Pub Date : 2024-08-01DOI: 10.1016/j.cancergen.2024.08.027
Cameron Grisdale , Erin Pleasance , Connor Frey , Caralyn Reisle , Laura Williamson , Jing Xu , Veronika Csizmok , John Dupuis , Kathleen Wee , Yaoqing Shen , Zakhar Krekhno , Melika Bonakdar , Greg Taylor , Asmita Jain , Melissa McConechy , Kilannin Krysiak , Jason Saliba , Arpad Danos , Adam Coffman , Susanna Kiwala , Steven Jones
Precision oncology relies on advanced sequencing technologies to guide treatment strategies, yet effectively translating genomic data into actionable insights remains a critical challenge. The Personalized OncoGenomics (POG) program at BC Cancer utilizes whole genome and transcriptome analysis (WGTA), providing a comprehensive view of the molecular biology of advanced cancer patient tumours, with over 1200 patients enrolled to-date. This analysis relies on curated clinical knowledgebases linking cancer variants and their clinical relevance, but the breadth and utility of these can be limited by access restrictions or missing information. CIViC (Clinical Interpretation of Variants in Cancer; civicdb.org) is an open-access, expert moderated, crowd-sourced knowledgebase of clinically relevant cancer variants that aims to address these limitations and is one of several sources used for variant interpretation in POG. Based on a retrospective cohort of POG cases, we evaluated the knowledgebase coverage of genes and variants involved in treatment recommendations from the molecular tumour board (MTB) as well as those suggested by genome analysts. We also considered the impact of quality of evidence on MTB recommendations and patient treatments. We found more than 95% of patients had an alteration considered clinically actionable by the MTB, demonstrating the benefit of WGTA paired with open-source automated variant matching and reporting software. Clinical interpretations derived from CIViC represented nearly 50% of therapeutic evidence reported at the MTB, emphasizing the role of open-access knowledge in precision oncology. Additionally, we identified genome signatures as a critical area with clinical implications requiring further curation efforts and evidence model development.
精准肿瘤学依赖于先进的测序技术来指导治疗策略,但有效地将基因组数据转化为可操作的见解仍是一项严峻的挑战。不列颠哥伦比亚癌症中心的个性化肿瘤基因组学(POG)计划利用全基因组和转录组分析(WGTA),提供晚期癌症患者肿瘤分子生物学的全面视图,迄今已有超过1200名患者加入该计划。这种分析依赖于将癌症变异及其临床相关性联系起来的临床知识库,但这些知识库的广度和实用性可能会受到访问限制或信息缺失的限制。CIViC(Clinical Interpretation of Variants in Cancer; civicdb.org,癌症变异临床解读;civicdb.org)是一个开放存取、专家主持、群众参与的临床相关癌症变异知识库,旨在解决这些局限性,是用于 POG 变异解读的几个来源之一。基于一组回顾性 POG 病例,我们评估了分子肿瘤委员会(MTB)治疗建议中涉及的基因和变异的知识库覆盖范围,以及基因组分析师提出的建议。我们还考虑了证据质量对 MTB 建议和患者治疗的影响。我们发现 95% 以上的患者有 MTB 认为在临床上可采取行动的变异,这证明了 WGTA 与开源自动变异匹配和报告软件搭配使用的好处。CIViC得出的临床解释占MTB报告的治疗证据的近50%,强调了开放获取知识在精准肿瘤学中的作用。此外,我们还发现基因组特征是一个具有临床影响的关键领域,需要进一步的整理工作和证据模型的开发。
{"title":"25. Enhancing precision oncology: The value of open-source knowledgebase integration","authors":"Cameron Grisdale , Erin Pleasance , Connor Frey , Caralyn Reisle , Laura Williamson , Jing Xu , Veronika Csizmok , John Dupuis , Kathleen Wee , Yaoqing Shen , Zakhar Krekhno , Melika Bonakdar , Greg Taylor , Asmita Jain , Melissa McConechy , Kilannin Krysiak , Jason Saliba , Arpad Danos , Adam Coffman , Susanna Kiwala , Steven Jones","doi":"10.1016/j.cancergen.2024.08.027","DOIUrl":"10.1016/j.cancergen.2024.08.027","url":null,"abstract":"<div><div>Precision oncology relies on advanced sequencing technologies to guide treatment strategies, yet effectively translating genomic data into actionable insights remains a critical challenge. The Personalized OncoGenomics (POG) program at BC Cancer utilizes whole genome and transcriptome analysis (WGTA), providing a comprehensive view of the molecular biology of advanced cancer patient tumours, with over 1200 patients enrolled to-date. This analysis relies on curated clinical knowledgebases linking cancer variants and their clinical relevance, but the breadth and utility of these can be limited by access restrictions or missing information. CIViC (Clinical Interpretation of Variants in Cancer; civicdb.org) is an open-access, expert moderated, crowd-sourced knowledgebase of clinically relevant cancer variants that aims to address these limitations and is one of several sources used for variant interpretation in POG. Based on a retrospective cohort of POG cases, we evaluated the knowledgebase coverage of genes and variants involved in treatment recommendations from the molecular tumour board (MTB) as well as those suggested by genome analysts. We also considered the impact of quality of evidence on MTB recommendations and patient treatments. We found more than 95% of patients had an alteration considered clinically actionable by the MTB, demonstrating the benefit of WGTA paired with open-source automated variant matching and reporting software. Clinical interpretations derived from CIViC represented nearly 50% of therapeutic evidence reported at the MTB, emphasizing the role of open-access knowledge in precision oncology. Additionally, we identified genome signatures as a critical area with clinical implications requiring further curation efforts and evidence model development.</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Page S8"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323389","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}
