Developing a disease-specific annotation protocol for VHL gene curation using Hypothes.is

Von Hippel-Lindau (VHL) disease is a rare, autosomal dominant disorder that predisposes individuals to developing tumors in many organs. There is significant phenotypic variability and genetic variants encountered within this syndrome, posing a considerable challenge to patient care. The lack of VHL variant data sharing paired with the absence of aggregated genotype-phenotype information results in an arduous process, when characterizing genetic variants and predicting patient prognosis. To address these gaps in knowledge, the Clinical Genome Resource (ClinGen) VHL Variant Curation Expert Panel (VCEP) has been resolving a list of variants of uncertain significance within the VHL gene. Through community curation, we crowdsourced the laborious task of variant annotation by modifying the ClinGen Community Curation (C3)-developed Baseline Annotation protocol and annotating all published VHL cases with the reported genotype-phenotype information in Hypothes.is, an open-access web annotation tool. This process, incorporated into the ClinGen VCEP's workflow, will aid in their curation efforts. To facilitate the curation at all levels of genetics expertise, our team developed a 4-day biocuration training protocol and resource guide. To date, 91.3% of annotations have been completed by undergraduate and high-school students without formal academic genetics specialization. Here, we present our VHL-specific annotation protocol utilizing Hypothes.is, which offers a standardized method to present case-resolution data, and our biocuration training protocol, which can be adapted for other rare disease platforms. By facilitating training for community curation of VHL disease, we increased student engagement with clinical genetics while enhancing knowledge translation in the field of hereditary cancer. Database URL: https://hypothes.is/groups/dKymJJpZ/vhl-hypothesis-annotation.

Abstract 1192: The Clinical Genome Resource (ClinGen) somatic cancer clinical domain working group

Interpretation of the clinical significance of somatic gene variants in cancer remains a major challenge in cancer diagnosis, prognosis and treatment response prediction. We will report on progress and plans of the Clinical Genome Resource (ClinGen) Somatic Cancer Clinical Domain Working Group (CDWG). The CDWG membership consists of over 150 multi-disciplinary experts in cancer biology, oncology, pathology, genetics, genomics and informatics. The mission of the ClinGen Somatic Cancer CDWG is to facilitate the development of data curation guidelines and standards to determine the clinical significance of somatic alterations in cancer, thereby enhancing the usability, dissemination and implementation of cancer somatic changes in the ClinGen resource and other knowledgebases including CIViC, ClinVar, and the Variant Interpretation for Cancer Consortium (VICC) MetaKB. Our goal is to create high-quality assertions of the clinical significance of specific somatic variants in cancer by leveraging the CIViC curation interface, adapting the germline procedures of ClinGen to somatic variant interpretation, and implementing the interoperability standards of the Global Alliance for Genomics and Health (GA4GH). The ClinGen Somatic effort is overseen by the Somatic CDWG and reports progress to the overall ClinGen consortium. There are Somatic Cancer subdomains focused on particular clinically important domains of cancer variant interpretation including three Task Forces (covering Pediatric Cancer, Hematologic Cancer, and Solid Tumors) and a growing number of Somatic Cancer Variant Curation Expert Panels (SC-VCEPs). To improve quality and consistency of clinical interpretations, each candidate somatic cancer VCEP must complete a four step approval process adapted from ClinGen’s work in Germline disease domains. The Somatic CDWG works to ensure that each group is aware of available training materials and detailed standard operating procedures. Each SC-VCEP also coordinates with the ClinGen Cancer Variant Interpretation Committee (CVI) whose goal is to support development of granular specifications for the AMP/ASCO/CAP guidelines for somatic variant interpretation. New SC-VCEPs are anticipated to focus on specific clinically relevant genes, pathways, disease entities, variant classes or treatment modalities. Currently, three SC-VCEPs have begun to work through the four step process (focused on FGFR mutations, NTRK fusions, and FLT3 mutations respectively), and two more SC-VCEPs are in the planning stage (Histone H3 and Ph-like ALL). To date, ClinGen Somatic groups have contributed 619 evidence lines into CIViC from 353 published papers and 21 assertions of clinical significance. Input from the AACR community is critical for the establishment of new SC-VCEPs that address areas of variant interpretation with the greatest need.

Citation Format: Jason Saliba, Gordana Raca, Angshumoy Roy, Ian King, Shamini Selvarajah, Xinjie Xu, Rashmi Kanagal-Shamanna, Laveniya Satgunaseelan, David Meredith, Mark Evans, Alanna Church, Panieh Terraf, Yassmine Akkari, Heather E. Williams, Wan-Hsin Lin, Chimene Kesserwan, Deborah I. Ritter, Kilannin Krysiak, Arpad Danos, Alex Wagner, Marilyn M. Li, Dmitriy Sonkin, Jonathan S. Berg, Sharon E. Plon, Heidi L. Rehm, Shashikant Kulkarni, Ramaswamy Govindan, Obi L. Griffith, Malachi Griffith, on behalf of the ClinGen Somatic CDWG. The Clinical Genome Resource (ClinGen) somatic cancer clinical domain working group [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1192.

