Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing. Proc Natl Acad Sci U S A. 2013;110:18761-18768. [PMID: 24191000 DOI: 10.1073/pnas.1313995110]

Discovery and Validation of Methylation Signatures in Circulating Cell-Free DNA for the Detection of Colorectal Cancer

This study was conducted with the primary objective of assessing the performance of cfDNA methylation in the detection of colorectal cancer (CRC). Five tumor tissue, 20 peripheral blood leucocyte, and 169 cfDNA samples were collected for whole-genome bisulfite sequencing (WGBS) analysis. Bioinformatic analysis was conducted to identify differentially methylated regions (DMRs) and their functional characteristics. Quantitative methylation-specific PCR (qMSP) was used to validate the methylation levels of DMRs in the tissues and leucocytes. cfDNA samples from CRC patients and healthy controls were used to evaluate the performance of the DMR analysis. WGBS analysis revealed a decrease in DNA methylation levels in the CpG context in CRC tumor tissues compared with adjacent normal tissues. A total of 132 DMRs in cfDNA were identified as potential markers for diagnosing CRC. In a cohort of 95 CRC patients and 74 healthy controls, a combination of the three DMRs (DAB1, PPP2R5C, and FAM19A5) yielded an AUC of 0.763, achieving 64.21% sensitivity and 78.38% specificity in discriminating CRC patients from healthy controls. This study provides insights into DNA methylation patterns in CRC and identifies a set of DMRs in cfDNA with potential diagnostic value for CRC. These DMRs hold promise as biomarkers for CRC detection, offering promise for non-invasive CRC diagnosis. Further research is warranted to validate these findings in larger cohorts.

TOTEM: a multi-cancer detection and localization approach using circulating tumor DNA methylation markers

BACKGROUND

Detection of cancer and identification of tumor origin at an early stage improve the survival and prognosis of patients. Herein, we proposed a plasma cfDNA-based approach called TOTEM to detect and trace the cancer signal origin (CSO) through methylation markers.

METHODS

We performed enzymatic conversion-based targeted methylation sequencing on plasma cfDNA samples collected from a clinical cohort of 500 healthy controls and 733 cancer patients with seven types of cancer (breast, colorectum, esophagus, stomach, liver, lung, and pancreas) and randomly divided these samples into a training cohort and a testing cohort. An independent validation cohort of 143 healthy controls, 79 liver cancer patients and 100 stomach cancer patients were recruited to validate the generalizability of our approach.

RESULTS

A total of 57 multi-cancer diagnostic markers and 873 CSO markers were selected for model development. The binary diagnostic model achieved an area under the curve (AUC) of 0.907, 0.908 and 0.868 in the training, testing and independent validation cohorts, respectively. With a training specificity of 98%, the specificities in the testing and independent validation cohorts were 100% and 98.6%, respectively. Overall sensitivity across all cancer stages was 65.5%, 67.3% and 55.9% in the training, testing and independent validation cohorts, respectively. Early-stage (I and II) sensitivity was 50.3% and 45.7% in the training and testing cohorts, respectively. For cancer patients correctly identified by the binary classifier, the top 1 and top 2 CSO accuracies were 77.7% and 86.5% in the testing cohort (n = 148) and 76.0% and 84.0% in the independent validation cohort (n = 100). Notably, performance was maintained with only 21 diagnostic and 214 CSO markers, achieving a training AUC of 0.865, a testing AUC of 0.866, and an integrated top 2 accuracy of 83.1% in the testing cohort.

CONCLUSIONS

TOTEM demonstrates promising potential for accurate multi-cancer detection and localization by profiling plasma methylation markers. The real-world clinical performance of our approach needs to be investigated in a much larger prospective cohort.

Cancer screening with multicancer detection tests: A translational science review

Multicancer detection (MCD) tests use a single, easily obtainable biospecimen, such as blood, to screen for more than one cancer concurrently. MCD tests can potentially be used to improve early cancer detection, including cancers that currently lack effective screening methods. However, these tests have unknown and unquantified benefits and harms. MCD tests differ from conventional cancer screening tests in that the organ responsible for a positive test is unknown, and a broad diagnostic workup may be necessary to confirm the location and type of underlying cancer. Among two prospective studies involving greater than 16,000 individuals, MCD tests identified those who had some cancers without currently recommended screening tests, including pancreas, ovary, liver, uterus, small intestine, oropharyngeal, bone, thyroid, and hematologic malignancies, at early stages. Reported MCD test sensitivities range from 27% to 95% but differ by organ and are lower for early stage cancers, for which treatment toxicity would be lowest and the potential for cure might be highest. False reassurance from a negative MCD result may reduce screening adherence, risking a loss in proven public health benefits from standard-of-care screening. Prospective clinical trials are needed to address uncertainties about MCD accuracy to detect different cancers in asymptomatic individuals, whether these tests can detect cancer sufficiently early for effective treatment and mortality reduction, the degree to which these tests may contribute to cancer overdiagnosis and overtreatment, whether MCD tests work equally well across all populations, and the appropriate diagnostic evaluation and follow-up for patients with a positive test.

Methylated circulating tumor DNA in hepatocellular carcinoma: A comprehensive analysis of biomarker potential and clinical implications

The intricate epigenetic landscape of hepatocellular carcinoma (HCC) is profoundly influenced by alterations in DNA methylation patterns. Understanding these alterations is crucial for unraveling the molecular mechanisms underlying HCC pathogenesis. Methylated circulating tumor DNA (ctDNA) presents itself as an encouraging avenue for biomarker discovery and holds substantial clinical implications in HCC management. This review comprehensively outlines the studies concerning DNA methylation in HCC and underscores the significance of methylated ctDNA within this context. Moreover, a variety of cfDNA methylation-based methodologies, such as 5hmC profiling, bisulfite-based, restriction enzyme-dependent, and enrichment-based methods, provide in-depth insights into the molecular pathology of HCC. Additionally, the integration of methylated ctDNA analysis into clinical practice represents a significant advancement in personalized HCC management. By facilitating cancer screening, prognosis assessment, and treatment response prediction, the utilization of methylated ctDNA signifies a pivotal stride toward enhancing patient care and outcomes in HCC.

LABS: linear amplification-based bisulfite sequencing for ultrasensitive cancer detection from cell-free DNA

Methylation-based liquid biopsies show promises in detecting cancer using circulating cell-free DNA; however, current limitations impede clinical application. Most assays necessitate substantial DNA inputs, posing challenges. Additionally, underrepresented tumor DNA fragments may go undetected during exponential amplification steps of traditional sequencing methods. Here, we report linear amplification-based bisulfite sequencing (LABS), enabling linear amplification of bisulfite-treated DNA fragments in a genome-wide, unbiased fashion, detecting cancer abnormalities with sub-nanogram inputs. Applying LABS to 100 patient samples revealed cancer-specific patterns, copy number alterations, and enhanced cancer detection accuracy by identifying tissue-of-origin and immune cell composition.

Emerging Prognostic Markers in Patients Undergoing Liver Resection for Hepatocellular Carcinoma: A Narrative Review

In patients with hepatocellular carcinoma (HCC), liver resection is potentially curative. Nevertheless, post-operative recurrence is common, occurring in up to 70% of patients. Factors traditionally recognized to predict recurrence and survival after liver resection for HCC include pathologic factors (i.e., microvascular and capsular invasion) and an increase in alpha-fetoprotein level. During the past decade, many new markers have been reported to correlate with prognosis after resection of HCC: liquid biopsy markers, gene signatures, inflammation markers, and other biomarkers, including PIVKA-II, immune checkpoint molecules, and proteins in urinary exosomes. However, not all of these new markers are readily available in clinical practice, and their reproducibility is unclear. Liquid biopsy is a powerful and established tool for predicting long-term outcomes after resection of HCC; the main limitation of liquid biopsy is represented by the cost related to its technical implementation. Numerous patterns of genetic expression capable of predicting survival after curative-intent hepatectomy for HCC have been identified, but published findings regarding these markers are heterogenous. Inflammation markers in the form of prognostic nutritional index and different blood cell ratios seem more easily reproducible and more affordable on a large scale than other emerging markers. To select the most effective treatment for patients with HCC, it is crucial that the scientific community validate new predictive markers for recurrence and survival after resection that are reliable and widely reproducible. More reports from Western countries are necessary to corroborate the evidence.

Novel regulatory mechanisms of N-glycan sialylation: Implication of integrin and focal adhesion kinase in the regulation

BACKGROUND

Sialylation of glycoproteins, including integrins, is crucial in various cancers and diseases such as immune disorders. These modifications significantly impact cellular functions and are associated with cancer progression. Sialylation, catalyzed by specific sialyltransferases (STs), has traditionally been considered to be regulated at the mRNA level.

SCOPE OF REVIEW

Recent research has expanded our understanding of sialylation, revealing ST activity changes beyond mRNA level variations. This includes insights into COPI vesicle formation and Golgi apparatus maintenance and identifying specific target proteins of STs that are not predictable through recombinant enzyme assays.

MAJOR CONCLUSIONS

This review summarizes that Golgi-associated pathways largely influence the regulation of STs. GOLPH3, GORAB, PI4K, and FAK have become critical elements in sialylation regulation. Some STs have been revealed to possess specificity for specific target proteins, suggesting the presence of additional, enzyme-specific regulatory mechanisms.

GENERAL SIGNIFICANCE

This study enhances our understanding of the molecular interplay in sialylation regulation, mainly focusing on the role of integrin and FAK. It proposes a bidirectional system where sialylations might influence integrins and vice versa. The diversity of STs and their specific linkages offer new perspectives in cancer research, potentially broadening our understanding of cellular mechanisms and opening avenues for new therapeutic approaches in targeting sialylation pathways.

Genome-Scale Multimodal Analysis of Cell-Free DNA Whole-Methylome Sequencing for Noninvasive Esophageal Cancer Detection

PURPOSE

Simultaneous profiling of cell-free DNA (cfDNA) methylation and fragmentation features to improve the performance of cfDNA-based cancer detection is technically challenging. We developed a method to comprehensively analyze multimodal cfDNA genomic features for more sensitive esophageal squamous cell carcinoma (ESCC) detection.

MATERIALS AND METHODS

Enzymatic conversion-mediated whole-methylome sequencing was applied to plasma cfDNA samples extracted from 168 patients with ESCC and 251 noncancer controls. ESCC characteristic cfDNA methylation, fragmentation, and copy number signatures were analyzed both across the genome and at accessible cis-regulatory DNA elements. To distinguish ESCC from noncancer samples, a first-layer classifier was developed for each feature type, the prediction results of which were incorporated to construct the second-layer ensemble model.

RESULTS

ESCC plasma genome displayed global hypomethylation, altered fragmentation size, and chromosomal copy number alteration. Methylation and fragmentation changes at cancer tissue-specific accessible cis-regulatory DNA elements were also observed in ESCC plasma. By integrating multimodal genomic features for ESCC detection, the ensemble model showed improved performance over individual modalities. In the training cohort with a specificity of 99.2%, the detection sensitivity was 81.0% for all stages and 70.0% for stage 0-II. Consistent performance was observed in the test cohort with a specificity of 98.4%, an all-stage sensitivity of 79.8%, and a stage 0-II sensitivity of 69.0%. The performance of the classifier was associated with the disease stage, irrespective of clinical covariates.

CONCLUSION

This study comprehensively profiles the epigenomic landscape of ESCC plasma and provides a novel noninvasive and sensitive ESCC detection approach with genome-scale multimodal analysis.

Targeted Nanoparticle-Based Diagnostic and Treatment Options for Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC), one of the deadliest cancers, presents significant challenges in diagnosis and treatment due to its aggressive, metastatic nature and lack of early detection methods. A key obstacle in PDAC treatment is the highly complex tumor environment characterized by dense stroma surrounding the tumor, which hinders effective drug delivery. Nanotechnology can offer innovative solutions to these challenges, particularly in creating novel drug delivery systems for existing anticancer drugs for PDAC, such as gemcitabine and paclitaxel. By using customization methods such as incorporating conjugated targeting ligands, tumor-penetrating peptides, and therapeutic nucleic acids, these nanoparticle-based systems enhance drug solubility, extend circulation time, improve tumor targeting, and control drug release, thereby minimizing side effects and toxicity in healthy tissues. Moreover, nanoparticles have also shown potential in precise diagnostic methods for PDAC. This literature review will delve into targeted mechanisms, pathways, and approaches in treating pancreatic cancer. Additional emphasis is placed on the study of nanoparticle-based delivery systems, with a brief mention of those in clinical trials. Overall, the overview illustrates the significant advances in nanomedicine, underscoring its role in transcending the constraints of conventional PDAC therapies and diagnostics.

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.

Circulating tumor DNA as prognostic markers of relapsed breast cancer: a systematic review and meta-analysis

Objective

Circulating tumor DNA (ctDNA) is increasingly being used as a potential prognosis biomarker in patients of breast cancer. This review aims to assess the clinical value of ctDNA in outcome prediction in breast cancer patients throughout the whole treatment cycle.

Methods

PubMed, Web of Science, Embase, Cochrane Library, Scopus, and clinical trials.gov were searched from January 2016 to May 2022. Conference abstracts published in last three years were also included. The following search terms were used: ctDNA OR circulating tumor DNA AND breast cancer OR breast carcinoma. Only studies written in English languages were included. The following pre-specified criteria should be met for inclusion: (1) observational studies (prospective or retrospective), randomized control trials, case-control studies and case series studies; (2) patients with breast cancer; (3) ctDNA measurement; (4) clinical outcome data such as objective response rate (ORR), pathological complete response (pCR), relapse-free survival (RFS), overall survival (OS), and so on. The random-effect model was preferred considering the potential heterogeneity across studies. The primary outcomes included postoperative short-term outcomes (ORR and pCR) and postoperative long-term outcomes (RFS, OS, and relapse). Secondary outcomes focused on ctDNA detection rate.

Results

A total of 30 studies, comprising of 19 cohort studies, 2 case-control studies and 9 case series studies were included. The baseline ctDNA was significantly negatively associated with ORR outcome (Relative Risk [RR] = 0.65, 95% confidence interval [CI]: 0.50-0.83), with lower ORR in the ctDNA-positive group than ctDNA-negative group. ctDNA during neoadjuvant therapy (NAT) treatment was significantly associated with pCR outcomes (Odds Ratio [OR] = 0.15, 95% CI: 0.04-0.54). The strong association between ctDNA and RFS or relapse outcome was significant across the whole treatment period, especially after the surgery (RFS: Hazard Ratio [HR] = 6.74, 95% CI: 3.73-12.17; relapse outcome: RR = 7.11, 95% CI: 3.05-16.53), although there was heterogeneity in these results. Pre-operative and post-operative ctDNA measurements were significantly associated with OS outcomes (pre-operative: HR = 2.03, 95% CI: 1.12-3.70; post-operative: HR = 6.03, 95% CI: 1.31-27.78).

Conclusions

In this review, ctDNA measurements at different timepoints are correlated with evaluation indexes at different periods after treatment. The ctDNA can be used as an early potential postoperative prognosis biomarker in breast cancer, and also as a reference index to evaluate the therapeutic effect at different stages.

Liquid Biopsy for Glioma Using Cell-Free DNA in Cerebrospinal Fluid

Glioma is one of the most common primary central nervous system (CNS) tumors, and its molecular diagnosis is crucial. However, surgical resection or biopsy is risky when the tumor is located deep in the brain or brainstem. In such cases, a minimally invasive approach to liquid biopsy is beneficial. Cell-free DNA (cfDNA), which directly reflects tumor-specific genetic changes, has attracted attention as a target for liquid biopsy, and blood-based cfDNA monitoring has been demonstrated for other extra-cranial cancers. However, it is still challenging to fully detect CNS tumors derived from cfDNA in the blood, including gliomas, because of the unique structure of the blood-brain barrier. Alternatively, cerebrospinal fluid (CSF) is an ideal source of cfDNA and is expected to contribute significantly to the liquid biopsy of gliomas. Several successful studies have been conducted to detect tumor-specific genetic alterations in cfDNA from CSF using digital PCR and/or next-generation sequencing. This review summarizes the current status of CSF-based cfDNA-targeted liquid biopsy for gliomas. It highlights how the approaches differ from liquid biopsies of other extra-cranial cancers and discusses the current issues and prospects.

Plasma cell-free DNA methylation analysis for ovarian cancer detection: Analysis of samples from a case-control study and an ovarian cancer screening trial

Analysis of cell-free DNA methylation (cfDNAme), alone or combined with CA125, could help to detect ovarian cancers earlier and may reduce mortality. We assessed cfDNAme in regions of ZNF154, C2CD4D and WNT6 via targeted bisulfite sequencing in diagnostic and early detection (preceding diagnosis) settings. Diagnostic samples were obtained via prospective blood collection in cell-free DNA tubes in a convenience series of patients with a pelvic mass. Early detection samples were matched case-control samples derived from the UK Familial Ovarian Cancer Screening Study (UKFOCSS). In the diagnostic set (ncases  = 27, ncontrols  = 41), the specificity of cfDNAme was 97.6% (95% CI: 87.1%-99.9%). High-risk cancers were detected with a sensitivity of 80% (56.3%-94.3%). Combination of cfDNAme and CA125 resulted in a sensitivity of 94.4% (72.7%-99.9%) for high-risk cancers. Despite technical issues in the early detection set (ncases  = 29, ncontrols  = 29), the specificity of cfDNAme was 100% (88.1%-100.0%). We detected 27.3% (6.0%-61.0%) of high-risk cases with relatively lower genomic DNA (gDNA) contamination. The sensitivity rose to 33.3% (7.5%-70.1%) in samples taken <1 year before diagnosis. We detected ovarian cancer in several patients up to 1 year before diagnosis despite technical limitations associated with archival samples (UKFOCSS). Combined cfDNAme and CA125 assessment may improve ovarian cancer screening in high-risk populations, but future large-scale prospective studies will be required to validate current findings.

Simultaneous single-cell analysis of 5mC and 5hmC with SIMPLE-seq

Dynamic 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) modifications to DNA regulate gene expression in a cell-type-specific manner and are associated with various biological processes, but the two modalities have not yet been measured simultaneously from the same genome at the single-cell level. Here we present SIMPLE-seq, a scalable, base resolution method for joint analysis of 5mC and 5hmC from thousands of single cells. Based on orthogonal labeling and recording of 'C-to-T' mutational signals from 5mC and 5hmC sites, SIMPLE-seq detects these two modifications from the same molecules in single cells and enables unbiased DNA methylation dynamics analysis of heterogeneous biological samples. We applied this method to mouse embryonic stem cells, human peripheral blood mononuclear cells and mouse brain to give joint epigenome maps at single-cell and single-molecule resolution. Integrated analysis of these two cytosine modifications reveals distinct epigenetic patterns associated with divergent regulatory programs in different cell types as well as cell states.

Molecular profiling in the management of hepatocellular carcinoma

PURPOSE OF REVIEW

The purpose of this review is to both summarize the current knowledge of hepatocellular carcinoma molecular biology and to suggest a framework in which to prospectively translate this knowledge into patient care. This is timely as recent guidelines recommend increased use of these technologies to advance personalized liver cancer care.

RECENT FINDINGS

The main themes covered here address germline and somatic genetic alterations recently discovered in hepatocellular carcinoma, largely owing to next generation sequencing technologies, and nascent efforts to translate these into contemporary practice.

SUMMARY

Early efforts of translating molecular profiling to hepatocellular carcinoma care demonstrate a growing number of potentially actionable alterations. Still lacking are a consensus on what biomarkers and technologies to adopt, at what scale and cost, and how to integrate them most effectively into care.

Non-invasive detection of lymphoma with circulating tumor DNA features and protein tumor markers

Background

According to GLOBOCAN 2020, lymphoma ranked as the 9th most common cancer and the 12th leading cause of cancer-related deaths worldwide. Traditional diagnostic methods rely on the invasive excisional lymph node biopsy, which is an invasive approach with some limitations. Most lymphoma patients are diagnosed at an advanced stage since they are asymptomatic at the beginning, which has significantly impacted treatment efficacy and prognosis of the disease.

Method

This study assessed the performance and utility of a newly developed blood-based assay (SeekInCare) for lymphoma early detection. SeekInCare utilized protein tumor markers and a comprehensive set of cancer-associated genomic features, including copy number aberration (CNA), fragment size (FS), end motif, and lymphoma-related virus, which were profiled by shallow WGS of cfDNA.

Results

Protein marker CA125 could be used for lymphoma detection independent of gender, and the sensitivity was 27.8% at specificity of 98.0%. After integrating these multi-dimensional features, 77.8% sensitivity was achieved at specificity of 98.0%, while its NPV and PPV were both more than 92% for lymphoma detection. The sensitivity of early-stage (I-II) lymphoma was up to 51.3% (47.4% and 55.0% for stage I and II respectively). After 2 cycles of treatment, the molecular response of SeekInCare was correlated with the clinical outcome.

Conclusion

In summary, a blood-based assay can be an alternative to detect lymphoma with adequate performance. This approach becomes particularly valuable in cases where obtaining tissue biopsy is difficult to obtain or inconclusive.

Multimodal epigenetic sequencing analysis (MESA) of cell-free DNA for non-invasive colorectal cancer detection

BACKGROUND

Detecting human cancers through cell-free DNA (cfDNA) in blood is a sensitive and non-invasive option. However, capturing multiple forms of epigenetic information remains a technical and financial challenge.

METHODS

To address this, we developed multimodal epigenetic sequencing analysis (MESA), a flexible and sensitive approach to capturing and integrating a diverse range of epigenetic features in cfDNA using a single experimental assay, i.e., non-disruptive bisulfite-free methylation sequencing, such as Enzymatic Methyl-seq. MESA enables simultaneous inference of four epigenetic modalities: cfDNA methylation, nucleosome occupancy, nucleosome fuzziness, and windowed protection score for regions surrounding gene promoters and polyadenylation sites.

RESULTS

When applied to 690 cfDNA samples from 3 colorectal cancer clinical cohorts, MESA's novel modalities, which include nucleosome fuzziness, and genomic features, including polyadenylation sites, improve cancer detection beyond the traditional epigenetic markers of promoter DNA methylation.

CONCLUSIONS

Together, MESA stands as a major advancement in the field by utilizing comprehensive and complementary epigenetic profiles of cfDNA for effective non-invasive cancer detection.

Proteomics-driven noninvasive screening of circulating serum protein panels for the early diagnosis of hepatocellular carcinoma

Early diagnosis of hepatocellular carcinoma (HCC) lacks highly sensitive and specific protein biomarkers. Here, we describe a staged mass spectrometry (MS)-based discovery-verification-validation proteomics workflow to explore serum proteomic biomarkers for HCC early diagnosis in 1002 individuals. Machine learning model determined as P4 panel (HABP2, CD163, AFP and PIVKA-II) clearly distinguish HCC from liver cirrhosis (LC, AUC 0.979, sensitivity 0.925, specificity 0.915) and healthy individuals (HC, AUC 0.992, sensitivity 0.975, specificity 1.000) in an independent validation cohort, outperforming existing clinical prediction strategies. Furthermore, the P4 panel can accurately predict LC to HCC conversion (AUC 0.890, sensitivity 0.909, specificity 0.877) with predicting HCC at a median of 11.4 months prior to imaging in prospective external validation cohorts (No.: Keshen 2018_005_02 and NCT03588442). These results suggest that proteomics-driven serum biomarker discovery provides a valuable reference for the liquid biopsy, and has great potential to improve early diagnosis of HCC.

The changing face of circulating tumor DNA (ctDNA) profiling: Factors that shape the landscape of methodologies, technologies, and commercialization

Liquid biopsies, in particular the profiling of circulating tumor DNA (ctDNA), have long held promise as transformative tools in cancer precision medicine. Despite a prolonged incubation phase, ctDNA profiling has recently experienced a strong wave of development and innovation, indicating its imminent integration into the cancer management toolbox. Various advancements in mutation-based ctDNA analysis methodologies and technologies have greatly improved sensitivity and specificity of ctDNA assays, such as optimized preanalytics, size-based pre-enrichment strategies, targeted sequencing, enhanced library preparation methods, sequencing error suppression, integrated bioinformatics and machine learning. Moreover, research breakthroughs have expanded the scope of ctDNA analysis beyond hotspot mutational profiling of plasma-derived apoptotic, mono-nucleosomal ctDNA fragments. This broader perspective considers alternative genetic features of cancer, genome-wide characterization, classical and newly discovered epigenetic modifications, structural variations, diverse cellular and mechanistic ctDNA origins, and alternative biospecimen types. These developments have maximized the utility of ctDNA, facilitating landmark research, clinical trials, and the commercialization of ctDNA assays, technologies, and products. Consequently, ctDNA tests are increasingly recognized as an important part of patient guidance and are being implemented in clinical practice. Although reimbursement for ctDNA tests by healthcare providers still lags behind, it is gaining greater acceptance. In this work, we provide a comprehensive exploration of the extensive landscape of ctDNA profiling methodologies, considering the multitude of factors that influence its development and evolution. By illuminating the broader aspects of ctDNA profiling, the aim is to provide multiple entry points for understanding and navigating the vast and rapidly evolving landscape of ctDNA methodologies, applications, and technologies.

Circulating tumor DNA predicts recurrence and assesses prognosis in operable gastric cancer: A systematic review and meta-analysis

BACKGROUND

Selecting the appropriate patient for further treatment after surgery for gastric cancer can improve the patient prognosis. Circulating tumor DNA (ctDNA) has the potential to predict recurrence and prognosis after gastric cancer surgery, but the results are still inconclusive. As the completed studies had small sample sizes and were inconsistent, a meta-analysis was conducted to assess the effect of ctDNA on recurrence and prognosis after gastric cancer surgery.

METHODS

PubMed, Embase, Scopus, and the Web of Science were searched for potentially eligible studies published up to April 7, 2023. Pooled relative risk (RR) and pooled hazard ratio (HR) were calculated to evaluate recurrence, recurrence-free survival (RFS), and overall survival (OS) following gastric cancer surgery.

RESULTS

A pooled analysis revealed that patients who were ctDNA positive before and after surgery were at a high risk of gastric cancer recurrence (RR = 1.79, 95% CI: 1.19-2.71; RR = 3.17, 95% CI: 2.36-4.25). The pooled data revealed that ctDNA-positive patients had a poorer RFS and OS (HR = 6.37, 95% CI: 2.70-15.01; HR = 4.58, 95% CI: 1.68-12.49).

CONCLUSIONS

ctDNA-positive patients were at a high risk of recurrence after gastric cancer surgery and had a poorer prognosis. Hence, ctDNA-positive patients needed close follow-up and further treatment.

Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization

Despite their promise, circulating tumor DNA (ctDNA)-based assays for multi-cancer early detection face challenges in test performance, due mostly to the limited abundance of ctDNA and its inherent variability. To address these challenges, published assays to date demanded a very high-depth sequencing, resulting in an elevated price of test. Herein, we developed a multimodal assay called SPOT-MAS (screening for the presence of tumor by methylation and size) to simultaneously profile methylomics, fragmentomics, copy number, and end motifs in a single workflow using targeted and shallow genome-wide sequencing (~0.55×) of cell-free DNA. We applied SPOT-MAS to 738 non-metastatic patients with breast, colorectal, gastric, lung, and liver cancer, and 1550 healthy controls. We then employed machine learning to extract multiple cancer and tissue-specific signatures for detecting and locating cancer. SPOT-MAS successfully detected the five cancer types with a sensitivity of 72.4% at 97.0% specificity. The sensitivities for detecting early-stage cancers were 73.9% and 62.3% for stages I and II, respectively, increasing to 88.3% for non-metastatic stage IIIA. For tumor-of-origin, our assay achieved an accuracy of 0.7. Our study demonstrates comparable performance to other ctDNA-based assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening.

The Origin of Highly Elevated Cell-Free DNA in Healthy Individuals and Patients with Pancreatic, Colorectal, Lung, or Ovarian Cancer

Cell-free DNA (cfDNA) concentrations from patients with cancer are often elevated compared with those of healthy controls, but the sources of this extra cfDNA have never been determined. To address this issue, we assessed cfDNA methylation patterns in 178 patients with cancers of the colon, pancreas, lung, or ovary and 64 patients without cancer. Eighty-three of these individuals had cfDNA concentrations much greater than those generally observed in healthy subjects. The major contributor of cfDNA in all samples was leukocytes, accounting for ∼76% of cfDNA, with neutrophils predominating. This was true regardless of whether the samples were derived from patients with cancer or the total plasma cfDNA concentration. High levels of cfDNA observed in patients with cancer did not come from either neoplastic cells or surrounding normal epithelial cells from the tumor's tissue of origin. These data suggest that cancers may have a systemic effect on cell turnover or DNA clearance.

SIGNIFICANCE

The origin of excess cfDNA in patients with cancer is unknown. Using cfDNA methylation patterns, we determined that neither the tumor nor the surrounding normal tissue contributes this excess cfDNA-rather it comes from leukocytes. This finding suggests that cancers have a systemic impact on cell turnover or DNA clearance. See related commentary by Thierry and Pisareva, p. 2122. This article is featured in Selected Articles from This Issue, p. 2109.

Evaluating Stacked Methylation Markers for Blood-Based Multicancer Detection

The ability to detect several types of cancer using a non-invasive, blood-based test holds the potential to revolutionize oncology screening. We mined tumor methylation array data from the Cancer Genome Atlas (TCGA) covering 14 cancer types and identified two novel, broadly-occurring methylation markers at TLX1 and GALR1. To evaluate their performance as a generalized blood-based screening approach, along with our previously reported methylation biomarker, ZNF154, we rigorously assessed each marker individually or combined. Utilizing TCGA methylation data and applying logistic regression models within each individual cancer type, we found that the three-marker combination significantly increased the average area under the ROC curve (AUC) across the 14 tumor types compared to single markers (p = 1.158 × 10-10; Friedman test). Furthermore, we simulated dilutions of tumor DNA into healthy blood cell DNA and demonstrated increased AUC of combined markers across all dilution levels. Finally, we evaluated assay performance in bisulfite sequenced DNA from patient tumors and plasma, including early-stage samples. When combining all three markers, the assay correctly identified nine out of nine lung cancer plasma samples. In patient plasma from hepatocellular carcinoma, ZNF154 alone yielded the highest combined sensitivity and specificity values averaging 68% and 72%, whereas multiple markers could achieve higher sensitivity or specificity, but not both. Altogether, this study presents a comprehensive pipeline for the identification, testing, and validation of multi-cancer methylation biomarkers with a considerable potential for detecting a broad range of cancer types in patient blood samples.

Multimodal analysis of cell-free DNA whole-methylome sequencing for cancer detection and localization

Multimodal epigenetic characterization of cell-free DNA (cfDNA) could improve the performance of blood-based early cancer detection. However, integrative profiling of cfDNA methylome and fragmentome has been technologically challenging. Here, we adapt an enzyme-mediated methylation sequencing method for comprehensive analysis of genome-wide cfDNA methylation, fragmentation, and copy number alteration (CNA) characteristics for enhanced cancer detection. We apply this method to plasma samples of 497 healthy controls and 780 patients of seven cancer types and develop an ensemble classifier by incorporating methylation, fragmentation, and CNA features. In the test cohort, our approach achieves an area under the curve value of 0.966 for overall cancer detection. Detection sensitivity for early-stage patients achieves 73% at 99% specificity. Finally, we demonstrate the feasibility to accurately localize the origin of cancer signals with combined methylation and fragmentation profiling of tissue-specific accessible chromatin regions. Overall, this proof-of-concept study provides a technical platform to utilize multimodal cfDNA features for improved cancer detection.

Multidimensional Analysis of a Cell-Free DNA Whole Methylome Sequencing Assay for Early Detection of Gastric Cancer: Protocol for an Observational Case-Control Study

BACKGROUND

Commonly used noninvasive serological indicators serve as a step before endoscope diagnosis and help identify the high-risk gastric cancer (GC) population. However, they are associated with high false positives and high false negatives. Alternative noninvasive approaches, such as cancer-related features in cell-free DNA (cfDNA) fragments, have been gradually identified and play essential roles in early cancer detection. The integrated analysis of multiple cfDNA features has enhanced detection sensitivity compared to individual features.

OBJECTIVE

This study aimed to develop and validate an assay based on assessing genomic-scale methylation and fragmentation profiles of plasma cfDNA for early cancer detection, thereby facilitating the early diagnosis of GC. The primary objective is to evaluate the overall specificity and sensitivity of the assay in predicting GC within the entire cohort, and subsequently within each clinical stage of GC. The secondary objective involved investigating the specificity and sensitivity of the assay in combination with possible serological indicators.

METHODS

This is an observational case-control study. Blood samples will be prospectively collected before gastroscopy from 180 patients with GC and 180 nonmalignant control subjects (healthy or with benign gastric diseases). Cases and controls will be randomly divided into a training and a testing data set at a ratio of 2:1. Plasma cfDNA will be isolated and extracted, followed by bisulfite-free low-depth whole methylome sequencing. A multidimensional model named Thorough Epigenetic Marker Integration Solution (THEMIS) will be constructed in the training data set. The model includes features such as the methylated fragment ratio, chromosomal aneuploidy of featured fragments, fragment size index, and fragment end motif. The performance of the model in distinguishing between patients with cancer and noncancer controls will then be evaluated in the testing data set. Furthermore, GC-related biomarkers, such as pepsinogen, gastrin-17, and Helicobacter pylori, will be measured for each patient, and their predictive accuracy will be assessed both independently and in combination with the THEMIS model.

RESULTS

Recruitment began in November 2022 and will be ended in April 2024. As of August 2022,250 patients have been enrolled. The final data analysis is anticipated to be completed by September 2024.

CONCLUSIONS

This is the first registered case-control study designed to investigate a stacked ensemble model integrating several cfDNA features generated from a bisulfite-free whole methylome sequencing assay. These features include methylation patterns, fragmentation profiles, and chromosomal copy number changes, with the aim of identifying the GC population. This study will determine whether multidimensional analysis of cfDNA will prove to be an effective strategy for distinguishing patients with GC from nonmalignant individuals within the Chinese population. We anticipate the THEMIS model will complement the standard-of-care screening and aid in identifying high-risk patients for further diagnosis.

TRIAL REGISTRATION

ClinicalTrial.gov NCT05668910; https://www.clinicaltrials.gov/study/NCT05668910.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/48247.

Pancreatic Cancer and Detection Methods

The pancreas is a vital organ with exocrine and endocrine functions. Pancreatitis is an inflammation of the pancreas caused by alcohol consumption and gallstones. This condition can heighten the risk of pancreatic cancer (PC), a challenging disease with a high mortality rate. Genetic and epigenetic factors contribute significantly to PC development, along with other risk factors. Early detection is crucial for improving PC outcomes. Diagnostic methods, including imagining modalities and tissue biopsy, aid in the detection and analysis of PC. In contrast, liquid biopsy (LB) shows promise in early tumor detection by assessing biomarkers in bodily fluids. Understanding the function of the pancreas, associated diseases, risk factors, and available diagnostic methods is essential for effective management and early PC detection. The current clinical examination of PC is challenging due to its asymptomatic early stages and limitations of highly precise diagnostics. Screening is recommended for high-risk populations and individuals with potential benign tumors. Among various PC screening methods, the N-NOSE plus pancreas test stands out with its high AUC of 0.865. Compared to other commercial products, the N-NOSE plus pancreas test offers a cost-effective solution for early detection. However, additional diagnostic tests are required for confirmation. Further research, validation, and the development of non-invasive screening methods and standardized scoring systems are crucial to enhance PC detection and improve patient outcomes. This review outlines the context of pancreatic cancer and the challenges for early detection.

Advances in methylation analysis of liquid biopsy in early cancer detection of colorectal and lung cancer

Methylation patterns in cell-free DNA (cfDNA) have emerged as a promising genomic feature for detecting the presence of cancer and determining its origin. The purpose of this study was to evaluate the diagnostic performance of methylation-sensitive restriction enzyme digestion followed by sequencing (MRE-Seq) using cfDNA, and to investigate the cancer signal origin (CSO) of the cancer using a deep neural network (DNN) analyses for liquid biopsy of colorectal and lung cancer. We developed a selective MRE-Seq method with DNN learning-based prediction model using demethylated-sequence-depth patterns from 63,266 CpG sites using SacII enzyme digestion. A total of 191 patients with stage I-IV cancers (95 lung cancers and 96 colorectal cancers) and 126 noncancer participants were enrolled in this study. Our study showed an area under the receiver operating characteristic curve (AUC) of 0.978 with a sensitivity of 78.1% for colorectal cancer, and an AUC of 0.956 with a sensitivity of 66.3% for lung cancer, both at a specificity of 99.2%. For colorectal cancer, sensitivities for stages I-IV ranged from 76.2 to 83.3% while for lung cancer, sensitivities for stages I-IV ranged from 44.4 to 78.9%, both again at a specificity of 99.2%. The CSO model's true-positive rates were 94.4% and 89.9% for colorectal and lung cancers, respectively. The MRE-Seq was found to be a useful method for detecting global hypomethylation patterns in liquid biopsy samples and accurately diagnosing colorectal and lung cancers, as well as determining CSO of the cancer using DNN analysis.Trial registration: This trial was registered at ClinicalTrials.gov (registration number: NCT04253509) for lung cancer on 5 February 2020, https://clinicaltrials.gov/ct2/show/NCT04253509 . Colorectal cancer samples were retrospectively registered at CRIS (Clinical Research Information Service, registration number: KCT0008037) on 23 December 2022, https://cris.nih.go.kr , https://who.init/ictrp . Healthy control samples were retrospectively registered.

Comprehensive tissue deconvolution of cell-free DNA by deep learning for disease diagnosis and monitoring

Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. Despite the great promise, the sensitive and accurate quantification of tissue-derived cfDNA remains challenging to existing methods due to the limited characterization of tissue methylation and the reliance on unsupervised methods. To fully exploit the clinical potential of tissue-derived cfDNA, here we present one of the largest comprehensive and high-resolution methylation atlas based on 521 noncancer tissue samples spanning 29 major types of human tissues. We systematically identified fragment-level tissue-specific methylation patterns and extensively validated them in orthogonal datasets. Based on the rich tissue methylation atlas, we develop the first supervised tissue deconvolution approach, a deep-learning-powered model, cfSort, for sensitive and accurate tissue deconvolution in cfDNA. On the benchmarking data, cfSort showed superior sensitivity and accuracy compared to the existing methods. We further demonstrated the clinical utilities of cfSort with two potential applications: aiding disease diagnosis and monitoring treatment side effects. The tissue-derived cfDNA fraction estimated from cfSort reflected the clinical outcomes of the patients. In summary, the tissue methylation atlas and cfSort enhanced the performance of tissue deconvolution in cfDNA, thus facilitating cfDNA-based disease detection and longitudinal treatment monitoring.

Plasma Epstein-Barr Virus DNA and Risk of Future Nasopharyngeal Cancer

BACKGROUND: We previously conducted a prospective study to show that nasopharyngeal cancer (NPC) screening with circulating Epstein–Barr virus (EBV) DNA analysis can improve survival. However, the long-term significance of positive results in individuals without cancer was unclear. METHODS: We conducted a second-round screening at a median of 43 months after the initial screening. Participants with detectable plasma EBV DNA were retested in 4 weeks, and those with persistently positive results were investigated with nasal endoscopy and magnetic resonance imaging. RESULTS: Of the 20,174 volunteers who participated in the first-round screening, 17,838 (88.6%) were rescreened. Among them, 423 (2.37%) had persistently detectable plasma EBV DNA. Twenty-four patients were identified as having NPC. A significantly higher proportion of patients had stage I/II cancer than in a historical cohort (67% vs. 20%; chi-square test, P<0.001), and they had superior 3-year progression-free survival (100% vs. 78.8%). Compared with participants with undetectable plasma EBV DNA in the first round of screening, participants with transiently and persistently positive results in the first round were more likely to have a cancer identified in the second round, with relative risks of 4.4 (95% confidence interval, 1.3 to 15.0) and 16.8 (95% confidence interval, 5.7 to 49.6), respectively. CONCLUSIONS: Individuals with detectable plasma EBV DNA but without an immediately identifiable NPC were more likely to have the cancer identified in another round of screening performed 3 to 5 years later. (Funded by Kadoorie Charitable Foundation and others; ClinicalTrials.gov number, NCT02063399.)

Testing the generalizability of cfDNA fragmentomic features across different studies for cancer early detection

cfDNA fragmentomic features have been used in cancer detection models; however, the generalizability of the models needs to be tested. We proposed a type of cfDNA fragmentomic feature named chromosomal arm-level fragment size distribution (ARM-FSD), evaluated and compared its performance and generalizability for lung cancer and pan-cancer detection with existing cfDNA fragmentomic features (as reference) by using cohorts from different institutions. The ARM-FSD lung cancer model outperformed the reference model by ∼10% when being tested by two external cohorts (AUC: 0.97 vs. 0.86; 0.87 vs. 0.76). For pan-cancer detection, the performance of the ARM-FSD based model is consistently higher than the reference (AUC: 0.88 vs. 0.75, 0.98 vs. 0.63) in a pan-cancer and a lung cancer external validation cohort, indicating that ARM-FSD model produces stable performance across multiple cohorts. Our study reveals ARM-FSD based models have a higher generalizability, and highlights the necessity of cross-study validation for predictive model development.

The Way to Malignant Transformation: Can Epigenetic Alterations Be Used to Diagnose Early-Stage Head and Neck Cancer?

Identifying and treating tumors early is the key to secondary prevention in cancer control. At present, prevention of oral cancer is still challenging because the molecular drivers responsible for malignant transformation of the 11 clinically defined oral potentially malignant disorders are still unknown. In this review, we focused on studies that elucidate the epigenetic alterations demarcating malignant and nonmalignant epigenomes and prioritized findings from clinical samples. Head and neck included, the genomes of many cancer types are largely hypomethylated and accompanied by focal hypermethylation on certain specific regions. We revisited prior studies that demonstrated that sufficient uptake of folate, the primary dietary methyl donor, is associated with oral cancer reduction. As epigenetically driven phenotypic plasticity, a newly recognized hallmark of cancer, has been linked to tumor initiation, cell fate determination, and drug resistance, we discussed prior findings that might be associated with this hallmark, including gene clusters (11q13.3, 19q13.43, 20q11.2, 22q11-13) with great potential for oral cancer biomarkers, and successful examples in screening early-stage nasopharyngeal carcinoma. Although one-size-fits-all approaches have been shown to be ineffective in most cancer therapies, the rapid development of epigenome sequencing methods raises the possibility that this nonmutagenic approach may be an exception. Only time will tell.

Dynamics of Sequence and Structural Cell-Free DNA Landscapes in Small-Cell Lung Cancer

PURPOSE

Patients with small-cell lung cancer (SCLC) have an exceptionally poor prognosis, calling for improved real-time noninvasive biomarkers of therapeutic response.

EXPERIMENTAL DESIGN

We performed targeted error-correction sequencing on 171 serial plasmas and matched white blood cell (WBC) DNA from 33 patients with metastatic SCLC who received treatment with chemotherapy (n = 16) or immunotherapy-containing (n = 17) regimens. Tumor-derived sequence alterations and plasma aneuploidy were evaluated serially and combined to assess changes in total cell-free tumor load (cfTL). Longitudinal dynamic changes in cfTL were monitored to determine circulating cell-free tumor DNA (ctDNA) molecular response during therapy.

RESULTS

Combined tiered analyses of tumor-derived sequence alterations and plasma aneuploidy allowed for the assessment of ctDNA molecular response in all patients. Patients classified as molecular responders (n = 9) displayed sustained elimination of cfTL to undetectable levels. For 14 patients, we observed initial molecular responses, followed by ctDNA recrudescence. A subset of patients (n = 10) displayed a clear pattern of molecular progression, with persistence of cfTL across all time points. Molecular responses captured the therapeutic effect and long-term clinical outcomes in a more accurate and rapid manner compared with radiographic imaging. Patients with sustained molecular responses had longer overall (log-rank P = 0.0006) and progression-free (log-rank P < 0.0001) survival, with molecular responses detected on average 4 weeks earlier than imaging.

CONCLUSIONS

ctDNA analyses provide a precise approach for the assessment of early on-therapy molecular responses and have important implications for the management of patients with SCLC, including the development of improved strategies for real-time tumor burden monitoring. See related commentary by Pellini and Chaudhuri, p. 2176.

A high-throughput test enables specific detection of hepatocellular carcinoma

High-throughput tests for early cancer detection can revolutionize public health and reduce cancer morbidity and mortality. Here we show a DNA methylation signature for hepatocellular carcinoma (HCC) detection in liquid biopsies, distinct from normal tissues and blood profiles. We developed a classifier using four CpG sites, validated in TCGA HCC data. A single F12 gene CpG site effectively differentiates HCC samples from other blood samples, normal tissues, and non-HCC tumors in TCGA and GEO data repositories. The markers were validated in a separate plasma sample dataset from HCC patients and controls. We designed a high-throughput assay using next-generation sequencing and multiplexing techniques, analyzing plasma samples from 554 clinical study participants, including HCC patients, non-HCC cancers, chronic hepatitis B, and healthy controls. HCC detection sensitivity was 84.5% at 95% specificity and 0.94 AUC. Implementing this assay for high-risk individuals could significantly decrease HCC morbidity and mortality.

Gene body hypomethylation of pyroptosis-related genes NLRP7, NLRP2, and NLRP3 facilitate non-invasive surveillance of hepatocellular carcinoma

Programmed cell death (PCD) resistance is a key driver of cancer occurrence and development. The prognostic relevance of PCD-related genes in hepatocellular carcinoma (HCC) has attracted considerable attention in recent years. However, there is still a lack of efforts to compare the methylation status of different types of PCD genes in HCC and their roles in its surveillance. The methylation status of genes related to pyroptosis, apoptosis, autophagy, necroptosis, ferroptosis, and cuproptosis was analyzed in tumor and non-tumor tissues from TCGA. Whole-genome bisulfite sequencing (WGBS) data of paired tumor tissue and buffy coat samples were used to filter the potential interference of blood leukocytes in cell-free DNA (cfDNA). The WGBS data of healthy individuals' and early-stage HCC patients' cfDNA were analyzed to evaluate the distinguishing ability. The average gene body methylation (gbDNAme) of pyroptosis-related genes (PRGs) was significantly altered in HCC tissues relative to normal tissues, and their distinguishing ability was higher compared to the other types of PCD-related genes. The gbDNAme of NLRP7, NLRP2, and NLRP3 was reflective of the hypomethylation in HCC tissues, and methylation levels of NLRP3 correlated positively with its expression level (r=0.51). The candidate hypomethylated PRGs could discriminate between early HCC patients and healthy controls in cfDNA analysis with high accuracy (area under the receiver operation curve, AUC=0.94). Furthermore, the hypomethylation of PRGs was associated with poor prognosis of HCC. Gene body hypomethylation of PRGs is a promising biomarker for early HCC detection, monitoring of tumor recurrence, and prognosis prediction.

Evaluation of circulating tumor DNA by electropherogram analysis and methylome profiling in high-risk neuroblastomas

Background

Liquid biopsy has emerged as a promising, non-invasive diagnostic approach in oncology because the analysis of circulating tumor DNA (ctDNA) reflects the precise status of the disease at diagnosis, progression, and response to treatment. DNA methylation profiling is also a potential solution for sensitive and specific detection of many cancers. The combination of both approaches, DNA methylation analysis from ctDNA, provides an extremely useful and minimally invasive tool with high relevance in patients with childhood cancer. Neuroblastoma is an extracranial solid tumor most common in children and responsible for up to 15% of cancer-related deaths. This high death rate has prompted the scientific community to search for new therapeutic targets. DNA methylation also offers a new source for identifying these molecules. However, the limited blood sample size which can be obtained from children with cancer and the fact that ctDNA content may occasionally be diluted by non-tumor cell-free DNA (cfDNA) complicate optimal quantities of material for high-throughput sequencing studies.

Methods

In this article, we present an improved method for ctDNA methylome studies of blood-derived plasma from high-risk neuroblastoma patients. We assessed the electropherogram profiles of ctDNA-containing samples suitable for methylome studies, using 10 ng of plasma-derived ctDNA from 126 samples of 86 high-risk neuroblastoma patients, and evaluated several bioinformatic approaches to analyze DNA methylation sequencing data.

Results

We demonstrated that enzymatic methyl-sequencing (EM-seq) outperformed bisulfite conversion-based method, based on the lower proportion of PCR duplicates and the higher percentage of unique mapping reads, mean coverage, and genome coverage. The analysis of the electropherogram profiles revealed the presence of nucleosomal multimers, and occasionally high molecular weight DNA. We established that 10% content of the mono-nucleosomal peak is sufficient ctDNA for successful detection of copy number variations and methylation profiles. Quantification of mono-nucleosomal peak also showed that samples at diagnosis contained a higher amount of ctDNA than relapse samples.

Conclusions

Our results refine the use of electropherogram profiles to optimize sample selection for subsequent high-throughput analysis and support the use of liquid biopsy followed by enzymatic conversion of unmethylated cysteines to assess the methylomes of neuroblastoma patients.

Multimodal analysis of genome-wide methylation, copy number aberrations, and end motif signatures enhances detection of early-stage breast cancer

Introduction

Breast cancer causes the most cancer-related death in women and is the costliest cancer in the US regarding medical service and prescription drug expenses. Breast cancer screening is recommended by health authorities in the US, but current screening efforts are often compromised by high false positive rates. Liquid biopsy based on circulating tumor DNA (ctDNA) has emerged as a potential approach to screen for cancer. However, the detection of breast cancer, particularly in early stages, is challenging due to the low amount of ctDNA and heterogeneity of molecular subtypes.

Methods

Here, we employed a multimodal approach, namely Screen for the Presence of Tumor by DNA Methylation and Size (SPOT-MAS), to simultaneously analyze multiple signatures of cell free DNA (cfDNA) in plasma samples of 239 nonmetastatic breast cancer patients and 278 healthy subjects.

Results

We identified distinct profiles of genome-wide methylation changes (GWM), copy number alterations (CNA), and 4-nucleotide oligomer (4-mer) end motifs (EM) in cfDNA of breast cancer patients. We further used all three signatures to construct a multi-featured machine learning model and showed that the combination model outperformed base models built from individual features, achieving an AUC of 0.91 (95% CI: 0.87-0.95), a sensitivity of 65% at 96% specificity.

Discussion

Our findings showed that a multimodal liquid biopsy assay based on analysis of cfDNA methylation, CNA and EM could enhance the accuracy for the detection of early- stage breast cancer.

Multi-omics integrated circulating cell-free DNA genomic signatures enhanced the diagnostic performance of early-stage lung cancer and postoperative minimal residual disease

BACKGROUND

Liquid biopsy is a promising non-invasive alternative for cancer screening and minimal residual disease (MRD) detection, although there are some concerns regarding its clinical applications. We aimed to develop an accurate detection platform based on liquid biopsy for both cancer screening and MRD detection in patients with lung cancer (LC), which is also applicable to clinical use.

METHODS

We applied a modified whole-genome sequencing (WGS) -based High-performance Infrastructure For MultIomics (HIFI) method for LC screening and postoperative MRD detection by combining the hyper-co-methylated read approach and the circulating single-molecule amplification and resequencing technology (cSMART2.0).

FINDINGS

For early screening of LC, the LC score model was constructed using the support vector machine, which showed sensitivity (51.8%) at high specificity (96.3%) and achieved an AUC of 0.912 in the validation set prospectively enrolled from multiple centers. The screening model achieved detection efficiency with an AUC of 0.906 in patients with lung adenocarcinoma and outperformed other clinical models in solid nodule cohort. When applied the HIFI model to real social population, a negative predictive value (NPV) of 99.92% was achieved in Chinese population. Additionally, the MRD detection rate improved significantly by combining results from WGS and cSMART2.0, with sensitivity of 73.7% at specificity of 97.3%.

INTERPRETATION

In conclusion, the HIFI method is promising for diagnosis and postoperative monitoring of LC.

FUNDING

This study was supported by CAMS Innovation Fund for Medical Sciences, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, Beijing Natural Science Foundation and Peking University People's Hospital.

Liquid biopsy in hematological malignancies: current and future applications

The assessment of the cancer mutational profile is crucial for patient management, stratification, and therapeutic decisions. At present, in hematological malignancies with a solid mass, such as lymphomas, tumor genomic profiling is generally performed on the tissue biopsy, but the tumor may harbor genetic lesions that are unique to other anatomical compartments. The analysis of circulating tumor DNA (ctDNA) on the liquid biopsy is an emerging approach that allows genotyping and monitoring of the disease during therapy and follow-up. This review presents the different methods for ctDNA analysis and describes the application of liquid biopsy in different hematological malignancies. In diffuse large B-cell lymphoma (DLBCL) and Hodgkin lymphoma (HL), ctDNA analysis on the liquid biopsy recapitulates the mutational profile of the tissue biopsy and can identify mutations otherwise absent on the tissue biopsy. In addition, changes in the ctDNA amount after one or two courses of chemotherapy significantly predict patient outcomes. ctDNA analysis has also been tested in myeloid neoplasms with promising results. In addition to mutational analysis, liquid biopsy also carries potential future applications of ctDNA, including the analysis of ctDNA fragmentation and epigenetic patterns. On these grounds, several clinical trials aiming at incorporating ctDNA analysis for treatment tailoring are currently ongoing in hematological malignancies.

Integrative modeling of tumor genomes and epigenomes for enhanced cancer diagnosis by cell-free DNA

Multi-cancer early detection remains a key challenge in cell-free DNA (cfDNA)-based liquid biopsy. Here, we perform cfDNA whole-genome sequencing to generate two test datasets covering 2125 patient samples of 9 cancer types and 1241 normal control samples, and also a reference dataset for background variant filtering based on 20,529 low-depth healthy samples. An external cfDNA dataset consisting of 208 cancer and 214 normal control samples is used for additional evaluation. Accuracy for cancer detection and tissue-of-origin localization is achieved using our algorithm, which incorporates cancer type-specific profiles of mutation distribution and chromatin organization in tumor tissues as model references. Our integrative model detects early-stage cancers, including those of pancreatic origin, with high sensitivity that is comparable to that of late-stage detection. Model interpretation reveals the contribution of cancer type-specific genomic and epigenomic features. Our methodologies may lay the groundwork for accurate cfDNA-based cancer diagnosis, especially at early stages.

Liquid Biopsy in the Management of Breast Cancer Patients: Where Are We Now and Where Are We Going

Liquid biopsy (LB) is an emerging diagnostic tool that analyzes biomarkers in the blood (and possibly in other body fluids) to provide information about tumor genetics and response to therapy. This review article provides an overview of LB applications in human cancer with a focus on breast cancer patients. LB methods include circulating tumor cells and cell-free tumor products, such as circulating tumor DNA. LB has shown potential in detecting cancer at an early stage, monitoring tumor progression and recurrence, and predicting patient response to therapy. Several studies have demonstrated its clinical utility in breast cancer patients. However, there are limitations to LB, including the lack of standardized assays and the need for further validation. Future potential applications of LB include identifying the minimal residual disease, early detection of recurrence, and monitoring treatment response in various cancer types. LB represents a promising non-invasive diagnostic tool with potential applications in breast cancer diagnosis, treatment, and management. Further research is necessary to fully understand its clinical utility and overcome its current limitations.

Shifting the Cancer Screening Paradigm: The Rising Potential of Blood-Based Multi-Cancer Early Detection Tests

Cancer remains a leading cause of death worldwide, partly owing to late detection which entails limited and often ineffective therapeutic options. Most cancers lack validated screening procedures, and the ones available disclose several drawbacks, leading to low patient compliance and unnecessary workups, adding up the costs to healthcare systems. Hence, there is a great need for innovative, accurate, and minimally invasive tools for early cancer detection. In recent years, multi-cancer early detection (MCED) tests emerged as a promising screening tool, combining molecular analysis of tumor-related markers present in body fluids with artificial intelligence to simultaneously detect a variety of cancers and further discriminate the underlying cancer type. Herein, we aim to provide a highlight of the variety of strategies currently under development concerning MCED, as well as the major factors which are preventing clinical implementation. Although MCED tests depict great potential for clinical application, large-scale clinical validation studies are still lacking.

Fragment length profiles of cancer mutations enhance detection of circulating tumor DNA in patients with early-stage hepatocellular carcinoma

BACKGROUND

Late detection of hepatocellular carcinoma (HCC) results in an overall 5-year survival rate of less than 16%. Liquid biopsy (LB) assays based on detecting circulating tumor DNA (ctDNA) might provide an opportunity to detect HCC early noninvasively. Increasing evidence indicates that ctDNA detection using mutation-based assays is significantly challenged by the abundance of white blood cell-derived mutations, non-tumor tissue-derived somatic mutations in plasma, and the mutational tumor heterogeneity.

