Targeted error-suppressed quantification of circulating tumor DNA using semi-degenerate barcoded adapters and biotinylated baits

Integrated approach to generate artificial samples with low tumor fraction for somatic variant calling benchmarking

BACKGROUND

High-throughput sequencing (HTS) has become the gold standard approach for variant analysis in cancer research. However, somatic variants may occur at low fractions due to contamination from normal cells or tumor heterogeneity; this poses a significant challenge for standard HTS analysis pipelines. The problem is exacerbated in scenarios with minimal tumor DNA, such as circulating tumor DNA in plasma. Assessing sensitivity and detection of HTS approaches in such cases is paramount, but time-consuming and expensive: specialized experimental protocols and a sufficient quantity of samples are required for processing and analysis. To overcome these limitations, we propose a new computational approach specifically designed for the generation of artificial datasets suitable for this task, simulating ultra-deep targeted sequencing data with low-fraction variants and demonstrating their effectiveness in benchmarking low-fraction variant calling.

RESULTS

Our approach enables the generation of artificial raw reads that mimic real data without relying on pre-existing data by using NEAT, a fine-grained read simulator that generates artificial datasets using models learned from multiple different datasets. Then, it incorporates low-fraction variants to simulate somatic mutations in samples with minimal tumor DNA content. To prove the suitability of the created artificial datasets for low-fraction variant calling benchmarking, we used them as ground truth to evaluate the performance of widely-used variant calling algorithms: they allowed us to define tuned parameter values of major variant callers, considerably improving their detection of very low-fraction variants.

CONCLUSIONS

Our findings highlight both the pivotal role of our approach in creating adequate artificial datasets with low tumor fraction, facilitating rapid prototyping and benchmarking of algorithms for such dataset type, as well as the important need of advancing low-fraction variant calling techniques.

Molecular assessment of endoscopically collected pancreatic juice and duodenal fluid from patients with pancreatic diseases

One concern associated with pancreatic diseases is the poor prognosis of pancreatic cancer. Even with advances in diagnostic modalities, risk stratification of premalignant lesions and differentiation of pancreatic cysts are challenging. Pancreatic lesions of concern include intraductal papillary mucinous neoplasms, mucinous cystic neoplasms, serous cystadenomas, pseudocysts, and retention cysts, as well as cystic degeneration of solid tumors such as solid pseudopapillary neoplasms and pancreatic neuroendocrine neoplasms. Pancreatic juice obtained during endoscopic retrograde cholangiopancreatography has previously been used for the detection of KRAS mutation. Recently, duodenal fluid, which can be obtained during the relatively minimally invasive procedures of endoscopic ultrasound (EUS) and esophagogastroduodenoscopy, and cyst fluid collected by EUS-guided fine-needle aspiration (FNA) were used for molecular biological analysis. Furthermore, advanced analytic methods with high sensitivity were used for the detection of single and multiple markers. Early detection of malignant pancreatic tumors and risk stratification of premalignant tumors can be performed using duodenal fluid samples with a single marker with high sensitivity. Technological advances in simultaneous detection of multiple markers allow for the differentiation of cystic pancreatic tumors. One thing to note is that the clinical guidelines do not recommend pancreatic cyst fluid and pancreatic juice (PJ) sampling by EUS-FNA and endoscopic retrograde cholangiopancreatography, respectively, in actual clinical practice, but state that they be performed at experienced facilities, and duodenal fluid sampling is not mentioned in the guidelines. With improved specimen handling and the combination of markers, molecular markers in PJ samples may be used in clinical practice in the near future.

MuA-based Molecular Indexing for Rare Mutation Detection by Next-Generation Sequencing

Detection of low-frequency mutations in cancer genomes or other heterogeneous cell populations requires high-fidelity sequencing. Molecular barcoding is one of the key technologies that enables the differentiation of true mutations from errors, which can be caused by sequencing or library preparation processes. However, current approaches where barcodes are introduced via primer extension or adaptor ligation do not utilize the full power of barcoding, due to complicated library preparation workflows and biases. Here we demonstrate the remarkable tolerance of MuA transposase to the presence of multiple replacements in transposon sequence, and explore this unique feature to engineer the MuA transposome complex with randomised nucleotides in 12 transposon positions, which can be introduced as a barcode into the target molecule after transposition event. We applied the approach of Unique MuA-based Molecular Indexing (UMAMI) to assess the power of rare mutation detection by shortgun sequencing on the Illumina platform. Our results show that UMAMI allows detection of rare mutations readily and reliably, and in this paper we report error rate values for the number of thermophilic DNA polymerases measured by using UMAMI.

