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Related Experiment Video

Updated: Jul 23, 2025

Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts

Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts

Published on: July 25, 2020

AMBAR - Interactive Alteration annotations for molecular tumor boards.

Axel Fürstberger¹, Nensi Ikonomi², Angelika M R Kestler³

¹Institute of Medical Systems Biology, Ulm University, Ulm 89081, Germany; Department of Pathology, Ulm University Hospital, Ulm 89081, Germany; Zentrum Personalisierte Medizin, Ulm University Hospital, Ulm 89081, Germany.

Computer Methods and Programs in Biomedicine

|July 13, 2023

Summary

This summary is machine-generated.

Molecular tumor boards (MTBs) can now streamline cancer therapy decisions with AMBAR, an interactive web application. AMBAR facilitates efficient analysis and documentation of patient data, improving personalized treatment planning.

Keywords:

Interactive application MTBs Personalized medicine

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Area of Science:

Oncology
Bioinformatics
Medical Informatics

Background:

Personalized cancer therapy relies on molecular profiling and expert knowledge.
Molecular tumor boards (MTBs) integrate diverse expertise for therapeutic decisions.
Current MTB data analysis is time-consuming and lacks adequate tools.

Purpose of the Study:

To develop an interactive web application, AMBAR (Alteration annotations for Molecular tumor BoARds), to support therapeutic decision-making in MTBs.

Main Methods:

Developed AMBAR as an R shiny-based interactive web application.
Incorporated features for customization, interactive filtering, and data visualization.
Enabled annotation of mutations and export to clinical systems.

Main Results:

AMBAR provides a user-friendly interface for managing and analyzing patient molecular data.
The application facilitates the integration of expert knowledge into the decision-making process.
AMBAR supports efficient documentation and export of annotated mutations for clinical use.

Conclusions:

AMBAR addresses the limitations of current MTB data management, enhancing efficiency and accuracy.
The tool supports personalized cancer therapy by improving the integration of molecular data and expert knowledge.
AMBAR is an open-source, dockerized application available for broader adoption in clinical settings.