Circulating H3K27 Methylated Nucleosome Plasma Concentration: Synergistic Information with Circulating Tumor DNA Molecular Profiling.

The molecular profiling of circulating tumor DNA (ctDNA) is a helpful tool not only in cancer treatment, but also in the early detection of relapse. However, the clinical interpretation of a ctDNA negative result remains challenging. The characterization of circulating nucleosomes (carrying cell-free DNA) and associated epigenetic modifications (playing a key role in the tumorigenesis of different cancers) may provide useful information for patient management, by supporting the contributive value of ctDNA molecular profiling. Significantly elevated concentrations of H3K27Me3 nucleosomes were found in plasmas at the diagnosis, and during the follow-up, of NSCLC patients, compared to healthy donors (p-value < 0.0001). By combining the H3K27Me3 level and the ctDNA molecular profile, we found that 25.5% of the patients had H3K27Me3 levels above the cut off, and no somatic alteration was detected at diagnosis. This strongly supports the presence of non-mutated ctDNA in the corresponding plasma. During the patient follow-up, a high H3K27Me3-nucleosome level was found in 15.1% of the sample, despite no somatic mutations being detected, allowing the identification of disease progression from 43.1% to 58.2% over molecular profiling alone. Measuring H3K27Me3-nucleosome levels in combination with ctDNA molecular profiling may improve confidence in the negative molecular result for cfDNA in lung cancer at diagnosis, and may also be a promising biomarker for molecular residual disease (MRD) monitoring, during and/or after treatment.

Evaluation of nucleosome concentrations in healthy dogs and dogs with cancer.

INTRODUCTION: Nucleosomes consist of small fragments of DNA wrapped around a histone octamer core. Diseases such as cancer or inflammation lead to cell death, which causes fragmentation and release of nucleosomes into the blood. The Nu.Q™ technology measures circulating nucleosome levels and exploits the different compositions of cancer derived nucleosomes in blood to detect and identify cancer even at early stages. The objectives of this study are to identify the optimal sample type for the Nu.Q™ H3.1 assay and to determine if it can accurately detect nucleosomes in the blood of healthy canines as well as those with cancer. MATERIALS AND METHODS: Blood samples from healthy canine volunteers as well as dogs newly diagnosed with lymphoma were used. The blood was processed at a variety of times under a variety of conditions to determine the most reliable sample type and conditions, and to develop an appropriate processing strategy to ensure reliably accurate results. RESULTS: Nucleosomes could be detected using a variety of sample collection and processing protocols. Nucleosome signals were highest in EDTA plasma and serum samples and most consistent in plasma. Samples should be processed within an hour of collection. Experiments showed that samples were able to withstand several freeze thaw cycles. Processing time and tcollection tube type did affect nucleosome detection levels. Finally, significantly elevated concentrations of nucleosomes were seen in a small cohort of dogs that had been newly diagnosed with lymphoma. CONCLUSIONS: When samples are collected and processed appropriately, the Nu.Q™ platform can reliably detect nucleosomes in the plasma of dogs. Further testing is underway to validate and optimize the Nu.Q™ platform for veterinary use.

A new nucleosomic-based model to identify and diagnose SSc-ILD.

BACKGROUND: Systemic sclerosis (SSc) is a rare connective tissue disease associated with rapid evolving interstitial lung disease (SSc-ILD), driving its mortality. Specific biomarkers associated with the evolution of the lung disease are highly needed. We aimed to identify specific biomarkers of SSc-ILD to predict the evolution of the disease. Nucleosomes are stable DNA/protein complexes that are shed into the blood stream making them ideal candidates for biomarkers. METHODS: We studied circulating cell-free nucleosomes (cf-nucleosomes) in SSc patients, 31 with ILD (SSc-ILD) and 67 without ILD. We analyzed plasma levels for cf-nucleosomes and investigated whether global circulating nucleosome levels in association with or without other biomarkers of interest for systemic sclerosis or lung fibrosis (e.g., serum growth factors: IGFBP-1 and the MMP enzyme: MMP-9), could be suitable potential biomarkers for the correct identification of SSc-ILD disease. RESULTS: We found that H3.1 nucleosome levels were significantly higher in patients with SSc-ILD compared SSc patients without ILD (p < 0.05) and levels of MMP-9 were significantly increased in patients with SSc-ILD compared to SSc patients without ILD (p < 0.05). Conversely, IGFBP-1 was significantly reduced in patients with SSc-ILD compared to SSc without ILD (p < 0.001). The combination of cf-nucleosomes H3.1 coupled to MMP-9 and IGFBP-1 increased the sensitivity for the differential detection of SSc-ILD. High levels of accuracy were reached with this combined model: its performances are strong with 68.4% of positive predictive value and 77.2% of negative predictive value for 90% of specificity. With our model, we identified a significant negative correlation with FVC % pred (r = -0.22) and TLC % pred (r = -0.31). The value of our model at T1 (baseline) has a predictive power over the Rodnan score at T2 (after 6-18 months), showed by a significant linear regression with R2 = 19% (p = 0.013). We identified in the sole group of SSc-ILD patients a significant linear regression with a R2 = 54.4% with the variation of DLCO between T1 and T2 (p < 0.05). CONCLUSION: In our study, we identified a new blood-based model with nucleosomic biomarker in order to diagnose SSc-ILD in a SSc cohort. This model is correlated with TLC and FVC at baseline and predictive of the skin evolution and the DLCO. Further longitudinal exploration studies should be performed in order to evaluate the potential of such diagnostic and predictive model.