MicroRNA Regulation of Epigenetic Modifiers in Breast Cancer

Epigenetics refers to the heritable changes in gene expression without a change in the DNA sequence itself. Two of these major changes include aberrant DNA methylation as well as changes to histone modification patterns. Alterations to the epigenome can drive expression of oncogenes and suppression of tumor suppressors, resulting in tumorigenesis and cancer progression. In addition to modifications of the epigenome, microRNA (miRNA) dysregulation is also a hallmark for cancer initiation and metastasis. Advances in our understanding of cancer biology demonstrate that alterations in the epigenome are not only a major cause of miRNA dysregulation in cancer, but that miRNAs themselves also indirectly drive these DNA and histone modifications. More explicitly, recent work has shown that miRNAs can regulate chromatin structure and gene expression by directly targeting key enzymes involved in these processes. This review aims to summarize these research findings specifically in the context of breast cancer. This review also discusses miRNAs as epigenetic biomarkers and as therapeutics, and presents a comprehensive summary of currently validated epigenetic targets in breast cancer

Rho GTPases: Big Players in Breast Cancer Initiation, Metastasis and Therapeutic Responses

Rho GTPases, a family of the Ras GTPase superfamily, are key regulators of the actin cytoskeleton. They were originally thought to primarily affect cell migration and invasion; however, recent advances in our understanding of the biology and function of Rho GTPases have demonstrated their diverse roles within the cell, including membrane trafficking, gene transcription, migration, invasion, adhesion, survival and growth. As these processes are critically involved in cancer initiation, metastasis and therapeutic responses, it is not surprising that studies have demonstrated important roles of Rho GTPases in cancer. Although the majority of data indicates an oncogenic role of Rho GTPases, tumor suppressor functions of Rho GTPases have also been revealed, suggesting a context and cell-type specific function for Rho GTPases in cancer. This review aims to summarize recent progresses in our understanding of the regulation and functions of Rho GTPases, specifically in the context of breast cancer. The potential of Rho GTPases as therapeutic targets and prognostic tools for breast cancer patients are also discussed

Behind the rainbow, "Tongqi" wives of men who have sex with men in China: a systematic review

open access articleBackground: Due to the restrictions and stigmatization of homosexuality in China, there has emerged the “Tongqi,” or the wives of men who have sex with men (MSM). There are around 14 million Tongqi wives whose needs for support are often overshadowed. This phenomenon has been largely under researched, this review is the first to address the current data on the Tongqi. The aim of this systematic review is to begin to provide insight into the pre-existing data and the further support that is needed for the wives of MSM. Methods: The researchers searched PubMed, Web of Science, EMBASE, PsycINFO, CNKI, Sinomed and WangFang databases from their inception date until June 7, 2019. Handsearching was also completed to provide a rich data set. Results: The articles were summarized and analyzed for thematic clusters. From the selected article, five themes emerged, including Sexual Health Issues, Intimate Partner Violence, Mental Health Status, Marriage Dissatisfaction, and Coping Strategies. These themes often intersected to provide a complex understanding of the current gaps in support provided to Tongqi. Conclusion: Tongqi wives remain a hidden population in Chinese mainstream society, who deserves a sensitive approach to support. The study revealed that the MSM wives suffer severe mental, physical, health, and life related harms. However, instead of situating them into the victim roles, many women take on an identity of empowerment and are working together, aiming to make social changes. In order to address the Tongqi phenomenon, it is also essential to reduce the discrimination toward homosexuality. Tongqi are a special group of Chinese women, they require further intensive research attention

Nanoparticle-Mediated Therapeutic Agent Delivery for Treating Metastatic Breast Cancer—Challenges and Opportunities

