Project description:Standardized variant curation is essential for clinical care recommendations for patients with inherited disorders. Clinical Genome Resource (ClinGen) variant curation expert panels are developing disease-associated gene specifications using the 2015 American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP) guidelines to reduce curation discrepancies. The ClinGen Myeloid Malignancy Variant Curation Expert Panel (MM-VCEP) was created collaboratively between the American Society of Hematology and ClinGen to perform gene- and disease-specific modifications for inherited myeloid malignancies. The MM-VCEP began optimizing ACMG/AMP rules for RUNX1 because many germline variants have been described in patients with familial platelet disorder with a predisposition to acute myeloid leukemia, characterized by thrombocytopenia, platelet functional/ultrastructural defects, and a predisposition to hematologic malignancies. The 28 ACMG/AMP codes were tailored for RUNX1 variants by modifying gene/disease specifications, incorporating strength adjustments of existing rules, or both. Key specifications included calculation of minor allele frequency thresholds, formulating a semi-quantitative approach to counting multiple independent variant occurrences, identifying functional domains and mutational hotspots, establishing functional assay thresholds, and characterizing phenotype-specific guidelines. Preliminary rules were tested by using a pilot set of 52 variants; among these, 50 were previously classified as benign/likely benign, pathogenic/likely pathogenic, variant of unknown significance (VUS), or conflicting interpretations (CONF) in ClinVar. The application of RUNX1-specific criteria resulted in a reduction in CONF and VUS variants by 33%, emphasizing the benefit of gene-specific criteria and sharing internal laboratory data.
Project description:Germline pathogenic variants in TP53 are associated with Li-Fraumeni syndrome, a cancer predisposition disorder inherited in an autosomal dominant pattern associated with a high risk of malignancy, including early-onset breast cancers, sarcomas, adrenocortical carcinomas, and brain tumors. Intense cancer surveillance for individuals with TP53 germline pathogenic variants is associated with reduced cancer-related mortality. Accurate and consistent classification of germline variants across clinical and research laboratories is important to ensure appropriate cancer surveillance recommendations. Here, we describe the work performed by the Clinical Genome Resource TP53 Variant Curation Expert Panel (ClinGen TP53 VCEP) focused on specifying the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines for germline variant classification to the TP53 gene. Specifications were developed for 20 ACMG/AMP criteria, while nine were deemed not applicable. The original strength level for the 10 criteria was also adjusted due to current evidence. Use of TP53-specific guidelines and sharing of clinical data among experts and clinical laboratories led to a decrease in variants of uncertain significance from 28% to 12% compared with the original guidelines. The ClinGen TP53 VCEP recommends the use of these TP53-specific ACMG/AMP guidelines as the standard strategy for TP53 germline variant classification.
Project description:Genomic profiles of tumors are often unique and represent characteristic mutational signatures defined by DNA damage or DNA repair response processes. The tumor-derived somatic information has been widely used in therapeutic applications, but it is grossly underutilized in the assessment of germline genetic variants. Here, we present a comprehensive approach for evaluating the pathogenicity of germline variants in cancer using an integrated interpretation of somatic and germline genomic data. We have previously demonstrated the utility of this integrated approach in the reassessment of pathogenic germline variants in selected cancer patients with unexpected or non-syndromic phenotypes. The application of this approach is presented in the assessment of rare variants of uncertain significance (VUS) in Lynch-related colon cancer, hereditary paraganglioma-pheochromocytoma syndrome, and Li-Fraumeni syndrome. Using this integrated method, germline VUS in PMS2, MSH6, SDHC, SHDA, and TP53 were assessed in 16 cancer patients after genetic evaluation. Comprehensive clinical criteria, somatic signature profiles, and tumor immunohistochemistry were used to re-classify VUS by upgrading or downgrading the variants to likely or unlikely actionable categories, respectively. Going forward, collation of such germline variants and creation of cross-institutional knowledgebase datasets that include integrated somatic and germline data will be crucial for the assessment of these variants in a larger cancer cohort.
Project description:Clinical variant interpretation is highly dependent on the choice of reference transcript. Although the longest transcript has traditionally been chosen as the reference, APPRIS principal and MANE Select transcripts, biologically supported reference sequences, are now available. In this study, we show that MANE Select and APPRIS principal transcripts are the best reference transcripts for clinical variation. APPRIS principal and MANE Select transcripts capture almost all ClinVar pathogenic variants, and they are particularly powerful over the 94% of coding genes in which they agree. We find that a vanishingly small number of ClinVar pathogenic variants affect alternative protein products. Alternative isoforms that are likely to be clinically relevant can be predicted using TRIFID scores, the highest scoring alternative transcripts are almost 700 times more likely to house pathogenic variants. We believe that APPRIS, MANE and TRIFID are essential tools for clinical variant interpretation.
