Bioinformatics: Characterizing Brain Tumor Data

生物信息学：表征脑肿瘤数据

基本信息

批准号：
10926324
负责人：
Mark Gilbert
金额：
$ 89.5万
依托单位：
DIVISION OF BASIC SCIENCES - NCI
依托单位国家：
美国
项目类别：
财政年份：
资助国家：
美国
起止时间：
至
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10926324
关键词：
Acceleration Animals Area Belief Big Data Biochemical Pathway Bioinformatics Biological Biological Process Biology Biomedical Research Blood specimen Brain Neoplasms Cancer Genome Anatomy Project Cancer Research Project Cell Line Cells Central Nervous System Neoplasms Chordoma Classification Clinical Data Clinical Trials Collaborations Collection Complex Computer Analysis DNA DNA Sequence DNA biosynthesis Data Data Analyses Databases Decision Making Development Disease Enrollment Evolution Explosion Formalin Freezing Functional disorder Funding Gene Expression Profile Gene Expression Profiling Generations Genes Genetic Genomic Data Commons Genomics Glioma Human Human Genome Project Hybrids Impact evaluation In Vitro Information Storage Laboratories Link Mainstreaming Malignant Neoplasms Malignant neoplasm of central nervous system Maps MicroRNAs Microarray Analysis Mining Modality Molecular Molecular Analysis Monitor Morphology Natural History Nature Nucleic Acids Paraffin Embedding Patients Pattern Pharmacotherapy Phenotype Process Proteins Proteomics RNA RNA chemical synthesis Research Research Personnel Resolution Resources Sampling Science Signal Transduction Pathway Source System Techniques Technology The Cancer Genome Atlas Therapeutic Time Tissue Sample Tissues Translating Treatment Efficacy Tumor Biology Tumor Tissue Variant Work analytical tool bioinformatics tool cDNA Arrays cell behavior clinical care clinical practice companion diagnostics data acquisition data streams data warehouse design differential expression driving force drug development genome wide methylation genome-wide histone methylation improved in vivo laboratory experiment mRNA Translation metabolomics methylation pattern molecular diagnostics molecular targeted therapies neuro-oncology novel novel therapeutics older patient participant enrollment patient prognosis patient stratification peripheral blood precision medicine programs prospective protein aminoacid sequence protein distribution sample collection small molecule stem cells therapeutic biomarker therapeutic target three dimensional structure transcriptomics treatment response treatment stratification user-friendly whole genome

项目摘要

As a hybrid science that links biological data with techniques for information storage, distribution, and analysis to support multiple areas of scientific research, including biomedicine, Bioinformatics has been driven by the great acceleration in data-generation processes in biology. The NOB for the past years has enrolled over 1000 patients on the Natural History study which mandates the collection of tumor tissue as well as peripheral blood samples for germline DNA. This includes an unprecedented number of patients with rare CNS cancers. Moreover, the sample collection is accompanied by careful and prospective clinical data acquisition, allowing an unprecedented wealth of matched molecular and clinical data permitting a wide variety of analyses. Advances in the molecular analysis of genes, proteins and metabolites have greatly improved our understanding of biological processes and disease and have increased our ability to monitor treatment response and stratify patients to improve treatment efficacy. Precision medicine facilitated by companion diagnostics is one of the driving forces accelerating the drug development process and improving therapeutic management. Launched in 2016, the NCI Genomic Data Commons (GDC) provides a single source for data from NCI initiatives and cancer research projects, including TCGA and TARGET, and the analytical tools needed to mine them. The new initiated NOB Bioinformatics has extended our bioinformatics and computational analyses efforts to utilize the GDC databases. For example, using the TCGA data effectively doubles the number of GBMs we have to work with and affords us the advantage of formulating computationally derived hypothesis based on one database with the ability to validate those hypotheses on a totally different database. For example, a significant amount of time has been spent by NOB Bioinformatics on the databases to try and understand the biologically basis for the more aggressive phenotype and thus shorter survival of GBMs from older patients compared to those of younger GBMs. To date we have found a very interesting set of differentially expressed genes and miRNAs as well as specific genome wide methylation patterns and specific chromosomal number variants that differentiate older versus younger GBMs. We are in the process of using some of these findings to perform wet lab experiments to better annotate the significance of these findings. Furthermore, in collaborated with NCI ClinOmics (now COMPASS) program we analyzed and created genomic profiling data from the rare CNS tumors, such as chordomas, and dissected signal transduction pathways, and aided in the design of novel therapeutics. In addition to characterizing the samples from patients enrolled, the NOB Bioinformatics has generated genomic-scale analyses of the many human glioma initiating cells/glioma stem cells (GIC/GSC) lines produced in laboratory. This characterization is both at the primary cell level (including evolution through passages) as well as evaluation of the impact of different treatments (differentiation, animal passages, drug treatment, etc) on the biological behavior of the cells.

