RESUMO
Advanced single-cell profiling technologies promote exploration of cell heterogeneity, and clustering of single-cell RNA (scRNA-seq) data enables discovery of coexpression genes and network relationships between genes. In particular, single-cell profiling of circulating tumor cells (CTCs) can provide unique insights into tumor heterogeneity (including in triple-negative breast cancer (TNBC)), while scRNA-seq leads to better understanding of subclonal architecture and biological function. Despite numerous reports suggesting a direct correlation between circulating tumor cells (CTCs) and poor clinical outcomes, few studies have provided a thorough heterogeneity characterization of CTCs. In addition, TNBC is a disease with not only intertumor but also intratumor heterogeneity and represents various biological distinct subgroups that may have relationships with immune functions that are not clearly established yet. In this article, we introduce a new scheme for detecting genotypic characterization of single-cell heterogeneities and apply it to CTC and TNBC single-cell RNA-seq data. First, we use an existing mixture exponential family graph model to partition the cell-cell network; then, with the Markov random field model, we obtain more flexible network rewiring. Finally, we find the cell heterogeneity and network relationships according to different high coexpression gene modules in different cell subsets. Our results demonstrate that this scheme provides a reasonable and effective way to model different cell clusters and different biological enrichment gene clusters. Thus, using different internal coexpression genes of different cell clusters, we can infer the differences in tumor composition and diversity.
Assuntos
Células Neoplásicas Circulantes/patologia , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Biomarcadores Tumorais/genética , Análise por Conglomerados , Perfilação da Expressão Gênica/métodos , Regulação Neoplásica da Expressão Gênica/genética , Redes Reguladoras de Genes/genética , Humanos , Cadeias de Markov , Modelos Teóricos , RNA/genética , RNA/metabolismo , RNA-Seq/métodos , Transcriptoma/genética , Neoplasias de Mama Triplo Negativas/patologia , Sequenciamento do Exoma/métodosRESUMO
The authors compared the effectiveness of thiazide diuretic (TD), angiotensin-converting enzyme inhibitor (ACEI), angiotensin receptor blocker (ARB), and calcium channel blocker (CCB) monotherapies for the treatment of nondiabetic hypertension using MarketScan Databases 2010-2014. Multivariable Cox regression models assessed whether the addition of a new antihypertensive drug, treatment discontinuation, or switch and major cardiovascular or cerebrovascular events varied across groups. A total of 565 009 patients started monotherapy with ACEIs (43.6%), CCBs (23.6%), TDs (18.8%), or ARBs (14.0%). Patients who took TDs had a higher risk for either drug addition or discontinuation than patients who took ACEIs (hazard ratio [HR], 0.69 [95% CI, 0.68-0.70] vs HR, 0.81 [95% CI, 0.80-0.81]), ARBs (HR, 0.67 [95% CI, 0.66-0.68] vs HR, 0.66 [95% CI, 0.65-0.67]), and CCBs (HR, 0.85 [95% CI, 0.84-0.87] vs HR, 0.94 [95% CI, 0.93-0.95]). Conversely, patients who took TDs experienced a lower risk of clinical events compared with patients who took ACEIs (HR, 1.24 [95% CI, 1.15-1.33]), ARBs (HR, 1.28 [95% CI, 1.18-1.39]), and CCBs (HR, 1.35 [95% CI, 1.25-1.46]). Our results provide a strong rationale for choosing TDs as first-line monotherapy for the control of hypertension.