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.

Enhanced specificity of clinical high-sensitivity tumor mutation profiling in cell-free DNA via paired normal sequencing using MSK-ACCESS

Circulating cell-free DNA from blood plasma of cancer patients can be used to non-invasively interrogate somatic tumor alterations. Here we develop MSK-ACCESS (Memorial Sloan Kettering - Analysis of Circulating cfDNA to Examine Somatic Status), an NGS assay for detection of very low frequency somatic alterations in 129 genes. Analytical validation demonstrated 92% sensitivity in de-novo mutation calling down to 0.5% allele frequency and 99% for a priori mutation profiling. To evaluate the performance of MSK-ACCESS, we report results from 681 prospective blood samples that underwent clinical analysis to guide patient management. Somatic alterations are detected in 73% of the samples, 56% of which have clinically actionable alterations. The utilization of matched normal sequencing allows retention of somatic alterations while removing over 10,000 germline and clonal hematopoiesis variants. Our experience illustrates the importance of analyzing matched normal samples when interpreting cfDNA results and highlights the importance of cfDNA as a genomic profiling source for cancer patients.

Liquid biopsies allow the non-invasive detection of somatic mutations from tumours. Here, the authors develop and test MSK-ACCESS, an NGS-based clinical assay for identifying low frequency mutations in 129 genes and describe how it benefits patients in the clinic.

Copy number and transcriptome alterations associated with metastatic lesion response to treatment in colorectal cancer

BACKGROUND

Therapeutic resistance is the main cause of death in metastatic colorectal cancer. To investigate genomic plasticity, most specifically of metastatic lesions, associated with response to first-line systemic therapy, we collected longitudinal liver metastatic samples and characterized the copy number aberration (CNA) landscape and its effect on the transcriptome.

METHODS

Liver metastatic biopsies were collected prior to treatment (pre, n = 97) and when clinical imaging demonstrated therapeutic resistance (post, n = 43). CNAs were inferred from whole exome sequencing and were correlated with both the status of the lesion and overall patient progression-free survival (PFS). We used RNA sequencing data from the same sample set to validate aberrations as well as independent datasets to prioritize candidate genes.

RESULTS

We identified a significantly increased frequency gain of a unique CN, in liver metastatic lesions after first-line treatment, on chr18p11.32 harboring 10 genes, including TYMS, which has not been reported in primary tumors (GISTIC method and test of equal proportions, FDR-adjusted p = 0.0023). CNA lesion profiles exhibiting different treatment responses were compared and we detected focal genomic divergences in post-treatment resistant lesions but not in responder lesions (two-tailed Fisher's Exact test, unadjusted p ≤ 0.005). The importance of examining metastatic lesions is highlighted by the fact that 15 out of 18 independently validated CNA regions found to be associated with PFS in this study were only identified in the metastatic lesions and not in the primary tumors.

CONCLUSION

This investigation of genomic-phenotype associations in a large colorectal cancer liver metastases cohort identified novel molecular features associated with treatment response, supporting the clinical importance of collecting metastatic samples in a defined clinical setting.

Digital next-generation sequencing of cell-free DNA for pancreatic cancer

Background and Aim

The clinical applicability of digital next‐generation sequencing (dNGS), which eliminates polymerase chain reaction (PCR) and sequencing error‐derived noise by using molecular barcodes (MBs), has not been fully evaluated. We evaluated the utility of dNGS of cell‐free DNA (cfDNA) in liquid biopsies obtained from patients with pancreatic cancer.