作为一门将生物数据与信息存储、分发和分析技术联系起来以支持包括生物医学在内的多个科学研究领域的混合科学，生物信息学一直受到生物学数据生成过程的极大加速的推动。过去几年，NOB 已招募了 1000 多名患者参加自然历史研究，该研究要求收集肿瘤组织以及外周血样本以获取种系 DNA。其中包括数量空前的罕见中枢神经系统癌症患者。此外，样本收集还伴随着仔细和前瞻性的临床数据采集，从而获得了前所未有的丰富的匹配分子和临床数据，从而可以进行广泛的分析。基因、蛋白质和代谢物分子分析的进步极大地提高了我们对生物过程和疾病的理解，并提高了我们监测治疗反应和对患者进行分层以提高治疗效果的能力。伴随诊断促进的精准医疗是加速药物开发过程和改善治疗管理的驱动力之一。 NCI 基因组数据共享 (GDC) 于 2016 年推出，为 NCI 倡议和癌症研究项目（包括 TCGA 和 TARGET）的数据提供单一来源，以及挖掘这些数据所需的分析工具。新启动的 NOB 生物信息学扩展了我们的生物信息学和计算分析工作，以利用 GDC 数据库。例如，使用 TCGA 数据有效地使我们必须使用的 GBM 数量增加一倍，并为我们提供了基于一个数据库制定计算得出的假设的优势，并且能够在完全不同的数据库上验证这些假设。例如，NOB 生物信息学在数据库上花费了大量时间，试图了解更具侵袭性的表型的生物学基础，从而与年轻患者相比，老年患者的 GBM 的生存期更短。迄今为止，我们已经发现了一组非常有趣的差异表达基因和 miRNA，以及特定的全基因组甲基化模式和区分老年和年轻 GBM 的特定染色体数量变异。我们正在利用其中一些发现进行湿实验室实验，以更好地诠释这些发现的重要性。此外，我们与 NCI ClinOmics（现为 COMPASS）项目合作，分析并创建了脊索瘤等罕见中枢神经系统肿瘤的基因组分析数据，并剖析了信号转导通路，并协助设计新型疗法。除了对入组患者的样本进行表征之外，NOB 生物信息学还对实验室产生的许多人类神经胶质瘤起始细胞/神经胶质瘤干细胞 (GIC/GSC) 系进行了基因组规模分析。这种表征既在原代细胞水平上（包括传代进化），也评估不同处理（分化、动物传代、药物处理等）对细胞生物学行为的影响。

项目成果

期刊论文数量（4）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Synthetic lethality-mediated precision oncology via the tumor transcriptome.

通过肿瘤转录组进行合成致死介导的精准肿瘤学。

DOI：
发表时间：
2021
期刊：
影响因子：
64.5
作者：
Lee, Joo Sang;Nair, Nishanth Ulhas;Dinstag, Gal;Chapman, Lesley;Chung, Youngmin;Wang, Kun;Sinha, Sanju;Cha, Hongui;Kim, Dasol;Schperberg, Alexander V;Srinivasan, Ajay;Lazar, Vladimir;Rubin, Eitan;Hwang, Sohyun;Berger, Raanan;Beker, Tuvik;R
通讯作者：
R

A critical analysis of neuro-oncology clinical trials.

神经肿瘤学临床试验的批判性分析。