Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-542
Dennis O'Rourke, Danyi Wang, J. Scheuenpflug, Zheng Feng
Introduction: Reliable detection of low mutant allele fractions (MAF) in circulating tumor DNA (ctDNA) offers clinically crucial information. Importantly, minimal residual disease (MRD) detection in solid tumors has been recognized as a powerful readout for response and early relapse prediction. Considering the high sample input requirement and assay complexity of whole exome sequencing (WES) or targeted NGS technologies, it is essential to develop a cost-effective absolute quantification approach to measure MAF with low DNA input amount. Clinically relevant gene variants present both in plasma ctDNA and tissue of origin were identified in a previous study of 25 late-stage CRC samples analyzed using the Guardant Health GuardantOMNI NGS panel (ctDNA) and WES (tumor). We further investigated the potential of using droplet digital PCR (ddPCR) to measure variants present only in ctDNA; particularly for those at low MAF which could be applied for MRD monitoring. Methods: We developed ddPCR assays for 13 variants which were detected with the GuardantOMNI panel in ctDNA and not tissue from 5 of 25 advanced stage CRC samples. MAF for the previously reported variants ranged from 64.0% (FBXW7 p.R505C) to 1.2% (TP53 R273H). Among the newly investigated variants the range was 2.2% (EPHA7 I146T) to 0.4% (PDGFRA1 pL31F and RB1 p.E440K). Other variants included KRAS G12D (30.8%), PIK3CA p.C420R (29.2%), TP53 p.R273H (1.2%) and ERBB4 p.I736T (1.1%). Positive control cDNA was designed and spiked into a pool of healthy plasma to determine the baseline wildtype levels and the sensitivity of each assay. Patient ctDNA was then measured. Results: MAF from ddPCR data and the GuardantOMNI panel showed high concordance (r2 = 0.9986) for all data points (n=13). When only considering those variants with MAF less than 5% (n=9; TP53 R273H, TSC2, EP300, PPP2R1A, LIG4, EPHA7, ERBB4, PDGFRA1, and RB1) the concordance remained high with r2 = 0.9532, thus demonstrating the accuracy and sensitivity of both platforms. All ddPCR results were achieved with at most 5ng input DNA and as low as 1ng in most cases. However, the concordance begins to weaken below 1% MAF (r2=0.4024), likely due to the limit of detection of the current ddPCR assays. Conclusions: We demonstrated that ddPCR offers a highly sensitive and purely quantitative method to measure low MAF with minimal sample input requirements, which highlights the potential use of ddPCR for MRD monitoring. As one possible MRD monitoring approach, NGS panel-based assays may identify all variants at baseline screening, followed by ddPCR as a complementary solution for MRD monitoring of single variants. Currently, there are ongoing efforts in examining longitudinal ctDNA variant changes in CRC patients receiving treatment to further confirm which variants could be used for MRD monitoring in CRC. Citation Format: Dennis O9Rourke, Danyi Wang, Juergen Scheuenpflug, Zheng Feng. Validation of low fraction allelic variants in plasma samples
{"title":"Abstract 542: Validation of low fraction allelic variants in plasma samples from patients with late stage colorectal cancer using droplet digital PCR: Potential clinical utility for minimal residual disease monitoring","authors":"Dennis O'Rourke, Danyi Wang, J. Scheuenpflug, Zheng Feng","doi":"10.1158/1538-7445.AM2021-542","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-542","url":null,"abstract":"Introduction: Reliable detection of low mutant allele fractions (MAF) in circulating tumor DNA (ctDNA) offers clinically crucial information. Importantly, minimal residual disease (MRD) detection in solid tumors has been recognized as a powerful readout for response and early relapse prediction. Considering the high sample input requirement and assay complexity of whole exome sequencing (WES) or targeted NGS technologies, it is essential to develop a cost-effective absolute quantification approach to measure MAF with low DNA input amount. Clinically