Pitel, Beth A.

AbstractAcute lymphoblastic leukemia (B‐ALL) with intrachromosomal amplification of chromosome 21 (iAMP21‐ALL) represents a recurrent high‐risk cytogenetic abnormality and accurate identification is critical for appropriate clinical management. Identification of iAMP21‐ALL has historically relied on fluorescence in situ hybridization (FISH) using a RUNX1 probe. Current classification requires ≥ five copies of RUNX1 per cell and ≥ three additional copies of RUNX1 on a single abnormal iAMP21‐chromosome. We sought to evaluate the performance of the RUNX1 probe in the identification of iAMP21‐ALL. This study was a retrospective evaluation of iAMP21‐ALL in the Mayo Clinic and Children's Oncology Group cohorts. Of 207 cases of iAMP21‐ALL, 188 (91%) were classified as “typical” iAMP21‐ALL, while 19 (9%) cases were classified as “unusual” iAMP21‐ALL. The “unusual” iAMP21 cases did not meet the current definition of iAMP21 by FISH but were confirmed to have iAMP21 by chromosomal microarray. Half of the “unusual” iAMP21‐ALL cases had less than five RUNX1 signals, while the remainder had ≥ five RUNX1 signals with some located apart from the abnormal iAMP21‐chromosome. Nine percent of iAMP21‐ALL cases fail to meet the FISH definition of iAMP21‐ALL demonstrating that laboratories are at risk of misidentification of iAMP21‐ALL when relying only on the RUNX1 FISH probe. Incorporation of chromosomal microarray testing circumvents these risks.

Abstract The basis for acquired resistance to JAK inhibition in patients with JAK2-driven hematologic malignancies is not well understood. We report a patient with a myeloproliferative neoplasm (MPN) with a BCR activator of RhoGEF and GTPase (BCR)–JAK2 fusion with initial hematologic response to ruxolitinib who rapidly developed B-lymphoid blast transformation. We analyzed pre-ruxolitinib and blast transformation samples using genome sequencing, DNA mate-pair sequencing (MPseq), RNA sequencing (RNA-seq), and chromosomal microarray to characterize possible mechanisms of resistance. No resistance mutations in the BCR-JAK2 fusion gene or transcript were identified, and fusion transcript expression levels remained stable. However, at the time of blast transformation, MPseq detected a new IKZF1 copy-number loss, which is predicted to result in loss of normal IKZF1 protein translation. RNA-seq revealed significant upregulation of genes negatively regulated by IKZF1, including IL7R and CRLF2. Disease progression was also characterized by adaptation to an activated B-cell receptor (BCR)–like signaling phenotype, with marked upregulation of genes such as CD79A, CD79B, IGLL1, VPREB1, BLNK, ZAP70, RAG1, and RAG2. In summary, IKZF1 deletion and a switch from cytokine dependence to activated BCR-like signaling phenotype represent putative mechanisms of ruxolitinib resistance in this case, recapitulating preclinical data on resistance to JAK inhibition in CRLF2-rearranged Philadelphia chromosome-like acute lymphoblastic leukemia.

