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

Accelerating the Development and Validation of Liquid Biopsy for Early Cancer Screening and Treatment Tailoring

Liquid biopsy (LB) is a minimally invasive method which aims to detect circulating tumor-derived components in body fluids. It provides an alternative to current cancer screening methods that use tissue biopsies for the confirmation of diagnosis. This paper attempts to determine how far the regulatory, policy, and governance framework provide support to LB implementation into healthcare systems and how the situation can be improved. For that reason, the European Alliance for Personalised Medicine (EAPM) organized series of expert panels including different key stakeholders to identify different steps, challenges, and opportunities that need to be taken to effectively implement LB technology at the country level across Europe. To accomplish a change of patient care with an LB approach, it is required to establish collaboration between multiple stakeholders, including payers, policymakers, the medical and scientific community, and patient organizations, both at the national and international level. Regulators, pharma companies, and payers could have a major impact in their own domain. Linking national efforts to EU efforts and vice versa could help in implementation of LB across Europe, while patients, scientists, physicians, and kit manufacturers can generate a pull by undertaking more research into biomarkers.

Circulating Cell-Free DNA in Renal Cell Carcinoma: The New Era of Precision Medicine

Simple Summary

Early diagnosis of renal cell carcinoma (RCC) is challenging and typically incidental. Currently, several therapeutic strategies are used for the treatment; however, no established predictive biomarker has been established yet, and the optimal treatment choice and sequence of use remain unclear. Moreover, the recurrence occurs in about one-third of patients after tumor resection. Although several prognostic classification systems have been proposed, most of them showed only limited potential in recurrence prediction. Therefore, identifying simple, reliable, and easily accessible biomarkers to anticipate the diagnosis, effectively evaluate the risk of relapse, and predict the response to the therapeutic regimens is an unmet clinical need. Circulating cell-free DNA (cfDNA), released from cancer cells into the bloodstream, was shown to be a non-invasive, viable, inexpensive method to diagnose and monitor several solid malignancies, designed as a potential blood RCC biomarker. This review aims to summarize the state of the art of the current genetic and epigenetic techniques of plasma and serum cfDNA detection and outline the potential application of liquid biopsy in RCC.

Abstract

Tumor biopsy is still the gold standard for diagnosing and prognosis renal cell carcinoma (RCC). However, its invasiveness, costs, and inability to accurately picture tumor heterogeneity represent major limitations to this procedure. Analysis of circulating cell-free DNA (cfDNA) is a non-invasive cost-effective technique that has the potential to ease cancer detection and prognosis. In particular, a growing body of evidence suggests that cfDNA could be a complementary tool to identify and prognosticate RCC while providing contemporary mutational profiling of the tumor. Further, recent research highlighted the role of cfDNA methylation profiling as a novel method for cancer detection and tissue-origin identification. This review synthesizes current knowledge on the diagnostic, prognostic, and predictive applications of cfDNA in RCC, with a specific focus on the potential role of cell-free methylated DNA (cfMeDNA).

New Perspectives on the Importance of Cell-Free DNA Biology

Body fluids are constantly replenished with a population of genetically diverse cell-free DNA (cfDNA) fragments, representing a vast reservoir of information reflecting real-time changes in the host and metagenome. As many body fluids can be collected non-invasively in a one-off and serial fashion, this reservoir can be tapped to develop assays for the diagnosis, prognosis, and monitoring of wide-ranging pathologies, such as solid tumors, fetal genetic abnormalities, rejected organ transplants, infections, and potentially many others. The translation of cfDNA research into useful clinical tests is gaining momentum, with recent progress being driven by rapidly evolving preanalytical and analytical procedures, integrated bioinformatics, and machine learning algorithms. Yet, despite these spectacular advances, cfDNA remains a very challenging analyte due to its immense heterogeneity and fluctuation in vivo. It is increasingly recognized that high-fidelity reconstruction of the information stored in cfDNA, and in turn the development of tests that are fit for clinical roll-out, requires a much deeper understanding of both the physico-chemical features of cfDNA and the biological, physiological, lifestyle, and environmental factors that modulate it. This is a daunting task, but with significant upsides. In this review we showed how expanded knowledge on cfDNA biology and faithful reverse-engineering of cfDNA samples promises to (i) augment the sensitivity and specificity of existing cfDNA assays; (ii) expand the repertoire of disease-specific cfDNA markers, thereby leading to the development of increasingly powerful assays; (iii) reshape personal molecular medicine; and (iv) have an unprecedented impact on genetics research.

Considerations of biomarker application for cancer continuum in the era of precision medicine

Purpose of the review

The goal of this review is to highlight emerging biomarker research by the key phases of the cancer continuum and outline the methodological considerations for biomarker application.

Recent findings

While biomarkers have an established role in targeted therapy and to some extent, disease monitoring, their role in early detection and survivorship remains to be elucidated. With the advent of omics technology, the discovery of biomarkers has been accelerated exponentially, therefore careful consideration to ensure an unbiased study design and robust validity is crucial.

Summary

The rigor of biomarker research holds the key to the success of precision health care. The potential clinical utility and the feasibility of implementation should be central to future biomarker research study design.

The rising tide of cell-free DNA profiling: from snapshot to temporal genome analysis

Genomes of diverse origins are continuously shed into human body fluids in the form of fragmented cell-free DNA (cfDNA). These molecules maintain the genetic and epigenetic codes of their originating source, and often carry additional layers of unique information in newly discovered physico-chemical features. Characterization of cfDNA thus presents the opportunity to non-invasively reconstruct major parts of the host- and metagenome in silico. Data from a single specimen can be leveraged to detect a broad range of disease-specific signatures and has already enabled the development of many pioneering diagnostic tests. Moreover, data from serial sampling may allow unparalleled mapping of the scantily explored landscape of temporal genomic changes as it relates to various changes in different physiological and pathological states of individuals. In this review, we explore how this vast dimension of biological information accessible through cfDNA analysis is being tapped towards the development of increasingly powerful molecular assays and how it is shaping emerging technologies. We also discuss how this departure from traditional paradigms of snapshot genetic testing may pave the way for an onrush of new and exciting discoveries in human biology.

Early diagnosis of pancreatic cancer: What strategies to avoid a foretold catastrophe

While great strides in improving survival rates have been made for most cancers in recent years, pancreatic ductal adenocarcinoma (PDAC) remains one of the solid tumors with the worst prognosis. PDAC mortality often overlaps with incidence. Surgical resection is the only potentially curative treatment, but it can be performed in a very limited number of cases. In order to improve the prognosis of PDAC, there are ideally two possible ways: the discovery of new strategies or drugs that will make it possible to treat the tumor more successfully or an earlier diagnosis that will allow patients to be operated on at a less advanced stage. The aim of this review was to summarize all the possible strategies available today for the early diagnosis of PDAC and the paths that research needs to take to make this goal ever closer. All the most recent studies on risk factors and screening modalities, new laboratory tests including liquid biopsy, new imaging methods and possible applications of artificial intelligence and machine learning were reviewed and commented on. Unfortunately, in 2022 the results for this type of cancer still remain discouraging, while a catastrophic increase in cases is expected in the coming years. The article was also written with the aim of highlighting the urgency of devoting more attention and resources to this pathology in order to reach a solution that seems more and more unreachable every day.

Expanded knowledge of cell-free DNA biology: potential to broaden the clinical utility

Noninvasive sampling of an individual's body fluids is an easy means to capture circulating cell-free DNA (cfDNA). These small fragments of DNA carry information on the contributing cell's genome, epigenome, and nuclease content. Analysis of cfDNA for the assessment of genetic risk has already revolutionized clinical practice, and a compendium of increasingly higher-resolution approaches based on epigenetic and fragmentomic cfDNA signatures continues to expand. Profiling cfDNA has unlocked a wealth of molecular information that can be translated to the clinic. This review covers the biological characteristics of cfDNA, recent advances in liquid biopsy and the clinical utility of cfDNA.

