Neoantigen Landscape Supports Feasibility of Personalized Cancer Vaccine for Follicular Lymphoma

Personalized cancer vaccines designed to target neoantigens represent a promising new treatment paradigm in oncology. In contrast to classical idiotype vaccines, we hypothesized that 'polyvalent' vaccines could be engineered for the personalized treatment of follicular lymphoma (FL) using neoantigen discovery by combined whole exome sequencing (WES) and RNA sequencing (RNA-Seq). Fifty-eight tumor samples from 57 patients with FL underwent WES and RNA-Seq. Somatic and B-cell clonotype neoantigens were predicted and filtered to identify high-quality neoantigens. B-cell clonality was determined by alignment of B-cell receptor (BCR) CDR3 regions from RNA-Seq data, grouping at the protein level, and comparison to the BCR repertoire from healthy individuals using RNA-Seq data. An average of 52 somatic mutations per patient (range: 2-172) were identified, and two or more (median: 15) high-quality neoantigens were predicted for 56 of 58 FL samples. The predicted neoantigen peptides were composed of missense mutations (77%), indels (9%), gene fusions (3%), and BCR sequences (11%). Building off of these preclinical analyses, we initiated a pilot clinical trial using personalized neoantigen vaccination combined with PD-1 blockade in patients with relapsed or refractory FL (#NCT03121677). Synthetic long peptide (SLP) vaccines targeting predicted high-quality neoantigens were successfully synthesized for and administered to all four patients enrolled. Initial results demonstrate feasibility, safety, and potential immunologic and clinical responses. Our study suggests that a genomics-driven personalized cancer vaccine strategy is feasible for patients with FL, and this may overcome prior challenges in the field.

Ultra-Deep Sequencing Reveals the Mutational Landscape of Classical Hodgkin Lymphoma

The malignant Hodgkin and Reed Sternberg (HRS) cells of classical Hodgkin lymphoma (cHL) are scarce in affected lymph nodes, creating a challenge to detect driver somatic mutations. As an alternative to cell purification techniques, we hypothesized that ultra-deep exome sequencing would allow genomic study of HRS cells, thereby streamlining analysis and avoiding technical pitfalls. To test this, 31 cHL tumor/normal pairs were exome sequenced to approximately 1,000× median depth of coverage. An orthogonal error-corrected sequencing approach verified >95% of the discovered mutations. We identified mutations in genes novel to cHL including: CDH5 and PCDH7, novel stop gain mutations in IL4R, and a novel pattern of recurrent mutations in pathways regulating Hippo signaling. As a further application of our exome sequencing, we attempted to identify expressed somatic single-nucleotide variants (SNV) in single-nuclei RNA sequencing (snRNA-seq) data generated from a patient in our cohort. Our snRNA analysis identified a clear cluster of cells containing a somatic SNV identified in our deep exome data. This cluster has differentially expressed genes that are consistent with genes known to be dysregulated in HRS cells (e.g., PIM1 and PIM3). The cluster also contains cells with an expanded B-cell clonotype further supporting a malignant phenotype. This study provides proof-of-principle that ultra-deep exome sequencing can be utilized to identify recurrent mutations in HRS cells and demonstrates the feasibility of snRNA-seq in the context of cHL. These studies provide the foundation for the further analysis of genomic variants in large cohorts of patients with cHL.

SIGNIFICANCE

Our data demonstrate the utility of ultra-deep exome sequencing in uncovering somatic variants in Hodgkin lymphoma, creating new opportunities to define the genes that are recurrently mutated in this disease. We also show for the first time the successful application of snRNA-seq in Hodgkin lymphoma and describe the expression profile of a putative cluster of HRS cells in a single patient.

Mutations associated with progression in follicular lymphoma predict inferior outcomes at diagnosis: Alliance A151303

Follicular lymphoma (FL) is clinically heterogeneous, with select patients tolerating extended watch-and-wait, whereas others require prompt treatment, suffer progression of disease within 24 months of treatment (POD24), and/or experience aggressive histologic transformation (t-FL). Because our understanding of the relationship between genetic alterations in FL and patient outcomes remains limited, we conducted a clinicogenomic analysis of 370 patients with FL or t-FL (from Cancer and Leukemia Group B/Alliance trials 50402/50701/50803, or real-world cohorts from Washington University School of Medicine, Cleveland Clinic, or University of Miami). FL subsets by grade, stage, watch-and-wait, or POD24 status did not differ by mutation burden, whereas mutation burden was significantly higher in relapsed/refractory (rel/ref) FL and t-FL than in newly diagnosed (dx) FL. Nonetheless, mutation burden in dx FL was not associated with frontline progression-free survival (PFS). CREBBP was the only gene more commonly mutated in FL than in t-FL yet mutated CREBBP was associated with shorter frontline PFS in FL. Mutations in 20 genes were more common in rel/ref FL or t-FL than in dx FL, including 6 significantly mutated genes (SMGs): STAT6, TP53, IGLL5, B2M, SOCS1, and MYD88. We defined a mutations associated with progression (MAP) signature as ≥2 mutations in these 7 genes (6 rel/ref FL or t-FL SMGs plus CREBBP). Patients with dx FL possessing a MAP signature had shorter frontline PFS, revealing a 7-gene set offering insight into FL progression risk potentially more generalizable than the m7-Follicular Lymphoma International Prognostic Index (m7-FLIPI), which had modest prognostic value in our cohort. Future studies are warranted to validate the poor prognosis associated with a MAP signature in dx FL, potentially facilitating novel trials specifically in this high-risk subset of patients.