relevant gene variants present both in plasma ctDNA and tissue of origin were identified in a previous study of 25 late-stage CRC samples analyzed using the Guardant Health GuardantOMNI NGS panel (ctDNA) and WES (tumor). We further investigated the potential of using droplet digital PCR (ddPCR) to measure variants present only in ctDNA; particularly for those at low MAF which could be applied for MRD monitoring. Methods: We developed ddPCR assays for 13 variants which were detected with the GuardantOMNI panel in ctDNA and not tissue from 5 of 25 advanced stage CRC samples. MAF for the previously reported variants ranged from 64.0% (FBXW7 p.R505C) to 1.2% (TP53 R273H). Among the newly investigated variants the range was 2.2% (EPHA7 I146T) to 0.4% (PDGFRA1 pL31F and RB1 p.E440K). Other variants included KRAS G12D (30.8%), PIK3CA p.C420R (29.2%), TP53 p.R273H (1.2%) and ERBB4 p.I736T (1.1%). Positive control cDNA was designed and spiked into a pool of healthy plasma to determine the baseline wildtype levels and the sensitivity of each assay. Patient ctDNA was then measured. Results: MAF from ddPCR data and the GuardantOMNI panel showed high concordance (r2 = 0.9986) for all data points (n=13). When only considering those variants with MAF less than 5% (n=9; TP53 R273H, TSC2, EP300, PPP2R1A, LIG4, EPHA7, ERBB4, PDGFRA1, and RB1) the concordance remained high with r2 = 0.9532, thus demonstrating the accuracy and sensitivity of both platforms. All ddPCR results were achieved with at most 5ng input DNA and as low as 1ng in most cases. However, the concordance begins to weaken below 1% MAF (r2=0.4024), likely due to the limit of detection of the current ddPCR assays. Conclusions: We demonstrated that ddPCR offers a highly sensitive and purely quantitative method to measure low MAF with minimal sample input requirements, which highlights the potential use of ddPCR for MRD monitoring. As one possible MRD monitoring approach, NGS panel-based assays may identify all variants at baseline screening, followed by ddPCR as a complementary solution for MRD monitoring of single variants. Currently, there are ongoing efforts in examining longitudinal ctDNA variant changes in CRC patients receiving treatment to further confirm which variants could be used for MRD monitoring in CRC. Citation Format: Dennis O9Rourke, Danyi Wang, Juergen Scheuenpflug, Zheng Feng. Validation of low fraction allelic variants in plasma samples ","PeriodicalId":10518,"journal":{"name":"Clinical Research (Excluding Clinical Trials)","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82256416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-609
D. Venet, Xiaoxiao Wang, F. Dupont, G. Rouas, L. Stenbeck, A. Mollbrink, D. Larsimont, J. Lundeberg, F. Rothé, C. Sotiriou
{"title":"Abstract 609: Contribution of the tumor and stroma compartments for TNBC molecular classification using spatial transcriptomics analysis","authors":"D. Venet, Xiaoxiao Wang, F. Dupont, G. Rouas, L. Stenbeck, A. Mollbrink, D. Larsimont, J. Lundeberg, F. Rothé, C. Sotiriou","doi":"10.1158/1538-7445.AM2021-609","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-609","url":null,"abstract":"","PeriodicalId":10518,"journal":{"name":"Clinical Research (Excluding Clinical Trials)","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81151277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-591
Tanya Kumar, Hariprasad Thangavel, N. Abdulkareem, Raksha R Bhat, Meghana V. Trivedi
{"title":"Abstract 591: Developing an immunofluorescence assay for detecting Rb and phospho-Rb on circulating tumor cells in breast cancer","authors":"Tanya Kumar, Hariprasad Thangavel, N. Abdulkareem, Raksha R Bhat, Meghana V. Trivedi","doi":"10.1158/1538-7445.AM2021-591","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-591","url":null,"abstract":"","PeriodicalId":10518,"journal":{"name":"Clinical Research (Excluding Clinical Trials)","volume":"90 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82671454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-505
