Abstract 3385: Comparison of genomic biomarkers identified by the whole exome, RNASeq and whole genome sequencing pipelines developed for the PDMR
Authors: Chen Li , Patidar Rajesh , Das Biswajit , Karlovich Chris , Vilimas Tomas , Camalier Corinne , Datta Vivekananda , Jiwani Shahanawaz , Walsh William , Fliss Palmer , McDermott Sean , McCutcheon Justine N. , Peach Amanda , Ahalt-Gottholm Michelle , Bonomi Carrie , Dougherty Kelly , Carter John , Alcoser Sergio Y. , Chase Tiffanie , Divelbiss1 Raymond , Gibson Marion , Hedger Kelly , Mallow Candace , McGlynn Chelsea , Morris Malorie , Radzyminski Marianne , Stotler Howard , Stottlemyer Jesse , Trail Debbie , Evrard Yvonne , Hollingshead Melinda G. , Williams Mickey , Doroshow James H. 
Published: August 2019

Background: The National Cancer Institute (NCI) has developed a Patient-Derived Models Repository (PDMR; www.pdmr.cancer.gov) of patient-derived xenografts (PDXs) with clinical annotation and comprehensive genomic characterization using whole exome sequencing (WES) and RNASeq. An in-house data analysis pipeline has been developed and validated to call germline and somatic variants and to perform transcriptional profiling in these models. There is a need to incorporate additional biomarkers into standard data analysis pipeline, including loss of heterozygosity (LOH), microsatellite instability (MSI), structure variants (SVs)/fusions and copy number variation (CNV) for identifying appropriate PDX models for preclinical drug studies. Validation of the methods used for the assessment of these and other genomic biomarkers is a crucial aspect in the development of the PDMR data analysis pipeline.

Methods: WGS, WES and RNASeq were conducted on 58 PDX samples and genomic biomarkers were derived from different assays. For LOH calling, a set of ~800,000 heterozygous SNPs was first constructed from a population level genomic database (gnomAD) and a specific list of ~3000 highly heterozygous SNPs from a previous study. LOH regions were detected using Runs of Homozygosity (BCFtools/RoH) based on the genotypes of ~800,000 SNPs. Finally, percent of genomic LOH was calculated as the percent of eligible LOH regions in the whole genome. For MSI calling. mSINGS was used to assign a microsatellite instability score based on the fraction of unstable microsatellite loci. Gene fusions were detected using Tophat-fusion and Fusion-catcher from RNASeq data and Manta from WGS. CNVs were derived from WGS and WES using CNVkit.

Results: Genomic biomarkers derived from WES and RNASeq were highly concordant with the ones derived from WGS. Specifically, we found 1) the percent of genomic LOH was highly correlated between WGS and WES across 52 samples with R2=0.99, where LOH% ranged from &lt;1% to ~50% and specimens within the same models had consistent data; 2) a strong concordance rate (91%) of MSI score was observed between WGS and WES across 49 samples; 3) clinically and diagnostically relevant structural variants/fusions (e.g. FGFR3-TACC3 and EWSR1-FLI1) detected from RNASeq data can be detected and validated from WGS data; and 4) CNV genomic profiles were highly correlated between WGS and WES and amplifications/deletions in clinically relevant genes were consistently detected by the two assays.

Conclusions: We observed excellent consistency between WGS, WES and RNASeq data in the assessment of percent of LOH, MSI score, SVs/fusions and CNVs. Our data analysis pipeline can accurately call genomic biomarkers from WES and RNASeq data, which facilitates the molecular characterization and prioritization of PDMR models for preclinical drug treatment.

Citation Format: Li Chen, Rajesh Patidar, Biswajit Das, Chris Karlovich, Tomas Vilimas, Corinne Camalier, Vivekananda Datta, Shahanawaz Jiwani, William Walsh, Palmer Fliss, Sean McDermott, Justine N. McCutcheon, Amanda Peach, Michelle Ahalt-Gottholm, Carrie Bonomi, Kelly Dougherty, John Carter, Sergio Y. Alcoser, Tiffanie Chase, Raymond Divelbiss1, Marion Gibson, Kelly Hedger, Candace Mallow, Chelsea McGlynn, Malorie Morris, Marianne Radzyminski, Howard Stotler, Jesse Stottlemyer, Debbie Trail, Yvonne Evrard, Melinda G. Hollingshead, Mickey Williams, James H. Doroshow. Comparison of genomic biomarkers identified by the whole exome, RNASeq and whole genome sequencing pipelines developed for the PDMR [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3385.