmed MIB-MS findings and showed SRPK1 protein levels were highly expressed in endometrioid and uterine serous cancer (USC) histological subtypes. Querying large-scale genomics studies of EC tumors revealed high expression of SRPK1 correlated with poor survival. Inhibition of SRPK1 in USC cells altered mRNA splicing, downregulating several oncogenes including MYC and Survivin resulting in apoptosis. Taken together, we present a SILAC-based MIB-MS kinome profiling platform for measuring kinase abundance in tumor tissues, and demonstrate its application to identify SRPK1 as a plausible kinase drug target for the treatment of EC.

scholarly journals Large Scale Profiling of Protein Isoforms Using Label-Free Quantitative Proteomics Revealed the Regulation of Nonsense-Mediated Decay in Moso Bamboo (Phyllostachys edulis)

Cells ◽  
2019 ◽  
Vol 8 (7) ◽  
pp. 744 ◽  
Author(s):  
Xiaolan Yu ◽  
Yongsheng Wang ◽  
Markus V. Kohnen ◽  
Mingxin Piao ◽  
Min Tu ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Quantitative Proteomics ◽  
Large Scale ◽  
Gene Annotation ◽  
Function Analysis ◽  
Moso Bamboo ◽  
Protein Isoforms ◽  
Label Free ◽  
Total Proteins ◽  
Protein Coding

Moso bamboo is an important forest species with a variety of ecological, economic, and cultural values. However, the gene annotation information of moso bamboo is only based on the transcriptome sequencing, lacking the evidence of proteome. The lignification and fiber in moso bamboo leads to a difficulty in the extraction of protein using conventional methods, which seriously hinders research on the proteomics of moso bamboo. The purpose of this study is to establish efficient methods for extracting the total proteins from moso bamboo for following mass spectrometry-based quantitative proteome identification. Here, we have successfully established a set of efficient methods for extracting total proteins of moso bamboo followed by mass spectrometry-based label-free quantitative proteome identification, which further improved the protein annotation of moso bamboo genes. In this study, 10,376 predicted coding genes were confirmed by quantitative proteomics, accounting for 35.8% of all annotated protein-coding genes. Proteome analysis also revealed the protein-coding potential of 1015 predicted long noncoding RNA (lncRNA), accounting for 51.03% of annotated lncRNAs. Thus, mass spectrometry-based proteomics provides a reliable method for gene annotation. Especially, quantitative proteomics revealed the translation patterns of proteins in moso bamboo. In addition, the 3284 transcript isoforms from 2663 genes identified by Pacific BioSciences (PacBio) single-molecule real-time long-read isoform sequencing (Iso-Seq) was confirmed on the protein level by mass spectrometry. Furthermore, domain analysis of mass spectrometry-identified proteins encoded in the same genomic locus revealed variations in domain composition pointing towards a functional diversification of protein isoform. Finally, we found that part transcripts targeted by nonsense-mediated mRNA decay (NMD) could also be translated into proteins. In summary, proteomic analysis in this study improves the proteomics-assisted genome annotation of moso bamboo and is valuable to the large-scale research of functional genomics in moso bamboo. In summary, this study provided a theoretical basis and technical support for directional gene function analysis at the proteomics level in moso bamboo.

Mass Spectrometry-Based Proteomics: From Cancer Biology to Protein Biomarkers, Drug Targets, and Clinical Applications

2014 ◽  
pp. e504-e510 ◽  
Author(s):  
Connie R. Jimenez ◽  
Henk M. W. Verheul
Keyword(s):  
Mass Spectrometry ◽  
Cancer Biology ◽  
Drug Targets ◽  
Large Scale ◽  
Specific Protein ◽  
Protein Profiling ◽  
Clinical Samples ◽  
Post Translational Modification ◽  
Protein Biomarkers ◽  
Mass Spectrometry Technology

