Development of personalized tumor biomarkers using massively parallel sequencing

Genome-wide analyses of cell-free DNA for therapeutic monitoring of patients with pancreatic cancer

Determining response to therapy for patients with pancreatic cancer can be challenging. We evaluated methods for assessing therapeutic response using cell-free DNA (cfDNA) in plasma from patients with metastatic pancreatic cancer in the CheckPAC trial (NCT02866383). Patients were evaluated before and after initiation of therapy using tumor-informed plasma whole-genome sequencing (WGMAF) and tumor-independent genome-wide cfDNA fragmentation profiles and repeat landscapes (ARTEMIS-DELFI). Using WGMAF, molecular responders had a median overall survival (OS) of 319 days compared to 126 days for nonresponders [hazard ratio (HR) = 0.29, 95% confidence interval (CI) = 0.11-0.79, P = 0.011]. For ARTEMIS-DELFI, patients with low scores after therapy initiation had longer median OS than patients with high scores (233 versus 172 days, HR = 0.12, 95% CI = 0.046-0.31, P < 0.0001). We validated ARTEMIS-DELFI in patients with pancreatic cancer in the PACTO trial (NCT02767557). These analyses suggest that noninvasive mutation and fragmentation-based cfDNA approaches can identify therapeutic response of individuals with pancreatic 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.

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.

Advances in tumor subclone formation and mechanisms of growth and invasion

Tumor subclones refer to distinct cell populations within the same tumor that possess different genetic characteristics. They play a crucial role in understanding tumor heterogeneity, evolution, and therapeutic resistance. The formation of tumor subclones is driven by several key mechanisms, including the inherent genetic instability of tumor cells, which facilitates the accumulation of novel mutations; selective pressures from the tumor microenvironment and therapeutic interventions, which promote the expansion of certain subclones; and epigenetic modifications, such as DNA methylation and histone modifications, which alter gene expression patterns. Major methodologies for studying tumor subclones include single-cell sequencing, liquid biopsy, and spatial transcriptomics, which provide insights into clonal architecture and dynamic evolution. Beyond their direct involvement in tumor growth and invasion, subclones significantly contribute to tumor heterogeneity, immune evasion, and treatment resistance. Thus, an in-depth investigation of tumor subclones not only aids in guiding personalized precision therapy, overcoming drug resistance, and identifying novel therapeutic targets, but also enhances our ability to predict recurrence and metastasis risks while elucidating the mechanisms underlying tumor heterogeneity. The integration of artificial intelligence, big data analytics, and multi-omics technologies is expected to further advance research in tumor subclones, paving the way for novel strategies in cancer diagnosis and treatment. This review aims to provide a comprehensive overview of tumor subclone formation mechanisms, evolutionary models, analytical methods, and clinical implications, offering insights into precision oncology and future translational research.

Ultrasensitive Detection and Monitoring of Circulating Tumor DNA Using Structural Variants in Early-Stage Breast Cancer

PURPOSE

The detection of circulating tumor DNA (ctDNA) after curative-intent therapy in early-stage breast cancer is highly prognostic of disease recurrence. Current ctDNA assays, mainly targeting single-nucleotide variants, vary in sensitivity and specificity. Although increasing the number of single-nucleotide variants in tumor-informed assays improves sensitivity, structural variants (SV) may achieve similar or better sensitivity without compromising specificity. SVs occur across all cancers, linked to genomic instability and tumorigenesis, with unique tumor- and patient-specific breakpoints occurring throughout the genome. SVs in breast cancer are underexplored, and their potential for ctDNA detection and monitoring has not been fully evaluated.

EXPERIMENTAL DESIGN

We retrospectively analyzed a tumor-informed SV-based ctDNA assay in a cohort of patients with early-stage breast cancer (n = 100, 568 timepoints) receiving neoadjuvant systemic therapy, evaluating ctDNA dynamics and lead times to clinical recurrence in the postoperative period.

RESULTS

ctDNA was detected in 96% (91/95) of participants at baseline with a median variant allele frequency of 0.15% (range: 0.0011%-38.7%); of these, 10% (9/91) had a variant allele frequency <0.01%. ctDNA detection at cycle 2 (C2) of neoadjuvant therapy was associated with a higher likelihood of distant recurrence (log-rank P = 0.047) and enhanced residual cancer burden prognostication (log-rank P = 0.041). ctDNA was detected prior to distant recurrence in all cases (100% sensitivity) with a median lead time of 417 days (range: 4-1,931 days).

CONCLUSIONS

These results demonstrate the clinical validity of ultrasensitive ctDNA detection and monitoring using SVs. Prospective trials are required to evaluate ctDNA-guided treatment strategies.

Circulating tumor DNA clearance as a predictive biomarker of pathologic complete response in patients with solid tumors treated with neoadjuvant immune checkpoint inhibitors: a systematic review and meta-analysis

BACKGROUND

In patients with solid tumors undergoing neoadjuvant immune checkpoint inhibitor (ICI) therapy, identifying biomarkers to predict pathologic complete response (pCR) preoperatively could enhance treatment modulation. Circulating tumor DNA (ctDNA) clearance is a potential predictor of pCR, though its analytical and clinical validity has yet to be established. This systematic review and meta-analysis aims to assess the role of ctDNA clearance as a predictor of pCR in patients with solid tumors treated with neoadjuvant ICIs.

MATERIALS AND METHODS

A systematic search of PubMed, EMBASE and conference proceedings up to 5 August 2024 was carried out to identify phase Ib, II or III clinical trials investigating ctDNA clearance and pCR in patients with solid tumors and detectable ctDNA, undergoing neoadjuvant therapy with ICIs. Using a bivariate model, we estimated the pooled sensitivity and specificity of ctDNA clearance in predicting pCR, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio, with 95% confidence intervals (CIs).

