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

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 rt900 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.