Project description:RUNX1 transcription factor regulates normal and malignant hematopoiesis. Somatic or germline mutant RUNX1 (mtRUNX1) is associated with poorer outcome in acute myeloid leukemia (AML). Knockdown or inhibition of RUNX1 induced more apoptosis of AML expressing mtRUNX1 versus wild-type RUNX1 and improved survival of mice engrafted with mtRUNX1-expressing AML. CRISPR/Cas9-mediated editing-out of RUNX1 enhancer (eR1) within its intragenic super-enhancer, or BET protein BRD4 depletion by short hairpin RNA, repressed RUNX1, inhibited cell growth, and induced cell lethality in AML cells expressing mtRUNX1. Moreover, treatment with BET protein inhibitor or degrader (BET-proteolysis targeting chimera) repressed RUNX1 and its targets, inducing apoptosis and improving survival of mice engrafted with AML expressing mtRUNX1. Library of Integrated Network-based Cellular Signatures 1000-connectivity mapping data sets queried with messenger RNA signature of RUNX1 knockdown identified novel expression-mimickers (EMs), which repressed RUNX1 and exerted in vitro and in vivo efficacy against AML cells expressing mtRUNX1. In addition, the EMs cinobufagin, anisomycin, and narciclasine induced more lethality in hematopoietic progenitor cells (HPCs) expressing germline mtRUNX1 from patients with AML compared with HPCs from patients with familial platelet disorder (FPD), or normal untransformed HPCs. These findings highlight novel therapeutic agents for AML expressing somatic or germline mtRUNX1.
Project description:Familial platelet disorder with associated myeloid malignancies (RUNX1-familial platelet disorder [RUNX1-FPD]) is caused by heterozygous pathogenic germline variants of RUNX1. In the present study, we evaluate the applicability of transactivation assays to investigate RUNX1 variants in different regions of the protein. We studied 11 variants to independently validate transactivation assays supporting variant classification following the ClinGen Myeloid Malignancies Variant Curation Expert Panel guidelines. Variant classification is key for the translation of genetic findings. We showed that new assays need to be developed to assess C-terminal RUNX1 variants. Two variants of uncertain significance (VUS) were reclassified to likely pathogenic. Additionally, our analyses supported the (likely) pathogenic classification of 2 other variants. We demonstrated functionality of 4 VUS, but reclassification to (likely) benign was challenging and suggested the need for reevaluating current classification guidelines. Finally, clinical utility of our assays was illustrated in the context of 7 families. Our data confirmed RUNX1-FPD suspicion in 3 families with RUNX1-FPD-specific family history, whereas for 3 variants identified in RUNX1-FPD-nonspecific families, no functional defect was detected. Applying functional assays to support RUNX1 variant classification can be essential for adequate care of index patients and their relatives at risk. It facilitates translation of genetic data into personalized medicine.
Project description:The clinical interpretation of genetic variants has come to rely heavily on reference population databases such as the Exome Aggregation Consortium (ExAC) database. Pathogenic variants in genes associated with severe, pediatric-onset, highly penetrant, autosomal dominant conditions are assumed to be absent or rare in these databases. Exome sequencing of a 6-year-old female patient with seizures, developmental delay, dysmorphic features, and failure to thrive identified an ASXL1 variant previously reported as causative of Bohring-Opitz syndrome (BOS). Surprisingly, the variant was observed seven times in the ExAC database, presumably in individuals without BOS. Although the BOS phenotype fit, the presence of the variant in reference population databases introduced ambiguity in result interpretation. Review of the literature revealed that acquired somatic mosaicism of ASXL1 variants (including pathogenic variants) during hematopoietic clonal expansion can occur with aging in healthy individuals. We examined all ASXL1 truncating variants in the ExAC database and determined most are likely somatic. Failure to consider somatic mosaicism may lead to the inaccurate assumption that conditions like BOS have reduced penetrance, or the misclassification of potentially pathogenic variants.
Project description:Pathogenicity predictors are computational tools that classify genetic variants as benign or pathogenic; this is currently a major challenge in genomic medicine. With more than fifty such predictors available, selecting the most suitable tool for clinical applications like genetic screening, molecular diagnostics, and companion diagnostics has become increasingly challenging. To address this issue, we have developed a cost-based framework that naturally considers the various components of the problem. This framework encodes clinical scenarios using a minimal set of parameters and treats pathogenicity predictors as rejection classifiers, a common practice in clinical applications where low-confidence predictions are routinely rejected. We illustrate our approach in four examples where we compare different numbers of pathogenicity predictors for missense variants. Our results show that no single predictor is optimal for all clinical scenarios and that considering rejection yields a different perspective on classifiers.
Project description:The broad use of next-generation sequencing and microarray platforms in research and clinical laboratories has led to an increasing appreciation of the role of germline mutations in genes involved in hematopoiesis and lineage differentiation that contribute to myeloid neoplasms. Despite implementation of the American College of Medical Genetics and Genomics and Association for Molecular Pathology 2015 guidelines for sequence variant interpretation, the number of variants deposited in ClinVar, a genomic repository of genotype and phenotype data, and classified as having uncertain significance or being discordantly classified among clinical laboratories remains elevated and contributes to indeterminate or inconsistent patient care. In 2018, the American Society of Hematology and the Clinical Genome Resource co-sponsored the Myeloid Malignancy Variant Curation Expert Panel to develop rules for classifying gene variants associated with germline predisposition to myeloid neoplasia. Herein, we demonstrate application of our rules developed for the RUNX1 gene to variants in six examples to show how we would classify them within the proposed framework.