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Airhart, S. D.

Publications and source records attributed to Airhart, S. D..

2 recordsLinked to original sources

A Genomically and Clinically Annotated Patient Derived Xenograft (PDX) Resource for Preclinical Research in Non-Small Cell Lung Cancer

Patient-derived xenograft models (PDXs) are an effective preclinical in vivo platform for testing the efficacy of novel drug and drug combinations for cancer therapeutics. Here we describe a repository of 79 genomically and clinically annotated lung cancer PDXs available from The Jackson Laboratory that have been extensively characterized for histopathological features, mutational profiles, gene expression, and copy number aberrations. Most of the PDXs are models of non-small cell lung cancer (NSCLC), including 37 lung adenocarcinoma (LUAD) and 33 lung squamous cell carcinoma (LUSC) models. Other lung cancer models in the repository include four small cell carcinomas, two large cell neuroendocrine carcinomas, two adenosquamous carcinomas, and one pleomorphic carcinoma. Models with both de novo and acquired resistance to targeted therapies with tyrosine kinase inhibitors are available in the collection. The genomic profiles of the LUAD and LUSC PDX models are consistent with those observed in patient tumors of the same tumor type from The Cancer Genome Atlas (TCGA) and to previously characterized gene expression-based molecular subtypes. Clinically relevant mutations identified in the original patient tumors were confirmed in engrafted tumors. Treatment studies performed for a subset of the models recapitulated the responses expected based on the observed genomic profiles. SignificanceThe collection of lung cancer Patient Derived Xenograft (PDX) models maintained at The Jackson Laboratory retain both the histologic features and treatment-relevant genomic alterations observed in the originating patient tumors and show expected responses to treatment with standard-of-care agents. The models serve as a valuable preclinical platform for translational cancer research. Information and data for the models are freely available from the Mouse Models of Human Cancer database (MMHCdb, http://tumor.informatics.jax.org/mtbwi/pdxSearch.do).

cancer biology↗

Bioinformatics workflows for genomic analysis of tumors from Patient Derived Xenografts (PDX): challenges and guidelines

Bioinformatics workflows for analyzing genomic data obtained from xenografted tumor (e.g., human tumors engrafted in a mouse host) must address several challenges, including separating mouse and human sequence reads and accurate identification of somatic mutations and copy number aberrations when paired normal DNA from the patient is not available. We report here data analysis workflows that address these challenges and result in reliable identification of somatic mutations, copy number alterations, and transcriptomic profiles of tumors from patient derived xenograft models. We validated our analytical approaches using simulated data and by assessing concordance of the genomic properties of xenograft tumors with data from primary human tumors in The Cancer Genome Atlas (TCGA). The commands and parameters for the workflows are available at https://github.com/TheJacksonLaboratory/PDX-Analysis-Workflows.

bioinformatics↗