A comparative analysis of RAS variants in patients with disorders of somatic mosaicism

PURPOSE

RAS genes (HRAS, KRAS, and NRAS) are commonly found to be mutated in cancers, and activating RAS variants are also found in disorders of somatic mosaicism (DoSM). A survey of the mutational spectrum of RAS variants in DoSM has not been performed.

METHODS

A total of 938 individuals with suspected DoSM underwent high-sensitivity clinical next-generation sequencing-based testing. We investigated the mutational spectrum and genotype-phenotype associations of mosaic RAS variants.

RESULTS

In this article, we present a series of individuals with DoSM with RAS variants. Classic hotspots, including Gly12, Gly13, and Gln61 constituted the majority of RAS variants observed in DoSM. Furthermore, we present 12 individuals with HRAS and KRAS in-frame duplication/insertion (dup/ins) variants in the switch II domain. Among the 18.3% individuals with RAS in-frame dup/ins variants, clinical findings were mainly associated with vascular malformations. Hotspots were associated with a broad phenotypic spectrum, including vascular tumors, vascular malformations, nevoid proliferations, segmental overgrowth, digital anomalies, and combinations of these. The median age at testing was higher and the variant allelic fraction was lower in individuals with in-frame dup/ins variants than those in individuals with mosaic RAS hotspots.

CONCLUSION

Our work provides insight into the allelic and clinical heterogeneity of mosaic RAS variants in nonmalignant conditions.

CIViCdb 2022: evolution of an open-access cancer variant interpretation knowledgebase

CIViC (Clinical Interpretation of Variants in Cancer; civicdb.org) is a crowd-sourced, public domain knowledgebase composed of literature-derived evidence characterizing the clinical utility of cancer variants. As clinical sequencing becomes more prevalent in cancer management, the need for cancer variant interpretation has grown beyond the capability of any single institution. CIViC contains peer-reviewed, published literature curated and expertly-moderated into structured data units (Evidence Items) that can be accessed globally and in real time, reducing barriers to clinical variant knowledge sharing. We have extended CIViC's functionality to support emergent variant interpretation guidelines, increase interoperability with other variant resources, and promote widespread dissemination of structured curated data. To support the full breadth of variant interpretation from basic to translational, including integration of somatic and germline variant knowledge and inference of drug response, we have enabled curation of three new Evidence Types (Predisposing, Oncogenic and Functional). The growing CIViC knowledgebase has over 300 contributors and distributes clinically-relevant cancer variant data currently representing >3200 variants in >470 genes from >3100 publications.

Clinical Utility of Next-Generation Sequencing Panel Testing in the Evaluation of Arteriovenous Malformations

Arteriovenous malformations (AVMs) are vascular lesions in which an overgrowth of blood vessels of varying sizes develops with one or more direct connections between the arterial and venous circulation. AVMs are seen in sporadic and syndromic conditions that are caused by a variety of genomic alterations. Here, we performed a retrospective review of the cases sent for next-generation sequencing (NGS) analysis for diseases of somatic mosaicism (DoSM). Specimens from 54 patients with clinical indication of AVMs were submitted for the DoSM NGS panel between October 2013 and Dec 2021. DNA extraction and sequence analysis were performed on affected tissues, including fresh tissue, formalin-fixed paraffin-embedded tissue, fibroblast cultures, and buccal specimens. Single-nucleotide variants (SNVs) with variant allele fractions (VAFs) greater than 3% and small insertions and deletions (indels, <21 bp) were called using VarScan2, Genome Analysis Toolkit (GATK), and Pindel. Variants with VAFs between 1-3% were manually reviewed based on the sequencing data quality and the known clinical significance. 38/54 (69.1%) patients were females and 16/54 (30.9%) were males. Ages ranged from 1 month to 73 years (median age 17 years). Most of the patients were indicated with sporadic AVM (81%), although additional clinical indications were noticed, including unspecified congenital vascular malformation (9.1%), capillary malformation (5.5%), arteriovenous fistula, and AVM associated with capillary and lymphatic malformations (1.8% each). The biopsied lesion was most often located in the head (43.6%), followed by the limbs (30.9%), and unspecified areas of the body in the remaining 25.5%. Among the 54 cases, 37 (68.5%) cases had pathogenic and/or likely pathogenic (P/LP) variants identified, 2 cases (3.7%) had variants of unknown significance, and the remaining 15 cases (27.8%) had negative results. MAP2K1 variants were found in 12 samples, followed by KRAS (8), TEK (7), PTEN (5), BRAF (4), TSC2 (2), HRAS (2), RASA1 (2), and PDGFRB (1). Of note, four cases had two P/LP variants. Among the 37 positive cases, 32 cases had somatic alterations; the remaining 5 cases had at least one germline P/LP variant, including PTEN (4) and RASA1 (1). In summary, the diagnostic yield of cases with clinical indication of AVMs was 68.5% using our in-house DoSM NGS panel. This study demonstrates the clinical utility of the DoSM NGS panel testing in the evaluation of a cohort with clinical presentations of AVMs.

