Detection of chromosomal alterations in the circulation of cancer patients with whole-genome sequencing

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

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

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

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

Immunotherapy for resectable lung cancer

Lung cancer remains a significant global health challenge, demanding innovative treatment strategies. Immune checkpoint blockade has revolutionized cancer care, leading to improved survival across advanced malignancies and has now become a standard therapy for earlier stage, resectable lung cancer. This review article consolidates the current landscape and future prospects of neoadjuvant and perioperative immunotherapy in lung cancer. The authors outline key findings from clinical trials in resectable lung cancer, including early efficacy, safety profiles, and emerging impact on disease recurrence, and overall survival. Additionally, this review elucidates the challenges encountered, including patient selection criteria, optimal treatment schedules, immune-related adverse events, and impact on surgery. This comprehensive analysis amalgamates current evidence with future directions, providing a roadmap for clinicians, researchers, and stakeholders to navigate the dynamic realm of immunotherapy for surgically resectable lung cancer.

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

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

Personalized Tumor-Specific Amplified DNA Junctions in Peripheral Blood of Patients with High-Grade Gliomas

PURPOSE

Monitoring disease progression in patients with high-grade gliomas (HGG) is challenging due to treatment-related changes in imaging and the requirement for neurosurgical intervention to obtain diagnostic tissue. DNA junctions in HGG often amplify oncogenes, making these DNA fragments potentially more abundant in blood than monoallelic mutations. In this study, we piloted a cell-free DNA approach for disease detection in the plasma of patients with HGG by leveraging patient-specific DNA junctions associated with oncogene amplifications.

EXPERIMENTAL DESIGN

Whole-genome sequencing of grade 3 or 4 isocitrate dehydrogenase-mutant or wild-type astrocytomas was utilized to identify amplified junctions. Individualized qPCR assays were developed using patient-specific primers designed for the amplified junction. ctDNA levels containing these junctions were measured in patient plasma samples.

RESULTS

Unique amplified junctions were evaluated by individualized semi-qPCR assays in presurgical plasma of 18 patients, 15 with tumor-associated focal amplifications and three without tumor-associated focal amplifications. high copy-number junctions were robustly detected in the plasma of 14 of 15 (93.3%) patients with amplified junctions and none of the controls. Changes in junction abundance correlated with disease trajectory in serial plasma samples from five patients, including increased abundance of amplified junctions preceding radiographic disease progression.

CONCLUSIONS

In patients with grade 3 or 4 astrocytomas who had tumor-associated amplifications, patient-specific amplified junctions were successfully detected in assayed plasma from most patients. Longitudinal analysis of plasma samples correlated with disease trajectory, including cytoreduction and progression.

Multi‑omics analysis identifies different molecular subtypes with unique outcomes in early-stage poorly differentiated lung adenocarcinoma

INTRODUCTION

Early-stage poorly differentiated lung adenocarcinoma (LUAD) is plagued by a high risk of postoperative recurrence, and its prognostic heterogeneity complicates treatment and surveillance planning. We conducted this integrative multi-omics study to identify those patients with a truly high risk of adverse outcomes.

METHODS

Whole-exome, RNA and whole methylome sequencing were carried out on 101 treatment-naïve early-stage poorly differentiated LUADs. Integrated analyses were conducted to disclose molecular characteristics and explore molecular subtyping. Functional validation of key molecules was carried out through in vitro and in vivo experiments.

RESULTS

Recurrent tumors exhibited significantly higher ploidy (p = 0.024), the fraction of the genome altered (FGA, p = 0.042), and aneuploidy (p < 0.05) compared to non-recurrent tumors, as well as a higher frequency of CNVs. Additionally, recurrent tumors showed hypomethylation at both the global level and in CpG island regions. Integrative transcriptomic and methylation analyses identified three molecular subtypes (C1, C2, and C3), with the C1 subtype presenting the worst prognosis (p = 0.024). Although frequently mutated genes showed similar mutation frequencies across the three subtypes, the C1 subtype exhibited the highest tumor mutation burden (TMB), mutant-allele tumor heterogeneity (MATH), aneuploidy, and HLA loss of heterozygosity (HLA-LOH), along with relatively lower immune cell infiltration. Furthermore, GINS1 and CPT1C were found to promote LUAD progression, and their high expression correlated with a poor prognosis.

CONCLUSIONS

This multi-omics study identified three integrative subtypes with distinct prognostic implications, paving the way for more precise management and postoperative monitoring of early-stage poorly differentiated LUAD.

Applications of ctDNA testing to monitor and detect residual disease in breast cancer

INTRODUCTION

In recent years, circulating tumor DNA (ctDNA) has emerged as a promising method for detection of minimal or molecular residual disease (MRD) among patients with breast cancer.

AREAS COVERED

In this narrative review, we provide a summary of currently available studies assessing use of ctDNA in detection of MRD in patients after completion of curative therapy. Additionally, we discuss limitations of present studies, future considerations, and an overview of ongoing trials evaluating the clinical utility of MRD-directed therapy interventions.

EXPERT OPINION

While the clinical utility of MRD-directed therapy guidance remains under investigation, collective data from studies overwhelmingly confirm the prognostic value of ctDNA status across various stages and subtypes of breast cancer. Results from ongoing clinical trials in the coming years will provide more clarity on the overall clinical benefit of MRD-directed interventions for breast cancer patients.

Genomics and the early diagnosis of lung cancer

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

Circulating tumor DNA: a revolutionary approach for early detection and personalized treatment of bladder cancer

Bladder cancer is a malignant tumor with a high global incidence and recurrence rate. Traditional diagnostic methods, such as cystoscopy and urine cytology, have limitations in sensitivity and specificity, particularly in detecting low-grade bladder cancer. Circulating tumor DNA (ctDNA) offers a non-invasive alternative, reflecting tumor genetic characteristics through blood samples. It demonstrates high sensitivity and repeatability, making it a promising tool for early detection, recurrence monitoring, and treatment evaluation. Clinical studies have shown that ctDNA not only detects tumor burden but also captures dynamic tumor mutations, aiding in personalized treatment strategies. Despite its potential, clinical implementation of ctDNA faces challenges, including optimization of detection techniques, standardization, and the cost of testing. This paper explores the role of ctDNA in advancing bladder cancer diagnosis and treatment, with a focus on refining its clinical application and guiding future research toward improved patient outcomes.

