Cancer Genetics最新文献

{"title":"31. A cross-consortia initiative for aligning the definitions and descriptions of gene fusions","authors":"Alex Wagner ,&nbsp;Reece Hart ,&nbsp;Johan den Dunnen ,&nbsp;Elspeth Bruford ,&nbsp;Ros Hastings ,&nbsp;Marina DiStefano ,&nbsp;Myungshin Kim ,&nbsp;Sarah Moore ,&nbsp;Gordana Raca","doi":"10.1016/j.cancergen.2024.08.033","DOIUrl":"10.1016/j.cancergen.2024.08.033","url":null,"abstract":"<div><div>Despite the well-established role of gene fusions in oncogenic processes, current practices for characterizing and annotating gene fusion events in the clinical setting and in biomedical literature are inconsistent. Consequently, evidence-based interpretation of functional and clinical significance of fusion variants requires laborious and time-consuming gathering and review of putative evidence. Differences between community standards inhibit the uniform communication of fusion events as well as the interoperability of tools, resources, and pipelines, ultimately impeding data sharing and downstream utility.</div><div>To address these challenges, a cross-consortia initiative between the Variant Interpretation for Cancer Consortium (VICC), CGC, ClinGen Somatic, and AMP was formed to develop a unified, standard nomenclature for representing the product of gene fusions (fusions.cancervariants.org). Invested participants across academic, government, and industry sectors engaged with these challenges to propose solutions via participation in community surveys and discussions to define and develop a standard for this diverse class of alterations. Our recent efforts to align these pre-release recommendations for fusion representation with the recommendations of the HGNC, ISCN, and HGVS nomenclature committees have resulted in consensus definitions and interoperable nomenclature systems for the description of gene fusions.</div><div>In January 2024, the first major release (21.0.0) of the HGVS nomenclature since 2020 includes the results of this work, which is also reflected in the cross-consortia recommendations. We discuss the vocabulary and nomenclature alignment between these related and cross-referenced standards, and provide recommendations for characterization and representation of gene fusions across these systems.</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Page S10"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"70. Acute myeloid leukemia with a novel AKAP9::PDGFRA fusion transformed from essential thrombocythemia","authors":"Yavuz Sahin,&nbsp;Jianming Pei,&nbsp;Don A. Baldwin,&nbsp;Nashwa Mansoor,&nbsp;Lori Koslosky,&nbsp;Peter Abdelmessieh,&nbsp;Y. Lynn Wang,&nbsp;Reza Nejati,&nbsp;Joseph Testa","doi":"10.1016/j.cancergen.2024.08.072","DOIUrl":"10.1016/j.cancergen.2024.08.072","url":null,"abstract":"<div><div>Acute myeloid leukemia (AML) is a heterogeneous hematological malignancy associated with various combinations of gene mutations, epigenetic abnormalities, and chromosome rearrangement-related gene fusions. Despite the significant degree of heterogeneity in its pathogenesis, many gene fusions and point mutations are recurrent in AML and have been employed in risk stratification over the last several decades. Gene fusions have long been recognized for understanding tumorigenesis and their proven roles in clinical diagnosis and targeted therapies. Advances in DNA sequencing technologies and computational biology have contributed significantly to the detection of known fusion genes as well as for the discovery of novel ones. Several recurring gene fusions in AML have been linked to prognosis, treatment response, and disease progression. Here, we present a case with a long history of essential thrombocythemia and hallmark CALR mutation transforming to AML characterized by a previously unreported <em>AKAP9::PDGFRA</em> fusion gene. We propose mechanisms by which this fusion may contribute to the pathogenesis of AML and its potential as a molecular target for tyrosine kinase inhibitors.