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

• 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
• 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

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 种最常用的处方药物中，只有 6 种对大多数患者非常有效，5 种 效果不大，6 几乎没有临床效果。更糟糕的是，因治疗而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 基因序列及其疾病。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 基因。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未知。 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）存在潜在改变生活的医学、伦理、 法律和社会并发症。有些药物会导致药物对不同患者的疗效或多或少。其他人可以 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应。与同类技术相比， 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 具有临床重要性的变异。在目标 1 中，我们将创建一组 GigaAssay 细胞系和读数 快速分析多种功能性细胞活动。在目标 2 中，我们将演示 GigaAssay 可以检测 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。