Literature DB >> 32102969

Phosphotyrosine-based Phosphoproteomics for Target Identification and Drug Response Prediction in AML Cell Lines.

Carolien van Alphen1, Jacqueline Cloos2, Robin Beekhof3, David G J Cucchi2, Sander R Piersma3, Jaco C Knol3, Alex A Henneman3, Thang V Pham3, Johan van Meerloo4, Gert J Ossenkoppele4, Henk M W Verheul5, Jeroen J W M Janssen4, Connie R Jimenez6.   

Abstract

Acute myeloid leukemia (AML) is a clonal disorder arising from hematopoietic myeloid progenitors. Aberrantly activated tyrosine kinases (TK) are involved in leukemogenesis and are associated with poor treatment outcome. Kinase inhibitor (KI) treatment has shown promise in improving patient outcome in AML. However, inhibitor selection for patients is suboptimal.In a preclinical effort to address KI selection, we analyzed a panel of 16 AML cell lines using phosphotyrosine (pY) enrichment-based, label-free phosphoproteomics. The Integrative Inferred Kinase Activity (INKA) algorithm was used to identify hyperphosphorylated, active kinases as candidates for KI treatment, and efficacy of selected KIs was tested.Heterogeneous signaling was observed with between 241 and 2764 phosphopeptides detected per cell line. Of 4853 identified phosphopeptides with 4229 phosphosites, 4459 phosphopeptides (4430 pY) were linked to 3605 class I sites (3525 pY). INKA analysis in single cell lines successfully pinpointed driver kinases (PDGFRA, JAK2, KIT and FLT3) corresponding with activating mutations present in these cell lines. Furthermore, potential receptor tyrosine kinase (RTK) drivers, undetected by standard molecular analyses, were identified in four cell lines (FGFR1 in KG-1 and KG-1a, PDGFRA in Kasumi-3, and FLT3 in MM6). These cell lines proved highly sensitive to specific KIs. Six AML cell lines without a clear RTK driver showed evidence of MAPK1/3 activation, indicative of the presence of activating upstream RAS mutations. Importantly, FLT3 phosphorylation was demonstrated in two clinical AML samples with a FLT3 internal tandem duplication (ITD) mutation.Our data show the potential of pY-phosphoproteomics and INKA analysis to provide insight in AML TK signaling and identify hyperactive kinases as potential targets for treatment in AML cell lines. These results warrant future investigation of clinical samples to further our understanding of TK phosphorylation in relation to clinical response in the individual patient.
© 2020 van Alphen et al.

Entities:  

Keywords:  Tyrosine kinases; acute myeloid leukemia; cell signaling; drug targets; kinase inhibitors; mass spectrometry; molecular biology; personalized medicine; phosphoproteome; phosphoproteomics; receptor tyrosine kinases

Mesh:

Substances:

Year:  2020        PMID: 32102969      PMCID: PMC7196578          DOI: 10.1074/mcp.RA119.001504

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  67 in total

1.  FLT3 internal tandem duplication mutations in adult acute myeloid leukaemia define a high-risk group.

Authors:  F M Abu-Duhier; A C Goodeve; G A Wilson; M A Gari; I R Peake; D C Rees; E A Vandenberghe; P R Winship; J T Reilly
Journal:  Br J Haematol       Date:  2000-10       Impact factor: 6.998

2.  Phosphotyrosine profiling identifies the KG-1 cell line as a model for the study of FGFR1 fusions in acute myeloid leukemia.

Authors:  Ting-Lei Gu; Valerie L Goss; Cynthia Reeves; Lana Popova; Julie Nardone; Joan Macneill; Denise K Walters; Yi Wang; John Rush; Michael J Comb; Brian J Druker; Roberto D Polakiewicz
Journal:  Blood       Date:  2006-08-31       Impact factor: 22.113

3.  PANTHER pathway: an ontology-based pathway database coupled with data analysis tools.

Authors:  Huaiyu Mi; Paul Thomas
Journal:  Methods Mol Biol       Date:  2009

4.  Activating mutation of D835 within the activation loop of FLT3 in human hematologic malignancies.

Authors:  Y Yamamoto; H Kiyoi; Y Nakano; R Suzuki; Y Kodera; S Miyawaki; N Asou; K Kuriyama; F Yagasaki; C Shimazaki; H Akiyama; K Saito; M Nishimura; T Motoji; K Shinagawa; A Takeshita; H Saito; R Ueda; R Ohno; T Naoe
Journal:  Blood       Date:  2001-04-15       Impact factor: 22.113

Review 5.  The role of kinase inhibitors in the treatment of patients with acute myeloid leukemia.

