Epigenetic Regulation of Epithelial-Mesenchymal Transition in Epithelial Stem Cells and Triple Negative Breast Cancer

Epithelial-mesenchymal transition (EMT) is a cellular program responsible for the conversion of stationary epithelial cells characterized by apical-basolateral polarity to motile mesenchymal cells with front-back end polarity. EMT drives the fundamental developmental processes of implantation, gastrulation and neural crest formation. This essential developmental program becomes reactivated during cancer progression to promote metastasis. These studies examine the molecular and epigenetic mechanisms responsible for the induction of EMT in several developmental epithelial stem cell models and Basal-like and Claudin-low breast cancer subtypes. Using trophoblast stem (TS) cells paused in EMT, we have defined the molecular and epigenetic mechanisms responsible for modulating the induction of EMT. Targeted inactivation of MAP3K4, knockdown of CBP, or overexpression of SNAI1 in TS cells induced intermediate EMT phenotypes. These TS cells exhibited epigenetic changes in the histone acetylation landscape that caused loss of epithelial maintenance while preserving self-renewal and multipotency. MAP3K4 controls the activity of the histone acetyltransferase CBP, and acetylation of histone H2B by CBP is required to maintain the epithelial phenotype of TS cells. Combined loss of MAP3K4/CBP activity represses expression of epithelial genes and causes TS cells to undergo EMT while maintaining self-renewal and multipotency. A similar EMT phenotype and an EMT gene signature shared with TS cells in EMT were found in Claudin-low breast cancer cells with properties of EMT and stemness. Therefore, it was hypothesized that the upregulated genes within the intersecting EMT signature define a novel set of genes critical to the induction of EMT and maintenance of the mesenchymal phenotype in breast cancer cells. We designed an RNAi screen in the Claudin-low EpCAM(-) population of SUM149 and SUM229 Basal-like breast cancer cells to identify genes responsible for maintaining the mesenchymal phenotype. Using this RNAi screening strategy for EMT-regulatory genes, the chromatin-remodeling factor Smarcd3/Baf60c was identified as a novel epigenetic regulator controlling the induction of EMT. Expression of Smarcd3/Baf60c in human mammary epithelial cells promoted EMT in a Wnt5a-dependent manner. These results highlight a new mechanism of epigenetic regulation of EMT, whereby Smarcd3/Baf60c promotes loss of epithelial cell polarity and dissolution of cell-cell junctions through activation of non-canonical WNT signaling.Doctor of Philosoph

MAP3K4/CBP-Regulated H2B Acetylation Controls Epithelial-Mesenchymal Transition in Trophoblast Stem Cells

Epithelial stem cells self-renew while maintaining multipotency, but the dependence of stem cell properties on maintenance of the epithelial phenotype is unclear. We previously showed that trophoblast stem (TS) cells lacking the protein kinase MAP3K4 maintain properties of both stemness and epithelial-mesenchymal transition (EMT). Here, we show that MAP3K4 controls the activity of the histone acetyltransferase CBP, and that acetylation of histones H2A and H2B by CBP is required to maintain the epithelial phenotype. Combined loss of MAP3K4/CBP activity represses expression of epithelial genes and causes TS cells to undergo EMT while maintaining their self-renewal and multipotency properties. The expression profile of MAP3K4 deficient TS cells defines an H2B acetylation regulated gene signature that closely overlaps with that of human breast cancer cells. Taken together, our data define an epigenetic switch that maintains the epithelial phenotype in TS cells and reveal previously unrecognized genes potentially contributing to breast cancer

Efficiently identifying genome-wide changes with next-generation sequencing data

We propose a new and effective statistical framework for identifying genome-wide differential changes in epigenetic marks with ChIP-seq data or gene expression with mRNA-seq data, and we develop a new software tool EpiCenter that can efficiently perform data analysis. The key features of our framework are: (i) providing multiple normalization methods to achieve appropriate normalization under different scenarios, (ii) using a sequence of three statistical tests to eliminate background regions and to account for different sources of variation and (iii) allowing adjustment for multiple testing to control false discovery rate (FDR) or family-wise type I error. Our software EpiCenter can perform multiple analytic tasks including: (i) identifying genome-wide epigenetic changes or differentially expressed genes, (ii) finding transcription factor binding sites and (iii) converting multiple-sample sequencing data into a single read-count data matrix. By simulation, we show that our framework achieves a low FDR consistently over a broad range of read coverage and biological variation. Through two real examples, we demonstrate the effectiveness of our framework and the usages of our tool. In particular, we show that our novel and robust ‘parsimony’ normalization method is superior to the widely-used ‘tagRatio’ method. Our software EpiCenter is freely available to the public