</div><div>Journal: Leukemia Research Reports</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Pages S22-S23"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"37. The clinical utility of the TSO500 clinically-verified test in patients with solid tumors: The Mayo Clinic experience","authors":"Hussam Al Kateb,&nbsp;Lisa Mullineaux,&nbsp;Adam McClung,&nbsp;Amber Pryzbylski,&nbsp;Claire Teigen,&nbsp;Beth Pitel,&nbsp;Kevin Halling","doi":"10.1016/j.cancergen.2024.08.039","DOIUrl":"10.1016/j.cancergen.2024.08.039","url":null,"abstract":"<div><div>Clinical Laboratories reimbursement for large cancer panels has been challenging with many health care payers arguing about the clinical utility of such panels. We sought to investigate the clinical utility of the TSO500 kit in patients with solid tumors (ST) by determining its ability to detect a target for an FDA-approved drug in tumor type (FDA-in-TT), and in other tumor type (FDA-in-OTT).</div><div>The TSO500 kit which is commercially offered by Illumina company along with an analysis pipeline has been clinically verified in our laboratory and has been offered since 2021 for clinical care. A total of 1194 cases representing over 25 solid tumor types that were tested on the TSO500 platform were included in the study.</div><div>The top 3 indications for testing were lung cancer (35.6%), unknown primary (UNP) (14.5%), and other tumor types (12.5%). FDA-in-TT and FDA-in-OTT variants were identified in 531/1194(44.5%), and (257/1194)(15.4%), total (788/1194)(66%) cases, respectively. Immunotherapy markers including microsatellite instability (MSI-H) and/or high tumor mutation burden (TMB-H) were detected in 324 cases representing 60% of cases with FDA-in-TT and FDA-in-OTT, and 30% of all tested cases, respectively. Interestingly, 43/172(25%) of UKP cases had FDA-approved-drug, of which 35/43(81%) had TMB-H.</div><div>The detection of an FDA-in-TT and FDA-in-OTT target in 66% of patients, 60% of whom had TMB-H, a biomarker for FDA-approved immunotherapy drugs that requires interrogating over one megabase of the genome for accurate detection, provides strong evidence for the clinical utility of a large panels testing like the TSO500 in patients with solid tumors.</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Page S12"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"11. Developing a robust bioinformatics workflow to support personalized neoantigen vaccine clinical trials","authors":"Kartik Singhal ,&nbsp;Susanna Kiwala ,&nbsp;Peter S. Goedegebuure ,&nbsp;Christopher Miller ,&nbsp;Evelyn Schmidt ,&nbsp;Huiming Xia ,&nbsp;My Hoang ,&nbsp;Mariam Khanfar ,&nbsp;Shelly O'Laughlin ,&nbsp;Nancy Myers ,&nbsp;Tammi Vickery ,&nbsp;Kelsy C. Cotto ,&nbsp;Sherri Davies ,&nbsp;Feiyu Du ,&nbsp;Thomas B. Mooney ,&nbsp;Gue Su Chang ,&nbsp;Jasreet Hundal ,&nbsp;John Garza ,&nbsp;Mike D. McLellan ,&nbsp;Joshua McMichael ,&nbsp;Malachi Griffith","doi":"10.1016/j.cancergen.2024.08.013","DOIUrl":"10.1016/j.cancergen.2024.08.013","url":null,"abstract":"<div><div>Personalized cancer vaccines (PCVs) leverage immunogenomics strategies to combat cancer. Somatic mutations in tumor cells generate neoantigens that may get presented on the tumor cell's surface by MHC molecules. Immunotherapies target neoantigens to stimulate tumor-specific immune responses. Our bioinformatics workflow has designed vaccines for over 170 patients across 11 of the 180 neoantigen vaccine trials on clinicaltrials.gov.</div><div>Despite the rise in PCV-related interventions, gaps in established protocols addressing the complexities associated with the design of PCVs still remain. Here, we summarize our bioinformatics pipeline and describe measures taken to ensure robust support for clinical trials at Washington University. Our Google Cloud immunotherapy pipeline (open MIT license) to predict neoantigen epitopes is implemented in Workflow Definition Language and containerized using Docker to ensure portability and reliability. The pVACtools software suite (pvactools.org) that carries out neoantigen identification and prioritization, is developed and updated following industry best practices including version control (Git), formal code review, automated unit and integration tests, and benchmark tests. The final steps of the bioinformatics workflow generate files recording the analysis parameters and QC results tailored to the FDA's requests. Candidates generated by the pipeline are reviewed at an Immunogenomics Tumor Board using the pVACview tool. Prioritized candidates undergo a rigorous examination of data QC metrics, variant support at genomic and transcriptomic levels, MHC binding prediction algorithms, and HLA allele concordance between the clinical data and in-silico prediction tools. Finally, a long-peptide order form generated by the pipeline is sent to the vaccine manufacturer for synthesis.