Inherited genetics of adult diffuse glioma and polygenic risk scores-a review

Knowledge about inherited and acquired genetics of adult diffuse glioma has expanded significantly over the past decade. Genomewide association studies (GWAS) stratified by histologic subtype identified six germline variants that were associated specifically with glioblastoma (GBM) and 12 that were associated with lower grade glioma. A GWAS performed using the 2016 WHO criteria, stratifying patients by IDH mutation and 1p/19q codeletion (as well as TERT promoter mutation), discovered that many of the known variants are associated with specific WHO glioma subtypes. In addition, the GWAS stratified by molecular group identified two additional novel regions: variants in D2HGDH that were associated with tumors that had an IDH mutation and a variant near FAM20C that was associated with tumors that had both IDH mutation and 1p/19q codeletion. The results of these germline associations have been used to calculate polygenic risk scores, from which to estimate relative and absolute risk of overall glioma and risk of specific glioma subtypes. We will review the concept of polygenic risk models and their potential clinical utility, as well as discuss the published adult diffuse glioma polygenic risk models. To date, these prior genetic studies have been done on European populations. Using the published glioma polygenic risk model, we show that the genetic associations published to date do not generalize across genetic ancestries, demonstrating that genetic studies need to be done on more diverse populations.

Tracing the Origin of Cell-Free DNA Molecules through Tissue-Specific Epigenetic Signatures

All cell and tissue types constantly release DNA fragments into human body fluids by various mechanisms including programmed cell death, accidental cell degradation and active extrusion. Particularly, cell-free DNA (cfDNA) in plasma or serum has been utilized for minimally invasive molecular diagnostics. Disease onset or pathological conditions that lead to increased cell death alter the contribution of different tissues to the total pool of cfDNA. Because cfDNA molecules retain cell-type specific epigenetic features, it is possible to infer tissue-of-origin from epigenetic characteristics. Recent research efforts demonstrated that analysis of, e.g., methylation patterns, nucleosome occupancy, and fragmentomics determined the cell- or tissue-of-origin of individual cfDNA molecules. This novel tissue-of origin-analysis enables to estimate the contributions of different tissues to the total cfDNA pool in body fluids and find tissues with increased cell death (pathologic condition), expanding the portfolio of liquid biopsies towards a wide range of pathologies and early diagnosis. In this review, we summarize the currently available tissue-of-origin approaches and point out the next steps towards clinical implementation.

Urine Cellular DNA Point Mutation and Methylation for Identifying Upper Tract Urinary Carcinoma

Simple Summary

It’s difficult to detect upper tract urothelial carcinoma at early stage. Invasive testing may increase risk of cancer recurrences in the bladder after radical nephroureterectomy. Thus, in the present study, we incorporated two-gene mutation and methylation biomarkers to conduct the diagnostic tool of upper tract urothelial carcinoma and performed external validation to investigate the utility and stability of the optimal panel. It showed a highly specific and robust performance. It may be used as a replaceable approach for early detection of upper tract urothelial carcinoma, resulting in less extensive examinations in patients at low risk.

Abstract

Background: To improve the selection of patients for ureteroscopy, avoid excessive testing and reduce costs, we aimed to develop and validate a diagnostic urine assay for upper tract urinary carcinoma (UTUC). Methods: In this cohort study we recruited 402 patients from six Hunan hospitals who underwent ureteroscopy for hematuria, including 95 patients with UTUC and 307 patients with non-UTUC findings. Midstream morning urine samples were collected before ureteroscopy and surgery. DNA was extracted and qPCR was used to analyze mutations in TERT and FGFR3 and the methylation of NRN1. In the training set, the random forest algorithm was used to build an optimal panel. Lastly, the Beijing cohort (n = 76) was used to validate the panel. Results: The panel combining the methylation with mutation markers led to an AUC of 0.958 (95% CI: 0.933–0.975) with a sensitivity of 91.58% and a specificity of 94.79%. The panel presented a favorable diagnostic value for UTUC vs. other malignant tumors (AUC = 0.920) and UTUC vs. benign disease (AUC = 0.975). Furthermore, combining the panel with age revealed satisfactory results, with 93.68% sensitivity, 94.44% specificity, AUC = 0.970 and NPV = 98.6%. In the external validation process, the model showed an AUC of 0.971, a sensitivity of 95.83% and a specificity of 92.31, respectively. Conclusions: A novel diagnostic model for analyzing hematuria patients for the risk of UTUC was developed, which could lead to a reduction in the need for invasive examinations. Combining NRN1 methylation and gene mutation (FGFR3 and TERT) with age resulted in a validated accurate prediction model.

Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing

The Oxford Nanopore (ONT) platform provides portable and rapid genome sequencing, and its ability to natively profile DNA methylation without complex sample processing is attractive for point-of-care real-time sequencing. We recently demonstrated ONT shallow whole-genome sequencing to detect copy number alterations (CNAs) from the circulating tumor DNA (ctDNA) of cancer patients. Here, we show that cell type and cancer-specific methylation changes can also be detected, as well as cancer-associated fragmentation signatures. This feasibility study suggests that ONT shallow WGS could be a powerful tool for liquid biopsy.

Cancer type classification using plasma cell-free RNAs derived from human and microbes

The utility of cell-free nucleic acids in monitoring cancer has been recognized by both scientists and clinicians. In addition to human transcripts, a fraction of cell-free nucleic acids in human plasma were proven to be derived from microbes and reported to have relevance to cancer. To obtain a better understanding of plasma cell-free RNAs (cfRNAs) in cancer patients, we profiled cfRNAs in ~300 plasma samples of 5 cancer types (colorectal cancer, stomach cancer, liver cancer, lung cancer, and esophageal cancer) and healthy donors (HDs) with RNA-seq. Microbe-derived cfRNAs were consistently detected by different computational methods when potential contaminations were carefully filtered. Clinically relevant signals were identified from human and microbial reads, and enriched Kyoto Encyclopedia of Genes and Genomes pathways of downregulated human genes and higher prevalence torque teno viruses both suggest that a fraction of cancer patients were immunosuppressed. Our data support the diagnostic value of human and microbe-derived plasma cfRNAs for cancer detection, as an area under the ROC curve of approximately 0.9 for distinguishing cancer patients from HDs was achieved. Moreover, human and microbial cfRNAs both have cancer type specificity, and combining two types of features could distinguish tumors of five different primary locations with an average recall of 60.4%. Compared to using human features alone, adding microbial features improved the average recall by approximately 8%. In summary, this work provides evidence for the clinical relevance of human and microbe-derived plasma cfRNAs and their potential utilities in cancer detection as well as the determination of tumor sites.

DNA methylation fingerprint of hepatocellular carcinoma from tissue and liquid biopsies

Hepatocellular carcinoma (HCC) is amongst the cancers with highest mortality rates and is the most common malignancy of the liver. Early detection is vital to provide the best treatment possible and liquid biopsies combined with analysis of circulating tumour DNA methylation show great promise as a non-invasive approach for early cancer diagnosis and monitoring with low false negative rates. To identify reliable diagnostic biomarkers of early HCC, we performed a systematic analysis of multiple hepatocellular studies and datasets comprising > 1500 genome-wide DNA methylation arrays, to define a methylation signature predictive of HCC in both tissue and cell-free DNA liquid biopsy samples. Our machine learning pipeline identified differentially methylated regions in HCC, some associated with transcriptional repression of genes related with cancer progression, that benchmarked positively against independent methylation signatures. Combining our signature of 38 DNA methylation regions, we derived a HCC detection score which confirmed the utility of our approach by identifying in an independent dataset 96% of HCC tissue samples with a precision of 98%, and most importantly successfully separated cfDNA of tumour samples from healthy controls. Notably, our risk score could identify cell-free DNA samples from patients with other tumours, including colorectal cancer. Taken together, we propose a comprehensive HCC DNA methylation fingerprint and an associated risk score for detection of HCC from tissue and liquid biopsies.