Chronic myeloid leukemia (CML) with p190 BCR::ABL1 transcript is rare but when present, it is usually associated with increased monocytes. IKZF1, a gene that encodes the lymphoid transcription factor IKAROS, is commonly deleted in B-lymphoblastic leukemia (B-ALL). Here, we describe a 66-year-old male with 2-weeks history of myalgias, night sweats, malaise, and fatigue, and white blood cells of 177K with 90% circulating blasts. At our institute, bone marrow examination showed ∼56% B-lymphoblasts, ∼3% myeloblasts, and increased monocytes (21%). Aberrant CD13 and CD25 expression was noted, which can be seen in B-ALL with BCR::ABL1 fusion (BAF). FISH leukemia panels detected 2-3 BAF, in 94.5% and 4% of the cells, consistent with an extra Ph+, and loss of IKZF1 locus in 91% of cells. RT-PCR showed BAF p190 breakpoint. The initial diagnosis was a B-ALL with BAF but given the presence of increased monocytes and left-shifted granulocytes, a preceding CML could not be ruled out. Subsequently, an abnormal karyotype with two clones was detected; one with an interstitial deletion of 7p leading to IKZF1 deletion, and t(9;22). Clone two, exhibited an extra Ph+, plus t(9;22); both clones were consistent with the proportion of abnormal cells detected by FISH 46,XY,del(7)(p15p11.2),t(9;22)(q34;q11.2)[19]/47,XY,t(9;22),+der(22)t(9;22)[1]. The immunophenotype obtained by flow cytometry/immunohistochemistry and RT-PCR was supportive of B-ALL. The morphologic picture along with the correlation of the karyotype, which detected two distinct cell populations, supported by FISH IKZF1/ BCR::ABL1 results led to a diagnosis of a preceding CML presenting in lymphoid blast crisis. Patient is undergoing initial
{"title":"67. An undiagnosed chronic myeloid leukemia (CML) with p190 BCR::ABL1 transcript, an extra Philadelphia chromosome, and IKARO","authors":"Fabiola Quintero-Rivera, Sumayya Aslam, Lynn Yang, Johnson Tso, Melissa Lyon, Katherine Dang, Ying Zhang, Kiran Naqvi, Sherif Rezk","doi":"10.1016/j.cancergen.2024.08.069","DOIUrl":"10.1016/j.cancergen.2024.08.069","url":null,"abstract":"<div><div>Chronic myeloid leukemia (CML) with p190 <em>BCR::ABL1</em> transcript is rare but when present, it is usually associated with increased monocytes. <em>IKZF1</em>, a gene that encodes the lymphoid transcription factor IKAROS, is commonly deleted in B-lymphoblastic leukemia (B-ALL). Here, we describe a 66-year-old male with 2-weeks history of myalgias, night sweats, malaise, and fatigue, and white blood cells of 177K with 90% circulating blasts. At our institute, bone marrow examination showed ∼56% B-lymphoblasts, ∼3% myeloblasts, and increased monocytes (21%). Aberrant CD13 and CD25 expression was noted, which can be seen in B-ALL with <em>BCR::ABL1</em> fusion (BAF). FISH leukemia panels detected 2-3 BAF, in 94.5% and 4% of the cells, consistent with an extra Ph+, and loss of <em>IKZF1</em> locus in 91% of cells. RT-PCR showed BAF p190 breakpoint. The initial diagnosis was a B-ALL with BAF but given the presence of increased monocytes and left-shifted granulocytes, a preceding CML could not be ruled out. Subsequently, an abnormal karyotype with two clones was detected; one with an interstitial deletion of 7p leading to <em>IKZF1</em> deletion, and t(9;22). Clone two, exhibited an extra Ph+, plus t(9;22); both clones were consistent with the proportion of abnormal cells detected by FISH 46,XY,del(7)(p15p11.2),t(9;22)(q34;q11.2)[19]/47,XY,t(9;22),+der(22)t(9;22)[1]. The immunophenotype obtained by flow cytometry/immunohistochemistry and RT-PCR was supportive of B-ALL. The morphologic picture along with the correlation of the karyotype, which detected two distinct cell populations, supported by FISH <em>IKZF1/ BCR::ABL1</em> results led to a diagnosis of a preceding CML presenting in lymphoid blast crisis. Patient is undergoing initial</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Pages S21-S22"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323396","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}
Pub Date : 2024-08-01DOI: 10.1016/j.cancergen.2024.08.012
Jeremy A. Arbesfeld , James S. Stevenson , Kathryn Stahl , Kori Kuzma , Alex H. Wagner
The detection of gene fusion events, in which two or more genes interact to drive aberrant expression of a gene product, plays a key role in clinical diagnostics. Although advances in sequencing technology have strengthened gene fusion data availability, there are limitations in the way such knowledge is interpreted in a clinical context. Specifically, current standards are imprecise for representing the complexity of fusions that are observed from biological specimens. To address this challenge, experts from VICC, CGC, and other clinical genomics communities developed a consensus, unified framework for the description of fusion events. We developed the FUSOR package, a Python library containing modeling and validation tools that implements this standard for use with gene fusion data.