Large scale genotype- and phenotype-driven machine learning in Von Hippel-Lindau disease

Von Hippel-Lindau (VHL) disease is a hereditary cancer syndrome where individuals are predisposed to tumor development in the brain, adrenal gland, kidney, and other organs. It is caused by pathogenic variants in the VHL tumor suppressor gene. Standardized disease information has been difficult to collect due to the rarity and diversity of VHL patients. Over 4100 unique articles published until October 2019 were screened for germline genotype-phenotype data. Patient data were translated into standardized descriptions using Human Genome Variation Society gene variant nomenclature and Human Phenotype Ontology terms and has been manually curated into an open-access knowledgebase called Clinical Interpretation of Variants in Cancer. In total, 634 unique VHL variants, 2882 patients, and 1991 families from 427 papers were captured. We identified relationship trends between phenotype and genotype data using classic statistical methods and spectral clustering unsupervised learning. Our analyses reveal earlier onset of pheochromocytoma/paraganglioma and retinal angiomas, phenotype co-occurrences and genotype-phenotype correlations including hotspots. It confirms existing VHL associations and can be used to identify new patterns and associations in VHL disease. Our database serves as an aggregate knowledge translation tool to facilitate sharing information about the pathogenicity of VHL variants.

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.

Abstract 1193: Enhancing pediatric cancer variant curation and representation through standardized classification and automation

Childhood cancers present unique challenges for variant interpretation in a clinical context due to their rarity, low mutation burden, diversity of molecular alterations, and heterogeneity among patients. Consequently, genes and variants associated with childhood tumors are under-represented in public cancer databases and knowledgebases. A focused effort is needed for the structured curation of genetic variant-level data to document diagnostic, prognostic, and therapeutic biomarkers for childhood cancers. The Pediatric Cancer Curation Advancement Subcommittee (PCCAS), a collaboration between the Clinical Interpretations of Variants in Cancer knowledgebase (CIViC; civicdb.org), the ClinGen Somatic Pediatric Cancer Taskforce, Disease Ontology (DO; disease-ontology.org) and CIViCmine (bionlp.bcgsc.ca/civicmine/), is addressing this challenge through enhanced curation, tagging, and automation.

PCCAS created a pediatric specific curation standard operating procedure (SOP) to harmonize pediatric evidence entered in CIViC. Our SOP provides general guidance and considerations to define and classify childhood cancers and to represent childhood cancer evidence on a spectrum of age-related incidence and presentation. For instance, pediatric evidence in CIViC is now tagged using Human Phenotype Ontology (HPO) age of onset terms, allowing pediatric evidence to be easily searched, tracked, and sorted. We also initiated the addition of new age of onset terms to enhance the granularity of these tags.

WHO ICD-O nomenclature has been chosen for pediatric disease classification in CIViC. ICD-O provides updated terminology including specific genetic subtypes, which are important in pediatric cancers where their underlying molecular profiles often define the disease. To aid curator selection of disease, we verified pediatric relevant ICD-O terms inclusion in DO and restructured DO disease hierarchies to ensure proper mapping.

CIViC highlights our pediatric cancer initiative in multiple areas including a homepage feature linking directly to a dedicated pediatric advanced search that returns all evidence tagged with pediatric or young adult age of onset. Most importantly, our childhood specific SOP and initiatives are included in all ClinGen Somatic Cancer and CIViC training sessions for consistent implementation.

CIViCmine supports CIViC by using natural language processing to identify important cancer biomarkers in the literature. To better identify pediatric biomarkers, we are adapting and refining CIViCmine to use MeSH terms and other approaches to enhance accuracy in the identification of childhood evidence in both the literature and CIViC. In conclusion, implementation of these procedures, features, and automation are pushing to make childhood cancer variant evidence more accessible and interpretable.

Citation Format: Jason Saliba, Jake Lever, Kilannin Krysiak, Arpad Danos, Alex Wagner, Heather E. Williams, Laveniya Satgunaseelan, David Meredith, Cameron J. Grisdale, Chimene Kesserwan, Jianling Ji, Shruti Rao, Catherine Cottrell, Alanna Church, Mark Evans, Yasmina Jaufeerally-Fakim, Lynn M. Schriml, Angshumoy Roy, Gordana Raca, Malachi Griffith, Obi L. Griffith. Enhancing pediatric cancer variant curation and representation through standardized classification and automation [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 1193.

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.

Phase 1/dose expansion trial of brentuximab vedotin and lenalidomide in relapsed or refractory diffuse large B-cell lymphoma

New therapies are needed for patients with relapsed/refractory (rel/ref) diffuse large B-cell lymphoma (DLBCL) who do not benefit from or are ineligible for stem cell transplant and chimeric antigen receptor therapy. The CD30-targeted, antibody-drug conjugate brentuximab vedotin (BV) and the immunomodulator lenalidomide (Len) have demonstrated promising activity as single agents in this population. We report the results of a phase 1/dose expansion trial evaluating the combination of BV/Len in rel/ref DLBCL. Thirty-seven patients received BV every 21 days, with Len administered continuously for a maximum of 16 cycles. The maximum tolerated dose of the combination was 1.2 mg/kg BV with 20 mg/d Len. BV/Len was well tolerated with a toxicity profile consistent with their use as single agents. Most patients required granulocyte colony-stimulating factor support because of neutropenia. The overall response rate was 57% (95% CI, 39.6-72.5), complete response rate, 35% (95% CI, 20.7-52.6); median duration of response, 13.1 months; median progression-free survival, 10.2 months (95% CI, 5.5-13.7); and median overall survival, 14.3 months (95% CI, 10.2-35.6). Response rates were highest in patients with CD30+ DLBCL (73%), but they did not differ according to cell of origin (P = .96). NK cell expansion and phenotypic changes in CD8+ T-cell subsets in nonresponders were identified by mass cytometry. BV/Len represents a potential treatment option for patients with rel/ref DLBCL. This combination is being further explored in a phase 3 study (registered on https://clinicaltrials.org as NCT04404283). This trial was registered on https://clinicaltrials.gov as NCT02086604.