Proteomics is optimally suited to bridge the gap between genomic information on the one hand and biologic functions and disease phenotypes at the other, since it studies the expression and/or post-translational modification (especially phosphorylation) of proteins—the major cellular players bringing about cellular functions—at a global level in biologic specimens. Mass spectrometry technology and (bio)informatic tools have matured to the extent that they can provide high-throughput, comprehensive, and quantitative protein inventories of cells, tissues, and biofluids in clinical samples at low level. In this article, we focus on next-generation proteomics employing nanoliquid chromatography coupled to high-resolution tandem mass spectrometry for in-depth (phospho)protein profiling of tumor tissues and (proximal) biofluids, with a focus on studies employing clinical material. In addition, we highlight emerging proteogenomic approaches for the identification of tumor-specific protein variants, and targeted multiplex mass spectrometry strategies for large-scale biomarker validation. Below we provide a discussion of recent progress, some research highlights, and challenges that remain for clinical translation of proteomic discoveries.

Expression of antibody-drug conjugates (ADC) biomarkers in colorectal cancer.

2020 ◽  
Vol 38 (4_suppl) ◽  
pp. 17-17
Author(s):  
Sheeno P. Thyparambil ◽  
Wei-Li Liao ◽  
Eunkyung An ◽  
Yuan Tian ◽  
Robert Heaton ◽  
...  
Keyword(s):  
Quantitative Proteomics ◽  
Tumor Tissue ◽  
Her2 Expression ◽  
Her2 Positive ◽  
Protein Levels ◽  
Drug Conjugates ◽  
Tumor Tissues ◽  
Ffpe Tumor ◽  
Unique Mechanism ◽  
Her2 Positivity

17 Background: Multiple ADCs are in clinical trials for CRC and the optimal strategy for selecting patients who may benefit from the treatment is evolving. Due to the unique mechanism of ADCs, patient selection should involve screening not only for the presence of the antibody target, but also for markers of resistance or response to the payload. We have built a multiplexed ADC biomarker panel in FFPE tumor tissue that simultaneously quantifies the protein levels of the antibody targets and also the payload markers. Methods: FFPE tumor tissues from 363 CRC patients were microdissected and solubilized for mass spectrometry-based targeted proteomic analysis in our CLIA certified laboratory. We quantified protein levels of EGFR, HER2, HER3, Axl, Mesothelin, FRalpha, Trop2 (antibody targets), tubulin-beta3 and TOPO1 (payload resistance and response markers, respectively) simultaneously. The multiplexed assay also quantified additional 22 clinically relevant proteins. Results: Expression of EGFR(83%), HER2(52%), HER3(21.5%), Axl(3.7%), Mesothelin(26.5%), FRalpha(3.7%), and Trop2(59.8%) may indicate likely response to ADCs. Expression of TUBB3(+) and TOPO1 (>1350amol/µg) in antibody target-positive subset may suggest resistance or response to payloads, such as taxanes and irinotecan, respectively (Table). Previously we identified that HER2 expression >750amol/µg correlated with HER2 positivity. Accordingly, 1.4% (5/355) of CRC patients were HER2 positive, of which 40% (2/5) had TOPO1 expression >1350amol/µg (75th percentile) suggesting that these 2 patients may receive benefit from a HER2/TOPO1 ADC. (+) indicates expression ≥LOQ; (-) indicates expression <LOQ. Conclusions: In patients with CRC, quantitative proteomics identified both antibody targets and markers of resistance or response to the payloads for multiple approved and investigational ADC therapies. [Table: see text]

scholarly journals Assessing Bias in Experiment Design for Large Scale Mass Spectrometry-based Quantitative Proteomics

2007 ◽  
Vol 6 (10) ◽  
pp. 1741-1748 ◽  
Author(s):  
Amol Prakash ◽  
Brian Piening ◽  
Jeff Whiteaker ◽  
Heidi Zhang ◽  
Scott A. Shaffer ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Quantitative Proteomics ◽  
Large Scale ◽  
Experiment Design

scholarly journals On ATG4B as Drug Target for Treatment of Solid Tumours—The Knowns and the Unknowns