Analytical Validation of the Labcorp Plasma Complete Test, a Cell-Free DNA Comprehensive Genomic Profiling Tool for Precision Oncology

To help guide treatment decisions and trial matching, tumor genomic profiling is an essential precision oncology tool. Liquid biopsy, a complementary approach to tissue testing, can assess tumor-specific DNA alterations circulating in the blood. Labcorp Plasma Complete is a next-generation sequencing, cell-free DNA comprehensive genomic profiling test that identifies clinically relevant somatic variants across 521 genes in advanced and metastatic solid cancers. Over 800 unique sequencing libraries across 27 cancer types were evaluated to establish analytical sensitivity, specificity, accuracy, and precision, reproducibility, and repeatability (PRR). Sensitivity was verified for each variant type, with a median variant allele frequency (VAF) of 1.25% and 1.27% for panel-wide single nucleotide variants (SNVs) and insertions/deletions (indels) (sequence mutations), respectively, with <1% VAF sensitivity observed for clinically actionable variants, 1.72-fold for copy number amplifications (CNAs), 0.48% fusion read fraction for translocations, and 0.47% sequence mutation VAF for microsatellite instability-high (MSI-H). Specificity was 99.9999% for SNVs and 100% for other variant types. PRR resulted in 94.9% average positive agreement (APA) and 99.9% average negative agreement (ANA) for sequence mutations and 100% APA and ANA for CNAs, translocations, and MSI-H. Orthogonal assays were utilized to assess accuracy, demonstrating concordance of 97.4% positive percent agreement and >99.99997% negative percent agreement across all variants. Overall, the test demonstrates high sensitivity, specificity, accuracy, and robustness to enable informed clinical decision-making.

Multimodal cell-free DNA whole-genome TAPS is sensitive and reveals specific cancer signals

The analysis of circulating tumour DNA (ctDNA) through minimally invasive liquid biopsies is promising for early multi-cancer detection and monitoring minimal residual disease. Most existing methods focus on targeted deep sequencing, but few integrate multiple data modalities. Here, we develop a methodology for ctDNA detection using deep (80x) whole-genome TET-Assisted Pyridine Borane Sequencing (TAPS), a less destructive approach than bisulphite sequencing, which permits the simultaneous analysis of genomic and methylomic data. We conduct a diagnostic accuracy study across multiple cancer types in symptomatic patients, achieving 94.9% sensitivity and 88.8% specificity. Matched tumour biopsies are used for validation, not for guiding the analysis, imitating an early detection scenario. Furthermore, in silico validation demonstrates strong discrimination (86% AUC) at ctDNA fractions as low as 0.7%. Additionally, we successfully track tumour burden and ctDNA shedding from precancerous lesions post-treatment without requiring matched tumour biopsies. This pipeline is ready for further clinical evaluation to extend cancer screening and improve patient triage and monitoring.

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.

Advances and challenges in the use of liquid biopsy in gynaecological oncology

Ovarian cancer, endometrial cancer, and cervical cancer are the three primary gynaecological cancers that pose a significant threat to women's health on a global scale. Enhancing global cancer survival rates necessitates advancements in illness detection and monitoring, with the goal of improving early diagnosis and prognostication of disease recurrence. Conventional methods for identifying and tracking malignancies rely primarily on imaging techniques and, when possible, protein biomarkers found in blood, many of which lack specificity. The process of collecting tumour samples necessitates intrusive treatments that are not suitable for specific purposes, such as screening, predicting, or evaluating the effectiveness of treatment, monitoring the presence of remaining illness, and promptly detecting relapse. Advancements in treatment are being made by the detection of genetic abnormalities in tumours, both inherited and acquired. Newly designed therapeutic approaches can specifically address some of these abnormalities. Liquid biopsy is an innovative technique for collecting samples that examine specific cancer components that are discharged into the bloodstream, such as circulating tumour DNA (ctDNA), circulating tumour cells (CTCs), cell-free RNA (cfRNA), tumour-educated platelets (TEPs), and exosomes. Mounting data indicates that liquid biopsy has the potential to improve the clinical management of gynaecological cancers through enhanced early diagnosis, prognosis prediction, recurrence detection, and therapy response monitoring. Understanding the distinct genetic composition of tumours can also inform therapy choices and the identification of suitable targeted treatments. The main benefits of liquid biopsy are its non-invasive characteristics and practicality, enabling the collection of several samples and the continuous monitoring of tumour changes over time. This review aims to provide an overview of the data supporting the therapeutic usefulness of each component of liquid biopsy. Additionally, it will assess the benefits and existing constraints associated with the use of liquid biopsy in the management of gynaecological malignancies. In addition, we emphasise future prospects in light of the existing difficulties and investigate areas where further research is necessary to clarify its rising clinical capabilities.

Cancer treatment monitoring using cell-free DNA fragmentomes

Circulating cell-free DNA (cfDNA) assays for monitoring individuals with cancer typically rely on prior identification of tumor-specific mutations. Here, we develop a tumor-independent and mutation-independent approach (DELFI-tumor fraction, DELFI-TF) using low-coverage whole genome sequencing to determine the cfDNA tumor fraction and validate the method in two independent cohorts of patients with colorectal or lung cancer. DELFI-TF scores strongly correlate with circulating tumor DNA levels (ctDNA) (r = 0.90, p < 0.0001, Pearson correlation) even in cases where mutations are undetectable. DELFI-TF scores prior to therapy initiation are associated with clinical response and are independent predictors of overall survival (HR = 9.84, 95% CI = 1.72-56.10, p < 0.0001). Patients with lower DELFI-TF scores during treatment have longer overall survival (62.8 vs 29.1 months, HR = 3.12, 95% CI 1.62-6.00, p < 0.001) and the approach predicts clinical outcomes more accurately than imaging. These results demonstrate the potential of using cfDNA fragmentomes to estimate tumor burden in cfDNA for treatment response monitoring and clinical outcome prediction.