Abstract 210: Advancing knowledgebase representation of pediatric cancer variants through ClinGen/CIViC collaboration

Childhood cancers are driven by unique profiles of somatic genetic alterations, with a significant contribution from predisposing germline variants. Understanding the genomic landscape of pediatric cancers is complicated by their rarity, the heterogeneity of variation within a given disease, and the complex forms of structural variation they contain. Variants in childhood disease may differ from those in adult versions of the same cancer type, or may have different clinical significance. Currently, pediatric variants are underrepresented in cancer variant databases, and an urgent need exists for their publicly available expert curation. To address this, the Pediatric Cancer Taskforce (PCT) was formed within the Clinical Genome Resource (ClinGen) Somatic Cancer Clinical Domain Working Group (CDWG) (https://www.clinicalgenome.org/working-groups/somatic/). The PCT is a multi-institutional group of 39 members with broad experience in childhood cancer and variant curation, whose work consists of standardization and classification of genetic variants in pediatric cancers. The CIViC knowledgebase (www.civicdb.org) is a freely available resource for Clinical Interpretation of Variants in Cancer, which leverages public curation and expert moderation to address the problem of annotating the large volume of clinically actionable cancer variants. PCT curators work together with PCT expert members and the CIViC team on variant curation, and have submitted over 230 Evidence Items and over 10 Assertions to CIViC. To further address issues specific to pediatric curation, the PCT is working with CIViC to develop new pediatric-specific CIViC features and modifications of the data model that will aid in pediatric curation. A pediatric user interface, as well as representation of large scale structural and copy number variation are being developed for version two of CIViC, expected to be released in 1-2 years, which will enable curation of a new class of structural variants often encountered in pediatric cancer. A novel standard operating procedure for childhood cancer curation in CIViC is being developed by PCT experts, curators and the CIViC team. This SOP will cover topics including curation of structural variants, as well as pediatric-specific variant tiering guidelines which take into account the sparse nature of evidence in pediatric cases. A companion resource, CIViCmine (http://bionlp.bcgsc.ca/civicmine/), will be further developed to incorporate pediatric data. These and other joint efforts of the PCT and CIViC will significantly enhance pediatric variant representation for public use, to support the care of children with cancer.

Citation Format: Arpad Danos, Wan-Hsin Lin, Jason Saliba, Angshumoy Roy, Alanna J. Church, Shruti Rao, Deborah Ritter, Kilannin Krysiak, Alex Wagner, Erica Barnell, Lana Sheta, Adam Coffman, Susanna Kiwala, Joshua F. McMichael, Laura Corson, Kevin Fisher, Heather E. Williams, Matthew Hiemenz, Katherine A. Janeway, Jianling Ji, Kesserwan A. Chimene, Laura Fuqua, Lisa Dyer, Huiling Xu, Jeffrey Jean, Laveniya Satgunaseelan, Liying Zhang, Ted W. Laetsch, Donald W. Parsons, Ryan Schmidt, Lynn M. Schriml, Kristen L. Sund, Shashikant Kulkarni, Subha Madhavan, Xinjie Xu, Rashmi Kanagal-Shamana, Marian Harris, Yasmine Akkari, Nurit Paz Yacov, Panieh Terraf, Malachi Griffith, Obi L. Griffith, Gordana Raca. Advancing knowledgebase representation of pediatric cancer variants through ClinGen/CIViC collaboration [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 210.

Abstract 206: CIViC knowledgebase adapts to field experts and community input

CIViC (civicdb.org) is an open access, expertly moderated knowledgebase for crowdsourcing Clinical Interpretations of Variants in Cancer. Stakeholders globally-including those in government, academia, industry and medicine-use CIViC to find and curate actionable interpretations of genomic variants in their therapeutic, prognostic, predisposing, diagnostic and functional contexts. Through engagement with curators and leaders in the field, CIViC has implemented several features including Assertions, Organizations and expanded help documentation.

The foundational unit of CIViC is the Evidence Item, which describes the clinical relevance of a specific variant curated from a single published source within peer-reviewed literature or ASCO abstract. Assertions aggregate Evidence Items for a given variant-disease or variant-disease-therapy combination. In response to the 2017 AMP-ASCO-CAP guidelines and collaborations with ClinGen, Assertions were modified to integrate ACMG variant pathogenicity classifications, AMP-ASCO-CAP tier designations and associations with NCCN guidelines and FDA approvals to provide a ‘state of the field' interpretation. At present, 12 Assertions spanning eight variants have been submitted by CIViC to ClinVar with one-star submitter status (Submitter ID: 506594), and CIViC has been cited as supporting information in two variants. Assertions exemplify CIViC's responsiveness to new field guidelines, expert collaborators' recommendations and its contributions to other resources.

To enhance community involvement, CIViC created Organization-attributed actions. Each action performed by a curator is tagged with their Organization. Curators may switch between Organizations if they belong to more than one. Currently, nine Organizations are recognized in CIViC, the largest being ClinGen with 79 members, 4 sub-organizations and over 24,000 actions. Organizations enable groups to prominently display and track their submissions, activity, and users.

CIViC's wide adoption has necessitated the development of robust educational material. CIViC has created nine YouTube videos, one of which is linked by the NIH ITCR homepage. CIViC has migrated help documents to a stand alone site (civic.readthedocs.io) and has made over 60 page modifications since 2019. Help documentation expansion was fueled by user feedback via the CIViC interface, collaborator meetings and in-person events (Curation Jamborees). Improved documentation allows CIViC to grow at scale, unhindered by the need for direct training.

