A Highly Sensitive and Specific Non-Invasive Test through Genome-Wide 5-Hydroxymethylation Mapping for Early Detection of Lung Cancer

A multiomics dataset of paired CT image and plasma cell-free DNA end motif for patients with pulmonary nodules

Diagnosing lung cancer at a curable stage offers the opportunity for a favorable prognosis. The emerging epigenomics analysis on plasma cell-free DNA (cfDNA), including 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) modifications, has acted as a promising approach facilitating the identification of lung cancer. And, integrating 5mC biomarker with chest computed tomography (CT) image features could optimize the diagnosis of lung cancer, exceeding the performance of models built on single feature. However, the clinical applicability of integrated markers might be limited by the potential risk of overfitting due to small sample size. Hence, we prospectively collected peripheral blood sample and the paired chest CT images of 2032 patients with indeterminate pulmonary nodules across 5 centers, and constructed a large-scale, multi-institutional, multiomics database that encompass CT imaging data and plasma cfDNA fragmentomic in 5mC-, 5hmC-enriched regions. To our best knowledge, this dataset is the first radio-epigenomic dataset with the largest sample size, and provides multi-dimensional insights for early diagnosis of lung cancer, facilitating the individuated management for lung cancer.

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.

Integrated multiomics signatures to optimize the accurate diagnosis of lung cancer

Diagnosing lung cancer from indeterminate pulmonary nodules (IPLs) remains challenging. In this multi-institutional study involving 2032 participants with IPLs, we integrate the clinical, radiomic with circulating cell-free DNA fragmentomic features in 5-methylcytosine (5mC)-enriched regions to establish a multiomics model (clinic-RadmC) for predicting the malignancy risk of IPLs. The clinic-RadmC yields an area-under-the-curve (AUC) of 0.923 on the external test set, outperforming the single-omics models, and models that only combine clinical features with radiomic, or fragmentomic features in 5mC-enriched regions (p < 0.050 for all). The superiority of the clinic-RadmC maintains well even after adjusting for clinic-radiological variables. Furthermore, the clinic-RadmC-guided strategy could reduce the unnecessary invasive procedures for benign IPLs by 10.9% ~ 35%, and avoid the delayed treatment for lung cancer by 3.1% ~ 38.8%. In summary, our study indicates that the clinic-RadmC provides a more effective and noninvasive tool for optimizing lung cancer diagnoses, thus facilitating the precision interventions.

Cell-free and extrachromosomal DNA profiling of small cell lung cancer

Small cell lung cancer (SCLC) is highly aggressive with poor prognosis. Despite a relative prevalence of circulating tumour DNA (ctDNA) in SCLC, liquid biopsies are not currently implemented, unlike non-SCLC where cell-free DNA (cfDNA) mutation profiling in the blood has utility for guiding targeted therapies and assessing minimal residual disease. cfDNA methylation profiling is highly sensitive for SCLC detection and holds promise for disease monitoring and molecular subtyping; cfDNA fragmentation profiling has also demonstrated clinical potential. Extrachromosomal DNA (ecDNA), that is often observed in SCLC, promotes tumour heterogeneity and chemotherapy resistance and can be detected in blood. We discuss how these cfDNA profiling modalities can be harnessed to expand the clinical applications of liquid biopsy in SCLC.

Elucidating epigenetic landscape of gastric premalignant lesions through genome-wide mapping of 5-hydroxymethylcytosines: A 12-year median follow-up study

BACKGROUND

Epigenetic modifications are crucial in tumourigenesis, yet the changes in novel epigenetic regulators like 5-hydroxymethylcytosines (5hmC) during the evolution of gastric premalignant lesions remain poorly understood. This study aims to investigate the implications of 5hmC in the progression from gastric premalignant lesions to gastric adenocarcinoma (GAC).

METHODS

To our knowledge, we conducted the largest and longest longitudinal study of a Chinese population with gastric precursor lesions, involving 29,176 patients with gastritis who underwent gastroscopy and biopsy between 2001 and 2015, with follow-up until 1 August, 2022. The median follow-up time was 12.2 years, and the overall GAC incidence rate was 0.82%. Genome-wide mapping of 5hmC in gastric premalignant lesions from a subset of individuals was performed using the 5hmC-Seal assay, including 21 samples that progressed to GAC during follow-up and 48 non-progressed age- and sex-matched controls.

RESULTS

We identified 213 differentially modified gene bodies, primarily concentrated in pathways related to cell division, cell cycle, energy metabolism, inflammation and tumourigenesis. An exploratory study was conducted to summarize a 5hmC-based epigenetic model for predicting cancer progression using multivariable logistic regression and machine learning. The nine-gene model showed an area under the curve of 87.5% (95% confidence interval: 72%-100%) in the validation samples (one of three), which were set aside before model training.

CONCLUSIONS

This study is the first to explore the 5hmC molecular landscape in gastric premalignant lesions, suggesting relevant pathways implicated in their evolution to GAC as well as the feasibility of exploiting genome-wide 5hmC mapping in assessing the risk of future cancer progression.

KEY POINTS

A largest longitudinal follow-up study of gastric precursor lesions in Chinese patients. Revealing novel 5hmC molecular landscape linked to gastric premalignant lesions. The feasibility of an innovative 5hmC-based predictive model for assessing gastric cancer progression risk.

Luteolin-Loaded Hyaluronidase Nanoparticles with Deep Tissue Penetration Capability for Idiopathic Pulmonary Fibrosis Treatment

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive interstitial lung disease characterized by sustained fibrotic lesions. Orally administered drugs usually fail to efficiently penetrate the interstitial tissue and reach the lesions, resulting in low treatment efficiency. Luteolin (Lut) is a natural flavonoid, active metabolites of which possess antioxidant, anti-inflammatory, anti-fibrotic, and anti-apoptotic properties. In this study, a nano-formulation is developed by loading Lut into hyaluronidase nanoparticles (Lut@HAase). These Lut@HAase nanoparticles (NPs) exhibit small size and good stability, suitable for noninvasive inhalation and accumulation in the lungs, and hyaluronidase at the site of lesions can degrade hyaluronic acid in the interstitial tissue, enabling efficient penetration of Lut. Lut's therapeutic effect, when administered via NPs, is studied both in vitro (using MRC5 cells) and in vivo (using IPF mice models), and its anti-fibrotic properties are found to inhibit inflammation and eliminate reactive oxygen species. Conclusively, this study demonstrates that Lut@HAase can improve lung function and enhance survival rates while reducing lung damage with few abnormalities during IPF treatment.

5-Hydroxymethylated Biomarkers in Cell-Free DNA Predict Occult Colorectal Cancer up to 36 Months Before Diagnosis in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial

PURPOSE

Using the prostate, lung, colorectal, and ovarian (PLCO) Cancer Screening Trial samples, we identified cell-free DNA (cfDNA) candidate biomarkers bearing the epigenetic mark 5-hydroxymethylcytosine (5hmC) that detected occult colorectal cancer (CRC) up to 36 months before clinical diagnosis.

MATERIALS AND METHODS

We performed the 5hmC-seal assay and sequencing on ≤8 ng cfDNA extracted from PLCO study participant plasma samples, including n = 201 cases (diagnosed with CRC within 36 months of blood collection) and n = 401 controls (no cancer diagnosis on follow-up). We conducted association studies and machine learning modeling to analyze the genome-wide 5hmC profiles within training and validation groups that were randomly selected at a 2:1 ratio.

RESULTS

We successfully obtained 5hmC profiles from these decades-old samples. A weighted Cox model of 32 5hmC-modified gene bodies showed a predictive detection value for CRC as early as 36 months before overt tumor diagnosis (training set AUC, 77.1% [95% CI, 72.2 to 81.9] and validation set AUC, 72.8% [95% CI, 65.8 to 79.7]). Notably, the 5hmC-based predictive model showed comparable performance regardless of sex and race/ethnicity, and significantly outperformed risk factors such as age and obesity (assessed as BMI). Finally, when splitting cases at median weighted prediction scores, Kaplan-Meier analyses showed significant risk stratification for CRC occurrence in both the training set (hazard ratio, [HR], 3.3 [95% CI, 2.6 to 5.8]) and validation set (HR, 3.1 [95% CI, 1.8 to 5.8]).

CONCLUSION

Candidate 5hmC biomarkers and a scoring algorithm have the potential to predict CRC occurrence despite the absence of clinical symptoms and effective predictors. Developing a minimally invasive clinical assay that detects 5hmC-modified biomarkers holds promise for improving early CRC detection and ultimately patient outcomes.

Cell-Free DNA Hydroxymethylation in Cancer: Current and Emerging Detection Methods and Clinical Applications

In the era of precision oncology, identifying abnormal genetic and epigenetic alterations has transformed the way cancer is diagnosed, managed, and treated. 5-hydroxymethylcytosine (5hmC) is an emerging epigenetic modification formed through the oxidation of 5-methylcytosine (5mC) by ten-eleven translocase (TET) enzymes. DNA hydroxymethylation exhibits tissue- and cancer-specific patterns and is essential in DNA demethylation and gene regulation. Recent advancements in 5hmC detection methods and the discovery of 5hmC in cell-free DNA (cfDNA) have highlighted the potential for cell-free 5hmC as a cancer biomarker. This review explores the current and emerging techniques and applications of DNA hydroxymethylation in cancer, particularly in the context of cfDNA.