Evolution of germline TP53 variant classification in children with cancer

Li-Fraumeni syndrome, caused by germline pathogenic variants in TP53, results in susceptibility to multiple cancers. Variants of uncertain significance (VUS) and reclassification of variants over time pose management concerns given improved survival with cancer surveillance for LFS patients. We describe the experience of TP53 variant reclassification at a pediatric cancer center.

METHODS

We reviewed medical records (2010-2019) of 756 patients seen in Texas Children's Cancer Genetics Clinic. We noted initial TP53 classification and any reclassifications. We then classified TP53 variants following ClinGen TP53 variant curation expert panel recommendations using data from ClinVar, medical literature and IARC database.

RESULTS

Of 234 patients tested for TP53, 27 (11.5%) reports contained pathogenic/likely pathogenic (P/LP) variants and 7 (3)% contained VUS. By January 2022, 4 of 6 unique VUS and 2 of 16 unique P/LP variants changed interpretations in ClinVar. Reinterpretation of these 4 VUS in ClinVar matched clinical decision at the time of initial report. Applying TP53 VCEP specifications classified 3 VUS to P/LP/benign, and one pathogenic variant to likely benign.

CONCLUSIONS

Planned review of variant significance is essential, especially for patients with high probability of LFS.

Standards for the classification of pathogenicity of somatic variants in cancer (oncogenicity): Joint recommendations of Clinical Genome Resource (ClinGen), Cancer Genomics Consortium (CGC), and Variant Interpretation for Cancer Consortium (VICC)

PURPOSE

Several professional societies have published guidelines for the clinical interpretation of somatic variants, which specifically address diagnostic, prognostic, and therapeutic implications. Although these guidelines for the clinical interpretation of variants include data types that may be used to determine the oncogenicity of a variant (eg, population frequency, functional, and in silico data or somatic frequency), they do not provide a direct, systematic, and comprehensive set of standards and rules to classify the oncogenicity of a somatic variant. This insufficient guidance leads to inconsistent classification of rare somatic variants in cancer, generates variability in their clinical interpretation, and, importantly, affects patient care. Therefore, it is essential to address this unmet need.

METHODS

Clinical Genome Resource (ClinGen) Somatic Cancer Clinical Domain Working Group and ClinGen Germline/Somatic Variant Subcommittee, the Cancer Genomics Consortium, and the Variant Interpretation for Cancer Consortium used a consensus approach to develop a standard operating procedure (SOP) for the classification of oncogenicity of somatic variants.

RESULTS

This comprehensive SOP has been developed to improve consistency in somatic variant classification and has been validated on 94 somatic variants in 10 common cancer-related genes.

CONCLUSION

The comprehensive SOP is now available for classification of oncogenicity of somatic variants.

A community approach to the cancer-variant-interpretation bottleneck

As guidelines, therapies, and literature on cancer variants expand, the lack of consensus variant interpretations impedes clinical applications. CIViC is a public domain, crowd-sourced, and adaptable knowledgebase of evidence for the Clinical Interpretation of Variants in Cancer, designed to reduce barriers to knowledge sharing and alleviate the variant interpretation bottleneck.

ClinGen Variant Curation Interface: a variant classification platform for the application of evidence criteria from ACMG/AMP guidelines

BACKGROUND

Identification of clinically significant genetic alterations involved in human disease has been dramatically accelerated by developments in next-generation sequencing technologies. However, the infrastructure and accessible comprehensive curation tools necessary for analyzing an individual patient genome and interpreting genetic variants to inform healthcare management have been lacking.

RESULTS

Here we present the ClinGen Variant Curation Interface (VCI), a global open-source variant classification platform for supporting the application of evidence criteria and classification of variants based on the ACMG/AMP variant classification guidelines. The VCI is among a suite of tools developed by the NIH-funded Clinical Genome Resource (ClinGen) Consortium and supports an FDA-recognized human variant curation process. Essential to this is the ability to enable collaboration and peer review across ClinGen Expert Panels supporting users in comprehensively identifying, annotating, and sharing relevant evidence while making variant pathogenicity assertions. To facilitate evidence-based improvements in human variant classification, the VCI is publicly available to the genomics community. Navigation workflows support users providing guidance to comprehensively apply the ACMG/AMP evidence criteria and document provenance for asserting variant classifications.

CONCLUSIONS

The VCI offers a central platform for clinical variant classification that fills a gap in the learning healthcare system, facilitates widespread adoption of standards for clinical curation, and is available at https://curation.clinicalgenome.org.