CIViC's rapid adaptation to the needs of the community is derived from its open access nature, commitment to data provenance, active connection with users, and abundance of educational material. CIViC rapidly integrates the guidelines, regulatory standards and community recommendations in a freely accessible resource that is flexible enough to evolve with the dynamic field of cancer genomics.

Citation Format: Lana M. Sheta, Arpad M. Danos, Jason Saliba, Kilannin Krysiak, Alex H. Wagner, Erica K. Barnell, Susanna Kiwala, Joshua F. McMichael, Adam Coffman, Shahil Pema, Lynzey Kujan, Kelsy C. Cotto, Cody Ramirez, Zachary L. Skidmore, Cameron J. Grisdale, Shruti Rao, Subha Madhaven, Malachi Griffith, Obi L. Griffith. CIViC knowledgebase adapts to field experts and community input [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 206.

Abstract 208: Development of Evidence Statement curation algorithms to aid cancer variant interpretation

The Clinical Interpretation of Variants in Cancer (CIViC) knowledgebase (civicdb.org) is an open access, centralized hub for structured, community curated and expertly moderated relationships between genomic variants and cancer. Evidence is curated from peer-reviewed, published literature and is classified into one of five Types: Predisposing, Diagnostic, Prognostic, Predictive (therapeutic), or Functional. The robustness of the Evidence is conveyed through the assignment of Levels with the first three derived from patient studies (Validated, Clinical, Case Study), Preclinical, generated from in vivo or in vitro data, and Inferential, which describes indirect associations.

Each Evidence Item requires an Evidence Statement written in the curator's own words summarizing the source's results regarding the variant's clinical impact. Collaborations with groups like ClinGen have generated a significant influx of new curators, increasing the demand for detailed principles regarding data prioritization in the Evidence Statement in order to streamline the curation process. The curation community would benefit from simpler, visual guides through the complex decisions needed to appropriately and consistently curate Evidence Items. We are devoting significant effort to continue the development of straightforward Evidence curation algorithms (decision trees) similar to those used in clinical molecular testing labs to aid CIViC curators.

Previously published guidelines on development of these statements are the basis of our Evidence algorithms. Obvious inflection points for curators are clearly identified with specific details noted for each to optimize decision efficiency. As the predominant Evidence Type comprising 57% of all CIViC submissions, 58% of referenced patient trials, and 92% of Preclinical submissions, Predictive Evidence is the initial focus of our pilot guidelines with Diagnostic and Prognostic to follow. Within the Predictive Evidence Type, clinical trials, case studies, and preclinical Levels each require vastly different Evidence Statement details and ultimately the creation of three separate, uniquely modeled algorithms.

The implementation of these algorithms will assist in streamlining both curation and the expert review process. Notably, a template is not being created, as the preservation of curator style and voice is important to maintain the community feel of the database. To ensure the highest level of clarity, our team is utilizing specific novice and experienced curators to assist with the development process. As these algorithms pass the pilot phase, they are being tested as curator training tools. Ultimately, these guidelines will be used to encourage independence in curators and to enhance the Evidence already contained in CIViC.

Citation Format: Jason Saliba, Lana Sheta, Kilannin Krysiak, Arpad Danos, Alex Marr, Erica Barnell, Shahil Pema, Wan-Hsin Lin, Panieh Terraf, Joshua F. McMichael, Cameron J. Grisdale, Shruti Rao, Susanna Kiwala, Adam Coffman, Alex Wagner, Obi L. Griffith, Malachi Griffith. Development of Evidence Statement curation algorithms to aid cancer variant interpretation [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 208.

Heterozygous HMGB1 loss-of-function variants are associated with developmental delay and microcephaly

13q12.3 microdeletion syndrome is a rare cause of syndromic intellectual disability. Identification and genetic characterization of patients with 13q12.3 microdeletion syndrome continues to expand the phenotypic spectrum associated with it. Previous studies identified four genes within the approximately 300 Kb minimal critical region including two candidate protein coding genes: KATNAL1 and HMGB1. To date, no patients carrying a sequence-level variant or a single gene deletion in HMGB1 or KATNAL1 have been described. Here we report six patients with loss-of-function variants involving HMGB1 and who had phenotypic features similar to the previously described 13q12.3 microdeletion syndrome cases. Common features included developmental delay, language delay, microcephaly, obesity and dysmorphic features. In silico analyses suggest that HMGB1 is likely to be intolerant to loss-of-function, and previous in vitro data are in line with the role of HMGB1 in neurodevelopment. These results strongly suggest that haploinsufficiency of the HMGB1 gene may play a critical role in the pathogenesis of the 13q12.3 microdeletion syndrome.

Impact of a 40-Gene Targeted Panel Test on Physician Decision Making for Patients With Acute Myeloid Leukemia

PURPOSE

Physicians treating hematologic malignancies increasingly order targeted sequencing panels to interrogate recurrently mutated genes. The precise impact of these panels on clinical decision making is not well understood.

METHODS

Here, we report our institutional experience with a targeted 40-gene panel (MyeloSeq) that is used to generate a report for both genetic variants and variant allele frequencies for the treating physician (the limit of mutation detection is approximately one AML cell in 50).