We tested use of FUSOR on patient sample data through development of a Translator module (http://tinyurl.com/FUSOR-Translator) that standardizes fusion calls from eight widely-used fusion detection algorithms including CICERO and Arriba and fusion calls from the AACR Project GENIE cohort. We assessed application of the VICC Gene Fusion Specification using FUSOR to evaluate the completeness of the specification for representing fusion variant calls. We demonstrate how application of the tool to real-world data identified gaps in the nascent specification, including the use of gene concepts not covered by the HUGO Gene Nomenclature committee and the improved alignment of evidence between assayed and categorical fusion concepts, that we were able to fill to improve the standard. We conclude with applications of the FUSOR tool for use with clinical variant curation workflows.
{"title":"10. Standardizing fusion calls in a computable format with FUSOR for downstream clinical assessment","authors":"Jeremy A. Arbesfeld , James S. Stevenson , Kathryn Stahl , Kori Kuzma , Alex H. Wagner","doi":"10.1016/j.cancergen.2024.08.012","DOIUrl":"10.1016/j.cancergen.2024.08.012","url":null,"abstract":"<div><div>The detection of gene fusion events, in which two or more genes interact to drive aberrant expression of a gene product, plays a key role in clinical diagnostics. Although advances in sequencing technology have strengthened gene fusion data availability, there are limitations in the way such knowledge is interpreted in a clinical context. Specifically, current standards are imprecise for representing the complexity of fusions that are observed from biological specimens. To address this challenge, experts from VICC, CGC, and other clinical genomics communities developed a consensus, unified framework for the description of fusion events. We developed the FUSOR package, a Python library containing modeling and validation tools that implements this standard for use with gene fusion data.</div><div>We tested use of FUSOR on patient sample data through development of a Translator module (<span><span>http://tinyurl.com/FUSOR-Translator</span><svg><path></path></svg></span>) that standardizes fusion calls from eight widely-used fusion detection algorithms including CICERO and Arriba and fusion calls from the AACR Project GENIE cohort. We assessed application of the VICC Gene Fusion Specification using FUSOR to evaluate the completeness of the specification for representing fusion variant calls. We demonstrate how application of the tool to real-world data identified gaps in the nascent specification, including the use of gene concepts not covered by the HUGO Gene Nomenclature committee and the improved alignment of evidence between assayed and categorical fusion concepts, that we were able to fill to improve the standard. We conclude with applications of the FUSOR tool for use with clinical variant curation workflows.</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":"142323462","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}
Pub Date : 2024-08-01DOI: 10.1016/j.cancergen.2024.08.078
Jennie Yao , Kartik Singhal , Susanna Kiwala , Peter Goedegebuure , Christopher Miller , Huiming Xia , My Hoang , Mariam Khanfar , Kelsy Cotto , Sherri Davies , Feiyu Du , Evelyn Schmidt , Gue Su Chang , Jasreet Hundal , Jeffrey Ward , William Inabinett , William Hoos , William Gillanders , Obi Griffith , Malachi Griffith
Advancements in immunogenomics and immuno-oncology have enabled the development of neoantigen vaccines, offering personalized cancer therapies by targeting cancer cell-specific somatic mutations. These mutations produce neoantigens that, when presented on tumor cells by MHC molecules, can elicit a robust and specific immune response. To date, there are 108 interventional studies listed on clinicaltrials.gov that explore the use of cancer vaccines. We have supported a number of these trials through the creation of bioinformatic pipelines, tools and procedures for the identification of patient-specific neoantigen candidates. Final prioritization of neoantigen candidates relies on manual review by an Immunogenomics Tumor Board (ITB) that meets weekly, increasing turnaround time and presenting a barrier to scaling.
Addressing this challenge, we introduce a machine learning-based approach to automate the selection of neoantigens peptides. We implemented a random forest model to train and test on existing ITB results from 21 patients and 1,324 peptides, including 297 peptides prioritized for personalized vaccine inclusion. This model aims to use features such as mutation position, driver gene status, tumor variant allele frequency, RNA expression, and other features to automatically predict whether a peptide will be accepted, rejected, or require further review for the vaccine. The model achieved an 88.89% sensitivity and 86.4% specificity, with an area under the curve of 0.933. By integrating this model into the vaccine development pipeline, we foresee a significant reduction in the time required to transition from patient sample collection to vaccine manufacturing, thereby enhancing the efficiency and scalability of personalized cancer vaccine production.