Cells ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 53 ◽  
Author(s):  
Agrotis ◽  
Ketteler
Keyword(s):  
Drug Target ◽  
Drug Targets ◽  
Critical Evaluation ◽  
Basic Research ◽  
Cancer Treatments ◽  
Initiation Phase ◽  
Survival Pathway ◽  
Bona Fide ◽  
Vacuolar Protein

Autophagy is an evolutionary conserved stress survival pathway that has been shown to play an important role in the initiation, progression, and metastasis of multiple cancers; however, little progress has been made to date in translation of basic research to clinical application. This is partially due to an incomplete understanding of the role of autophagy in the different stages of cancer, and also to an incomplete assessment of potential drug targets in the autophagy pathway. While drug discovery efforts are on-going to target enzymes involved in the initiation phase of the autophagosome, e.g., unc51-like autophagy activating kinase (ULK)1/2, vacuolar protein sorting 34 (Vps34), and autophagy-related (ATG)7, we propose that the cysteine protease ATG4B is a bona fide drug target for the development of anti-cancer treatments. In this review, we highlight some of the recent advances in our understanding of the role of ATG4B in autophagy and its relevance to cancer, and perform a critical evaluation of ATG4B as a druggable cancer target.

scholarly journals TargetSeeker-MS: A Computational Method for Drug Target Discovery using Protein Separation Coupled to Mass Spectrometry

2019 ◽  
Author(s):  
Mathieu Lavallée-Adam ◽  
Alexander Pelletier ◽  
Jolene K. Diedrich ◽  
William Low ◽  
Antonio F. M. Pinto ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Drug Target ◽  
Drug Targets ◽  
Protein Separation ◽  
Computational Method ◽  
Drug Target Discovery ◽  
C Elegans ◽  
Computational Analyses ◽  
Novel Drug

ABSTRACTWhen coupled to mass spectrometry (MS), energetics-based protein separation (EBPS) techniques, such as thermal shift assay, have shown great potential to identify the targets of a drug on a proteome scale. Nevertheless, the computational analyses assessing the confidence of drug target predictions made by these methods have remained rudimentary and significantly differ depending on the protocol used to produce the data. To identify drug targets in datasets produced using different EBPS-MS techniques, we have developed a novel flexible computational approach named TargetSeeker-MS. We showed that TargetSeeker-MS reproducibly identifies known and novel drug targets in C. elegans and HEK293 samples that were treated with the fungicide benomyl and processed using two different EBPS techniques. We also validated a novel benomyl target in vitro. TargetSeeker-MS, which is available online, allows for the confident identification of targets of a drug on a proteome scale, thereby facilitating the evaluation of its clinical viability.

scholarly journals Stable isotope dimethyl labelling for quantitative proteomics and beyond

2016 ◽  
Vol 374 (2079) ◽  
pp. 20150364 ◽  
Author(s):  
Jue-Liang Hsu ◽  
Shu-Hui Chen
Keyword(s):  
Mass Spectrometry ◽  
Stable Isotope ◽  
Quantitative Proteomics ◽  
Large Scale ◽  
Protein Identification ◽  
Cost Effective ◽  
Quantitative Mass Spectrometry ◽  
Post Translational Modifications ◽  
Labelling Method ◽  
Identification And Characterization

Stable-isotope reductive dimethylation, a cost-effective, simple, robust, reliable and easy-to- multiplex labelling method, is widely applied to quantitative proteomics using liquid chromatography-mass spectrometry. This review focuses on biological applications of stable-isotope dimethyl labelling for a large-scale comparative analysis of protein expression and post-translational modifications based on its unique properties of the labelling chemistry. Some other applications of the labelling method for sample preparation and mass spectrometry-based protein identification and characterization are also summarized. This article is part of the themed issue ‘Quantitative mass spectrometry’.

scholarly journals Kinome Profiling of Primary Endometrial Tumors Using Multiplexed Inhibitor Beads and Mass Spectrometry Identifies SRPK1 as Candidate Therapeutic Target