RESULTS

In total, 346 sequencing reports were generated for 325 patients with suspected hematologic malignancies over an 8-month period (August 2018 to April 2019). To determine the influence of genomic data on clinical care for patients with acute myeloid leukemia (AML), we analyzed 122 consecutive reports from 109 patients diagnosed with AML and surveyed the treating physicians with a standardized questionnaire. The panel was ordered most commonly at diagnosis (61.5%), but was also used to assess response to therapy (22.9%) and to detect suspected relapse (15.6%). The panel was ordered at multiple timepoints during the disease course for 11% of patients. Physicians self-reported that 50 of 114 sequencing reports (44%) influenced clinical care decisions in 44 individual patients. Influences were often nuanced and extended beyond identifying actionable genetic variants with US Food and Drug Administration-approved drugs.

CONCLUSION

This study provides insights into how physicians are currently using multigene panels capable of detecting relatively rare AML cells. The most influential way to integrate these tools into clinical practice will be to perform prospective clinical trials that assess patient outcomes in response to genomically driven interventions.

Abstract PO-06: Ultradeep sequencing of classical Hodgkin lymphoma (cHL) identifies recurrent somatic mutations and demonstrates the production of reproducible data from rare malignant cells

Purpose/Background: cHL patients who receive standard therapy have a high rate of event-free and overall survival. However, some patients (~10%) will be refractory to initial therapy and up to 1/3 will relapse. Thus, improved methods of prognostication and new treatment targets are needed. High-throughput sequencing can identify recurrent somatic mutations that drive lymphomagenesis and impact treatment response. However, Hodgkin-Reed-Sternberg (HRS) cells have a low (~1%) abundance in cHL biopsies, creating a challenge for comprehensive and accurate detection of somatic mutations in bulk lymphoma biopsies. Genomic studies of cHL have characterized HRS somatic mutations through the analysis of malignant cells obtained using purification techniques, cell-free DNA, or DNA amplified through whole-genome amplification. We hypothesized that ultradeep sequencing of bulk lymphoma biopsies provides a more accessible approach to HRS characterization while also creating robust and reproducible data.

Methods: We performed exome sequencing on 32 fresh frozen samples from 31 cHL patients obtained prior to treatment (27) or after relapse (4) with paired normal skin samples (31). The Illumina HiSeq platform (2 x 150bp reads) was used with multiple independent library constructions and a 1,000X median coverage goal. Sequence data were aligned to GRCh38. SNVs and INDELs were called using multiple algorithms. We employed several variant filtering strategies, including manual review, to remove common polymorphisms and false positives. Because we discovered mutations with VAFs close to the platform error rate (~1%), we used an orthogonal sequencing strategy (Haloplex) to validate all somatic variants.

Results: We observed 4,020 somatic variants. On average, we observed 32 protein-coding mutations/case, excluding one hypermutated case in which 3,084 variants were observed. We identified a potential loss-of-function insertion in MSH6 that could explain the hypermutated phenotype. We achieved a 99% validation rate across the cohort for somatic variants discovered in exomes. We confirmed known recurrently mutated cHL genes (e.g., SOCS1 [43%], STAT6 [20%], TNFAIP3 [40%]). We identified several significantly recurrent mutated genes not well characterized in cHL, including IGLL5 [26%] and IL4R [13%]. All IL4R mutations are potential loss-of-function mutations that could result in greater activation of STAT6 through ablation of ITIM negative modulation. We identified an enrichment of SOCS1 and IGLL5 mutations that is likely the result of aberrant somatic hypermutation. Pathway analysis also identified an enrichment of mutations in MAPK pathways.

Conclusion: These data suggest that cHL somatic mutations can be confidently identified via ultradeep exome sequencing without cell purification. We show that cHL genomes harbor somatic variation that inform new targets for treatment and prognostication.

Citation Format: Felicia Gomez, Matthew Mosior, Zachary Skidmore, Alina Schmidt, Fernanda Rodrigues-Martins, Kilannin Krysiak, Cody Ramirez, Eric Duncavage, Grace Triska, Lee Trani, Nancy Bartlett, Amanda Cashen, Neha Mehta-Shah, Friederike Kreisel, Malachi Griffith, Todd Fehniger, Obi Griffith. Ultradeep sequencing of classical Hodgkin lymphoma (cHL) identifies recurrent somatic mutations and demonstrates the production of reproducible data from rare malignant cells [abstract]. In: Proceedings of the AACR Virtual Meeting: Advances in Malignant Lymphoma; 2020 Aug 17-19. Philadelphia (PA): AACR; Blood Cancer Discov 2020;1(3_Suppl):Abstract nr PO-06.

A Spontaneous Aggressive ERα+ Mammary Tumor Model Is Driven by Kras Activation

The NRL-PRL murine model, defined by mammary-selective transgenic rat prolactin ligand rPrl expression, establishes spontaneous ER+ mammary tumors in nulliparous females, mimicking the association between elevated prolactin (PRL) and risk for development of ER+ breast cancer in postmenopausal women. Whole-genome and exome sequencing in a discovery cohort (n = 5) of end-stage tumors revealed canonical activating mutations and copy number amplifications of Kras. The frequent mutations in this pathway were validated in an extension cohort, identifying activating Ras alterations in 79% of tumors (23 of 29). Transcriptome analyses over the course of oncogenesis revealed marked alterations associated with Ras activity in established tumors compared with preneoplastic tissues; in cell-intrinsic processes associated with mitosis, cell adhesion, and invasion; as well as in the surrounding tumor environment. These genomic analyses suggest that PRL induces a selective bottleneck for spontaneous Ras-driven tumors that may model a subset of aggressive clinical ER+ breast cancers.

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.