RESULTS

Thirteen trials involving 380 patients with detectable ctDNA at baseline were included. ctDNA was assessed with a tumor-informed approach in 11 (85%) trials. Overall, 38% of patients achieved pCR and 73% had ctDNA clearance before/at the surgery. Pooled sensitivity was 0.98 (95% CI 0.86-1.00), specificity was 0.53 (95% CI 0.37-0.69), positive likelihood ratio was 2.09 (95% CI 1.48-2.93), negative likelihood ratio was 0.04 (95% CI 0.01-0.26), diagnostic odds ratio was 57.36 (95% CI 8.12-405.12). Significant heterogeneity was observed across studies (I2 ∼70% for all metrics), indicating considerable variability in the diagnostic performance.

CONCLUSION

The lack of ctDNA clearance may identify patients unlikely to have a pCR. Instead, the confirmatory power of ctDNA clearance is limited by low specificity and high heterogeneity due to the variability of the assays, and warrants further study. Therefore, clinicians should not rely on the use of ctDNA clearance to inform treatment decisions in the neoadjuvant setting.

Liquid biopsy in cancer management: Integrating diagnostics and clinical applications

Liquid biopsy is an innovative, minimally invasive diagnostic tool revolutionizing cancer management by enabling the detection and analysis of cancer-related biomarkers from bodily fluids such as blood, urine, or cerebrospinal fluid. Unlike traditional tissue biopsies, which require invasive procedures, liquid biopsy offers a more accessible and repeatable method for tracking cancer progression, detecting early-stage cancers, and monitoring therapeutic responses. The technology primarily focuses on analyzing circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and other cancer-derived genetic materials. These biomarkers provide critical information on tumor heterogeneity, mutation profiles, and potential drug resistance. In clinical practice, liquid biopsy has demonstrated its utility in identifying actionable mutations, guiding personalized treatment strategies, and assessing minimal residual disease (MRD). While liquid biopsy holds immense promise, challenges related to its sensitivity, specificity, and standardization remain. Efforts to optimize pre-analytical and analytical processes, along with the establishment of robust regulatory frameworks, are crucial for its widespread clinical adoption. This abstract highlights the transformative potential of liquid biopsy in cancer diagnosis, prognosis, and treatment monitoring, emphasizing its role in advancing personalized oncology. Further research, clinical trials, and regulatory harmonization will be vital in realizing its full potential in precision cancer care.

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.

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.

Delta-radiomics in cancer immunotherapy response prediction: A systematic review

Background

The new immunotherapies have not only changed the oncological therapeutic approach but have also made it necessary to develop new imaging methods for assessing the response to treatment. Delta radiomics consists of the analysis of radiomic features variation between different medical images, usually before and after therapy.

Purpose

This review aims to evaluate the role of delta radiomics in the immunotherapy response assessment.

Methods

A systematic search was performed in PubMed, Scopus, and Web Of Science using "delta radiomics AND immunotherapy" as search terms. The included articles' methodological quality was measured using the Radiomics Quality Score (RQS) tool.

Results

Thirteen articles were finally included in the systematic review. Overall, the RQS of the included studies ranged from 4 to 17, with a mean RQS total of 11,15 ± 4,18 with a corresponding percentage of 30.98 ± 11.61 %. Eleven articles out of 13 performed imaging at multiple time points. All the included articles performed feature reduction. No study carried out prospective validation, decision curve analysis, or cost-effectiveness analysis.

Conclusions

Delta radiomics has been demonstrated useful in evaluating the response in oncologic patients undergoing immunotherapy. The overall quality was found law, due to the lack of prospective design and external validation. Thus, further efforts are needed to bring delta radiomics a step closer to clinical implementation.

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.

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

Background and Objective

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

Methods

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

Key Content and Findings

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

Conclusions

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

Using cfDNA and ctDNA as Oncologic Markers: A Path to Clinical Validation

The detection of circulating tumor DNA (ctDNA) in liquid biopsy samples as an oncological marker is being used in clinical trials at every step of clinical management. As ctDNA-based liquid biopsy kits are developed and used in clinics, companies work towards increased convenience, accuracy, and cost over solid biopsies and other oncological markers. The technology used to differentiate ctDNA and cell-free DNA (cfDNA) continues to improve with new tests and methodologies being able to detect down to mutant allele frequencies of 0.001% or 1/100,000 copies. Recognizing this development in technology, the FDA has recently given pre-market approval and breakthrough device designations to multiple companies. The purpose of this review is to look at the utility of measuring total cfDNA, techniques used to differentiate ctDNA from cfDNA, and the utility of different ctDNA-based liquid biopsy kits using relevant articles from PubMed, clinicaltrials.gov, FDA approvals, and company newsletters. Measuring total cfDNA could be a cost-effective, viable prognostic marker, but various factors do not favor it as a monitoring tool during chemotherapy. While there may be a place in the clinic for measuring total cfDNA in the future, the lack of standardization means that it is difficult to move forward with large-scale clinical validation studies currently. While the detection of ctDNA has promising standardized liquid biopsy kits from various companies with large clinical trials ongoing, their applications in screening and minimal residual disease can suffer from lower sensitivity. However, researchers are working towards solutions to these issues with innovations in technology, multi-omics, and sampling. With great promise, further research is needed before liquid biopsies can be recommended for everyday clinical management.

