Clinical Research (Excluding Clinical Trials)最新文献

{"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}

{"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}

{"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}

{"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}

{"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}

{"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}

{"title":"Abstract 446: CRISPRi-SNPs-seq identified regulatory loci conferring prostate cancer","authors":"Yijun Tian, Jong-A Park, Liang Wang","doi":"10.1158/1538-7445.AM2021-446","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-446","url":null,"abstract":"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.","PeriodicalId":10518,"journal":{"name":"Clinical Research (Excluding Clinical Trials)","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89467950","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}

{"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}

{"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}

{"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}