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PCIG: a web-based application to explore immune–genomics interactions across cancer types

MOTIVATION: Genomic alterations can modulate the tumor immunophenotype depending on their nature and tissue of origin. Although this immune–genomic interaction may shape disease progression and response to immunotherapy, the factors governing such dynamics and the influence of each tissue-specific c...

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Detalles Bibliográficos
Autores principales: Pedrola, Anna, Franch-Expósito, Sebastià, Lahoz, Sara, Esteban-Fabró, Roger, Dienstmann, Rodrigo, Bassaganyas, Laia, Camps, Jordi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9004641/
https://www.ncbi.nlm.nih.gov/pubmed/35179562
http://dx.doi.org/10.1093/bioinformatics/btac111
Descripción
Sumario:MOTIVATION: Genomic alterations can modulate the tumor immunophenotype depending on their nature and tissue of origin. Although this immune–genomic interaction may shape disease progression and response to immunotherapy, the factors governing such dynamics and the influence of each tissue-specific context remain poorly understood. RESULTS: Here, we have developed the PanCancer ImmunoGenomics (PCIG) tool, a web-based resource that provides researchers with the opportunity to mine immunome–genome relationships across several cancer types using data from the Pan-Cancer Analysis of Whole-Genomes (PCAWG) study, which comprises >2,600 samples spanning across 20 different cancer primary sites. PCIG yields an integrative analysis of the crosstalk between somatic genomic alterations and different immune features, thus helping to understand immune response-related processes. AVAILABILITY AND IMPLEMENTATION: PCIG is freely available at https://pcig.vhio.net and is supported by all major web browsers. PCIG was developed with Django, which is a Python-based free and open-source framework, and it uses SQL Server as a relational database management system. The code is freely available for download at GitHub https://github.com/AnnaPG/PCIG and in its online supplementary material. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.