Literature DB >> 28442448

Phosphotyrosine-based-phosphoproteomics scaled-down to biopsy level for analysis of individual tumor biology and treatment selection.

Mariette Labots1, Johannes C van der Mijn1, Robin Beekhof1, Sander R Piersma1, Richard R de Goeij-de Haas1, Thang V Pham1, Jaco C Knol1, Henk Dekker1, Nicole C T van Grieken2, Henk M W Verheul3, Connie R Jiménez4.   

Abstract

Mass spectrometry-based phosphoproteomics of cancer cell and tissue lysates provides insight in aberrantly activated signaling pathways and potential drug targets. For improved understanding of individual patient's tumor biology and to allow selection of tyrosine kinase inhibitors in individual patients, phosphoproteomics of small clinical samples should be feasible and reproducible. We aimed to scale down a pTyr-phosphopeptide enrichment protocol to biopsy-level protein input and assess reproducibility and applicability to tumor needle biopsies. To this end, phosphopeptide immunoprecipitation using anti-phosphotyrosine beads was performed using 10, 5 and 1mg protein input from lysates of colorectal cancer (CRC) cell line HCT116. Multiple needle biopsies from 7 human CRC resection specimens were analyzed at the 1mg-level. The total number of phosphopeptides captured and detected by LC-MS/MS ranged from 681 at 10mg input to 471 at 1mg HCT116 protein. ID-reproducibility ranged from 60.5% at 10mg to 43.9% at 1mg. Per 1mg-level biopsy sample, >200 phosphopeptides were identified with 57% ID-reproducibility between paired tumor biopsies. Unsupervised analysis clustered biopsies from individual patients together and revealed known and potential therapeutic targets. SIGNIFICANCE: This study demonstrates the feasibility of label-free pTyr-phosphoproteomics at the tumor biopsy level based on reproducible analyses using 1mg of protein input. The considerable number of identified phosphopeptides at this level is attributed to an effective down-scaled immuno-affinity protocol as well as to the application of ID propagation in the data processing and analysis steps. Unsupervised cluster analysis reveals patient-specific profiles. Together, these findings pave the way for clinical trials in which pTyr-phosphoproteomics will be performed on pre- and on-treatment biopsies. Such studies will improve our understanding of individual tumor biology and may enable future pTyr-phosphoproteomics-based personalized medicine.
Copyright © 2017. Published by Elsevier B.V.

Entities:  

Keywords:  Cancer; MS/MS; Personalized medicine; Phosphoproteomics; Phosphotyrosine signaling; Targeted therapy; Treatment selection

Mesh:

Substances:

Year:  2017        PMID: 28442448     DOI: 10.1016/j.jprot.2017.04.014

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


  9 in total

1.  Quantitative Analysis of Tyrosine Phosphorylation from FFPE Tissues Reveals Patient-Specific Signaling Networks.

Authors:  Ishwar N Kohale; Danielle M Burgenske; Ann C Mladek; Katrina K Bakken; Jenevieve Kuang; Judy C Boughey; Liewei Wang; Jodi M Carter; Eric B Haura; Matthew P Goetz; Jann N Sarkaria; Forest M White
Journal:  Cancer Res       Date:  2021-05-20       Impact factor: 12.701

2.  Centromere protein F (CENPF), a microtubule binding protein, modulates cancer metabolism by regulating pyruvate kinase M2 phosphorylation signaling.

Authors:  Muhammad Shahid; Min Young Lee; Honit Piplani; Allen M Andres; Bo Zhou; Austin Yeon; Minjung Kim; Hyung L Kim; Jayoung Kim
Journal:  Cell Cycle       Date:  2018-12-17       Impact factor: 5.173

3.  High-Density, Targeted Monitoring of Tyrosine Phosphorylation Reveals Activated Signaling Networks in Human Tumors.

Authors:  Lauren E Stopfer; Cameron T Flower; Aaron S Gajadhar; Bhavin Patel; Sebastien Gallien; Daniel Lopez-Ferrer; Forest M White
Journal:  Cancer Res       Date:  2021-01-28       Impact factor: 13.312

Review 4.  Current Strategies to Enhance Anti-Tumour Immunity.

Authors:  Katherine W Cook; Lindy G Durrant; Victoria A Brentville
Journal:  Biomedicines       Date:  2018-03-23

5.  INKA, an integrative data analysis pipeline for phosphoproteomic inference of active kinases.

Authors:  Robin Beekhof; Carolien van Alphen; Alex A Henneman; Jaco C Knol; Thang V Pham; Frank Rolfs; Mariette Labots; Evan Henneberry; Tessa Ys Le Large; Richard R de Haas; Sander R Piersma; Valentina Vurchio; Andrea Bertotti; Livio Trusolino; Henk Mw Verheul; Connie R Jimenez
Journal:  Mol Syst Biol       Date:  2019-04-12       Impact factor: 11.429

6.  Kinase Inhibitor Treatment of Patients with Advanced Cancer Results in High Tumor Drug Concentrations and in Specific Alterations of the Tumor Phosphoproteome.

Authors:  Mariette Labots; Thang V Pham; Richard J Honeywell; Jaco C Knol; Robin Beekhof; Richard de Goeij-de Haas; Henk Dekker; Maarten Neerincx; Sander R Piersma; Johannes C van der Mijn; Donald L van der Peet; Martijn R Meijerink; Godefridus J Peters; Nicole C T van Grieken; Connie R Jiménez; Henk M W Verheul
Journal:  Cancers (Basel)       Date:  2020-02-01       Impact factor: 6.639

Review 7.  Mass Spectrometric-Based Proteomics for Biomarker Discovery in Osteosarcoma: Current Status and Future Direction.

Authors:  Nutnicha Sirikaew; Dumnoensun Pruksakorn; Parunya Chaiyawat; Somchai Chutipongtanate
Journal:  Int J Mol Sci       Date:  2022-08-28       Impact factor: 6.208

8.  Selection of Protein Kinase Inhibitors Based on Tumor Tissue Kinase Activity Profiles in Patients with Refractory Solid Malignancies: An Interventional Molecular Profiling Study.

Authors:  Mariette Labots; Johannes C Van der Mijn; Henk Dekker; Rita Ruijter; Thang V Pham; Hans J Van der Vliet; Jacobus J M Van der Hoeven; Gerrit A Meijer; Henk M W Verheul
Journal:  Oncologist       Date:  2018-07-17

9.  Identification of Phospho-Tyrosine Targets as a Strategy for the Treatment of Esophageal Adenocarcinoma Cells.

Authors:  John Lee; Rongbing Chen; T Mohanakumar; Ross Bremner; Sumeet Mittal; Timothy P Fleming
Journal:  Onco Targets Ther       Date:  2021-06-21       Impact factor: 4.147

  9 in total

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