Novel Markers for Liquid Biopsies in Cancer Management: Circulating Platelets and Extracellular Vesicles

Although radiologic imaging and histologic assessment of tumor tissues are classic approaches for diagnosis and monitoring of treatment response, they have many limitations. These include challenges in distinguishing benign from malignant masses, difficult access to the tumor, high cost of the procedures, and tumor heterogeneity. In this setting, liquid biopsy has emerged as a potential alternative for both diagnostic and monitoring purposes. The approaches to liquid biopsy include cell-free DNA/circulating tumor DNA, long and micro noncoding RNAs, proteins/peptides, carbohydrates/lectins, lipids, and metabolites. Other approaches include detection and analysis of circulating tumor cells, extracellular vesicles, and tumor-activated platelets. Ultimately, reliable use of liquid biopsies requires bioinformatics and statistical integration of multiple datasets to achieve approval in a Clinical Laboratory Improvement Amendments setting. This review provides a balanced and critical assessment of recent discoveries regarding tumor-derived biomarkers in liquid biopsies along with the potential and pitfalls for cancer detection and longitudinal monitoring.

Sensitive detection of stage I lung adenocarcinoma using plasma cell-free DNA breakpoint motif profiling

Background

Early diagnosis benefits lung cancer patients with higher survival, but most patients are diagnosed after metastasis. Although cell-free DNA (cfDNA) analysis holds promise, its sensitivity for detecting early-stage lung cancer is unsatisfying. We leveraged cfDNA fragmentomics to develop a predictive model for invasive stage I lung adenocarcinoma (LUAD).

Methods

292 stage I LUAD patients from three medical centers were included together with 230 healthy controls whose plasma cfDNA samples were profiled by whole-genome sequencing (WGS). Multiple cfDNA fragmentomic motif features and machine learning models were compared in the training cohort to select the best model. Model performance was assessed in the internal and external validation cohorts and an additional dataset.

Findings

A logistic regression model using the 6bp-breakpoint-motif feature was selected. It yielded 98·0% sensitivity and 94·7% specificity in the internal validation cohort [Area Under the Curve (AUC): 0·985], while 92·5% sensitivity and 90·0% specificity were achieved in the external validation cohort (AUC: 0·954). It is sensitive for early-stage (100% sensitivity for minimally invasive adenocarcinoma, MIA) and <1 cm (92·9%–97·7% sensitivity) tumors. The predictive power remained high when reducing sequencing depth to 0·5× (AUC: 0·977 and 0·931 for internal and external cohorts).

Interpretation

Here we have established a cfDNA breakpoint motif-based model for detecting early-stage LUAD, including MIA and very small-size tumors, shedding light on early cancer diagnosis in clinical practice.

Funding

National Key R&D Program of China; National Natural Science Foundation of China; CAMS Initiative for Innovative Medicine; Special Research Fund for Central Universities, Peking Union Medical College; Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences; Beijing Hope Run Special Fund of Cancer Foundation of China.

The applications of plasma cell-free DNA in cancer detection: Implications in the management of breast cancer patients

Liquid biopsy probes DNA, RNA, and proteins in body fluids for cancer detection and is one of the most rapidly developing areas in oncology. Tumor-derived DNA (circulating tumor DNA, ctDNA) in the context of cell-free DNA (cfDNA) in blood has been the main target for its potential utilities in cancer detection. Liquid biopsy can report tumor burden in real-time without invasive interventions, and would be feasible for screening tumor types that lack standard-of-care screening approaches. Two major approaches to interrogating ctDNA are genetic mutation and DNA methylation profiling. Mutation profiling can identify tumor driver mutations and guide precision therapy. Targeted genomic profiling of DNA methylation has become the main approach for cancer screening in the general population. Here we review the recent technological development and ongoing efforts in clinical applications. For clinical applications, we focus on breast cancer, in which subtype-specific biology demarcates the applications of ctDNA.

Clinical and Biological Aspects of Disseminated Tumor Cells and Dormancy in Breast Cancer

Progress in detection and treatment have drastically improved survival for early breast cancer patients. However, distant recurrence causes high mortality and is typically considered incurable. Cancer dissemination occurs via circulating tumor cells (CTCs) and up to 75% of breast cancer patients could harbor micrometastatses at time of diagnosis, while metastatic recurrence often occurs years to decades after treatment. During clinical latency, disseminated tumor cells (DTCs) can enter a state of cell cycle arrest or dormancy at distant sites, and are likely shielded from immune detection and treatment. While this is a challenge, it can also be seen as an outstanding opportunity to target dormant DTCs on time, before their transformation into lethal macrometastatic lesions. Here, we review and discuss progress made in our understanding of DTC and dormancy biology in breast cancer. Strides in our mechanistic insights of these features has led to the identification of possible targeting strategies, yet, their integration into clinical trial design is still uncertain. Incorporating minimally invasive liquid biopsies and rationally designed adjuvant therapies, targeting both proliferating and dormant tumor cells, may help to address current challenges and improve precision cancer care.

Pre-PCR Mutation-Enrichment Methods for Liquid Biopsy Applications

Liquid biopsy is having a remarkable impact on healthcare- and disease-management in the context of personalized medicine. Circulating free DNA (cfDNA) is one of the most instructive liquid-biopsy-based biomarkers and harbors valuable information for diagnostic, predictive, and prognostic purposes. When it comes to cancer, circulating DNA from the tumor (ctDNA) has a wide range of applications, from early cancer detection to the early detection of relapse or drug resistance, and the tracking of the dynamic genomic make-up of tumor cells. However, the detection of ctDNA remains technically challenging, due, in part, to the low frequency of ctDNA among excessive circulating cfDNA originating from normal tissues. During the past three decades, mutation-enrichment methods have emerged to boost sensitivity and enable facile detection of low-level mutations. Although most developed techniques apply mutation enrichment during or following initial PCR, there are a few techniques that allow mutation selection prior to PCR, which provides advantages. Pre-PCR enrichment techniques can be directly applied to genomic DNA and diminish the influence of PCR errors that can take place during amplification. Moreover, they have the capability for high multiplexity and can be followed by established mutation detection and enrichment technologies without changes to their established procedures. The first approaches for pre-PCR enrichment were developed by employing restriction endonucleases directly on genomic DNA in the early 1990s. However, newly developed pre-PCR enrichment methods provide higher sensitivity and versatility. This review describes the available pre-PCR enrichment methods and focuses on the most recently developed techniques (NaME-PrO, UVME, and DEASH/MAESTRO), emphasizing their applications in liquid biopsies.

Liquid biopsies to predict CDK4/6 inhibitor efficacy and resistance in breast cancer

Cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors combined with endocrine therapy have transformed the treatment of estrogen receptor-positive (ER+) and human epidermal growth factor receptor 2 negative (HER2-) metastatic breast cancer. However, some patients do not respond to this treatment, and patients inevitably develop resistance, such that novel biomarkers are needed to predict primary resistance, monitor treatment response for acquired resistance, and personalize treatment strategies. Circumventing the spatial and temporal limitations of tissue biopsy, newly developed liquid biopsy approaches have the potential to uncover biomarkers that can predict CDK4/6 inhibitor efficacy and resistance in breast cancer patients through a simple blood test. Studies on circulating tumor DNA (ctDNA)-based liquid biopsy biomarkers of CDK4/6 inhibitor resistance have focused primarily on genomic alterations and have failed thus far to identify clear and clinically validated predictive biomarkers, but emerging epigenetic ctDNA methodologies hold promise for further discovery. The present review outlines recent advances and future directions in ctDNA-based biomarkers of CDK4/6 inhibitor treatment response.

The Early Detection of Breast Cancer Using Liquid Biopsies: Model Estimates of the Benefits, Harms, and Costs

Simple Summary

Breast cancer screening is associated with benefits, such as mortality reduction and improved quality of life, and harms, such as false-positive results, overdiagnoses, and costs. Novel screen tests could be considered to reduce the harms and increase the benefits of screening. Liquid biopsies have been proposed as a novel method for the early detection of breast cancer. However, studies show that liquid biopsies based on cell-free DNA have a low sensitivity for early-stage breast cancer. Using the microsimulation model MISCAN-Fadia, we model the benefits, harms, and costs of the early detection of breast cancer using liquid biopsies for varying levels of liquid biopsy sensitivity and specificity. We found that liquid biopsies are unlikely to be an alternative to digital mammography, given the test performance based on a CCGA substudy. When liquid biopsies are unable to detect the precursor lesion of breast cancer—ductal carcinoma in situ (DCIS)—they need to be able to detect small, early-stage tumors, with high specificity, at low costs in order to be an alternative to digital mammography. We estimated a maximum liquid biopsy price of USD 187, which is substantially lower than currently listed prices.