Daniel L Menezes, W. See, A. Risueño, Jianglin Ma, I. L. Torre, B. Skikne, C. Beach, Keshava Kumar, A. Thakurta
{"title":"Abstract 505: Oral azacitidine modulates the immune microenvironment in acute myeloid leukemia (AML) patients in remission: A subanalysis from the QUAZAR AML-001 Trial","authors":"Daniel L Menezes, W. See, A. Risueño, Jianglin Ma, I. L. Torre, B. Skikne, C. Beach, Keshava Kumar, A. Thakurta","doi":"10.1158/1538-7445.AM2021-505","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-505","url":null,"abstract":"","PeriodicalId":10518,"journal":{"name":"Clinical Research (Excluding Clinical Trials)","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80941959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-570
J. Carey, A. Leal, Bryan Chesnick, Denise Butler, Michael A Rongione, Siân Jones, R. Scharpf, Mette Villadsen, S. Bojesen, J. Johansen, C. Feltoft, V. Velculescu, N. Dracopoli
Genome-wide cfDNA fragmentation patterns have previously been demonstrated to distinguish with high sensitivity and specificity between plasma samples from individuals with and without cancer. To further evaluate cfDNA fragmentation as a blood-based screening test for cancer, we have used low coverage whole genome sequencing to analyze plasma samples from 280 patients referred to an advanced diagnostic center due to non-organ specific signs and symptoms of cancer. Within three months of inclusion, 74 of these patients were diagnosed with one of 16 different solid cancers while 206 patients did not have cancer. Using an improved version of our genome-wide cfDNA fragmentation analyses, we observed high performance in distinguishing cancer and non-cancer samples (AUC=0.92, 95% CI 0.88-0.96), including lung cancer (n=12, AUC=0.91, 95% CI 0.80-1.00) and colorectal cancer (n=12, AUC=0.94, 95% CI 0.89-0.99). Although many of the patients in this cohort had other common illnesses including cardiovascular, autoimmune, and inflammatory diseases, the machine learning models of cfDNA fragmentation were able to detect cancer with high sensitivity and specificity. These data support the development of genome-wide cfDNA fragmentation analyses as a non-invasive detection screening approach for both single and multiple cancers. Citation Format: Jacob Carey, Alessandro Leal, Bryan Chesnick, Denise Butler, Michael Rongione, Sian Jones, Rob Scharpf, Mette Villadsen, Stig E. Bojesen, Julia S. Johansen, Claus L. Feltoft, Victor E. Velculescu, Nicholas C. Dracopoli. Detecting cancer using genome-wide cfDNA nucleosomal fragmentation in a prospective multi cancer cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 570.
全基因组cfDNA片段模式先前已被证明具有高灵敏度和特异性区分患有和非癌症个体的血浆样本。为了进一步评估cfDNA片段作为一种基于血液的癌症筛查试验，我们使用低覆盖率全基因组测序分析了280名因非器官特异性癌症体征和症状而转诊到先进诊断中心的患者的血浆样本。在三个月内，这些患者中有74人被诊断出患有16种不同的实体癌之一，而206名患者没有癌症。使用改进版本的全基因组cfDNA片段分析，我们观察到在区分癌症和非癌症样本(AUC=0.92, 95% CI 0.88-0.96)方面的高性能，包括肺癌(n=12, AUC=0.91, 95% CI 0.80-1.00)和结直肠癌(n=12, AUC=0.94, 95% CI 0.89-0.99)。尽管该队列中的许多患者患有其他常见疾病，包括心血管疾病、自身免疫性疾病和炎症性疾病，但cfDNA片段化的机器学习模型能够以高灵敏度和特异性检测癌症。这些数据支持全基因组cfDNA片段分析作为一种非侵入性检测筛查单一和多种癌症的方法的发展。引文格式:Jacob Carey, Alessandro Leal, Bryan Chesnick, Denise Butler, Michael Rongione, Sian Jones, Rob Scharpf, Mette Villadsen, Stig E. Bojesen, Julia S. Johansen, Claus L. Feltoft, Victor E. Velculescu, Nicholas C. Dracopoli。在前瞻性多癌队列中使用全基因组cfDNA核小体片段检测癌症[摘要]。见:美国癌症研究协会2021年年会论文集;2021年4月10日至15日和5月17日至21日。费城(PA): AACR;癌症杂志，2021;81(13 -增刊):摘要第570期。
{"title":"Abstract 570: Detecting cancer using genome-wide cfDNA nucleosomal fragmentation in a prospective multi cancer cohort","authors":"J. Carey, A. Leal, Bryan Chesnick, Denise Butler, Michael A Rongione, Siân Jones, R. Scharpf, Mette Villadsen, S. Bojesen, J. Johansen, C. Feltoft, V. Velculescu, N. Dracopoli","doi":"10.1158/1538-7445.AM2021-570","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-570","url":null,"abstract":"Genome-wide cfDNA fragmentation patterns have previously been demonstrated to distinguish with high sensitivity and specificity between plasma samples from individuals with and without cancer. To further evaluate cfDNA fragmentation as a blood-based screening test