Circulating tumour DNA alterations: emerging biomarker in head and neck squamous cell carcinoma

Head and Neck cancers (HNC) are a heterogeneous group of upper aero-digestive tract cancer and account for 931,922 new cases and 467,125 deaths worldwide. About 90% of these cancers are of squamous cell origin (HNSCC). HNSCC is associated with excessive tobacco and alcohol consumption and infection with oncogenic viruses. Genotyping tumour tissue to guide clinical decision-making is becoming common practice in modern oncology, but in the management of patients with HNSCC, cytopathology or histopathology of tumour tissue remains the mainstream for diagnosis and treatment planning. Due to tumour heterogeneity and the lack of access to tumour due to its anatomical location, alternative methods to evaluate tumour activities are urgently needed. Liquid biopsy approaches can overcome issues such as tumour heterogeneity, which is associated with the analysis of small tissue biopsy. In addition, liquid biopsy offers repeat biopsy sampling, even for patients with tumours with access limitations. Liquid biopsy refers to biomarkers found in body fluids, traditionally blood, that can be sampled to provide clinically valuable information on both the patient and their underlying malignancy. To date, the majority of liquid biopsy research has focused on blood-based biomarkers, such as circulating tumour DNA (ctDNA), circulating tumour cells (CTCs), and circulating microRNA. In this review, we will focus on ctDNA as a biomarker in HNSCC because of its robustness, its presence in many body fluids, adaptability to existing clinical laboratory-based technology platforms, and ease of collection and transportation. We will discuss mechanisms of ctDNA release into circulation, technological advances in the analysis of ctDNA, ctDNA as a biomarker in HNSCC management, and some of the challenges associated with translating ctDNA into clinical and future perspectives. ctDNA provides a minimally invasive method for HNSCC prognosis and disease surveillance and will pave the way in the future for personalized medicine, thereby significantly improving outcomes and reducing healthcare costs.

Single-molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer

Somatic mutations are a hallmark of tumorigenesis and may be useful for non-invasive diagnosis of cancer. We analyzed whole-genome sequencing data from 2,511 individuals in the Pan-Cancer Analysis of Whole Genomes (PCAWG) study as well as 489 individuals from four prospective cohorts and found distinct regional mutation type-specific frequencies in tissue and cell-free DNA from patients with cancer that were associated with replication timing and other chromatin features. A machine-learning model using genome-wide mutational profiles combined with other features and followed by CT imaging detected >90% of patients with lung cancer, including those with stage I and II disease. The fixed model was validated in an independent cohort, detected patients with cancer earlier than standard approaches and could be used to monitor response to therapy. This approach lays the groundwork for non-invasive cancer detection using genome-wide mutation features that may facilitate cancer screening and monitoring.

Comparison of tumor-informed and tumor-naïve sequencing assays for ctDNA detection in breast cancer

Analysis of circulating tumor DNA (ctDNA) to monitor cancer dynamics and detect minimal residual disease has been an area of increasing interest. Multiple methods have been proposed but few studies have compared the performance of different approaches. Here, we compare detection of ctDNA in serial plasma samples from patients with breast cancer using different tumor-informed and tumor-naïve assays designed to detect structural variants (SVs), single nucleotide variants (SNVs), and/or somatic copy-number aberrations, by multiplex PCR, hybrid capture, and different depths of whole-genome sequencing. Our results demonstrate that the ctDNA dynamics and allele fractions (AFs) were highly concordant when analyzing the same patient samples using different assays. Tumor-informed assays showed the highest sensitivity for detection of ctDNA at low concentrations. Hybrid capture sequencing targeting between 1,347 and 7,491 tumor-identified mutations at high depth was the most sensitive assay, detecting ctDNA down to an AF of 0.00024% (2.4 parts per million, ppm). Multiplex PCR targeting 21-47 tumor-identified SVs per patient detected ctDNA down to 0.00047% AF (4.7 ppm) and has potential as a clinical assay.

Tumor type classification and candidate cancer-specific biomarkers discovery via semi-supervised learning

Identifying cancer-related differentially expressed genes provides significant information for diagnosing tumors, predicting prognoses, and effective treatments. Recently, deep learning methods have been used to perform gene differential expression analysis using microarray-based high-throughput gene profiling and have achieved good results. In this study, we proposed a new robust multiple-datasets-based semi-supervised learning model, MSSL, to perform tumor type classification and candidate cancer-specific biomarkers discovery across multiple tumor types and multiple datasets, which addressed the following long-lasting obstacles: (1) the data volume of the existing single dataset is not enough to fully exert the advantages of deep learning; (2) a large number of datasets from different research institutions cannot be effectively used due to inconsistent internal variances and low quality; (3) relatively uncommon cancers have limited effects on deep learning methods. In our article, we applied MSSL to The Cancer Genome Atlas (TCGA) and the Gene Expression Comprehensive Database (GEO) pan-cancer normalized-level3 RNA-seq data and got 97.6% final classification accuracy, which had a significant performance leap compared with previous approaches. Finally, we got the ranking of the importance of the corresponding genes for each cancer type based on classification results and validated that the top genes selected in this way were biologically meaningful for corresponding tumors and some of them had been used as biomarkers, which showed the efficacy of our method.

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

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

Genome-wide tiled detection of circulating Mycobacterium tuberculosis cell-free DNA using Cas13

Detection of microbial cell-free DNA (cfDNA) circulating in the bloodstream has emerged as a promising new approach for diagnosing infection. Microbial diagnostics based on cfDNA require assays that can detect rare and highly fragmented pathogen nucleic acids. We now report WATSON (Whole-genome Assay using Tiled Surveillance Of Nucleic acids), a method to detect low amounts of pathogen cfDNA that couples pooled amplification of genomic targets tiled across the genome with pooled CRISPR/Cas13-based detection of these targets. We demonstrate that this strategy of tiling improves cfDNA detection compared to amplification and detection of a single targeted locus. WATSON can detect cfDNA from Mycobacterium tuberculosis in plasma of patients with active pulmonary tuberculosis, a disease that urgently needs accurate, minimally-invasive, field-deployable diagnostics. We thus demonstrate the potential for translating WATSON to a lateral flow platform. WATSON demonstrates the ability to capitalize on the strengths of targeting microbial cfDNA to address the need for point-of-care diagnostic tests for infectious diseases.