</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Page S4"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"72. What's under VarCat's hat: Modeling variant oncogenicity classifications with GA4GH Standards","authors":"Kathryn Stahl,&nbsp;Wesley Goar,&nbsp;Kori Kuzma,&nbsp;Alex Wagner","doi":"10.1016/j.cancergen.2024.08.074","DOIUrl":"10.1016/j.cancergen.2024.08.074","url":null,"abstract":"<div><div>The Variation Categorizer (VarCat) is a tool for classifying variant oncogenicity for variant-disease pairings in a clinical laboratory workflow. VarCat implements the ClinGen/CGC/VICC oncogenicity guidelines to assist in the classification of a variant's capability for driving cancer formation and growth. VarCat provides an intuitive interface for structured data sharing and produces classification assessments compliant with genomic knowledge standards specified by the Global Alliance for Genomics and Health (GA4GH).</div><div>Here, we present the models, structures, and capabilities provided by VarCat's API and demonstrate its ability to create standardized assessments. VarCat leverages harmonized data from several genomic knowledge sources collated by the VICC MetaKB service. VarCat ensures comprehensive analysis by incorporating standardized gene, variant, therapeutic, disease, and evidence data, and it is driving the development of GA4GH genomic knowledge formats for oncogenicity data. We also describe the suite of normalization microservices used by MetaKB and VarCat to harmonize genomic knowledge concepts. We illustrate how VarCat reduces barriers to interoperable variant-associated evidence through the adoption of the GA4GH Variation Representation Specification (VRS). We also present standardized evidence data using the AMP/ASCO/CAP guidelines for clinical actionability. Overall, our work illustrates how GA4GH Genomic Knowledge Standards drive data interoperability and successful knowledge exchange, ultimately enhancing genetic disease comprehension and advancing patient care.</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Page S23"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"12. Contextualizing clinical significance using FDA label supplemented DGI data","authors":"Matthew Cannon ,&nbsp;James Stevenson ,&nbsp;Kathryn Stahl ,&nbsp;Rohit Basu ,&nbsp;Adam Coffman ,&nbsp;Susanna Kiwala ,&nbsp;Joshua McMichael ,&nbsp;Elaine Mardis ,&nbsp;Obi Griffith ,&nbsp;Malachi Griffith ,&nbsp;Alex Wagner","doi":"10.1016/j.cancergen.2024.08.014","DOIUrl":"10.1016/j.cancergen.2024.08.014","url":null,"abstract":"<div><div>The drug-gene interaction database (DGIdb) is a resource that aggregates interaction data from over 40 different resources into one platform with the primary goal of making the druggable genome accessible to clinicians and researchers. By providing a public, computationally accessible database, the DGIdb enables therapeutic insights through broad aggregation of DGI data.</div><div>As part of our aggregation process, DGIdb preserves data regarding interaction types, directionality, and other attributes that enable filtering or biochemical insight. However, source data are often incomplete and may not contain the original physiological context of the interaction. Without this context, the therapeutic relevance of an interaction may be compromised or lost. In this report, we address these missing data and extract therapeutic context from free-text sources. We apply existing large language models (LLMs) that have been fine-tuned on additional medical corpuses to tag and extract indications, cancer types, and relevant pharmacogenomics from free-text, FDA approved labels. We are then able to utilize our in-house normalization services to link extracted data back to formally grouped concepts.</div><div>In a preliminary test set of 355 FDA labels, we were able to normalize 59.4%, 49.8%, and 49.1% of extracted chemical, disease, and genetic entities back to harmonized concepts. Extracting this data allows us to supplement our existing interactions with relevant context that may inform the therapeutic relevance of a particular interaction. Inclusion of these data will be particularly invaluable for variant interpretation pipelines where mutational status can lead to the identification of a lifesaving therapeutic and a positive patient outcome.