Circulating DNA fragmentomics and cancer screening

Stool and blood biomarkers for colorectal cancer management: an update on screening and disease monitoring

BACKGROUND

Biomarkers have revolutionized the management of colorectal cancer (CRC), facilitating early detection, prevention, personalized treatment, and minimal residual disease (MRD) monitoring. This review explores current CRC screening strategies and emerging biomarker applications.

MAIN BODY

We summarize the landscape of non-invasive CRC screening and MRD detection strategies, discuss the limitations of the current approaches, and highlight the promising potential of novel biomarker solutions. The fecal immunochemical test remained the cornerstone of CRC screening, but its sensitivity has been improved by assays that combined its performance with other stool analytes. However, their sensitivity for advanced adenomas and the patient compliance both remain suboptimal. Blood-based tests promise to increase compliance but require further refinement to compete with stool-based biomarker tests. The ideal scenario involves leveraging blood tests to increase screening participation, and simultaneously promote stool- and endoscopy-based screening among those who are compliant. Once solely reliant on upfront surgery followed by stage and pathology-driven adjuvant chemotherapy, the treatment of stage II and III colon cancer has undergone a revolutionary transformation with the advent of MRD testing after surgery. A decade ago, the concept of using a post-surgical test instead of stage and pathology to determine the need for adjuvant chemotherapy was disruptive. Today, a blood test may be more informative of the need for chemotherapy than the stage at diagnosis.

CONCLUSION

Biomarker research is not just improving, but bringing a transformative change to CRC clinical management. Early detection is not just getting better, but improving thanks to a multi-modality approach, and personalized treatment plans are not just becoming a reality, but a promising future with MRD testing.

Multiomics biomarkers were not superior to clinical variables for pan-cancer screening

BACKGROUND

Cancer screening tests are considered pivotal for early diagnosis and survival. However, the efficacy of these tests for improving survival has recently been questioned. This study aims to test if cancer screening could be improved by biomarkers in peripheral blood based on multi-omics data.

METHODS

We utilize multi-omics data from 500,000 participants in the UK Biobank. Machine learning is applied to search for proteins, metabolites, genetic variants, or clinical variables to diagnose cancers collectively and individually.

RESULTS

Here we show that the overall performance of the potential blood biomarkers do not outperform clinical variables for collective diagnosis. However, we observe promising results for individual cancers in close proximity to peripheral blood, with an Area Under the Curve (AUC) greater than 0.8.

CONCLUSIONS

Our findings suggest that the identification of blood biomarkers for cancer might be complicated by variable overlap between molecular changes in tumor tissues and peripheral blood. This explanation is supported by local proteomics analyses of different tumors, which all show high AUCs, greater than 0.9. Thus, multi-omics biomarkers for the diagnosis of individual cancers may potentially be effective, but not for groups of cancers.

Recent advances in the use of liquid biopsy for the diagnosis and treatment of lung cancer

INTRODUCTION

In the era of precision medicine, liquid biopsy rapidly emerges as an integrative diagnostic tool to successfully stratify solid tumor patients in accordance with molecular fingerprinting. As the matter of fact, a plethora of analytes may be isolated from liquid biosources supporting the potential application of liquid biopsy in several clinical scenarios. Despite this promising role, liquid biopsy is drastically affected by low abundance of analytes in biological matrix requiring highly sensitive technologies, trained personnel, and optimized diagnostic procedures to successfully administrate this revolutionary diagnostic tool in clinical practice.

AREAS COVERED

This review aims to investigate the recent advancements in technical approaches available to manage liquid biopsy samples, particularly focusing on their application in LC diagnosis and treatment.

EXPERT OPINION

The rapidly evolving scenario of liquid biopsy-based approaches is revolutionizing clinical administration of lung cancer patients. Of note, the integration of genomic, epigenomic, and transcriptomic markers lays the basis for 'comprehensive' molecular fingerprinting of lung cancer patients. Here, the next-generation technologies are fundamental in molecular profiling in diagnostic routine biofluids.