Abstract

Breast cancer screening is associated with harms, such as false-positives and overdiagnoses, and, thus, novel screen tests can be considered. Liquid biopsies have been proposed as a novel method for the early detection of cancer, but low cell-free DNA tumor fraction might pose a problem for the use in population screening. Using breast cancer microsimulation model MISCAN-Fadia, we estimated the outcomes of using liquid biopsies in breast cancer screening in women aged 50 to 74 in the United States. For varying combinations of test sensitivity and specificity, we quantify the impact of the use of liquid biopsies on the harms and benefits of screening, and we estimate the maximum liquid biopsy price for cost-effective implementation in breast cancer screening at a cost-effectiveness threshold of USD 50,000. We investigate under what conditions liquid biopsies could be a suitable alternative to digital mammography and compare these conditions to a CCGA substudy. Outcomes were compared to digital mammography screening, and include mortality reduction, overdiagnoses, quality-adjusted life-years (QALYs), and the maximum price of a liquid biopsy for cost-effective implementation. When liquid biopsies are unable to detect DCIS, a large proportion of overdiagnosed cases is prevented but overall breast cancer mortality reduction and quality of life are lower, and costs are higher compared to digital mammography screening. Liquid biopsies prices should be restricted to USD 187 per liquid biopsy depending on test performance. Overall, liquid biopsies that are unable to detect ductal carcinoma in situ (DCIS) need to be able to detect small, early-stage tumors, with high specificity, at low costs in order to be an alternative to digital mammography. Liquid biopsies might be more suitable as an addition to digital mammography than as an alternative.

CancerNet: a unified deep learning network for pan-cancer diagnostics

Background

Despite remarkable advances in cancer research, cancer remains one of the leading causes of death worldwide. Early detection of cancer and localization of the tissue of its origin are key to effective treatment. Here, we leverage technological advances in machine learning or artificial intelligence to design a novel framework for cancer diagnostics. Our proposed framework detects cancers and their tissues of origin using a unified model of cancers encompassing 33 cancers represented in The Cancer Genome Atlas (TCGA). Our model exploits the learned features of different cancers reflected in the respective dysregulated epigenomes, which arise early in carcinogenesis and differ remarkably between different cancer types or subtypes, thus holding a great promise in early cancer detection.

Results

Our comprehensive assessment of the proposed model on the 33 different tissues of origin demonstrates its ability to detect and classify cancers to a high accuracy (> 99% overall F-measure). Furthermore, our model distinguishes cancers from pre-cancerous lesions to metastatic tumors and discriminates between hypomethylation changes due to age related epigenetic drift and true cancer.

Conclusions

Beyond detection of primary cancers, our proposed computational model also robustly detects tissues of origin of secondary cancers, including metastatic cancers, second primary cancers, and cancers of unknown primaries. Our assessment revealed the ability of this model to characterize pre-cancer samples, a significant step forward in early cancer detection. Deployed broadly this model can deliver accurate diagnosis for a greatly expanded target patient population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04783-y.

Current and Future Perspectives of Cell-Free DNA in Liquid Biopsy

A liquid biopsy is a minimally invasive or non-invasive method to analyze a range of tumor material in blood or other body fluids, including circulating tumor cells (CTCs), cell-free DNA (cfDNA), messenger RNA (mRNA), microRNA (miRNA), and exosomes, which is a very promising technology. Among these cancer biomarkers, plasma cfDNA is the most widely used in clinical practice. Compared with a tissue biopsy of traditional cancer diagnosis, in assessing tumor heterogeneity, a liquid biopsy is more reliable because all tumor sites release cfDNA into the blood. Therefore, a cfDNA liquid biopsy is less invasive and comprehensive. Moreover, the development of next-generation sequencing technology makes cfDNA sequencing more sensitive than a tissue biopsy, with higher clinical applicability and wider application. In this publication, we aim to review the latest perspectives of cfDNA liquid biopsy clinical significance and application in cancer diagnosis, treatment, and prognosis. We introduce the sequencing techniques and challenges of cfDNA detection, analysis, and clinical applications, and discuss future research directions.

Detection of ovarian cancer using plasma cell-free DNA methylomes

BACKGROUND

Ovarian cancer (OC) is a highly lethal gynecologic cancer, and it is hard to diagnose at an early stage. Clinically, there are no ovarian cancer-specific markers for early detection. Here, we demonstrate the use of cell-free DNA (cfDNA) methylomes to detect ovarian cancer, especially the early-stage OC.

EXPERIMENTAL DESIGN

Plasma from 74 epithelial ovarian cancer patients, 86 healthy volunteers, and 20 patients with benign pelvic masses was collected. The cfDNA methylomes of these samples were generated by cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq). The differentially methylated regions (DMRs) were identified by the contrasts between tumor and non-tumor groups, and the discrimination performance was evaluated with the iterative training and testing method.

RESULTS

The DMRs identified for cfDNA methylomes can well discriminate tumor groups and non-tumor groups (ROC values from 0.86 to 0.98). The late-stage top 300 DMRs are more late-stage-specific and failed to detect early-stage OC. However, the early-stage markers have the potential to discriminate all-stage OCs from non-tumor samples.

CONCLUSIONS

This study demonstrates that cfDNA methylomes generated with cfMeDIP-seq could be used to identify OC-specific biomarkers for OC, especially early OC detection. To detect early-stage OC, the biomarkers should be directly identified from early OC plasma samples rather than mix-stage ones. Further exploration of DMRs from a k larger early-stage OC cohort is warranted.

Global DNA hypomethylation of colorectal tumours detected in tissue and liquid biopsies may be related to decreased methyl-donor content

BACKGROUND

Hypomethylation of long interspersed nuclear element 1 (LINE-1) is characteristic of various cancer types, including colorectal cancer (CRC). Malfunction of several factors or alteration of methyl-donor molecules' (folic acid and S-adenosylmethionine) availability can contribute to DNA methylation changes. Detection of epigenetic alterations in liquid biopsies can assist in the early recognition of CRC. Following the investigations of a Hungarian colon tissue sample set, our goal was to examine the LINE-1 methylation of blood samples along the colorectal adenoma-carcinoma sequence and in inflammatory bowel disease. Moreover, we aimed to explore the possible underlying mechanisms of global DNA hypomethylation formation on a multi-level aspect.

METHODS

LINE-1 methylation of colon tissue (n = 183) and plasma (n = 48) samples of healthy controls and patients with colorectal tumours were examined with bisulfite pyrosequencing. To investigate mRNA expression, microarray analysis results were reanalysed in silico (n = 60). Immunohistochemistry staining was used to validate DNA methyltransferases (DNMTs) and folate receptor beta (FOLR2) expression along with the determination of methyl-donor molecules' in situ level (n = 40).

RESULTS

Significantly decreased LINE-1 methylation level was observed in line with cancer progression both in tissue (adenoma: 72.7 ± 4.8%, and CRC: 69.7 ± 7.6% vs. normal: 77.5 ± 1.7%, p ≤ 0.01) and liquid biopsies (adenoma: 80.0 ± 1.7%, and CRC: 79.8 ± 1.3% vs. normal: 82.0 ± 2.0%, p ≤ 0.01). However, no significant changes were recognized in inflammatory bowel disease cases. According to in silico analysis of microarray data, altered mRNA levels of several DNA methylation-related enzymes were detected in tumours vs. healthy biopsies, namely one-carbon metabolism-related genes-which met our analysing criteria-showed upregulation, while FOLR2 was downregulated. Using immunohistochemistry, DNMTs, and FOLR2 expression were confirmed. Moreover, significantly diminished folic acid and S-adenosylmethionine levels were observed in parallel with decreasing 5-methylcytosine staining in tumours compared to normal adjacent to tumour tissues (p ≤ 0.05).

CONCLUSION

Our results suggest that LINE-1 hypomethylation may have a distinguishing value in precancerous stages compared to healthy samples in liquid biopsies. Furthermore, the reduction of global DNA methylation level could be linked to reduced methyl-donor availability with the contribution of decreased FOLR2 expression.