Abstract 3215: ClinGen somatic cancer working group: Disseminating standardized cancer molecular diagnostic data and evidence through global collaboration and expert curation

The Clinical Genome (ClinGen) Resource is a US National Human Genome Research Institute (NHGRI)-funded program dedicated to building an expert curated and freely available central resource that defines the clinical relevance of genes and variants for use in precision medicine. Teams of experts in various clinical domains come together as working groups within ClinGen to facilitate the interpretation, annotation and utilization of genes-variants for clinical application. Somatic Cancer is one such ClinGen Clinical Domain Working Group (CDWG) that consists of over 90 members worldwide, including clinicians, clinical laboratory diagnosticians, genomic scientists and bioinformaticians. Members of this CDWG identify high priority somatic variants in different cancer types that require expert curation and consensus in their clinical interpretation. In order to accurately implement practice guidelines/standards for variant interpretation, the Somatic Cancer CDWG recently established a somatic Variant Curation Expert Panel (VCEP) approval process. Based on their interest and clinical domain expertise, a subset of the CDWG members formed somatic VCEPs to perform authoritative curation on the shortlisted genes-somatic variants within the context of a disease, therapeutic indication or biological pathway. Expert curation within these VCEPs is performed by utilizing guidelines such as those recommended by AMP/ASCO/CAP (Li et al. 2017) and the Somatic Cancer CDWG (Ritter et al. 2016). Wherever necessary, the somatic VCEPs will develop: 1) gene- and disease-specific modifications to address gaps in existing variant assessment guidelines, 2) quantitative approaches for variant interpretation, and 3) implement standardized protocols for annotating somatic variants in genes for a specific disease, drug or biological pathway. Furthermore, ClinGen recently formed the Cancer Variant Interpretation (CVI) committee to provide support, review and feedback on the provisional somatic variant interpretation proposals developed by the VCEPs. The CVI provides somatic VCEPs with a preliminary approval before the final approval by the ClinGen CDWG oversight committee and ultimately ‘expert panel' status in ClinVar, an NCBI-maintained database of clinically relevant gene variants. NTRK fusions in cancer is the first Somatic VCEP going through the ClinGen Somatic Expert Panel approval process. Alterations in the FGFR pathway in GU cancers is the second somatic VCEP under consideration. The Somatic CDWG uses the CIViC (Clinical Interpretation of Variants in Cancer) platform for curation of somatic variants. To date, the CDWG has curated 268 evidence items relating to cancer variants in CIViC, 6 assertions, and 33 evidence source suggestions. The ultimate goal of the Somatic CDWG is to enhance the usability, dissemination and implementation of cancer somatic changes in the ClinGen resource and other cancer variant knowledgebases.

Citation Format: Shruti Rao, Deborah Ritter, Arpad Danos, Gordana Raca, Angshumoy Roy, Kilannin Krysiak, Wan-Hsin Lin, Erica Barnell, Matthew McCoy, Beth Pitel, Dmitriy Sonkin, Jue Wang, Seyed Ali Hosseini, Shamini Selvarajah, Ian King, Rashmi Kanagal-Shamana, Xinjie Xu, Jeremy L. Warner, Funda Meric-Bernstam, Jason D. Merker, Marilyn Li, Alex H. Wagner, Malachi Griffith, Obi L. Griffith, Shashikant Kulkarni, Subha Madhavan. ClinGen somatic cancer working group: Disseminating standardized cancer molecular diagnostic data and evidence through global collaboration and expert curation [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 3215.

Abstract 5462: Adding CIViC knowledge to variant annotation pipelines with CIViCpy

Precision oncology is dependent upon the matching of tumor variants to relevant knowledge describing the clinical significance of those variants. We recently developed the Clinical Interpretations for Variants in Cancer (CIViC; civicdb.org) crowd-sourced, expert-moderated, and open-access knowledgebase. CIViC provides a structured framework for evaluating genomic variants of various types (e.g., fusions, SNVs) for their clinical utility based on therapeutic, prognostic, predisposing, diagnostic, and functional evidence. CIViC has a documented API for accessing CIViC records: Assertions, Evidence, Variants, and Genes. Third-party tools that analyze or access the contents of this knowledgebase must programmatically leverage this API, often reimplementing redundant functionality in the pursuit of common analysis tasks that are beyond the scope of the CIViC web application.

We recently published CIViCpy v1.0 (civicpy.org), a software development kit (SDK) for extracting and analyzing the contents of the CIViC knowledgebase. CIViCpy enables users to query CIViC content as dynamic objects in Python. Here we highlight new features and informative analyses introduced since the original publication. New features include an extended variant search functionality that supports queries by variant name, HGVS, and ClinGen Allele Registry ID (CAID). In addition to the CIViC-native GRCh37 coordinates, CIViCpy now supports variant queries from multiple alternative human genome builds, including hg18 and GRCh38. CIViCpy also includes multiple easy-to-use tools for straightforward installation in a variety of compute environments.

A commonly requested feature is the annotation of user-provided variants in Variant Call Format (VCF) with CIViC data. CIViCpy now provides convenient methods, including a command line interface (CLI), for performing this task. We illustrate the use of newly added features by annotating pan-cancer VCF files from The Cancer Genome Atlas (TCGA). We show that CIViCpy is able to quickly and efficiently annotate patient variants in the context of the reported disease type, appending data about the associated CIViC Evidence and Assertions to the provided VCF files.

The clinical interpretation of genomic variants in cancers requires high-throughput tools for interoperability and analysis of variant interpretation knowledge. These needs are met by CIViCpy, an SDK for downstream applications and rapid analysis. The new features discussed here allow users to easily incorporate CIViC knowledge into their variant annotation pipelines. CIViCpy (civicpy.org) is fully documented, open-source, and freely available online.