Abstract 449: A standard operating procedure for the curation of gene fusions

Despite the well-established role of recurrent gene fusions as oncogenic drivers, current practices for characterizing and interpreting gene fusion events in clinical testing and in biomedical literature are inconsistent. From the conceptual definition of gene fusions to the salient elements that characterize these alterations, a lack of community-driven standards for the curation of gene fusions has resulted in a disparate landscape of fusion representations and supporting tools. Consequently, the evidence-based clinical evaluation of gene fusions requires extensive expert review for accurate interpretation of observed gene fusions with respect to putative evidence from biomedical literature. Furthermore, the lack of these standards inhibits the interoperability of tools, resources, and pipelines - impeding data sharing and downstream utility.To address these challenges, a cross-consortia initiative between the Variant Interpretation for Cancer Consortium and ClinGen was formed to develop a standard operating procedure (SOP) for the curation of gene fusions. The SOP is under development by an international and diverse set of experts in the representation, detection, and clinical interpretation of gene fusions. Participating stakeholders across academic, government, and industry sectors showcased challenges and solutions, and participated in community surveys and discussions to define and develop the SOP for this diverse class of alterations.An initial result of this effort was the precise molecular definition of genomic events and features constituting gene fusions. We distinguish these from similar but distinct classes of structural alterations through clinically-relevant examples. Next, we discuss our findings on community practices around the description and evaluation of gene fusions. We provide our recommendations for characterization and representation of gene fusions from these practices, and compare these recommendations to existing variant representation standards and formats (e.g. HGVS variant nomenclature). We also discuss the concurrent application of formats for standardized human- and machine-readable representations of gene fusion events.We conclude with discussion of the salient elements to enable rapid, scalable, and consistent evaluation of fusions curated from the biomedical literature. Recommendations are provided for the standardized capture of these elements to enable both intuitive and precise characterization of this diverse class of alterations in clinical reporting and literature. In summary, we provide a clinical-practice driven framework and nomenclature for gene fusions, including recommendations for human readability, computational precision, and data integrity within the SOP. This work is a substantial advancement towards standardized communication, investigation, and sharing of gene fusion data across clinical and research domains and specialties.

Citation Format: Alex H. Wagner, Ioannis S. Vlachos, Dmitriy Sonkin, Panieh Terraf, Chimene Kesserwan, Andrea Sboner, Thomas Coard, Christian Reich, Deborah I. Ritter, Peter Horak, Ying S. Zou, Anna Tanska, Aaron M. Berlin, Anna Lu, Daniel Cameron, Heather E. Williams, Wan-Hsin Lin, Gokce Toruner, Arpad Danos, Jason Saliba, Huiling Xu, Xinjie Xu, Georgina Ryland, Michele Ceccarelli, Liying Zhang, Sarah Rapisardo, Catherine Rehder, Xuelu Liu, Aparna Pallavajjala, Nicole Park, Laveniya Satgunaseelan, Kristy Lee, Jie Liu, Obi Griffith, Robert R. Freimuth, Albrecht Stenzinger, Linda B. Baughn, Michael Baudis, Jennifer Lee, Marilyn Li, Angshumoy Roy, Gordana Raca. A standard operating procedure for the curation of gene fusions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 449.

Abstract 3211: Evolution of the CIViC knowledgebase for community driven curation of clinical variants in cancer

With increasing adoption of next generation sequencing into clinical practice, the problem of clinical interpretation of tumor variants arises as a bottleneck for patient care, as effective annotation of these variants draws from a constantly increasing body of largely unstructured clinical and preclinical results. One model to sustain clinical variant curation is to house variant annotation behind a paywall, using access fees to fund further curation effort. An alternate approach is to leverage public curation and expert moderation to create a free public resource to house and distribute this knowledge. The Clinical Interpretation of Variants in Cancer (CIViC, www.civicdb.org) knowledgebase employs the latter approach, and is a free and open-access public resource with an intuitive user interface and flexible public API for programmatic access to all content, which is available to the public with no restrictions on usage. All data is available for retrieval without login, while registration with a free account is required to contribute curation. The provenance of all curation and revision in CIViC is viewable through the web interface, and curators may also leave public comments on all content. Selected expert editors review and revise submitted content, which is clearly labeled as accepted once it has fully undergone moderation. All content in CIViC adheres to a structured data model which follows a published standard operating procedure for curation. This data model incorporates ontologies, standards and guidelines from across the field to promote interoperability and compatibility with other efforts. The CIViC interface also allows curators and organizations to track and display summary statistics of all their activity. CIViC currently has a community of over 190 curators and 16,000 clinical and research users around the world.

CIViC continually develops and improves both new and existing features in response to user feedback as well as collaborative and internal development goals. Recently, the drugs and treatment terms used in predictive/therapeutic annotation have been normalized to the NCI Thesaurus. A conflict of interest (COI) statement is now required for all CIViC Editors, and functionality for writing and displaying the COI has been built into the interface. CIViC employs Predictive (Therapeutic), Prognostic, Diagnostic, Predisposing evidence types, and we highlight the recently introduced Functional evidence type, which has seen continued development. We will present the rationale for these changes including demonstrating how adding a Dominant Negative term better supports curation of functional genomics data sets. A focus of functional curation has been TP53, with over 50 evidence items to date. With multiple use cases for this type of data including targeted therapeutics, identification of relevant hotspots, or characterization of cancer driver mechanisms, functional evidence can be used to support conventional concepts of clinical utility and expand the CIViC data model. These developments provide a mechanism for discussion and integration of functional data into somatic variant interpretation guidelines, an area being explored but lacking expert consensus.