Breast cancer (BC) is the second leading cause of cancer-related death in American women and more than 90% of BC-related death is caused by metastatic BC (MBC). This review stresses the limited success of traditional therapies as well as the use of nanomedicine for treating MBC. Understanding the biological barriers of MBC that nanoparticle in vivo trafficking must overcome could provide valuable new insights for translating nanomedicine from the bench side to the bedside. A view about nanomedicine applied in BC therapy has been summarized with their present status, which is gaining attention in the clinically-applied landscape. The progressions of drug/gene delivery systems, especially the status of their preclinical or clinical trials, are also discussed. Here we highlight that the treatment of metastasis, in addition to the extensively described inhibition of primary tumor growth, is an indispensable requirement for nanomedicine. Along with more innovations in material chemistry and more progressions in biology, nanomedicine will constantly supply more exciting new approaches for targeted drug/gene delivery against MBC

Amygdala's T1-weighted image radiomics outperforms volume for differentiation of anxiety disorder and its subtype

IntroductionAnxiety disorder is the most common psychiatric disorder among adolescents, with generalized anxiety disorder (GAD) being a common subtype of anxiety disorder. Current studies have revealed abnormal amygdala function in patients with anxiety compared with healthy people. However, the diagnosis of anxiety disorder and its subtypes still lack specific features of amygdala from T1-weighted structural magnetic resonance (MR) imaging. The purpose of our study was to investigate the feasibility of using radiomics approach to distinguish anxiety disorder and its subtype from healthy controls on T1-weighted images of the amygdala, and provide a basis for the clinical diagnosis of anxiety disorder.MethodsT1-weighted MR images of 200 patients with anxiety disorder (including 103 GAD patients) as well as 138 healthy controls were obtained in the Healthy Brain Network (HBN) dataset. We extracted 107 radiomics features for the left and right amygdala, respectively, and then performed feature selection using the 10-fold LASSO regression algorithm. For the selected features, we performed group-wise comparisons, and use different machine learning algorithms, including linear kernel support vector machine (SVM), to achieve the classification between the patients and healthy controls.ResultsFor the classification task of anxiety patients vs. healthy controls, 2 and 4 radiomics features were selected from left and right amygdala, respectively, and the area under receiver operating characteristic curve (AUC) of linear kernel SVM in cross-validation experiments was 0.6739±0.0708 for the left amygdala features and 0.6403±0.0519 for the right amygdala features; for classification task for GAD patients vs. healthy controls, 7 and 3 features were selected from left and right amygdala, respectively, and the cross-validation AUCs were 0.6755±0.0615 for the left amygdala features and 0.6966±0.0854 for the right amygdala features. In both classification tasks, the selected amygdala radiomics features had higher discriminatory significance and effect sizes compared with the amygdala volume.DiscussionOur study suggest that radiomics features of bilateral amygdala potentially could serve as a basis for the clinical diagnosis of anxiety disorder

Graph-Regularized Dual Lasso for Robust eQTL Mapping

Motivation: As a promising tool for dissecting the genetic basis of complex traits, expression quantitative trait loci (eQTL) mapping has attracted increasing research interest. An important issue in eQTL mapping is how to effectively integrate networks representing interactions among genetic markers and genes. Recently, several Lasso-based methods have been proposed to leverage such network information. Despite their success, existing methods have three common limitations: (i) a preprocessing step is usually needed to cluster the networks; (ii) the incompleteness of the networks and the noise in them are not considered; (iii) other available information, such as location of genetic markers and pathway information are not integrated. Results: To address the limitations of the existing methods, we propose Graph-regularized Dual Lasso (GDL), a robust approach for eQTL mapping. GDL integrates the correlation structures among genetic markers and traits simultaneously. It also takes into account the incompleteness of the networks and is robust to the noise. GDL utilizes graph-based regularizers to model the prior networks and does not require an explicit clustering step. Moreover, it enables further refinement of the partial and noisy networks. We further generalize GDL to incorporate the location of genetic makers and gene-pathway information. We perform extensive experimental evaluations using both simulated and real datasets. Experimental results demonstrate that the proposed methods can effectively integrate various available priori knowledge and significantly outperform the state-of-the-art eQTL mapping methods