Label-Free Human Disease Characterization through Circulating Cell-Free DNA Analysis Using Raman Spectroscopy.

Circulating cell-free DNA (ccfDNA) is a liquid biopsy biomaterial attracting significant attention for the implementation of precision medicine diagnostics. Deeper knowledge related to its structure and biology would enable the development of such applications. In this study, we employed Raman spectroscopy to unravel the biomolecular profile of human ccfDNA in health and disease. We established reference Raman spectra of ccfDNA samples from healthy males and females with different conditions, including cancer and diabetes, extracting information about their chemical composition. Comparative observations showed a distinct spectral pattern in ccfDNA from breast cancer patients taking neoadjuvant therapy. Raman analysis of ccfDNA from healthy, prediabetic, and diabetic males uncovered some differences in their biomolecular fingerprints. We also studied ccfDNA released from human benign and cancer cell lines and compared it to their respective gDNA, confirming it mirrors its cellular origin. Overall, we explored for the first time Raman spectroscopy in the study of ccfDNA and provided spectra of samples from different sources. Our findings introduce Raman spectroscopy as a new approach to implementing liquid biopsy diagnostics worthy of further elaboration.

In Vivo Estimation of the Biological Effects of Endocrine Disruptors in Rabbits after Combined and Long-Term Exposure: Study Protocol.

Recently, an increasing number of chemical compounds are being characterized as endocrine disruptors since they have been proven to interact with the endocrine system, which plays a crucial role in the maintenance of homeostasis. Glyphosate is the active substance of the herbicide Roundup®, bisphenol A (BPA) and di (2-ethylhexyl) phthalate (DEHP) are used as plasticizers, while triclosan (TCS), methyl (MePB), propyl (PrPB), and butyl (BuPB) parabens are used as antimicrobial agents and preservatives mainly in personal care products. Studies indicate that exposure to these substances can affect humans causing developmental problems and problems in the endocrine, reproductive, nervous, immune, and respiratory systems. Although there are copious studies related to these substances, there are few in vivo studies related to combined exposure to these endocrine disruptors. The aim of the present pilot study is the investigation and assessment of the above substances' toxicity in rabbits after twelve months of exposure to glyphosate (both pure and commercial form) and to a mixture of all the above substances at subtoxic levels. The lack of data from the literature concerning rabbits' exposure to these substances and the restrictions of the 3Rs Principle will result in a limited number of animals available for use (four animals per group, twenty animals in total).

Tissue-Specific Methylation Biosignatures for Monitoring Diseases: An In Silico Approach.

Tissue-specific gene methylation events are key to the pathogenesis of several diseases and can be utilized for diagnosis and monitoring. Here, we established an in silico pipeline to analyze high-throughput methylome datasets to identify specific methylation fingerprints in three pathological entities of major burden, i.e., breast cancer (BrCa), osteoarthritis (OA) and diabetes mellitus (DM). Differential methylation analysis was conducted to compare tissues/cells related to the pathology and different types of healthy tissues, revealing Differentially Methylated Genes (DMGs). Highly performing and low feature number biosignatures were built with automated machine learning, including: (1) a five-gene biosignature discriminating BrCa tissue from healthy tissues (AUC 0.987 and precision 0.987), (2) three equivalent OA cartilage-specific biosignatures containing four genes each (AUC 0.978 and precision 0.986) and (3) a four-gene pancreatic ß-cell-specific biosignature (AUC 0.984 and precision 0.995). Next, the BrCa biosignature was validated using an independent ccfDNA dataset showing an AUC and precision of 1.000, verifying the biosignature's applicability in liquid biopsy. Functional and protein interaction prediction analysis revealed that most DMGs identified are involved in pathways known to be related to the studied diseases or pointed to new ones. Overall, our data-driven approach contributes to the maximum exploitation of high-throughput methylome readings, helping to establish specific disease profiles to be applied in clinical practice and to understand human pathology.

Effect of systemic treatment on the micronuclei frequency in the peripheral blood of patients with metastatic colorectal cancer.

Colorectal cancer (CRC) is the third most diagnosed type of cancer affecting males, and the second most diagnosed type of cancer affecting females, and one of the leading causes of cancer-related mortality globally. The estimation of the micronuclei (MN) frequency in peripheral blood lymphocytes (PBLs) from patients with CRC is proposed as a prognostic/predictive easy-to-use biomarker. In this study, we aimed to investigate the effects of systemic treatment on the MN frequency in PBLs from patients with CRC in order to determine the effectiveness of the MN frequency as a biomarker. For this purpose, from 2016 to 2018, we quantified the MN frequency as a prognostic/predictive biomarker in serial samples from 25 patients with metastatic CRC (mCRC) using cytokinesis block micronucleus assay (CBMN assay). The MN frequency in the PBLs of the patients was evaluated before, during the middle and at the end of the therapy (approximately 0, 3 and 6 months). The results revealed a common pattern regarding the fluctuation in the MN frequency. Statistical analysis confirmed that when the disease response was estimated with radiological criteria, a good response was depicted at the MN frequency and vice versa. Consequently, the findings of this study suggest that the MN frequency may serve as a promising prognostic/predictive biomarker for the monitoring of the treatment response of patients with CRC.