A multiplex blood-based assay targeting DNA methylation in PBMCs enables early detection of breast cancer

Methods for the Analysis of Multiple Epigenomic Mediators in Environmental Epidemiology

PURPOSE OF REVIEW

Epigenetic changes can be highly influenced by environmental factors and have in turn been proposed to influence chronic disease. Being able to quantify to which extent epigenomic processes are mediators of the association between environmental exposures and diseases is of interest for epidemiologic research. In this review, we summarize the proposed mediation analysis methods with applications to epigenomic data.

RECENT FINDINGS

The ultra-high dimensionality and high correlations that characterize omics data have hindered the precise quantification of mediated effects. Several methods have been proposed to deal with mediation in high-dimensional settings, including methods that incorporate dimensionality reduction techniques to the mediation algorithm. Although important methodological advances have been conducted in the previous years, key challenges such as the development of sensitivity analyses, dealing with mediator-mediator interactions, including environmental mixtures as exposures, or the integration of different omic data should be the focus of future methodological developments for epigenomic mediation analysis.

Important role of DNA methylation hints at significant potential in tuberculosis

Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis (Mtb) infection, has persisted as a major global public health threat for millennia. Until now, TB continues to challenge efforts aimed at controlling it, with drug resistance and latent infections being the two main factors hindering treatment efficacy. The scientific community is still striving to understand the underlying mechanisms behind Mtb's drug resistance and latent infection. DNA methylation, a critical epigenetic modification occurring throughout an individual's growth and development, has gained attention following advances in high-throughput sequencing technologies. Researchers have observed abnormal DNA methylation patterns in the host genome during Mtb infection. Given the escalating issue of drug-resistant Mtb, delving into the role of DNA methylation in TB's development is crucial. This review article explores DNA methylation's significance in human growth, development and disease, and its role in regulating Mtb's evolution and infection processes. Additionally, it discusses potential applications of DNA methylation research in tuberculosis.

Intelligent scoring system based on dynamic optical breast imaging for early detection of breast cancer

Early detection of breast cancer can significantly improve patient outcomes and five-year survival in clinical screening. Dynamic optical breast imaging (DOBI) technology reflects the blood oxygen metabolism level of tumors based on the theory of tumor neovascularization, which offers a technical possibility for early detection of breast cancer. In this paper, we propose an intelligent scoring system integrating DOBI features assessment and a malignancy score grading reporting system for early detection of breast cancer. Specifically, we build six intelligent feature definition models to depict characteristics of regions of interest (ROIs) from location, space, time and context separately. Similar to the breast imaging-reporting and data system (BI-RADS), we conclude the malignancy score grading reporting system to score and evaluate ROIs as follows: Malignant (≥ 80 score), Likely Malignant (60-80 score), Intermediate (35-60 score), Likely Benign (10-35 score), and Benign (<10 score). This system eliminates the influence of subjective physician judgments on the assessment of the malignant probability of ROIs. Extensive experiments on 352 Chinese patients demonstrate the effectiveness of the proposed system compared to state-of-the-art methods.

Ultrasensitive and Quantitative DNA Methylation Detection Method Based on the MutS Protein

DNA methylation is closely related to cancer. It is generally accepted that DNA methylation detection is crucial in cancer diagnosis, prognosis, and treatment monitoring. Therefore, there is an urgent demand for developing a simple, rapid, highly sensitive, and highly specific methylation detection method to detect DNA methylation at specific sites quantitatively. In this work, we introduce a DNA methylation detection method based on MutS and methylation-specific PCR, named MutS-based methylation-specific PCR (MB-MSP), which has the advantages of simplicity, speed, high specificity, sensitivity, and broad applicability. Utilizing the MutS's ability to bind mismatched base pairs, we inhibit not only the amplification of unmethylated DNA but also nonspecific primer amplification. We achieved a detection sensitivity of 0.5% for the methylated genes of ACP1, CLEC11A, and SEPT9 by MB-MSP. It has a good linear relationship and a detection time of only 1.5 h. To validate the feasibility of the MB-MSP method in clinical application, we conducted methylation detection on plasma-circulating tumor DNA samples from 10 liver cancer patients and 5 healthy people, achieving a 100% accuracy rate. In conclusion, MB-MSP, as a novel and reliable DNA methylation detection tool, holds significant application value and potential for advancing early cancer diagnosis.

Ultrasensitive electrochemical detection and inhibition evaluation of DNA methyltransferase based on cascade strand displacement amplification

An electrochemical sensing approach for ultrasensitive DNA methyltransferase (MTase) activity assay is proposed. After specific cleavage reaction in the presence of a methylated state, strand displacement polymerization (SDP) is initiated in the solution. The product of upstream SDP further triggers downstream SDP, which enriches abundant electrochemical species at the electrode. The whole process is quite convenient with shared enzymes. Due to the cascade signal amplification, ultrahigh sensitivity is promised. Inhibitor screening results are also demonstrated to be good. Besides, target MTase can be accurately determined in human serum samples, confirming excellent practical utility. This work provides a reliable approach for the analysis of MTase activity, which is of vital importance for related biological studies and clinical applications.

Imaging and AI based chromatin biomarkers for diagnosis and therapy evaluation from liquid biopsies

Multiple genomic and proteomic studies have suggested that peripheral blood mononuclear cells (PBMCs) respond to tumor secretomes and thus could provide possible avenues for tumor prognosis and treatment evaluation. We hypothesized that the chromatin organization of PBMCs obtained from liquid biopsies, which integrates secretome signals with gene expression programs, provides efficient biomarkers to characterize tumor signals and the efficacy of proton therapy in tumor patients. Here, we show that chromatin imaging of PBMCs combined with machine learning methods provides such robust and predictive chromatin biomarkers. We show that such chromatin biomarkers enable the classification of 10 healthy and 10 pan-tumor patients. Furthermore, we extended our pipeline to assess the tumor types and states of 30 tumor patients undergoing (proton) radiation therapy. We show that our pipeline can thereby accurately distinguish between three tumor groups with up to 89% accuracy and enables the monitoring of the treatment effects. Collectively, we show the potential of chromatin biomarkers for cancer diagnostics and therapy evaluation.