Cell-free DNA 5-hydroxymethylcytosine is highly sensitive for MRD assessment in acute myeloid leukemia

T7 Endonuclease I-Mediated Single-Base Mismatch Biosensing Strategy for High-Resolution Quantitative Analysis of 5-Hydroxymethylcytosine in Genomic DNA

5-hydroxymethylcytosine (5hmC) plays a pivotal role in the DNA demethylation pathway and transcriptional regulation. While sequencing-based methods such as TET-assisted bisulfite sequencing offer single-base resolution, they are not ideal for dynamic, time-sensitive quantification. Here, we present a novel enzymatic biosensing strategy leveraging T7 endonuclease I for rapid and locus-specific 5hmC detection with a single-base resolution. This electrochemical platform captures double-tagged dsDNA and detects 5hmC by monitoring the signal reduction upon T7 endonuclease cleavage of A-C mismatches. The method achieved high sensitivity, detecting as little as 10 pg of hydroxymethylated DNA amid a 100,000-fold excess of methylated or unmethylated DNA. Furthermore, we demonstrated its ability to quantify real-time 5hmC variation during umbilical cord mesenchymal stem cell differentiation. This approach offers a powerful tool for 5hmC analysis in dynamic biological processes.

Epigenetic modifications of cfDNA in liquid biopsy for the cancer care continuum

This review provides a comprehensive overview of the latest advancements in the clinical utility of liquid biopsy, with a particular focus on epigenetic approaches aimed at overcoming challenges in cancer diagnosis and treatment. It begins by elucidating key epigenetic terms, including methylomics, fragmentomics, and nucleosomics. The review progresses to discuss methods for analyzing circulating cell-free DNA (cfDNA) and highlights recent studies showcasing the clinical relevance of epigenetic modifications in areas such as diagnosis, drug treatment response, minimal residual disease (MRD) detection, and prognosis prediction. While acknowledging hurdles like the complexity of interpreting epigenetic data and the absence of standardization, the review charts a path forward. It advocates for the integration of multi-omic data through machine learning algorithms to refine predictive models and stresses the importance of collaboration among clinicians, researchers, and data scientists. Such cooperative efforts are essential to fully leverage the potential of epigenetic features in clinical practice.

Clinical applications of circulating tumor DNA in hematological malignancies: From past to the future

Liquid biopsy, particularly circulating tumor DNA (ctDNA), has drawn a lot of attention as a non- or minimal-invasive detection approach for clinical applications in patients with cancer. Many hematological malignancies are well suited for serial and repeated ctDNA surveillance due to relatively high ctDNA concentrations and high loads of tumor-specific genetic and epigenetic abnormalities. Progress of detecting technology in recent years has improved sensitivity and specificity significantly, thus broadening and strengthening the potential utilities of ctDNA including early diagnosis, prognosis estimation, treatment response evaluation, minimal residual disease monitoring, targeted therapy selection, and immunotherapy surveillance. This manuscript reviews the detection methodologies, clinical application and future challenges of ctDNA in hematological malignancies, especially for lymphomas, myeloma and leukemias.

5-Hydroxymethylcytosine in Cell-Free DNA Predicts Immunotherapy Response in Lung Cancer

Immune checkpoint inhibitors (ICIs) drastically improve therapeutic outcomes for lung cancer, but accurately predicting individual patient responses to ICIs remains a challenge. We performed the genome-wide profiling of 5-hydroxymethylcytosine (5hmC) in 85 plasma cell-free DNA (cfDNA) samples from lung cancer patients and developed a 5hmC signature that was significantly associated with progression-free survival (PFS). We built a 5hmC predictive model to quantify the 5hmC level and validated the model in the validation, test, and control sets. Low weighted predictive scores (wp-scores) were significantly associated with a longer PFS compared to high wp-scores in the validation [median 7.6 versus 1.8 months; p = 0.0012; hazard ratio (HR) 0.12; 95% confidence interval (CI), 0.03-0.54] and test (median 14.9 versus 3.3 months; p = 0.00074; HR 0.10; 95% CI, 0.02-0.50) sets. Objective response rates in patients with a low or high wp-score were 75.0% (95% CI, 42.8-94.5%) versus 0.0% (95% CI, 0.0-60.2%) in the validation set (p = 0.019) and 80.0% (95% CI, 44.4-97.5%) versus 0.0% (95% CI, 0.0-36.9%) in the test set (p = 0.0011). The wp-scores were also significantly associated with PFS in patients receiving single-agent ICI treatment (p < 0.05). In addition, the 5hmC predictive signature demonstrated superior predictive capability to tumor programmed death-ligand 1 and specificity to ICI treatment response prediction. Moreover, we identified novel 5hmC-associated genes and signaling pathways integral to ICI treatment response in lung cancer. This study provides proof-of-concept evidence that the cfDNA 5hmC signature is a robust biomarker for predicting ICI treatment response in lung cancer.

Cell-Free DNA 5-Hydroxymethylcytosine Signatures for Lung Cancer Prognosis

Accurate prognostic markers are essential for guiding effective lung cancer treatment strategies. The level of 5-hydroxymethylcytosine (5hmC) in tissue is independently associated with overall survival (OS) in lung cancer patients. We explored the prognostic value of cell-free DNA (cfDNA) 5hmC through genome-wide analysis of 5hmC in plasma samples from 97 lung cancer patients. In both training and validation sets, we discovered a cfDNA 5hmC signature significantly associated with OS in lung cancer patients. We built a 5hmC prognostic model and calculated the weighted predictive scores (wp-score) for each sample. Low wp-scores were significantly associated with longer OS compared to high wp-scores in the training [median 22.9 versus 8.2 months; p = 1.30 × 10-10; hazard ratio (HR) 0.04; 95% confidence interval (CI), 0.00-0.16] and validation (median 18.8 versus 5.2 months; p = 0.00059; HR 0.22; 95% CI: 0.09-0.57) sets. The 5hmC signature independently predicted prognosis and outperformed age, sex, smoking, and TNM stage for predicting lung cancer outcomes. Our findings reveal critical genes and signaling pathways with aberrant 5hmC levels, enhancing our understanding of lung cancer pathophysiology. The study underscores the potential of cfDNA 5hmC as a superior prognostic tool for guiding more personalized therapeutic strategies for lung cancer patients.