for cancer, we have used low coverage whole genome sequencing to analyze plasma samples from 280 patients referred to an advanced diagnostic center due to non-organ specific signs and symptoms of cancer. Within three months of inclusion, 74 of these patients were diagnosed with one of 16 different solid cancers while 206 patients did not have cancer. Using an improved version of our genome-wide cfDNA fragmentation analyses, we observed high performance in distinguishing cancer and non-cancer samples (AUC=0.92, 95% CI 0.88-0.96), including lung cancer (n=12, AUC=0.91, 95% CI 0.80-1.00) and colorectal cancer (n=12, AUC=0.94, 95% CI 0.89-0.99). Although many of the patients in this cohort had other common illnesses including cardiovascular, autoimmune, and inflammatory diseases, the machine learning models of cfDNA fragmentation were able to detect cancer with high sensitivity and specificity. These data support the development of genome-wide cfDNA fragmentation analyses as a non-invasive detection screening approach for both single and multiple cancers. Citation Format: Jacob Carey, Alessandro Leal, Bryan Chesnick, Denise Butler, Michael Rongione, Sian Jones, Rob Scharpf, Mette Villadsen, Stig E. Bojesen, Julia S. Johansen, Claus L. Feltoft, Victor E. Velculescu, Nicholas C. Dracopoli. Detecting cancer using genome-wide cfDNA nucleosomal fragmentation in a prospective multi cancer cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 570.","PeriodicalId":10518,"journal":{"name":"Clinical Research (Excluding Clinical Trials)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83844694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-636
S. Grover, T. Alcindor, J. Berman, J. Chan, A. Denburg, R. Deyell, D. Eisenstat, C. Fernandez, P. Grundy, Abha A. Gupta, C. Hawkins, M. Irwin, N. Jabado, Steven J. M. Jones, M. Moran, D. Morgenstern, S. Rassekh, A. Shlien, D. Sinnett, P. Sorensen, P. Sullivan, Michael D. Taylor, A. Villani, J. Whitlock, D. Malkin
Background: Over 4300 children, adolescents, and young adults (CAYA) are diagnosed with cancer each year in Canada, 1/3 of whom have refractory/metastatic disease or will relapse. A national collaborative program, PRecision Oncology For Young peopLE (PROFYLE), was created with the goal to develop and implement a pipeline providing access to tumor molecular profiling to identify novel targeted treatment options in a clinically relevant timeframe for CAYA with hard-to-treat cancers. Design: PROFYLE unites 21 institutions, building upon 3 pre-existing regional pediatric precision oncology programs (Personalized Oncogenomics (POG), SickKids Cancer Sequencing (KiCS), and Personalized Targeted Therapy in Refractory or Relapsed Cancer in Childhood (TRICEPS)). PROFYLE nodes (genomics/bioinformatics, proteomics, modeling, biomarkers, data/biobanking, therapeutics, bioethics, policy, AYA) are unified by a shared governance structure. PROFYLE includes genomic and transcriptomic sequencing of paired germline/cancer fresh/frozen samples. Inclusion criteria: ≤29y; treatment at a Canadian center; diagnosis of a hard-to-treat cancer. Profiling results are reviewed by multidisciplinary Molecular Tumor Boards. A report including a results/recommendations summary of actionable findings (therapeutic, diagnostic, prognostic, cancer predisposition), potential targeted therapy options including available clinical trials, clarification of diagnosis, and genetic counseling referral is provided to the treating oncologist. Results: To date, >800 CAYA are enrolled in PROFYLE and POG, KiCS, TRICEPS. Cancer diagnoses: 35% sarcoma, 18% leukemia/lymphoma, 14% CNS tumor, 14% neuroblastoma, 19% other. At study entry, 44% of participants had not relapsed, 39% 1 relapse, 14% 2 relapses, and 3% 3+ relapses. 