Transformer-based representation learning and multiple-instance learning for cancer diagnosis exclusively from raw sequencing fragments of bisulfite-treated plasma cell-free DNA

Early cancer diagnosis from bisulfite-treated cell-free DNA (cfDNA) fragments requires tedious data analytical procedures. Here, we present a deep-learning-based approach for early cancer interception and diagnosis (DECIDIA) that can achieve accurate cancer diagnosis exclusively from bisulfite-treated cfDNA sequencing fragments. DECIDIA relies on transformer-based representation learning of DNA fragments and weakly supervised multiple-instance learning for classification. We systematically evaluate the performance of DECIDIA for cancer diagnosis and cancer type prediction on a curated dataset of 5389 samples that consist of colorectal cancer (CRC; n = 1574), hepatocellular cell carcinoma (HCC; n = 1181), lung cancer (n = 654), and non-cancer control (n = 1980). DECIDIA achieved an area under the receiver operating curve (AUROC) of 0.980 (95% CI, 0.976-0.984) in 10-fold cross-validation settings on the CRC dataset by differentiating cancer patients from cancer-free controls, outperforming benchmarked methods that are based on methylation intensities. Noticeably, DECIDIA achieved an AUROC of 0.910 (95% CI, 0.896-0.924) on the externally independent HCC testing set in distinguishing HCC patients from cancer-free controls, although there was no HCC data used in model development. In the settings of cancer-type classification, we observed that DECIDIA achieved a micro-average AUROC of 0.963 (95% CI, 0.960-0.966) and an overall accuracy of 82.8% (95% CI, 81.8-83.9). In addition, we distilled four sequence signatures from the raw sequencing reads that exhibited differential patterns in cancer versus control and among different cancer types. Our approach represents a new paradigm towards eliminating the tedious data analytical procedures for liquid biopsy that uses bisulfite-treated cfDNA methylome.

Clinical Applications of Circulating Tumor DNA Profiling in GI Cancers

Over the next few years, the analysis of circulating tumor DNA (ctDNA) through liquid biopsy is expected to enter clinical practice and revolutionize the approach to biomarker testing and treatment selection in GI cancers. In fact, growing evidence support the use of ctDNA testing as a noninvasive, effective, and highly specific tool for molecular profiling in GI cancers. Analysis of blood ctDNA has been investigated in multiple settings including early tumor detection, minimal residual disease evaluation, tumor diagnosis and evaluation of prognostic/predictive biomarkers for targeted treatment selection, longitudinal monitoring of treatment response, and identification of resistance mechanisms. Here, we review the clinical applications, advantages, and limitations of ctDNA profiling for precision oncology in GI cancers.

Clinical Validation of a Cell-Free DNA Fragmentome Assay for Augmentation of Lung Cancer Early Detection

Lung cancer screening via annual low-dose computed tomography has poor adoption. We conducted a prospective case-control study among 958 individuals eligible for lung cancer screening to develop a blood-based lung cancer detection test that when positive is followed by a low-dose computed tomography. Changes in genome-wide cell-free DNA fragmentation profiles (fragmentomes) in peripheral blood reflected genomic and chromatin characteristics of lung cancer. We applied machine learning to fragmentome features to identify individuals who were more or less likely to have lung cancer. We trained the classifier using 576 cases and controls from study samples and validated it in a held-out group of 382 cases and controls. The validation demonstrated high sensitivity for lung cancer and consistency across demographic groups and comorbid conditions. Applying test performance to the screening eligible population in a 5-year model with modest utilization assumptions suggested the potential to prevent thousands of lung cancer deaths. Significance: Lung cancer screening has poor adoption. Our study describes the development and validation of a novel blood-based lung cancer screening test utilizing a highly affordable, low-coverage genome-wide sequencing platform to analyze cell-free DNA fragmentation patterns. The test could improve lung cancer screening rates leading to substantial public health benefits. See related commentary by Haber and Skates, p. 2025.

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.

Circulating tumor DNA to guide diagnosis and treatment of localized and locally advanced non-small cell lung cancer

Liquid biopsy is a minimally invasive method for biomarkers detection in body fluids, particularly in blood, which offers an elevated and growing number of clinical applications in oncology. As a result of the improvement in the techniques for DNA analysis, above all next-generation sequencing (NGS) assays, circulating tumor DNA (ctDNA) has become the most informing tumor-derived material for most types of cancer, including non-small cell lung cancer (NSCLC). Although ctDNA concentration is higher in patients with advanced tumors, it can be detected even in patients with early-stage disease. Therefore, numerous clinical applications of ctDNA in the management of early-stage lung cancer are emerging, such as lung cancer screening, the identification of minimal residual disease (MRD), and the prediction of relapse before radiologic progression. Moreover, a high number of clinical trials are ongoing to better define the impact of ctDNA evaluation in this setting. Aim of this review is to offer a comprehensive overview of the most relevant implementations in using ctDNA for the management of early-stage lung cancer, addressing available data, technical aspects, limitations, and future perspectives.

