Background: Nucleosome repositioning in cancer is believed to cause many changes in genome organisation and gene expression. Understanding these changes is important to elucidate fundamental aspects of cancer. It is also important for medical diagnostics based on cell-free DNA (cfDNA), which originates from genomic DNA regions protected from digestion by nucleosomes.
Results: We have generated high-resolution nucleosome maps in paired tumour and normal tissues from the same breast cancer patients using MNase-assisted histone H3 ChIP-seq and compared them with the corresponding cfDNA from blood plasma. This analysis has detected single-nucleosome repositioning at key regulatory regions in a patient-specific manner and common cancer-specific patterns across patients. The nucleosomes gained in tumour versus normal tissue were particularly informative of cancer pathways, with ~ 20-fold enrichment at CpG islands, a large fraction of which marked promoters of genes encoding DNA-binding proteins. The tumour tissues were characterised by a 5-10 bp decrease in the average distance between nucleosomes (nucleosome repeat length, NRL), which is qualitatively similar to the differences between pluripotent and differentiated cells. This effect was correlated with gene activity, differential DNA methylation and changes in local occupancy of linker histone variants H1.4 and H1X.
Conclusions: Our study offers a novel resource of high-resolution nucleosome maps in breast cancer patients and reports for the first time the effect of systematic decrease of NRL in paired tumour versus normal breast tissues from the same patient. Our findings provide a new mechanistic understanding of nucleosome repositioning in tumour tissues that can be valuable for patient diagnostics, stratification and monitoring.
Background: miR-182 promoter hypermethylation frequently occurs in various tumors, including acute myeloid leukemia, and leads to low expression of miR-182. However, whether adult acute lymphocyte leukemia (ALL) cells have high miR-182 promoter methylation has not been determined.
Methods: To assess the methylation status of the miR-182 promoter, methylation and unmethylation-specific PCR analysis, bisulfite-sequencing analysis, and MethylTarget™ assays were performed to measure the frequency of methylation at the miR-182 promoter. Bone marrow cells were isolated from miR-182 knockout (182KO) and 182 wild type (182WT) mice to construct BCR-ABL (P190) and Notch-induced murine B-ALL and T-ALL models, respectively. Primary ALL samples were performed to investigate synergistic effects of the hypomethylation agents (HMAs) and the BCL2 inhibitor venetoclax (Ven) in vitro.
Results: miR-182 (miR-182-5P) expression was substantially lower in ALL blasts than in normal controls (NCs) because of DNA hypermethylation at the miR-182 promoter in ALL blasts but not in normal controls (NCs). Knockout of miR-182 (182KO) markedly accelerated ALL development, facilitated the infiltration, and shortened the OS in a BCR-ABL (P190)-induced murine B-ALL model. Furthermore, the 182KO ALL cell population was enriched with more leukemia-initiating cells (CD43+B220+ cells, LICs) and presented higher leukemogenic activity than the 182WT ALL population. Furthermore, depletion of miR-182 reduced the OS in a Notch-induced murine T-ALL model, suggesting that miR-182 knockout accelerates ALL development. Mechanistically, overexpression of miR-182 inhibited proliferation and induced apoptosis by directly targeting PBX3 and BCL2, two well-known oncogenes, that are key targets of miR-182. Most importantly, DAC in combination with Ven had synergistic effects on ALL cells with miR-182 promoter hypermethylation, but not on ALL cells with miR-182 promoter hypomethylation.
Conclusions: Collectively, we identified miR-182 as a tumor suppressor gene in ALL cells and low expression of miR-182 because of hypermethylation facilitates the malignant phenotype of ALL cells. DAC + Ven cotreatment might has been applied in the clinical try for ALL patients with miR-182 promoter hypermethylation. Furthermore, the methylation frequency at the miR-182 promoter should be a potential biomarker for DAC + Ven treatment in ALL patients.
Background: The unknown tissue of origin in head and neck cancer of unknown primary (hnCUP) leads to invasive diagnostic procedures and unspecific and potentially inefficient treatment options for patients. The most common histologic subtype, squamous cell carcinoma, can stem from various tumor primary sites, including the oral cavity, oropharynx, larynx, head and neck skin, lungs, and esophagus. DNA methylation profiles are highly tissue-specific and have been successfully used to classify tissue origin. We therefore developed a support vector machine (SVM) classifier trained with publicly available DNA methylation profiles of commonly cervically metastasizing squamous cell carcinomas (n = 1103) in order to identify the primary tissue of origin of our own cohort of squamous cell hnCUP patient's samples (n = 28). Methylation analysis was performed with Infinium MethylationEPIC v1.0 BeadChip by Illumina.
Results: The SVM algorithm achieved the highest overall accuracy of tested classifiers, with 87%. Squamous cell hnCUP samples on DNA methylation level resembled squamous cell carcinomas commonly metastasizing into cervical lymph nodes. The most frequently predicted cancer localization was the oral cavity in 11 cases (39%), followed by the oropharynx and larynx (both 7, 25%), skin (2, 7%), and esophagus (1, 4%). These frequencies concord with the expected distribution of lymph node metastases in epidemiological studies.
Conclusions: On DNA methylation level, hnCUP is comparable to primary tumor tissue cancer types that commonly metastasize to cervical lymph nodes. Our SVM-based classifier can accurately predict these cancers' tissues of origin and could significantly reduce the invasiveness of hnCUP diagnostics and enable a more precise therapy after clinical validation.
Background: Epigenetic Scores (EpiScores) for blood protein levels have been associated with disease outcomes and measures of brain health, highlighting their potential usefulness as clinical biomarkers. They are typically derived via penalised regression, whereby a linear weighted sum of DNA methylation (DNAm) levels at CpG sites are predictive of protein levels. Here, we examine 84 previously published protein EpiScores as possible biomarkers of cross-sectional and longitudinal measures of general cognitive function and brain health, and incident dementia across three independent cohorts.
Results: Using 84 protein EpiScores as candidate biomarkers, associations with general cognitive function (both cross-sectionally and longitudinally) were tested in three independent cohorts: Generation Scotland (GS), and the Lothian Birth Cohorts of 1921 and 1936 (LBC1921 and LBC1936, respectively). A meta-analysis of general cognitive functioning results in all three cohorts identified 18 EpiScore associations (absolute meta-analytic standardised estimates ranged from 0.03 to 0.14, median of 0.04, PFDR < 0.05). Several associations were also observed between EpiScores and global brain volumetric measures in the LBC1936. An EpiScore for the S100A9 protein (a known Alzheimer disease biomarker) was associated with general cognitive functioning (meta-analytic standardised beta: - 0.06, P = 1.3 × 10-9), and with time-to-dementia in GS (Hazard ratio 1.24, 95% confidence interval 1.08-1.44, P = 0.003), but not in LBC1936 (Hazard ratio 1.11, P = 0.32).
Conclusions: EpiScores might make a contribution to the risk profile of poor general cognitive function and global brain health, and risk of dementia, however these scores require replication in further studies.
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