Literature DB >> 29660496

Quantitative targeted proteomic analysis of potential markers of tyrosine kinase inhibitor (TKI) sensitivity in EGFR mutated lung adenocarcinoma.

Shivangi Awasthi1, Tapan Maity2, Benjamin L Oyler3, Yue Qi2, Xu Zhang2, David R Goodlett4, Udayan Guha5.   

Abstract

Lung cancer causes the highest mortality among all cancers. Patients harboring kinase domain mutations in the epidermal growth factor receptor (EGFR) respond to EGFR tyrosine kinase inhibitors (TKIs), however, acquired resistance always develops. Moreover, 30-40% of patients with EGFR mutations exhibit primary resistance. Hence, there is an unmet need for additional biomarkers of TKI sensitivity that complement EGFR mutation testing and predict treatment response. We previously identified phosphopeptides whose phosphorylation is inhibited upon treatment with EGFR TKIs, erlotinib and afatinib in TKI sensitive cells, but not in resistant cells. These phosphosites are potential biomarkers of TKI sensitivity. Here, we sought to develop modified immuno-multiple reaction monitoring (immuno-MRM)-based quantitation assays for select phosphosites including EGFR-pY1197, pY1172, pY998, AHNAK-pY160, pY715, DAPP1-pY139, CAV1-pY14, INPPL1-pY1135, NEDD9-pY164, NF1-pY2579, and STAT5A-pY694. These sites were significantly hypophosphorylated by erlotinib and a 3rd generation EGFR TKI, osimertinib, in TKI-sensitive H3255 cells, which harbor the TKI-sensitizing EGFRL858R mutation. However, in H1975 cells, which harbor the TKI-resistant EGFRL858R/T790M mutant, osimertinib, but not erlotinib, could significantly inhibit phosphorylation of EGFR-pY-1197, STAT5A-pY694 and CAV1-pY14, suggesting these sites also predict response in TKI-resistant cells. We could further validate EGFR-pY-1197 as a biomarker of TKI sensitivity by developing a calibration curve-based modified immuno-MRM assay. SIGNIFICANCE: In this report, we have shown the development and optimization of MRM assays coupled with global phosphotyrosine enrichment (modified immuno-MRM) for a list of 11 phosphotyrosine peptides. Our optimized assays identified the targets reproducibly in biological samples with good selectivity. We also developed and characterized quantitation methods to determine endogenous abundance of these targets and correlated the results of the relative quantification with amounts estimated from the calibration curves. This approach represents a way to validate and verify biomarker candidates discovered from large-scale global phospho-proteomics analysis. The application of these modified immuno-MRM assays in lung adenocarcinoma cells provides proof-of concept for the feasibility of clinical applications. These assays may be used in prospective clinical studies of EGFR TKI treatment of EGFR mutant lung cancer to correlate treatment response and other clinical endpoints.
Copyright © 2018. Published by Elsevier B.V.

Entities:  

Keywords:  EGFR; Lung cancer; MRM; Phosphoproteomics; Targeted proteomics; Tyrosine kinase inhibitor

Mesh:

Substances:

Year:  2018        PMID: 29660496      PMCID: PMC7984720          DOI: 10.1016/j.jprot.2018.04.005

Source DB:  PubMed          Journal:  J Proteomics        ISSN: 1874-3919            Impact factor:   4.044


  48 in total

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2.  Evaluation of absolute peptide quantitation strategies using selected reaction monitoring.

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Journal:  Proteomics       Date:  2011-02-16       Impact factor: 3.984

3.  Peptide Immunoaffinity Enrichment and Targeted Mass Spectrometry Enables Multiplex, Quantitative Pharmacodynamic Studies of Phospho-Signaling.

Authors:  Jeffrey R Whiteaker; Lei Zhao; Ping Yan; Richard G Ivey; Uliana J Voytovich; Heather D Moore; Chenwei Lin; Amanda G Paulovich
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Journal:  N Engl J Med       Date:  2010-06-24       Impact factor: 91.245

5.  Immobilized Metal Affinity Chromatography Coupled to Multiple Reaction Monitoring Enables Reproducible Quantification of Phospho-signaling.