Molecular methods for colorectal cancer screening: Progress with next-generation sequencing evolution

Currently, colorectal cancer (CRC) represents the third most common malignancy and the second most deadly cancer worldwide, with a higher incidence in developed countries. Like other solid tumors, CRC is a heterogeneous genomic disease in which various alterations, such as point mutations, genomic rearrangements, gene fusions or chromosomal copy number alterations, can contribute to the disease development. However, because of its orderly natural history, easily accessible onset location and high lifetime incidence, CRC is ideally suited for preventive intervention, but the many screening efforts of the last decades have been compromised by performance limitations and low penetrance of the standard screening tools. The advent of next-generation sequencing (NGS) has both facilitated the identification of previously unrecognized CRC features such as its relationship with gut microbial pathogens and revolutionized the speed and throughput of cataloguing CRC-related genomic alterations. Hence, in this review, we summarized the several diagnostic tools used for CRC screening in the past and the present, focusing on recent NGS approaches and their revolutionary role in the identification of novel genomic CRC characteristics, the advancement of understanding the CRC carcinogenesis and the screening of clinically actionable targets for personalized medicine.

Antigen Receptors Gene Analysis for Minimal Residual Disease Detection in Acute Lymphoblastic Leukemia: The Role of High Throughput Sequencing

The prognosis of adult acute lymphoblastic leukemia (ALL) is variable but more often dismal. Indeed, its clinical management is challenging, current therapies inducing complete remission in 65–90% of cases, but only 30–40% of patients being cured. The major determinant of treatment failure is relapse; consequently, measurement of residual leukemic blast (minimal residual disease, MRD) has become a powerful independent prognostic indicator in adults. Numerous evidences have also supported the clinical relevance of MRD assessment for risk class assignment and treatment selection. MRD can be virtually evaluated in all ALL patients using different technologies, such as polymerase chain reaction amplification of fusion transcripts and clonal rearrangements of antigen receptor genes, flow cytometric study of leukemic immunophenotypes and, the most recent, high throughput sequencing (HTS). In this review, the authors focused on the latest developments on MRD monitoring with emphasis on the use of HTS, as well as on the clinical impact of MRD monitoring.

Bioplatforms in liquid biopsy: advances in the techniques for isolation, characterization and clinical applications

Tissue biopsy analysis has conventionally been the gold standard for cancer prognosis, diagnosis and prediction of responses/resistances to treatments. The existing biopsy procedures used in clinical practice are, however, invasive, painful and often associated with pitfalls like poor recovery of tumor cells and infeasibility for repetition in single patients. To circumvent these limitations, alternative non-invasive, rapid and economical, yet sturdy, consistent and dependable, biopsy techniques are required. Liquid biopsy is an emerging technology that fulfills these criteria and potentially much more in terms of subject-specific real-time monitoring of cancer progression, determination of tumor heterogeneity and treatment responses, and specific identification of the type and stages of cancers. The present review first briefly revisits the state-of-the-art technique of liquid biopsy and then proceeds to address in detail, the advances in the potential clinical applications of four major biological agencies present in liquid biopsy samples (circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), exosomes and tumor-educated platelets (TEPs)). Finally, the authors conclude with the limitations that need to be addressed in order for liquid biopsy to effectively replace the conventional invasive biopsy methods in the clinical settings.

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.

The Promise of Circulating Tumor DNA in Head and Neck Cancer

As the seventh most common cancer globally, head and neck cancers (HNC) exert considerable disease burden, with an estimated 277,597 deaths worldwide in 2020 alone. Traditional risk factors for HNC include tobacco, alcohol, and betel nut; more recently, human papillomavirus has emerged as a distinct driver of disease. Currently, limitations of cancer screening and surveillance methods often lead to identifying HNC in more advanced stages, with associated poor outcomes. Liquid biopsies, in particular circulating tumor DNA (ctDNA), offer the potential for enhancing screening, early diagnosis, and surveillance in HNC patients, with potential improvements in HNC patient outcomes. In this review, we examine current methodologies for detecting ctDNA and highlight current research illustrating viral and non-viral ctDNA biomarker utilities in HNC screening, diagnosis, treatment response, and prognosis. We also summarize current challenges and future directions for ctDNA testing in HNC patients.

Direct comparison of circulating tumor DNA sequencing assays with targeted large gene panels

Next generation sequencing (NGS) assays with large targeted gene panels can comprehensively profile cancer somatic mutations in a tumor sample. Given the rapid adoption of such assays for circulating tumor DNA (ctDNA) analysis in clinical oncology, it is essential for the community to understand their analytical performance in liquid biopsy settings. Here, we directly compared five ctDNA NGS assays, most of which having a panel of 400 or more genes, with simulated samples harboring mutations relevant to solid tumors or myeloid malignancy. Our results indicate that the detection sensitivity and reproducibility of all five assays was 90% or higher when the mutations were at 0.5% or 1.0% allele frequency, and with optimal DNA input of 30 ng or 50 ng per vendor’s protocol. The performances decreased and varied dramatically, when mutations were at a 0.1% allele frequency and/or when a lower genomic input of 10 ng DNA was used. Interestingly, one of the assays repeatedly showed higher rate of false positivity than the others across two different sample sets. Multiple intrinsic technical factors pertaining to the NGS assays were further investigated. Notable differences among the assays were seen for depth of coverage and background noise, which profoundly impacted assay performance. The results derived from this study are highly informative and provide a framework to assess and select suitable assays for specific application in cancer monitoring and potential clinical use.

Cell-free DNA for the detection of emerging treatment failure in relapsed/ refractory multiple myeloma

Interrogation of cell-free DNA (cfDNA) represents an emerging approach to non-invasively estimate disease burden in multiple myeloma (MM). Here, we examined low-pass whole genome sequencing (LPWGS) of cfDNA for its predictive value in relapsed/ refractory MM (RRMM). We observed that cfDNA positivity, defined as ≥10% tumor fraction by LPWGS, was associated with significantly shorter progression-free survival (PFS) in an exploratory test cohort of 16 patients who were actively treated on diverse regimens. We prospectively determined the predictive value of cfDNA in 86 samples from 45 RRMM patients treated with elotuzumab, pomalidomide, bortezomib, and dexamethasone in a phase II clinical trial (NCT02718833). PFS in patients with tumor-positive and -negative cfDNA after two cycles of treatment was 1.6 and 17.6 months, respectively (HR 7.6, P < 0.0001). Multivariate hazard modelling confirmed cfDNA as independent risk factor (HR 96.6, P = 6.92e-05). While correlating with serum-free light chains and bone marrow, cfDNA additionally discriminated patients with poor PFS among those with the same response by IMWG criteria. In summary, detectability of MM-derived cfDNA, as a measure of substantial tumor burden with therapy, independently predicts poor PFS and may provide refinement for standard-of-care response parameters to identify patients with poor response to treatment earlier than is currently feasible.

Liquid biopsy: a step closer to transform diagnosis, prognosis and future of cancer treatments

Over the past decade, invasive techniques for diagnosing and monitoring cancers are slowly being replaced by non-invasive methods such as liquid biopsy. Liquid biopsies have drastically revolutionized the field of clinical oncology, offering ease in tumor sampling, continuous monitoring by repeated sampling, devising personalized therapeutic regimens, and screening for therapeutic resistance. Liquid biopsies consist of isolating tumor-derived entities like circulating tumor cells, circulating tumor DNA, tumor extracellular vesicles, etc., present in the body fluids of patients with cancer, followed by an analysis of genomic and proteomic data contained within them. Methods for isolation and analysis of liquid biopsies have rapidly evolved over the past few years as described in the review, thus providing greater details about tumor characteristics such as tumor progression, tumor staging, heterogeneity, gene mutations, and clonal evolution, etc. Liquid biopsies from cancer patients have opened up newer avenues in detection and continuous monitoring, treatment based on precision medicine, and screening of markers for therapeutic resistance. Though the technology of liquid biopsies is still evolving, its non-invasive nature promises to open new eras in clinical oncology. The purpose of this review is to provide an overview of the current methodologies involved in liquid biopsies and their application in isolating tumor markers for detection, prognosis, and monitoring cancer treatment outcomes.

Impact of Circulating Tumor DNA-Based Detection of Molecular Residual Disease on the Conduct and Design of Clinical Trials for Solid Tumors

Earlier detection of cancer recurrence using circulating tumor DNA (ctDNA) to detect molecular residual disease (MRD) has the potential to dramatically affect cancer management. We review evidence supporting the use of ctDNA as a biomarker for detection of MRD and highlight the potential impact that ctDNA testing could have on the conduct of clinical trials.

Limitations and opportunities of technologies for the analysis of cell-free DNA in cancer diagnostics

Cell-free DNA (cfDNA) in the circulating blood plasma of patients with cancer contains tumour-derived DNA sequences that can serve as biomarkers for guiding therapy, for the monitoring of drug resistance, and for the early detection of cancers. However, the analysis of cfDNA for clinical diagnostic applications remains challenging because of the low concentrations of cfDNA, and because cfDNA is fragmented into short lengths and is susceptible to chemical damage. Barcodes of unique molecular identifiers have been implemented to overcome the intrinsic errors of next-generation sequencing, which is the prevailing method for highly multiplexed cfDNA analysis. However, a number of methodological and pre-analytical factors limit the clinical sensitivity of the cfDNA-based detection of cancers from liquid biopsies. In this Review, we describe the state-of-the-art technologies for cfDNA analysis, with emphasis on multiplexing strategies, and discuss outstanding biological and technical challenges that, if addressed, would substantially improve cancer diagnostics and patient care.

Role of circulating tumor DNA and circulating tumor cells in breast cancer: History and updates

Circulating tumor DNA, cell-free DNA, and circulating tumor cells have been at the epitome of recent research in breast cancer. These forms of liquid biopsies have been used in monitoring disease progression, estimating the risk of relapse, and response to treatment. Much has been done in relation to serial monitoring of circulating tumor DNA in patients with primary breast cancer for detection of occult metastatic disease. Some studies have also explored their use in monitoring treatment response. As the field of liquid biopsies expands, more prospective studies are needed to tailor management in an individualistic approach. In this literature review, the authors explore the multiple uses of circulating tumor DNA and circulating tumor cells in breast cancer.

A Review of Circulating Tumor DNA in the Diagnosis and Monitoring of Esophageal Cancer

Circulating tumor DNA (ctDNA) is a type of cell-free DNA released by tumor cells after necrosis and apoptosis, and it can be actively secreted by tumor cells. Since ctDNA is derived from various tumor sites, it can provide far more comprehensive genomic and epigenomic information than a single-site biopsy. Therefore, ctDNA can overcome tumor heterogeneity, which is the major limitation of a traditional tissue biopsy approach. Noninvasive ctDNA assays allow continuous real-time monitoring of the molecular status of cancers. Recently, ctDNA assays have been widely used in clinical practice, including cancer diagnosis, evaluation of therapeutic efficacy and prognosis, and monitoring of relapse and metastasis. Although ctDNA shows a high diagnostic performance in advanced esophageal cancer, it is far from satisfactory for early diagnosis of esophageal cancer. Monitoring the dynamic changes of ctDNA is beneficial for the evaluation of therapeutic efficacy and prediction of early recurrence in esophageal cancer. It is necessary to establish standards for individualized ctDNA detection in the evaluation of treatment response and surveillance of esophageal cancer and to develop clinical practice guideline for the systemic treatment of patients with "ctDNA recurrence." This review aims to provide an update on the role of ctDNA in the diagnosis and monitoring of esophageal cancer.

