Related Experiment Video
Updated: Jul 4, 2025
Depletion of Mouse Cells from Human Tumor Xenografts Significantly Improves Downstream Analysis of Target Cells
Published on: July 29, 2016
An analysis pipeline for understanding 6-thioguanine effects on a mouse tumour genome
Patricio Yankilevich1, Loulieta Nazerai2,3, Shona Caroline Willis2,3
1Bioinformatics Core Facility, Instituto de Investigación en Biomedicina de Buenos Aires (IBioBA) - CONICET - Partner Institute of the Max Planck Society, Buenos Aires, Argentina. pyankilevich@ibioba-mpsp-conicet.gov.ar.
Abstract:
Mouse tumour models are extensively used as a pre-clinical research tool in the field of oncology, playing an important role in anticancer drugs discovery. Accordingly, in cancer genomics research, the demand for next-generation sequencing (NGS) is increasing, and consequently, the need for data analysis pipelines is likewise growing. Most NGS data analysis solutions to date do not support mouse data or require highly specific configuration for their use. Here, we present a genome analysis pipeline for mouse tumour NGS data including the whole-genome sequence (WGS) data analysis flow for somatic variant discovery, and the RNA-seq data flow for differential expression, functional analysis and neoantigen prediction. The pipeline is based on standards and best practices and integrates mouse genome references and annotations. In a recent study, the pipeline was applied to demonstrate the efficacy of low dose 6-thioguanine (6TG) treatment on low-mutation melanoma in a pre-clinical mouse model. Here, we further this study and describe in detail the pipeline and the results obtained in terms of tumour mutational burden (TMB) and number of predicted neoantigens, and correlate these with 6TG effects on tumour volume. Our pipeline was expanded to include a neoantigen analysis, resulting in neopeptide prediction and MHC class I antigen presentation evaluation. We observed that the number of predicted neoepitopes were more accurate indicators of tumour immune control than TMB. In conclusion, this study demonstrates the usability of the proposed pipeline, and suggests it could be an essential robust genome analysis platform for future mouse genomic analysis.
Insights
A new genome analysis pipeline efficiently processes mouse tumor next-generation sequencing data. This tool accurately predicts neoantigens, outperforming tumor mutational burden for assessing immune control in cancer research.
Area of Science:
- Oncology
- Bioinformatics
- Genomics
Background:
- Mouse tumor models are crucial for preclinical oncology research and anticancer drug discovery.
- Next-generation sequencing (NGS) demand is rising in cancer genomics, increasing the need for specialized data analysis pipelines.
- Existing NGS analysis tools often lack support for mouse data or require complex configurations.
Purpose of the Study:
- To present a comprehensive genome analysis pipeline tailored for mouse tumor NGS data.
- To enable whole-genome sequence (WGS) analysis for somatic variants and RNA-seq analysis for differential expression, functional analysis, and neoantigen prediction.
- To validate the pipeline's utility in a preclinical mouse model treated with 6-thioguanine (6TG).
Main Methods:
- Development of a genome analysis pipeline integrating mouse genome references and annotations.
- Application of the pipeline for whole-genome sequence (WGS) data analysis to discover somatic variants.
- Utilization of RNA-seq data analysis for differential expression, functional analysis, and neoantigen prediction, including MHC class I antigen presentation evaluation.
Main Results:
- The pipeline successfully analyzed mouse tumor NGS data, including WGS and RNA-seq.
- Tumor mutational burden (TMB) and predicted neoantigens were correlated with 6TG treatment effects on tumor volume.
- Predicted neoepitopes proved to be more accurate indicators of tumor immune control than TMB.
Conclusions:
- The developed pipeline is a usable and robust platform for mouse genomic analysis.
- The pipeline facilitates detailed analysis of tumor mutational burden and neoantigen prediction.
- Neoantigen prediction offers superior insights into tumor immune control compared to TMB in preclinical models.
More Related Videos
09:33Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens
Published on: August 25, 2023
10:27Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
Published on: July 25, 2020