Purpose: Acute myeloid leukemia (AML) is the most common acute leukemia in adults, affecting approximately 20,000 patients annually in the United States. AML genetic subtypes, as defined by the World Health Organization (WHO), are identified through fluorescence in situ hybridization (FISH), conventional chromosome analysis, and sequencing techniques. Mate pair sequencing (MPseq) is a next generation sequencing (NGS) technology optimized to detect genome wide structural variants and copy number alterations at high resolution. Our study goal was to investigate the prognostic value of MPseq in comparison to FISH, chromosome, and sequencing studies in the evaluation of AML patients. Methods: We performed a prospective study using blood and bone marrow samples from 105 patients with a diagnosis of AML, using MPseq, along with chromosome, FISH, and NGS or PCR studies to detect small mutations. Cytogenetic and molecular genetic results were correlated with MPseq findings. We also analyzed the MPseq data for chromoplexy, chromothripsis, and progressive complexity. Junction and copy number burden, the incidence of structural variation in the genome and the percent of the genome with aberrant copy number, were evaluated. Overall survival statistics were stratified by AML subtypes and observed anomalies. Results: Although structural variants in AML were characterized at a high resolution using MPseq when compared to conventional cytogenetic methods, risk stratification using current European Leukemia Net (ELN) guidelines was not improved by MPseq. The cohorts involving 5q and/or 7q deletions exhibited high levels of genomic complexity when compared to normal karyotype AML (NK-AML). The incidence of copy number gains, losses and junctions was greatest in 5q and 7q co-deletions (5q/7q) (16.5, 25.0, 69.3) and 5q deletions (5q) (9.8, 16.7, 31.6) subtypes compared to 7q deletions (3.4, 7.0, 6.7) and NK-AML (2.6, 4.3, 3.8) (p<0.001) subtypes. Chromoplexy, chromothripsis, and progressive structural complexity were detected in most samples with 5q deletions and 5q/7q co-deletions, but absent in samples with 7q or NK-AML. Biallelic inactivation of TP53 by sequencing mutation and/or deletion was common in the 5q/7q co-deletion (14/18 cases) and 5q deletion cohorts (7/10 cases), rare in the 7q deletion cohort (1/11 cases), and absent in the NK-AML (n=44) cohort. The median OS was significantly worse for patients with 5q/7q deletions (122.5 days) and 5q deletions (248 days) compared to NK-AML (413.5 days; p<0.001 and p=0.017, respectively) and between 5q/7q deletions and 7q deletions (370.5 days; p<0.001). No significant difference was observed between 5q/7q and 5q deletion subtypes, between NK and 7q deletion subtypes and between 5q and 7q deletion subtypes. The median OS was also significantly shorter for patients with TP53 alterations compared to patients with normal TP53 status. Patients with chromoplexy, chromothripsis and/or progressive structural complexity identified by MPseq had a significantly shorter median OS compared to patients without these features. (p<0.0001) Discussion: Risk stratifications based on current guidelines using cytogenetic and sequencing results were not adjusted due to MPseq results, which is not surprising when primary abnormalities are observed by conventional cytogenetic methods. NK-AML cases did not appear to benefit from a high resolution genomic evaluation. However, MPseq added value when structural variation required additional characterization, detecting novel rearrangements, such as a KAT6A/SORBS3 fusion. Lastly, we recognized common mischaracterizations made by conventional chromosome studies - including missed TP53 deletions in 7 cases, 5q/7q deletions misinterpreted as monosomies, cryptic NUP98 rearrangements, and unappreciated genomic complexity correlating with poor OS. These mischaracterizations challenge the use of conventional chromosome studies as a gold standard without accompanying FISH or MPseq studies. MPseq, similar to other structural methodologies such as optical mapping and long read sequencing, should be considered important complements to standard cytologic techniques given the important additional genomic information obtained. The additional structural variant characterization will be critical in paving the way for genomic discovery with the overall goal of improving prognostication for patient care. Figure Disclosures Vasmatzis: WholeGenome LLC.: Other: Owner; Mayo Clinic: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract Somatic variants in cancer-relevant genes are interpreted from multiple partially overlapping perspectives. When considered in discovery and translational research endeavors, it is important to determine if a particular variant observed in a gene of interest is oncogenic/pathogenic or not, as such knowledge provides the foundation on which targeted cancer treatment research is based. In contrast, clinical applications are dominated by diagnostic, prognostic, or therapeutic interpretations which in part also depends on underlying variant oncogenicity/pathogenicity. The Association for Molecular Pathology, the American Society of Clinical Oncology, and the College of American Pathologists (AMP/ASCO/CAP) have published structured somatic variant clinical interpretation guidelines which specifically address diagnostic, prognostic, and therapeutic implications. These guidelines have been well-received by the oncology community. Many variant knowledgebases, clinical laboratories/centers have adopted or are in the process of adopting these guidelines. The AMP/ASCO/CAP guidelines also describe different data types which are used to determine oncogenicity/pathogenicity of a variant, such as: population frequency, functional data, computational predictions, segregation, and somatic frequency. A second collaborative effort created the European Society for Medical Oncology (ESMO) Scale for Clinical Actionability of molecular Targets to provide a harmonized vocabulary that provides an evidence-based ranking system of molecular targets that supports their value as clinical targets. However, neither of these clinical guideline systems provide systematic and comprehensive procedures for aggregating population frequency, functional data, computational predictions, segregation, and somatic frequency to consistently interpret variant oncogenicity/pathogenicity, as has been published in the ACMG/AMP guidelines for interpretation of pathogenicity of germline variants. In order to address this unmet need for somatic variant oncogenicity/pathogenicity interpretation procedures, the Variant Interpretation for Cancer Consortium (VICC, a GA4GH driver project) Knowledge Curation and Interpretation Standards (KCIS) working group (WG) has developed a Standard Operating Procedure (SOP) with contributions from members of ClinGen Somatic Clinical Domain WG, and ClinGen Somatic/Germline variant curation WG using an approach similar to the ACMG/AMP germline pathogenicity guidelines to categorize evidence of oncogenicity/pathogenicity as very strong, strong, moderate or supporting. This SOP enables consistent and comprehensive assessment of oncogenicity/pathogenicity of somatic variants and latest version of an SOP can be found at https://cancervariants.org/wg/kcis/. Citation Format: Peter Horak, Malachi Griffith, Arpad Danos, Beth A. Pitel, Subha Madhavan, Xuelu Liu, Jennifer Lee, Gordana Raca, Shirley Li, Alex H. Wagner, Shashikant Kulkarni, Obi L. Griffith, Debyani Chakravarty, Dmitriy Sonkin. A standard operating procedure for the interpretation of oncogenicity/pathogenicity of somatic mutations [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 5707.