Enhanced detection of minimal residual disease by targeted sequencing of phased variants in circulating tumor DNA

Circulating tumor-derived DNA (ctDNA) is an emerging biomarker for many cancers, but the limited sensitivity of current detection methods reduces its utility for diagnosing minimal residual disease. Here we describe phased variant enrichment and detection sequencing (PhasED-seq), a method that uses multiple somatic mutations in individual DNA fragments to improve the sensitivity of ctDNA detection. Leveraging whole-genome sequences from 2,538 tumors, we identify phased variants and their associations with mutational signatures. We show that even without molecular barcodes, the limits of detection of PhasED-seq outperform prior methods, including duplex barcoding, allowing ctDNA detection in the ppm range in participant samples. We profiled 678 specimens from 213 participants with B cell lymphomas, including serial cell-free DNA samples before and during therapy for diffuse large B cell lymphoma. In participants with undetectable ctDNA after two cycles of therapy using a next-generation sequencing-based approach termed cancer personalized profiling by deep sequencing, an additional 25% have ctDNA detectable by PhasED-seq and have worse outcomes. Finally, we demonstrate the application of PhasED-seq to solid tumors.

Detecting Liquid Remnants of Solid Tumors: Circulating Tumor DNA Minimal Residual Disease

Growing evidence demonstrates that circulating tumor DNA (ctDNA) minimal residual disease (MRD) following treatment for solid tumors predicts relapse. These results suggest that ctDNA MRD could identify candidates for adjuvant therapy and measure response to such treatment. Importantly, factors such as assay type, amount of ctDNA release, and technical and biological background can affect ctDNA MRD results. Furthermore, the clinical utility of ctDNA MRD for treatment personalization remains to be fully established. Here, we review the evidence supporting the value of ctDNA MRD in solid cancers and highlight key considerations in the application of this potentially transformative biomarker.

SIGNIFICANCE

ctDNA analysis enables detection of MRD and predicts relapse after definitive treatment for solid cancers, thereby promising to revolutionize personalization of adjuvant and consolidation therapies.

Validation of a Circulating Tumor DNA-Based Next-Generation Sequencing Assay in a Cohort of Patients with Solid tumors: A Proposed Solution for Decentralized Plasma Testing

BACKGROUND

Characterization of circulating tumor DNA (ctDNA) has been integrated into clinical practice. Although labs have standardized validation procedures to develop single locus tests, the efficacy of on-site plasma-based next-generation sequencing (NGS) assays still needs to be proved.

MATERIALS AND METHODS

In this retrospective study, we profiled DNA from matched tissue and plasma samples from 75 patients with cancer. We applied an NGS test that detects clinically relevant alterations in 33 genes and microsatellite instability (MSI) to analyze plasma cell-free DNA (cfDNA).

RESULTS

The concordance between alterations detected in both tissue and plasma samples was higher in patients with metastatic disease. The NGS test detected 77% of sequence alterations, amplifications, and fusions that were found in metastatic samples compared with 45% of those alterations found in the primary tumor samples (p = .00005). There was 87% agreement on MSI status between the NGS test and tumor tissue results. In three patients, MSI-high ctDNA correlated with response to immunotherapy. In addition, the NGS test revealed an FGFR2 amplification that was not detected in tumor tissue from a patient with metastatic gastric cancer, emphasizing the importance of profiling plasma samples in patients with advanced cancer.

CONCLUSION

Our validation experience of a plasma-based NGS assay advances current knowledge about translating cfDNA testing into clinical practice and supports the application of plasma assays in the management of oncology patients with metastatic disease. With an in-house method that minimizes the need for invasive procedures, on-site cfDNA testing supplements tissue biopsy to guide precision therapy and is entitled to become a routine practice.

IMPLICATIONS FOR PRACTICE

This study proposes a solution for decentralized liquid biopsy testing based on validation of a next-generation sequencing (NGS) test that detects four classes of genomic alterations in blood: sequence mutations (single nucleotide substitutions or insertions and deletions), fusions, amplifications, and microsatellite instability (MSI). Although there are reference labs that perform single-site comprehensive liquid biopsy testing, the targeted assay this study validated can be established locally in any lab with capacity to offer clinical molecular pathology assays. To the authors' knowledge, this is the first report that validates evaluating an on-site plasma-based NGS test that detects the MSI status along with common sequence alterations encountered in solid tumors.

Ultrasound-Based Method for the Identification of Novel MicroRNA Biomarkers in Prostate Cancer

The detection of circulating microRNA (miRNA)-based biomarkers represents an innovative, non-invasive method for the early detection of cancer. However, the low concentration of miRNAs released in body fluids and the difficult identification of the tumor site have limited their clinical use as effective cancer biomarkers. To evaluate if ultrasound treatment could amplify the release of extracellular cancer biomarkers, we treated a panel of prostate cancer (PCa) cell lines with an ultrasound-based prototype and profiled the release of miRNAs in the extracellular space, with the aim of identifying novel miRNA-based biomarkers that could be used for PCa diagnosis and the monitoring of tumor evolution. We provide evidence that US-mediated sonoporation amplifies the release of miRNAs from both androgen-dependent (AD) and -independent (AI) PCa cells. We identified four PCa-related miRNAs, whose levels in LNCaP and DU145 supernatants were significantly increased following ultrasound treatment: mir-629-5p, mir-374-5p, mir-194-5p, and let-7d-5p. We further analyzed a publicly available dataset of PCa, showing that the serum expression of these novel miRNAs was upregulated in PCa patients compared to controls, thus confirming their clinical relevance. Our findings highlight the potential of using ultrasound to identify novel cell-free miRNAs released from cancer cells, with the aim of developing new biomarkers with diagnostic and predictive value.

Circulating tumour DNA for clinicians: current and future clinical applications

This review introduces clinicians to the basic concepts of the biology of circulating tumour DNA (ctDNA), which is required to understand clinical use of ctDNA technology. We provide an overview of how new technology has improved the sensitivity of ctDNA detection over the last decade and the available techniques for ctDNA analysis including whole-genome sequencing (WGS), targeted cancer-associated gene panels, and methylation analysis. We discuss the most recent evidence from clinical trials for ctDNA in patient care including precision treatment of advanced cancers, disease monitoring, improving adjuvant treatment, and screening for early detection of cancer. Finally, we outline how ctDNA is likely to directly impact radiologists, and identify further research required for ctDNA to progress into routine clinical application.

