A Method for Identification of the Methylation Level of CpG Islands From NGS Data

Advances in the role of GPX3 in ovarian cancer (Review)

Ovarian cancer (OC) is the 5th most common malignancy in women, and the leading cause of death from gynecologic malignancies. Owing to tumor heterogeneity, lack of reliable early diagnostic methods and high incidence of chemotherapy resistance, the 5‑year survival rate of patients with advanced OC remains low despite considerable advances in detection and therapeutic approaches. Therefore, identifying novel therapeutic targets to improve the prognosis of patients with OC is crucial. The expression of glutathione peroxidase 3 (GPX3) plays a crucial role in the growth, proliferation and differentiation of various malignant tumors. In OC, GPX3 is the only antioxidant enzyme the high expression of which is negatively correlated with the overall survival of patients. GPX3 may affect lipid metabolism in tumor stem cells by influencing redox homeostasis in the tumor microenvironment. The maintenance of stemness in OC stem cells (OCSCs) is strongly associated with poor prognosis and recurrence in patients. The aim of the present study was to review the role of GPX3 in OC and investigate the potential factors and effects of GPX3 on OCSCs. The findings of the current study offer novel potential targets for drug therapy in OC, enhance the theoretical foundation of OC drug therapy and provide valuable references for clinical treatment.

Optimizing healthcare system by amalgamation of text processing and deep learning: a systematic review

The explosion of clinical textual data has drawn the attention of researchers. Owing to the abundance of clinical data, it is becoming difficult for healthcare professionals to take real-time measures. The tools and methods are lacking when compared to the amount of clinical data generated every day. This review aims to survey the text processing pipeline with deep learning methods such as CNN, RNN, LSTM, and GRU in the healthcare domain and discuss various applications such as clinical concept detection and extraction, medically aware dialogue systems, sentiment analysis of drug reviews shared online, clinical trial matching, and pharmacovigilance. In addition, we highlighted the major challenges in deploying text processing with deep learning to clinical textual data and identified the scope of research in this domain. Furthermore, we have discussed various resources that can be used in the future to optimize the healthcare domain by amalgamating text processing and deep learning.

The key role of differential broad H3K4me3 and H3K4ac domains in breast cancer

Epigenetic processes are radically altered in cancer cells. The altered epigenetic events may include histone post-translational modifications (PTMs), DNA modifications, and/or alterations in the levels and modifications of chromatin modifying enzymes and chromatin remodelers. With changes in gene programming are changes in the genomic distribution of histone PTMs. Genes that are poised or transcriptionally active have histone H3 trimethylated lysine 4 (H3K4me3) located at the transcription start site and at the 5' end of the gene. However, a small population of genes that are involved in cell identity or cancer cell properties have a broad H3K4me3 domain that may stretch for several kilobases through the coding region of the gene. Each cancer cell type appears to mark a select set of cancer-related genes in this manner. In this study, we determined which genes were differentially marked with the broad H3K4me3 domain in normal-like (MCF10A), luminal-type breast cancer (MCF7), and triple-negative breast cancer (MDA-MB-231) cells. We also determined whether histone H3 acetylated lysine 4 (H3K4ac), also a mark of active promoters, had a broad domain configuration. We applied two peak callers (MACS2, PeakRanger) to analyze H3K4me3 and H3K4ac chromatin immunoprecipitation sequencing (ChIP-Seq) data. We identified genes with a broad H3K4me3 and/or H3K4ac domain specific to each cell line and show that the genes have critical roles in the breast cancer subtypes. Furthermore, we show that H3K4ac marks enhancers. The identified genes with the broad H3K4me3/H3K4ac domain have been targeted in clinical and pre-clinical studies including therapeutic treatments of breast cancer.

A New Bias Site for Epigenetic Modifications: How Non-Canonical GC Base Pairs Favor Mechanochemical Cleavage of DNA

Properties of non-canonical GC base pairs and their relations with mechanochemical cleavage of DNA are analyzed. A hypothesis of the involvement of the transient GC wobble base pairs both in the mechanisms of the mechanochemical cleavage of DNA and epigenetic mechanisms involving of 5-methylcytosine, is proposed. The hypothesis explains the increase in the frequency of the breaks of the sugar-phosphate backbone of DNA after cytosines, the asymmetric character of these breaks, and an increase in break frequency in CpG after cytosine methylation. As an alternative hypothesis, probable implication of GC⁺ Hoogsteen base pairs is considered, which now exemplify the best-studied non-canonical GC base pairs in the DNA double helix. Also see the video abstract here https://youtu.be/EUunVWL0ptw.