Advances in early detection of non-small cell lung cancer: A comprehensive review

BACKGROUND

Lung cancer has the highest mortality rate among malignancies globally. In addition, due to the growing number of smokers there is considerable concern over its growth. Early detection is an essential step towards reducing complications in this regard and helps to ensure the most effective treatment, reduce health care costs, and increase survival rates.

AIMS

To define the most efficient and cost-effective method of early detection in clinical practice.

MATERIALS AND METHODS

We collected the Information used to write this review by searching papers through PUBMED that were published from 2021 to 2024, mainly systematic reviews, meta-analyses and clinical-trials. We also included other older but notable papers that we found essential and valuable for understanding.

RESULTS

EB-OCT has a varied sensitivity and specificity-an average of 94.3% and 89.9 for each. On the other hand, detecting biomarkers via liquid biopsy carries an average sensitivity of 91.4% for RNA molecules detection, and 97% for combined methylated DNA panels. Moreover, CTCs detection did not prove to have a significant role as a screening method due to the rarity of CTCs in the bloodstream thus the need for more blood samples and for enrichment techniques.

DISCUSSION

Although low-dose CT scan (LDCT) is the current golden standard screening procedure, it is accompanied by a highly false positive rate. In comparison to other radiological screening methods, Endobronchial optical coherence tomography (EB-OCT) has shown a noticeable advantage with a significant degree of accuracy in distinguishing between subtypes of non-small cell lung cancer. Moreover, numerous biomarkers, including RNA molecules, circulating tumor cells, CTCs, and methylated DNA, have been studied in the literature. Many of these biomarkers have a specific high sensitivity and specificity, making them potential candidates for future early detection approaches.

CONCLUSION

LDCT is still the golden standard and the only recommended screening procedure for its high sensitivity and specificity and proven cost-effectiveness. Nevertheless, the notable false positive results acquired during the LDCT examination caused a presumed concern, which drives researchers to investigate better screening procedures and approaches, particularly with the rise of the AI era or by combining two methods in a well-studied screening program like LDCT and liquid biopsy. we suggest conducting more clinical studies on larger populations with a clear demographical target and adopting approaches for combining one of these new methods with LDCT to decrease false-positive cases in early detection.

DNA methylation and gene expression as determinants of genome-wide cell-free DNA fragmentation

Circulating cell-free DNA (cfDNA) is emerging as an avenue for cancer detection, but the characteristics of cfDNA fragmentation in the blood are poorly understood. We evaluate the effect of DNA methylation and gene expression on genome-wide cfDNA fragmentation through analysis of 969 individuals. cfDNA fragment ends more frequently contained CCs or CGs, and fragments ending with CGs or CCGs are enriched or depleted, respectively, at methylated CpG positions. Higher levels and larger sizes of cfDNA fragments are associated with CpG methylation and reduced gene expression. These effects are validated in mice with isogenic tumors with or without the mutant IDH1, and are associated with genome-wide changes in cfDNA fragmentation in patients with cancer. Tumor-related hypomethylation and increased gene expression are associated with decrease in cfDNA fragment size that may explain smaller cfDNA fragments in human cancers. These results provide a connection between epigenetic changes and cfDNA fragmentation with implications for disease detection.

Systematically Evaluating Cell-Free DNA Fragmentation Patterns for Cancer Diagnosis and Enhanced Cancer Detection via Integrating Multiple Fragmentation Patterns

Cell-free DNA (cfDNA) fragmentation patterns have immense potential for early cancer detection. However, the definition of fragmentation varies, ranging from the entire genome to specific genomic regions. These patterns have not been systematically compared, impeding broader research and practical implementation. Here, 1382 plasma cfDNA sequencing samples from 8 cancer types are collected. Considering that cfDNA within open chromatin regions is more susceptible to fragmentation, 10 fragmentation patterns within open chromatin regions as features and employed machine learning techniques to evaluate their performance are examined. All fragmentation patterns demonstrated discernible classification capabilities, with the end motif showing the highest diagnostic value for cross-validation. Combining cross and independent validation results revealed that fragmentation patterns that incorporated both fragment length and coverage information exhibited robust predictive capacities. Despite their diagnostic potential, the predictive power of these fragmentation patterns is unstable. To address this limitation, an ensemble classifier via integrating all fragmentation patterns is developed, which demonstrated notable improvements in cancer detection and tissue-of-origin determination. Further functional bioinformatics investigations on significant feature intervals in the model revealed its impressive ability to identify critical regulatory regions involved in cancer pathogenesis.