Citation Format: Arpad Danos, Kilannin Krysiak, Erica K. Barnell, Adam C. Coffman, Joshua F. McMichael, Susanna Kiwala, Nicholas C. Spies, Lana M. Sheta, Shahil P. Pema, Lynzey Kujan, Kaitlin A. Clark, Sydney Anderson, Amber Wollam, Brian Li, Justin Guerra, Shruti Rao, Deborah I. Ritter, Cameron J. Grisdale, Gordana Raca, Alex H. Wagner, Subha Madhavan, Malachi Griffith, Obi L. Griffith. Evolution of the CIViC knowledgebase for community driven curation of clinical variants in cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3211.

Clinical Genetics Lacks Standard Definitions and Protocols for the Collection and Use of Diversity Measures

Genetics researchers and clinical professionals rely on diversity measures such as race, ethnicity, and ancestry (REA) to stratify study participants and patients for a variety of applications in research and precision medicine. However, there are no comprehensive, widely accepted standards or guidelines for collecting and using such data in clinical genetics practice. Two NIH-funded research consortia, the Clinical Genome Resource (ClinGen) and Clinical Sequencing Evidence-generating Research (CSER), have partnered to address this issue and report how REA are currently collected, conceptualized, and used. Surveying clinical genetics professionals and researchers (n = 448), we found heterogeneity in the way REA are perceived, defined, and measured, with variation in the perceived importance of REA in both clinical and research settings. The majority of respondents (>55%) felt that REA are at least somewhat important for clinical variant interpretation, ordering genetic tests, and communicating results to patients. However, there was no consensus on the relevance of REA, including how each of these measures should be used in different scenarios and what information they can convey in the context of human genetics. A lack of common definitions and applications of REA across the precision medicine pipeline may contribute to inconsistencies in data collection, missing or inaccurate classifications, and misleading or inconclusive results. Thus, our findings support the need for standardization and harmonization of REA data collection and use in clinical genetics and precision health research.

A harmonized meta-knowledgebase of clinical interpretations of somatic genomic variants in cancer

Precision oncology relies on accurate discovery and interpretation of genomic variants, enabling individualized diagnosis, prognosis and therapy selection. We found that six prominent somatic cancer variant knowledgebases were highly disparate in content, structure and supporting primary literature, impeding consensus when evaluating variants and their relevance in a clinical setting. We developed a framework for harmonizing variant interpretations to produce a meta-knowledgebase of 12,856 aggregate interpretations. We demonstrated large gains in overlap between resources across variants, diseases and drugs as a result of this harmonization. We subsequently demonstrated improved matching between a patient cohort and harmonized interpretations of potential clinical significance, observing an increase from an average of 33% per individual knowledgebase to 57% in aggregate. Our analyses illuminate the need for open, interoperable sharing of variant interpretation data. We also provide a freely available web interface (search.cancervariants.org) for exploring the harmonized interpretations from these six knowledgebases.

Standard operating procedure for curation and clinical interpretation of variants in cancer

Manually curated variant knowledgebases and their associated knowledge models are serving an increasingly important role in distributing and interpreting variants in cancer. These knowledgebases vary in their level of public accessibility, and the complexity of the models used to capture clinical knowledge. CIViC (Clinical Interpretation of Variants in Cancer - www.civicdb.org) is a fully open, free-to-use cancer variant interpretation knowledgebase that incorporates highly detailed curation of evidence obtained from peer-reviewed publications and meeting abstracts, and currently holds over 6300 Evidence Items for over 2300 variants derived from over 400 genes. CIViC has seen increased adoption by, and also undertaken collaboration with, a wide range of users and organizations involved in research. To enhance CIViC’s clinical value, regular submission to the ClinVar database and pursuit of other regulatory approvals is necessary. For this reason, a formal peer reviewed curation guideline and discussion of the underlying principles of curation is needed. We present here the CIViC knowledge model, standard operating procedures (SOP) for variant curation, and detailed examples to support community-driven curation of cancer variants.

A case for expert curation: an overview of cancer curation in the Clinical Genome Resource (ClinGen)

We describe the Clinical Genome Resource (ClinGen) cancer-related curation activities and the importance of curation to the evolving state of variant interpretation in a clinical context for both pediatric and adult cancer patients. We highlight specific examples from the CDH1 and PTEN Variant Curation Expert Panels (VCEPs) of the FDA-recognized process by which ClinGen VCEPs specify the American College of Medical Genetics and Genomics/Association of Molecular Pathology evidence code to develop variant classifications. We also review gene curations performed within the Hereditary Cancer Clinical Domain. We describe the parallel efforts for curation of somatic cancer variants from the Somatic Cancer Working Group. The ClinGen Germline/Somatic Committee is working to improve incorporation of both hereditary and somatic variant data to aid clinical interpretation. These ClinGen efforts rely on broad data sharing and detailed phenotypic and molecular information from published case studies to provide expert-curated variant interpretation to the cancer community.