Liquid biopsy for early cancer detection: technological revolutions and clinical dilemma

INTRODUCTION

Liquid biopsy is an innovative advancement in oncology, offering a noninvasive method for early cancer detection and monitoring by analyzing circulating tumor cells, DNA, RNA, and other biomarkers in bodily fluids. This technique has the potential to revolutionize precision oncology by providing real-time analysis of tumor dynamics, enabling early detection, monitoring treatment responses, and tailoring personalized therapies based on the molecular profiles of individual patients.

AREAS COVERED

In this review, the authors discuss current methodologies, technological challenges, and clinical applications of liquid biopsy. This includes advancements in detecting minimal residual disease, tracking tumor evolution, and combining liquid biopsy with other diagnostic modalities for precision oncology. Key areas explored are the sensitivity, specificity, and integration of multi-omics, AI, ML, and LLM technologies.

EXPERT OPINION

Liquid biopsy holds great potential to revolutionize cancer care through early detection and personalized treatment strategies. However, its success depends on overcoming technological and clinical hurdles, such as ensuring high sensitivity and specificity, interpreting results amidst tumor heterogeneity, and making tests accessible and affordable. Continued innovation and collaboration are crucial to fully realize the potential of liquid biopsy in improving early cancer detection, treatment, and monitoring.

Harnessing the potential of genomic characterization of mutational profiles to improve early diagnosis of lung cancer

INTRODUCTION

Lung Cancer (LC) continues to be a leading cause of cancer-related mortality globally, largely due to the asymptomatic nature of its early stages and the limitations of current diagnostic methods such as Low-Dose Computed Tomography (LDCT), whose often result in late diagnosis, highlighting an urgent need for innovative, minimally invasive diagnostic techniques that can improve early detection rates.

AREAS COVERED

This review delves into the potential of genomic characterization and mutational profiling to enhance early LC diagnosis, exploring the current state and limitations of traditional diagnostic approaches and the revolutionary role of Liquid Biopsies (LB), including cell-free DNA (cfDNA) analysis through fragmentomics and methylomics. New genomic technologies that allow for earlier detection of LC are scrutinized, alongside a detailed discussion on the literature that shaped our understanding in this field.

EXPERT OPINION

Despite the promising advancements in genomic characterization techniques, several challenges remain, such as the heterogeneity of LC mutations, the high cost, and limited accessibility of Next-Generation Sequencing (NGS) technologies. Additionally, there is a critical need of standardized protocols for interpreting mutational data. Future research should focus on overcoming these barriers to integrate these novel diagnostic methods into standard clinical practice, potentially revolutionizing the management of LC patients.

The Impact of Liquid Biopsy in Advanced Ovarian Cancer Care

INTRODUCTION

Ovarian cancer is the third most common gynaecological cancer and has a very high mortality rate. The cornerstone of treatment is complete debulking surgery plus chemotherapy. Even with treatment, 80% of patients have a recurrence. Circulating tumour DNA (ctDNA) has been shown to be useful in the control and follow-up of some tumours. It could be an option to define complete cytoreduction and for the early diagnosis of recurrence.

OBJECTIVE

We aimed to demonstrate the usefulness of ctDNA and cell-free DNA (cfDNA) as a marker of complete cytoreduction and during follow-up in patients with advanced ovarian cancer.

MATERIAL AND METHODS

We selected 22 women diagnosed with advanced high-grade serous ovarian cancer, of which only 4 had complete records. We detected cfDNA by polymerase chain reaction (PCR), presented as ng/mL, and detected ctDNA with droplet digital PCR (ddPCR). We calculated Pearson correlation coefficients to evaluate correlations among cfDNA, ctDNA, and cancer antigen 125 (CA125), a biomarker.

RESULTS

The results obtained in the evaluation of cfDNA and ctDNA and their correlation with tumour markers and the radiology of patients with complete follow-up show disease progression during the disease, stable disease, or signs of recurrence. cfDNA and ctDNA correlated significantly with CA125. Following cfDNA and ctDNA over time indicated a recurrence several months earlier than computed tomography and CA125 changes.

CONCLUSION

An analysis of cfDNA and ctDNA offers a non-invasive clinical tool for monitoring the primary tumour to establish a complete cytoreduction and to diagnose recurrence early.

Latest Research Progress of Liquid Biopsy in Tumor-A Narrative Review

Human life expectancy is significantly impacted by cancer, with liquid biopsy emerging as an advantageous method for cancer detection because of its noninvasive nature, high accuracy, ease of sampling, and cost-effectiveness compared with conventional tissue biopsy techniques. Liquid biopsy shows promise in early cancer detection, real-time monitoring, and personalized treatment for various cancers, including lung, cervical, and prostate cancers, and offers innovative approaches for cancer diagnosis and management. By utilizing circulating tumor DNA, circulating tumor cells, and exosomes as biomarkers, liquid biopsy enables the tracking of cancer progression. Various techniques commonly used in life sciences research, such as polymerase chain reaction (PCR), next-generation sequencing (NGS), and droplet digital PCR, are employed to assess cancer progression on the basis of different indicators. This review examines the latest advancements in liquid biopsy markers-circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and exosomes-for cancer diagnosis over the past three years, with a focus on their detection methodologies and clinical applications. It encapsulates the pivotal aims of liquid biopsy, including early detection, therapy response prediction, treatment monitoring, prognostication, and its relevance in minimal residual disease, while also addressing the challenges facing routine clinical adoption. By combining the latest research advancements and practical clinical experiences, this work focuses on discussing the clinical significance of DNA methylation biomarkers and their applications in tumor screening, auxiliary diagnosis, companion diagnosis, and recurrence monitoring. These discussions may help enhance the application of liquid biopsy throughout the entire process of tumor diagnosis and treatment, thereby providing patients with more precise and effective treatment plans.

