Advancing Precision Oncology in Hereditary Paraganglioma-Pheochromocytoma Syndromes: Integrated Interpretation and Data Sharing of the Germline and Tumor Genomes

Standard methods of variant assessment in hereditary cancer susceptibility genes are limited by the lack of availability of key supporting evidence. In cancer, information derived from tumors can serve as a useful source in delineating the tumor behavior and the role of germline variants in tumor progression. We have previously demonstrated the value of integrating tumor and germline findings to comprehensively assess germline variants in hereditary cancer syndromes. Building on this work, herein, we present the development and application of the INT2GRATE|HPPGL platform. INT2GRATE (INTegrated INTerpretation of GeRmline And Tumor gEnomes) is a multi-institution oncology consortium that aims to advance the integrated application of constitutional and tumor data and share the integrated variant information in publicly accessible repositories. The INT2GRATE|HPPGL platform enables automated parsing and integrated assessment of germline, tumor, and genetic findings in hereditary paraganglioma-pheochromocytoma syndromes (HPPGLs). Using INT2GRATE|HPPGL, we analyzed 8600 variants in succinate dehydrogenase (SDHx) genes and their associated clinical evidence. The integrated evidence includes germline variants in SDHx genes; clinical genetics evidence: personal and family history of HPPGL-related tumors; tumor-derived evidence: somatic inactivation of SDHx alleles, KIT and PDGFRA status in gastrointestinal stromal tumors (GISTs), multifocal or extra-adrenal tumors, and metastasis status; and immunohistochemistry staining status for SDHA and SDHB genes. After processing, 8600 variants were submitted programmatically from the INT2GRATE|HPPGL platform to ClinVar via a custom-made INT2GRATE|HPPGL variant submission schema and an application programming interface (API). This novel integrated variant assessment and data sharing in hereditary cancers aims to improve the clinical assessment of genomic variants and advance precision oncology.

Abstract 562: Oncovirus detection and integration analysis from human tumor samples using targeted massively parallel sequencing

Viruses are a major contributor to oncogenesis, causing 10-15% of human cancers. Molecular pathways involved in malignant transformation are frequently activated by genetic alterations, including but not limited to, somatic mutations, copy number aberrations, structural variants, and oncoviruses. Precision cancer medicine aims to classify tumors by site, histology, and molecular tests to determine an “individualized” profile of cancer alterations. However, clinical tests for these various alterations are sequential, time consuming, and use a lot of material, which is often quite limited (e.g., biopsies). Moreover, tests for the presence of viral sequence are generally performed separately to tests (such as massively parallel sequencing) to detect human genomic alterations. Here we present a hybrid capture and massively parallel sequencing approach to detect viral infection concurrently with targeted genomic analysis, which may decrease assay costs, increase sensitivity and scalability, and detect many types of alterations, thereby providing a more complete tumor genetic profile all from a single sample.

We have created a custom hybrid capture probeset for targeted Illumina sequencing to determine whether oncoviruses are present in tissue samples and also determine if the virus has integrated into the host’s genome. We have created both ‘detection’ and ‘integration’ baits for several oncoviruses, including polyomaviruses, human papilloma viruses, Epstein-Barr virus, human cytomegalovirus, Kaposi sarcoma herpesvirus, human T-lymphotropic virus, and hepatitis B virus. To distinguish between different strains of a single virus, strain-specific detection baits were created to bind to variable regions of viral genomes. The integration bait was designed to bind to regions of the viral genomes that are commonly integrated into the human genome. This baitset can also be combined with other capture panels targeting oncogenes to simultaneously determine infection and integration statuses, as well as somatic mutations, copy number and structural variants.

To detect virus presence, reads were aligned to a hybrid reference of both the human, and targeted virus genomes. Viral integration status and integration loci were determined by leveraging discordant read pairs that aligned to both the human genome and a viral genome. We have tested our techniques on tissue samples that were infected with either Merkel Cell Polyomavirus or Epstein-Barr virus, as determined using quantitative polymerase chain reaction (qPCR) or immunohistochemistry (IHC) techniques, and have successfully detected these viruses and identified viral integration loci. Overall, this viral hybrid capture probeset provides the ability to simultaneously determine a tissue sample’s infection and viral integration status alongside other somatic genomic analyses, saving both time and sample material.

Citation Format: Robert T. Burns, Samuel S. Hunter, Matthew D. Ducar, Aaron R. Thorner, James A. Decaprio, Paul Van Hummelen, Alexander Frieden, Anwesha Nag, Haley A. Coleman, Michael K. Slevin, Andrea Clapp, Samantha D. Drinan, Suzanne R. McShane, Edwin Thai, Priyanka Shivdasani, Joshua Bohannon, Johann Hoeftberger, Reuben Jacobs, Bruce M. Wollison, Neil A. Patel, Monica D. Manam, Phani Davineni, Matthew Meyerson, Laura E. MacConaill. Oncovirus detection and integration analysis from human tumor samples using targeted massively parallel sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 562. doi:10.1158/1538-7445.AM2017-562

Abstract 3644: Optimization of library construction for massively parallel sequencing using low-input, FFPE-derived DNA without additional PCR amplification

Massively parallel sequencing (MPS) is increasingly used in the laboratory and clinic to identify genomic factors contributing to tumorigenesis, such as somatic mutations, DNA insertions and deletions, transcriptome and epigenetic changes, and chromosomal abnormalities. Because tumor specimens are often quite limited or are from rare and precious samples, it is necessary to prepare sequencing libraries from minimal amounts of DNA. Indeed, it can be challenging to extract sufficient amounts of starting material from fresh-frozen paraffin embedded (FFPE) samples for library construction, and frequently samples are not processed because they do not reach minimum requirements. Therefore, it is of great importance to improve currently available protocols to process low yield FFPE-derived DNA for MPS. This will allow for the inclusion of more tumor samples to be sequenced per cohort, resulting in increased ability to identify genomic factors involved in tumorigenesis.

Here, we optimized the KAPA Library Preparation Kit (Kapa Biosystems, Wilmington, MA) to successfully perform library construction from low-yield FFPE and fresh frozen samples. The kit normally requires an input of at least 100 ng of DNA. However, we were able to modify the protocol to prepare libraries from as little as 10 ng of starting material by optimizing the ratio of adapter:input DNA and SPRI-clean-up, performing low-volume reactions, and using IDT universal blockers during hybrid capture. Additional library enrichment PCR was not required. Library yields were sufficient for downstream hybrid capture and sequencing, and sequencing metrics were comparable to samples that were prepped using the manufacturer's recommendations. Experiments are underway to demonstrate that library complexity remains unchanged.

Citation Format: Aaron R. Thorner, Liuda Ziaugra, Matthew D. Ducar, Ling Lin, Angelica Laing, Haley A. Coleman, Suzanne R. McShane, Andrea Clapp, Rachel R. Paquette, Bruce M. Wollison, Johann Hoeftberger, Neil A. Patel, Samuel S. Hunter, Monica D. Manam, Laura E. MacConaill, William C. Hahn, Matthew L. Meyerson, Paul van Hummelen. Optimization of library construction for massively parallel sequencing using low-input, FFPE-derived DNA without additional PCR amplification. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3644.