Pub Date : 2024-08-01DOI: 10.1016/j.cancergen.2024.08.013
Kartik Singhal , Susanna Kiwala , Peter S. Goedegebuure , Christopher Miller , Evelyn Schmidt , Huiming Xia , My Hoang , Mariam Khanfar , Shelly O'Laughlin , Nancy Myers , Tammi Vickery , Kelsy C. Cotto , Sherri Davies , Feiyu Du , Thomas B. Mooney , Gue Su Chang , Jasreet Hundal , John Garza , Mike D. McLellan , Joshua McMichael , Malachi Griffith
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.
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.
{"title":"11. Developing a robust bioinformatics workflow to support personalized neoantigen vaccine clinical trials","authors":"Kartik Singhal , Susanna Kiwala , Peter S. Goedegebuure , Christopher Miller , Evelyn Schmidt , Huiming Xia , My Hoang , Mariam Khanfar , Shelly O'Laughlin , Nancy Myers , Tammi Vickery , Kelsy C. Cotto , Sherri Davies , Feiyu Du , Thomas B. Mooney , Gue Su Chang , Jasreet Hundal , John Garza , Mike D. McLellan , Joshua McMichael , 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}
Pub Date : 2024-08-01DOI: 10.1016/j.cancergen.2024.08.074
Kathryn Stahl, Wesley Goar, Kori Kuzma, Alex Wagner
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).
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.
{"title":"72. What's under VarCat's hat: Modeling variant oncogenicity classifications with GA4GH Standards","authors":"Kathryn Stahl, Wesley Goar, Kori Kuzma, 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}
Pub Date : 2024-08-01DOI: 10.1016/j.cancergen.2024.08.014
Matthew Cannon , James Stevenson , Kathryn Stahl , Rohit Basu , Adam Coffman , Susanna Kiwala , Joshua McMichael , Elaine Mardis , Obi Griffith , Malachi Griffith , Alex Wagner
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.
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.
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.
{"title":"12. Contextualizing clinical significance using FDA label supplemented DGI data","authors":"Matthew Cannon , James Stevenson , Kathryn Stahl , Rohit Basu , Adam Coffman , Susanna Kiwala , Joshua McMichael , Elaine Mardis , Obi Griffith , Malachi Griffith , 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}
Pub Date : 2024-08-01DOI: 10.1016/j.cancergen.2024.08.032
Celeste Eno , Rama Sompallae , T. Niroshi Senaratne
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.
{"title":"30. Current next generation sequencing reporting practices: A GOAL Consortium report","authors":"Celeste Eno , Rama Sompallae , 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}
Pub Date : 2024-08-01DOI: 10.1016/j.cancergen.2024.08.037
Mohana Priya Jayavel, Ha Nguyen, Madina Sukhanova, Lucas Santana dos Santos, Behtash Nezami, Juehua Gao, Erica Vormittag-Nocito, Lawrence Jennings, Xinyan Lu
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.
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.
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.
{"title":"35. Integrated comprehensive genomic profiling of meningiomas: A single institutional study","authors":"Mohana Priya Jayavel, Ha Nguyen, Madina Sukhanova, Lucas Santana dos Santos, Behtash Nezami, Juehua Gao, Erica Vormittag-Nocito, Lawrence Jennings, 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}
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.
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.
{"title":"55. Advancing bladder carcinoma diagnosis: The innovative potential of the BCDx multi-omics approach","authors":"Thakshila Habarakada Liyanage, 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}
Pub Date : 2024-08-01DOI: 10.1016/j.cancergen.2024.08.048
Lucilla Pizzo , Jian Zhao , Akiko Shimamura , Sara Lewis , Marcin Wlodarski , Bo Hong , Erica Andersen
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.