{"title":"76. Automating immunogenomic tumor board decision-making for neoantigen cancer vaccine design","authors":"Jennie Yao , Kartik Singhal , Susanna Kiwala , Peter Goedegebuure , Christopher Miller , Huiming Xia , My Hoang , Mariam Khanfar , Kelsy Cotto , Sherri Davies , Feiyu Du , Evelyn Schmidt , Gue Su Chang , Jasreet Hundal , Jeffrey Ward , William Inabinett , William Hoos , William Gillanders , Obi Griffith , Malachi Griffith","doi":"10.1016/j.cancergen.2024.08.078","DOIUrl":"10.1016/j.cancergen.2024.08.078","url":null,"abstract":"<div><div>Advancements in immunogenomics and immuno-oncology have enabled the development of neoantigen vaccines, offering personalized cancer therapies by targeting cancer cell-specific somatic mutations. These mutations produce neoantigens that, when presented on tumor cells by MHC molecules, can elicit a robust and specific immune response. To date, there are 108 interventional studies listed on clinicaltrials.gov that explore the use of cancer vaccines. We have supported a number of these trials through the creation of bioinformatic pipelines, tools and procedures for the identification of patient-specific neoantigen candidates. Final prioritization of neoantigen candidates relies on manual review by an Immunogenomics Tumor Board (ITB) that meets weekly, increasing turnaround time and presenting a barrier to scaling.</div><div>Addressing this challenge, we introduce a machine learning-based approach to automate the selection of neoantigens peptides. We implemented a random forest model to train and test on existing ITB results from 21 patients and 1,324 peptides, including 297 peptides prioritized for personalized vaccine inclusion. This model aims to use features such as mutation position, driver gene status, tumor variant allele frequency, RNA expression, and other features to automatically predict whether a peptide will be accepted, rejected, or require further review for the vaccine. The model achieved an 88.89% sensitivity and 86.4% specificity, with an area under the curve of 0.933. By integrating this model into the vaccine development pipeline, we foresee a significant reduction in the time required to transition from patient sample collection to vaccine manufacturing, thereby enhancing the efficiency and scalability of personalized cancer vaccine production.</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Page S24"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323336","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}
Pub Date : 2024-08-01DOI: 10.1016/j.cancergen.2024.08.046
Avinash Dharmadhikari, Sara Kreimer, Jianling Ji, Ryan Schmidt, Miao Sun, Gordana Raca, Yachen Pan, Cindy Fong, Meagan Hughes, Jessica Lee, Minnelly Lu, Joseph Miller, Dean Anselmo, Jaclyn Biegel, Matthew Deardorff
Purpose
To describe early results from a highly sensitive genetic panel to evaluate patients with largely mosaic vascular anomalies
Methods
This is a single-center study utilizing a 218 gene panel with unique molecular identifier (UMI) adapters and an average 1000X target coverage. DNA was obtained from fresh, frozen or paraffin-embedded tissue, blood, buccal brushes, or cells pelleted from fluid.
Results
24 patients were evaluated in a vascular anomalies center and 6 patients were evaluated by dermatology, genetics, or oncology. 23/30 patients (76.7%) had identified causal variants. 25 variants were described: 11 PIK3CA, 4 TEK, 2 GNAQ, 2 KRAS, 1 KDR, 1 CELSR1, 1 PTEN, 1 SUFU, 1 MAP2K1, and 1 MTOR. These variants were classified as 21 pathogenic, 1 likely pathogenic, and 3 variants of uncertain significance (VUS). Of the 11 variants in PIK3CA, the kinase domain substitution at p.His1047 was the most frequently observed (36.3%). Mean variant allele frequency (VAF) was 18.7%, with a minimum VAF of 1.9%, therefore most variants were consistent with somatic mosaicism. Variants in CELSR1 and SUFU were identified at VAFs suggestive of a germline origin in patients who were not known to have germline variants. 6 patients had an alteration of clinical management based on the findings.
Conclusions
This genetic panel is highly effective in identifying somatic and germline clinically significant variants in patients with vascular anomalies. The prevalence of causative variants is higher than reported in previous studies. Future directions include validation of this panel in additional specimen types to extend utility.