13% had a cancer-predisposing pathogenic/likely pathogenic germline variant, 39% had ≥1 potentially actionable somatic alteration, and 13% had a therapeutically targetable somatic alteration. The most frequent classes of alterations were RAS/MAPK, immune checkpoint, cell cycle, DNA repair, epigenetic, PI3K/AKT/mTOR, RTK. Of clinicians who reported the utility of results, 78% indicated the findings had the potential to inform a medical decision. Future Directions: We will build on PROFYLE9s success by addressing the challenge of real-time availability of target-based therapies through innovative clinical trial strategies incorporating new drugs, off-label use, drug combinations, basket and single patient study designs to enable improved access to therapies for CAYA with actionable molecular targets. We will work on policy-relevant research to facilitate implementation of precision oncology care for CAYA in Canada. We will leverage knowledge developed by PROFYLE thus far by integrating omics, modeling and biomarkers research in the trials being developed. Citation Format: Stephanie A. Grover, Thierry Alcindor, Jason N. Berman, Jennifer A. Chan, Avram E. Denburg, Rebecca J. Deyell,
背景:在加拿大，每年有超过4300名儿童、青少年和年轻人(CAYA)被诊断为癌症，其中1/3患有难治性/转移性疾病或会复发。一个国家合作项目，精准肿瘤学青年(PROFYLE)，其目标是开发和实施一个管道，提供肿瘤分子分析，以确定新的靶向治疗方案，在临床相关的时间框架内，难以治疗的CAYA癌症。设计:PROFYLE联合了21家机构，建立在3个已有的区域儿科精准肿瘤学项目(个性化肿瘤基因组学(POG)、SickKids癌症测序(KiCS)和难治性或复发性儿童癌症个性化靶向治疗(TRICEPS))的基础上。PROFYLE节点(基因组学/生物信息学、蛋白质组学、建模、生物标志物、数据/生物银行、治疗学、生物伦理学、政策、AYA)由共享的治理结构统一。PROFYLE包括配对生殖系/癌症新鲜/冷冻样本的基因组和转录组测序。纳入标准:≤29y;在加拿大中心接受治疗;诊断出一种难以治疗的癌症。谱分析结果由多学科分子肿瘤委员会审查。一份报告，包括结果/建议总结可操作的发现(治疗，诊断，预后，癌症易感性)，潜在的靶向治疗方案，包括可用的临床试验，诊断的澄清，以及提供给治疗肿瘤学家的遗传咨询转诊。结果:迄今为止，PROFYLE和POG、KiCS、肱三头肌共纳入了1,800例CAYA。癌症诊断:35%肉瘤，18%白血病/淋巴瘤，14%中枢神经系统肿瘤，14%神经母细胞瘤，19%其他。在研究开始时，44%的参与者没有复发，39%复发，14%复发，3%复发。13%的人有癌症易感致病性/可能致病性种系变异，39%的人有≥1个潜在可操作的体细胞改变，13%的人有治疗可靶向的体细胞改变。最常见的改变类别是RAS/MAPK、免疫检查点、细胞周期、DNA修复、表观遗传、PI3K/AKT/mTOR、RTK。在报告结果效用的临床医生中，78%的人表示这些发现有可能为医疗决策提供信息。未来方向:我们将在profyle9成功的基础上，通过创新的临床试验策略，包括新药、标签外使用、药物组合、篮子和单患者研究设计，解决基于靶向治疗的实时可用性挑战，从而改善具有可操作分子靶点的CAYA治疗的可及性。我们将开展政策相关研究，促进加拿大CAYA精准肿瘤护理的实施。我们将利用PROFYLE迄今为止开发的知识，将组学、建模和生物标志物研究整合到正在开发的试验中。引文格式:Stephanie A. Grover, Thierry Alcindor, Jason N. Berman, Jennifer A. Chan, Avram E. Denburg, Rebecca J. Deyell, David D. Eisenstat, Conrad V. Fernandez, Paul E. Grundy, Abha Gupta, Cynthia Hawkins, Meredith S. Irwin, Nada Jabado, Steven J. Jones, Michael F. Moran, Daniel A. Morgenstern, Shahrad R. Rassekh, Adam Shlien, Daniel Sinnett, Paul H. Sorensen, Patrick J. Sullivan, Michael D. Taylor, Anita Villani, James A. Whitlock, David Malkin代表Terry Fox PROFYLE联盟。PROFYLE:泛加拿大精确肿瘤学项目，针对患有难以治疗的癌症的儿童、青少年和年轻人。见:美国癌症研究协会2021年年会论文集;2021年4月10日至15日和5月17日至21日。费城(PA): AACR;癌症杂志，2021;81(13 -增刊):636。
{"title":"Abstract 636: PROFYLE: The pan-Canadian precision oncology program for children, adolescents and young adults with hard-to-treat cancer","authors":"S. Grover, T. Alcindor, J. Berman, J. Chan, A. Denburg, R. Deyell, D. Eisenstat, C. Fernandez, P. Grundy, Abha A. Gupta, C. Hawkins, M. Irwin, N. Jabado, Steven J. M. Jones, M. Moran, D. Morgenstern, S. Rassekh, A. Shlien, D. Sinnett, P. Sorensen, P. Sullivan, Michael D. Taylor, A. Villani, J. Whitlock, D. Malkin","doi":"10.1158/1538-7445.AM2021-636","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-636","url":null,"abstract":"Background: Over 4300 children, adolescents, and young adults (CAYA) are diagnosed with cancer each year in Canada, 1/3 of whom have refractory/metastatic disease or will relapse. A national collaborative program, PRecision Oncology For Young peopLE (PROFYLE), was created with the goal to develop and implement a pipeline providing access to tumor molecular profiling to identify novel targeted treatment options in a clinically relevant timeframe for CAYA with hard-to-treat cancers. Design: PROFYLE unites 21 institutions, building upon 3 pre-existing regional pediatric precision oncology programs (Personalized Oncogenomics (POG), SickKids Cancer Sequencing (KiCS), and Personalized Targeted Therapy in Refractory or Relapsed Cancer in Childhood (TRICEPS)). PROFYLE nodes (genomics/bioinformatics, proteomics, modeling, biomarkers, data/biobanking, therapeutics, bioethics, policy, AYA) are unified by a shared governance structure. PROFYLE includes genomic and transcriptomic sequencing of paired germline/cancer fresh/frozen samples. Inclusion