Chromatin- and nucleosome-associated features in liquid biopsy: implications for cancer biomarker discovery

Cell-free DNA (cfDNA) from the bloodstream has been studied for cancer biomarker discovery, and chromatin-derived epigenetic features have come into the spotlight for their potential to expand clinical applications. Methylation, fragmentation, and nucleosome positioning patterns of cfDNA have previously been shown to reveal epigenomic and inferred transcriptomic information. More recently, histone modifications have emerged as a tool to further identify tumor-specific chromatin variants in plasma. A number of sequencing methods have been developed to analyze these epigenetic markers, offering new insights into tumor biology. Features within cfDNA allow for cancer detection, subtype and tissue of origin classification, and inference of gene expression. These methods provide a window into the complexity of cancer and the dynamic nature of its progression. In this review, we highlight the array of epigenetic features in cfDNA that can be extracted from chromatin- and nucleosome-associated organization and outline potential use cases in cancer management.

Is ctDNA ready to outpace imaging in monitoring early and advanced breast cancer?

INTRODUCTION

Circulating tumor DNA (ctDNA) and radiological imaging are increasingly recognized as crucial elements in breast cancer management. While radiology remains the cornerstone for screening and monitoring, ctDNA holds distinctive advantages in anticipating diagnosis, recurrence, or progression, providing concurrent biological insights complementary to imaging results.

AREAS COVERED

This review delves into the current evidence on the synergistic relationship between ctDNA and imaging in breast cancer. It presents data on the clinical validity and utility of ctDNA in both early and advanced settings, providing insights into emerging liquid biopsy techniques like epigenetics and fragmentomics. Simultaneously, it explores the present and future landscape of imaging methodologies, particularly focusing on radiomics.

EXPERT OPINION

Numerous are the current technical, strategic, and economic challenges preventing the clinical integration of ctDNA analysis in the breast cancer monitoring. Understanding these complexities and devising targeted strategies is pivotal to effectively embedding this methodology into personalized patient care.

Liquid Biopsies Based on Cell-Free DNA Integrity as a Biomarker for Cancer Diagnosis: A Meta-Analysis

Liquid biopsies have been identified as a viable source of cancer biomarkers. We aim to evaluate the diagnostic accuracy of cell-free DNA integrity (cfDI) in liquid biopsies for cancer. A comprehensive literature search was conducted through PubMed, Embase, Web of Science, and Cochrane Library up to June 2024. Seventy-two study units from forty-six studies, comprising 4286 cancer patients, were identified and evaluated. The Quality Assessment for Studies of Diagnostic Accuracy-2 (QUADAS-2) was used to assess study quality. Meta-regression analysis was employed to investigate the underlying factors contributing to heterogeneity, alongside an evaluation of publication bias. The bivariate random-effect model was utilized to compute the primary diagnostic outcomes and their corresponding 95% confidence intervals (CIs). The pooled sensitivity, specificity, and positive and negative likelihood ratios of cfDI in cancer diagnosis were 0.70 and 0.77, 3.26 and 0.34, respectively. The overall area under the curve was 0.84, with a diagnostic odds ratio of 10.63. This meta-analysis suggested that the cfDI index has a promising potential as a non-invasive and accurate diagnostic tool for cancer. Study registration: The study was registered at PROSPERO (reference No. CRD42021276290).

Liquid Biopsy Based on Cell-Free DNA and RNA

This review delves into the rapidly evolving landscape of liquid biopsy technologies based on cell-free DNA (cfDNA) and cell-free RNA (cfRNA) and their increasingly prominent role in precision medicine. With the advent of high-throughput DNA sequencing, the use of cfDNA and cfRNA has revolutionized noninvasive clinical testing. Here, we explore the physical characteristics of cfDNA and cfRNA, present an overview of the essential engineering tools used by the field, and highlight clinical applications, including noninvasive prenatal testing, cancer testing, organ transplantation surveillance, and infectious disease testing. Finally, we discuss emerging technologies and the broadening scope of liquid biopsies to new areas of diagnostic medicine.

Use of ctDNA in early breast cancer: analytical validity and clinical potential

Circulating free tumor DNA (ctDNA) analysis is gaining popularity in precision oncology, particularly in metastatic breast cancer, as it provides non-invasive, real-time tumor information to complement tissue biopsies, allowing for tailored treatment strategies and improved patient selection in clinical trials. Its use in early breast cancer has been limited so far, due to the relatively low sensitivity of available techniques in a setting characterized by lower levels of ctDNA shedding. However, advances in sequencing and bioinformatics, as well as the use of methylome profiles, have led to an increasing interest in the application of ctDNA analysis in early breast cancer, from screening to curative treatment evaluation and minimal residual disease (MRD) detection. With multiple prospective clinical trials in this setting, ctDNA evaluation may become useful in clinical practice. This article reviews the data regarding the analytical validity of the currently available tests for ctDNA detection and the clinical potential of ctDNA analysis in early breast cancer.

Diagnostic and Prognostic Value of Circulating DNA Fragments in Glioblastoma Multiforme Patients

Novel blood-circulating molecules, as potential biomarkers for glioblastoma multiforme (GBM) diagnosis and monitoring, are attracting particular attention due to limitations of imaging modalities and invasive tissue biopsy procedures. This study aims to assess the diagnostic and prognostic values of circulating cell-free DNA (cfDNA) in relation to inflammatory status in GBM patients and to determine the concentration and average size of DNA fragments typical of tumour-derived DNA fractions. Preoperative plasma samples from 40 patients (GBM 65.0 ± 11.3 years) and 40 healthy controls (HC 70.4 ± 5.4 years) were compared. The cfDNA concentrations and lengths were measured using the electrophoresis platform, and inflammatory indices (NLR, PLR, LMR, and SII) were calculated from complete blood cell analysis. More fragmented cfDNA and 4-fold higher 50-700 bp cfDNA concentrations were detected in GBM patients than in healthy controls. The average cfDNA size in the GBM group was significantly longer (median 336 bp) than in the HC group (median 271 bp). Optimal threshold values were 1265 pg/μL for 50-700 bp cfDNA (AUC = 0.857) and 290 bp for average cfDNA size (AUC = 0.814). A Kaplan-Meier survival curves analysis also demonstrated a higher mortality risk in the GBM group with a cut-off >303 bp cfDNA. This study is the first to have revealed glioblastoma association with high levels of cfDNA > 1000 pg/μL of 50-700 bp in length, which can be aggravated by immunoinflammatory reactivity.

A review on the impact of single-stranded library preparation on plasma cell-free diversity for cancer detection

In clinical oncology, cell-free DNA (cfDNA) has shown immense potential in its ability to noninvasively detect cancer at various stages and monitor the progression of therapy. Despite the rapid improvements in cfDNA liquid biopsy approaches, achieving the required sensitivity to detect rare tumor-derived cfDNA still remains a challenge. For next-generation sequencing, the perceived presentation of cfDNA is strongly linked to the extraction and library preparation protocols. Conventional double-stranded DNA library preparation (dsDNA-LP) focuses on assessing ~167bp double-stranded mononucleosomal (mncfDNA) and its other oligonucleosomal cell-free DNA counterparts in plasma. However, dsDNA-LP methods fail to include short, single-stranded, or nicked DNA in the final library preparation, biasing the representation of the actual cfDNA populations in plasma. The emergence of single-stranded library preparation (ssDNA-LP) strategies over the past decade has now allowed these other populations of cfDNA to be studied from plasma. With the use of ssDNA-LP, single-stranded, nicked, and ultrashort cfDNA can be comprehensively assessed for its molecular characteristics and clinical potential. In this review, we overview the current literature on applications of ssDNA-LP on plasma cfDNA from a potential cancer liquid biopsy perspective. To this end, we discuss the molecular principles of single-stranded DNA adapter ligation, how library preparation contributes to the understanding of native cfDNA characteristics, and the potential for ssDNA-LP to improve the sensitivity of circulating tumor DNA detection. Additionally, we review the current literature on the newly reported species of plasma ultrashort single-stranded cell-free DNA plasma, which appear biologically distinct from mncfDNA. We conclude with a discussion of future perspectives of ssDNA-LP for liquid biopsy endeavors.

Cell-free DNA fragmentomics and second malignant neoplasm risk in patients with PTEN hamartoma tumor syndrome

Individuals with PTEN hamartoma tumor syndrome (PHTS) harbor pathogenic germline PTEN variants that confer a significantly increased lifetime risk of various organ-specific cancers including second primary malignant neoplasms (SMNs). Currently, there are no reliable biomarkers that can predict individual-level cancer risk. Despite the highly promising value of cell-free DNA (cfDNA) as a biomarker for underlying sporadic cancers, the utility of cfDNA in individuals with known cancer-associated germline variants and subclinical cancers remains poorly understood. We perform ultra-low-pass whole-genome sequencing (ULP-WGS) of cfDNA from plasma samples from patients with PHTS and cancer as well as those without cancer. Analysis of cfDNA reveals that patients with PHTS and SMNs have distinct cfDNA size distribution, aberrant genome-wide fragmentation, and differential fragment end motif frequencies. Our work provides evidence that cfDNA profiles may be used as a marker for SMN risk in patients with PHTS.

What is the role of the neutrophil extracellular traps in the cardiovascular disease burden associated with hemodialysis bioincompatibility?

Despite significant progress in dialysis modalities, intermittent renal replacement therapy remains an "unphysiological" treatment that imperfectly corrects uremic disorders and may lead to low-grade chronic inflammation, neutrophil activation, and oxidative stress due to repetitive blood/membrane interactions contributing to the "remaining uremic syndrome" and cardiovascular disease burden of hemodialysis patients. Understanding dialysis bioincompatibility pathways still remains a clinical and biochemical challenge. Indeed, surrogate biomarkers of inflammation including C-reactive protein could not discriminate between all components involved in these complex pathways. A few examples may serve to illustrate the case. Cytokine release during dialysis sessions may be underestimated due to their removal using high-flux dialysis or hemodiafiltration modalities. Complement activation is recognized as a key event of bioincompatibility. However, it appears as an early and transient event with anaphylatoxin level normalization at the end of the dialysis session. Complement activation is generally assumed to trigger leukocyte stimulation leading to proinflammatory mediators' secretion and oxidative burst. In addition to being part of the innate immune response involved in eliminating physically and enzymatically microbes, the formation of Neutrophil Extracellular Traps (NETs), known as NETosis, has been recently identified as a major harmful component in a wide range of pathologies associated with inflammatory processes. NETs result from the neutrophil degranulation induced by reactive oxygen species overproduction via NADPH oxidase and consist of modified chromatin decorated with serine proteases, elastase, bactericidal proteins, and myeloperoxidase (MPO) that produces hypochlorite anion. Currently, NETosis remains poorly investigated as a sensitive and integrated marker of bioincompatibility in dialysis. Only scarce data could be found in the literature. Oxidative burst and NADPH oxidase activation are well-known events in the bioincompatibility phenomenon. NET byproducts such as elastase, MPO, and circulating DNA have been reported to be increased in dialysis patients more specifically during dialysis sessions, and were identified as predictors of poor outcomes. As NETs and MPO could be taken up by endothelium, NETs could be considered as a vascular memory of intermittent bioincompatibility phenomenon. In this working hypothesis article, we summarized the puzzle pieces showing the involvement of NET formation during hemodialysis and postulated that NETosis may act as a disease modifier and may contribute to the comorbid burden associated with dialysis bioincompatibility.

Cancer signature ensemble integrating cfDNA methylation, copy number, and fragmentation facilitates multi-cancer early detection

Cell-free DNA (cfDNA) sequencing has demonstrated great potential for early cancer detection. However, most large-scale studies have focused only on either targeted methylation sites or whole-genome sequencing, limiting comprehensive analysis that integrates both epigenetic and genetic signatures. In this study, we present a platform that enables simultaneous analysis of whole-genome methylation, copy number, and fragmentomic patterns of cfDNA in a single assay. Using a total of 950 plasma (361 healthy and 589 cancer) and 240 tissue samples, we demonstrate that a multifeature cancer signature ensemble (CSE) classifier integrating all features outperforms single-feature classifiers. At 95.2% specificity, the cancer detection sensitivity with methylation, copy number, and fragmentomic models was 77.2%, 61.4%, and 60.5%, respectively, but sensitivity was significantly increased to 88.9% with the CSE classifier (p value < 0.0001). For tissue of origin, the CSE classifier enhanced the accuracy beyond the methylation classifier, from 74.3% to 76.4%. Overall, this work proves the utility of a signature ensemble integrating epigenetic and genetic information for accurate cancer detection.

Circulating DNA reveals a specific and higher fragmentation of the Y chromosome

Chromosome stability is a key point in genome evolution, particularly that of the Y chromosome. The Y chromosome loss in blood and tumor cells is well established. Through processes that are common to other chromosomes too, the Y chromosome undergoes degradation and fragmentation in the blood stream before elimination. This process gives rise to circulating DNA (cirDNA) fragments, whose examination may provide potential insight into the role of DNA fragmentation in blood for the Y chromosome elimination. In this study, we employed shallow whole genome sequencing (sWGS) to comprehensively assess the total cirDNA and the individual chromosome fragment size profiles in the plasma of healthy male individuals. Here, we show that (i) the fragment size profiles of total circulating DNA (cirDNA) and DNA fragments originating from autosomes and the X chromosome in blood plasma are homogeneous, and have a remarkably low variability (mean CV = 7%) among healthy individuals, (ii) the Y chromosome has a distinct fragment size profile with the accumulation of the fragment < 145 bp and depletion of the dinucleosome-associated fragments (290-390 bp), and its fragment fraction in blood decreases with age. These results indicate a higher fragmentation of the Y chromosome compared to other chromosomes and this in turn might be due to its increased susceptibility to degradation. Our findings pave the way for an elucidation of the impact of chromosomal origin on DNA degradation and the Y chromosome biology.

Biomarkers of lung cancer for screening and in never-smokers-a narrative review

Background and Objective

Lung cancer is the leading cause of cancer-related mortality worldwide, partially attributed to late-stage diagnoses. In order to mitigate this, lung cancer screening (LCS) of high-risk patients is performed using low dose computed tomography (CT) scans, however this method is burdened by high false-positive rates and radiation exposure for patients. Further, screening programs focus on individuals with heavy smoking histories, and as such, never-smokers who may otherwise be at risk of lung cancer are often overlooked. To resolve these limitations, biomarkers have been posited as potential supplements or replacements to low-dose CT, and as such, a large body of research in this area has been produced. However, comparatively little information exists on their clinical efficacy and how this compares to current LCS strategies.

Methods

Here we conduct a search and narrative review of current literature surrounding biomarkers of lung cancer to supplement LCS, and biomarkers of lung cancer in never-smokers (LCINS).

Key Content and Findings

Many potential biomarkers of lung cancer have been identified with varying levels of sensitivity, specificity, clinical efficacy, and supporting evidence. Of the markers identified, multi-target panels of circulating microRNAs, lipids, and metabolites are likely the most clinically efficacious markers to aid current screening programs, as these provide the highest sensitivity and specificity for lung cancer detection. However, circulating lipid and metabolite levels are known to vary in numerous systemic pathologies, highlighting the need for further validation in large cohort randomised studies.

Conclusions

Lung cancer biomarkers is a fast-expanding area of research and numerous biomarkers with potential clinical applications have been identified. However, in all cases the level of evidence supporting clinical efficacy is not yet at a level at which it can be translated to clinical practice. The priority now should be to validate existing candidate markers in appropriate clinical contexts and work to integrating these into clinical practice.

Multidimensional fragmentomic profiling of cell-free DNA released from patient-derived organoids

BACKGROUND

Fragmentomics, the investigation of fragmentation patterns of cell-free DNA (cfDNA), has emerged as a promising strategy for the early detection of multiple cancers in the field of liquid biopsy. However, the clinical application of this approach has been hindered by a limited understanding of cfDNA biology. Furthermore, the prevalence of hematopoietic cell-derived cfDNA in plasma complicates the in vivo investigation of tissue-specific cfDNA other than that of hematopoietic origin. While conventional two-dimensional cell lines have contributed to research on cfDNA biology, their limited representation of in vivo tissue contexts underscores the need for more robust models. In this study, we propose three-dimensional organoids as a novel in vitro model for studying cfDNA biology, focusing on multifaceted fragmentomic analyses.

RESULTS

We established nine patient-derived organoid lines from normal lung airway, normal gastric, and gastric cancer tissues. We then extracted cfDNA from the culture medium of these organoids in both proliferative and apoptotic states. Using whole-genome sequencing data from cfDNA, we analyzed various fragmentomic features, including fragment size, footprints, end motifs, and repeat types at the end. The distribution of cfDNA fragment sizes in organoids, especially in apoptosis samples, was similar to that found in plasma, implying occupancy by mononucleosomes. The footprints determined by sequencing depth exhibited distinct patterns depending on fragment sizes, reflecting occupancy by a variety of DNA-binding proteins. Notably, we discovered that short fragments (< 118 bp) were exclusively enriched in the proliferative state and exhibited distinct fragmentomic profiles, characterized by 3 bp palindromic end motifs and specific repeats.

CONCLUSIONS

In conclusion, our results highlight the utility of in vitro organoid models as a valuable tool for studying cfDNA biology and its associated fragmentation patterns. This, in turn, will pave the way for further enhancements in noninvasive cancer detection methodologies based on fragmentomics.

Circulating Tumour DNA as Biomarker for Colorectal Liver Metastases: A Systematic Review and Meta-Analysis

Circulating tumour DNA (ctDNA) is a potential biomarker that could contribute to more judicious patient selection for personalised treatment. This review and meta-analysis gives an overview of the current knowledge in the literature investigating the value of ctDNA in patients with colorectal liver metastases (CRLM). A systematic search was conducted in electronic databases for studies published prior to the 26th of May 2023. Studies investigating the association between ctDNA and oncological outcomes in patients undergoing curative-intent local therapy for CRLM were included. Meta-analyses were performed to pool hazard ratios (HR) for the recurrence-free survival (RFS) and overall survival (OS). A total of eleven studies were included and nine were eligible for meta-analyses. Patients with detectable ctDNA after surgery experienced a significantly higher chance of recurrence (HR 3.12, 95% CI 2.27-4.28, p < 0.000010) and shorter OS (HR 5.04, 95% CI 2.53-10.04, p < 0.00001) compared to patients without detectable ctDNA. A similar association for recurrence was found in patients with detectable ctDNA after the completion of adjuvant therapy (HR 6.39, 95% CI 2.13-19.17, p < 0.0009). The meta-analyses revealed no association between detectable ctDNA before surgery and the RFS and OS. These meta-analyses demonstrate the strong association between detectable ctDNA after treatment and oncological outcomes in CRLM patients.

Sequence-Based Platforms for Discovering Biomarkers in Liquid Biopsy of Non-Small-Cell Lung Cancer

Lung cancer detection and monitoring are hampered by a lack of sensitive biomarkers, which results in diagnosis at late stages and difficulty in tracking response to treatment. Recent developments have established liquid biopsies as promising non-invasive methods for detecting biomarkers in lung cancer patients. With concurrent advances in high-throughput sequencing technologies and bioinformatics tools, new approaches for biomarker discovery have emerged. In this article, we survey established and emerging biomarker discovery methods using nucleic acid materials derived from bodily fluids in the context of lung cancer. We introduce nucleic acid biomarkers extracted from liquid biopsies and outline biological sources and methods of isolation. We discuss next-generation sequencing (NGS) platforms commonly used to identify novel biomarkers and describe how these have been applied to liquid biopsy. We highlight emerging biomarker discovery methods, including applications of long-read sequencing, fragmentomics, whole-genome amplification methods for single-cell analysis, and whole-genome methylation assays. Finally, we discuss advanced bioinformatics tools, describing methods for processing NGS data, as well as recently developed software tailored for liquid biopsy biomarker detection, which holds promise for early diagnosis of lung cancer.

Circulating Tumor DNA in Head and Neck Squamous Cell Carcinoma

Tumors shed cell-free DNA (cfDNA) into the plasma. "Liquid biopsies" are a diagnostic test to analyze cfDNA in order to detect minimal residual cancer, profile the genomic tumor landscape, and monitor cancers non-invasively over time. This technique may be useful in patients with head and neck squamous cell carcinoma (HNSCC) due to genetic tumor heterogeneity and limitations in imaging sensitivity. However, there are technical challenges that need to be overcome for the widespread use of liquid biopsy in the clinical management of these patients. In this review, we discuss our current understanding of HNSCC genetics and the role of cfDNA genomic analyses as an emerging precision diagnostic tool.