Prostate Cancer Biomarkers: From diagnosis to prognosis and precision-guided therapeutics

Prostate cancer (PCa) is one of the most commonly diagnosed malignancies and among the leading causes of cancer-related death worldwide. It is a highly heterogeneous disease, ranging from remarkably slow progression or inertia to highly aggressive and fatal disease. As therapeutic decision-making, clinical trial design and outcome highly depend on the appropriate stratification of patients to risk groups, it is imperative to differentiate between benign versus more aggressive states. The incorporation of clinically valuable prognostic and predictive biomarkers is also potentially amenable in this process, in the timely prevention of metastatic disease and in the decision for therapy selection. This review summarizes the progress that has so far been made in the identification of the genomic events that can be used for the classification, prediction and prognostication of PCa, and as major targets for clinical intervention. We include an extensive list of emerging biomarkers for which there is enough preclinical evidence to suggest that they may constitute crucial targets for achieving significant advances in the management of the disease. Finally, we highlight the main challenges that are associated with the identification of clinically significant PCa biomarkers and recommend possible ways to overcome such limitations.

cfDNA Sequencing: Technological Approaches and Bioinformatic Issues

In the era of precision medicine, it is crucial to identify molecular alterations that will guide the therapeutic management of patients. In this context, circulating tumoral DNA (ctDNA) released by the tumor in body fluids, like blood, and carrying its molecular characteristics is becoming a powerful biomarker for non-invasive detection and monitoring of cancer. Major recent technological advances, especially in terms of sequencing, have made possible its analysis, the challenge still being its reliable early detection. Different parameters, from the pre-analytical phase to the choice of sequencing technology and bioinformatic tools can influence the sensitivity of ctDNA detection.

Optimizing Nanopore sequencing-based detection of structural variants enables individualized circulating tumor DNA-based disease monitoring in cancer patients

Here, we describe a novel approach for rapid discovery of a set of tumor-specific genomic structural variants (SVs), based on a combination of low coverage cancer genome sequencing using Oxford Nanopore with an SV calling and filtering pipeline. We applied the method to tumor samples of high-grade ovarian and prostate cancer patients and validated on average ten somatic SVs per patient with breakpoint-spanning PCR mini-amplicons. These SVs could be quantified in ctDNA samples of patients with metastatic prostate cancer using a digital PCR assay. The results suggest that SV dynamics correlate with and may improve existing treatment-response biomarkers such as PSA. https://github.com/UMCUGenetics/SHARC .

Circulating tumor DNA in lung cancer: real-time monitoring of disease evolution and treatment response

Lung cancer is one of the leading causes of all cancer-related deaths. Circulating tumor DNA (ctDNA) is released from apoptotic and necrotic tumor cells. Several sensitive techniques have been invented and adapted to quantify ctDNA genomic alterations. Applications of ctDNA in lung cancer include early diagnosis and detection, prognosis prediction, detecting mutations and structural alterations, minimal residual disease, tumor mutational burden, and tumor evolution tracking. Compared to surgical biopsy and radiographic imaging, the advantages of ctDNA are that it is a non-invasive procedure, allows real-time monitoring, and has relatively high sensitivity and specificity. Given the massive research on non-small cell lung cancer, attention should be paid to small cell lung cancer.

Current status of ctDNA in precision oncology for hepatocellular carcinoma

The conventional method used to obtain a tumor biopsy for hepatocellular carcinoma (HCC) is invasive and does not evaluate dynamic cancer progression or assess tumor heterogeneity. It is thus imperative to create a novel non-invasive diagnostic technique for improvement in cancer screening, diagnosis, treatment selection, response assessment, and predicting prognosis for HCC. Circulating tumor DNA (ctDNA) is a non-invasive liquid biopsy method that reveals cancer-specific genetic and epigenetic aberrations. Owing to the development of technology in next-generation sequencing and PCR-based assays, the detection and quantification of ctDNA have greatly improved. In this publication, we provide an overview of current technologies used to detect ctDNA, the ctDNA markers utilized, and recent advances regarding the multiple clinical applications in the field of precision medicine for HCC.

Next generation sequencing for liquid biopsy based testing in non-small cell lung cancer in 2021

Lung cancer is the leading cause of cancer death worldwide, with non-small cell lung cancer (NSCLC) representing its most commonly diagnosed sub-type. Despite the significant improvements in lung cancer biomarkers knowledge, accompanied by substantial technological advances in molecular tumor profiling, a considerable fraction (up to 30 %) of advanced NSCLC patient presents with major testing challenges or tissue unavailability for molecular analysis. In this context, liquid biopsy is on the rise, currently gaining considerable interest within the molecular pathology and oncology community. Molecular profiling of liquid biopsy specimens using next generation molecular biology methodologies is a rapidly evolving field with promising applications not exclusively limited to advanced stages but also more recently expanding to early stages cancer patients. Here, we offer an overview of some of the most consolidated and emerging applications of next generation sequencing technologies for liquid biopsy testing in NSCLC.