criteria: ≤29y; treatment at a Canadian center; diagnosis of a hard-to-treat cancer. Profiling results are reviewed by multidisciplinary Molecular Tumor Boards. A report including a results/recommendations summary of actionable findings (therapeutic, diagnostic, prognostic, cancer predisposition), potential targeted therapy options including available clinical trials, clarification of diagnosis, and genetic counseling referral is provided to the treating oncologist. Results: To date, >800 CAYA are enrolled in PROFYLE and POG, KiCS, TRICEPS. Cancer diagnoses: 35% sarcoma, 18% leukemia/lymphoma, 14% CNS tumor, 14% neuroblastoma, 19% other. At study entry, 44% of participants had not relapsed, 39% 1 relapse, 14% 2 relapses, and 3% 3+ relapses. 13% had a cancer-predisposing pathogenic/likely pathogenic germline variant, 39% had ≥1 potentially actionable somatic alteration, and 13% had a therapeutically targetable somatic alteration. The most frequent classes of alterations were RAS/MAPK, immune checkpoint, cell cycle, DNA repair, epigenetic, PI3K/AKT/mTOR, RTK. Of clinicians who reported the utility of results, 78% indicated the findings had the potential to inform a medical decision. Future Directions: We will build on PROFYLE9s success by addressing the challenge of real-time availability of target-based therapies through innovative clinical trial strategies incorporating new drugs, off-label use, drug combinations, basket and single patient study designs to enable improved access to therapies for CAYA with actionable molecular targets. We will work on policy-relevant research to facilitate implementation of precision oncology care for CAYA in Canada. We will leverage knowledge developed by PROFYLE thus far by integrating omics, modeling and biomarkers research in the trials being developed. Citation Format: Stephanie A. Grover, Thierry Alcindor, Jason N. Berman, Jennifer A. Chan, Avram E. Denburg, Rebecca J. Deyell, ","PeriodicalId":10518,"journal":{"name":"Clinical Research (Excluding Clinical Trials)","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89291885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-446
Yijun Tian, Jong-A Park, Liang Wang
Introduction: Genome-wide association studies (GWAS) along with expression quantitative trait loci (eQTL) have identified hundreds of genetic variants and target genes in prostate cancer (prCa). Although genetic predisposition has mainly been described in prostate cancer (PrCa), functional characterization of these risk loci remains a challenge. Methods: Low multiplicity of infection creates single lentiviral integrated cell population, which enable us to evaluate biological significance of steric hindrance at certain SNP sites in large scale. To screen for regulatory SNP, we designed a guide RNA library to target 2166 potential functional SNP sites with CRISPOR software. We performed negative screening in dCas9-KRAB stable prostate cell lines and applied RIGOR program to discover the SNPs that are essential for cell proliferation. We further validated regulatory role of selected SNPs using luciferase reporter assay, ChIP-qPCR and CRISPR-based SNP editing in prostate cells. Results: After gRNA interfering for 21 days, we performed RIGOR analysis and identified 153 proliferation-essential SNPs, covered by one or multiple prostate cancer cell lines. Intersection analysis showed that these SNPs tended to reside in 59-UTR and intron regions. To characterize regulatory role of these SNPs, we performed functional analysis in a SNP rs60 since prostate cells containing guide RNAs targeting rs60 were significantly depleted (FDR Conclusion: CRISPRi-SNPs-seq is a powerful screening tool to identify regulatory SNPs essential for cell proliferation. In combination with in-depth functional assays, the technology will facilitate discovery of regulatory variants and their genes responsible for disease risk. Citation Format: Yijun Tian, Jong A. Park, Liang Wang. CRISPRi-SNPs-seq identified regulatory loci conferring prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 446.