Abstract Comprehensive interpretation of a patient's cancer genome is a cross-disciplinary process requiring the expertise of oncologists, molecular pathologists, genetic counselors, genomic scientists, and bioinformaticians. The Variant Interpretation for Cancer Consortium (VICC) has created a non-clinical forum for the variant interpretation process by connecting experts from multiple academic institutions and industry to create a Virtual Molecular Tumor Board (VMTB). During VICC-VMTB sessions, experts retrospectively discuss de-identified, challenging patient cases in the context of genomic interpretation guidelines to evaluate a patient's profile across several distinct components: genomic variants; disease context; therapeutic history; family history; demographic information; genomic assay information; and variant allele frequency. These components are processed through the prism of publically available knowledge and expertise of VMTB members, resulting in a broad spectrum of clinically relevant assertions about the patient's disease that may be of prognostic, diagnostic, or predictive relevance. Through these evaluations, the VICC-VMTB primarily works as a means of illuminating challenges in genomic interpretation and advancing the objectives of domain-specific VICC working groups. Examples of challenges that have been highlighted by the VICC-VMTB forum include: 1) inconsistent disease and therapy ontologies across resources are being addressed by Disease Harmonization & Drug Harmonization working groups, respectively; 2) use of machine-learning and natural language processing into clinical-grade variant interpretation are being addressed by the AI-Assisted Curation working group; 3) aggregation and harmonization of knowledgebase data into a centralized resource is being addressed by the Data Licensing and Variant Harmonization working groups; 4) inefficiencies in knowledgebase search functions are being addressed by the Search working group; 5) determination of accurate prediction of biological consequences of rare variants is being addressed by the In Silico Interpretation working group; and 6) standardization of genomic variant curation is being addressed by the Knowledge Curation and Interpretation Standards working group. These VICC working groups provide dedicated expert assemblies intended to specifically tackle these challenges, further increasing the breadth for which genomic information can be made useful in cancer variant interpretation. The VICC-VMTB has been a pertinent link between cancer genomes and clinical interpretation. We are confident VICC-VMTB will continue to be a gateway of acceleration and progress needed in the field of cancer interpretation to provide accurate and efficient answers for our patients in the future. Citation Format: Beth A. Pitel, Shruti Rao, Catherine Del Vecchio Fitz, Subha Madhavan, Rodrigo Dientsmann, Peter Horak, Ian King, Susan M. Mockus, Gordana Raca, Damian T. Rieke, Peter Rogan, Dmitriy Sonkin, David Tamborero, Ioannis S. Vlachos, Brian Walsh, Jeremy L. Warner, Malachi Griffith, Obi L. Griffith, Debyani Chakravarty, Alex H. Wagner. The Virtual Molecular Tumor Board of the Variant Interpretation for Cancer Consortium: A systematic gateway connecting cancer genome interpretation and progress in genomic knowledgebases 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 3222.

Abstract 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 The use of clinical gene sequencing is now commonplace, and genome analysts and molecular pathologists are often tasked with the labor-intensive process of interpreting the clinical significance of large numbers of tumor variants. Numerous independent knowledgebases have been constructed to alleviate this manual burden, however these knowledgebases are non-interoperable. As a result, the analyst is left with a difficult tradeoff: for each knowledgebase used the analyst must understand the nuances particular to that resource and integrate its evidence accordingly when generating the clinical report, but for each knowledgebase omitted there is increased potential for missed findings of clinical significance.The Variant Interpretation for Cancer Consortium (VICC; cancervariants.org) was formed as a driver project of the Global Alliance for Genomics and Health (GA4GH; ga4gh.org) to address this concern. VICC members include representatives from several major somatic interpretation knowledgebases including CIViC, OncoKB, Jax-CKB, the Weill Cornell PMKB, the IRB-Barcelona Cancer Biomarkers Database, and others. Previously, the VICC built and reported on a harmonized meta-knowledgebase of 19,551 biomarker associations of harmonized variants, diseases, drugs, and evidence across the constituent resources.In that study, we analyzed the frequency with which the tumor samples from the AACR Project GENIE cohort would match to harmonized associations. Variant matches increased dramatically from 57% to 86% when broader matching to regions describing categorical variants were allowed. Unlike precise sequence variants with specified alternate alleles, categorical variants describe a collection of potential variants with a common feature, such as “V600” (non-valine alleles at the 600 residue), “Exon 20 mutations” (all non-silent mutations in exon 20), or “Gain-of-function” (hypermorphic alterations that activate or amplify gene activity). However, matching observed sequence variants to categorical variants is challenging, as the latter are typically only described as unstructured text. Here we describe the expressive and computational GA4GH Variation Representation specification (vr-spec.readthedocs.io), which we co-developed as members of the GA4GH Genomic Knowledge Standards work stream. This specification provides a schema for common, precise forms of variation (e.g. SNVs and Indels) and the method for computing identifiers from these objects. We highlight key aspects of the specification and our work to apply it to the characterization of categorical variation, showcasing the variant terminology and classification tools developed by the VICC to support this effort. These standards and tools are free, open-source, and extensible, overcoming barriers to standardized variant knowledge sharing and search. Citation Format: Alex H. Wagner, Reece K. Hart, Larry Babb, Robert R. Freimuth, Adam Coffman, Yonghao Liang, Beth Pitel, Angshumoy Roy, Matthew Brush, Jennifer Lee, Anna Lu, Thomas Coard, Shruti Rao, Deborah Ritter, Brian Walsh, Susan Mockus, Peter Horak, Ian King, Dmitriy Sonkin, Subha Madhavan, Gordana Raca, Debyani Chakravarty, Malachi Griffith, Obi L. Griffith. Harmonization standards from the Variant Interpretation for Cancer Consortium [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 1096.