Methods

Fifty‐eight patients with pancreatic cancer undergoing endoscopic ultrasound‐guided fine‐needle aspiration (EUS‐FNA) were included. Samples were subjected to sequencing of 50 cancer‐related genes using next‐generation sequencing (NGS). The results were used as reference gene alterations. NGS of cfDNA from plasma was performed for patients with a mutant allele frequency (MAF) >1% and an absolute mutant number > 10 copies/plasma mL in KRAS or GNAS by digital PCR. Sequence readings with and without MBs were compared with reference to EUS‐FNA‐derived gene alterations.

Results

The concordance rate between dNGS of cfDNA and EUS‐FNA‐derived gene alterations was higher with than without MBs (p = 0.039), and MAF cut‐off values in dNGS could be decreased to 0.2%. dNGS using MBs eliminated PCR and sequencing error by 74% and 68% for TP53 and all genes, respectively. Overall, dNGS detected mutations in KRAS (45%) and TP53 (26%) and copy number alterations in CCND2, CCND3, CDK4, FGFR1, and MYC, which are targets of molecular‐targeted drugs.

Conclusions

dNGS of cfDNA using MBs is useful for accurate detection of gene alterations even with low levels of MAFs. These results may be used to inform the development of diagnostics and therapeutics that can improve the prognosis of pancreatic cancer.

Chasing ctDNA in Patients With Sarcoma

Liquid biopsies are new technologies that allow cancer profiling of tumor fragments found in body fluids, such as peripheral blood, collected noninvasively from patients with malignancies. These assays are increasingly valuable in clinical oncology practice as prognostic biomarkers, as guides for therapy selection, for treatment monitoring, and for early detection of disease progression and relapse. However, application of these assays to rare cancers, such as pediatric and adult sarcomas, have lagged. In this article, we review the technical challenges of applying liquid biopsy technologies to sarcomas, provide an update on progress in the field, describe common pitfalls in interpreting liquid biopsy data, and discuss the intersection of sarcoma clinical care and commercial assays emerging on the horizon.

Alignment-free clustering of UMI tagged DNA molecules

MOTIVATION

Next-Generation Sequencing has led to the availability of massive genomic datasets whose processing raises many challenges, including the handling of sequencing errors. This is especially pertinent in cancer genomics, e.g. for detecting low allele frequency variations from circulating tumor DNA. Barcode tagging of DNA molecules with unique molecular identifiers (UMI) attempts to mitigate sequencing errors; UMI tagged molecules are polymerase chain reaction (PCR) amplified, and the PCR copies of UMI tagged molecules are sequenced independently. However, the PCR and sequencing steps can generate errors in the sequenced reads that can be located in the barcode and/or the DNA sequence. Analyzing UMI tagged sequencing data requires an initial clustering step, with the aim of grouping reads sequenced from PCR duplicates of the same UMI tagged molecule into a single cluster, and the size of the current datasets requires this clustering process to be resource-efficient.

RESULTS

We introduce Calib, a computational tool that clusters paired-end reads from UMI tagged sequencing experiments generated by substitution-error-dominant sequencing platforms such as Illumina. Calib clusters are defined as connected components of a graph whose edges are defined in terms of both barcode similarity and read sequence similarity. The graph is constructed efficiently using locality sensitive hashing and MinHashing techniques. Calib's default clustering parameters are optimized empirically, for different UMI and read lengths, using a simulation module that is packaged with Calib. Compared to other tools, Calib has the best accuracy on simulated data, while maintaining reasonable runtime and memory footprint. On a real dataset, Calib runs with far less resources than alignment-based methods, and its clusters reduce the number of tentative false positive in downstream variation calling.

AVAILABILITY AND IMPLEMENTATION

Calib is implemented in C++ and its simulation module is implemented in Python. Calib is available at https://github.com/vpc-ccg/calib.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

SinoDuplex: An Improved Duplex Sequencing Approach to Detect Low-frequency Variants in Plasma cfDNA Samples

Accurate detection of low frequency mutations from plasma cell-free DNA in blood using targeted next generation sequencing technology has shown promising benefits in clinical settings. Duplex sequencing technology is the most commonly used approach in liquid biopsies. Unique molecular identifiers are attached to each double-stranded DNA template, followed by production of low-error consensus sequences to detect low frequency variants. However, high sequencing costs have hindered application of this approach in clinical practice. Here, we have developed an improved duplex sequencing approach called SinoDuplex, which utilizes a pool of adapters containing pre-defined barcode sequences to generate far fewer barcode combinations than with random sequences, and implemented a novel computational analysis algorithm to generate duplex consensus sequences more precisely. SinoDuplex increased the output of duplex sequencing technology, making it more cost-effective. We evaluated our approach using reference standard samples and cell-free DNA samples from lung cancer patients. Our results showed that SinoDuplex has high sensitivity and specificity in detecting very low allele frequency mutations. The source code for SinoDuplex is freely available at https://github.com/SinOncology/sinoduplex.