Citation Format: Susanna Kiwala, Alex H. Wagner, Adam C. Coffman, Joshua F. McMichael, Kelsy C. Cotto, Thomas B. Mooney, Erica K. Barnell, Kilannin Krysiak, Arpad M. Danos, Jason M. Walker, Obi L. Griffith, Malachi Griffith. Adding CIViC knowledge to variant annotation pipelines with CIViCpy [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 5462.

Open-Sourced CIViC Annotation Pipeline to Identify and Annotate Clinically Relevant Variants Using Single-Molecule Molecular Inversion Probes

PURPOSE

Clinical targeted sequencing panels are important for identifying actionable variants for patients with cancer; however, existing approaches do not provide transparent and rationally designed clinical panels to accommodate the rapidly growing knowledge within oncology.

MATERIALS AND METHODS

We used the Clinical Interpretations of Variants in Cancer (CIViC) database to develop an Open-Sourced CIViC Annotation Pipeline (OpenCAP). OpenCAP provides methods to identify variants within the CIViC database, build probes for variant capture, use probes on prospective samples, and link somatic variants to CIViC clinical relevance statements. OpenCAP was tested using a single-molecule molecular inversion probe (smMIP) capture design on 27 cancer samples from 5 tumor types. In total, 2,027 smMIPs were designed to target 111 eligible CIViC variants (61.5 kb of genomic space).

RESULTS

When compared with orthogonal sequencing, CIViC smMIP sequencing demonstrated a 95% sensitivity for variant detection (n = 61 of 64 variants). Variant allele frequencies for variants identified on both sequencing platforms were highly concordant (Pearson’s r = 0.885; n = 61 variants). Moreover, for individuals with paired tumor and normal samples (n = 12), 182 clinically relevant variants missed by orthogonal sequencing were discovered by CIViC smMIP sequencing.

CONCLUSION

The OpenCAP design paradigm demonstrates the utility of an open-source and open-access database built on attendant community contributions with peer-reviewed interpretations. Use of a public repository for variant identification, probe development, and variant interpretation provides a transparent approach to build dynamic next-generation sequencing–based oncology panels.

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.

CIViCpy: A Python Software Development and Analysis Toolkit for the CIViC Knowledgebase

PURPOSE

Precision oncology depends on the matching of tumor variants to relevant knowledge describing the clinical significance of those variants. We recently developed the Clinical Interpretations for Variants in Cancer (CIViC; civicdb.org) crowd-sourced, expert-moderated, and open-access knowledgebase. CIViC provides a structured framework for evaluating genomic variants of various types (eg, fusions, single-nucleotide variants) for their therapeutic, prognostic, predisposing, diagnostic, or functional utility. CIViC has a documented application programming interface for accessing CIViC records: assertions, evidence, variants, and genes. Third-party tools that analyze or access the contents of this knowledgebase programmatically must leverage this application programming interface, often reimplementing redundant functionality in the pursuit of common analysis tasks that are beyond the scope of the CIViC Web application.

METHODS

To address this limitation, we developed CIViCpy (civicpy.org), a software development kit for extracting and analyzing the contents of the CIViC knowledgebase. CIViCpy enables users to query CIViC content as dynamic objects in Python. We assess the viability of CIViCpy as a tool for advancing individualized patient care by using it to systematically match CIViC evidence to observed variants in patient cancer samples.

RESULTS

We used CIViCpy to evaluate variants from 59,437 sequenced tumors of the American Association for Cancer Research Project GENIE data set. We demonstrate that CIViCpy enables annotation of > 1,200 variants per second, resulting in precise variant matches to CIViC level A (professional guideline) or B (clinical trial) evidence for 38.6% of tumors.

CONCLUSION

The clinical interpretation of genomic variants in cancers requires high-throughput tools for interoperability and analysis of variant interpretation knowledge. These needs are met by CIViCpy, a software development kit for downstream applications and rapid analysis. CIViCpy is fully documented, open-source, and available free online.

Text-mining clinically relevant cancer biomarkers for curation into the CIViC database

BACKGROUND

Precision oncology involves analysis of individual cancer samples to understand the genes and pathways involved in the development and progression of a cancer. To improve patient care, knowledge of diagnostic, prognostic, predisposing, and drug response markers is essential. Several knowledgebases have been created by different groups to collate evidence for these associations. These include the open-access Clinical Interpretation of Variants in Cancer (CIViC) knowledgebase. These databases rely on time-consuming manual curation from skilled experts who read and interpret the relevant biomedical literature.

METHODS

To aid in this curation and provide the greatest coverage for these databases, particularly CIViC, we propose the use of text mining approaches to extract these clinically relevant biomarkers from all available published literature. To this end, a group of cancer genomics experts annotated sentences that discussed biomarkers with their clinical associations and achieved good inter-annotator agreement. We then used a supervised learning approach to construct the CIViCmine knowledgebase.

RESULTS

We extracted 121,589 relevant sentences from PubMed abstracts and PubMed Central Open Access full-text papers. CIViCmine contains over 87,412 biomarkers associated with 8035 genes, 337 drugs, and 572 cancer types, representing 25,818 abstracts and 39,795 full-text publications.

CONCLUSIONS

Through integration with CIVIC, we provide a prioritized list of curatable clinically relevant cancer biomarkers as well as a resource that is valuable to other knowledgebases and precision cancer analysts in general. All data is publically available and distributed with a Creative Commons Zero license. The CIViCmine knowledgebase is available at http://bionlp.bcgsc.ca/civicmine/.

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.