Ning Qing Liu

Global demethylation is part of a conserved program of epigenetic reprogramming to naive pluripotency. The transition from primed hypermethylated embryonic stem cells (ESCs) to naive hypomethylated ones (serum-to-2i) is a valuable model system for epigenetic reprogramming. We present a mathematical model, which accurately predicts global DNA demethylation kinetics. Experimentally, we show that the main drivers of global demethylation are neither active mechanisms (Aicda, Tdg, and Tet1-3) nor the reduction of de novo methylation. UHRF1 protein, the essential targeting factor for DNMT1, is reduced upon transition to 2i, and so is recruitment of the maintenance methylation machinery to replication foci. Concurrently, there is global loss of H3K9me2, which is needed for chromatin binding of UHRF1. These mechanisms synergistically enforce global DNA hypomethylation in a replication-coupled fashion. Our observations establish the molecular mechanism for global demethylation in naive ESCs, which has key parallels with those operating in primordial germ cells and early embryos.

Tumors growing in metabolically challenged environments, such as glioblastoma in the brain, are particularly reliant on crosstalk with their tumor microenvironment (TME) to satisfy their high energetic needs. To study the intricacies of this metabolic interplay, we interrogated the heterogeneity of the glioblastoma TME using single-cell and multi-omics analyses and identified metabolically rewired tumor-associated macrophage (TAM) subpopulations with pro-tumorigenic properties. These TAM subsets, termed lipid-laden macrophages (LLMs) to reflect their cholesterol accumulation, are epigenetically rewired, display immunosuppressive features, and are enriched in the aggressive mesenchymal glioblastoma subtype. Engulfment of cholesterol-rich myelin debris endows subsets of TAMs to acquire an LLM phenotype. Subsequently, LLMs directly transfer myelin-derived lipids to cancer cells in an LXR/Abca1-dependent manner, thereby fueling the heightened metabolic demands of mesenchymal glioblastoma. Our work provides an in-depth understanding of the immune-metabolic interplay during glioblastoma progression, thereby laying a framework to unveil targetable metabolic vulnerabilities in glioblastoma.

The genus Artemisia consists of about 500 species, occurring throughout the world. Some very important drug leads have been discovered from this genus, notably artemisinin, the well known anti-malarial drug isolated from the Chinese herb Artemisia annua. The genus is also known for its aromatic nature and hence research has been focussed on the chemical compositions of the volatile secondary metabolites obtained from various Artemisia species. In the southern African region, A. afra is one of the most popular and commonly used herbal medicines. It is used to treat various ailments ranging from coughs and colds to malaria and diabetes. Although it is one of the most popular local herbal medicines, only limited scientific research, mainly focussing on the volatile secondary metabolites content, has been conducted on this species. The aim of this review was therefore to collect all available scientific literature published on A. afra and combine it into this paper. In this review, a general overview will be given on the morphology, taxonomy and geographical distribution of A. afra. The major focus will however be on the secondary metabolites, mainly the volatile secondary metabolites, which have been identified from this species. In addition all of the reported biological activities of the extracts derived from this species have been included as well as the literature on the pharmacology and toxicology. We aim at bringing together most of the available scientific research conducted on this species, which is currently scattered across various publications, into this review paper.

BACKGROUND: Clinical outcome of patients with triple-negative breast cancer (TNBC) is highly variable. This study aims to identify and validate a prognostic protein signature for TNBC patients to reduce unnecessary adjuvant systemic therapy. METHODS: Frozen primary tumors were collected from 126 lymph node-negative and adjuvant therapy-naive TNBC patients. These samples were used for global proteome profiling in two series: an in-house training (n = 63) and a multicenter test (n = 63) set. Patients who remained free of distant metastasis for a minimum of 5 years after surgery were defined as having good prognosis. Cox regression analysis was performed to develop a prognostic signature, which was independently validated. All statistical tests were two-sided. RESULTS: An 11-protein signature was developed in the training set (median follow-up for good-prognosis patients = 117 months) and subsequently validated in the test set (median follow-up for good-prognosis patients = 108 months) showing 89.5% sensitivity (95% confidence interval [CI] = 69.2% to 98.1%), 70.5% specificity (95% CI = 61.7% to 74.2%), 56.7% positive predictive value (95% CI = 43.8% to 62.1%), and 93.9% negative predictive value (95% CI = 82.3% to 98.9%) for poor-prognosis patients. The predicted poor-prognosis patients had higher risk to develop distant metastasis than the predicted good-prognosis patients in univariate (hazard ratio [HR] = 13.15; 95% CI = 3.03 to 57.07; P = .001) and multivariable (HR = 12.45; 95% CI = 2.67 to 58.11; P = .001) analysis. Furthermore, the predicted poor-prognosis group had statistically significantly more breast cancer-specific mortality. Using our signature as guidance, more than 60% of patients would have been exempted from unnecessary adjuvant chemotherapy compared with conventional prognostic guidelines. CONCLUSIONS: We report the first validated proteomic signature to assess the natural course of clinical TNBC.