The clinical imperative for inclusivity: Race, ethnicity, and ancestry (REA) in genomics

The Clinical Genome Resource (ClinGen) Ancestry and Diversity Working Group highlights the need to develop guidance on race, ethnicity, and ancestry (REA) data collection and use in clinical genomics. We present quantitative and qualitative evidence to characterize: (1) acquisition of REA data via clinical laboratory requisition forms, and (2) information disparity across populations in the Genome Aggregation Database (gnomAD) at clinically relevant sites ascertained from annotations in ClinVar. Our requisition form analysis showed substantial heterogeneity in clinical laboratory ascertainment of REA, as well as marked incongruity among terms used to define REA categories. There was also striking disparity across REA populations in the amount of information available about clinically relevant variants in gnomAD. European ancestral populations constituted the majority of observations (55.8%), allele counts (59.7%), and private alleles (56.1%) in gnomAD at 550 loci with "pathogenic" and "likely pathogenic" expert-reviewed variants in ClinVar. Our findings highlight the importance of implementing and supporting programs to increase diversity in genome sequencing and clinical genomics, as well as measuring uncertainty around population-level datasets that are used in variant interpretation. Finally, we suggest the need for a standardized REA data collection framework to be developed through partnerships and collaborations and adopted across clinical genomics.

Clinical validity assessment of genes frequently tested on hereditary breast and ovarian cancer susceptibility sequencing panels

PURPOSE

Several genes on hereditary breast and ovarian cancer susceptibility test panels have not been systematically examined for strength of association with disease. We employed the Clinical Genome Resource (ClinGen) clinical validity framework to assess the strength of evidence between selected genes and breast or ovarian cancer.

METHODS

Thirty-one genes offered on cancer panel testing were selected for evaluation. The strength of gene-disease relationship was systematically evaluated and a clinical validity classification of either Definitive, Strong, Moderate, Limited, Refuted, Disputed, or No Reported Evidence was assigned.

RESULTS

Definitive clinical validity classifications were made for 10/31 and 10/32 gene-disease pairs for breast and ovarian cancer respectively. Two genes had a Moderate classification whereas, 6/31 and 6/32 genes had Limited classifications for breast and ovarian cancer respectively. Contradictory evidence resulted in Disputed or Refuted assertions for 9/31 genes for breast and 4/32 genes for ovarian cancer. No Reported Evidence of disease association was asserted for 5/31 genes for breast and 11/32 for ovarian cancer.

CONCLUSION

Evaluation of gene-disease association using the ClinGen clinical validity framework revealed a wide range of classifications. This information should aid laboratories in tailoring appropriate gene panels and assist health-care providers in interpreting results from panel testing.

Pathogenic Germline Variants in 10,389 Adult Cancers

We conducted the largest investigation of predisposition variants in cancer to date, discovering 853 pathogenic or likely pathogenic variants in 8% of 10,389 cases from 33 cancer types. Twenty-one genes showed single or cross-cancer associations, including novel associations of SDHA in melanoma and PALB2 in stomach adenocarcinoma. The 659 predisposition variants and 18 additional large deletions in tumor suppressors, including ATM, BRCA1, and NF1, showed low gene expression and frequent (43%) loss of heterozygosity or biallelic two-hit events. We also discovered 33 such variants in oncogenes, including missenses in MET, RET, and PTPN11 associated with high gene expression. We nominated 47 additional predisposition variants from prioritized VUSs supported by multiple evidences involving case-control frequency, loss of heterozygosity, expression effect, and co-localization with mutations and modified residues. Our integrative approach links rare predisposition variants to functional consequences, informing future guidelines of variant classification and germline genetic testing in cancer.

Integrating somatic variant data and biomarkers for germline variant classification in cancer predisposition genes

In its landmark paper about Standards and Guidelines for the Interpretation of Sequence Variants, the American College of Medical Genetics and Genomics (ACMG), and Association for Molecular Pathology (AMP) did not address how to use tumor data when assessing the pathogenicity of germline variants. The Clinical Genome Resource (ClinGen) established a multidisciplinary working group, the Germline/Somatic Variant Subcommittee (GSVS) with this focus. The GSVS implemented a survey to determine current practices of integrating somatic data when classifying germline variants in cancer predisposition genes. The GSVS then reviewed and analyzed available resources of relevant somatic data, and performed integrative germline variant curation exercises. The committee determined that somatic hotspots could be systematically integrated into moderate evidence of pathogenicity (PM1). Tumor RNA sequencing data showing altered splicing may be considered as strong evidence in support of germline pathogenicity (PVS1) and tumor phenotypic features such as mutational signatures be considered supporting evidence of pathogenicity (PP4). However, at present, somatic data such as focal loss of heterozygosity and mutations occurring on the alternative allele are not recommended to be systematically integrated, instead, incorporation of this type of data should take place under the advisement of multidisciplinary cancer center tumor-normal sequencing boards.

Adapting crowdsourced clinical cancer curation in CIViC to the ClinGen minimum variant level data community-driven standards

Harmonization of cancer variant representation, efficient communication, and free distribution of clinical variant-associated knowledge are central problems that arise with increased usage of clinical next-generation sequencing. The Clinical Genome Resource (ClinGen) Somatic Working Group (WG) developed a minimal variant level data (MVLD) representation of cancer variants, and has an ongoing collaboration with Clinical Interpretations of Variants in Cancer (CIViC), an open-source platform supporting crowdsourced and expert-moderated cancer variant curation. Harmonization between MVLD and CIViC variant formats was assessed by formal field-by-field analysis. Adjustments to the CIViC format were made to harmonize with MVLD and support ClinGen Somatic WG curation activities, including four new features in CIViC: (1) introduction of an assertions feature for clinical variant assessment following the Association of Molecular Pathologists (AMP) guidelines, (2) group-level curation tracking for organizations, enabling member transparency, and curation effort summaries, (3) introduction of ClinGen Allele Registry IDs to CIViC, and (4) mapping of CIViC assertions into ClinVar submission with automated submissions. A generalizable workflow utilizing MVLD and new CIViC features is outlined for use by ClinGen Somatic WG task teams for curation and submission to ClinVar, and provides a model for promoting harmonization of cancer variant representation and efficient distribution of this information.

Somatic cancer variant curation and harmonization through consensus minimum variant level data

BACKGROUND

To truly achieve personalized medicine in oncology, it is critical to catalog and curate cancer sequence variants for their clinical relevance. The Somatic Working Group (WG) of the Clinical Genome Resource (ClinGen), in cooperation with ClinVar and multiple cancer variant curation stakeholders, has developed a consensus set of minimal variant level data (MVLD). MVLD is a framework of standardized data elements to curate cancer variants for clinical utility. With implementation of MVLD standards, and in a working partnership with ClinVar, we aim to streamline the somatic variant curation efforts in the community and reduce redundancy and time burden for the interpretation of cancer variants in clinical practice.

METHODS

We developed MVLD through a consensus approach by i) reviewing clinical actionability interpretations from institutions participating in the WG, ii) conducting extensive literature search of clinical somatic interpretation schemas, and iii) survey of cancer variant web portals. A forthcoming guideline on cancer variant interpretation, from the Association of Molecular Pathology (AMP), can be incorporated into MVLD.

RESULTS

Along with harmonizing standardized terminology for allele interpretive and descriptive fields that are collected by many databases, the MVLD includes unique fields for cancer variants such as Biomarker Class, Therapeutic Context and Effect. In addition, MVLD includes recommendations for controlled semantics and ontologies. The Somatic WG is collaborating with ClinVar to evaluate MVLD use for somatic variant submissions. ClinVar is an open and centralized repository where sequencing laboratories can report summary-level variant data with clinical significance, and ClinVar accepts cancer variant data.

CONCLUSIONS

We expect the use of the MVLD to streamline clinical interpretation of cancer variants, enhance interoperability among multiple redundant curation efforts, and increase submission of somatic variants to ClinVar, all of which will enhance translation to clinical oncology practice.

Destabilized SMC5/6 complex leads to chromosome breakage syndrome with severe lung disease

The structural maintenance of chromosomes (SMC) family of proteins supports mitotic proliferation, meiosis, and DNA repair to control genomic stability. Impairments in chromosome maintenance are linked to rare chromosome breakage disorders. Here, we have identified a chromosome breakage syndrome associated with severe lung disease in early childhood. Four children from two unrelated kindreds died of severe pulmonary disease during infancy following viral pneumonia with evidence of combined T and B cell immunodeficiency. Whole exome sequencing revealed biallelic missense mutations in the NSMCE3 (also known as NDNL2) gene, which encodes a subunit of the SMC5/6 complex that is essential for DNA damage response and chromosome segregation. The NSMCE3 mutations disrupted interactions within the SMC5/6 complex, leading to destabilization of the complex. Patient cells showed chromosome rearrangements, micronuclei, sensitivity to replication stress and DNA damage, and defective homologous recombination. This work associates missense mutations in NSMCE3 with an autosomal recessive chromosome breakage syndrome that leads to defective T and B cell function and acute respiratory distress syndrome in early childhood.

SV-STAT accurately detects structural variation via alignment to reference-based assemblies

Background

Genomic deletions, inversions, and other rearrangements known collectively as structural variations (SVs) are implicated in many human disorders. Technologies for sequencing DNA provide a potentially rich source of information in which to detect breakpoints of structural variations at base-pair resolution. However, accurate prediction of SVs remains challenging, and existing informatics tools predict rearrangements with significant rates of false positives or negatives.

Results

To address this challenge, we developed ‘Structural Variation detection by STAck and Tail’ (SV-STAT) which implements a novel scoring metric. The software uses this statistic to quantify evidence for structural variation in genomic regions suspected of harboring rearrangements. To demonstrate SV-STAT, we used targeted and genome-wide approaches. First, we applied a custom capture array followed by Roche/454 and SV-STAT to three pediatric B-lineage acute lymphoblastic leukemias, identifying five structural variations joining known and novel breakpoint regions. Next, we detected SVs genome-wide in paired-end Illumina data collected from additional tumor samples. SV-STAT showed predictive accuracy as high as or higher than leading alternatives. The software is freely available under the terms of the GNU General Public License version 3 at https://gitorious.org/svstat/svstat.

Conclusions

SV-STAT works across multiple sequencing chemistries, paired and single-end technologies, targeted or whole-genome strategies, and it complements existing SV-detection software. The method is a significant advance towards accurate detection and genotyping of genomic rearrangements from DNA sequencing data.