HER2 expression identifies dynamic functional states within circulating breast cancer cells

Circulating tumor cells (CTCs) in women with advanced estrogen receptor-positive/HER2-negative breast cancer acquire a HER2-positive subpopulation following multiple courses of therapy1,2. In contrast to HER2-amplified primary breast cancer, which is highly sensitive to HER2-targeted therapy, the clinical significance of acquired HER2 heterogeneity during the evolution of metastatic breast cancer is unknown. Here, we analyzed CTCs from 19 ER+/HER2− patients, 84% of whom had acquired CTCs expressing HER2. Cultured CTCs maintain discrete HER2+ and HER2− subpopulations: HER2+ CTCs are more proliferative but not addicted to HER2, consistent with activation of multiple signaling pathways. HER2− CTCs show activation of Notch and DNA damage pathways, exhibiting resistance to cytotoxic chemotherapy, but sensitivity to Notch inhibition. HER2+ and HER2− CTCs interconvert spontaneously, with cells of one phenotype producing daughters of the opposite within four cell doublings. While HER2+ and HER2− CTCs have comparable tumor initiating potential, differential proliferation favors the HER2+ state, while oxidative stress or cytotoxic chemotherapy enhances transition to the HER2− phenotype. Simultaneous treatment with paclitaxel and Notch inhibitors achieves sustained suppression of tumorigenesis in orthotopic CTC-derived tumor models. Together, these results point to distinct yet interconverting phenotypes within patient-derived CTCs, contributing to progression of breast cancer and acquisition of drug resistance

Nucleoside Reverse Transcriptase Inhibitor Resistance Mutations Associated with First-Line Stavudine-Containing Antiretroviral Therapy: Programmatic Implications for Countries Phasing Out Stavudine

Background The World Health Organization Antiretroviral Treatment Guidelines recommend phasing-out stavudine because of its risk of long-term toxicity. There are two mutational pathways of stavudine resistance with different implications for zidovudine and tenofovir cross-resistance, the primary candidates for replacing stavudine. However, because resistance testing is rarely available in resource-limited settings, it is critical to identify the cross-resistance patterns associated with first-line stavudine failure. Methods We analyzed HIV-1 resistance mutations following first-line stavudine failure from 35 publications comprising 1,825 individuals. We also assessed the influence of concomitant nevirapine vs. efavirenz, therapy duration, and HIV-1 subtype on the proportions of mutations associated with zidovudine vs. tenofovir cross-resistance. Results Mutations with preferential zidovudine activity, K65R or K70E, occurred in 5.3% of individuals. Mutations with preferential tenofovir activity, ≥two thymidine analog mutations (TAMs) or Q151M, occurred in 22% of individuals. Nevirapine increased the risk of TAMs, K65R, and Q151M. Longer therapy increased the risk of TAMs and Q151M but not K65R. Subtype C and CRF01_AE increased the risk of K65R, but only CRF01_AE increased the risk of K65R without Q151M. Conclusions Regardless of concomitant nevirapine vs. efavirenz, therapy duration, or subtype, tenofovir was more likely than zidovudine to retain antiviral activity following first-line d4T therap

Dynamic Reprogramming of the Kinome in Response to Targeted MEK Inhibition in Triple-Negative Breast Cancer

Kinase inhibitors have limited success in cancer treatment because tumors circumvent their action. Using a quantitative proteomics approach, we assessed kinome activity in response to MEK inhibition in triple negative breast cancer (TNBC) cells and genetically engineered mice (GEMMs). MEK inhibition caused acute ERK activity loss, resulting in rapid c-Myc degradation that induced expression and activation of several receptor tyrosine kinases (RTKs). RNAi knockdown of ERK or c-Myc mimicked RTK induction by MEK inhibitors, whereas prevention of proteasomal c-Myc degradation blocked kinome reprogramming. MEK inhibitor-induced RTK stimulation overcame MEK2 but not MEK1 inhibition, reactivating ERK and producing drug resistance. The C3Tag GEMM for TNBC similarly induced RTKs in response to MEK inhibition. The inhibitor-induced RTK profile suggested a kinase inhibitor combination therapy that produced GEMM tumor apoptosis and regression where single agents were ineffective. This approach defines mechanisms of drug resistance, allowing rational design of combination therapies for cancer

Exome-wide association study to identify rare variants influencing COVID-19 outcomes : Results from the Host Genetics Initiative

Publisher Copyright: Copyright: © 2022 Butler-Laporte et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75–10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.Peer reviewe

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders