Sensitive tumour detection and classification using plasma cell-free DNA methylomes

RNA methylation: A new promising biomaker in cancer liquid biopsy

RNA methylation is a vital epigenetic modification that regulates gene expression by influencing RNA processes such as transcription, degradation, translation, and transport. Aberrant methylation, including modifications like m6A, m5C, m1A, m7G, and m3C, is closely linked to tumorigenesis and progression. Liquid biopsy, a non-invasive technique analyzing tumor markers in body fluids, offers significant potential for early diagnosis and dynamic monitoring. In this context, RNA methylation, due to its tumor-specific properties, is emerging as a valuable marker. However, significant challenges remain in its clinical application. This review explores the roles of RNA methylation in cancer, recent advances in detection technologies, and its potential as a liquid biopsy marker in tumor management. It highlights its promising applications in cancer diagnosis, prognosis, and personalized treatment in the era of precision oncology.

Artificial Intelligence in cancer epigenomics: a review on advances in pan-cancer detection and precision medicine

DNA methylation is a fundamental epigenetic modification that regulates gene expression and maintains genomic stability. Consequently, DNA methylation remains a key biomarker in cancer research, playing a vital role in diagnosis, prognosis, and tailored treatment strategies. Aberrant methylation patterns enable early cancer detection and therapeutic stratification; however, their complex patterns necessitates advanced analytical tools. Recent advances in artificial intelligence (AI) and machine learning (ML), including deep learning networks and graph-based models, have revolutionized cancer epigenomics by enabling rapid, high-resolution analysis of DNA methylation profiles. Moreover, these technologies are accelerating the development of Multi-Cancer Early Detection (MCED) tests, such as GRAIL's Galleri and CancerSEEK, which improve diagnostic accuracy across diverse cancer types. In this review, we explore the synergy between AI and DNA methylation profiling to advance precision oncology. We first examine the role of DNA methylation as a biomarker in cancer, followed by an overview of DNA profiling technologies. We then assess how AI-driven approaches transform clinical practice by enabling early detection and accurate classification. Despite their promise, challenges remain, including limited sensitivity for early-stage cancers, the black-box nature of many AI algorithms, and the need for validation across diverse populations to ensure equitable implementation. Future directions include integrating multi-omics data, developing explainable AI frameworks, and addressing ethical concerns, such as data privacy and algorithmic bias. By overcoming these gaps, AI-powered epigenetic diagnostics can enable earlier detection, more effective treatments, and improved patient outcomes, globally. In summary, this review synthesizes current advancements in the field and envisions a future where AI and epigenomics converge to redefine cancer diagnostics and therapy.

Promises and pitfalls of multi-cancer early detection using liquid biopsy tests

Cancer screening is an essential public health intervention for diagnosing cancers at an early stage that can enable earlier treatment - ideally with curative intent - and thus lead to improved outcomes. Over the past decade, liquid biopsy-based tests have emerged as a promising, minimally invasive and broadly applicable screening approach by combining multi-cancer early detection (MCED) with tumour tissue-of-origin identification. Large-scale randomized clinical trials evaluating liquid biopsy-based MCED approaches are now under way, although whether the diagnostic performance of this first generation of MCED tests is sufficient to translate into clinical benefits remains to be determined. In this Review, we discuss the promises and pitfalls of current MCED tests and highlight possible trajectories for the field of early cancer detection.

Liquid Biopsy Approaches for Cancer Characterization, Residual Disease Detection, and Therapy Monitoring

Liquid biopsy encompasses a variety of molecular approaches to detect circulating tumor DNA (ctDNA) and has become a powerful tool in the diagnosis and treatment of solid tumors. Current applications include comprehensive genomic profiling for identifying targetable mutations and therapeutic resistance mechanisms, with emerging applications in minimal residual disease detection and treatment response monitoring. Increasingly, the potential for liquid biopsy in guiding treatment decisions is under active investigation through prospective clinical trials using ctDNA-adaptive interventions in patients with early-stage and metastatic cancers. Limitations arise on the basis of the sensitivity and feasibility of individual liquid biopsy assays; nonetheless, emerging technologies set the stage for improving these shortcomings. As the global oncology community continues to ascertain the clinical value of liquid biopsy across the continuum of patient care, this minimally invasive approach heralds a significant advancement in the promise of precision oncology.

Modulating cell-free DNA biology as the next frontier in liquid biopsies

Technical advances over the past two decades have enabled robust detection of cell-free DNA (cfDNA) in biological samples. Yet, higher clinical sensitivity is required to realize the full potential of liquid biopsies. This opinion article argues that to overcome current limitations, the abundance of informative cfDNA molecules - such as circulating tumor DNA (ctDNA) - collected in a sample needs to increase. To accomplish this, new methods to modulate the biological processes that govern cfDNA production, trafficking, and clearance in the body are needed, informed by a deeper understanding of cfDNA biology. Successful development of such methods could enable a major leap in the performance of liquid biopsies and vastly expand their utility across the spectrum of clinical care.

Tumor-educated platelet, a potential liquid biopsy biosource in pancreatic cancer: A review

Pancreatic cancer (PC) is a frequent and aggressive digestive system cancer with a very poor prognosis. The best chance for recovery lies in early surgical removal of the tumor. Unfortunately, because PC often develops without noticeable symptoms, diagnosis is frequently delayed. Limited treatment options, the metastasis potential of pancreatic cancer cells, and its generally poor prognosis mean that patients are often diagnosed late, significantly reducing the effectiveness of treatment. Consequently, there's a critical need for new biomarkers and technologies to improve early detection through screening. Recently, the liquid biopsy has developed as a powerful means for detecting and monitoring cancer at the molecular level. Its advantages include the ease and non-invasive nature of sample collection and its ability to reflect the dynamic changes within a tumor. Platelets, the second most numerous type of blood cell, offer a particularly promising source for liquid biopsy. It is known that cancer affects various aspects of platelets, including their number, size, activation state, and the proteins and RNA they contain. However, the full implications of these changes for cancer detection have not yet been fully integrated into routine clinical practice. Platelets have a unique ability to captivate nucleic acids and proteins from their surroundings, and they alter their transcriptome in response to external signals. This leads to the development of tumor-educated platelets (TEPs). Liquid biopsies that utilize TEP biomarkers hold considerable potential for screening, early detection, prognosis, guiding personalized treatment strategies, ongoing monitoring of the disease, and predicting recurrence. Encouraging results from preclinical studies have highlighted the potential of platelets as a novel liquid biopsy source for a wide range of cancers. This review will explore the potential of using platelets as a liquid biopsy method, specifically for pancreatic cancer.

An artificial intelligence-based model for prediction of clonal hematopoiesis variants in cell-free DNA samples

Circulating tumor DNA is a critical biomarker in cancer diagnostics, but its accurate interpretation requires careful consideration of clonal hematopoiesis (CH), which can contribute to variants in cell-free DNA and potentially obscure true tumor-derived signals. Accurate detection of somatic variants of CH origin in plasma samples remains challenging in the absence of matched white blood cells sequencing. Here we present an open-source machine learning framework (MetaCH) which classifies variants in cfDNA from plasma-only samples as CH or tumor origin, surpassing state-of-the-art classification rates.

Coupling Immunoprecipitation with Multiplexed Digital PCR for Cell-Free DNA Methylation Detection in Small Plasma Volumes of Early-Onset Colorectal Cancer

Colorectal cancer (CRC) remains a major global health challenge, with an increasing incidence of early-onset cases among young adults. Targeted analysis of cell-free DNA (cfDNA) methylation in blood has emerged as a promising minimally invasive diagnostic approach. While digital PCR (dPCR) offers high sensitivity and low turnaround times, conventional bisulfite-based dPCR assays require large plasma volumes due to cfDNA degradation, limiting clinical feasibility. To overcome this limitation, we developed a bisulfite-free, low-plasma-volume assay by coupling cell-free methylated DNA immunoprecipitation (cfMeDIP) with multiplexed dPCR for methylation detection. Assays were designed for CRC targets based on publicly available bisulfite-based plasma data and optimized for native, bisulfite-untreated cfDNA. The cfMeDIP-dPCR assays were first developed and optimized on circulating tumor DNA surrogates derived from HCT116 cells and subsequently validated in a pilot study, including 32 early-onset CRC (EO-CRC) patients and 29 non-CRC individuals. Methylation ratios, defined as the proportion of methylated to total cfDNA copies per marker, served as a diagnostic indicator. Three out of four selected markers (SEPT9, KCNQ5, and C9orf50) were successfully adapted, with significantly higher methylation ratios (p ≤ 0.001) in the EO-CRC cohort. KCNQ5 demonstrated the highest diagnostic performance, achieving an 85% sensitivity at a 90% specificity, with methylation ratios correlating with the tumor stage. This study presents the first cfMeDIP-dPCR approach, demonstrating its potential as a sensitive liquid biopsy assay. Requiring only 0.5 mL of plasma, i.e., more than 20 times less than a sensitivity-matched bisulfite-based assay, cfMeDIP-dPCR facilitates clinical implementation for CRC and other diseases with epigenetic signatures.

Peak analysis of cell-free RNA finds recurrently protected narrow regions with clinical potential

BACKGROUND

Cell-free RNAs (cfRNAs) can be detected in biofluids and have emerged as valuable disease biomarkers. Accurate identification of the fragmented cfRNA signals, especially those originating from pathological cells, is crucial for understanding their biological functions and clinical value. However, many challenges still need to be addressed for their application, including developing specific analysis methods and translating cfRNA fragments with biological support into clinical applications.

RESULTS

We present cfPeak, a novel method combining statistics and machine learning models to detect the fragmented cfRNA signals effectively. When test in real and artificial cfRNA sequencing (cfRNA-seq) data, cfPeak shows an improved performance compared with other applicable methods. We reveal that narrow cfRNA peaks preferentially overlap with protein binding sites, vesicle-sorting sites, structural sites, and novel small non-coding RNAs (sncRNAs). When applied in clinical cohorts, cfPeak identified cfRNA peaks in patients' plasma that enable cancer detection and are informative of cancer types and metastasis.

CONCLUSIONS

Our study fills the gap in the current small cfRNA-seq analysis at fragment-scale and builds a bridge to the scientific discovery in cfRNA fragmentomics. We demonstrate the significance of finding low abundant tissue-derived signals in small cfRNA and prove the feasibility for application in liquid biopsy.

Are Non-invasive Multi-cancer Early Cancer Detection Tests the Future?

Current cancer screening methods are effective for detecting early stage cancers and even preventing some cancers, but their effectiveness has only been demonstrated for a handful of cancers, and for many cancers, there are no screening tests clinically available. In addition, the majority of the screening methods are not ideal, resulting in suboptimal compliance and the occurrence of preventable cancers. A screening test that is convenient, safe, accurate and that can screen for multiple cancers is an ideal screening test that would address many of the shortcomings of the current tests. Multi-cancer detection tests (MCD) have the potential to meet these challenges and have engendered substantial enthusiasm in light of this. Using advances in DNA sequencing technology, cancer epigenetics and artificial intelligence, they are able to detect a large number of cancers predominantly via the patterns of methylated DNA alterations, DNA sequence alterations, and DNA fragment patterns of cell free DNA in the plasma and can accurately distinguish the cancer site of origin. Of note, some of the tests also combine circulating free DNA (cfDNA) with protein-based markers. However, for the majority of early stage cancers, the sensitivity is modest and below that of most of the current standard of care cancer screening tests. Furthermore, the clinical utility of screening for many of the cancers detectable by MCD tests remains to be proven. Here we describe the features of MCD tests, review the current data supporting their potential to be used in the clinic for cancer screening, and discuss the knowledge gaps surrounding understanding their clinical utility, with a focus on GI cancer screening.

Genomic and fragmentomic landscapes of cell-free DNA for early cancer detection

Genomic analyses of cell-free DNA (cfDNA) in plasma are enabling noninvasive blood-based biomarker approaches to cancer detection and disease monitoring. Current approaches for identification of circulating tumour DNA typically use targeted tumour-specific mutations or methylation analyses. An emerging approach is based on the recognition of altered genome-wide cfDNA fragmentation in patients with cancer. Recent studies have revealed a multitude of characteristics that can affect the compendium of cfDNA fragments across the genome, collectively called the 'cfDNA fragmentome'. These changes result from genomic, epigenomic, transcriptomic and chromatin states of an individual and affect the size, position, coverage, mutation, structural and methylation characteristics of cfDNA. Identifying and monitoring these changes has the potential to improve early detection of cancer, especially using highly sensitive multi-feature machine learning approaches that would be amenable to broad use in populations at increased risk. This Review highlights the rapidly evolving field of genome-wide analyses of cfDNA characteristics, their comparison to existing cfDNA methods, and recent related innovations at the intersection of large-scale sequencing and artificial intelligence. As the breadth of clinical applications of cfDNA fragmentome methods have enormous public health implications for cancer screening and personalized approaches for clinical management of patients with cancer, we outline the challenges and opportunities ahead.

Peripheral Blood T-Cell Receptor Repertoire Diversity as a Potential Biomarker in the Diagnosis and Treatment Evaluation of Colorectal and Lung Cancers: A Prospective Observational Study

BACKGROUND

T-cell receptor (TCR) diversity 50 (D50) values could assess peripheral blood (PB) TCR diversity and immunity. This study aimed to evaluate the potential D50 value in the diagnosis and treatment evaluation of colorectal cancer (CRC) and nonsmall-cell lung cancer (NSCLC).

METHODS

This prospective observational study enrolled patients with CRC, benign colorectal disease (BCD), NSCLC, or benign nodule controls (BNC) and healthy donors (HD) at Yunnan Cancer Hospital between January 2021 and June 2022. PB specimens were used for TCRβ sequencing, and D50 was calculated and compared within different groups. The area under the curve (AUC) was used to evaluate the diagnostic performance of D50 in CRC and NSCLC.

RESULTS

A total of 114 HD and 115 CRC, 31 BCD, 67 NSCLC, and 25 BNC patients were enrolled. Both CRC and NSCLC patients exhibited significantly lower D50 compared with HDs (p < 0.001), whereas BCD and BNC patients showed a modest decrease in TCR diversity (p < 0.05). NSCLC patients with lymph node metastases had markedly lower D50 than those without lymph node metastasis (0.05 vs. 0.11, p < 0.01). Higher D50 was found in CRC and NSCLC patients with normal carcinoembryonic antigen (CEA) levels (p < 0.05). The potential of D50 value for early detection of CRC and NSCLC was demonstrated, with an area under the receiver operating characteristic curve (AUC) of 0.736 for CRC (sensitivity: 71.30%, specificity: 68.42%) and 0.768 for NSCLC (sensitivity: 83.58%, specificity: 60.53%). Significant differences in D50 values were observed between patients with tumor regression grade (TRG) 0-1 and those with TRG 2-3 (p = 0.027), with an AUC of 0.731 (sensitivity: 68.75%, specificity: 76.92%).

CONCLUSION

These findings suggest that the PB TCR D50 values may have significant clinical value in cancer diagnosis and in evaluating the efficacy of neoadjuvant therapies.

Liquid Biopsy on Microfluidics: From Existing Endogenous to Emerging Exogenous Biomarkers Analysis

Liquid biopsy is an appealing approach for early diagnosis and assessment of treatment efficacy in cancer. Typically, liquid biopsy involves the detection of endogenous biomarkers, including circulating tumor cells (CTCs), extracellular vesicles (EVs), circulating tumor DNA (ctDNA), circulating tumor RNA (ctRNA), and proteins. The levels of these endogenous biomarkers are higher in cancer patients compared to those in healthy individuals. However, the clinical application of liquid biopsy using endogenous biomarker analysis faces challenges due to its low abundance and poor stability in circulation. Recently, a promising strategy involving the engineering of exogenous probes has been developed to overcome these limitations. These exogenous probes are activated within the tumor microenvironment, generating distinct exogenous markers that can be easily distinguished from background biological signals. Alternatively, these exogenous probes can be labeled with intrinsic endogenous biomarkers in vivo and detected in vitro after metabolic processes. In this review, we primarily focus on microfluidic-based liquid biopsy techniques that allow for the transition from analyzing existing endogenous biomarkers to emerging exogenous ones. First, we introduce common endogenous biomarkers, as well as synthetic exogenous ones. Next, we discuss recent advancements in microfluidic-based liquid biopsy techniques for analyzing both existing endogenous and emerging exogenous biomarkers. Lastly, we provide insights into future directions for liquid biopsy on microfluidic systems.

DNA methylation in breast cancer: early detection and biomarker discovery through current and emerging approaches

Breast cancer remains one of the most common cancers in women worldwide. Early detection is critical for improving patient outcomes, yet current screening methods have limitations. Therefore, there is a pressing need for more sensitive and specific approaches to detect breast cancer in its earliest stages. Liquid biopsy has emerged as a promising non-invasive method for early cancer detection and management. DNA methylation, an epigenetic alteration that often precedes genetic changes, has been observed in precancerous or early cancer stages, making it a valuable biomarker. This review explores the role of DNA methylation in breast cancer and its potential for developing blood-based tests. We discuss advancements in DNA methylation detection methods, recent discoveries of potential DNA methylation biomarkers from both single-omics and multi-omics integration studies, and the role of machine learning in enhancing diagnostic accuracy. Challenges and future directions are also addressed. Although challenges remain, advances in multi-omics integration and machine learning continue to enhance the clinical potential of methylation-based biomarkers. Ongoing research is crucial to further refine these approaches and improve early detection and patient outcomes.

Blood-based biomarkers in pancreatic ductal adenocarcinoma: developments over the last decade and what holds for the future- a review

Pancreatic Ductal Adenocarcinoma (PDAC) accounts for a significant burden of global cancer deaths worldwide. The dismal outcomes associated with PDAC can be overcome by detecting the disease early and developing tools that predict response to treatment, allowing the selection of the most optimal treatment. Over the last couple of years, significant progress has been made in the development of novel biomarkers that aid in diagnosis, prognosis, treatment selection, and monitoring response. Blood-based biomarkers offer an alternative to tissue-based diagnosis and offer immense potential in managing PDAC. In this review, we have discussed the advances in blood-based biomarkers in PDAC, such as DNA (mutations and methylations), RNA, protein biomarkers and circulating tumor cells (CTC) over the last decade and also elucidated all aspects of practical implementation of these biomarkers in clinical practice. We have also discussed implementing multiomics utilizing more than one biomarker and targeted therapies that have been developed using these biomarkers.

Genomics and the early diagnosis of lung cancer

Lung cancer (LC) remains the leading cause of cancer-related mortality worldwide, with most cases diagnosed at advanced stages, resulting in poor survival rates. Early detection significantly improves outcomes, yet current screening methods, such as low-dose computed tomography (LDCT), are limited by high false-positive rates, radiation exposure, and restricted eligibility criteria. This review highlights the transformative potential of genomic and molecular technologies in advancing the early detection of LC. Key innovations include liquid biopsy tools, such as circulating tumor DNA (ctDNA) and cell-free DNA (cfDNA) analysis, which offer minimally invasive approaches to detect tumor-specific genetic and epigenetic alterations. Emerging biomarkers, including methylation signatures, cfDNA fragmentomics, and multi-omics profiles, demonstrate improved sensitivity and specificity in identifying early-stage tumors. Advanced platforms like next-generation sequencing (NGS) and machine-learning algorithms further enhance diagnostic accuracy. Integrated approaches that combine genomic data with LDCT imaging and artificial intelligence (AI) show promise in addressing current limitations by improving risk stratification and nodule characterization. The review also explores multi-cancer early detection assays and precision diagnostic strategies tailored for diverse at-risk populations. By leveraging these advancements, clinicians can achieve earlier diagnoses, reduce unnecessary procedures, and ultimately decrease LC mortality.

Evolution of genome-wide methylation profiling technologies

In this mini-review, we explore the advancements in genome-wide DNA methylation profiling, tracing the evolution from traditional methods such as methylation arrays and whole-genome bisulfite sequencing to the cutting-edge single-molecule profiling enabled by long-read sequencing (LRS) technologies. We highlight how LRS is transforming clinical and translational research, particularly by its ability to simultaneously measure genetic and epigenetic information, providing a more comprehensive understanding of complex disease mechanisms. We discuss current challenges and future directions in the field, emphasizing the need for innovative computational tools and robust, reproducible approaches to fully harness the capabilities of LRS in molecular diagnostics.

Fragmentomics profiling and quantification of plasma Epstein-Barr virus DNA enhance prediction of future nasopharyngeal carcinoma

Fragmentomics analysis of plasma autosomal DNA has shown promise in cancer diagnostics. Here we evaluated the clinical utility of plasma Epstein-Barr virus (EBV) DNA fragmentomics analysis for nasopharyngeal carcinoma (NPC) screening. Among our prospective cohort of approximately 20,000 subjects that underwent two rounds of screening, we analyzed the first-round blood samples of subjects who tested positive for EBV DNA via polymerase chain reaction (PCR) (n = 558). We found that those who subsequently developed NPC in the second round exhibited a distinctive mononucleosomal size pattern, an NPC-associated end motif (specifically, a depletion of CC-motif) and aberrations in methylation identified through fragmentomics-based methylation analysis (FRAGMA). Subjects with these aberrant fragmentomics features and higher quantity of EBV DNA had a relative risk of 87.1 times greater for developing NPC in the second round compared to subjects tested negative for EBV DNA on PCR. These results demonstrate plasma DNA fragmentomics could predict future cancer risk.

The role of immunotherapy in targeting tumor microenvironment in genitourinary cancers

Genitourinary (GU) cancers, including renal cell carcinoma, prostate cancer, bladder cancer, and testicular cancer, represent a significant health burden and are among the leading causes of cancer-related mortality worldwide. Despite advancements in traditional treatment modalities such as chemotherapy, radiotherapy, and surgery, the complex interplay within the tumor microenvironment (TME) poses substantial hurdles to achieving durable remission and cure. The TME, characterized by its dynamic and multifaceted nature, comprises various cell types, signaling molecules, and the extracellular matrix, all of which are instrumental in cancer progression, metastasis, and therapy resistance. Recent breakthroughs in immunotherapy (IO) have opened a new era in the management of GU cancers, offering renewed hope by leveraging the body's immune system to combat cancer more selectively and effectively. This approach, distinct from conventional therapies, aims to disrupt cancer's ability to evade immune detection through mechanisms such as checkpoint inhibition, therapeutic vaccines, and adoptive cell transfer therapies. These strategies highlight the shift towards personalized medicine, emphasizing the importance of understanding the intricate dynamics within the TME for the development of targeted treatments. This article provides an in-depth overview of the current landscape of treatment strategies for GU cancers, with a focus on IO targeting the specific cell types of TME. By exploring the roles of various cell types within the TME and their impact on cancer progression, this review aims to underscore the transformative potential of IO strategies in TME targeting, offering more effective and personalized treatment options for patients with GU cancers, thereby improving outcomes and quality of life.

Biomarker-informed care for patients with renal cell carcinoma

Kidney cancer is a commonly diagnosed cancer in adults, and clear cell renal cell carcinoma (ccRCC) is the most common histological subtype. Immune checkpoint inhibitors have revolutionized care for patients with ccRCC, either as adjuvant therapy or combined with other agents in advanced disease. However, biomarkers to predict therapeutic benefits are lacking. Here, we explore biomarkers that predict therapeutic response in other tumor types and discuss the reasons for their ineffectiveness in ccRCC. We also review emerging predictive and prognostic biomarkers to prioritize in ccRCC, including gene expression signatures.

Noninvasive Multicancer Detection Using DNA Hypomethylation of LINE-1 Retrotransposons

PURPOSE

The detection of ctDNA, which allows noninvasive tumor molecular profiling and disease follow-up, promises optimal and individualized management of patients with cancer. However, detecting small fractions of tumor DNA released when the tumor burden is reduced remains a challenge.

EXPERIMENTAL DESIGN

We implemented a new, highly sensitive strategy to detect bp resolution methylation patterns from plasma DNA and assessed the potential of hypomethylation of long interspersed nuclear element-1 retrotransposons as a noninvasive multicancer detection biomarker. The Detection of Long Interspersed Nuclear Element Altered Methylation ON plasma DNA method targets 30 to 40,000 young long interspersed nuclear element-1 retrotransposons scattered throughout the genome, covering about 100,000 CpG sites and is based on a reference-free analysis pipeline.

RESULTS

Resulting machine learning-based classifiers showed powerful correct classification rates discriminating healthy and tumor plasmas from six types of cancers (colorectal, breast, lung, ovarian, and gastric cancers and uveal melanoma, including localized stages) in two independent cohorts (AUC = 88%-100%, N = 747). The Detection of Long Interspersed Nuclear Element Altered Methylation ON plasma DNA method can also be used to perform copy number alteration analysis that improves cancer detection.

CONCLUSIONS

This should lead to the development of more efficient noninvasive diagnostic tests adapted to all patients with cancer, based on the universality of these factors. See related commentary by Szymanski et al., p. 1179.

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.

Selective adsorption of unmethylated DNA on ZnO nanowires for separation of methylated DNA

DNA methylation is a crucial epigenetic modification used as a biomarker for early cancer progression. However, existing methods for DNA methylation analysis are complex, time-consuming, and prone to DNA degradation. This work demonstrates selective capture of unmethylated DNAs using ZnO nanowires without chemical or biological modifications, thereby concentrating methylated DNA, particularly those with high methylation levels that can predict cancer risk. We observe varying affinities between methylated and unmethylated DNA on ZnO nanowires, which may be influenced by differences in hydrogen bonding strength, potentially related to the effects of methylation on DNA strand behavior, including self-aggregation and stretching inhibition. As a result, the nanowire-based microfluidic device effectively collects unmethylated DNA, leading to a significantly increased ratio of methylated to unmethylated DNA, particularly for collecting low-concentration methylated DNA. This simplified microfluidic device, composed of ZnO nanowires, enables direct separation of specific methylated DNA, offering a potential approach for DNA methylation mapping in clinical disease diagnostics.

Advances in Non-Invasive Screening Methods for Gastrointestinal Cancers: How Continued Innovation Has Revolutionized Early Cancer Detection

The early diagnosis of gastrointestinal cancers is essential for better survival and to reduce the burden of malignancies worldwide [...].

Circulating tumor DNA to monitor treatment response in solid tumors and advance precision oncology

Circulating tumor DNA (ctDNA) has emerged as a dynamic biomarker in cancer, as evidenced by its increasing integration into clinical practice. Carrying tumor specific characteristics, ctDNA can be used to inform treatment selection, monitor response, and identify drug resistance. In this review, we provide a comprehensive, up-to-date summary of ctDNA in monitoring treatment response with a focus on lung, colorectal, and breast cancers, and discuss current challenges and future directions.

Genome-wide cell-free DNA methylation profiling in advanced stage ovarian cancer. Are we looking at the tumor or the patient's immune response to the tumor?

The aim of this study was to identify differentially methylated regions in cell-free DNA (cfDNA) between healthy persons and patients with advanced stage ovarian cancer (ASOC) and to identify differences in cfDNA methylation before and after cytoreductive surgery. Plasma-derived cfDNA was analyzed by a high-throughput genome wide DNA methylation sequencing technique: MeD-seq. A training set of therapy naïve cfDNA samples of patients with ASOC (≥FIGO stage IIIB, n=10) was compared with cfDNA of healthy controls (n=10) to define a ASOC specific cfDNA methylation signature. A cumulative hypermethylation score was constructed and a validation set of pre- and postoperative samples of 39 patients were compared using this score. MeD-seq results of tumor tissue samples were correlated with cfDNA results. Patients with ASOC showed a clear distinct cfDNA methylation signature from healthy controls (p<0.0001). This cfDNA-methylation signature resulted in preoperative hypermethylation scores (135; interquartile range 110-163) that were significantly higher than postoperative hypermethylation scores (91; interquartile range 76-101) (p<0.001). The cfDNA methylation signature at baseline differed from tumor tissue and was more closely related to DNA methylation of immune-related cells (T-lymphocytes, neutrophil granulocytes, monocytes, and B-lymphocytes) than to ASOC tissue. MeD-seq provides a promising method for genome wide methylation profiling of cfDNA. Patients with ASOC could clearly be distinguished from healthy controls and differed pre- and postoperatively.

Liquid Biopsy in HPV-Associated Head and Neck Cancer: A Comprehensive Review

Objectives: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer globally, with HPV-positive cases emerging as a distinct subtype with unique clinical and molecular characteristics. Current diagnostic methods, including tissue biopsy and imaging, face limitations in terms of invasiveness, static disease assessment, and difficulty in distinguishing recurrence from treatment-related changes. This review aimed to assess the potential of liquid biopsy as a minimally invasive tool for the diagnosis, treatment monitoring, and surveillance of HPV-associated HNSCC. Methods: This systematic review analyzed literature from PubMed/MEDLINE, Embase, and Web of Science, focusing on original research and reviews related to liquid biopsy applications in HPV-positive HNSCC. Included studies were evaluated based on the robustness of the study design, clinical relevance, and analytical performance of liquid biopsy technologies. Biomarker types, detection methods, and implementation strategies were assessed to identify advancements and challenges in this field. Results: Liquid biopsy technologies, including circulating HPV DNA, ctDNA, and extracellular vesicles, demonstrated high sensitivity (90-95%) and specificity (>98%) in detecting HPV-positive HNSCC. These methods enabled real-time monitoring of tumor dynamics, early detection of recurrence, and insights into treatment resistance. Longitudinal analysis revealed that biomarker clearance during treatment correlates strongly with patient outcomes. Conclusions: Liquid biopsy is a transformative diagnostic and monitoring tool for HPV-associated HNSCC, offering minimally invasive, real-time insights into tumor biology. While challenges remain in standardization and clinical implementation, ongoing research and technological innovations hold promise for integrating liquid biopsy into personalized cancer care, ultimately improving patient outcomes.

Circulating cell-free DNA methylation analysis of pancreatic cancer patients for early noninvasive diagnosis

Background

Aberrant hypermethylation of genomic DNA CpG islands (CGIs) is frequently observed in human pancreatic cancer (PAC). A plasma cell-free DNA (cfDNA) methylation analysis method can be utilized for the early and noninvasive detection of PAC. This study also aimed to differentiate PAC from other cancer types.

Methods

We employed the methylated CpG tandem amplification and sequencing (MCTA-Seq) method, which targets approximately one-third of CGIs, on plasma samples from PAC patients (n = 50) and healthy controls (n = 52), as well as from cancerous and adjacent noncancerous tissue samples (n = 66). The method's efficacy in detecting PAC and distinguishing it from hepatocellular carcinoma (HCC), colorectal cancer (CRC), and gastric cancer (GC) was evaluated. Additionally, a methylation score and typing system for PAC was also established.

Results

We identified a total of 120 cfDNA methylation biomarkers, including IRX4, KCNS2, and RIMS4, for the detection of PAC in blood. A panel comprising these biomarkers achieved a sensitivity of 97% and 86% for patients in the discovery and validation cohorts, respectively, with a specificity of 100% in both cohorts. The methylation scoring and typing systems were clinically applicable. Furthermore, we identified hundreds of differentially methylated cfDNA biomarkers between PAC and HCC, CRC, and GC. Certain combinations of these markers can be used in a highly specific (approximately 100%) algorithm to differentiate PAC from HCC, CRC, and GC in blood.

Conclusions

Our study identified cfDNA methylation markers for PAC, offering a novel approach for the early, noninvasive diagnosis of PAC.

Liquid biopsy entering clinical practice: Past discoveries, current insights, and future innovations

In recent years, liquid biopsy has gained prominence as an emerging biomarker in cancer research, providing critical insights into tumor biology and metastasis. Technological advancements have enabled its integration into clinical practice, with ongoing trials demonstrating encouraging outcomes. Key applications of liquid biopsy include early cancer detection, cancer staging, prognosis evaluation, and real-time monitoring of tumor progression to optimize treatment decisions. In this review, we present a comprehensive conceptual framework for liquid biopsy, discuss the challenges in its research and clinical application, and highlight its significant potential in identifying therapeutic targets and resistance mechanisms across various cancer types. Furthermore, we explore the emerging role of liquid biopsy-based multicancer screening, which has shown promising advancements. Looking ahead, standardization, multi-omics coanalysis, and the advancement of precision medicine and personalized treatments are expected to drive the future development and integration of liquid biopsy into routine clinical workflows, enhancing cancer diagnosis and treatment management.

Non-invasive diagnosis for urothelial carcinoma using a dual-target DNA methylation biomarker panel

BACKGROUND

Urothelial carcinoma (UC) is a common malignancy worldwide. Aberrant DNA methylation is implicated in UC carcinogenesis. This study sought to delineate the DNA methylation landscape in UC and identify DNA methylation-based biomarkers for early detection of UC.

METHODS

Whole genome bisulfite sequencing (WGBS) was conducted on bladder cancer tissues and paired normal tissues. By integrating WGBS data with The Cancer Genome Atlas (TCGA) UBC data, a DNA methylation-based biomarker was identified. When combined with a known UC biomarker AL021918.2, the performance of the dual-target test was evaluated in voided urine samples from 224 UC patients and 419 controls.

RESULTS

Notable hypomethylation was observed in UC samples compared to normal samples. Through differential methylation analysis, differential methylation CpG sites, regions, and genes were identified. Of these, Transmembrane protein 106A gene (TMEM106A) was screened as a new UC biomarker. In a dual-target test, using triplex quantitative methylation-specific PCR (qMSP) to examine TMEM106A and AL021918.2 methylation levels, the training set showed a sensitivity of 89.0 %, a specificity of 92.9 %, and an area under the curve (AUC) value of 0.941 (95 % confidence interval [CI]: 0.913-0.969). Similarly, the validation set showed a sensitivity of 90.0 %, a specificity of 91.1 %, and an AUC value of 0.922 (95 % CI: 0.881-0.962). In addition, our dual-target test demonstrated outstanding detection rates for low-grade or early-stage tumors.

CONCLUSIONS

We provide a comprehensive analysis of DNA methylation profiles in UC, and highlight the promising clinical potential of dual-target urine tests for UC detection.

Clinicopathological Predictors of the Presence of Blood Circulating Tumor DNA in Early-Stage Non-Small Cell Lung Cancers

The implementation of lung cancer screening programs across the world has drawn considerable attention to improving early-stage lung cancer detection and prognostication. Several blood-based assays detecting circulating tumor DNA (ctDNA) recently emerged as noninvasive methods to detect malignancies. However, their limited sensitivity and predictive value remain a hurdle to their clinical use. We aimed to evaluate the association between clinicopathological parameters and presurgical ctDNA detection in clinical stage I non-small cell lung cancer patients to further understand ctDNA shedding biology. The cohort included 180 adenocarcinomas (LUAD) and 80 squamous cell carcinomas (LUSC) stage I patients who underwent lung cancer resection. Patients' clinical and pathological features were collected. A multicancer early-detection test (GRAIL LLC) was used to detect ctDNA using targeted methylation patterns. The association between the cell-free DNA tumor methylated fraction (TMeF) and the clinicopathological predictors was evaluated using univariate and multivariate modeling. LUSC was associated with a higher TMeF than LUAD. Pathological stage, tumor grade, and tumor volume were key determinants of ctDNA detection in both LUSC and LUAD. In LUAD, ctDNA detection also correlated with histologic pattern composition, necrosis, acute inflammation, and, to a lesser degree, spread through alveolar spaces and lymphovascular invasion. Based on our results, we propose classification methods for both LUAD (using histologic pattern composition) and LUSC (using tumor grade and pathological stage) to identify patients likely to have high ctDNA levels. These results confirm previous findings and suggest that previously unidentified factors, including histologic pattern composition and acute inflammation, influence ctDNA levels. These results will help in understanding the ctDNA shedding process and may allow identification of patients eligible for ctDNA detection-based follow-up.

Imaging and outcome correlates of ctDNA methylation markers in prostate cancer: a comparative, cross-sectional [⁶⁸Ga]Ga-PSMA-11 PET/CT study

BACKGROUND

To validate the clinical utility of a previously identified circulating tumor DNA methylation marker (meth-ctDNA) panel for disease detection and survival outcomes, meth-ctDNA markers were compared to PSA levels and PSMA PET/CT findings in men with different stages of prostate cancer (PCa).

METHODS

122 PCa patients who underwent [⁶⁸Ga]Ga-PSMA-11 PET/CT and plasma sampling (03/2019-08/2021) were analyzed. cfDNA was extracted, and a panel of 8 individual meth-ctDNA markers was queried. PET scans were qualitatively and quantitatively assessed. PSA and meth-ctDNA markers were compared to PET findings, and their relative prognostic value was evaluated.

RESULTS

PSA discriminated best between negative and tumor-indicative PET scans in all (AUC 0.77) and hormone-sensitive (hsPC) patients (0.737). In castration-resistant PCa (CRPC), the meth-ctDNA marker KLF8 performed best (AUC 0.824). CHST11 differentiated best between non- and metastatic scans (AUC 0.705) overall, KLF8 best in hsPC and CRPC (AUC 0.662, 0.85). Several meth-ctDNA markers correlated low to moderate with the tumor volume in all (5/8) and CRPC patients (6/8), while PSA levels correlated moderately to strongly with the tumor volume in all groups (all p < 0.001). CRPC overall survival was independently associated with LDAH and PSA (p = 0.0168, p < 0.001).

CONCLUSION

The studied meth-ctDNA markers are promising for the minimally-invasive detection and prognostication of CRPC but do not allow for clinical characterization of hsPC. Prospective studies are warranted for their use in therapy response and outcome prediction in CRPC and potential incremental value for PCa monitoring in PSA-low settings.

The Promise of Infrared Spectroscopy in Liquid Biopsies for Solid Cancer Detection

Attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy has shown significant promise in the context of liquid biopsy, offering a potential tool for cancer diagnostics. Unlike traditional tissue biopsies, which may not fully capture the clonal heterogeneity of tumors, liquid biopsy reflects the dynamic state of the disease and its progression more comprehensively. Biofluids such as serum and plasma are low-cost, minimally invasive diagnostic media with well-established clinical uses. This review assesses the use of ATR-FTIR spectroscopy to detect biochemical changes in biofluids linked to various malignancies, including breast, ovarian, endometrial, prostate, bladder, kidney, pancreatic, colorectal, hepatic, esophageal, gastric, lung, and brain cancers. While ATR-FTIR offers the advantages of rapid, minimally invasive detection and real-time disease monitoring, its integration into clinical practice faces challenges, particularly in terms of reproducibility due to variability in sample preparation, spectral acquisition, and data processing. The translation of ATR-FTIR into routine diagnostics will require validation through large-scale cohort studies and multicenter trials to ensure its clinical reliability and effectiveness.

5-hydroxymethylcytosine features of portal venous blood predict metachronous liver metastases of colorectal cancer and reveal phosphodiesterase 4 as a therapeutic target

Metachronous liver metastases (MLM) are characterised by high incidence and high mortality in clinical colorectal cancer treatment. Currently traditional clinical methods cannot effectively predict and prevent the occurrence of metachronous liver metastasis in colorectal cancer. Based on 5hmC-Seal analysis of blood and tissue samples, this study found that portal venous blood was more relevant to tumour gDNA than peripheral blood. We performed a novel epigenetic liquid biopsy strategy using the 10 5hmC epigenetic alterations, to accurately distinguish MLM patients from patients without metastases. Among these epigenetic alterations, phosphodiesterase 4 (PDE4D) was highly increased in MLM patients and correlated with poor survival. Moreover, our studies demonstrated that PDE4D was a key metastasis-driven target for drug development. Interfering with the function of PDE4D significantly repressed liver metastases. Similarly, roflumilast, a PDE4 inhibitor for chronic obstructive pulmonary disease (COPD) therapy, also inhibits liver metastases. Further studies indicate that blocking the function of PDE4D can affect CRC invasion through the HIF-1α-CCN2 pathway. To develop a more efficient PDE4 inhibitor and reduce the occurrence of adverse events, we also designed several new compounds based on 2-arylbenzofurans and discovered lead L11 with potent affinity for PDE4D and significant suppression of liver metastases. In this work, our study provides a promising strategy for predicting metachronous liver metastasis and discovers L11 as a potential repurposed drug for inhibiting liver metastasis, which have the potential to benefit patients with CRC in the future. KEY POINTS: 5hmC epigenetic markers derived from portal venous blood could accurately predict metachronous metastasis of colorectal cancer. PDE4D was a key metastasis-driven target that promoted metachronous metastasis via the HIF-1α-CCN2 pathway. The newly synthesised compound L11 could specifically inhibit PDE4D and abolish metachronous metastasis of colorectal cancer without obvious toxic side effects.

Adaptive Universal Principles for Real-world Observational Studies (AUPROS): an approach to designing real-world observational studies for clinical, epidemiologic, and precision oncology research

The field of precision oncology has witnessed several advances that stimulated the development of new clinical trial designs and the emergence of real-world data (RWD) as an important resource for evidence generation in healthcare decision-making. Here, we highlight our experience with an innovative approach to a set of Adaptive, Universal Principles for Real-world Observational Studies (AUPROS). To demonstrate the utility of these principles, we used a mixed-methods approach to assess three studies that follow AUPROS at Princess Margaret Cancer Centre: (1) Molecular Epidemiology of ThorAcic Lesions (METAL), (2) Translational Head And NecK Study (THANKS), and (3) CAnadian CAncers With Rare Molecular Alterations (CARMA; NCT04151342). We performed resource assessments, stakeholder-directed surveys and discussions, analysis of funding, research output, collaborations, and a Strengths-Weaknesses-Opportunities-Threats (SWOT) analysis. Based on these analyses, AUPROS is an approach that is applicable to a wide range of observational study designs. The universality of AUPROS allows for multi-purpose analyses of various RWD, and the adaptive nature creates opportunities for multi-source funding and collaborations. Following AUPROS can offer cost and logistical benefits and may lead to increased research productivity. Several challenges were identified pertinent to ethics approvals, sustainability, complex coordination, and data quality that require local adaptation of these principles.

Leveraging epigenetic alterations in pancreatic ductal adenocarcinoma for clinical applications

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy characterized by late detection and poor prognosis. Recent research highlights the pivotal role of epigenetic alterations in driving PDAC development and progression. These changes, in conjunction with genetic mutations, contribute to the intricate molecular landscape of the disease. Specific modifications in DNA methylation, histone marks, and non-coding RNAs are emerging as robust predictors of disease progression and patient survival, offering the potential for more precise prognostic tools compared to conventional clinical staging. Moreover, the detection of epigenetic alterations in blood and other non-invasive samples holds promise for earlier diagnosis and improved management of PDAC. This review comprehensively summarises current epigenetic research in PDAC and identifies persisting challenges. These include the complex nature of epigenetic profiles, tumour heterogeneity, limited access to early-stage samples, and the need for highly sensitive liquid biopsy technologies. Addressing these challenges requires the standardisation of methodologies, integration of multi-omics data, and leveraging advanced computational tools such as machine learning and artificial intelligence. While resource-intensive, these efforts are essential for unravelling the functional consequences of epigenetic changes and translating this knowledge into clinical applications. By overcoming these hurdles, epigenetic research has the potential to revolutionise the management of PDAC and improve patient outcomes.

Innovative approaches in colorectal cancer screening: advances in detection methods and the role of artificial intelligence

Colorectal cancer (CRC) is the third most prevalent cancer globally and poses a significant health threat, making early detection crucial. This review paper explored emerging detection methods for early screening of CRC, including gut microbiota, metabolites, genetic markers, and artificial intelligence (AI)-based technologies. Current screening methods have their respective advantages and limitations, particularly in detecting precursors. First, the importance of the gut microbiome in CRC progression is discussed, highlighting how specific microbial alterations can serve as biomarkers for early detection, potentially enhancing diagnostic accuracy when combined with traditional screening methods. Next, research on metabolic reprogramming illustrates the relationship between metabolic changes and CRC, with studies developing metabolite-based detection models that show good sensitivity for early diagnosis. In terms of genetic markers, methylated DNA markers like SEPTIN9 have demonstrated high sensitivity, although further validation across diverse populations is necessary. Lastly, AI technology has shown immense potential in improving adenoma detection rates, significantly enhancing the quality of colonoscopic examinations through image recognition techniques. This review aims to provide a comprehensive perspective on new strategies for CRC screening, emphasizing the potential of noninvasive detection technologies and the prospects of AI and genomics in clinical applications. Despite several challenges, this review advocates for future large-scale prospective studies to validate the effectiveness and cost-effectiveness of these new screening methods while promoting the implementation of screening protocols tailored to individual characteristics.

Artificial intelligence and machine learning in cell-free-DNA-based diagnostics

The discovery of circulating fetal and tumor cell-free DNA (cfDNA) molecules in plasma has opened up tremendous opportunities in noninvasive diagnostics such as the detection of fetal chromosomal aneuploidies and cancers and in posttransplantation monitoring. The advent of high-throughput sequencing technologies makes it possible to scrutinize the characteristics of cfDNA molecules, opening up the fields of cfDNA genetics, epigenetics, transcriptomics, and fragmentomics, providing a plethora of biomarkers. Machine learning (ML) and/or artificial intelligence (AI) technologies that are known for their ability to integrate high-dimensional features have recently been applied to the field of liquid biopsy. In this review, we highlight various AI and ML approaches in cfDNA-based diagnostics. We first introduce the biology of cell-free DNA and basic concepts of ML and AI technologies. We then discuss selected examples of ML- or AI-based applications in noninvasive prenatal testing and cancer liquid biopsy. These applications include the deduction of fetal DNA fraction, plasma DNA tissue mapping, and cancer detection and localization. Finally, we offer perspectives on the future direction of using ML and AI technologies to leverage cfDNA fragmentation patterns in terms of methylomic and transcriptional investigations.

Single-molecule systems for the detection and monitoring of plasma-circulating nucleosomes and oncoproteins in diffuse midline glioma

The analysis of cell-free tumor DNA (ctDNA) and proteins in the blood of patients with cancer potentiates a new generation of non-invasive diagnostic approaches. However, confident detection of tumor-originating markers is challenging, especially in the context of brain tumors, where these analytes in plasma are extremely scarce. Here, we apply a sensitive single-molecule technology to profile multiple histone modifications on individual nucleosomes from the plasma of patients with diffuse midline glioma (DMG). The system reveals epigenetic patterns unique to DMG, significantly differentiating this group of patients from healthy subjects or individuals diagnosed with other cancer types. We further develop a method to directly quantify the tumor-originating oncoproteins, lysine 27 to methionine substitution in histone H3 (H3-K27M) and mutant p53, from <1 mL of plasma, allowing for the accurate molecular classification of patients with DMG. We show that our strategy correlates with MRI and droplet-digital PCR (ddPCR) measurements of ctDNA, highlighting the clinical potential of single-molecule-based, multi-parametric assays for DMG diagnosis and treatment monitoring.

High-throughput methylation sequencing reveals novel biomarkers for the early detection of renal cell carcinoma

PURPOSE

Renal cell carcinoma (RCC) is a common malignancy, with patients frequently diagnosed at an advanced stage due to the absence of sufficiently sensitive detection technologies, significantly compromising patient survival and quality of life. Advances in cell-free DNA (cfDNA) methylation profiling using liquid biopsies offer a promising non-invasive diagnostic option, but robust biomarkers for early detection are current not available. This study aimed to identify methylation biomarkers for RCC and establish a DNA methylation signature-based prognostic model for this disease.

METHODS

High-throughput methylation sequencing was performed on peripheral blood samples obtained from 49 primarily Stage I RCC patients and 44 healthy controls. Comparative analysis and Least Absolute Shrinkage and Selection Operator (LASSO) regression methods were employed to identify RCC methylation signatures.Subsequently, methylation markers-based diagnostic and prognostic models for RCC were independently trained and validated using random forest and Cox regression methodologies, respectively.

RESULTS

Comparative analysis revealed 864 differentially methylated CpG islands (DMCGIs), 96.3% of which were hypermethylated. Using a training set from The Cancer Genome Atlas (TCGA) dataset of 443 early-stage RCC tumors and matched normal tissues, we applied LASSO regression and identified 23 methylation signatures. We then constructed a random forest-based diagnostic model for early-stage RCC and validated the model using two independent datasets: a TCGA set of 460 RCC tumors and controls, and a blood sample set from our study of 15 RCC cases and 29 healthy controls. For Stage I RCC tissue, the model showed excellent discrimination (AUC-ROC: 0.999, sensitivity: 98.5%, specificity: 100%). Blood sample validation also yielded commendable results (AUC-ROC: 0.852, sensitivity: 73.9%, specificity: 89.7%). Further analysis using Cox regression identified 7 of the 23 DMCGIs as prognostic markers for RCC, allowing the development of a prognostic model with strong predictive power for 1-, 3-, and 5-year survival (AUC-ROC > 0.7).

CONCLUSIONS

Our findings highlight the critical role of hypermethylation in RCC etiology and progression, and present these identified biomarkers as promising candidates for diagnostic and prognostic applications.

Global DNA methylomes reveal oncogenic-associated 5-hydroxylmethylated cytosine (5hmC) signatures in the cell-free DNA of cancer patients

Characterization of tumor epigenetic aberrations is integral to understanding the mechanisms of tumorigenesis and provide diagnostic, prognostic, and predictive information of high clinical relevance. Among the different tumor-associated epigenetic signatures, 5 methyl-cytosine (5mC) and 5-hydroxymethylcytosine (5hmC) are the two most well-characterized DNA methylation alterations linked to cancer pathogenesis. 5hmC has a tissue-specific distribution and its abundance is subjected to changes in tumor DNA, making it a promising biomarker. Detecting tumor-related DNA methylation alterations in tissues is highly invasive, while the analysis of the cell-free DNA (cfDNA) is poised to supplement, if not replace, surgical biopsies. Despite many studies attempted to identify new epigenetic targets for liquid biopsy assays, little is known about the regulatory roles of 5hmC, its impacts on the molecular phenotypes in tumors. Most importantly, whether the oncogenic-associated 5hmC signatures found in tumor tissues can be recapitulated in patients' cfDNA. In this study, we performed the unbiased and simultaneous detection of 5mC and 5hmC whole-genome DNA modifications at base-resolution from two distinct cancer cohorts, from patients with bladder cancer or B-Cell lymphoma, their corresponding normal tissues, and cfDNAs from plasma. We analyzed tissue-specific methylation patters and searched for signatures in gene coding and regulatory regions linked to cancerous states. We then looked for methylation signatures in patients' cfDNA to determine if they were consistent with the tumor-specific patterns. We determined the functional significance of 5hmC in tissue specific transcription and uncovered hundreds of tumor-associated 5hmC signatures. These tumor-associated 5hmC changes, particularly in genes and enhancers, were functionally significant in tumorigenesis pathways and correlated with tumor specific gene expression. To investigate if cfDNA is a faithful surrogate for tumor-associated 5hmC, we devised a targeted capture strategy to examine the alterations of 5hmC in cfDNA from patients with bladder cancer and lymphoma with sufficient sensitivity and specificity and confirmed that they recapitulated the patterns we observed in tumor tissues. Our results provide analytic validation of 5hmC as a cancer-specific biomarker. The methods described here for systematic characterization of 5hmC at functional elements open new avenues to discover epigenetic markers for non-invasive diagnosis, monitoring, and stratifying cancer.

Impact of Higher Cell-Free DNA Yields on Liquid Biopsy Testing in Glioblastoma Patients

BACKGROUND

Minimally invasive molecular profiling using cell-free DNA (cfDNA) is increasingly important to the management of cancer patients; however, low sensitivity remains a major limitation, particularly for brain tumor patients. Transiently attenuating cfDNA clearance from the body-thereby, allowing more cfDNA to be sampled-has been proposed to improve the performance of liquid biopsy diagnostics. However, there is a paucity of clinical data on the effect of higher cfDNA recovery. Here, we investigated the impact of collecting greater quantities of cfDNA on circulating tumor DNA (ctDNA) sensitivity in the "low-shedding" cancer type glioblastoma by analyzing up to approximately 15-fold more plasma than routinely obtained clinically.

METHODS

We tested 70 plasma samples (median 17.0 mL, range 2.5-66.5) from 8 IDH-wild-type glioblastoma patients using an optimized version of the MAESTRO-Pool ctDNA assay. Results were compared with simulated single-blood-tube equivalents of cfDNA. ctDNA results were then compared with magnetic resonance imaging (MRI) and pathology assessments of true progression vs pseudoprogression in glioblastoma patients.

RESULTS

Larger cfDNA yields exhibited a doubling in ctDNA-positivity while achieving a median specificity of 99% and more precise ctDNA quantification. In 8 glioblastoma patients, ctDNA was detected in 88%, including at multiple timepoints in 6/7. In the setting of indeterminate progression by MRI, our data suggested that MAESTRO-Pool with large plasma volumes can help distinguish true glioblastoma progression from pseudoprogression.

CONCLUSIONS

Our findings provide a proof-of-principle that most glioblastomas shed ctDNA into plasma and that greater ctDNA yields could help improve liquid biopsies for "low-shedding" cancer types such as glioblastoma.

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.

Prediction of brain metastasis development with DNA methylation signatures

Brain metastases (BMs) are the most common and among the deadliest brain tumors. Currently, there are no reliable predictors of BM development from primary cancer, which limits early intervention. Lung adenocarcinoma (LUAD) is the most common BM source and here we obtained 402 tumor and plasma samples from a large cohort of patients with LUAD with or without BM (n = 346). LUAD DNA methylation signatures were evaluated to build and validate an accurate model predicting BM development from LUAD, which was integrated with clinical factors to provide comprehensive patient-specific BM risk probabilities in a nomogram. Additionally, immune and cell interaction gene sets were differentially methylated at promoters in BM versus paired primary LUAD and had aligning dysregulation in the proteome. Immune cells were differentially abundant in BM versus LUAD. Finally, liquid biomarkers identified from methylated cell-free DNA sequenced in plasma were used to generate and validate accurate classifiers for early BM detection. Overall, LUAD methylomes can be leveraged to predict and noninvasively identify BM, moving toward improved patient outcomes with personalized treatment.

Clinical validation of a tissue-agnostic genome-wide methylome enrichment molecular residual disease assay for head and neck malignancies

BACKGROUND

Outcomes for patients with locally advanced head and neck cancer (HNC) treated with curative intent remain disappointing, with 5-year survival rates at 50%. Most recurrences occur within the first 2 years after treatment, providing a window of opportunity to identify patients with molecular residual disease (MRD). A tissue-agnostic test for MRD detection in patients with human papillomavirus (HPV) positive and negative HNC, where tissue is often scarce, is needed.

PATIENTS AND METHODS

Patients with stage I-IVB HNC, including patients positive and negative for HPV, were enrolled and peripheral blood plasma was collected longitudinally at diagnosis and ∼3, 12, and 24 months after curative intent treatment. The full cohort includes 325 patients with 1155 samples. Samples were split into distinct sets to train and validate a classifier capable of identifying MRD using a tissue-agnostic genome-wide methylome enrichment platform. The primary endpoint was recurrence-free survival (RFS).

RESULTS

With a median follow-up of 60 months, patients in the blinded validation set with MRD positivity experienced significantly worse RFS with a hazard ratio (HR) of 35.7 [95% confidence interval (CI) 10.8-117.8; P < 0.0001]. For patients with HPV negativity, HR was 42.3 (95% CI 9.8-182.3; P < 0.0001); for patients with HPV-positive oropharyngeal cancer, HR was 24.1 (95% CI 3.0-196.8; P < 0.0001). Moreover, the lead time between MRD positivity and clinical recurrence was up to 14.9 months, with a mean lead time of 4.1 months. Surveillance sensitivity was 91% (95% CI 77% to 97%) and specificity was 88% (95% CI 80% to 93%).

CONCLUSIONS

Here we validate the clinical performance characteristics of a tissue-agnostic genome-wide methylome enrichment assay for MRD detection in patients with HNC. The MRD detection test showed high sensitivity for identifying recurrence at high specificity across different anatomical sites, HPV status, and treatment regimens, highlighting the broad applicability for MRD detection in patients with HNC.

DNA methylation urine test in the diagnosis of upper tract urothelial carcinoma: a systematic review and meta-analysis

OBJECTIVE

The DNA methylation urine test, a noninvasive early detection method for upper tract urothelial carcinoma (UTUC), is currently in full swing. This study aimed to systematically assess its diagnostic performance on UTUC.

MATERIALS AND METHODS

PubMed, Scopus, Embase, and Cochrane were our main databases when searching articles published from January 2000 to December 2023. Sensitivity and specificity were study primary endpoints. I2 was used to evaluated heterogeneity, meanwhile subgroup and meta-regression analyses were adopted to investigated the source of heterogeneity. Sensitivity analysis was performed to evaluate the result robustness, while Deeks' funnel plot asymmetry test was for the publication bias.

RESULTS

Nine studies with 1326 patients were included. The pooled sensitivity was 0.89 (95% CI: 0.83-0.93) and specificity were 0.91 (95% CI: 0.83-0.96). The area under the receiver operating characteristic curve was 0.96 (95% CI: 0.93-0.97). Substantial heterogeneity was found during the data synthesis, whereas the pooled results remained robust in the sensitivity analysis. None of the potential covariates-urine sample collection method, population, country, methylation test method, or tumor grade-could account for the heterogeneity.

CONCLUSION

DNA methylation urine test is a promising method with high efficiency for UTUC early detection. Nevertheless, owing to the significant heterogeneity, more well-organized studies are warranted to further explore its diagnostic efficiency and application context.

Circulating tumor DNA predicts recurrence and survival in patients with resectable gastric and gastroesophageal junction cancer

BACKGROUND

Gastric and gastroesophageal junction (GEJ) cancer represents a significant global health challenge, with high recurrence rates and poor survival outcomes. This study investigates circulating tumor DNA (ctDNA) as a biomarker for assessing recurrence risk in patients with resectable gastric and GEJ adenocarcinomas (AC).

METHODS

Patients with resectable gastric and GEJ AC, undergoing perioperative chemotherapy and surgery, were prospectively enrolled. Serial plasma samples were collected at baseline, after one cycle of chemotherapy, after preoperative chemotherapy, and after surgery. ctDNA was assessed by a ddPCR test (TriMeth), which targets the gastrointestinal cancer-specific methylation patterns of the genes C9orf50, KCNQ5, and CLIP4.

RESULTS

ctDNA analysis was performed on 229 plasma samples from 86 patients. At baseline, ctDNA was detected in 56% of patients, which decreased to 37% following one cycle of chemotherapy, 25% after preoperative chemotherapy and 15% after surgical resection. The presence of ctDNA after one cycle of chemotherapy was associated with reduced recurrence-free survival (RFS) (HR = 2.54, 95% confidence interval (CI) 1.33-4.85, p = 0.005) and overall survival (OS) (HR = 2.23, 95% CI 1.07-4.62, p = 0.032). Similarly, ctDNA after surgery was associated with significantly shorter RFS (HR = 6.22, 95% CI 2.39-16.2, p < 0.001) and OS (HR = 6.37, 95% CI 2.10-19.3, p = 0.001). Multivariable regression analysis confirmed ctDNA after surgery as an independent prognostic factor (p < 0.001).

CONCLUSION

ctDNA analysis has the potential to identify patients at elevated risk of recurrence, thus providing personalized treatment strategies for patients with resectable gastric and GEJ cancer. Further validation in larger cohorts and ctDNA-guided interventions are needed for future clinical use.

DNA methylation in mammalian development and disease

The DNA methylation field has matured from a phase of discovery and genomic characterization to one seeking deeper functional understanding of how this modification contributes to development, ageing and disease. In particular, the past decade has seen many exciting mechanistic discoveries that have substantially expanded our appreciation for how this generic, evolutionarily ancient modification can be incorporated into robust epigenetic codes. Here, we summarize the current understanding of the distinct DNA methylation landscapes that emerge over the mammalian lifespan and discuss how they interact with other regulatory layers to support diverse genomic functions. We then review the rising interest in alternative patterns found during senescence and the somatic transition to cancer. Alongside advancements in single-cell and long-read sequencing technologies, the collective insights made across these fields offer new opportunities to connect the biochemical and genetic features of DNA methylation to cell physiology, developmental potential and phenotype.

Application of Circulating Tumor DNA in the Auxiliary Diagnosis and Prognosis Prediction of Glioma

Glioma is the most common primary malignant brain tumor. Despite significant advances in the past decade in understanding the molecular pathogenesis of this tumor and exploring therapeutic strategies, the prognosis of patients with glioma remains poor. Accurate diagnosis of glioma is very important for the treatment and prognosis. Although the gold-standard method for the diagnosis and prognosis prediction of patients with glioma is tissue biopsy, it still has many limitations. Liquid biopsy can provide information on the auxiliary diagnosis and prognosis of gliomas. In this review, we summarized the application of cell-free DNA (cfDNA) and circulating tumor DNA (ctDNA) in the auxiliary diagnosis and prognosis of glioma. The common methods used to detect ctDNA in gliomas using samples including blood and cerebrospinal fluid (CSF) and the detection techniques for ctDNA, including droplet digital PCR (ddPCR) and next-generation sequencing (NGS), were discussed. Detection of ctDNA from plasma of patients with brain tumors remains challenging because of the blood-brain barrier (BBB). CSF has been proposed as a medium for ctDNA analysis in brain tumors, and mutation detection using plasma ctDNA was less sensitive than CSF ctDNA sequencing. Moreover, ongoing relevant clinical studies were summarized. Finally, we discussed the challenges, and future directions for the studies on ctDNA in glioma.