High efficiency error suppression for accurate detection of low-frequency variants

Detection of cancer-associated somatic mutations has broad applications for oncology and precision medicine. However, this becomes challenging when cancer-derived DNA is in low abundance, such as in impure tissue specimens or in circulating cell-free DNA. Next-generation sequencing (NGS) is particularly prone to technical artefacts that can limit the accuracy for calling low-allele-frequency mutations. State-of-the-art methods to improve detection of low-frequency mutations often employ unique molecular identifiers (UMIs) for error suppression; however, these methods are highly inefficient as they depend on redundant sequencing to assemble consensus sequences. Here, we present a novel strategy to enhance the efficiency of UMI-based error suppression by retaining single reads (singletons) that can participate in consensus assembly. This 'Singleton Correction' methodology outperformed other UMI-based strategies in efficiency, leading to greater sensitivity with high specificity in a cell line dilution series. Significant benefits were seen with Singleton Correction at sequencing depths ≤16 000×. We validated the utility and generalizability of this approach in a cohort of >300 individuals whose peripheral blood DNA was subjected to hybrid capture sequencing at ∼5000× depth. Singleton Correction can be incorporated into existing UMI-based error suppression workflows to boost mutation detection accuracy, thus improving the cost-effectiveness and clinical impact of NGS.

Molecular Profiling of Liquid Biopsy Samples for Precision Medicine

In the context of oncology, liquid biopsies consist of harvesting cancer biomarkers, such as circulating tumor cells, tumor-derived cell-free DNA, and extracellular vesicles, from bodily fluids. These biomarkers provide a source of clinically actionable molecular information that can enable precision medicine. Herein, we review technologies for the molecular profiling of liquid biopsy markers with special emphasis on the analysis of low abundant markers from mixed populations.

A high-throughput protocol for isolating cell-free circulating tumor DNA from peripheral blood

The analysis of cell-free circulating tumor DNA (ctDNA) is potentially a less invasive, more dynamic assessment of cancer progression and treatment response than characterizing solid tumor biopsies. Standard isolation methods require separation of plasma by centrifugation, a time-consuming step that complicates automation. To address these limitations, we present an automatable magnetic bead-based ctDNA isolation method that eliminates centrifugation to purify ctDNA directly from peripheral blood (PB). To develop and test our method, ctDNA from cancer patients was purified from PB and plasma. We found that allelic fractions of somatic single-nucleotide variants from target gene capture libraries were comparable, indicating that the PB ctDNA purification method may be a suitable replacement for the plasma-based protocols currently in use.

Ultrasensitive Detection of Circulating Tumor DNA in Lymphoma via Targeted Hybridization Capture and Deep Sequencing of Barcoded Libraries

Liquid biopsies are rapidly emerging as powerful tools for the early detection of cancer, noninvasive genomic profiling of localized or metastatic tumors, prompt detection of treatment resistance-associated mutations, and monitoring of therapeutic response and minimal residual disease in patients during clinical follow-up. Growing evidence strongly supports the utility of circulating tumor DNA (ctDNA) as a biomarker for the stratification and clinical management of lymphoma patients. However, ctDNA is diluted by variable amounts of cell-free DNA (cfDNA) shed by nonneoplastic cells causing a background signal of wild-type DNA that limits the sensitivity of methods that rely on DNA sequencing. Here, we describe an error suppression method for single-molecule counting that relies on targeted sequencing of cfDNA libraries constructed with semi-degenerate barcode adapters. Custom pools of biotinylated DNA baits for target enrichment can be designed to specifically track somatic mutations in one patient, survey mutation hotspots with diagnostic and prognostic value or be comprised of comprehensive gene panels with broad patient coverage in lymphoma. Such methods are amenable to track ctDNA levels during longitudinal liquid biopsy testing with high specificity and sensitivity and characterize, in real time, the genetic profiles of tumors without the need of standard invasive biopsies. The analysis of ultra-deep sequencing data according to the bioinformatics pipelines also described in this chapter affords to harness lower limits of detection for ctDNA below 0.1%.