Electronic supplementary material

The online version of this article (doi:10.1186/s13029-016-0051-0) contains supplementary material, which is available to authorized users.

Pharmacogenetic characterization of naturally occurring germline NT5C1A variants to chemotherapeutic nucleoside analogs

BACKGROUND

Mutations or alterations in expression of the 5' nucleotidase gene family can lead to altered responses to treatment with nucleoside analogs. While investigating leukemia susceptibility genes, we discovered a very rare p.L254P NT5C1A missense variant in the substrate recognition motif. Given the paucity of cellular drug response data from the NT5C1A germline variation, we characterized p.L254P and eight rare variants of NT5C1A from genomic databases.

MATERIALS AND METHODS

Through lentiviral infection, we created HEK293 cell lines that stably overexpress wild-type NT5C1A, p.L254P, or eight NT5C1A variants reported in the National Heart Lung and Blood Institute Exome Variant Server (one truncating and seven missense). IC50 values were determined by cytotoxicity assays after exposure to chemotherapeutic nucleoside analogs (cladribine, gemcitabine, 5-fluorouracil). In addition, we used structure-based homology modeling to generate a three-dimensional model for the C-terminal region of NT5C1A.

RESULTS

The p.R180X (truncating), p.A214T, and p.L254P missense changes were the only variants that significantly impaired protein function across all nucleotide analogs tested (>5-fold difference vs. wild-type; P<0.05). Several of the remaining variants individually showed differential effects (both more and less resistant) across the analogs tested. The homology model provided a structural framework to understand the impact of NT5C1A mutants on catalysis and drug processing. The model predicted active site residues within NT5C1A motif III and we experimentally confirmed that p.K314 (not p.K320) is required for NT5C1A activity.

CONCLUSION

We characterized germline variation and predicted protein structures of NT5C1A. Individual missense changes showed considerable variation in response to the different nucleoside analogs tested, which may impact patients' responses to treatment.

Abstract 3301: Uncovering novel radiation sensitivity syndromes through exome sequencing

INTRODUCTION: The study of genetic disorders resulting in heightened sensitivity to ionizing radiation provides important molecular insights to DNA damage checkpoint and repair mechanisms. Individuals with these disorders have an increased risk of cancer and developmental abnormalities. We identified patients with unexplained radiation sensitivity disorders through the Texas Children's Cancer Center and Genetics Consult Service at Texas Children's Hospital. Children were screened for the known disorders prior to enrolling in a research study with whole exome sequencing. SUBJECTS: We identified three families with documented ionizing radiation sensitivity: (1) a sibling pair, one of whom had sternal osteomyelitis and a lung transplant (age 2) and a brother with eosinophilia and pneumonia (age 1); (2) a sibling pair, one child with astrocytoma (age 2) with severe leukoencephalopathy after radiation and a sister with medulloblastoma (age 2) and atypical encapsulated neuroma (age 13); and (3) a proband with leukemia and astrocytoma (age 2). All parents were unaffected. METHODS: We performed Illumina whole exome sequencing of probands and parents (when available), calling single nucleotide variants and insertions/deletions with ATLAS and PINDEL. We removed events &gt;1% in 1079 unaffected normal samples, &gt;1% dbSNP, or &gt; = 20 individuals in Exome Aggregation Consortium. We kept rare missense and truncating variants, and prioritized rare compound heterozygous, homozygous, or mutations shared by affected sibs. RESULTS: In the proband with sternal osteomyelitis and lung transplant, we identified and validated compound heterozygous missense mutations in NDNL2 (MAGEG1), a small, intronless gene. NDNL2 is involved in the SMC5-SMC6 complex, and suggested to play a role in DNA repair. The known functions of NDNL2 may explain the finding of the patient's cells displaying altered phosphorylation upon DNA damage for NBN (absent) and SMC1 (reduced). We are currently investigating the link between mutant NDNL2 and phosphorylation of NBN and SMC1. In kindred 2 (previously shown to transmit a SMARCB1 splice site mutation), the siblings share rare compound heterozygous missense mutations in ROBO1, and a nonsense mutation in MEGF6. In kindred 3, the proband with leukemia and astrocytoma was known to carry a large Xp deletion, but we identified no obvious candidate underlying radiation sensitivity. CONCLUSION: Careful study of rare kindreds with unexplained radiation sensitivity may provide new insights to the DNA damage response. Interestingly, two families also carried a known genetic condition (SMARCB1 mutation and Xp microdeletion) that may explain cancer phenotype but does not appear to underlie radiation sensitivity. The very rare biallelic missense mutations in NDNL2 implicate it as a candidate radiation sensitivity gene to be validated by further functional testing. Both siblings in this family had severe infections resulting in death in early childhood.