全基因组关联研究(GWAS)和表达数量性状位点(eQTL)已经在前列腺癌(prCa)中发现了数百种遗传变异和靶基因。虽然遗传易感性主要描述在前列腺癌(PrCa)，功能表征这些风险位点仍然是一个挑战。方法:低感染的多重性形成单一的慢病毒整合细胞群，这使我们能够大规模地评估某些SNP位点的空间阻滞性的生物学意义。为了筛选调控SNP，我们设计了一个引导RNA文库，利用CRISPOR软件靶向2166个潜在的功能SNP位点。我们对dCas9-KRAB稳定的前列腺细胞系进行阴性筛选，并应用RIGOR程序发现细胞增殖所必需的snp。我们在前列腺细胞中使用荧光素酶报告基因检测、ChIP-qPCR和基于crispr的SNP编辑进一步验证了所选SNP的调节作用。结果:在gRNA干扰21天后，我们进行了严格分析，鉴定出153个增殖必需snp，覆盖在一个或多个前列腺癌细胞系中。交叉分析表明，这些snp倾向于位于59-UTR和内含子区域。为了表征这些SNP的调控作用，我们对SNP rs60进行了功能分析，因为含有靶向rs60的引导rna的前列腺细胞显着耗尽(FDR结论:crispr -SNP -seq是鉴定细胞增殖必需的调控SNP的强大筛选工具。结合深入的功能分析，该技术将有助于发现调节变异及其与疾病风险相关的基因。引用格式:田义军，朴钟a，王亮。crispr - snp -seq鉴定了前列腺癌的调控位点[摘要]。见:美国癌症研究协会2021年年会论文集;2021年4月10日至15日和5月17日至21日。费城(PA): AACR;癌症杂志，2021;81(13 -增刊):摘要第446期。
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Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-487
V. Ting, Carmen Chak Lui Wong, Y. Kwong, T. Yau
{"title":"Abstract 487: Genomic difference of CD4 CD8 double-positive T cells versus conventional CD4 T cells and CD8 T cells in responders undergoing immunotherapy in advanced HCC","authors":"V. Ting, Carmen Chak Lui Wong, Y. Kwong, T. Yau","doi":"10.1158/1538-7445.AM2021-487","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-487","url":null,"abstract":"","PeriodicalId":10518,"journal":{"name":"Clinical Research (Excluding Clinical Trials)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89509630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-508
S. Emma, A. Bates, R. Hernandez, J. Grudzinski, I. Marsh, J. Jagodinsky, B. Bednarz, A. Pieper, Elizabeth G. Sumiec, E. Nystuen, G. A. Sosa, Ravi B. Patel, J. Weichert, Z. Morris
{"title":"Abstract 508: Mechanisms of cooperative response to bempegaldesleukin (BEMPEG) and90Y-NM600 targeted radionuclide therapy in the treatment of a syngeneic murine model of head and neck squamous cell carcinoma","authors":"S. Emma, A. Bates, R. Hernandez, J. Grudzinski, I. Marsh, J. Jagodinsky, B. Bednarz, A. Pieper, Elizabeth G. Sumiec, E. Nystuen, G. A. Sosa, Ravi B. Patel, J. Weichert, Z. Morris","doi":"10.1158/1538-7445.AM2021-508","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-508","url":null,"abstract":"","PeriodicalId":10518,"journal":{"name":"Clinical Research (Excluding Clinical Trials)","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89531011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-571
Catalin C. Barbacioru, Han-Yu Chuang, R. Nagy, Darya I. Chudova, Amirali Talasaz
Background: Several computational methods have been developed to identify copy number alterations (CNA) leading to or associated with cancer development and shown in recent studies to precede cancer diagnosis by many years. Current methods involving cell-free DNA (cfDNA) targeted sequencing data are based on the depth of coverage of on-target or off-target regions, whereas computational methods incorporating germline SNP information for making inferences on copy number alterations and tumor fraction remain underdeveloped. Methods: Using sequencing data from a large database of more than 100k clinical cell-free DNA (cfDNA) patient samples (Guardant Health, CA), we developed a probabilistic model to simultaneously normalize molecular coverage, segment the genome, predict copy number alterations, and estimate the tumor content in cfDNA samples, while accounting for mixtures of cell populations. The model is using off-target and on-target coverage. Copy number status, including loss of heterozygosity (LoH), is inferred in order to predict gene level somatic CNAs or genome wide instability/LoH. Results: We demonstrated the improvement from the off-target incorporation in three aspects. First, to estimate sensitivity improvement in detections of CNAs, we simulated deletions and amplifications of regions exceeding 40 Mb, using coverage and MAF variability observed in existing data. Combining coverage of on-target and off-target regions is expected to improve the LoD for detection of CNAs by 20%, when compared to CNA detection from on-target coverage. Next, we obtained samples from 15,618 cancer patients of different cancer types processed on GuardantOMNI® RUO and determined human leukocyte antigen (HLA) allele-specific copy number using this off-target assisted method. We observed a high prevalence (more than 15%) of LoH in HLA in bladder cancer, prostate cancer, NSCLC and HNSC, consistent with previous studies that HLA LOH is a common feature of several cancer types and diminishes immunotherapy efficacy. Finally, tumor fraction (TF) estimate was validated