{"title":"46. Clinical SNP-array adds value to diagnosis and surveillance of bone marrow failure syndromes","authors":"Lucilla Pizzo , Jian Zhao , Akiko Shimamura , Sara Lewis , Marcin Wlodarski , Bo Hong , 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}
dic(7;9) is a rare (<1%) and recurrent abnormality in both pediatric and adult B-ALL, resulting in partial monosomy of chromosomes 7p and 9p. Co-occurrence of dic(7;9) with PAX5 gene alterations including deletions, mutations and amplification have been reported. PAX5 encodes the B lymphoid transcription factor gene that is important in regulating B cell lineage differentiation, leading to B-cell development and may play a crucial role in B lymphoid leukemogenesis.
Here, we present two cases of pediatric B-ALL with dic(7;9) with complex genomic aberrations.
Case 1: is a four year old female who presented in 2024 with orbital and left sinus maxillary masses, anemia, fever and leukocytosis with peripheral blasts. Karyotype and fish were complex with 45,XX,der(7)dic(7;9)(p11.2;p13)del(7)(p13p11.2)t(7;20)(p13;q11.2),der(20)t(7;20)(p13;q11.2)[13]/46,XX[7]. SNP array revealed loss of 7p and 9p including IKAROS and PAX5, respectively.
Cerebral sinus fluid demonstrated a leukocytosis with leukemic blasts, resulting in a CNS3b classification. She had negative minimal residual disease at the end of induction on a very high-risk standard of care protocol and on consolidation therapy.
Case 2: is a 10 year old male referred in 2022 for a month of fever and fatigue.. karyotype was complex with several rearrangements. 45,XY,dic(7)t(7;9)(p13;p13),-9,der(10)t(9;10)(q34.1;q22),der(12)t(7;12)(p13;p13),der(13)t(10;13)(q22;q34)[11]/46,XY[9].
The patient was treated on a standard risk standard of care protocol and had negative minimal residual disease at the end of induction. He remains in remission during maintenance therapy.
Given the two dic (7;9) cases described here have complex karyotypes, it is possible that PAX5 and IKZF1 alterations may be contributing to this complex cytogenetic entity.
{"title":"77. dic(7;9):A distinct entity in B-ALL with multiple genomic aberrations including IKAROS and PAX5","authors":"Ashwini Yenamandra, Rebecca Smith, Kun Zhao, Yingda Wang, Brianna Smith, Christine Smith, Meng-Chang Hsiao, Debra Friedman","doi":"10.1016/j.cancergen.2024.08.079","DOIUrl":"10.1016/j.cancergen.2024.08.079","url":null,"abstract":"<div><div>dic(7;9) is a rare (<1%) and recurrent abnormality in both pediatric and adult B-ALL, resulting in partial monosomy of chromosomes 7p and 9p. Co-occurrence of dic(7;9) with <em>PAX5</em> gene alterations including deletions, mutations and amplification have been reported. <em>PAX5</em> encodes the B lymphoid transcription factor gene that is important in regulating B cell lineage differentiation, leading to B-cell development and may play a crucial role in B lymphoid leukemogenesis.</div><div>Here, we present two cases of pediatric B-ALL with dic(7;9) with complex genomic aberrations.</div><div>Case 1: is a four year old female who presented in 2024 with orbital and left sinus maxillary masses, anemia, fever and leukocytosis with peripheral blasts. Karyotype and fish were complex with 45,XX,der(7)dic(7;9)(p11.2;p13)del(7)(p13p11.2)t(7;20)(p13;q11.2),der(20)t(7;20)(p13;q11.2)[13]/46,XX[7]. SNP array revealed loss of 7p and 9p including <em>IKAROS</em> and <em>PAX5</em>, respectively.</div><div>Cerebral sinus fluid demonstrated a leukocytosis with leukemic blasts, resulting in a CNS3b classification. She had negative minimal residual disease at the end of induction on a very high-risk standard of care protocol and on consolidation therapy.</div><div>Case 2: is a 10 year old male referred in 2022 for a month of fever and fatigue.. karyotype was complex with several rearrangements. 45,XY,dic(7)t(7;9)(p13;p13),-9,der(10)t(9;10)(q34.1;q22),der(12)t(7;12)(p13;p13),der(13)t(10;13)(q22;q34)[11]/46,XY[9].</div><div>The patient was treated on a standard risk standard of care protocol and had negative minimal residual disease at the end of induction. He remains in remission during maintenance therapy.</div><div>Given the two dic (7;9) cases described here have complex karyotypes, it is possible that <em>PAX5</em> and <em>IKZF1</em> alterations may be contributing to this complex cytogenetic entity.</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Pages S24-S25"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323337","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.2024.08.008