{"title":"44. UMI-based expanded NGS panel in precision molecular diagnosis of vascular anomalies: Early results","authors":"Avinash Dharmadhikari, Sara Kreimer, Jianling Ji, Ryan Schmidt, Miao Sun, Gordana Raca, Yachen Pan, Cindy Fong, Meagan Hughes, Jessica Lee, Minnelly Lu, Joseph Miller, Dean Anselmo, Jaclyn Biegel, Matthew Deardorff","doi":"10.1016/j.cancergen.2024.08.046","DOIUrl":"10.1016/j.cancergen.2024.08.046","url":null,"abstract":"<div><h3>Purpose</h3><div>To describe early results from a highly sensitive genetic panel to evaluate patients with largely mosaic vascular anomalies</div></div><div><h3>Methods</h3><div>This is a single-center study utilizing a 218 gene panel with unique molecular identifier (UMI) adapters and an average 1000X target coverage. DNA was obtained from fresh, frozen or paraffin-embedded tissue, blood, buccal brushes, or cells pelleted from fluid.</div></div><div><h3>Results</h3><div>24 patients were evaluated in a vascular anomalies center and 6 patients were evaluated by dermatology, genetics, or oncology. 23/30 patients (76.7%) had identified causal variants. 25 variants were described: 11 <em>PIK3CA</em>, 4 <em>TEK</em>, 2 <em>GNAQ</em>, 2 <em>KRAS</em>, 1 <em>KDR</em>, 1 <em>CELSR1</em>, 1 <em>PTEN</em>, 1 <em>SUFU</em>, 1 <em>MAP2K1</em>, and 1 <em>MTOR</em>. These variants were classified as 21 pathogenic, 1 likely pathogenic, and 3 variants of uncertain significance (VUS). Of the 11 variants in <em>PIK3CA</em>, the kinase domain substitution at p.His1047 was the most frequently observed (36.3%). Mean variant allele frequency (VAF) was 18.7%, with a minimum VAF of 1.9%, therefore most variants were consistent with somatic mosaicism. Variants in <em>CELSR1</em> and <em>SUFU</em> were identified at VAFs suggestive of a germline origin in patients who were not known to have germline variants. 6 patients had an alteration of clinical management based on the findings.</div></div><div><h3>Conclusions</h3><div>This genetic panel is highly effective in identifying somatic and germline clinically significant variants in patients with vascular anomalies. The prevalence of causative variants is higher than reported in previous studies. Future directions include validation of this panel in additional specimen types to extend utility.</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Page S14"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323202","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}
Copy number deletions at chromosomal region 3p14 are rare constitutional occurrences and the genes within this region are mainly unclassified. The small number of publications describing patients with 3p14 deletions list phenotypes of multiple congenital anomalies, movement disorders, feeding difficulties, developmental delay, and autism. Despite these recurring patient phenotypes, no potential candidate genes within this region have been identified.
Here we describe two unrelated cases with overlapping 3p14.2 to 3p14.1 single-copy deletions. The first case is a 5-year-old male with childhood apraxia of speech, global developmental delay, autism spectrum disorder, and hyperkinesis. This patient's deletion is 3.1 Mb in size and contains 15 known genes and 8 OMIM genes. The second case is a 2-year-old female with prematurity, global developmental delay, failure to thrive, feeding difficulties, feeding tube dependency, short stature, microcephaly, PDA closure, autism spectrum disorder, and abnormalities on brain MRI. This patient's deletion is 3.5 Mb in size and contains 24 known genes and 10 OMIM genes.
Taken together, 7 OMIM genes are deleted in both patients: PTPRG, FEZF2, CADPS, SNTN, THOC7, ATXN7, SCAANT1. We will explore how deletion of these potential candidate genes may impact the patients' shared phenotypes of autism and global developmental delay. Additionally, we will examine the three genes (PSMD6, PRICKLE2, ADAMTS9) that are deleted only in the second patient, who displays a more severe phenotype. This assessment may identify candidate genes for follow-up functional studies and will contribute to the literature by describing patients with rare copy number losses in this region.
{"title":"45. Examining potential candidate genes within deletions of 3p14.2 to 3p14.1 in two cases of autism and developmental delay","authors":"Rebecca Smith, Ashwini Yenamandra, Meng-Chang Hsiao, Monica Guardado, Jeanette Saffir, Scott Ward","doi":"10.1016/j.cancergen.2024.08.047","DOIUrl":"10.1016/j.cancergen.2024.08.047","url":null,"abstract":"<div><div>Copy number deletions at chromosomal region 3p14 are rare constitutional occurrences and the genes within this region are mainly unclassified. The small number of publications describing patients with 3p14 deletions list phenotypes of multiple congenital anomalies, movement disorders, feeding difficulties, developmental delay, and autism. Despite these recurring patient phenotypes, no potential candidate genes within this region have been identified.</div><div>Here we describe two unrelated cases with overlapping 3p14.2 to 3p14.1 single-copy deletions. The first case is a 5-year-old male with childhood apraxia of speech, global developmental delay, autism spectrum disorder, and hyperkinesis. This patient's deletion is 3.1 Mb in size and contains 15 known genes and 8 OMIM genes. The second case is a 2-year-old female with prematurity, global developmental delay, failure to thrive, feeding difficulties, feeding tube dependency, short stature, microcephaly, PDA closure, autism spectrum disorder, and abnormalities on brain MRI. This patient's deletion is 3.5 Mb in size and contains 24 known genes and 10 OMIM genes.</div><div>Taken together, 7 OMIM genes are deleted in both patients: <em>PTPRG, FEZF2, CADPS, SNTN, THOC7, ATXN7, SCAANT1</em>. We will explore how deletion of these potential candidate genes may impact the patients' shared phenotypes of autism and global developmental delay. Additionally, we will examine the three genes (<em>PSMD6, PRICKLE2, ADAMTS9</em>) that are deleted only in the second patient, who displays a more severe phenotype. This assessment may identify candidate genes for follow-up functional studies and will contribute to the literature by describing patients with rare copy number losses in this region.</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":"142323203","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}