Cell-Free DNA in Dermatology Research

In various diseases, particularly cancer, cell-free DNA (cfDNA) has been widely studied as a marker of disease prognosis or to facilitate the detection of therapeutic targets. In dermatology, most studies have focused on melanoma; other skin diseases such as vascular malformations and psoriasis have also been examined. Genetic alterations unique to the tissue of origin such as sequence variations, copy number alterations, chromosomal rearrangements, differential DNA methylation patterns, and fragmentation patterns can be identified in circulation providing information on patient disease status. These alterations can be detected either by PCR-based methods or next-generation sequencing depending on the target of interest. In this article, we discuss the origins of cfDNA, the most common methods of detection, current studies assessing cfDNA as a biomarker, and cfDNA's potential clinical applications in melanoma and other skin diseases. In addition, we provide important factors to consider during blood processing and DNA extraction as well as limitations for each assay.

Development of an automated liquid biopsy assay for methylated markers in advanced breast cancer

Current molecular liquid biopsy assays to detect recurrence or monitor response to treatment require sophisticated technology, highly trained personnel, and a turnaround time of weeks. We describe the development and technical validation of an automated Liquid Biopsy for Breast Cancer Methylation (LBx-BCM) prototype, a DNA methylation detection cartridge assay that is simple to perform and quantitatively detects nine methylated markers within 4.5 h. LBx-BCM demonstrated high interassay reproducibility when analyzing exogenous methylated DNA (75-300 DNA copies) spiked into plasma (Coefficient of Variation, CV = 7.1 - 10.9%) and serum (CV = 19.1 - 36.1%). It also demonstrated high interuser reproducibility (Spearman r = 0.887, P < 0.0001) when samples of metastatic breast cancer (MBC, N = 11) and normal control (N = 4) were evaluated independently by two users. Analyses of interplatform reproducibility indicated very high concordance between LBx-BCM and the reference assay, cMethDNA, among 66 paired plasma samples (MBC N = 40, controls N = 26; Spearman r = 0.891; 95% CI = 0.825 - 0.933, P< 0.0001). LBx-BCM achieved a ROC AUC = 0.909 (95% CI = 0.836 - 0.982), 83% sensitivity and 92% specificity; cMethDNA achieved a ROC AUC = 0.896 (95% CI = 0.817 - 0.974), 83% sensitivity and 92% specificity in test set samples. The automated LBx-BCM cartridge prototype is fast, with performance levels equivalent to the highly sensitive, manual cMethDNA method. Future prospective clinical studies will evaluate LBx-BCM detection sensitivity and its ability to monitor therapeutic response during treatment for advanced breast cancer.

DNA methylation-based predictors of health: applications and statistical considerations

DNA methylation data have become a valuable source of information for biomarker development, because, unlike static genetic risk estimates, DNA methylation varies dynamically in relation to diverse exogenous and endogenous factors, including environmental risk factors and complex disease pathology. Reliable methods for genome-wide measurement at scale have led to the proliferation of epigenome-wide association studies and subsequently to the development of DNA methylation-based predictors across a wide range of health-related applications, from the identification of risk factors or exposures, such as age and smoking, to early detection of disease or progression in cancer, cardiovascular and neurological disease. This Review evaluates the progress of existing DNA methylation-based predictors, including the contribution of machine learning techniques, and assesses the uptake of key statistical best practices needed to ensure their reliable performance, such as data-driven feature selection, elimination of data leakage in performance estimates and use of generalizable, adequately powered training samples.

Insight of pancreatic cancer: recommendations for improving its therapeutic efficacy in the next decade

Pancreatic cancer is one of the most malignant digestive system tumors. The effectiveness of pancreatic cancer treatment is still dismal, and the 5-year survival rate is only about 10%. Further improving the diagnosis and treatment of pancreatic cancer is the top priority of oncology research and clinical practice. Based on the existing clinical and scientific research experience, the review provides insight into the hotspots and future directions for pancreatic cancer, which focuses on early detection, early diagnosis, molecular typing and precise treatment, new drug development and regimen combination, immunotherapy, database development, model establishment, surgical technology and strategy change, as well as innovation of traditional Chinese medicine and breakthrough of treatment concept.

Circulating tumour DNA: a challenging innovation to develop "precision onco-surgery" in pancreatic adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is predicted to become the third leading cause of cancer-related mortality within the next decade. Management of PDAC remains challenging with limited effective treatment options and a dismal long-term prognosis. Liquid biopsy and circulating biomarkers seem to be promising to improve the multidisciplinary approach in PDAC treatment. Circulating tumour DNA (ctDNA) is the most studied blood liquid biopsy analyte and can provide insight into the molecular profile and individual characteristics of the tumour in real-time and in advance of standard imaging modalities. This could pave the way for identifying new therapeutic targets and markers of tumour response to supplement diagnostic and provide enhanced stratified treatment. Although its specificity seems excellent, the current sensitivity of ctDNA remains a limitation for clinical use, especially in patients with a low tumour burden. Increasing evidence suggests that ctDNA is a pertinent candidate biomarker to assess minimal residual disease after surgery but also a strong independent prognostic biomarker. This review explores the current knowledge and recent developments in ctDNA as a screening, diagnostic, prognostic and predictive biomarker in the management of resectable PDAC but also technical and analytical challenges that must be overcome to move toward "precision onco-surgery."

Preoperative Diagnosis and Molecular Characterization of Gliomas With Liquid Biopsy and Radiogenomics

Gliomas are a heterogenous group of central nervous system tumors with different outcomes and different therapeutic needs. Glioblastoma, the most common subtype in adults, has a very poor prognosis and disabling consequences. The World Health Organization (WHO) classification specifies that the typing and grading of gliomas should include molecular markers. The molecular characterization of gliomas has implications for prognosis, treatment planning, and prediction of treatment response. At present, gliomas are diagnosed via tumor resection or biopsy, which are always invasive and frequently risky methods. In recent years, however, substantial advances have been made in developing different methods for the molecular characterization of tumors through the analysis of products shed in body fluids. Known as liquid biopsies, these analyses can potentially provide diagnostic and prognostic information, guidance on choice of treatment, and real-time information on tumor status. In addition, magnetic resonance imaging (MRI) is another good source of tumor data; radiomics and radiogenomics can link the imaging phenotypes to gene expression patterns and provide insights to tumor biology and underlying molecular signatures. Machine and deep learning and computational techniques can also use quantitative imaging features to non-invasively detect genetic mutations. The key molecular information obtained with liquid biopsies and radiogenomics can be useful not only in the diagnosis of gliomas but can also help predict response to specific treatments and provide guidelines for personalized medicine. In this article, we review the available data on the molecular characterization of gliomas using the non-invasive methods of liquid biopsy and MRI and suggest that these tools could be used in the future for the preoperative diagnosis of gliomas.

The utility of cfDNA in TGCT patient management: a systematic review

Background:

Testicular germ cell tumors (TGCTs) are the most common young male malignancy with a steadily rising incidence. Standard clinical practice is radical orchidectomy of suspicious lumps followed by histopathological diagnosis and tumor subtyping. This practice can lead to complications and quality of life issues for the patients. Liquid biopsies, especially cell-free DNA (cfDNA), promised to be true surrogates for tissue biopsies, which are considered dangerous to perform in cases of testicular tumors. In this study, we have performed a systematic review on the potential of cfDNA in TGCT patient management, its potential challenges in translation to clinical application and possible approaches in further research.

Materials & Methods:

The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines on EuropePMC and PUBMED electronic databases, with the last update being on October 21, 2021. Due to the high heterogeneity in identified research articles, we have performed an overview of their efficacy.

Results:

Eight original articles have been identified on cfDNA in TGCT patients published from 2004 to 2021, of which six had more than one TGCT patient enrolled and were included in the final analysis. Three studies investigated cfDNA methylation, one has investigated mutations in cfDNA, two have investigated cfDNA amount, and one has investigated cfDNA integrity in TGCT. The sensitivity of cfDNA for TGCT was found to be higher than in serum tumor markers and lower than miR-371a-3p, with comparable specificity. cfDNA methylation analysis has managed to accurately detect teratoma in TGCT patients.

