High-throughput functional analysis and clinical relevance of all possible variants of a gene

基因所有可能变异的高通量功能分析和临床相关性

基本信息

批准号：
10601908
负责人：
Martin Schiller
金额：
$ 39.85万
依托单位：
HELIGENICS INC
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-02-02 至 2025-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10601908
关键词：
Acute Address Affect American Amino Acid Substitution Biochemical Bioinformatics Biological Biological Assay Biology Biotechnology Cause of Death Cell Cycle Progression Cell Line Cells Cessation of life Climacteric Clinical Clinical Trials Code Data Detection Development Disease Doxycycline Drug Prescriptions Drug Targeting Drug resistance Drug usage ERBB2 gene Enhancers Ethics Expression Library FDA approved Future Genes Genetic Genetic Variation Genome Genomics Goals Growth HIV Health Human Human Genetics Human Genome Legal Lentivirus Vector Libraries Life MAP Kinase Gene MCF7 cell Malignant Epithelial Cell Measures Medical Medical Genetics Methods Modernization Morbidity - disease rate NF-kappa B National Human Genome Research Institute Newborn Infant Patients Persons Pharmaceutical Preparations Pharmacologic Substance Phase Positioning Attribute Production Prognosis Protein Tyrosine Kinase Proteins Quality of life RNA Splicing Recommendation Reporter Reporting Reproducibility Resistance Services Signal Transduction Small Business Innovation Research Grant Speed Stimulation of Cancer Cell Growth Structure Surveys Technology Testing Therapeutic Transfection Tyrosine Kinase Domain Tyrosine Kinase Inhibitor United States United States National Institutes of Health Variant Viral Work cDNA Library chemotherapy clinical effect clinical trial analysis clinically relevant clinically significant cost design disease diagnosis dosage drug action drug development drug efficacy feasibility testing genetic element genetic testing genetic variant improved innovation interest medical schools mortality mutant novel novel strategies novel therapeutics promoter public database resistance mutation response screening trait transcription factor variant of unknown significance

项目摘要

Modern pharmaceuticals have greatly improved the quality of life for many patients suffering a variety of illnesses. Unfortunately, among the 17 most commonly prescribed drugs, only 6 are highly effective for most patients, 5 have a modest effect, and 6 show little clinical effect. Worse still, unwanted illness and death from treatment of patients with the incorrect drug or dosage causes over 275,000 unnecessary deaths annually in the United States, making it the 3rd-leading cause of death. Genomic screening can minimize the loss of lives by clearly defining the cause-and-effect between a patient’s genetic sequence and their disease. Many gene sequences are known to affect a person’s response to drugs. The FDA lists over 450 warnings or recommendations for drug use based on possible genetic variants in specific genes. Other public databases list ~60,000 “characterized” gene variants, but their importance is often unknown. Moreover, these variants represent a vanishingly small fraction of >900 million known human genetic variations. The vast number of “Variants of Uncertain Significance” (VUS) present potentially life-altering medical, ethical, legal, and societal complications. Some cause drugs to be more or less effective in different patients. Others can stimulate growth of cancer cells or make those cells resistant to chemotherapies. To understand the biological impact of gene variants, Heligenics has developed the GigaAssay™ technology to measure the functional effect of all variations within any selected gene. In contrast to similar technologies, the GigaAssay reports the activity of each variant of the gene, with high accuracy and reproducibility. In this proposal, we plan to improve the GigaAssay and show its feasibility for detection and analysis of gene variants that have clinical importance. In Aim 1 we will create a battery of GigaAssay cell lines and readouts for rapid analysis of several functional cellular activities. In Aim 2 we will demonstrate that the GigaAssay can detect gene variants that cause resistance to an FDA-approved chemotherapy drug. This work will directly address numerous goals of the “Illuminating the Druggable Genome” project of the NIH. Future plans include expanding the number of GigaAssays, increasing the speed or number of genes that can be studied, and partnering with drug developers and clinical trial managers to identify the optimal drug for each patient, based on his or her genetic variants.

现代药物极大地改善了许多患有各种疾病的患者的生活质量。不幸的是，在 17 种最常用的处方药中，只有 6 种对大多数患者非常有效，5 种效果有限，而且 6 例几乎没有临床效果，更糟糕的是，治疗过程中会导致不必要的疾病和死亡。在美国，服用错误药物或剂量的患者每年导致超过 275,000 例不必要的死亡州，使其成为第三大死因。基因组筛查可以通过明确定义患者的症状之间的因果关系来最大程度地减少生命损失已知许多基因序列会影响人对药物的反应。 FDA 根据特定人群中可能的基因变异列出了 450 多种药物使用警告或建议其他公共数据库列出了约 60,000 个“特征化”基因变体，但它们的重要性往往是未知的。此外，这些变异仅代表超过 9 亿已知人类遗传变异中的极小一部分。大量的“意义不确定的变体”（VUS）呈现出潜在的改变生活的医学、伦理、一些法律和社会并发症会导致药物对不同的患者或多或少有效。刺激癌细胞生长或使这些细胞对化疗产生抵抗力。为了了解基因变异的生物学影响，Heligenics 开发了 GigaAssay™ 技术测量任何选定基因内所有变异的功能效果与类似技术相比， GigaAssay 报告基因每个变体的活性，具有高精度和可重复性。在本提案中，我们计划改进 GigaAssay 并展示其用于基因检测和分析的可行性在目标 1 中，我们将创建一组 GigaAssay 细胞系和读数。在目标 2 中，我们将证明 GigaAssay 可以检测多种功能性细胞活动。导致对 FDA 批准的化疗药物产生耐药性的基因变异。这项工作将直接实现 NIH“阐明可药物基因组”项目的众多目标。未来的计划包括扩大 GigaAssay 的数量、提高速度或基因数量进行研究，并与药物开发商和临床试验管理者合作，以确定每种药物的最佳药物患者，根据他或她的基因变异。