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Liquid biopsies are revolutionizing the detection and management of malignant diseases. While repetitive DNA sequences, such as LINE-1 and ALU are established in cell-free DNA (cfDNA) research, their clinical applications remain limited. In this study, we explore human satellite 2 (HSATII), a prevalent repeat DNA sequence in plasma that exhibits increased levels in cancer patients, thereby positioning it as a potential pan-cancer biomarker. We employed targeted sequencing and copy number variation (CNV) analysis using two primer pairs to assess the differential abundance of HSATII sequences in the plasma of breast cancer patients compared to healthy individuals. PCR amplicons of HSATII from 10 patients and 10 control subjects were sequenced, generating 151 bp paired-end reads. By constructing a pooled reference dataset, HSATII copy ratios were estimated in the patients. Our analysis revealed several significant CNVs in HSATII, with certain sequences displaying notable gains and losses across all breast cancer patients, suggesting their potential as biomarkers. However, we observed pronounced fragmentation of cfDNA in cancer, leading to the loss of longer PCR amplicons (>180 bp). While not all observed losses can be attributed to fragmentation artifacts, this phenomenon does introduce complexity in interpreting CNV data. Notably, this research marks the first instance of targeted HSATII sequencing in a liquid biopsy context. Our findings lay the groundwork for developing sequencing-based assays to detect differentially represented HSATII sequences, potentially advancing the field of minimally-invasive cancer screening. [ABSTRACT FROM AUTHOR]

Body fluids are constantly replenished with a population of genetically diverse cell-free DNA (cfDNA) fragments, representing a vast reservoir of information reflecting real-time changes in the host and metagenome. As many body fluids can be collected non-invasively in a one-off and serial fashion, this reservoir can be tapped to develop assays for the diagnosis, prognosis, and monitoring of wide-ranging pathologies, such as solid tumors, fetal genetic abnormalities, rejected organ transplants, infections, and potentially many others. The translation of cfDNA research into useful clinical tests is gaining momentum, with recent progress being driven by rapidly evolving preanalytical and analytical procedures, integrated bioinformatics, and machine learning algorithms. Yet, despite these spectacular advances, cfDNA remains a very challenging analyte due to its immense heterogeneity and fluctuation in vivo. It is increasingly recognized that high-fidelity reconstruction of the information stored in cfDNA, and in turn the development of tests that are fit for clinical roll-out, requires a much deeper understanding of both the physico-chemical features of cfDNA and the biological, physiological, lifestyle, and environmental factors that modulate it. This is a daunting task, but with significant upsides. In this review we showed how expanded knowledge on cfDNA biology and faithful reverse-engineering of cfDNA samples promises to (i) augment the sensitivity and specificity of existing cfDNA assays; (ii) expand the repertoire of disease-specific cfDNA markers, thereby leading to the development of increasingly powerful assays; (iii) reshape personal molecular medicine; and (iv) have an unprecedented impact on genetics research. [ABSTRACT FROM AUTHOR]