Circulating Liquid Biopsy Biomarkers in Glioblastoma: Advances and Challenges

Gliomas, particularly glioblastoma (GBM), represent the most prevalent and aggressive tumors of the central nervous system (CNS). Despite recent treatment advancements, patient survival rates remain low. The diagnosis of GBM traditionally relies on neuroimaging methods such as magnetic resonance imaging (MRI) or computed tomography (CT) scans and postoperative confirmation via histopathological and molecular analysis. Imaging techniques struggle to differentiate between tumor progression and treatment-related changes, leading to potential misinterpretation and treatment delays. Similarly, tissue biopsies, while informative, are invasive and not suitable for monitoring ongoing treatments. These challenges have led to the emergence of liquid biopsy, particularly through blood samples, as a promising alternative for GBM diagnosis and monitoring. Presently, blood and cerebrospinal fluid (CSF) sampling offers a minimally invasive means of obtaining tumor-related information to guide therapy. The idea that blood or any biofluid tests can be used to screen many cancer types has huge potential. Tumors release various components into the bloodstream or other biofluids, including cell-free nucleic acids such as microRNAs (miRNAs), circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), proteins, extracellular vesicles (EVs) or exosomes, metabolites, and other factors. These factors have been shown to cross the blood-brain barrier (BBB), presenting an opportunity for the minimally invasive monitoring of GBM as well as for the real-time assessment of distinct genetic, epigenetic, transcriptomic, proteomic, and metabolomic changes associated with brain tumors. Despite their potential, the clinical utility of liquid biopsy-based circulating biomarkers is somewhat constrained by limitations such as the absence of standardized methodologies for blood or CSF collection, analyte extraction, analysis methods, and small cohort sizes. Additionally, tissue biopsies offer more precise insights into tumor morphology and the microenvironment. Therefore, the objective of a liquid biopsy should be to complement and enhance the diagnostic accuracy and monitoring of GBM patients by providing additional information alongside traditional tissue biopsies. Moreover, utilizing a combination of diverse biomarker types may enhance clinical effectiveness compared to solely relying on one biomarker category, potentially improving diagnostic sensitivity and specificity and addressing some of the existing limitations associated with liquid biomarkers for GBM. This review presents an overview of the latest research on circulating biomarkers found in GBM blood or CSF samples, discusses their potential as diagnostic, predictive, and prognostic indicators, and discusses associated challenges and future perspectives.

Monitoring Hepatocellular Carcinoma Using Tumor Content in Circulating Cell-Free DNA

PURPOSE

The objective of the study was to evaluate the use of tumor content in circulating cell-free DNA (ccfDNA) for monitoring hepatocellular carcinoma (HCC) throughout its natural history.

EXPERIMENTAL DESIGN

We included 67 patients with hepatitis B virus-related HCC, of whom 17 had paired pre- and posttreatment samples, and 90 controls. Additionally, in a prospective cohort with hepatitis B virus surface antigen-positive participants recruited in 2012 and followed up biannually with blood sample collections until 2019, we included 270 repeated samples before diagnosis from 63 participants who later developed HCC (pre-HCC samples). Shallow whole-genome sequencing and the ichorCNA method were used to analyze genome-wide copy number and tumor content in ccfDNA.

RESULTS

High tumor content was associated with advanced tumor stage (P < 0.001) and poor survival after HCC diagnosis [HR = 12.35; 95% confidence interval (CI) = 1.413-107.9; P = 0.023]. Tumor content turned negative after surgery (P = 0.027), whereas it remained positive after transarterial chemoembolization treatment (P = 0.578). In non-HCC samples, the mean tumor content (±SD) was 0.011 (±0.007) and had a specificity of 97.8% (95% CI = 92.2%-99.7%). In pre-HCC samples, the tumor content increased from 0.014 at 4 years before diagnosis to 0.026 at 1 year before diagnosis. The sensitivity of tumor content in detecting HCC increased from 22.7% (95% CI = 11.5%-37.8%) within 1 year before diagnosis to 30.4% (95% CI = 13.2%-52.9%) at the Barcelona Clinic Liver Cancer (BCLC) stage 0/A, 81.8% (95% CI = 59.7%-94.8%) at stage B, and 95.5% (95% CI = 77.2%-99.9%) at stage C.

CONCLUSIONS

The tumor content in ccfDNA is correlated with tumor burden and may help in monitoring HCC 1 yearearlier than clinical diagnosis and in predicting patient prognosis.

In vitro size-selection of short circulating tumor DNA fragments from late-stage lung cancer patients enhance the detection of mutations and aneuploidies

Introduction

Recent studies have demonstrated differences between the fragment length profiles of cell-free DNA (cfDNA) from cancer patients and healthy individuals. This has led to the development of in vitro size-selection procedures which can isolate the short fragments that are enriched with mutated circulating tumor DNA (ctDNA). This has yet to be investigated in a large cohort of lung cancer patients.

Materials and methods

We used plasma samples from 35 stage III and IV lung cancer patients and performed targeted next-generation sequencing (NGS) and variant calling from cfDNA with and without size-selection of short fragments. We identified clonal hematopoiesis (CH) and germline mutations using targeted NGS on paired buffy coat (BC) samples. In addition, we performed a genome-wide copy-number alteration analysis on the cfDNA samples with and without size-selection.

Results

ctDNA containing tumor mutations had a different fragment length profile compared to cfDNA fragments with CH or germline mutations. In vitro size-selection resulted in a median 1.36-fold (interquartile range (IQR): 0.63 to 2.48) mutational allele fraction (MAF) enrichment of tumor mutations whereas CH/germline mutations had a median 0.95-fold (IQR: 0.62 to 1.05) MAF enrichment. Key oncogenic drivers, including KRAS and EGFR were more likely to have a MAF increase with size-selection. Size-selection also increased the number plasma aneuploidy positive samples from 8 of 35 to 20 of 35.

Conclusion

This study expands the knowledge regarding ctDNA fragmentation in lung cancer patients and we demonstrate that in vitro size-selection can increase MAF of tumor mutations and plasma aneuploidy calls. Size-selection could lead to increased sensitivity of ctDNA detection, which is crucial for clinical implementation of liquid biopsies. This study is the largest of its kind studying cfDNA samples from 35 lung cancer patients containing 109 mutations in total.