Conclusion:

Potential challenges in cfDNA application to TGCT patient management were identified. The challenges relating to the biology of TGCT with its low mutational burden and low cfDNA amounts in blood plasma make next-generation sequencing (NGS) methods especially challenging. We have also proposed possible approaches to help find clinical application, including a focus on cfDNA methylation analysis, and potentially solving the challenge of teratoma detection.

A novel and sensitive DNA methylation marker for the urine-based liquid biopsies to detect bladder cancer

Background

Better prognostic outcome is closely correlated with early detection of bladder cancer. Current non-invasive urianalysis relies on simultaneously testing multiple methylation markers to achieve relatively high accuracy. Therefore, we have developed an easy-to-use, convenient, and accurate single-target urine-based DNA methylation test for the malignancy.

Methods

By analyzing TCGA data, 344 candidate markers with 424 primer pairs and probe sets synthesized were systematically screened in cancer cell lines, paired tissue specimens, and urine sediments from bladder cancer patients and normal controls. The identified marker was further validated in large case-control cohorts. Wilcoxon rank sum tests and c2 tests were performed to compare methylation levels between case-control groups and correlate methylation levels with demographic and clinical characteristics. In addition, MSP, qMSP, RT-PCR, western blot analysis, and immunohistochemistry were performed to measure levels of DNA methylation, mRNA transcription, and protein expression in cancer cell lines and tissues.

Results

A top-performing DMRTA2 marker identified was tested in both discovery and validation sets, showing similar sensitivity and specificity for bladder cancer detection. Overall sensitivity in the aggregate set was 82.9%(179/216). The specificity, from a control group consisting of patients with lithangiuria, prostatoplasia, and prostatitis, is 92.5%(468/506). Notably, the methylation assay had the highest sensitivities for tumors at stages of T1(90.4%) and T2(95.0%) compared with Ta (63.0%), T3(81.8%), and T4(81.8%). Furthermore, the test showed admirable detection rate of 80.0%(24/30) for recurring cancers. While methylation was observed in 39/54(72.2%) urine samples from patients with carcinomas of renal pelvis and ureter, it was detected at extremely low rate of 6.0%(8/133) in kidney and prostate cancers. Compared with SV-HUC-1, the normal bladder epithelial cell line, DMRTA2 was hypermethylated in 8/9 bladder cancer cell lines, consistent with the results of MSP and qMSP, but not correlated with mRNA and protein expression levels in these cell lines. Similarly, DMRTA2 immunostaining was moderate in some tissues but weak in others. Further studies are needed to address functional implications of DMRTA2 hypermethylation.

Conclusions

Our data demonstrated that a single-target DNA methylation signature, mDMRTA2, could be highly effective to detect both primary and recurring bladder cancer via urine samples.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09616-y.

Pan-cancer methylome analysis for cancer diagnosis and classification of cancer cell of origin

The accurate and early diagnosis and classification of cancer origin from either tissue or liquid biopsy is crucial for selecting the appropriate treatment and reducing cancer-related mortality. Here, we established the CAncer Cell-of-Origin (CACO) methylation panel using the methylation data of the 28 types of cancer in The Cancer Genome Atlas (7950 patients and 707 normal controls) as well as healthy whole blood samples (95 subjects). We showed that the CACO methylation panel had high diagnostic potential with high sensitivity and specificity in the discovery (maximum AUC = 0.998) and validation (maximum AUC = 1.000) cohorts. Moreover, we confirmed that the CACO methylation panel could identify the cancer cell type of origin using the methylation profile from liquid as well as tissue biopsy, including primary, metastatic, and multiregional cancer samples and cancer of unknown primary, independent of the methylation analysis platform and specimen preparation method. Together, the CACO methylation panel can be a powerful tool for the classification and diagnosis of cancer.

Start of an era: circulating cell-free DNA for early detection of cancers

Effective screening modalities are currently available for only a small subset of cancers, and they generally have suboptimal performance with complicated procedures. Therefore, there is an urgent need to develop simple, accurate, and non-invasive methods for early detection of cancers. Genetic and epigenetic alterations in plasma circulating cell-free DNA (cfDNA) have shown the potential to revolutionize methods of early detection of cancers and facilitate subsequent diagnosis to improve survival of patients. The medical interest in cfDNA assays has been inspired by emerging single- and multi-early detection of cancers studies. This review summarizes current technological and clinical advances, in the hopes of providing insights into the development and applications of cfDNA assays in various cancers and clinical scenarios. The key phases of clinical development of biomarkers are highlighted, and the future developments of cfDNA-based liquid biopsies in early detection of cancers are outlined. It is hoped that this study can boost the potential integration of cfDNA-based early detection of cancers into the current clinical workflow.

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Liquid biopsy, characterized by minimal invasiveness and user friendliness, can identify multiple cancers at the early stage and localize the tissue of origin

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The state-of-the-art technology facilitates the application of circulating cell-free DNA (cfDNA) assays in the early detection of cancers

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cfDNA assays are expected to be integrated into the clinical workflow after technological refinement and clinical trial validation

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The development and application strategies of cfDNA assays in various cancers and clinical scenarios can vary, and the harm-and-benefit should be balanced carefully

Identification of tissue of origin in cancer of unknown primary using a targeted bisulfite sequencing panel

Aim: To construct a targeted bisulfite sequencing panel predicting origin of cancer of unknown primary. Methods: A bisulfite sequencing panel targeting 2793 tissue-specific markers was performed in 100 clinical samples. Results: The authors' prediction model showed 0.85 accuracy for the 'first-ranked' tissue type and 0.93 accuracy for the 'second-ranked' tissue type using 2793 tissue-specific markers and 0.84 accuracy for the 'first-ranked' tissue type and 0.92 accuracy for the 'second-ranked' tissue type when the number of tissue-specific markers was reduced to 514. Conclusion: Targeted bisulfite sequencing is a useful method for predicting the tissue of origin in patients with cancer of unknown primary.

Circulating Tumor DNA: An Emerging Tool in Gastrointestinal Cancers

Circulating tumor DNA (ctDNA) is tumor-derived fragmented DNA in the bloodstream that has come from primary or metastatic cancer sites. Neoplasm-specific genetic and epigenetic abnormalities are increasingly being identified through liquid biopsy: a novel, minimally invasive technique used to isolate and analyze ctDNA in the peripheral circulation. Liquid biopsy and other emerging ctDNA technologies represent a paradigm shift in cancer diagnostics because they allow for the detection of minimal residual disease in patients with early-stage disease, improve risk stratification, capture tumor heterogeneity and genomic evolution, and enhance ctDNA-guided adjuvant and palliative cancer therapy. Moreover, ctDNA can be used to monitor the tumor response to neoadjuvant and postoperative therapy in patients with metastatic disease. Using clearance of ctDNA as an endpoint for escalation/de-escalation of adjuvant chemotherapy for patients considered to have high-risk disease has become an important area of research. The possibility of using ctDNA as a surrogate for treatment response-including for overall survival, progression-free survival, and disease-free survival-is an attractive concept; this surrogate will arguably reduce study duration and expedite the development of new therapies. In this review, we summarize the current evidence on the applications of ctDNA for the diagnosis and management of gastrointestinal tumors. Gastrointestinal cancers-including tumors of the esophagus, stomach, colon, liver, and pancreas-account for one-quarter of global cancer diagnoses and contribute to more than one-third of cancer-related deaths. Given the prevalence of gastrointestinal malignancies, ctDNA technology represents a powerful tool to reduce the global burden of disease.