Pub Date : 2024-08-01DOI: 10.1016/j.cancergen.2024.08.049
Hussain Alcassab, Chin-Ting Wu, Awdhesh Kalia, Manjunath Nimmakayalu, Xiaojun Liu
Human Cancer cell lines provide a valuable model for detecting genomic alterations and chromosomal aberrations to identify and validate new diagnostic or therapeutic targets. Here, we recharacterize the T-cell acute lymphocytic leukemia (T-ALL) cell line CCRF-CEM (ATCC #CCL-119) using karyotyping, FISH, aCGH, and emerging genomic technologies of optical genome mapping (OGM) and nanopore long-read sequencing (LRS). Consistent with the previous literature, karyotyping and FISH indicated a modal number of 47, with t(8;9)(p12;p24) and trisomy 20 in analyzed metaphases. ACGH confirmed trisomy 20 apparent in the karyotype but also showed both an unbalanced der(5)t(5;14)(q35.2;q32.2) translocation, independently confirmed by FISH, and a 226-kb deletion at 10q23.31 containing the tumor suppressor gene PTEN, concordant with existing literature. Saphyr-based OGM analysis confirmed the aCGH data; however, OGM analysis additionally identified monosomy X (copy number fraction 1.579), which could arise from a subclonal population as previously reported, and the breakpoint at 8p11.21 as the true region of the balanced translocation. Strikingly, OGM also identified a novel likely pathogenic cryptic 81.9-kb deletion at 1p33 overlapping the STIL gene (80X coverage). Deletions of STIL are known to occur in T-cell leukemias although this aberration has not been described in the CCRF-CEM cell line. We are currently in the process of analyzing LRS data to validate OGM findings and determine precise deletion breakpoints. Collectively, our data have identified a novel chromosomal aberration in the CCRF-CEM cell line providing a framework for further functional characterization.
{"title":"47. Genomic characterization of the T-ALL cell line CCRF-CEM using optical genome mapping and nanopore sequencing","authors":"Hussain Alcassab, Chin-Ting Wu, Awdhesh Kalia, Manjunath Nimmakayalu, Xiaojun Liu","doi":"10.1016/j.cancergen.2024.08.049","DOIUrl":"10.1016/j.cancergen.2024.08.049","url":null,"abstract":"<div><div>Human Cancer cell lines provide a valuable model for detecting genomic alterations and chromosomal aberrations to identify and validate new diagnostic or therapeutic targets. Here, we recharacterize the T-cell acute lymphocytic leukemia (T-ALL) cell line CCRF-CEM (ATCC #CCL-119) using karyotyping, FISH, aCGH, and emerging genomic technologies of optical genome mapping (OGM) and nanopore long-read sequencing (LRS). Consistent with the previous literature, karyotyping and FISH indicated a modal number of 47, with t(8;9)(p12;p24) and trisomy 20 in analyzed metaphases. ACGH confirmed trisomy 20 apparent in the karyotype but also showed both an unbalanced der(5)t(5;14)(q35.2;q32.2) translocation, independently confirmed by FISH, and a 226-kb deletion at 10q23.31 containing the tumor suppressor gene <em>PTEN</em>, concordant with existing literature. Saphyr-based OGM analysis confirmed the aCGH data; however, OGM analysis additionally identified monosomy X (copy number fraction 1.579), which could arise from a subclonal population as previously reported, and the breakpoint at 8p11.21 as the true region of the balanced translocation. Strikingly, OGM also identified a novel likely pathogenic cryptic 81.9-kb deletion at 1p33 overlapping the <em>STIL</em> gene (80X coverage). Deletions of <em>STIL</em> are known to occur in T-cell leukemias although this aberration has not been described in the CCRF-CEM cell line. We are currently in the process of analyzing LRS data to validate OGM findings and determine precise deletion breakpoints. Collectively, our data have identified a novel chromosomal aberration in the CCRF-CEM cell line providing a framework for further functional characterization.</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":"142323207","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}
Pub Date : 2024-08-01DOI: 10.1016/j.cancergen.2024.08.053
Marwa Daghsni, Taimoor Sheikh, Lynn H. Sniezek, Michaelia M. Austin, Mahmoud Aarabi, Svetlana Yatsenko
Chromosome analysis and fluorescence in situ hybridization (FISH) testing are the standard techniques in diagnosis, classification, and risk assessment of hematologic neoplasms such as myelodysplastic syndrome (MDS), acute myelogenous leukemia (AML), B-cell acute lymphoblastic leukemia (B-ALL), and chronic lymphocytic leukemia (CLL). Notably, the result of conventional cytogenetic testing is normal or non-informative in at least 10% of B-ALL, 50% of MDS/AML, and 15% of CLL cases, preventing accurate characterization of cancer genomic profile. Chromosomal microarray analysis (CMA) is widely used for detection of cryptic chromosomal imbalances and copy-neutral loss of heterozygosity, which are beyond the resolution of conventional cytogenetic methodologies. This study has evaluated the CMA utility and diagnostic yield in patients with an established diagnosis of either B-ALL, MDS/AML, or CLL, and negative findings of G-banding karyotype and disease-relevant FISH panel testing. During a 5-year period, karyotype, FISH and CMA were performed on 3628 samples, including 2720 cases of MDS/AML, 240 B-ALL and 668 CLL cases. At diagnosis normal karyotype and FISH were reported for 1466/2720 (54%) of patients with MDS/AML, 23/240 (9.6%) of B-ALL, and 112/668 (16.8%) of CLL cases. Using CMA, submicroscopic copy number alterations of diagnostic and prognostic significance were identified in 14.6% of MDS/AML cases, 26.1% of B-ALL, and 6.3% of CLL patients. Additionally, CMA revealed clones with large chromosomal abnormalities that were not observed among metaphase cells. Implementation of CMA in diagnosis of hematologic malignancies can significantly improve the diagnostic yield and provide data for a patient-specific risk stratification, prognostication, and therapeutic decisions.
