Biology subjects

Oh, E. C.

Publications and source records attributed to Oh, E. C..

3 recordsLinked to original sources

bioRxiv2024

CYP3A5 inhibition causes G1/S blockade and synergizes with CDK4/6 inhibitor to suppress prostate cancer cell growth: Implications in reducing health disparity

Prostate cancer (PC) is a leading cause of death in men because of the high incidence and long-term inefficacy of the existing treatment options. Furthermore, it exhibits significant health disparities that affect African-American (AA) men more adversely than others do. Previously, we established CYP3A5, a highly expressed protein in AAs PC, as a positive regulator of androgen receptor (AR) signaling. We examined the impact of CYP3A5 depletion on genome-wide transcriptional output using RNA sequencing to gain deeper mechanistic insights. The data revealed that 561 genes were downregulated and 263 were upregulated upon silencing of CYP3A5 in PC cells. Furthermore, in silico pathway analyses of differentially expressed genes suggested that the cell cycle regulation pathway was most significantly affected by CYP3A5 inhibition. Cell cycle analysis of CYP3A5-silenced cells and those treated with clobetasol, a specific CYP3A5 pharmacological inhibitor, showed G1/S phase blockade. Both CYP3A5-depletion and pharmacological inhibition resulted in the downregulation of cyclin D, cyclin B, and CDK2, along with the upregulation of p27kip1 but had minimal effects on CDK4/6 levels. Combination treatment with clobetasol and the CDK4/6 inhibitor palbociclib exhibited synergy with combination index (CI) values ranging from 0.28-0.78. Our findings support the utility of CYP3A5 as a druggable therapeutic target that works more effectively in combination with CDK4/6 inhibition to limit the progression of PC, especially for AA patients with AA. This combination addresses CDK4/6 inhibitor resistance, which is often linked to CDK2 overexpression, and can potentially be useful in reducing disparities in the clinical outcomes of PC. SignificanceOur study highlights CYP3A5 as a key regulator of the cell cycle in prostate cancer (PC). Its overexpression in African American (AA) patients may be a key molecular driver of disparities in outcomes. The combination of CYP3A5 and CDK4/6 inhibitors shows a synergistic effect on therapeutic outcomes and addresses CDK2-mediated resistance. Thus, targeting both CYP3A5 and CDK4/6 could improve treatment outcomes, especially in AA PC patients.

cancer biology↗

bioRxiv2023

Detection of interactions between genetic marker sets and environment in a genome-wide study of hypertension

As human complex diseases are influenced by the interplay of genes and environment, detecting gene-environment interactions (G x E) can shed light on biological mechanisms of diseases and play an important role in disease risk prediction. Development of powerful quantitative tools to incorporate G x E in complex diseases has potential to facilitate the accurate curation and analysis of large genetic epidemiological studies. However, most of existing methods that interrogate G x E focus on the interaction effects of an environmental factor and genetic variants, exclusively for common or rare variants. In this study, we proposed two tests, MAGEIT_RAN and MAGEIT_FIX, to detect interaction effects of an environmental factor and a set of genetic markers containing both rare and common variants, based on the MinQue for Summary statistics. The genetic main effects in MAGEIT_RAN and MAGEIT_FIX are modeled as random or fixed, respectively. Through simulation studies, we illustrated that both tests had type I error under control and MAGEIT_RAN was overall the most powerful test. We applied MAGEIT to a genome-wide analysis of gene-alcohol interactions on hypertension in the Multi-Ethnic Study of Atherosclerosis. We detected two genes, CCNDBP1 and EPB42, that interact with alcohol usage to influence blood pressure. Pathway analysis identified sixteen significant pathways related to signal transduction and development that were associated with hypertension, and several of them were reported to have an interactive effect with alcohol intake. Our results demonstrated that MAGEIT can detect biologically relevant genes that interact with environmental factors to influence complex traits.

genetics↗

bioRxiv2022

Retrospective varying coefficient association analysis of longitudinal binary traits: application to the identification of genetic loci associated with hypertension

Many genetic studies contain rich information on longitudinal phenotypes that require powerful analytical tools for optimal analysis. Genetic analysis of longitudinal data that incorporates temporal variation is important for understanding the genetic architecture and biological variation of complex diseases. Most of the existing methods assume that the contribution of genetic variants is constant over time and fail to capture the dynamic pattern of disease progression. However, the relative influence of genetic variants on complex traits fluctuates over time. In this study, we propose a retrospective varying coefficient mixed model association test, RVMMAT, to detect time-varying genetic effect on longitudinal binary traits. We model dynamic genetic effect using smoothing splines, estimate model parameters by maximizing a double penalized quasi-likelihood function, design a joint test using a Cauchy combination method, and evaluate statistical significance via a retrospective approach to achieve robustness to model misspecification. Through simulations, we illustrated that the retrospective varying-coefficient test was robust to model misspecification under different ascertainment schemes and gained power over the association methods assuming constant genetic effect. We applied RVMMAT to a genome-wide association analysis of longitudinal measure of hypertension in the Multi-Ethnic Study of Atherosclerosis. Pathway analysis identified two important pathways related to G-protein signaling and DNA damage. Our results demonstrated that RVMMAT could detect biologically relevant loci and pathways in a genome scan and provided insight into the genetic architecture of hypertension.

genetics↗