Plasma cell-free RNA profiling distinguishes cancers from pre-malignant conditions in solid and hematologic malignancies

Cell-free RNA (cfRNA) in plasma reflects phenotypic alterations of both localized sites of cancer and the systemic host response. Here we report that cfRNA sequencing enables the discovery of messenger RNA (mRNA) biomarkers in plasma with the tissue of origin-specific to cancer types and precancerous conditions in both solid and hematologic malignancies. To explore the diagnostic potential of total cfRNA from blood, we sequenced plasma samples of eight hepatocellular carcinoma (HCC) and ten multiple myeloma (MM) patients, 12 patients of their respective precancerous conditions, and 20 non-cancer (NC) donors. We identified distinct gene sets and built classification models using Random Forest and linear discriminant analysis algorithms that could distinguish cancer patients from premalignant conditions and NC individuals with high accuracy. Plasma cfRNA biomarkers of HCC are liver-specific genes and biomarkers of MM are highly expressed in the bone marrow compared to other tissues and are related to cell cycle processes. The cfRNA level of these biomarkers displayed a gradual transition from noncancerous states through precancerous conditions and cancer. Sequencing data were cross-validated by quantitative reverse transcription PCR and cfRNA biomarkers were validated in an independent sample set (20 HCC, 9 MM, and 10 NC) with AUC greater than 0.86. cfRNA results observed in precancerous conditions require further validation. This work demonstrates a proof of principle for using mRNA transcripts in plasma with a small panel of genes to distinguish between cancers, noncancerous states, and precancerous conditions.

Ultrasensitive DNA Methylation Ratio Detection Based on the Target-Induced Nanoparticle-Coupling and Site-Specific Base Oxidation Damage for Colorectal Cancer

DNA methylation analysis holds great promise in the whole process management of cancer early screening, diagnosis, and prognosis monitoring. Nevertheless, accurate detection of target methylated DNA, especially its methylation ratio in the genome, remains challenging. Herein, we report for the first time an integrated strategy of target-induced nanoparticle-coupling and site-specific base oxidation damage for DNA methylation analysis with the assistance of well-designed nanosensors. The ultrahigh sensitivity for detecting target methylated DNA as low as 32 × 10^-17 M and high specificity for distinguishing 0.001% methylation ratio are achieved by this proposed strategy without amplification operations. Notably, the precise quantification of target DNA methylation ratio has been achieved for the first time. Through quantitative detection of target methylated DNA and methylation ratio, this proposed strategy could reliably diagnose and monitor cancer progression and treatment responses for colorectal cancer, which is superior to the clinical Septin 9 kit. It is anticipated that the proposed strategy has attractive application prospects in early diagnosis and monitoring for colorectal cancer and other various diseases.

Probabilistic modeling methods for cell-free DNA methylation based cancer classification

Background

cfMeDIP-seq is a low-cost method for determining the DNA methylation status of cell-free DNA and it has been successfully combined with statistical methods for accurate cancer diagnostics. We investigate the diagnostic classification aspect by applying statistical tests and dimension reduction techniques for feature selection and probabilistic modeling for the cancer type classification, and we also study the effect of sequencing depth.

Methods

We experiment with a variety of statistical methods that use different feature selection and feature extraction methods as well as probabilistic classifiers for diagnostic decision making. We test the (moderated) t-tests and the Fisher’s exact test for feature selection, principal component analysis (PCA) as well as iterative supervised PCA (ISPCA) for feature generation, and GLMnet and logistic regression methods with sparsity promoting priors for classification. Probabilistic programming language Stan is used to implement Bayesian inference for the probabilistic models.

Results and conclusions

We compare overlaps of differentially methylated genomic regions as chosen by different feature selection methods, and evaluate probabilistic classifiers by evaluating the area under the receiver operating characteristic scores on discovery and validation cohorts. While we observe that many methods perform equally well as, and occasionally considerably better than, GLMnet that was originally proposed for cfMeDIP-seq based cancer classification, we also observed that performance of different methods vary across sequencing depths, cancer types and study cohorts. Overall, methods that seem robust and promising include Fisher’s exact test and ISPCA for feature selection as well as a simple logistic regression model with the number of hyper and hypo-methylated regions as features.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04651-9.

Bioinformatics analysis methods for cell-free DNA

As a kind of novel non-invasive marker for molecular detection, cell-free DNA (cfDNA) has potential value for the early diagnosis of diseases, prognosis assessment, and efficacy monitoring. The constant developments in molecular biology detection technologies have led to an increase in clinical studies on the use of cfDNA detection methods for patients, and many gratifying outcomes have been achieved. In this review, the contributions of bioinformatics tools to the study of cfDNA are well discussed. The focus of the review is on cfDNA identification signals, cfDNA identification methods, and the relationship of cfDNA with human diseases such as hepatic cancer, lung cancer, end-stage kidney disease, and ischemic stroke. The research significance and existing problems of using cfDNA as a biomarker for diseases are also discussed.

Circulating tumor DNA (ctDNA) in adjuvant therapy of early stage colon cancer: current status and future perspectives

BACKGROUND

This article reviews the current knowledge on circulating tumor DNA (ctDNA) in early stage colon cancer and ongoing trials on ctDNA-guided treatment in the adjuvant setting.

METHODS

A literature search of Pubmed was performed to identify studies on ctDNA in early stage colon cancer and neoadjuvant or adjuvant treatment. For ongoing trials, we searched clinicaltrials.gov and the Australian New Zealand Clinical Trials Registry (ANZCTR).

RESULTS

Several studies show that ctDNA is a strong predictor for recurrence and survival after surgery and adjuvant chemotherapy. The specificity of this marker is extremely high, and the sensitivity is increasing with the development of technology. Recurrences can be detected very early and the analysis can potentially be used to guide neoadjuvant and adjuvant treatment. Ongoing and planned studies are now looking into escalation and de-escalation of therapy according to ctDNA-status after surgery.

CONCLUSION

Serial measurement of ctDNA shows great promise as a marker for both prognosis and response to treatment in early colon cancer. Future studies will show whether we can use this analysis for tailoring treatment for patients in the adjuvant and neoadjuvant setting. With improved technology, ctDNA has the potential of becoming a 'game-changer' in the treatment of early stage colon cancers.

The future of early cancer detection

A proactive approach to detecting cancer at an early stage can make treatments more effective, with fewer side effects and improved long-term survival. However, as detection methods become increasingly sensitive, it can be difficult to distinguish inconsequential changes from lesions that will lead to life-threatening cancer. Progress relies on a detailed understanding of individualized risk, clear delineation of cancer development stages, a range of testing methods with optimal performance characteristics, and robust evaluation of the implications for individuals and society. In the future, advances in sensors, contrast agents, molecular methods, and artificial intelligence will help detect cancer-specific signals in real time. To reduce the burden of cancer on society, risk-based detection and prevention needs to be cost effective and widely accessible.

Combinatorial Power of cfDNA, CTCs and EVs in Oncology

Liquid biopsy is a promising technique for clinical management of oncological patients. The diversity of analytes circulating in the blood useable for liquid biopsy testing is enormous. Circulating tumor cells (CTCs), cell-free DNA (cfDNA) and extracellular vesicles (EVs), as well as blood cells and other soluble components in the plasma, were shown as liquid biopsy analytes. A few studies directly comparing two liquid biopsy analytes showed a benefit of one analyte over the other, while most authors concluded the benefit of the additional analyte. Only three years ago, the first studies to examine the value of a characterization of more than two liquid biopsy analytes from the same sample were conducted. We attempt to reflect on the recent development of multimodal liquid biopsy testing in this review. Although the analytes and clinical purposes of the published multimodal studies differed significantly, the additive value of the analytes was concluded in almost all projects. Thus, the blood components, as liquid biopsy reservoirs, are complementary rather than competitive, and orthogonal data sets were even shown to harbor synergistic effects. The unmistakable potential of multimodal liquid biopsy testing, however, is dampened by its clinical utility, which is yet to be proven, the lack of methodical standardization and insufficiently mature reimbursement, logistics and data handling.