Authors:  Catherine C Smith; Neil P Shah
Journal:  Am Soc Clin Oncol Educ Book       Date:  2013

6.  Preclinical anticancer activity of the potent, oral Src inhibitor AZD0530.

Authors:  Tim P Green; Mike Fennell; Robin Whittaker; Jon Curwen; Vivien Jacobs; Jack Allen; Armelle Logie; Judith Hargreaves; D Mark Hickinson; Robert W Wilkinson; Paul Elvin; Brigitte Boyer; Neil Carragher; Patrick A Plé; Alun Bermingham; Geoffrey A Holdgate; Walter H J Ward; Laurent F Hennequin; Barry R Davies; Gerard F Costello
Journal:  Mol Oncol       Date:  2009-02-07       Impact factor: 6.603

7.  Phosphoproteomic analysis of AML cell lines identifies leukemic oncogenes.

Authors:  Denise K Walters; Valerie L Goss; Eric P Stoffregen; Ting-Lei Gu; Kimberly Lee; Julie Nardone; Laura McGreevey; Michael C Heinrich; Michael W Deininger; Roberto Polakiewicz; Brian J Druker
Journal:  Leuk Res       Date:  2006-02-07       Impact factor: 3.156

8.  The identification of 2-(1H-indazol-4-yl)-6-(4-methanesulfonyl-piperazin-1-ylmethyl)-4-morpholin-4-yl-thieno[3,2-d]pyrimidine (GDC-0941) as a potent, selective, orally bioavailable inhibitor of class I PI3 kinase for the treatment of cancer .

Authors:  Adrian J Folkes; Khatereh Ahmadi; Wendy K Alderton; Sonia Alix; Stewart J Baker; Gary Box; Irina S Chuckowree; Paul A Clarke; Paul Depledge; Suzanne A Eccles; Lori S Friedman; Angela Hayes; Timothy C Hancox; Arumugam Kugendradas; Letitia Lensun; Pauline Moore; Alan G Olivero; Jodie Pang; Sonal Patel; Giles H Pergl-Wilson; Florence I Raynaud; Anthony Robson; Nahid Saghir; Laurent Salphati; Sukhjit Sohal; Mark H Ultsch; Melanie Valenti; Heidi J A Wallweber; Nan Chi Wan; Christian Wiesmann; Paul Workman; Alexander Zhyvoloup; Marketa J Zvelebil; Stephen J Shuttleworth
Journal:  J Med Chem       Date:  2008-09-25       Impact factor: 7.446

9.  Gene expression profiles associated with pediatric relapsed AML.

Authors:  Costa Bachas; Gerrit Jan Schuurhuis; C Michel Zwaan; Marry M van den Heuvel-Eibrink; Monique L den Boer; Eveline S J M de Bont; Zinia J Kwidama; Dirk Reinhardt; Ursula Creutzig; Valérie de Haas; Gertjan J L Kaspers; Jacqueline Cloos
Journal:  PLoS One       Date:  2015-04-07       Impact factor: 3.240

10.  The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible.

Authors:  Damian Szklarczyk; John H Morris; Helen Cook; Michael Kuhn; Stefan Wyder; Milan Simonovic; Alberto Santos; Nadezhda T Doncheva; Alexander Roth; Peer Bork; Lars J Jensen; Christian von Mering
Journal:  Nucleic Acids Res       Date:  2016-10-18       Impact factor: 16.971

View more
  5 in total

Review 1.  Phosphoproteomics: a valuable tool for uncovering molecular signaling in cancer cells.

Authors:  Jacqueline S Gerritsen; Forest M White
Journal:  Expert Rev Proteomics       Date:  2021-09-16       Impact factor: 4.250

2.  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

Review 3.  Combining Mass Spectrometry-Based Phosphoproteomics with a Network-Based Approach to Reveal FLT3-Dependent Mechanisms of Chemoresistance.

Authors:  Giusj Monia Pugliese; Sara Latini; Giorgia Massacci; Livia Perfetto; Francesca Sacco
Journal:  Proteomes       Date:  2021-04-27

4.  FLT3-ITD transduces autonomous growth signals during its biosynthetic trafficking in acute myelogenous leukemia cells.

Authors:  Kouhei Yamawaki; Isamu Shiina; Takatsugu Murata; Satoru Tateyama; Yutarou Maekawa; Mariko Niwa; Motoyuki Shimonaka; Koji Okamoto; Toshihiro Suzuki; Toshirou Nishida; Ryo Abe; Yuuki Obata
Journal:  Sci Rep       Date:  2021-11-22       Impact factor: 4.379

5.  Proteomic and phosphoproteomic measurements enhance ability to predict ex vivo drug response in AML.

Authors:  Sara J C Gosline; Cristina Tognon; Michael Nestor; Sunil Joshi; Rucha Modak; Alisa Damnernsawad; Camilo Posso; Jamie Moon; Joshua R Hansen; Chelsea Hutchinson-Bunch; James C Pino; Marina A Gritsenko; Karl K Weitz; Elie Traer; Jeffrey Tyner; Brian Druker; Anupriya Agarwal; Paul Piehowski; Jason E McDermott; Karin Rodland
Journal:  Clin Proteomics       Date:  2022-07-27       Impact factor: 5.000

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.