</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Pages S4-S5"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"30. Current next generation sequencing reporting practices: A GOAL Consortium report","authors":"Celeste Eno ,&nbsp;Rama Sompallae ,&nbsp;T. Niroshi Senaratne","doi":"10.1016/j.cancergen.2024.08.032","DOIUrl":"10.1016/j.cancergen.2024.08.032","url":null,"abstract":"<div><div>Molecular testing by next generation sequencing (NGS) panels are widely used for oncology specimens; however, the reporting of the results vary greatly across institutions. A 70-question survey was sent to member laboratories in the Genomics Organization for Academic Laboratories (GOAL) consortium to assess current reporting practices to assess the potential for standardization. GOAL is a non-profit organization with aims of cross-institutional collaborations, including shared assay content and interpretative frameworks, to allow for academic laboratory success. Each laboratory had the opportunity to fill out the survey for hematological and solid tumor-based panels or a combined survey for both types of tumors. A total of 28 surveys were received from 21 academic tertiary-care laboratories regarding NGS reporting practices. Only a few practices differed significantly between heme and solid tumor panels, including repeat testing. Most notably, the survey respondents noted the time and review process for testing was formidable, including review of previous results, care in reporting potential germline findings, and integrating other ancillary testing. Through these efforts, GOAL seeks to bridge the gap in result reporting, ultimately improving consistency and accuracy of NGS-based molecular testing for cancer. We anticipate the results of this study will help serve as a benchmark for clinical laboratories looking to compare practices with their peers and reveal potential areas for standardization or improvement of clinical reporting.</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Page S10"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"35. Integrated comprehensive genomic profiling of meningiomas: A single institutional study","authors":"Mohana Priya Jayavel,&nbsp;Ha Nguyen,&nbsp;Madina Sukhanova,&nbsp;Lucas Santana dos Santos,&nbsp;Behtash Nezami,&nbsp;Juehua Gao,&nbsp;Erica Vormittag-Nocito,&nbsp;Lawrence Jennings,&nbsp;Xinyan Lu","doi":"10.1016/j.cancergen.2024.08.037","DOIUrl":"10.1016/j.cancergen.2024.08.037","url":null,"abstract":"<div><div>Meningioma is the most common central nervous system tumor and understudied because of its benign nature. High-grade meningiomas often show poorer outcome and enriched with high-risk copy-number-aberrations (CNAs) including losses/segmental-losses of chromosomes 1p, 3p, 4p/q, 6p/q, 10p/q, 14q, 18p/q and 19p/q, CDKN2A/B homozygous-deletion (CDKN2A/B-homo) and TERT promoter-mutation (TERTp) detected by comprehensive genomic profiling (CGP) including SNP-microarray, next generation sequencing (NGS) and DNA-methylation. In this study, we performed CGP on a large series of meningioma.</div><div>We identified 122 (45.2%) cases with high-risk CNAs in 270 cases assessed, including 33 WHO-grade-I, 67 WHO-grade-II and 22 WHO-grade-III. Fifty-one (41.8%) cases had hypodiploidy characterized by losses of 22, 14, 10, X/Y, 6 and 8; Eighteen (14.8%) showed polyploidy with relative losses of 1p, 14, 18, 6 and 10. In 53 (43.4%) cases with near-diploidy, half showed complex CNAs with losses/segmental-losses involving 1p, 3p, 19p,14q and 6q. Five cases (4.1%) showed CDKN2A/B-homo. NGS performed in 30 cases revealed mutations in NF2 (n=20), ARID1A (n=7), MSH6 (n=4). Seven (6.6%, 7/106) had TERTp mutation. Methylation profiling matched classifier for meningioma in 92% (79/86) of cases tested. CGP upgraded 58% WHO-grade-I and 67.2% WHO-grade-II tumors to WHO-grade-II and III, respectively. Although follow-up data is limited, 51 patients (41.8%) had tumor recurrence.</div><div>Our study showed that meningiomas are enriched by high-risk CNAs even in low-grade tumors, less frequent TERTp mutation or CDKN2A/B-homo. CGP is of clinical importance for tumor molecular characterizations. CGP should be utilized clinically and integrated in future WHO classifications for tumor grading and risk stratification.