Integrative Analysis of 5-Hydroxymethylcytosine and Transcriptional Profiling Identified 5hmC-Modified lncRNA Panel as Non-Invasive Biomarkers for Diagnosis and Prognosis of Pancreatic Cancer

Pancreatic adenocarcinoma (PAAD) is the fourth leading cause of cancer-related deaths worldwide. 5-Hydroxymethylcytosine (5hmC)-mediated epigenetic regulation has been reported to be involved in cancer pathobiology and has emerged to be promising biomarkers for cancer diagnosis and prognosis. However, 5hmC alterations at long non-coding RNA (lncRNA) genes and their clinical significance remained unknown. In this study, we performed the genome-wide investigation of lncRNA-associated plasma cfDNA 5hmC changes in PAAD by plotting 5hmC reads against lncRNA genes, and identified six PAAD-specific lncRNAs with abnormal 5hmC modifications compared with healthy individuals. Then we applied machine-learning and Cox regression approaches to develop predictive diagnostic (5hLRS) and prognostic (5hLPS) models using the 5hmC-modified lncRNAs. The 5hLRS demonstrated excellent performance in discriminating PAAD from healthy controls with an area under the curve (AUC) of 0.833 in the training cohort and 0.719 in the independent testing cohort. The 5hLPS also effectively divides PAAD patients into high-risk and low-risk groups with significantly different clinical outcomes in the training cohort (log-rank test p = 0.04) and independent testing cohort (log-rank test p = 0.0035). Functional analysis based on competitive endogenous RNA (ceRNA) and enrichment analysis suggested that these differentially regulated 5hmC modified lncRNAs were associated with angiogenesis, circulatory system process, leukocyte differentiation and metal ion homeostasis that are known important events in the development and progression of PAAD. In conclusion, our study indicated the potential clinical utility of 5hmC profiles at lncRNA loci as valuable biomarkers for non-invasive diagnosis and prognostication of cancers.

Early-stage multi-cancer detection using an extracellular vesicle protein-based blood test

Background

Detecting cancer at early stages significantly increases patient survival rates. Because lethal solid tumors often produce few symptoms before progressing to advanced, metastatic disease, diagnosis frequently occurs when surgical resection is no longer curative. One promising approach to detect early-stage, curable cancers uses biomarkers present in circulating extracellular vesicles (EVs). To explore the feasibility of this approach, we developed an EV-based blood biomarker classifier from EV protein profiles to detect stages I and II pancreatic, ovarian, and bladder cancer.

Methods

Utilizing an alternating current electrokinetics (ACE) platform to purify EVs from plasma, we use multi-marker EV-protein measurements to develop a machine learning algorithm that can discriminate cancer cases from controls. The ACE isolation method requires small sample volumes, and the streamlined process permits integration into high-throughput workflows.

Results

In this case-control pilot study, comparison of 139 pathologically confirmed stage I and II cancer cases representing pancreatic, ovarian, or bladder patients against 184 control subjects yields an area under the curve (AUC) of 0.95 (95% CI: 0.92 to 0.97), with sensitivity of 71.2% (95% CI: 63.2 to 78.1) at 99.5% (97.0 to 99.9) specificity. Sensitivity is similar at both early stages [stage I: 70.5% (60.2 to 79.0) and stage II: 72.5% (59.1 to 82.9)]. Detection of stage I cancer reaches 95.5% in pancreatic, 74.4% in ovarian (73.1% in Stage IA) and 43.8% in bladder cancer.

Conclusions

This work demonstrates that an EV-based, multi-cancer test has potential clinical value for early cancer detection and warrants future expanded studies involving prospective cohorts with multi-year follow-up.

Finding cancer early can make treatment easier and improve odds of survival. However, many tumors go unnoticed until they have grown large enough to cause symptoms. While scans can detect tumors earlier, routine full-body imaging is impractical for population screening. New cancer detection methods being explored are based on observations that tumors release tiny particles called extracellular vesicles (EVs) into the bloodstream, containing proteins from the tumor. Here, we used a method to purify EVs from patients’ blood followed by a method to detect tumor proteins in the EVs. Our method quickly and accurately detected early-stage pancreatic, ovarian, or bladder cancer. With further testing, this method may provide a useful screening tool for clinicians to detect cancers at an earlier stage.

Hinestrosa et al. describe the early-stage detection of cancer using biomarkers present in circulating extracellular vesicles purified via an alternating current electrokinetics platform. They show, in a case-control study, that 95.7% of pancreatic, 75.0% of ovarian and 43.8% of bladder stage I and II cancers can be detected.

The Fight against Cancer by Microgravity: The Multicellular Spheroid as a Metastasis Model

Cancer is a disease exhibiting uncontrollable cell growth and spreading to other parts of the organism. It is a heavy, worldwide burden for mankind with high morbidity and mortality. Therefore, groundbreaking research and innovations are necessary. Research in space under microgravity (µg) conditions is a novel approach with the potential to fight cancer and develop future cancer therapies. Space travel is accompanied by adverse effects on our health, and there is a need to counteract these health problems. On the cellular level, studies have shown that real (r-) and simulated (s-) µg impact survival, apoptosis, proliferation, migration, and adhesion as well as the cytoskeleton, the extracellular matrix, focal adhesion, and growth factors in cancer cells. Moreover, the µg-environment induces in vitro 3D tumor models (multicellular spheroids and organoids) with a high potential for preclinical drug targeting, cancer drug development, and studying the processes of cancer progression and metastasis on a molecular level. This review focuses on the effects of r- and s-µg on different types of cells deriving from thyroid, breast, lung, skin, and prostate cancer, as well as tumors of the gastrointestinal tract. In addition, we summarize the current knowledge of the impact of µg on cancerous stem cells. The information demonstrates that µg has become an important new technology for increasing current knowledge of cancer biology.

Pancreatic cancer evolution and heterogeneity: integrating omics and clinical data

Pancreatic ductal adenocarcinoma (PDAC), already among the deadliest epithelial malignancies, is rising in both incidence and contribution to overall cancer deaths. Decades of research have improved our understanding of PDAC carcinogenesis, including characterizing germline predisposition, the cell of origin, precursor lesions, the sequence of genetic alterations, including simple and structural alterations, transcriptional changes and subtypes, tumour heterogeneity, metastatic progression and the tumour microenvironment. These fundamental advances inform contemporary translational efforts in primary prevention, screening and early detection, multidisciplinary management and survivorship, as prospective clinical trials begin to adopt molecular-based selection criteria to guide targeted therapies. Genomic and transcriptomic data on PDAC were also included in the international pan-cancer analysis of approximately 2,600 cancers, a milestone in cancer research that allows further insight through comparison with other tumour types. Thus, this is an ideal time to review our current knowledge of PDAC evolution and heterogeneity, gained from the study of preclinical models and patient biospecimens, and to propose a model of PDAC evolution that takes into consideration findings from varied sources, with a particular focus on the genomics of human PDAC.

Detecting Neuroendocrine Prostate Cancer Through Tissue-Informed Cell-Free DNA Methylation Analysis

PURPOSE

Neuroendocrine prostate cancer (NEPC) is a resistance phenotype that emerges in men with metastatic castration-resistant prostate adenocarcinoma (CR-PRAD) and has important clinical implications, but is challenging to detect in practice. Herein, we report a novel tissue-informed epigenetic approach to noninvasively detect NEPC.

EXPERIMENTAL DESIGN

We first performed methylated immunoprecipitation and high-throughput sequencing (MeDIP-seq) on a training set of tumors, identified differentially methylated regions between NEPC and CR-PRAD, and built a model to predict the presence of NEPC (termed NEPC Risk Score). We then performed MeDIP-seq on cell-free DNA (cfDNA) from two independent cohorts of men with NEPC or CR-PRAD and assessed the accuracy of the model to predict the presence NEPC.

RESULTS

The test cohort comprised cfDNA samples from 48 men, 9 with NEPC and 39 with CR-PRAD. NEPC Risk Scores were significantly higher in men with NEPC than CR-PRAD (P = 4.3 × 10-7) and discriminated between NEPC and CR-PRAD with high accuracy (AUROC 0.96). The optimal NEPC Risk Score cutoff demonstrated 100% sensitivity and 90% specificity for detecting NEPC. The independent, multi-institutional validation cohort included cfDNA from 53 men, including 12 with NEPC and 41 with CR-PRAD. NEPC Risk Scores were significantly higher in men with NEPC than CR-PRAD (P = 7.5×10-12) and perfectly discriminated NEPC from CR-PRAD (AUROC 1.0). Applying the predefined NEPC Risk Score cutoff to the validation cohort resulted in 100% sensitivity and 95% specificity for detecting NEPC.

CONCLUSIONS

Tissue-informed cfDNA methylation analysis is a promising approach for noninvasive detection of NEPC in men with advanced prostate cancer.