{"title":"51. Utility of microarray in the diagnosis of hematologic neoplasms with normal FISH and karyotype","authors":"Marwa Daghsni, Taimoor Sheikh, Lynn H. Sniezek, Michaelia M. Austin, Mahmoud Aarabi, Svetlana Yatsenko","doi":"10.1016/j.cancergen.2024.08.053","DOIUrl":"10.1016/j.cancergen.2024.08.053","url":null,"abstract":"<div><div>Chromosome analysis and fluorescence in situ hybridization (FISH) testing are the standard techniques in diagnosis, classification, and risk assessment of hematologic neoplasms such as myelodysplastic syndrome (MDS), acute myelogenous leukemia (AML), B-cell acute lymphoblastic leukemia (B-ALL), and chronic lymphocytic leukemia (CLL). Notably, the result of conventional cytogenetic testing is normal or non-informative in at least 10% of B-ALL, 50% of MDS/AML, and 15% of CLL cases, preventing accurate characterization of cancer genomic profile. Chromosomal microarray analysis (CMA) is widely used for detection of cryptic chromosomal imbalances and copy-neutral loss of heterozygosity, which are beyond the resolution of conventional cytogenetic methodologies. This study has evaluated the CMA utility and diagnostic yield in patients with an established diagnosis of either B-ALL, MDS/AML, or CLL, and negative findings of G-banding karyotype and disease-relevant FISH panel testing. During a 5-year period, karyotype, FISH and CMA were performed on 3628 samples, including 2720 cases of MDS/AML, 240 B-ALL and 668 CLL cases. At diagnosis normal karyotype and FISH were reported for 1466/2720 (54%) of patients with MDS/AML, 23/240 (9.6%) of B-ALL, and 112/668 (16.8%) of CLL cases. Using CMA, submicroscopic copy number alterations of diagnostic and prognostic significance were identified in 14.6% of MDS/AML cases, 26.1% of B-ALL, and 6.3% of CLL patients. Additionally, CMA revealed clones with large chromosomal abnormalities that were not observed among metaphase cells. Implementation of CMA in diagnosis of hematologic malignancies can significantly improve the diagnostic yield and provide data for a patient-specific risk stratification, prognostication, and therapeutic decisions.</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Page S16"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323211","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}
Pub Date : 2024-08-01DOI: 10.1016/j.cancergen.2024.08.062
Brianna Munnich , Haowen Zhou , Mark Watson , Cory Bernadt , Steven (Siyu) Lin , Jon Ritter , Chieh-Yu Lin , Ramaswamy Govindan , Siddarth Rawal , Changhuei Yang , Richard Cote
Brain metastases can occur in nearly half of patients with early and locally advanced (stage I-III) non-small cell lung cancer (NSCLC). There are no reliable histopathologic or molecular means to identify those who are likely to develop brain metastases. We sought to determine if deep learning (DL) could be applied to routine hematoxylin and eosin (H&E) stained primary tumor tissue sections from Stage I-III NSCLC patients to predict the development of brain metastasis. Diagnostic slides from 158 patients with Stage I to III NSCLC followed for at least 5 years for development of brain metastases (Met+, 65 patients) versus no progression (Met-, 93 patients) were subjected to whole slide imaging. Three separate iterations of DL were performed by first selecting 118 cases (45 Met+, 73 Met-) to train and validate the DL algorithm, while 40 separate cases (20 Met+, 20 Met-) were used as the test set. DL algorithm results were compared to a blinded review by four expert pathologists. The DL-based algorithm was able to distinguish eventual development of brain metastases with an accuracy of 87% (p<0.0001) compared to an average of 57.3% by the four pathologists, and appears to be particularly useful in predicting brain metastases in Stage I patients. DL-based algorithms using routine H&E-stained slides may identify patients likely to develop brain metastases from those that will remain disease free over extended (>5 year) follow-up and may thus be spared systemic therapy.
