iTReX: Interactive exploration of mono- and combination therapy dose response profiling data.

Asymmetric sensitivity scoring Differential combination sensitivity scoring Drug target networks Interactive drug screen analysis Personalized medicine Therapy response profiling and exploration

Journal

Pharmacological research
ISSN: 1096-1186
Titre abrégé: Pharmacol Res
Pays: Netherlands
ID NLM: 8907422

Informations de publication

Date de publication:
01 2022
Historique:
received: 10 09 2021
revised: 18 11 2021
accepted: 19 11 2021
pubmed: 2 12 2021
medline: 23 3 2022
entrez: 1 12 2021
Statut: ppublish

Résumé

High throughput screening methods, measuring the sensitivity and resistance of tumor cells to drug treatments have been rapidly evolving. Not only do these screens allow correlating response profiles to tumor genomic features for developing novel predictors of treatment response, but they can also add evidence for therapy decision making in precision oncology. Recent analysis methods developed for either assessing single agents or combination drug efficacies enable quantification of dose-response curves with restricted symmetric fit settings. Here, we introduce iTReX, a user-friendly and interactive Shiny/R application, for both the analysis of mono- and combination therapy responses. The application features an extended version of the drug sensitivity score (DSS) based on the integral of an advanced five-parameter dose-response curve model and a differential DSS for combination therapy profiling. Additionally, iTReX includes modules that visualize drug target interaction networks and support the detection of matches between top therapy hits and the sample omics features to enable the identification of druggable targets and biomarkers. iTReX enables the analysis of various quantitative drug or therapy response readouts (e.g. luminescence, fluorescence microscopy) and multiple treatment strategies (drug treatments, radiation). Using iTReX we validate a cost-effective drug combination screening approach and reveal the application's ability to identify potential sample-specific biomarkers based on drug target interaction networks. The iTReX web application is accessible at https://itrex.kitz-heidelberg.de.

Identifiants

pubmed: 34848323
pii: S1043-6618(21)00580-6
doi: 10.1016/j.phrs.2021.105996
pii:
doi:

Substances chimiques

Antineoplastic Agents 0

Banques de données

DRKS
['DRKS00007623']

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

105996

Informations de copyright

Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.

Auteurs

Dina ElHarouni (D)

Bioinformatics and Omics Data Analytics, German Cancer Research Center (DKFZ), Heidelberg, Germany; Hopp Children's Cancer Center (KiTZ), Heidelberg, Germany; Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany; Faculty of Biosciences, Heidelberg University, Heidelberg, Germany.

Yannick Berker (Y)

Hopp Children's Cancer Center (KiTZ), Heidelberg, Germany; Clinical Cooperation Unit Pediatric Oncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.

Heike Peterziel (H)

Hopp Children's Cancer Center (KiTZ), Heidelberg, Germany; Clinical Cooperation Unit Pediatric Oncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.

Apurva Gopisetty (A)

Hopp Children's Cancer Center (KiTZ), Heidelberg, Germany; Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.

Laura Turunen (L)

Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.

Sina Kreth (S)

Hopp Children's Cancer Center (KiTZ), Heidelberg, Germany; Division of Neuroblastoma Genomics, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.

Sabine A Stainczyk (SA)

Hopp Children's Cancer Center (KiTZ), Heidelberg, Germany; Division of Neuroblastoma Genomics, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.

Ina Oehme (I)

Hopp Children's Cancer Center (KiTZ), Heidelberg, Germany; Clinical Cooperation Unit Pediatric Oncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.

Vilja Pietiäinen (V)

Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.

Natalie Jäger (N)

Hopp Children's Cancer Center (KiTZ), Heidelberg, Germany; Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.

Olaf Witt (O)

Hopp Children's Cancer Center (KiTZ), Heidelberg, Germany; Clinical Cooperation Unit Pediatric Oncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany; Department of Pediatric Oncology, Hematology, Immunology and Pulmonology Heidelberg University Hospital, Heidelberg, Germany.

Matthias Schlesner (M)

Bioinformatics and Omics Data Analytics, German Cancer Research Center (DKFZ), Heidelberg, Germany; Biomedical Informatics, Data Mining and Data Analytics, Faculty of Applied Computer Science and Medical Faculty, University of Augsburg, Augsburg, Germany.

Sina Oppermann (S)

Hopp Children's Cancer Center (KiTZ), Heidelberg, Germany; Clinical Cooperation Unit Pediatric Oncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.

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Classifications MeSH