2020 ◽  
Vol 19 (12) ◽  
pp. 2068-2089
Author(s):  
Alison M. Kurimchak ◽  
Vikas Kumar ◽  
Carlos Herrera-Montávez ◽  
Katherine J. Johnson ◽  
Nishi Srivastava ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Rna Splicing ◽  
Large Scale ◽  
Cell Cycle Progression ◽  
The United States ◽  
Loss Of Function ◽  
Proteomics Analysis ◽  
Compensatory Response ◽  
Cycle Progression ◽  
Protein Levels

Endometrial carcinoma (EC) is the most common gynecologic malignancy in the United States, with limited effective targeted therapies. Endometrial tumors exhibit frequent alterations in protein kinases, yet only a small fraction of the kinome has been therapeutically explored. To identify kinase therapeutic avenues for EC, we profiled the kinome of endometrial tumors and normal endometrial tissues using Multiplexed Inhibitor Beads and Mass Spectrometry (MIB-MS). Our proteomics analysis identified a network of kinases overexpressed in tumors, including Serine/Arginine-Rich Splicing Factor Kinase 1 (SRPK1). Immunohistochemical (IHC) analysis of endometrial tumors confirmed MIB-MS findings and showed SRPK1 protein levels were highly expressed in endometrioid and uterine serous cancer (USC) histological subtypes. Moreover, querying large-scale genomics studies of EC tumors revealed high expression of SRPK1 correlated with poor survival. Loss-of-function studies targeting SRPK1 in an established USC cell line demonstrated SRPK1 was integral for RNA splicing, as well as cell cycle progression and survival under nutrient deficient conditions. Profiling of USC cells identified a compensatory response to SRPK1 inhibition that involved EGFR and the up-regulation of IGF1R and downstream AKT signaling. Co-targeting SRPK1 and EGFR or IGF1R synergistically enhanced growth inhibition in serous and endometrioid cell lines, representing a promising combination therapy for EC.

scholarly journals A Multiplexed, Automated Immuno-Mass Spectrometry Assay for Simultaneous and Precise Concentrations in Cell Lines and Tumor Tissues

The Analyst ◽  
2021 ◽  
Author(s):  
Bjoern C Froehlich ◽  
Robert Popp ◽  
Constance A Sobsey ◽  
Sahar Ibrahim ◽  
Andre M LeBlanc ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Cell Lines ◽  
Drug Target ◽  
Pi3 Kinase ◽  
Mtor Pathway ◽  
Negative Regulator ◽  
Α Subunit ◽  
Tumor Tissues ◽  
Major Drug ◽  
Mass Spectrometry Assay

The PI3-kinase/AKT/mTOR pathway plays a central role in cancer signaling. While p110α is the catalytic α-subunit of PI3-kinase and a major drug target, PTEN is the main negative regulator of...

Algorithm of combining chromatography mass spectrometry-untargeted profiling and multivariate analysis for identification of marker-substances in samples of complex composition

2020 ◽  
Vol 86 (7) ◽  
pp. 12-19
Author(s):  
I. V. Plyushchenko ◽  
D. G. Shakhmatov ◽  
I. A. Rodin
Keyword(s):  
Mass Spectrometry ◽  
Multivariate Analysis ◽  
Large Scale ◽  
Complex Composition ◽  
Unified Protocol ◽  
Chromatography Mass Spectrometry ◽  
Marker Substances ◽  
Selection Testing ◽  
Untargeted Profiling

A viral development of statistical data processing, computing capabilities, chromatography-mass spectrometry, and omics technologies (technologies based on the achievements of genomics, transcriptomics, proteomics, metabolomics) in recent decades has not led to formation of a unified protocol for untargeted profiling. Systematic errors reduce the reproducibility and reliability of the obtained results, and at the same time hinder consolidation and analysis of data gained in large-scale multi-day experiments. We propose an algorithm for conducting omics profiling to identify potential markers in the samples of complex composition and present the case study of urine samples obtained from different clinical groups of patients. Profiling was carried out by the method of liquid chromatography mass spectrometry. The markers were selected using methods of multivariate analysis including machine learning and feature selection. Testing of the approach was performed using an independent dataset by clustering and projection on principal components.

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