Barina Aqil , Lucas Santana-Santos , Juehua Gao , Xinyan Lu , Amandeep Kaur , Erica Vormittag-Nocito , Lawrence Jennings , Yasmin Abaza , Madina Sukhanova
KIT (proto-oncogene) plays significant role in diagnosis and prognosis of myeloid neoplasms (MNs). The hot-spot KIT D816 mutation in exon 17 is recognized by WHO classification as poor prognostic marker for acute myeloid leukemia (AML) with RUNX1::RUNX1T1 and as one of diagnostic and prognostic criteria for systemic mastocytosis (SM), a MN characterized by clonal proliferation of mast cells. The role of activating KIT mutations outside of codon 816 was recognized, resulting in addition of few critical KIT regions in updated consensus proposal for SM diagnosis. However, information on prognostic weight of these 'non-hot-spot' changes is limited. Here we present results of comparative analysis of clinicopathological and survival parameters for patients diagnosed with MNs with activating KIT changes outside of codon 816 (N=14) using patients with MNs with KIT D816 (N=26) as comparative group. Most of study patients had AML (65%) followed by MDS and MDS/MPN (35% combined). Both study groups had same representation of normal, non-complex and complex karyotypes, and karyotypes with diagnostic t(8;21) and inv(16). IHC staining for c-KIT (CD117) detected significantly lower percentage of mast cells with c-Kit protein expression in non-D816 group in contrast to patients with D816 KIT (p<0.0076). Consistent with that, none of the non-D816 group patients developed SM compared to 31% of D816 group patients who developed SM. Notably, the group with non-D816 KIT showed better OS compared to patients with D816 change (p<0.016). Our results support the hypothesis of weaker prognostic impact of non-D816 KIT mutations compared to D816 hot-spot.
{"title":"6. Hot-spot D816 KIT has different clinical outcome compared to non-D816 KIT variants in myeloid neoplasms","authors":"Barina Aqil , Lucas Santana-Santos , Juehua Gao , Xinyan Lu , Amandeep Kaur , Erica Vormittag-Nocito , Lawrence Jennings , Yasmin Abaza , Madina Sukhanova","doi":"10.1016/j.cancergen.2024.08.008","DOIUrl":"10.1016/j.cancergen.2024.08.008","url":null,"abstract":"<div><div><em>KIT</em> (proto-oncogene) plays significant role in diagnosis and prognosis of myeloid neoplasms (MNs). The hot-spot <em>KIT</em> D816 mutation in exon 17 is recognized by WHO classification as poor prognostic marker for acute myeloid leukemia (AML) with <em>RUNX1::RUNX1T1</em> and as one of diagnostic and prognostic criteria for systemic mastocytosis (SM), a MN characterized by clonal proliferation of mast cells. The role of activating <em>KIT</em> mutations outside of codon 816 was recognized, resulting in addition of few critical <em>KIT</em> regions in updated consensus proposal for SM diagnosis. However, information on prognostic weight of these 'non-hot-spot' changes is limited. Here we present results of comparative analysis of clinicopathological and survival parameters for patients diagnosed with MNs with activating <em>KIT</em> changes outside of codon 816 (N=14) using patients with MNs with <em>KIT</em> D816 (N=26) as comparative group. Most of study patients had AML (65%) followed by MDS and MDS/MPN (35% combined). Both study groups had same representation of normal, non-complex and complex karyotypes, and karyotypes with diagnostic t(8;21) and inv(16). IHC staining for c-KIT (CD117) detected significantly lower percentage of mast cells with c-Kit protein expression in non-D816 group in contrast to patients with D816 <em>KIT</em> (p<0.0076). Consistent with that, none of the non-D816 group patients developed SM compared to 31% of D816 group patients who developed SM. Notably, the group with non-D816 <em>KIT</em> showed better OS compared to patients with D816 change (p<0.016). Our results support the hypothesis of weaker prognostic impact of non-D816 <em>KIT</em> mutations compared to D816 hot-spot.