by comparing the TF against the maximum variant allele fraction of known oncogenic driver mutations in 6,000 cancer cases of various types. High concordance was observed in CRC samples (R2=0.75), gastric cancer (R2=0.63) and bladder cancer (R2=0.6), which suggest the use of this metric to better estimate tumor shedding levels in cfDNA in cases when driver mutations are not represented on a targeting panel. Conclusion: Our results show that probabilistic modeling of coverage data generated from both on-target and off-target cfDNA sequencing can detect gene specific or whole genome level somatic copy number alterations and LoH. This method may enable improvements in CNA detection accuracy, sensitivity, and specificity in plasma and provides more precise interrogation of LoH status and tumor fraction. Citation Format: Catalin Barbacioru, Han-Yu Chuang, Rebecca Nagy, Darya Chudova, AmirAli Talasaz. Detect
{"title":"Abstract 571: Detection of somatic copy number alterations from on-target and off-target sequencing data","authors":"Catalin C. Barbacioru, Han-Yu Chuang, R. Nagy, Darya I. Chudova, Amirali Talasaz","doi":"10.1158/1538-7445.AM2021-571","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-571","url":null,"abstract":"Background: Several computational methods have been developed to identify copy number alterations (CNA) leading to or associated with cancer development and shown in recent studies to precede cancer diagnosis by many years. Current methods involving cell-free DNA (cfDNA) targeted sequencing data are based on the depth of coverage of on-target or off-target regions, whereas computational methods incorporating germline SNP information for making inferences on copy number alterations and tumor fraction remain underdeveloped. Methods: Using sequencing data from a large database of more than 100k clinical cell-free DNA (cfDNA) patient samples (Guardant Health, CA), we developed a probabilistic model to simultaneously normalize molecular coverage, segment the genome, predict copy number alterations, and estimate the tumor content in cfDNA samples, while accounting for mixtures of cell populations. The model is using off-target and on-target coverage. Copy number status, including loss of heterozygosity (LoH), is inferred in order to predict gene level somatic CNAs or genome wide instability/LoH. Results: We demonstrated the improvement from the off-target incorporation in three aspects. First, to estimate sensitivity improvement in detections of CNAs, we simulated deletions and amplifications of regions exceeding 40 Mb, using coverage and MAF variability observed in existing data. Combining coverage of on-target and off-target regions is expected to improve the LoD for detection of CNAs by 20%, when compared to CNA detection from on-target coverage. Next, we obtained samples from 15,618 cancer patients of different cancer types processed on GuardantOMNI® RUO and determined human leukocyte antigen (HLA) allele-specific copy number using this off-target assisted method. We observed a high prevalence (more than 15%) of LoH in HLA in bladder cancer, prostate cancer, NSCLC and HNSC, consistent with previous studies that HLA LOH is a common feature of several cancer types and diminishes immunotherapy efficacy. Finally, tumor fraction (TF) estimate was validated by comparing the TF against the maximum variant allele fraction of known oncogenic driver mutations in 6,000 cancer cases of various types. High concordance was observed in CRC samples (R2=0.75), gastric cancer (R2=0.63) and bladder cancer (R2=0.6), which suggest the use of this metric to better estimate tumor shedding levels in cfDNA in cases when driver mutations are not represented on a targeting panel. Conclusion: Our results show that probabilistic modeling of coverage data generated from both on-target and off-target cfDNA sequencing can detect gene specific or whole genome level somatic copy number alterations and LoH. This method may enable improvements in CNA detection accuracy, sensitivity, and specificity in plasma and provides more precise interrogation of LoH status and tumor fraction. Citation Format: Catalin Barbacioru, Han-Yu Chuang, Rebecca Nagy, Darya Chudova, AmirAli Talasaz. Detect","PeriodicalId":10518,"journal":{"name":"Clinical Research (Excluding Clinical Trials)","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90005902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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