Hormone therapy use and breast tissue DNA methylation: analysis of epigenome wide data from the normal breast study

AI-driven feature selection and epigenetic pattern analysis: A screening strategy of CpGs validated by pyrosequencing for body fluid identification

Identification of body fluid stain at crime scene is one of the important tasks of forensic evidence analysis. Currently, body fluid-specific CpGs detected by DNA methylation microarray screening, have been widely studied for forensic body fluid identification. However, some CpGs have limited ability to distinguish certain body fluid types. The ongoing need is to discover novel methylation markers and fully validate them to enhance their evidentiary strength in complex forensic scenarios. This research gathered forensic-related DNA methylation microarrays data from the Gene Expression Omnibus (GEO) database. A novel screening strategy for marker selection was developed, combining feature selection algorithms (elastic net, information gain ratio, feature importance based on Random Forest, and mutual information coefficient) with epigenetic pattern analysis, to identify CpG markers for body fluid identification. The selected CpGs were validated through pyrosequencing on peripheral blood, saliva, semen, vaginal secretions, and menstrual blood samples, and machine learning classification models were constructed based on the sequencing results. Pyrosequencing results revealed 14 CpGs with high specificity in five types of body fluid samples. A machine learning classification model, developed based on the pyrosequencing results, could effectively distinguish five types of body fluid samples, achieving 100 % accuracy on the test set. Utilizing six CpG markers, it was also feasible to attain ideal efficacy in identifying body fluid stains. Our research proposes a systematic and scientific strategy for screening body fluid-specific CpGs, contributing new insights and methods to forensic body fluid identification.

Environment factors, DNA methylation, and cancer

Today, the rapid development of science and technology and the rapid change in economy and society are changing the way of life of human beings and affecting the natural, living, working, and internal environment on which human beings depend. At the same time, the global incidence of cancer has increased significantly yearly, and cancer has become the number one killer that threatens human health. Studies have shown that diet, living habits, residential environment, mental and psychological factors, intestinal flora, genetics, social factors, and viral and non-viral infections are closely related to human cancer. However, the molecular mechanisms of the environment and cancer development remain to be further explored. In recent years, DNA methylation has become a key hub and bridge for environmental and cancer research. Some environmental factors can alter the hyper/hypomethylation of human cancer suppressor gene promoters, proto-oncogene promoters, and the whole genome, causing low/high expression or gene mutation of related genes, thereby exerting oncogenic or anticancer effects. It is expected to develop early warning markers of cancer environment based on DNA methylation, thereby providing new methods for early detection of cancers, diagnosis, and targeted therapy. This review systematically expounds on the internal mechanism of environmental factors affecting cancer by changing DNA methylation, aiming to help establish the concept of cancer prevention and improve people's health.

Effect of contraceptive hormonal therapy on mammographic breast density: A longitudinal cohort study

PURPOSE

Evaluate the longitudinal relationship between mammographic density and hormonal contraceptive use in late reproductive-aged women.

METHODS

Patients aged 35-50 years old who underwent 5 or more screening mammograms within a 7.5-year period between 2004 and 2019 in a single urban tertiary care center were randomly selected. Patients were categorized into four cohorts based on hormonal contraceptive exposure during a 2-year lead-in period and a 7.5-year study period: 1) never exposed, 2) always exposed, 3) interval hormonal contraceptive start, and 4) interval hormonal contraceptive stop. The primary outcome was difference in BI-RADS breast density category between initial and final mammograms.

RESULTS

Of the 708 patients included, long-term use of combined oral contraceptives or a levonorgestrel intrauterine device were not associated with an increase in breast density category over the 7.5-year study period, compared to those with no hormonal contraceptive exposure. Initiation of combined oral contraceptives was associated with an increase in breast density category (β = 0.31, P = 0.045); however, no difference in initial density category was noted between those exposed and those never exposed to combined oral contraceptives during the 2-year lead-in period, and discontinuation was not associated with a decrease in breast density category when compared to those with continuous exposure.

CONCLUSION(S)

Long-term use of combined oral contraceptives or a levonorgestrel intrauterine device was not associated with an increase in BI-RADS breast density category. Initiation of a combined oral contraceptive was associated with an increase in breast density category, although this may be a transient effect.

Associations of breast cancer related exposures and gene expression profiles in normal breast tissue-The Norwegian Women and Cancer normal breast tissue study

BACKGROUND

Normal breast tissue is utilized in tissue-based studies of breast carcinogenesis. While gene expression in breast tumor tissue is well explored, our knowledge of transcriptomic signatures in normal breast tissue is still incomplete. The aim of this study was to investigate variability of gene expression in a large sample of normal breast tissue biopsies, according to breast cancer related exposures (obesity, smoking, alcohol, hormone therapy, and parity).

METHODS

We analyzed gene expression profiles from 311 normal breast tissue biopsies from cancer-free, post-menopausal women, using Illumina bead chip arrays. Principal component analysis and K-means clustering was used for initial analysis of the dataset. The association of exposures and covariates with gene expression was determined using linear models for microarrays.

RESULTS

Heterogeneity of the breast tissue and cell composition had the strongest influence on gene expression profiles. After adjusting for cell composition, obesity, smoking, and alcohol showed the highest numbers of associated genes and pathways, whereas hormone therapy and parity were associated with negligible gene expression differences.

CONCLUSION

Our results provide insight into associations between major exposures and gene expression profiles and provide an informative baseline for improved understanding of exposure-related molecular events in normal breast tissue of cancer-free, post-menopausal women.

Ten Years of EWAS

Epigenome-wide association study (EWAS) has been applied to analyze DNA methylation variation in complex diseases for a decade, and epigenome as a research target has gradually become a hot topic of current studies. The DNA methylation microarrays, next-generation, and third-generation sequencing technologies have prepared a high-quality platform for EWAS. Here, the progress of EWAS research is reviewed, its contributions to clinical applications, and mainly describe the achievements of four typical diseases. Finally, the challenges encountered by EWAS and make bold predictions for its future development are presented.