Authors:  Jacob J Kennedy; Ping Yan; Lei Zhao; Richard G Ivey; Uliana J Voytovich; Heather D Moore; Chenwei Lin; Era L Pogosova-Agadjanyan; Derek L Stirewalt; Kerryn W Reding; Jeffrey R Whiteaker; Amanda G Paulovich
Journal:  Mol Cell Proteomics       Date:  2015-11-30       Impact factor: 5.911

6.  Cancer Statistics, 2017.

Authors:  Rebecca L Siegel; Kimberly D Miller; Ahmedin Jemal
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7.  Preexistence and clonal selection of MET amplification in EGFR mutant NSCLC.

Authors:  Alexa B Turke; Kreshnik Zejnullahu; Yi-Long Wu; Youngchul Song; Dora Dias-Santagata; Eugene Lifshits; Luca Toschi; Andrew Rogers; Tony Mok; Lecia Sequist; Neal I Lindeman; Carly Murphy; Sara Akhavanfard; Beow Y Yeap; Yun Xiao; Marzia Capelletti; A John Iafrate; Charles Lee; James G Christensen; Jeffrey A Engelman; Pasi A Jänne
Journal:  Cancer Cell       Date:  2010-01-19       Impact factor: 31.743

8.  Small cell lung cancer transformation and T790M mutation: complimentary roles in acquired resistance to kinase inhibitors in lung cancer.

Authors:  Kenichi Suda; Isao Murakami; Kazuko Sakai; Hiroshi Mizuuchi; Shigeki Shimizu; Katsuaki Sato; Kenji Tomizawa; Shuta Tomida; Yasushi Yatabe; Kazuto Nishio; Tetsuya Mitsudomi
Journal:  Sci Rep       Date:  2015-09-24       Impact factor: 4.379

9.  Concerted regulation of focal adhesion dynamics by galectin-3 and tyrosine-phosphorylated caveolin-1.

Authors:  Jacky G Goetz; Bharat Joshi; Patrick Lajoie; Scott S Strugnell; Trevor Scudamore; Liliana D Kojic; Ivan R Nabi
Journal:  J Cell Biol       Date:  2008-03-17       Impact factor: 10.539

10.  Comprehensive molecular profiling of lung adenocarcinoma.

Authors: 
Journal:  Nature       Date:  2014-07-09       Impact factor: 49.962

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Journal:  PLoS One       Date:  2020-06-18       Impact factor: 3.240

2.  E-cadherin and NEDD9 expression in primary colorectal cancer, metastatic lymph nodes and liver metastases.

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3.  Dataset describing the development, optimization and application of SRM/MRM based targeted proteomics strategy for quantification of potential biomarkers of EGFR TKI sensitivity.

Authors:  Shivangi Awasthi; Tapan Maity; Benjamin L Oyler; Xu Zhang; David R Goodlett; Udayan Guha
Journal:  Data Brief       Date:  2018-05-02

4.  A GWAS approach identifies Dapp1 as a determinant of air pollution-induced airway hyperreactivity.

Authors:  Hadi Maazi; Jaana A Hartiala; Yuzo Suzuki; Amanda L Crow; Pedram Shafiei Jahani; Jonathan Lam; Nisheel Patel; Diamanda Rigas; Yi Han; Pin Huang; Eleazar Eskin; Aldons J Lusis; Frank D Gilliland; Omid Akbari; Hooman Allayee
Journal:  PLoS Genet       Date:  2019-12-23       Impact factor: 5.917

5.  SCAMP3 is a mutant EGFR phosphorylation target and a tumor suppressor in lung adenocarcinoma.

Authors:  Abhilash Venugopalan; Matthew Lynberg; Constance M Cultraro; Khoa Dang P Nguyen; Xu Zhang; Maryam Waris; Noelle Dayal; Asebot Abebe; Tapan K Maity; Udayan Guha
Journal:  Oncogene       Date:  2021-04-13       Impact factor: 9.867

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