A 5-Hydroxymethylcytosine-Based Noninvasive Model for Early Detection of Colorectal Carcinomas and Advanced Adenomas: The METHOD-2 Study

PURPOSE

Detection of colorectal carcinomas at a time when there are more treatment options is associated with better outcomes. This prospective case-control study assessed the 5-hydroxymethylcytosine (5hmC) biomarkers in circulating cell-free DNA (cfDNA) for early detection of colorectal carcinoma and advanced adenomas (AA).

EXPERIMENTAL DESIGN

Plasma cfDNA samples from 2,576 study participants from the multicenter METHOD-2 study (NCT03676075) were collected, comprising patients with newly diagnosed colorectal carcinoma (n = 1,074), AA (n = 356), other solid tumors (n = 80), and non-colorectal carcinoma/AA controls (n = 1,066), followed by genome-wide 5hmC profiling using the 5hmC-Seal technique and the next-generation sequencing. A weighted diagnostic model for colorectal carcinoma (stage I-III) and AA was developed using the elastic net regularization in a discovery set and validated in independent samples.

RESULTS

Distribution of 5hmC in cfDNA reflected gene regulatory relevance and tissue of origin. Besides being confirmed in internal validation, a 96-gene model achieved an area under the curve (AUC) of 90.7% for distinguishing stage I-III colorectal carcinoma from controls in 321 samples from multiple centers for external validation, regardless of primary location or mutation status. This model also showed cancer-type specificity as well as high capacity for distinguishing AA from controls with an AUC of 78.6%. Functionally, differential 5hmC features associated with colorectal carcinoma and AA demonstrated relevance to colorectal carcinoma biology, including pathways such as calcium and MAPK signaling.

CONCLUSIONS

Genome-wide mapping of 5hmC in cfDNA shows promise as a highly sensitive and specific noninvasive blood test to be integrated into screening programs for improving early detection of colorectal carcinoma and high-risk AA.

Machine learning identifies cell-free DNA 5-hydroxymethylation biomarkers that detect occult colorectal cancer in PLCO Screening Trial subjects

Background

Colorectal cancer (CRC) is a leading cause of cancer-related mortality, and CRC detection through screening improves survival rates. A promising avenue to improve patient screening compliance is the development of minimally-invasive liquid biopsy assays that target CRC biomarkers on circulating cell-free DNA (cfDNA) in peripheral plasma. In this report, we identify cfDNA biomarker candidate genes bearing the epigenetic mark 5-hydroxymethylcytosine (5hmC) that diagnose occult CRC up to 36 months prior to clinical diagnosis using the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial samples.

Methods

Archived PLCO Trial plasma samples containing cfDNA were obtained from the National Cancer Institute (NCI) biorepositories. Study subjects included those who were diagnosed with CRC within 36 months of blood collection (i.e., case, n = 201) and those who were not diagnosed with any cancer during an average of 16.3 years of follow-up (i.e., controls, n = 402). Following the extraction of 3 - 8 ng cfDNA from less than 300 microliters plasma, we employed the sensitive 5hmC-Seal chemical labeling approach, followed by next-generation sequencing (NGS). We then conducted association studies and machine-learning modeling to analyze the genome-wide 5hmC profiles within training and validation groups that were randomly selected at a 2:1 ratio.

Results

Despite the technical challenges associated with the PLCO samples (e.g., limited plasma volumes, low cfDNA amounts, and long archival times), robust genome-wide 5hmC profiles were successfully obtained from these samples. Association analyses using the Cox proportional hazards models suggested several epigenetic pathways relevant to CRC development distinguishing cases from controls. A weighted Cox model, comprised of 32-associated gene bodies, showed predictive detection value for CRC as early as 24-36 months prior to overt tumor presentation, and a trend for increased predictive power was observed for blood samples collected closer to CRC diagnosis. Notably, the 5hmC-based predictive model showed comparable performance regardless of sex and self-reported race/ethnicity, and significantly outperformed risk factors such as age and obesity according to BMI (body mass index). Additionally, further improvement of predictive performance was achieved by combining the 5hmC-based model and risk factors for CRC.

Conclusions

An assay of 5hmC epigenetic signals on cfDNA revealed candidate biomarkers with the potential to predict CRC occurrence despite the absence of clinical symptoms or the availability of effective predictors. Developing a minimally-invasive clinical assay that detects 5hmC-modified biomarkers holds promise for improving early CRC detection and ultimately patient survival through higher compliance screening and earlier intervention. Future investigation to expand this strategy to prospectively collected samples is warranted.