Literature DB >> 24929890

Phenotypic drug screening and target validation for improved personalized therapy reveal the complexity of phenotype-genotype correlations in clear cell renal cell carcinoma.

Meike Schneider1, Julia Schüler2, Rouven Höfflin3, Nina Korzeniewski3, Carsten Grüllich4, Wilfried Roth5, Dogu Teber6, Boris Hadaschik6, Sascha Pahernik6, Markus Hohenfellner6, Stefan Duensing7.   

Abstract

OBJECTIVES: Novel personalized therapeutic approaches are urgently needed for patients with metastatic clear cell renal cell carcinoma (ccRCC). METHODS AND MATERIALS: We combined the development of a primary patient-derived ccRCC cell line with a phenotypic drug screen consisting of 101 approved anticancer compounds.
RESULTS: We identified the MNNG HOS transforming gene (MET)-anaplastic lymphoma receptor tyrosine kinase (ALK) inhibitor crizotinib as the top hit of our drug screen, whereas compounds targeting the vascular endothelial growth factor (VEGF) or mammalian target of rapamycin (mTOR) pathway showed no or only minor in vitro activity. Among the known major crizotinib targets MET, ALK, and ROS-1, only MET was expressed in our ccRCC cell line. Subsequent sequence analysis revealed a heterozygous R988C mutation of the MET gene and a VHL deletion in both the primary tumor and the tumor-derived ccRCC cell line. However, we were unable to show an activation of MET and, further, MET knockdown did not result in increased apoptosis or cytotoxicity. Therefore, our results suggest that MET R988C does not function as a major oncogenic driver mutation but rather represents a sequence variant. However, we provide evidence that the cytotoxic effect of crizotinib in our cell line model correlates with its ability to inhibit P-glycoprotein (ABCB1)-associated transport functions.
CONCLUSIONS: Our study shows that a phenotypic screen of a patient-derived tumor cell line can identify compounds with antitumor activity but with an unexpected mode of action. Our results underscore that target validation and phenotype-genotype correlations remain a major experimental challenge. The implications of our findings for a personalized management of patients with cancer are discussed.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Crizotinib; Drug screen; MET; Personalized therapy; Renal cancer

Mesh:

Substances:

Year:  2014        PMID: 24929890     DOI: 10.1016/j.urolonc.2014.03.011

Source DB:  PubMed          Journal:  Urol Oncol        ISSN: 1078-1439            Impact factor:   3.498


  7 in total

Review 1.  Targeting glycogen metabolism in bladder cancer.

Authors:  Carolyn Ritterson Lew; Sunny Guin; Dan Theodorescu
Journal:  Nat Rev Urol       Date:  2015-05-26       Impact factor: 14.432

2.  Effective downsizing but enhanced intratumoral heterogeneity following neoadjuvant sorafenib in patients with non-metastatic renal cell carcinoma.

Authors:  Gencay Hatiboglu; Markus Hohenfellner; Aysenur Arslan; Boris Hadaschik; Dogu Teber; Jan Philipp Radtke; Peter Hallscheidt; Yanis Tolstov; Wilfried Roth; Carsten Grüllich; Johannes Huesing; Stefan Duensing; Sascha Pahernik
Journal:  Langenbecks Arch Surg       Date:  2016-12-23       Impact factor: 3.445

Review 3.  Kidney Cancer Models for Pre-Clinical Drug Discovery: Challenges and Opportunities.

Authors:  Laura Pohl; Jana Friedhoff; Christina Jurcic; Miriam Teroerde; Isabella Schindler; Konstantina Strepi; Felix Schneider; Adam Kaczorowski; Markus Hohenfellner; Anette Duensing; Stefan Duensing
Journal:  Front Oncol       Date:  2022-05-10       Impact factor: 5.738

4.  Whole-Exome Sequencing Identifies the VHL Mutation (c.262T > C, p.Try88Arg) in Non-Obstructive Azoospermia-Associated Cystic Renal Cell Carcinoma.

Authors:  Yonghong Man; Xuejun Shang; Chunyu Liu; Wei Zhang; Qian Huang; Suheng Ma; Rita Shiang; Feng Zhang; Ling Zhang; Zhibing Zhang
Journal:  Curr Oncol       Date:  2022-03-28       Impact factor: 3.109

5.  Targeting the Proteasome in Advanced Renal Cell Carcinoma: Complexity and Limitations of Patient-Individualized Preclinical Drug Discovery.

Authors:  Jielin Li; Laura Pohl; Julia Schüler; Nina Korzeniewski; Philipp Reimold; Adam Kaczorowski; Weibin Hou; Stefanie Zschäbitz; Cathleen Nientiedt; Dirk Jäger; Markus Hohenfellner; Anette Duensing; Stefan Duensing
Journal:  Biomedicines       Date:  2021-05-31

6.  Spatial niche formation but not malignant progression is a driving force for intratumoural heterogeneity.

Authors:  Rouven Hoefflin; Bernd Lahrmann; Gregor Warsow; Daniel Hübschmann; Cathleen Spath; Britta Walter; Xin Chen; Luisa Hofer; Stephan Macher-Goeppinger; Yanis Tolstov; Nina Korzeniewski; Anette Duensing; Carsten Grüllich; Dirk Jäger; Sven Perner; Gita Schönberg; Joanne Nyarangi-Dix; Sanjay Isaac; Gencay Hatiboglu; Dogu Teber; Boris Hadaschik; Sascha Pahernik; Wilfried Roth; Roland Eils; Matthias Schlesner; Holger Sültmann; Markus Hohenfellner; Niels Grabe; Stefan Duensing
Journal:  Nat Commun       Date:  2016-06-13       Impact factor: 14.919

7.  Screening of metabolic modulators identifies new strategies to target metabolic reprogramming in melanoma.

Authors:  Cecilie Abildgaard; Salvatore Rizza; Helle Christiansen; Steffen Schmidt; Christina Dahl; Ahmad Abdul-Al; Annette Christensen; Giuseppe Filomeni; Per Guldberg
Journal:  Sci Rep       Date:  2021-02-23       Impact factor: 4.379

  7 in total

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