Understanding breast cancer heterogeneity through non-genetic heterogeneity

Intricacy in treatment and diagnosis of breast cancer has been an obstacle due to genotype and phenotype heterogeneity. Understanding of non-genetic heterogeneity mechanisms along with considering role of genetic heterogeneity may fill the gaps in landscape painting of heterogeneity. The main factors contribute to non-genetic heterogeneity including: transcriptional pulsing/bursting or discontinuous transcriptions, stochastic partitioning of components at cell division and various signal transduction from tumor ecosystem. Throughout this review, we desired to provide a conceptual framework focused on non-genetic heterogeneity, which has been intended to offer insight into prediction, diagnosis and treatment of breast cancer.

dPCR application in liquid biopsies: divide and conquer

Introduction: Precision medicine is already a reality in oncology, since biomarker-driven therapies have clearly improved patient survival. Furthermore, a new, minimally invasive strategy termed 'liquid biopsy' (LB) has revolutionized the field by allowing comprehensive cancer genomic profiling through the analysis of circulating tumor DNA (ctDNA). However, its detection requires extremely sensitive and efficient technologies. A powerful molecular tool based on the principle of 'divide and conquer' has emerged to solve this problem. Thus, digital PCR (dPCR) allows absolute and accurate quantification of target molecules.Areas covered: In this review we will discuss the fundamentals of dPCR and the most common approaches used for partition of samples and quantification. The advantages and limitations of dPCR will be mentioned in the context of LB in oncology.Expert opinion: In our opinion, dPCR has proven to be one of the most sensitive methods available for LB analysis, albeit some aspects such as its capacity of multiplexing and protocol standardization still require further improvements. Furthermore, the increasing sensitivities and lower costs of next generation sequencing (NGS) methods position dPCR as a confirmatory and complementary technique for NGS results which will likely prove to be very useful for treatment monitoring and assessing minimal residual disease.

Tumor DNA as a Cancer Biomarker through the Lens of Colorectal Neoplasia

Biomarkers have a wide range of applications in the clinical management of cancer, including screening and therapeutic management. Tumor DNA released from neoplastic cells has become a particularly active area of cancer biomarker development due to the critical role somatic alterations play in the pathophysiology of cancer and the ability to assess released tumor DNA in accessible clinical samples, in particular blood (i.e., liquid biopsy). Many of the early applications of tumor DNA as a biomarker were pioneered in colorectal cancer due to its well-defined genetics and common occurrence, the effectiveness of early detection, and the availability of effective therapeutic options. Herein, in the context of colorectal cancer, we describe how the intended clinical application dictates desired biomarker test performance, how features of tumor DNA provide unique challenges and opportunities for biomarker development, and conclude with specific examples of clinical application of tumor DNA as a biomarker with particular emphasis on early detection.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Considerations for the use of circulating tumor DNA sequencing as a screening tool in cancer predisposition syndromes

Liquid biopsy, specifically circulating tumor DNA (ctDNA) detection, has started to revolutionize the clinical management of patients with cancer by surpassing many limitations of traditional tissue biopsies, particularly for serial testing. ctDNA sequencing has been successfully utilized for cancer detection, prognostication, and assessment of disease response and evolution. While the applications of ctDNA analysis are growing, the majority of studies to date have primarily evaluated its use as a tool for tracking a known cancer, and in most cases at advanced stage. Herein, we discuss the potential application of ctDNA for surveillance and early cancer detection in patients with a cancer predisposition syndrome.

Microarray-based analysis of the BRAF V600 mutations in circulating tumor DNA in melanoma patients

BACKGROUND

Circulating tumor DNA (ctDNA) holds great potential for cancer therapy and can provide diagnostic and prognostic information before and during treatment.

METHODS

Plasma DNA samples from 97 melanoma patients, 20 healthy donors and 3 patients with benign skin tumors were analyzed by microarray analysis and droplet digital PCR (ddPCR).

RESULTS

A microarray for simultaneous detection of six BRAF V600 mutations in ctDNA has been developed. The method allows the detection of 0.05% mutated DNA from WT DNA background. For paired samples (pre-surgery plasma and tumor tissue) isolated from 74 patients, the concordance of genotypes between tumor DNA and ctDNA was 65% (48/74). BRAF mutations in ctDNA were detected in 27/50 patients with BRAF-positive tumors and in 3/24 patients with BRAF wild-type tumors. The presence of ctDNA BRAF mutations in 23 plasma samples from melanoma patients undergoing therapy correlated significantly with tumor progression (P=0.005). The increase in cell-free DNA levels measured by ddPCR also correlated with disease progression (P=0.02). The concordance of results obtained by microarray identification of BRAF mutations and those obtained by ddPCR was 91%.

CONCLUSION

The novel microarray-based approach can be a useful non-invasive tool for accurate identification of ctDNA BRAF mutations to monitor disease progression.

Establishment of multiplex allele-specific blocker PCR for enrichment and detection of 4 common EGFR mutations in non-small cell lung cancer

Background

Lung cancer is one of the most severe cancers and the majority of patients miss the best timing for surgery when diagnosed, thus having to rely on radiotherapy, chemotherapy or target therapy. Epidermal growth factor receptor (EGFR) upregulation occurs in a large percentage of patients, who can then benefit from tyrosine kinase inhibitors (TKI). However, the EGFR mutations they carry will vary the effectiveness of TKI. Circulating tumor DNA (ctDNA) contains genetic information from cancer tissue that can be used as a liquid biopsy by non-invasive sampling. This study aimed to provide a solution for minor allele detection from ctDNA.

Methods

Our novel method, named multiplex allele-specific blocker PCR (MAB PCR), combines amplification refractory mutation system (ARMS), blocker PCR and fluorescent-labeled probes for better discrimination and higher throughput. MAB PCR was specially designed for low-quality samples such as ctDNA. A sensitive assay based on MAB PCR was developed for enriching and detecting four common EGFR mutations. This assay was optimized and evaluated with manufactured plasmids, and validated with 34 tissue samples and 94 plasma samples.

Results

The limit of detection of this assay was 10² copies and the detection sensitivity reached 0.1% mutant allele fraction (MAF). The results of clinical sample testing had 100% accordance with sequencing, which proved that this assay was accurate and applicable in clinical settings.

Conclusions

This assay could accomplish low-cost and rapid detection of 4 common EGFR mutations sensitively and accurately, which has huge potential in clinical usage for guiding medication. Furthermore, this design could be used to detect other mutations.