High-Content Analysis-Based Sensitivity Prediction and Novel Therapeutics Screening for c-Met-Addicted Glioblastoma

(1) Background: Recent advances in precision oncology research rely on indicating specific genetic alterations associated with treatment sensitivity. Developing ex vivo systems to identify cancer patients who will respond to a specific drug remains important. (2) Methods: cells from 12 patients with...

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Main Authors: Jeong-Woo Oh, Yun Jeong Oh, Suji Han, Nam-Gu Her, Do-Hyun Nam
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Cancers
Subjects:
Online Access:https://www.mdpi.com/2072-6694/13/3/372
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author Jeong-Woo Oh
Yun Jeong Oh
Suji Han
Nam-Gu Her
Do-Hyun Nam
author_facet Jeong-Woo Oh
Yun Jeong Oh
Suji Han
Nam-Gu Her
Do-Hyun Nam
author_sort Jeong-Woo Oh
collection DOAJ
description (1) Background: Recent advances in precision oncology research rely on indicating specific genetic alterations associated with treatment sensitivity. Developing ex vivo systems to identify cancer patients who will respond to a specific drug remains important. (2) Methods: cells from 12 patients with glioblastoma were isolated, cultured, and subjected to high-content screening. Multi-parameter analyses assessed the c-Met level, cell viability, apoptosis, cell motility, and migration. A drug repurposing screen and large-scale drug sensitivity screening data across 59 cancer cell lines and patient-derived cells were obtained from 125 glioblastoma samples. (3) Results: High-content analysis of patient-derived cells provided robust and accurate drug responses to c-Met-targeted agents. Only the cells of one glioblastoma patient (PDC6) showed elevated c-Met level and high susceptibility to the c-Met inhibitors. Multi-parameter image analysis also reflected a decreased c-Met expression and reduced cell growth and motility by a c-Met-targeting antibody. In addition, a drug repurposing screen identified Abemaciclib as a distinct CDK4/6 inhibitor with a potent c-Met-inhibitory function. Consistent with this, we present large-scale drug sensitivity screening data showing that the Abemaciclib response correlates with the response to c-Met inhibitors. (4) Conclusions: Our study provides a new insight into high-content screening platforms supporting drug sensitivity prediction and novel therapeutics screening.
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spelling doaj.art-cffe560d13ac4a3dbeb60b8d9cf0cdc12023-12-03T13:58:57ZengMDPI AGCancers2072-66942021-01-0113337210.3390/cancers13030372High-Content Analysis-Based Sensitivity Prediction and Novel Therapeutics Screening for c-Met-Addicted GlioblastomaJeong-Woo Oh0Yun Jeong Oh1Suji Han2Nam-Gu Her3Do-Hyun Nam4Institute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, KoreaInstitute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, KoreaResearch Institute, National Cancer Center, Goyang 10408, KoreaInstitute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, KoreaInstitute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, Korea(1) Background: Recent advances in precision oncology research rely on indicating specific genetic alterations associated with treatment sensitivity. Developing ex vivo systems to identify cancer patients who will respond to a specific drug remains important. (2) Methods: cells from 12 patients with glioblastoma were isolated, cultured, and subjected to high-content screening. Multi-parameter analyses assessed the c-Met level, cell viability, apoptosis, cell motility, and migration. A drug repurposing screen and large-scale drug sensitivity screening data across 59 cancer cell lines and patient-derived cells were obtained from 125 glioblastoma samples. (3) Results: High-content analysis of patient-derived cells provided robust and accurate drug responses to c-Met-targeted agents. Only the cells of one glioblastoma patient (PDC6) showed elevated c-Met level and high susceptibility to the c-Met inhibitors. Multi-parameter image analysis also reflected a decreased c-Met expression and reduced cell growth and motility by a c-Met-targeting antibody. In addition, a drug repurposing screen identified Abemaciclib as a distinct CDK4/6 inhibitor with a potent c-Met-inhibitory function. Consistent with this, we present large-scale drug sensitivity screening data showing that the Abemaciclib response correlates with the response to c-Met inhibitors. (4) Conclusions: Our study provides a new insight into high-content screening platforms supporting drug sensitivity prediction and novel therapeutics screening.https://www.mdpi.com/2072-6694/13/3/372high-content analysistargeted therapeuticsc-Met inhibitorCDK4/6 inhibitor
spellingShingle Jeong-Woo Oh
Yun Jeong Oh
Suji Han
Nam-Gu Her
Do-Hyun Nam
High-Content Analysis-Based Sensitivity Prediction and Novel Therapeutics Screening for c-Met-Addicted Glioblastoma
Cancers
high-content analysis
targeted therapeutics
c-Met inhibitor
CDK4/6 inhibitor
title High-Content Analysis-Based Sensitivity Prediction and Novel Therapeutics Screening for c-Met-Addicted Glioblastoma
title_full High-Content Analysis-Based Sensitivity Prediction and Novel Therapeutics Screening for c-Met-Addicted Glioblastoma
title_fullStr High-Content Analysis-Based Sensitivity Prediction and Novel Therapeutics Screening for c-Met-Addicted Glioblastoma
title_full_unstemmed High-Content Analysis-Based Sensitivity Prediction and Novel Therapeutics Screening for c-Met-Addicted Glioblastoma
title_short High-Content Analysis-Based Sensitivity Prediction and Novel Therapeutics Screening for c-Met-Addicted Glioblastoma
title_sort high content analysis based sensitivity prediction and novel therapeutics screening for c met addicted glioblastoma
topic high-content analysis
targeted therapeutics
c-Met inhibitor
CDK4/6 inhibitor
url https://www.mdpi.com/2072-6694/13/3/372
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