Identifying neuroblastoma drivers and bringing them to the clinic

识别神经母细胞瘤驱动因素并将其带到诊所

基本信息

批准号：
10197505
负责人：
STEPHEN X SKAPEK
金额：
$ 43.74万
依托单位：
UT SOUTHWESTERN MEDICAL CENTER
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：
2021-04-02 至 2024-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10197505
关键词：
11q 17q Algorithmic Analysis Bayesian Method Biological Biological Markers Biology Biometry Cell Line Cells Child Clinic Clinical Clinical Trials Clustered Regularly Interspaced Short Palindromic Repeats Combined Modality Therapy Communities Computational algorithm Copy Number Polymorphism Data Development Disease Gene Dosage Gene Expression Gene Expression Profiling Genes Genomic approach Genomics Goals Leadership Link MYCN gene Malignant Childhood Neoplasm Malignant Neoplasms Modeling Molecular Molecular Biology Molecular Genetics Mutate Mutation Neuroblastoma Nucleotides Oncogenic Outcome Parents Patients Pattern Pediatric Oncology Group Positioning Attribute Pre-Clinical Model Preclinical Testing Proteins Recurrence Research Research Personnel Rhabdomyosarcoma Risk Scientist Solid Testing Translating Tumor Suppressor Proteins Validation Work base candidate validation childhood cancer mortality cohort computational pipelines disorder risk effective therapy functional genomics genomic data high risk improved improved outcome innovation insight molecular targeted therapies mutant neuroblastoma cell new therapeutic target next generation sequencing novel novel strategies patient derived xenograft model precision medicine programs risk stratification stem success targeted biomarker tool tumor virtual young adult

项目摘要

Project Summary Our overall goal is to improve outcomes for children with forms of cancer that cannot be eradicated with current therapies. We are focused on neuroblastoma, an especially challenging form of childhood cancer that accounts for a large proportion of childhood cancer deaths each year, and we have assembled a team to explore a new approach in which a novel computational pipeline is applied to existing genomics data and a functional genomics screen to reveal new insights into neuroblastoma biology. We anticipate that new biomarkers for risk stratification and assignment of molecularly targeted therapy will stem from our work. In the US each year, over 700 children and young adults develop neuroblastoma, among the most common solid malignancies in children. Sadly, the chance of cure is low for those with high-risk disease, and this bleak outlook has only modestly improved with the application of multifaceted therapies in recent years. New molecular biology and molecular genetics tools at the close of the last century brought new insights into the underpinnings of neuroblastoma, including the fact that copy-number gain in the MYCN gene is among the most important determinants of biologic risk. However, that has not been translated into better treatment and other molecular derangements contribute to poor chances of survival for children with this disease. Many clinicians, scientists, and patients and their parents anticipated that the more recent genomics revolution would usher in “precision” medicine focused on the mutant forms of proteins anticipated to drive the disease. That promise has not been fully realized in cancers like neuroblastoma that lack highly-recurrent, targetable mutations. Our team came together to explore a new approach to help close this gap. Given the few recurrent mutations in this disease, we are considering neuroblastoma to be a cancer in which normal developmental programs are corrupted by altered gene expression and that the altered gene expression is often “hard-wired” into the cell by gains and losses in the copies of the genes encoding oncogenic drivers and tumor suppressors. We exploring the capacity for a new computational algorithm to identify those cancer drivers/suppressors using existing genomic datasets. Second, we propose to use a focused but high-throughput cell-based screen to quickly provide functional validation of the candidate neuroblastoma drivers. Finally, we are using this information to develop a new biologically-based tool for assigning risk and guiding treatment assignment for children with neuroblastoma. If successful, we can extend this developmental model to other forms of childhood cancer.

项目概要我们的总体目标是改善患有目前无法根除的癌症的儿童的治疗结果我们专注于神经母细胞瘤，这是一种特别具有挑战性的儿童癌症形式。每年有很大一部分儿童癌症死亡，我们组建了一个团队来探索新的方法将新颖的计算管道应用于现有基因组学数据和功能基因组学的方法我们期望通过筛选揭示神经母细胞瘤生物学的新见解。分子靶向治疗的分配将源于我们的工作。在美国，每年有超过 700 名儿童和年轻人患上神经母细胞瘤，这是最常见的实体瘤之一可悲的是，患有高危疾病的人治愈的机会很低，而且前景黯淡。近年来，随着新分子生物学的应用，这种情况仅略有改善。上世纪末的分子遗传学工具为人类的基础带来了新的见解。神经母细胞瘤，其中 MYCN 基因的拷贝数增加是最重要的因素之一然而，这还没有转化为更好的治疗和其他分子手段。精神错乱导致患有这种疾病的儿童的生存机会很低。患者及其父母预计最近的基因组学革命将迎来“精准” 医学重点关注预期会导致这种疾病的蛋白质突变形式，但这一承诺并未实现。在神经母细胞瘤等缺乏高度复发性、可靶向突变的癌症中得到了充分实现。鉴于很少出现复发性突变，我们的团队齐心协力探索一种新方法来帮助缩小这一差距。对于这种疾病，我们认为神经母细胞瘤是一种癌症，其中正常发育程序受到影响被改变的基因表达所破坏，并且改变的基因表达通常通过以下方式“硬连接”到细胞中：我们探索编码致癌驱动因素和肿瘤抑制因素的基因拷贝的增加和减少。新的计算算法能够利用现有的技术来识别那些癌症驱动因素/抑制因素其次，我们建议使用集中但高通量的基于细胞的筛选来快速进行。最后，我们使用这些信息来验证候选神经母细胞瘤驱动因素。开发一种新的基于生物学的工具，用于分配风险并指导患有以下疾病的儿童的治疗分配如果成功，我们可以将这种发育模型扩展到其他形式的儿童癌症。

项目成果

期刊论文数量（3）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Dissecting embryonic and extra-embryonic lineage crosstalk with stem cell co-culture.

通过干细胞共培养剖析胚胎和胚胎外谱系串扰。

DOI：
发表时间：
2023-03-08
期刊：
影响因子：
0
作者：
Wei, Yulei;Zhang, E;Yu, Leqian;Ci, Baiquan;Guo, Lei;Sakurai, Masahiro;Takii, Shino;Liu, Jian;Schmitz, Daniel A;Ding, Yi;Zhan, Linfeng;Zheng, Canbin;Sun, Hai;Xu, Lin;Okamura, Daiji;Ji, Weizhi;Tan, Tao;Wu, Jun
通讯作者：
Wu, Jun

Dissecting embryonic and extraembryonic lineage crosstalk with stem cell co-culture.

通过干细胞共培养剖析胚胎和胚胎外谱系串扰。

DOI：
发表时间：
2023-12-21
期刊：
影响因子：
64.5
作者：
Wei, Yulei;Zhang, E;Yu, Leqian;Ci, Baiquan;Sakurai, Masahiro;Guo, Lei;Zhang, Xin;Lin, Sirui;Takii, Shino;Liu, Lizhong;Liu, Jian;Schmitz, Daniel A;Su, Ting;Zhang, Junmei;Shen, Qiaoyan;Ding, Yi;Zhan, Linfeng;Sun, Hai;Zheng, Canbin;Xu
通讯作者：
Xu

Reconstructing Spatial Transcriptomics at the Single-cell Resolution with BayesDeep.

使用 BayesDeep 以单细胞分辨率重建空间转录组学。