</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Page S11"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"55. Advancing bladder carcinoma diagnosis: The innovative potential of the BCDx multi-omics approach","authors":"Thakshila Habarakada Liyanage,&nbsp;Asel Habarakada Liyanage","doi":"10.1016/j.cancergen.2024.08.057","DOIUrl":"10.1016/j.cancergen.2024.08.057","url":null,"abstract":"<div><div>The use of multi-omic biomarkers in liquid biopsies is emerging as a promising method for enhancing disease detection accuracy. However, it faces significant challenges, such as the complexity of integrating and interpreting data from various omic layers, which is time-consuming, low-throughput, and costly. Additionally, there is currently no simple instrument capable of detecting all the omics simultaneously. Early Is Good (EIG) has developed the Multi-Omic Integration Platform (MIP) to tackle these challenges in early disease detection. MIP can detect DNA, RNA, and proteins simultaneously using a standard plate reader, employing localized surface plasmon resonance (LSPR) of gold nanoparticles to enhance the bioluminescence resonance energy transfer (BRET) readout signal.</div><div>The novel MIP assay technology is applied to early bladder cancer recurrence monitoring using a multi-omic biomarker panel that includes miRNA, mRNA, lncRNA, and proteins. Current methods for identifying bladder cancer (BC) involve cystoscopy and urinary cytology. Cystoscopy, with 97% sensitivity for high-grade tumors, is invasive, operator-dependent, and costly. It often misses small or carcinoma in situ tumors, which can progress to muscle-invasive bladder cancer (MIBC) in about half of the patients. It also causes side effects like dysuria (50%), hematuria (19%), and urinary tract infections (3%), leading to discomfort, anxiety, and embarrassment. Urinary cytology, with 80-90% sensitivity and 98-100% specificity for high-grade tumors, struggles with low sensitivity (4-31%) for low-grade tumors and has a higher rate of false positives. This highlights the need for innovative approaches like the MIP, which offers non-invasive, highly sensitive, and comprehensive detection capabilities, potentially transforming the clinical management of bladder cancer. MIP has shown 100% sensitivity and 100% NPV for bladder cancer recurrence monitoring by combining the multi-omic biomarkers.</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Page S18"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142322857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"46. Clinical SNP-array adds value to diagnosis and surveillance of bone marrow failure syndromes","authors":"Lucilla Pizzo ,&nbsp;Jian Zhao ,&nbsp;Akiko Shimamura ,&nbsp;Sara Lewis ,&nbsp;Marcin Wlodarski ,&nbsp;Bo Hong ,&nbsp;Erica Andersen","doi":"10.1016/j.cancergen.2024.08.048","DOIUrl":"10.1016/j.cancergen.2024.08.048","url":null,"abstract":"<div><div>Cytogenomic SNP microarray (SNP-A) utilization for diagnosis and monitoring of bone marrow failure syndromes (BMFS) is increasing. Understanding the biology of these heterogeneous diseases is required to appropriately identify, interpret, and track prognostically significant clones, some of which may represent revertant somatic genetic rescue (SGR) events. We reviewed SNP-A findings from our encounter of over 100 BMFS cases tested at our institution. Abnormal results were reported in 30 cases, including nine aplastic anemia (AA, 30%), eleven Shwachman-Diamond syndrome (SDS, 37%), six SAMD9/SAMD9L-related syndrome (20%), and four Diamond-Blackfan anemia (DBA, 13%) cases. In 15 (50%) cases, the SNP-A profile was consistent with SGR and acquired correction of the disease-causing variant. Isolated CN-LOH of the chromosome containing the disease-causing gene was observed in 12 (40%) cases, including CN-LOH 7q in two individuals with SDS (SBDS gene) and three individuals with SAMD9/SAMD9L-associated syndromes, and CN-LOH 2p and 19q in two individuals with RPS7 and RPS19-associated DBA, respectively. SGR-associated CNVs included isochromosome 7q (SBDS) and 20q deletion (EIF6 gene) in three cases of SDS. Malignant transformation SNP-A findings were observed in 4/30 (13%) cases, including CN-LOH 17p with TP53 Tier 1 variant in an SDS case and monosomy 7 in three cases of SAMD9/SAMD9L-related syndromes. Concurrent review of cytogenetic/FISH, NGS, and/or germline BMFS results, where available; identification of low-level, complex and/or coexisting clones; and accurate clonal estimation for sequential tracking are essential, and add value to clinical management. Our results emphasize the value of SNP-A in the diagnosis, prognosis, and monitoring of BMFS.</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Page S15"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}