METHODS

Here, we employed concurrent analysis of cancer-related mutations, and their fragment length profiles to differentiate mutations from different sources. To distinguish persons with HCC (PwHCC) from healthy participants, we built a classification model using three fragmentomic features of ctDNA through deep sequencing of thirteen genes associated with HCC.

RESULTS

Our model achieved an area under the curve (AUC) of 0.88, a sensitivity of 89%, and a specificity of 82% in the discovery cohort consisting of 55 PwHCC and 55 healthy participants. In an independent validation cohort of 54 PwHCC and 53 healthy participants, the established model achieved comparable classification performance with an AUC of 0.86 and yielded a sensitivity and specificity of 81%.

CONCLUSIONS

Our study provides a rationale for subsequent clinical evaluation of our assay performance in a large-scale prospective study.

Can Liquid Biopsy Based on ctDNA/cfDNA Replace Tissue Biopsy for the Precision Treatment of EGFR-Mutated NSCLC?

More and more clinical trials have explored the role of liquid biopsy in the diagnosis and treatment of EGFR-mutated NSCLC. In certain circumstances, liquid biopsy has unique advantages and offers a new way to detect therapeutic targets, analyze drug resistance mechanisms in advanced patients, and monitor MRD in patients with operable NSCLC. Although its potential cannot be ignored, more evidence is needed to support the transition from the research stage to clinical application. We reviewed the latest progress in research on the efficacy and resistance mechanisms of targeted therapy for advanced NSCLC patients with plasma ctDNA EGFR mutation and the evaluation of MRD based on ctDNA detection in perioperative and follow-up monitoring.

Locus-Specific Bisulfate NGS Sequencing of GSTP1, RNF219, and KIAA1539 Genes in the Total Pool of Cell-Free and Cell-Surface-Bound DNA in Prostate Cancer: A Novel Approach for Prostate Cancer Diagnostics

The locus-specific methylation of three genes (GSTP1, RNF219, and KIAA1539, also known as FAM214B) in the total pool of blood cell-free DNA, including cell-free DNA from plasma and cell-surface-bound DNA, of patients with prostate cancer and healthy donors was studied on the MiSeq platform. Our study found a higher methylation index of loci for total cell-free DNA compared with cell-free DNA. For total cell-free DNA, the methylation of GSTP1 in each of the 11 positions provided a complete separation of cancer patients from healthy donors, whereas for cell-free DNA, there were no positions in the three genes allowing for such separation. Among the prostate cancer patients, the minimum proportion of GSTP1 genes methylated in any of the 17 positions was 12.1% of the total circulated DNA fragments, and the minimum proportion of GSTP1 genes methylated in any of the 11 diagnostically specific positions was 8.4%. Total cell-free DNA was shown to be more convenient and informative as a source of methylated DNA molecules circulating in the blood than cell-free DNA.

CRAG: de novo characterization of cell-free DNA fragmentation hotspots in plasma whole-genome sequencing

The fine-scale cell-free DNA fragmentation patterns in early-stage cancers are poorly understood. We developed a de novo approach to characterize the cell-free DNA fragmentation hotspots from plasma whole-genome sequencing. Hotspots are enriched in open chromatin regions, and, interestingly, 3'end of transposons. Hotspots showed global hypo-fragmentation in early-stage liver cancers and are associated with genes involved in the initiation of hepatocellular carcinoma and associated with cancer stem cells. The hotspots varied across multiple early-stage cancers and demonstrated high performance for the diagnosis and identification of tissue-of-origin in early-stage cancers. We further validated the performance with a small number of independent case-control-matched early-stage cancer samples.

A framework for clinical cancer subtyping from nucleosome profiling of cell-free DNA

Cell-free DNA (cfDNA) has the potential to inform tumor subtype classification and help guide clinical precision oncology. Here we develop Griffin, a framework for profiling nucleosome protection and accessibility from cfDNA to study the phenotype of tumors using as low as 0.1x coverage whole genome sequencing data. Griffin employs a GC correction procedure tailored to variable cfDNA fragment sizes, which generates a better representation of chromatin accessibility and improves the accuracy of cancer detection and tumor subtype classification. We demonstrate estrogen receptor subtyping from cfDNA in metastatic breast cancer. We predict estrogen receptor subtype in 139 patients with at least 5% detectable circulating tumor DNA with an area under the receive operator characteristic curve (AUC) of 0.89 and validate performance in independent cohorts (AUC = 0.96). In summary, Griffin is a framework for accurate tumor subtyping and can be generalizable to other cancer types for precision oncology applications.

HCC biomarkers - state of the old and outlook to future promising biomarkers and their potential in everyday clinical practice

Hepatocellular carcinoma (HCC) is one of the most common and deadly tumors worldwide. Management of HCC depends on reliable biomarkers for screening, diagnosis, and monitoring of the disease, as well as predicting response towards therapy and safety. To date, imaging has been the established standard technique in the diagnosis and follow-up of HCC. However, imaging techniques have their limitations, especially in the early detection of HCC. Therefore, there is an urgent need for reliable, non/minimal invasive biomarkers. To date, alpha-fetoprotein (AFP) is the only serum biomarker used in clinical practice for the management of HCC. However, AFP is of relatively rather low quality in terms of specificity and sensitivity. Liquid biopsies as a source for biomarkers have become the focus of clinical research. Our review highlights alternative biomarkers derived from liquid biopsies, including circulating tumor cells, proteins, circulating nucleic acids, and exosomes, and their potential for clinical application. Using defined combinations of different biomarkers will open new perspectives for diagnosing, treating, and monitoring HCC.

Diagnostic performance of circulating tumor DNA as a minimally invasive biomarker for hepatocellular carcinoma: a systematic review and meta-analysis

Purpose

This study aimed to assess the diagnostic performance of circulating tumor DNA (ctDNA) in hepatocellular carcinoma (HCC).

Materials and Methods

We enrolled all relevant studies published up to 5 January 2022. Three primary subgroups were investigated: qualitative or quantitative ctDNA analyses, combined alpha-fetoprotein (AFP), and ctDNA assay. In addition to the three primary subgroups, we also evaluated the diagnostic value of methylated SEPTIN9 (mSEPT9), which has been studied extensively in the diagnosis of hepatocellular carcinoma. After a search based on four primary databases, we used a bivariate linear mixed model to analyze the pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). We also plotted hierarchical summary receiver operating characteristics (HSROC) and utilized lambda as well as the area under the curve (AUC) to create summary receiver operating characteristic (SROC) curves to estimate the diagnostic value of ctDNA.

Results

A total of 59 qualified articles with 9,766 subjects were incorporated into our meta-analysis. The integrated SEN, SPE, and DOR in the qualitative studies were 0.50 (95% CI [0.43-0.56]), 0.90 (95% CI [0.86-0.93]), and 8.72 (95% CI [6.18-12.32]), respectively, yielding an AUC of 0.78 and lambda of 1.93 (95% CI [1.56-2.33]). For quantitative studies, the corresponding values were 0.69 (95% CI [0.63-0.74]), 0.84 (95% CI [0.77-0.89]), 11.88 (95% CI [7.78-18.12]), 0.81, and 2.32 (95% CI [1.96-2.69]), respectively. Six studies were included to evaluate the SETP9 methylation, which yielded an AUC of 0.86, a SEN of 0.80 (95% CI [0.71-0.87]), and a SPE of 0.77 (95% CI [0.68-0.85]). Likewise, ctDNA concentration yielded an AUC of 0.73, with a SEN of 0.63 (95% CI [0.56-0.70]) and a SPE of 0.86 (95% CI [0.74-0.93]). AFP combined with ctDNA assay resulted in an AUC of 0.89, with a SEN of 0.82 (95% CI [0.77-0.86]) and a SPE of 0.84 (95% CI [0.76-0.90]).

Conclusion

This study shows that circulating tumor DNA, particularly mSEPT9, shows promising diagnostic potential in HCC; however, it is not enough to diagnose HCC independently, and ctDNA combined with conventional assays such as AFP can effectively improve diagnostic performance.