</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Pages S2-S3"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142322863","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.2024.07.003
Bilgesu Ak , Özge Güngör , Emin Karaca , Burak Durmaz , Denis S. Bozer , Mahmut Töbü , Haluk Akın
The present study described an extremely rare case of acute promyelocytic leukemia (APL) characterized by a complex three‑way (15;22;17)(q22;q11.2;q21) translocation. Acute promyelocytic leukemia (APL) is a specific subtype of acute myeloid leukemia with distinctive clinical and therapeutic characteristics. Besides being characterized by the t(15;17)(q22;q12) translocation, this subtype is also notable for its response to all-trans-retinoic acid (ATRA) treatment. APL is highly responsive to a combination of ATRA and chemotherapeutic agents, achieving over 90 % complete remission rates and over 80 % long-term remission rates. In this case, a 79-year-old male patient presented with complaints of weakness, fatigue, and petechial rash, with no other significant medical history except for diabetes mellitus and hypertension. Conventional cytogenetic methods, dual-color dual-fusion, and dual-color break-apart fluorescent in situ hybridization techniques together identified the t(15;22;17) translocation. RT-PCR analysis was performed for expression of PML/RARA fusion transcripts. The patient, diagnosed with APL, exhibited a complete response to all-trans retinoic acid (ATRA) and idarubicin treatment. In this paper, we present the second documented case of t(15;22;17) and explore the remarkable remission observed following treatment with All-Trans Retinoic Acid (ATRA).
{"title":"A complex t(15;22;17)(q22;q11.2;q21) variant of APL","authors":"Bilgesu Ak , Özge Güngör , Emin Karaca , Burak Durmaz , Denis S. Bozer , Mahmut Töbü , Haluk Akın","doi":"10.1016/j.cancergen.2024.07.003","DOIUrl":"10.1016/j.cancergen.2024.07.003","url":null,"abstract":"<div><p>The present study described an extremely rare case of acute promyelocytic leukemia (APL) characterized by a complex three‑way (15;22;17)(q22;q11.2;q21) translocation. Acute promyelocytic leukemia (APL) is a specific subtype of acute myeloid leukemia with distinctive clinical and therapeutic characteristics. Besides being characterized by the t(15;17)(q22;q12) translocation, this subtype is also notable for its response to all-trans-retinoic acid (ATRA) treatment. APL is highly responsive to a combination of ATRA and chemotherapeutic agents, achieving over 90 % complete remission rates and over 80 % long-term remission rates. In this case, a 79-year-old male patient presented with complaints of weakness, fatigue, and petechial rash, with no other significant medical history except for diabetes mellitus and hypertension. Conventional cytogenetic methods, dual-color dual-fusion, and dual-color break-apart fluorescent in situ hybridization techniques together identified the t(15;22;17) translocation. RT-PCR analysis was performed for expression of PML/RARA fusion transcripts. The patient, diagnosed with APL, exhibited a complete response to all-trans retinoic acid (ATRA) and idarubicin treatment. In this paper, we present the second documented case of t(15;22;17) and explore the remarkable remission observed following treatment with All-Trans Retinoic Acid (ATRA).</p></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Pages 48-51"},"PeriodicalIF":1.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141839783","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}