Molecular Profiling and Bioinformatics

分子分析和生物信息学

基本信息

批准号：
10696184
负责人：
MICHAEL E. BERENS
金额：
$ 17.52万
依托单位：
BECKMAN RESEARCH INSTITUTE/CITY OF HOPE
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-13 至 2026-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10696184
关键词：
Accreditation Adoption Aftercare Alleles Aneuploidy Anti-CD47 Antibodies Beds Bioinformatics Biological Products CLIA certified Catheters Cell Nucleus Cells Certification Characteristics Cities Clinic Clinical Clinical Data Clinical Trials Collaborations Consultations DNA sequencing Data Data Analytics Data Reporting Data Set Decision Making Development Effectiveness Eligibility Determination Engineering Enrollment Ensure Etoposide Evolution Excision Fostering Future Gene Expression Profiling Genes Genomics Glioblastoma Glioma Goals Harvest Herpesviridae Herpesviridae Infections Individual Infection Infiltration Infrastructure Intervention Laboratories Lead Liquid substance Loss of Heterozygosity Lymphocyte Machine Learning Manuscripts Methods Microdialysis Mission Modeling Molecular Molecular Profiling Mus Mutation Normal tissue morphology Oncolytic Oncolytic viruses Operative Surgical Procedures PTEN gene Patient Care Patients Phenotype Population Pre-Clinical Model Predisposition Process RNA Research Research Personnel Research Project Grants Resistance Resources Running Sampling Secure Services Simplexvirus Single Nucleotide Polymorphism Specimen Surgically-Created Resection Cavity TOP2A gene Techniques Technology Testing The Cancer Genome Atlas Therapeutic Therapeutic Intervention Tissue-Specific Gene Expression Tissues Transcript Tumor Tissue Variant Work Writing bioinformatics pipeline bioinformatics tool biomedical informatics design exome exome sequencing experimental study feature selection genomic data genomic profiles immune cell infiltrate immunological status immunopharmacology improved improved outcome inhibitor insight novel participant enrollment patient derived xenograft model pre-clinical preclinical study programs response small molecule inhibitor synergism transcriptome transcriptome sequencing transcriptomics tumor tumor heterogeneity tumor-immune system interactions

项目摘要

PROJECT SUMMARY – CORE B The U19 Molecular Profiling and Bioinformatics Core (Core B) will provide state-of-the-art genomics and bioinformatics technology and expertise to advance each of the projects in the City of Hope U19 program. In anticipation of delivering on the larger mission of the Glioblastoma Translational Network (GTN), Core B will provide CAP-certified, CLIA-approved exome and transcriptome sequencing that returns data for patient care decision-making. Core B bridges bench discovery of molecular determinants of glioblastoma vulnerability to the three novel agents in this U19 and the clinical setting, in which precision use of these treatments may have the highest likelihood of benefiting patients. Core B will achieve this by: A) Providing comprehensive CLIA-certified genomic profiling for patients enrolled on our U19 clinical trials, as well as genomic sequencing of preclinical models, and offering single cell/nuclei transcriptomic analyses of harvested cell infiltrates collected from the tumor bed following resection or dispersed tissue. These studies will provide granular insight into tumor heterogeneity, tumor sensitivity or resistance, and tumor evolution. B) Identifying signatures of vulnerability to the agents being evaluated. For Project 1, GBM exome and transcriptomic data will be analyzed to identify features that modify susceptibility to oncolytic herpes virus infection, the impact of alleles of genes that play a role in HSV replication, and deconvolution of patient tumors to depict the host cell infiltrate comprising the pretreatment microenvironment immune status of syngeneic models and glioma patients enrolled in the oncolytic virus/anti CD-47 clinical trial. For Project 2, exome and transcriptome data from tumors of patients enrolled in the clinical trial evaluating tasquinimod will be deconvoluted to discern populations of immune cell infiltrates to compare with post-treatment single cell transcriptomic analysis of resection cavity fluid collected from surgically placed catheters. Tumors from syngeneic glioma models receiving different treatments will analyzed by single nuclei transcriptomics for cell deconvolution. For Project 3, we will further develop a synergy signature indicative of GBM vulnerability to the combination of pevonedistat + etoposide, leading to a patient-enrichment strategy for future clinical trials. Preliminary data indicates that PTEN status (copy number, mutation, expression levels) serves as a determinant for likelihood of response to the neddylation inhibitor, pevonedistat, as well as the synergistic activity of etoposide (TOP2A inhibitor) with pevonedistat. C). Deliver state-of-the-art biomedical informatics and data analytics expertise and services. Core B will provide state-of-the-art bioinformatics methods, including machine learning techniques, to derive highest value from the preclinical and clinical data in each project. Core B will also foster data and information exchange and collaboration with individual Projects/Cores across the GTN. The long term goal of Core B is to participate in the design, development, and adoption of an adaptive, signature-guided umbrella clinical trial supporting all new treatments emerging from the GTN.

项目摘要 – 核心 B U19 分子分析和生物信息学核心（核心 B）将提供最先进的基因组学和生物信息学技术和专业知识来推进希望之城 U19 计划中的每个项目。为了实现胶质母细胞瘤转化网络 (GTN) 的更大使命，Core B 将提供经过 CAP 认证、CLIA 批准的外显子组和转录组测序，为患者护理返回数据核心 B 将胶质母细胞瘤易感性的分子决定因素的发现与 U19 和临床环境中的三种新型药物，其中这些治疗的精确使用可能会产生核心 B 将通过以下方式实现这一目标：A) 提供全面的 CLIA 认证。为参加我们的 U19 临床试验的患者进行基因组分析，以及临床前的基因组测序模型，并提供从收集的收获细胞浸润物的单细胞/核转录组分析切除或分散组织后的肿瘤床这些研究将提供对肿瘤的详细了解。异质性、肿瘤敏感性或耐药性以及肿瘤进化 B) 识别脆弱性的特征。对于项目 1，将分析 GBM 外显子组和转录组数据来识别。改变对溶瘤疱疹病毒感染易感性的特征，发挥作用的基因等位基因的影响在 HSV 复制中的作用，以及对患者肿瘤进行解卷积以描述宿主细胞浸润，包括同基因模型和参加溶瘤治疗的胶质瘤患者的治疗前微环境免疫状态对于项目 2，来自参与的患者肿瘤的外显子组和转录组数据。评估他喹莫德的临床试验将进行解卷积，以识别免疫细胞浸润的群体与手术收集的切除腔液的治疗后单细胞转录组分析进行比较接受不同治疗的同基因神经胶质瘤模型放置的肿瘤将通过单个导管进行分析。对于项目 3，我们将进一步开发指示性协同特征。 GBM 对 pevonedistat + 依托泊苷组合的脆弱性，从而导致患者丰富策略未来的临床试验初步数据表明PTEN状态（拷贝数、突变、表达水平）。作为对 neddylation 抑制剂、pevonedistat 以及依托泊苷（TOP2A 抑制剂）与 pevonedistat C) 的协同活性。信息学和数据分析专业知识和服务将提供最先进的生物信息学方法，包括机器学习技术，从每个领域的临床前和临床数据中获得最高价值核心 B 还将促进与各个项目/核心的数据和信息交换与协作。 Core B 的长期目标是参与 GTN 的设计、开发和采用。适应性、签名引导的伞形临床试验支持 GTN 中出现的所有新疗法。