Rapid and highly-specific generation of targeted DNA sequencing libraries enabled by linking capture probes with universal primers

Targeted Next Generation Sequencing (NGS) is being adopted increasingly broadly in many research, commercial and clinical settings. Currently used target capture methods, however, typically require complex and lengthy (sometimes multi-day) workflows that complicates their use in certain applications. In addition, small panels for high sequencing depth applications such as liquid biopsy typically have low on-target rates, resulting in unnecessarily high sequencing cost. We have developed a novel targeted sequencing library preparation method, named Linked Target Capture (LTC), which replaces typical multi-day target capture workflows with a single-day, combined ‘target-capture-PCR’ workflow. This approach uses physically linked capture probes and PCR primers and is expected to work with panel sizes from 100 bp to >10 Mbp. It reduces the time and complexity of the capture workflow, eliminates long hybridization and wash steps and enables rapid library construction and target capture. High on-target read fractions are achievable due to repeated sequence selection in the target-capture-PCR step, thus lowering sequencing cost. We have demonstrated this technology on sample types including cell-free DNA (cfDNA) and formalin-fixed, paraffin-embedded (FFPE) derived DNA, capturing a 35-gene pan-cancer panel, and therein detecting single nucleotide variants, copy number variants, insertions, deletions and gene fusions. With the integration of unique molecular identifiers (UMIs), variants as low as 0.25% abundance were detected, limited by input mass and sequencing depth. Additionally, sequencing libraries were prepared in less than eight hours from extracted DNA to loaded sequencer, demonstrating that LTC holds promise as a broadly applicable tool for rapid, cost-effective and high performance targeted sequencing.

A Novel Multiplex Droplet Digital PCR Assay to Identify and Quantify KRAS Mutations in Clinical Specimens

Recurrent activating point mutations in KRAS are critical drivers in pancreatic cancer and have been attributed to resistance to anti-epidermal growth factor receptor therapy in colorectal cancer. Although KRAS genotyping provides limited clinical utility in the diagnosis and management of pancreatic cancer patients at present, inferences about the fractional abundance of KRAS mutations may inform on tumor purity in traditionally challenging clinical specimens and their potential use in precision medicine. KRAS genetic testing has indeed become an essential tool to guide treatment decisions in colorectal cancer, but an unmet need for methods standardization exists. Here, we present a unique droplet digital PCR method that enables the simultaneous detection and quantification of KRAS exon 2, 3, and 4 point mutations and copy number alterations. We have validated 13 mutations (G12S, G12R, G12D, G12A, G12V, G12C, G13D, G60V, Q61H, Q61L, A146V, A146T, and A146P) and focal KRAS amplifications by conducting this assay in a cohort of 100 DNA samples extracted from fresh frozen tumor biopsies, formaldehyde-fixed, paraffin-embedded tissue, and liquid biopsy specimens. Despite its modest lower limit of detection (approximately 1%), this assay will be a rapid cost-effective means to infer the purity of biopsy specimens carrying KRAS mutations and can be used in noninvasive serial monitoring of circulating tumor DNA to evaluate clinical response and/or detect early signs of relapse.

Detecting Rare Mutations and DNA Damage with Sequencing-Based Methods

There is a great need in biomedical and genetic research to detect DNA damage and de novo mutations, but doing so is inherently challenging because of the rarity of these events. The enormous capacity of current DNA sequencing technologies has opened the door for quantifying sequence variants present at low frequencies in vivo, such as within cancerous tissues. However, these sequencing technologies are error prone, resulting in high noise thresholds. Most DNA sequencing methods are also generally incapable of identifying chemically modified bases arising from DNA damage. In recent years, numerous specialized modifications to sequencing methods have been developed to address these shortcomings. Here, we review this landscape of emerging techniques, highlighting their respective strengths, weaknesses, and target applications.