The yin and yang of chromosomal instability in prostate cancer

Metastatic prostate cancer remains an incurable lethal disease. Studies indicate that prostate cancer accumulates genomic changes during disease progression and displays the highest levels of chromosomal instability (CIN) across all types of metastatic tumours. CIN, which refers to ongoing chromosomal DNA gain or loss during mitosis, and derived aneuploidy, are known to be associated with increased tumour heterogeneity, metastasis and therapy resistance in many tumour types. Paradoxically, high CIN levels are also proposed to be detrimental to tumour cell survival, suggesting that cancer cells must develop adaptive mechanisms to ensure their survival. In the context of prostate cancer, studies indicate that CIN has a key role in disease progression and might also offer a therapeutic vulnerability that can be pharmacologically targeted. Thus, a comprehensive evaluation of the causes and consequences of CIN in prostate cancer, its contribution to aggressive advanced disease and a better understanding of the acquired CIN tolerance mechanisms can translate into new tumour classifications, biomarker development and therapeutic strategies.

Association of preoperative and postoperative circulating tumour DNA (ctDNA) with PIK3CA gene mutation with risk of recurrence in patients with non-metastatic breast cancer

BACKGROUND

Circulating tumour DNA (ctDNA), contains tumour-specific gene mutation in blood circulation and could aid in postoperative risk stratification of non-metastatic breast cancer. In this study, we investigated the feasibility of detecting PIK3CA gene mutations in ctDNA in the preoperative (preop) and postoperative period (postop), and its prognostic significance in patients with breast cancer.

METHODS

A cohort of patients with breast cancer undergoing curative surgery with available blood samples preoperatively and postoperatively (Post op) at either Post op time period; week 1-2, week 3-4 or weeks 5-12 were enrolled. PIK3CA gene mutations at exons 9 and 20 were detected in ctDNA with High resolution melting (HRM) PCR and Allele specific fluorescence probe-based PCR.

RESULTS

A total of 62 patients (age, median (IQR), 51.50 (45.0-65.0) years), with a median follow-up of 90 months (interquartile range (IQR),60-120 months) were enrolled. In total, 25 (40.3%) and 22 (35%) patients with breast cancer had detectable PIK3CA gene mutations in ctDNA in preoperative and postoperative period, respectively. PIK3CA gene mutations in ctDNA in postoperative period (hazard ratio (H.R: 18.05, p = 0.001) were a negative prognostic factor for recurrencefree survival (RFS) and overall survival (OS) (H.R: 11.9, p = 0.01) in patients with breast cancer. Subgroup analysis of ctDNA indicate that positive ctDNA in both preoperative/postoperative period and post op period only were found to have prognostic effect on RFS and OS (RFS; p < 0.0001, O·S; p = 0.0007). Moreover, ctDNA-based detection preceded clinical detection of recurrence in patients with an average lead time of 12 months (IQR:20-28.5 months) across all the breast cancer subtypes.

CONCLUSION

We highlighted the prognostic ability of ctDNA in patients with breast cancer in perioperative period. However, future prospective studies are needed to assess the utility of ctDNA in clinical practice.

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.

Genome-wide repeat landscapes in cancer and cell-free DNA

Genetic changes in repetitive sequences are a hallmark of cancer and other diseases, but characterizing these has been challenging using standard sequencing approaches. We developed a de novo kmer finding approach, called ARTEMIS (Analysis of RepeaT EleMents in dISease), to identify repeat elements from whole-genome sequencing. Using this method, we analyzed 1.2 billion kmers in 2837 tissue and plasma samples from 1975 patients, including those with lung, breast, colorectal, ovarian, liver, gastric, head and neck, bladder, cervical, thyroid, or prostate cancer. We identified tumor-specific changes in these patients in 1280 repeat element types from the LINE, SINE, LTR, transposable element, and human satellite families. These included changes to known repeats and 820 elements that were not previously known to be altered in human cancer. Repeat elements were enriched in regions of driver genes, and their representation was altered by structural changes and epigenetic states. Machine learning analyses of genome-wide repeat landscapes and fragmentation profiles in cfDNA detected patients with early-stage lung or liver cancer in cross-validated and externally validated cohorts. In addition, these repeat landscapes could be used to noninvasively identify the tissue of origin of tumors. These analyses reveal widespread changes in repeat landscapes of human cancers and provide an approach for their detection and characterization that could benefit early detection and disease monitoring of patients with cancer.

Biomarkers and computational models for predicting efficacy to tumor ICI immunotherapy

Numerous studies have shown that immune checkpoint inhibitor (ICI) immunotherapy has great potential as a cancer treatment, leading to significant clinical improvements in numerous cases. However, it benefits a minority of patients, underscoring the importance of discovering reliable biomarkers that can be used to screen for potential beneficiaries and ultimately reduce the risk of overtreatment. Our comprehensive review focuses on the latest advancements in predictive biomarkers for ICI therapy, particularly emphasizing those that enhance the efficacy of programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibitors and cytotoxic T-lymphocyte antigen-4 (CTLA-4) inhibitors immunotherapies. We explore biomarkers derived from various sources, including tumor cells, the tumor immune microenvironment (TIME), body fluids, gut microbes, and metabolites. Among them, tumor cells-derived biomarkers include tumor mutational burden (TMB) biomarker, tumor neoantigen burden (TNB) biomarker, microsatellite instability (MSI) biomarker, PD-L1 expression biomarker, mutated gene biomarkers in pathways, and epigenetic biomarkers. TIME-derived biomarkers include immune landscape of TIME biomarkers, inhibitory checkpoints biomarkers, and immune repertoire biomarkers. We also discuss various techniques used to detect and assess these biomarkers, detailing their respective datasets, strengths, weaknesses, and evaluative metrics. Furthermore, we present a comprehensive review of computer models for predicting the response to ICI therapy. The computer models include knowledge-based mechanistic models and data-based machine learning (ML) models. Among the knowledge-based mechanistic models are pharmacokinetic/pharmacodynamic (PK/PD) models, partial differential equation (PDE) models, signal networks-based models, quantitative systems pharmacology (QSP) models, and agent-based models (ABMs). ML models include linear regression models, logistic regression models, support vector machine (SVM)/random forest/extra trees/k-nearest neighbors (KNN) models, artificial neural network (ANN) and deep learning models. Additionally, there are hybrid models of systems biology and ML. We summarized the details of these models, outlining the datasets they utilize, their evaluation methods/metrics, and their respective strengths and limitations. By summarizing the major advances in the research on predictive biomarkers and computer models for the therapeutic effect and clinical utility of tumor ICI, we aim to assist researchers in choosing appropriate biomarkers or computer models for research exploration and help clinicians conduct precision medicine by selecting the best biomarkers.

Gene point mutation information translation and detection: Leveraging single base extension and CRISPR/Cas12a

Gene point mutations play a significant role in the development of cancer. Therefore, developing a sensitive, specific, and universally applicable method for detecting gene point mutation is crucial for clinical diagnosis, prognosis, and cancer treatment. Recently, gene point mutation detection methods based on CRISPR/Cas12a detection have emerged. However, existing methods generally lack universality and specificity. In this study, we have developed a CRISPR/Cas12a-based method that combines improved allele-specific polymerase chain reaction and single base extension to translate the point mutation information in the target dsDNA into length information in ssDNA activators to overcome the limitations associated with PAM sequences in the CRISPR/Cas12a system. Our method achieved a detection limit of 0.002% for clinically significant EGFR T790M mutation. The CRISPR/Cas12a system we constructed demonstrates high sensitivity, specificity, and universality in detecting gene point mutations, making it a promising tool for clinical cancer screening.

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.

Utility of metagenomic Next-Generation Sequencing for simultaneously detecting pathogens and neoplasms

Objectives

Clinicians often face the challenge of differentially diagnosing febrile patients who are suspected of infectious diseases, since the clinical manifestations of infection and cancer may overlap. A single test that can detect both pathogens and tumor could provide timely and accurate diagnostic clues to aid the treatment and management of these patients.

Methods

We enrolled eight patients to evaluate the utility of metagenomic Next-Generation Sequencing for simultaneously detecting pathogens and neoplasms using body fluids and tissue samples. Patients were selected by the following criteria: 1) Tumor was not considered upon hospitalization, but mNGS testing indicated neoplasm; 2) Tumor was not excluded, but microbial infection was primarily suspected according to initial clinical assessment.

Results

We detected potential pathogens in five patients, three of whom had progressed into critical infections. Moreover, abnormal chromosomal copy numbers were identified in all patients that indicated presence of neoplasms, which were pathologically confirmed.

Conclusions

Although copy number variations do not render a definitive cancer diagnosis, it can prompt clinicians to conduct more focused diagnostic testing for cancer, potentially saving time and cost. As a result, integrating copy number analysis with pathogen detection in mNGS may help establish rapid and accurate diagnosis for febrile patients.

Language model enables end-to-end accurate detection of cancer from cell-free DNA

We present a language model Affordable Cancer Interception and Diagnostics (ACID) that can achieve high classification performance in the diagnosis of cancer exclusively from using raw cfDNA sequencing reads. We formulate ACID as an autoregressive language model. ACID is pretrained with language sentences that are obtained from concatenation of raw sequencing reads and diagnostic labels. We benchmark ACID against three methods. On testing set subjected to whole-genome sequencing, ACID significantly outperforms the best benchmarked method in diagnosis of cancer [Area Under the Receiver Operating Curve (AUROC), 0.924 versus 0.853; P < 0.001] and detection of hepatocellular carcinoma (AUROC, 0.981 versus 0.917; P < 0.001). ACID can achieve high accuracy with just 10 000 reads per sample. Meanwhile, ACID achieves the best performance on testing sets that were subjected to bisulfite sequencing compared with benchmarked methods. In summary, we present an affordable, simple yet efficient end-to-end paradigm for cancer detection using raw cfDNA sequencing reads.

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.

A Practical Approach for Targeting Structural Variants Genome-wide in Plasma Cell-free DNA

Interrogating plasma cell-free DNA (cfDNA) to detect cancer offers promise; however, no current tests scan structural variants (SVs) throughout the genome. Here, we report a simple molecular workflow to enrich a tumorigenic SV (DNA palindromes/fold-back inversions) that often demarcates genomic amplification and its feasibility for cancer detection by combining low-throughput next-generation sequencing with automated machine learning (Genome-wide Analysis of Palindrome Formation, GAPF-seq). Tumor DNA signal manifested as skewed chromosomal distributions of high-coverage 1-kb bins (HCBs), differentiating 39 matched breast tumor DNA from normal DNA with an average AUC of 0.9819. In a proof-of-concept liquid biopsy study, cfDNA from 0.5 mL plasma from prostate cancer patients was sufficient for binary classification against matched buffy coat DNA with an average AUC of 0.965. HCBs on the X chromosome emerged as a determinant feature and were associated with AR amplification. GAPF-seq could generate unique cancer-specific SV profiles in an agnostic liquid biopsy setting.

Long-Read DNA and RNA Sequencing to Streamline Clinical Genetic Testing and Reduce Barriers to Comprehensive Genetic Testing

BACKGROUND

Obtaining a precise molecular diagnosis through clinical genetic testing provides information about disease prognosis or progression, allows accurate counseling about recurrence risk, and empowers individuals to benefit from precision therapies or take part in N-of-1 trials. Unfortunately, more than half of individuals with a suspected Mendelian condition remain undiagnosed after a comprehensive clinical evaluation, and the results of any individual clinical genetic test ordered during a typical evaluation may take weeks or months to return. Furthermore, commonly used technologies, such as short-read sequencing, are limited in the types of disease-causing variation they can identify. New technologies, such as long-read sequencing (LRS), are poised to solve these problems.

CONTENT

Recent technical advances have improved accuracy, increased throughput, and decreased the costs of commercially available LRS technologies. This has resolved many historical concerns about the use of LRS in the clinical environment and opened the door to widespread clinical adoption of LRS. Here, we review LRS technology, how it has been used in the research setting to clarify complex variants or identify disease-causing variation missed by prior clinical testing, and how it may be used clinically in the near future.

SUMMARY

LRS is unique in that, as a single data source, it has the potential to replace nearly every other clinical genetic test offered today. When analyzed in a stepwise fashion, LRS will simplify laboratory processes, reduce barriers to comprehensive genetic testing, increase the rate of genetic diagnoses, and shorten the amount of time required to make a molecular diagnosis.

Promising and Minimally Invasive Biomarkers: Targeting Melanoma

The therapeutic landscape of malignant melanoma has been radically reformed in recent years, with novel treatments emerging in both the field of cancer immunotherapy and signalling pathway inhibition. Large-scale tumour genomic characterization has accurately classified malignant melanoma into four different genomic subtypes so far. Despite this, only somatic mutations in BRAF oncogene, as assessed in tumour biopsies, has so far become a validated predictive biomarker of treatment with small molecule inhibitors. The biology of tumour evolution and heterogeneity has uncovered the current limitations associated with decoding genomic drivers based only on a single-site tumour biopsy. There is an urgent need to develop minimally invasive biomarkers that accurately reflect the real-time evolution of melanoma and that allow for streamlined collection, analysis, and interpretation. These will enable us to face challenges with tumour tissue attainment and process and will fulfil the vision of utilizing "liquid biopsy" to guide clinical decisions, in a manner akin to how it is used in the management of haematological malignancies. In this review, we will summarize the most recent published evidence on the role of minimally invasive biomarkers in melanoma, commenting on their future potential to lead to practice-changing discoveries.

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.

Liquid biopsy for early detection of lung cancer

Lung cancer is the leading cause of cancer-related mortality worldwide. Early cancer detection plays an important role in improving treatment success and patient prognosis. In the past decade, liquid biopsy became an important tool for cancer diagnosis, as well as for treatment selection and response monitoring. Liquid biopsy is a broad term that defines a non-invasive test done on a sample of blood or other body fluid to look for cancer cells or other analytes that can include DNA, RNA, or other molecules released by tumor cells. Liquid biopsies mainly include circulating tumor DNA, circulating RNA, microRNA, proteins, circulating tumor cells, exosomes, and tumor-educated platelets. This review summarizes the progress and clinical application potential of liquid biopsy for early detection of lung cancer.

Liquid biopsy: creating opportunities in brain space

In recent years, liquid biopsy has emerged as an alternative method to diagnose and monitor tumors. Compared to classical tissue biopsy procedures, liquid biopsy facilitates the repetitive collection of diverse cellular and acellular analytes from various biofluids in a non/minimally invasive manner. This strategy is of greater significance for high-grade brain malignancies such as glioblastoma as the quantity and accessibility of tumors are limited, and there are collateral risks of compromised life quality coupled with surgical interventions. Currently, blood and cerebrospinal fluid (CSF) are the most common biofluids used to collect circulating cells and biomolecules of tumor origin. These liquid biopsy analytes have created opportunities for real-time investigations of distinct genetic, epigenetic, transcriptomics, proteomics, and metabolomics alterations associated with brain tumors. This review describes different classes of liquid biopsy biomarkers present in the biofluids of brain tumor patients. Moreover, an overview of the liquid biopsy applications, challenges, recent technological advances, and clinical trials in the brain have also been provided.

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.

Copy number aberrations in circulating tumor DNA enables prognosis prediction and molecular characterization of breast cancer

BACKGROUND

Low-pass whole-genome sequencing (LP-WGS)-based circulating tumor DNA (ctDNA) analysis is a versatile tool for somatic copy number aberration (CNA) detection, and this study aims to explore its clinical implication in breast cancer.

METHODS

We analyzed LP-WGS ctDNA data from 207 metastatic breast cancer (MBC) patients to explore prognostic value of ctDNA CNA burden and validated it in 465 stage II-III triple-negative breast cancer (TNBC) patients who received neoadjuvant chemotherapy in phase III PEARLY trial (NCT02441933). The clinical implication of locus level LP-WGS ctDNA profiling was further evaluated.

RESULTS

We found that a high baseline ctDNA CNA burden predicts poor overall survival and progression-free survival of MBC patients. The post hoc analysis of the PEARLY trial showed that a high baseline ctDNA CNA burden predicted poor disease-free survival independent from pathologic complete response (pCR), validating its robust prognostic significance. The 24-month disease-free survival rate was 96.9% and 55.9% in [pCR(+) and low I-score] and [non-pCR and high I-score] patients, respectively. The locus-level ctDNA CNA profile classified MBC patients into 5 molecular clusters and revealed targetable oncogenic CNAs. LP-WGS ctDNA and in vitro analysis identified the BCL6 amplification as a resistance factor for CDK4/6 inhibitors. We estimated ctDNA-based homologous recombination deficiency status of patients by shallowHRD algorithm, which was highest in the TNBC and correlated with platinum-based chemotherapy response.

CONCLUSIONS

These results demonstrate LP-WGS ctDNA CNA analysis as an essential tool for prognosis prediction and molecular profiling. Particularly, ctDNA CNA burden can serve as a useful determinant for escalating or de-escalating (neo)adjuvant strategy in TNBC patients.

Cell-free DNA approaches for cancer early detection and interception

Rapid advancements in the area of early cancer detection have brought us closer to achieving the goals of finding cancer early enough to treat or cure it, while avoiding harms of overdiagnosis. We evaluate progress in the development of early cancer detection tests in the context of the current principles for cancer screening. We review cell-free DNA (cfDNA)-based approaches using mutations, methylation, or fragmentomes for early cancer detection. Lastly, we discuss the challenges in demonstrating clinical utility of these tests before integration into routine clinical care.

Genome-guided discovery of cancer therapeutic targets

The success of precision oncology-which aims to match the right therapies to the right patients based on molecular status-is predicated on a robust pipeline of molecular targets against which therapies can be developed. Recent advances in genomics and functional genetics have enabled the unbiased discovery of novel molecular targets at scale. We summarize the promise and challenges in integrating genomic and functional genetic landscapes of cancer to establish the next generation of cancer targets.

Utility of clinical metagenomics in diagnosing malignancies in a cohort of patients with Epstein-Barr virus positivity

Backgrounds

Differentiation between benign and malignant diseases in EBV-positive patients poses a significant challenge due to the lack of efficient diagnostic tools. Metagenomic Next-Generation Sequencing (mNGS) is commonly used to identify pathogens of patients with fevers of unknown-origin (FUO). Recent studies have extended the application of Next-Generation Sequencing (NGS) in identifying tumors in body fluids and cerebrospinal fluids. In light of these, we conducted this study to develop and apply metagenomic methods to validate their role in identifying EBV-associated malignant disease.

Methods

We enrolled 29 patients with positive EBV results in the cohort of FUO in the Department of Infectious Diseases of Huashan Hospital affiliated with Fudan University from 2018 to 2019. Upon enrollment, these patients were grouped for benign diseases, CAEBV, and malignant diseases according to their final diagnosis, and CNV analysis was retrospectively performed in 2022 using samples from 2018 to 2019.

Results

Among the 29 patients. 16 of them were diagnosed with benign diseases, 3 patients were diagnosed with CAEBV and 10 patients were with malignant diseases. 29 blood samples from 29 patients were tested for mNGS. Among all 10 patients with malignant diagnosis, CNV analysis suggested neoplasms in 9 patients. Of all 19 patients with benign or CAEBV diagnosis, 2 patients showed abnormal CNV results. The sensitivity and specificity of CNV analysis for the identification for tumors were 90% and 89.5%, separately.

Conclusions

The application of mNGS could assist in the identification of microbial infection and malignancies in EBV-related diseases. Our results demonstrate that CNV detection through mNGS is faster compared to conventional oncology tests. Moreover, the convenient collection of peripheral blood samples adds to the advantages of this approach.

Minimal residual disease in solid tumors: an overview

Minimal residual disease (MRD) is termed as the small numbers of remnant tumor cells in a subset of patients with tumors. Liquid biopsy is increasingly used for the detection of MRD, illustrating the potential of MRD detection to provide more accurate management for cancer patients. As new techniques and algorithms have enhanced the performance of MRD detection, the approach is becoming more widely and routinely used to predict the prognosis and monitor the relapse of cancer patients. In fact, MRD detection has been shown to achieve better performance than imaging methods. On this basis, rigorous investigation of MRD detection as an integral method for guiding clinical treatment has made important advances. This review summarizes the development of MRD biomarkers, techniques, and strategies for the detection of cancer, and emphasizes the application of MRD detection in solid tumors, particularly for the guidance of clinical treatment.

Circulating tumor cells and circulating tumor DNA in breast cancer diagnosis and monitoring

Liquid biopsy, including both circulating tumor cells and circulating tumor DNA, is becoming more popular as a diagnostic tool in the clinical management of breast cancer. Elevated concentrations of these biomarkers during cancer treatment may be used as markers for cancer progression as well as to understand the mechanisms underlying metastasis and treatment resistance. Thus, these circulating markers serve as tools for cancer assessing and monitoring through a simple, non-invasive blood draw. However, despite several study results currently noting a potential clinical impact of ctDNA mutation tracking, the method is not used clinically in cancer diagnosis among patients and more studies are required to confirm it. This review focuses on understanding circulating tumor biomarkers, especially in breast cancer.

Tumor-agnostic ctDNA levels by mFAST-SeqS in first-line HR-positive, HER2 negative metastatic breast cancer patients as a biomarker for survival

This prospective cohort study reports aneuploidy score by mFast-SeqS as a strong prognostic marker in MBC patients. mFAST-SeqS is an affordable and easily implementable method for the assessment of total ctDNA levels and, as such, provides an alternative prognostic tool. One mixed cohort (cohort A, n = 45) starting any type of treatment in any line of therapy and one larger cohort (cohort B, n = 129) consisting of patients starting aromatase inhibitors (AI) as first-line therapy were used. mFAST-SeqS was performed using plasma of blood in which CTCs (CellSearch) were enumerated. The resulting aneuploidy score was correlated with categorized CTC count and associated with outcome. The aneuploidy score was significantly correlated with CTC count, but discordance was observed in 31.6% when applying cut-offs of 5. In both cohorts, aneuploidy score was a significant prognostic marker for both PFS and OS. In the Cox regression models, the HR for aneuploidy score for PFS was 2.52 (95% CI: 1.56-4.07), and the HR for OS was 2.37 (95% CI: 1.36-4.14). Results presented here warrant further investigations into the clinical utility of this marker in MBC patients.

Validation of the Labcorp Plasma Focus Test to Facilitate Precision Oncology Through Cell-Free DNA Genomic Profiling of Solid Tumors

Genomic profiling is critical for precision oncology to guide treatment decisions. Liquid biopsy testing is a complementary approach to tissue testing, particularly when tissue is not readily available. The Labcorp Plasma Focus test is a circulating cell-free DNA genomic profiling test that identifies actionable variants in solid cancers, including non-small-cell lung, colorectal, melanoma, breast, esophageal, gastroesophageal junction, and gastric cancers. This study highlights the analytical validation of the test, including accuracy compared with orthogonal methods, as well as sensitivity, specificity, precision, reproducibility, and repeatability. Concordance with orthogonal methods showed percent positive agreement of 98.7%, 89.3%, and 96.2% for single nucleotide variants (SNVs), insertion/deletions (indels), and copy number amplifications (CNAs), respectively, and 100.0% for translocations and microsatellite instability (MSI). Analytical sensitivity revealed a median limit of detection of 0.7% and 0.6% for SNVs and indels, 1.4-fold for CNAs, 0.5% variant allele frequency for translocations, and 0.6% for MSI. Specificity was >99% for SNVs/indels and 100% for CNAs, translocations, and MSI. Average positive agreement from precision, reproducibility, and repeatability experiments was 97.5% and 88.9% for SNVs/indels and CNAs, and 100% for translocations and MSI. Taken together, these data show that the Labcorp Plasma Focus test is a highly accurate, sensitive, and specific approach for cell-free DNA genomic profiling to supplement tissue testing and inform treatment decisions.

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.

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.