{"title":"60. AI-guided histopathology predicts brain metastasis in lung cancer patients","authors":"Brianna Munnich , Haowen Zhou , Mark Watson , Cory Bernadt , Steven (Siyu) Lin , Jon Ritter , Chieh-Yu Lin , Ramaswamy Govindan , Siddarth Rawal , Changhuei Yang , Richard Cote","doi":"10.1016/j.cancergen.2024.08.062","DOIUrl":"10.1016/j.cancergen.2024.08.062","url":null,"abstract":"<div><div>Brain metastases can occur in nearly half of patients with early and locally advanced (stage I-III) non-small cell lung cancer (NSCLC). There are no reliable histopathologic or molecular means to identify those who are likely to develop brain metastases. We sought to determine if deep learning (DL) could be applied to routine hematoxylin and eosin (H&E) stained primary tumor tissue sections from Stage I-III NSCLC patients to predict the development of brain metastasis. Diagnostic slides from 158 patients with Stage I to III NSCLC followed for at least 5 years for development of brain metastases (Met+, 65 patients) versus no progression (Met-, 93 patients) were subjected to whole slide imaging. Three separate iterations of DL were performed by first selecting 118 cases (45 Met+, 73 Met-) to train and validate the DL algorithm, while 40 separate cases (20 Met+, 20 Met-) were used as the test set. DL algorithm results were compared to a blinded review by four expert pathologists. The DL-based algorithm was able to distinguish eventual development of brain metastases with an accuracy of 87% (p<0.0001) compared to an average of 57.3% by the four pathologists, and appears to be particularly useful in predicting brain metastases in Stage I patients. DL-based algorithms using routine H&E-stained slides may identify patients likely to develop brain metastases from those that will remain disease free over extended (>5 year) follow-up and may thus be spared systemic therapy.</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Pages S19-S20"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142322880","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}
Pub Date : 2024-08-01DOI: 10.1016/j.cancergen.2024.07.002
Mario Ćuk , Busra Unal , Connor P. Hayes , McKenzie Walker , Anđela Bevanda , Viktorija Antolović , Arezou A. Ghazani
ATM gene is implicated in the development of breast cancer in the heterozygous state, and Ataxia-telangiectasia (A-T) in a homozygous or compound heterozygous state. Ataxia-telangiectasia (A-T) is a rare cerebellar ataxia syndrome presenting with progressive neurologic impairment, telangiectasia, and an increased risk of leukemia and lymphoma.
Although the role of ATM, separately, in association with A-T and breast cancer is well documented, there is a limited number of studies investigating ATM variants when segregating with both phenotypes in the same family. Here, using joint analysis and whole genome sequencing, we investigated ATM c.1564_1565del in a family with one homozygous member presenting with A-T (OMIM # 208900) and three heterozygous members, of whom one had breast cancer (OMIM #114480). To our knowledge, this is the first study of ATM c.1564_1565del segregation with both A-T and breast cancer phenotypes within the same kindred. This study highlights the need for a comprehensive genomic approach in the appropriate cancer risk management of heterozygote carriers of ATM in families with A-T.
{"title":"Whole genome joint analysis reveals ATM:C.1564_1565del variant segregating with Ataxia-Telangiectasia and breast cancer","authors":"Mario Ćuk , Busra Unal , Connor P. Hayes , McKenzie Walker , Anđela Bevanda , Viktorija Antolović , Arezou A. Ghazani","doi":"10.1016/j.cancergen.2024.07.002","DOIUrl":"10.1016/j.cancergen.2024.07.002","url":null,"abstract":"<div><p><em>ATM</em> gene is implicated in the development of breast cancer in the heterozygous state, and Ataxia-telangiectasia (A-T) in a homozygous or compound heterozygous state. Ataxia-telangiectasia (A-T) is a rare cerebellar ataxia syndrome presenting with progressive neurologic impairment, telangiectasia, and an increased risk of leukemia and lymphoma.</p><p>Although the role of <em>ATM,</em> separately, in association with A-T and breast cancer is well documented, there is a limited number of studies investigating <em>ATM</em> variants when segregating with both phenotypes in the same family. Here, using joint analysis and whole genome sequencing, we investigated <em>ATM</em> c.1564_1565del in a family with one homozygous member presenting with A-T (OMIM # <span><span>208900</span><svg><path></path></svg></span>) and three heterozygous members, of whom one had breast cancer (OMIM #<span><span>114480</span><svg><path></path></svg></span>). To our knowledge, this is the first study of <em>ATM</em> c.1564_1565del segregation with both A-T and breast cancer phenotypes within the same kindred. This study highlights the need for a comprehensive genomic approach in the appropriate cancer risk management of heterozygote carriers of <em>ATM</em> in families with A-T.</p></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Pages 43-47"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141789616","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}