PURPOSE The cancer research community is constantly evolving to better understand tumor biology, disease etiology, risk stratification, and pathways to novel treatments. Yet the clinical cancer genomics field has been hindered by redundant efforts to meaningfully collect and interpret disparate data types from multiple high-throughput modalities and integrate into clinical care processes. Bespoke data models, knowledgebases, and one-off customized resources for data analysis often lack adequate governance and quality control needed for these resources to be clinical grade. Many informatics efforts focused on genomic interpretation resources for neoplasms are underway to support data collection, deposition, curation, harmonization, integration, and analytics to support case review and treatment planning. METHODS In this review, we evaluate and summarize the landscape of available tools, resources, and evidence used in the evaluation of somatic and germline tumor variants within the context of molecular tumor boards. RESULTS Molecular tumor boards (MTBs) are collaborative efforts of multidisciplinary cancer experts equipped with genomic interpretation resources to aid in the delivery of accurate and timely clinical interpretations of complex genomic results for each patient, within an institution or hospital network. Virtual MTBs (VMTBs) provide an online forum for collaborative governance, provenance, and information sharing between experts outside a given hospital network with the potential to enhance MTB discussions. Knowledge sharing in VMTBs and communication with guideline-developing organizations can lead to progress evidenced by data harmonization across resources, crowd-sourced and expert-curated genomic assertions, and a more informed and explainable usage of artificial intelligence. CONCLUSION Advances in cancer genomics interpretation aid in better patient and disease classification, more streamlined identification of relevant literature, and a more thorough review of available treatments and predicted patient outcomes.

AbstractInfant leukemias are a rare group of neoplasms that are clinically and biologically distinct from their pediatric and adult counterparts. Unlike leukemia in older children where survival rates are generally favorable, infants with leukemia have a 5‐year event‐free survival rate of <50%. The majority of infant leukemias are characterized by KMT2A (MLL) rearrangements (~70 to 80% in acute lymphoblastic leukemia), which appear to be drivers of early leukemogenesis. In this report, we describe three cases: a 9‐month‐old female infant with B‐acute lymphoblastic leukemia (B‐ALL), an 8‐month‐old female presenting with B/myeloid mixed phenotype acute leukemia (MPAL), and a 16‐month‐old male with B‐ALL. The first case had a normal karyotype and B‐ALL FISH results consistent with an atypical KMT2A rearrangement. The second case had trisomy 10 as the sole chromosomal abnormality and a normal KMT2A FISH result. Case 3 had trisomy 8 and a t(11;15)(q23;q21), an atypical KMT2A rearrangement by FISH studies, and a focal deletion of 15q with a breakpoint within the USP8 gene by chromosomal microarray. Mate pair sequencing was performed on all three cases and identified a KMT2A‐USP2 rearrangement (cases 1 and 2) or a KMT2A‐USP8 rearrangement (case 3). These recently characterized KMT2A fusions have been described exclusively in infant and pediatric leukemia cases where the incidence varies vary according to leukemia subtype, are considered high‐risk, with a high incidence of central nervous system involvement, poor response to initial prednisone treatment, and poor event free survival. Additionally, approximately half of cases are unable to be resolved using standard cytogenetic approaches and are likely under recognized. Therefore, targeted molecular approaches are suggested in genetically unresolved infant leukemia cases to characterize these prognostically relevant clones.