Citation Format: Deborah I. Ritter, Andrea K. Petersen, Katherine M. Haines, Ryan C. Zabriskie, David A. Wheeler, Sharon E. Plon. Uncovering novel radiation sensitivity syndromes through exome sequencing. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3301. doi:10.1158/1538-7445.AM2015-3301

Assessing structural variation in a personal genome-towards a human reference diploid genome

Background

Characterizing large genomic variants is essential to expanding the research and clinical applications of genome sequencing. While multiple data types and methods are available to detect these structural variants (SVs), they remain less characterized than smaller variants because of SV diversity, complexity, and size. These challenges are exacerbated by the experimental and computational demands of SV analysis. Here, we characterize the SV content of a personal genome with Parliament, a publicly available consensus SV-calling infrastructure that merges multiple data types and SV detection methods.

Results

We demonstrate Parliament’s efficacy via integrated analyses of data from whole-genome array comparative genomic hybridization, short-read next-generation sequencing, long-read (Pacific BioSciences RSII), long-insert (Illumina Nextera), and whole-genome architecture (BioNano Irys) data from the personal genome of a single subject (HS1011). From this genome, Parliament identified 31,007 genomic loci between 100 bp and 1 Mbp that are inconsistent with the hg19 reference assembly. Of these loci, 9,777 are supported as putative SVs by hybrid local assembly, long-read PacBio data, or multi-source heuristics. These SVs span 59 Mbp of the reference genome (1.8%) and include 3,801 events identified only with long-read data. The HS1011 data and complete Parliament infrastructure, including a BAM-to-SV workflow, are available on the cloud-based service DNAnexus.

Conclusions

HS1011 SV analysis reveals the limits and advantages of multiple sequencing technologies, specifically the impact of long-read SV discovery. With the full Parliament infrastructure, the HS1011 data constitute a public resource for novel SV discovery, software calibration, and personal genome structural variation analysis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1479-3) contains supplementary material, which is available to authorized users.

Identifying gene disruptions in novel balanced de novo constitutional translocations in childhood cancer patients by whole-genome sequencing

Purpose

We applied whole genome sequencing to children diagnosed with neoplasms and found to carry apparently balanced constitutional translocations, to discover novel genic disruptions.

Methods

We applied SV calling programs CREST, Break Dancer, SV-STAT and CGAP-CNV, and developed an annotative filtering strategy to achieve nucleotide resolution at the translocations.

Results

We identified the breakpoints for t(6;12) (p21.1;q24.31) disrupting HNF1A in a patient diagnosed with hepatic adenomas and Maturity Onset Diabetes of the Young (MODY). Translocation as the disruptive event of HNF1A, a gene known to be involved in MODY3, has not been previously reported. In a subject with Hodgkin’s lymphoma and subsequent low-grade glioma, we identified t(5;18) (q35.1;q21.2), disrupting both SLIT3 and DCC, genes previously implicated in both glioma and lymphoma.

Conclusions

These examples suggest that implementing clinical whole genome sequencing in the diagnostic work-up of patients with novel but apparently balanced translocations may reveal unanticipated disruption of disease-associated genes and aid in prediction of the clinical phenotype.

The importance of being cis: evolution of orthologous fish and mammalian enhancer activity

Conserved noncoding elements (CNEs) in vertebrate genomes often act as developmental enhancers, but a critical issue is how well orthologous CNE sequences retain the same activity in their respective species, a characteristic important for generalization of model organism studies. To quantify how well CNE enhancer activity has been preserved, we compared the anatomy-specific activities of 41 zebra fish CNEs in zebra fish embryos with the activities of orthologous human CNEs in mouse embryos. We found that 13/41 (∼30%) of the orthologous CNE pairs exhibit conserved positive activity in zebra fish and mouse. Conserved positive activity is only weakly associated with either sequence conservation or the absence of bases undergoing accelerated evolution. A stronger effect is that disparate activity is associated with transcription factor binding site divergence. To distinguish the contributions of cis- versus trans-regulatory changes, we analyzed 13 CNEs in a three-way experimental comparison: human CNE tested in zebra fish, human CNE tested in mouse, and orthologous zebra fish CNE tested in zebra fish. Both cis- and trans-changes affect a significant fraction of CNEs, although human and zebra fish sequences exhibit disparate activity in zebra fish (indicating cis regulatory changes) twice as often as human sequences show disparate activity when tested in mouse and zebra fish (indicating trans regulatory changes). In all four cases where the zebra fish and human CNE display a similar expression pattern in zebra fish, the human CNE also displays a similar expression pattern in mouse. This suggests that the endogenous enhancer activity of ∼30% of human CNEs can be determined from experiments in zebra fish alone, and to identify these CNEs, both the zebra fish and the human sequences should be tested.

cneViewer: a database of conserved non-coding elements for studies of tissue-specific gene regulation

There are thousands of strongly conserved non-coding elements (CNEs) in vertebrate genomes, and their functions remain largely unknown. However, without biologically relevant criteria for prioritizing them, selecting a particular CNE sequences to study can be haphazard. To address this problem, we present cneViewer-a database and webtool that systematizes information on conserved non-coding DNA elements in zebrafish. A key feature here is the ability to search for CNEs that may be relevant to tissue-specific gene regulation, based on known developmental expression patterns of nearby genes. cneViewer provides this and other organizing features that significantly facilitate experimental design and CNE analysis.