Quantitative Detection and Resolution of BRAF V600 Status in Colorectal Cancer Using Droplet Digital PCR and a Novel Wild-Type Negative Assay

Highly Sensitive Detection of PIK3CA Mutations by Looping-Out Probes-Based Melting Curve Analysis

PIK3CA mutations have important therapeutic and prognostic implications in various cancer types. However, highly sensitive detection of PIK3CA hotspot mutations in heterogeneous tumor samples remains a challenge in clinical settings. To establish a rapid PCR assay for highly sensitive detection of multiple PIK3CA hotspot mutations. We described a novel melting curve analysis-based assay using looping-out probes that can enrich target mutations in the background of excess wild-type and concurrently reveal the presence of mutations. The analytical and clinical performance of the assay were evaluated. The developed assay could detect 10 PIK3CA hotspot mutations at a mutant allele fraction of 0.05-0.5% within 2 h in a single step. Analysis of 82 breast cancer tissue samples revealed 43 samples with PIK3CA mutations, 28 of which were confirmed by Sanger sequencing. Further testing of 175 colorectal cancer tissue samples showed that 24 samples contained PIK3CA mutations and 19 samples were confirmed by Sanger sequencing. Droplet digital PCR supported that all mutation-containing samples undetected by sequencing contained mutations with a low allele fraction. The rapidity, ease of use, high sensitivity and accuracy make the new assay a potential screening tool for PIK3CA mutations in clinical laboratories.

Accurate Detection of Multiple Tumor Mutations in Formalin-Fixed Paraffin-Embedded Tissues by Coupling Sequence Artifacts Elimination and Mutation Enrichment With MeltArray

Formalin-fixed paraffin-embedded (FFPE) tissues are the primary source of DNA for companion diagnostics (CDx) of cancers. Degradation of FFPE tissue DNA and inherent tumor heterogeneity constitute serious challenges in current CDx assays. To address these limitations, we introduced sequence artifact elimination and mutation enrichment to MeltArray, a highly multiplexed PCR approach, to establish an integrated protocol that provides accuracy, ease of use, and rapidness. Using PIK3CA mutations as a model, we established a MeltArray protocol that could eliminate sequence artifacts completely and enrich mutations from 23.5- to 59.4-fold via a single-reaction pretreatment step comprising uracil-DNA-glycosylase excision and PCR clamping. The entire protocol could identify 13 PIK3CA hotspot mutations of 0.05% to 0.5% mutant allele fractions within 5 hours. Evaluation of 106 breast cancer and 40 matched normal FFPE tissue samples showed that all 47 PIK3CA mutant samples were from the cancer tissue, and no false-positive results were detected in the normal samples. Further evaluation of 105 colorectal and 40 matched normal FFPE tissue samples revealed that 11 PIK3CA mutants were solely from the cancer sample. The detection results of our protocol were consistent with those of the droplet digital PCR assays that underwent sequence artifact elimination. Of the 60 colorectal samples with next-generation sequencing results, the MeltArray protocol detected 2 additional mutant samples with low mutant allele fractions. We conclude that the new protocol provides an improved alternative to current CDx assays for detecting tumor mutations in FFPE tissue DNA.

Quantification of rare somatic single nucleotide variants by droplet digital PCR using SuperSelective primers

Somatic single-nucleotide variants (SNVs) occur every time a cell divides, appearing even in healthy tissues at low frequencies. These mutations may accumulate as neutral variants during aging, or eventually, promote the development of neoplasia. Here, we present the SP-ddPCR, a droplet digital PCR (ddPCR) based approach that utilizes customized SuperSelective primers aiming at quantifying the proportion of rare SNVs. For that purpose, we selected five potentially pathogenic variants identified by whole-exome sequencing (WES) occurring at low variant allele frequency (VAF) in at-risk colon healthy mucosa of patients diagnosed with colorectal cancer or advanced adenoma. Additionally, two APC SNVs detected in two cancer lesions were added to the study for WES-VAF validation. SuperSelective primers were designed to quantify SNVs at low VAFs both in silico and in clinical samples. In addition to the two APC SNVs in colonic lesions, SP-ddPCR confirmed the presence of three out of five selected SNVs in the normal colonic mucosa with allelic frequencies ≤ 5%. Moreover, SP-ddPCR showed the presence of two potentially pathogenic variants in the distal normal mucosa of patients with colorectal carcinoma. In summary, SP-ddPCR offers a rapid and feasible methodology to validate next-generation sequencing data and accurately quantify rare SNVs, thus providing a potential tool for diagnosis and stratification of at-risk patients based on their mutational profiling.

Quantification of Isoniazid-Heteroresistant Mycobacterium tuberculosis Using Droplet Digital PCR

The quantitative detection of drug-resistance mutations in Mycobacterium tuberculosis (MTB) is critical for determining the drug resistance status of a sample. We developed a drop-off droplet digital PCR (ddPCR) assay targeting all major isoniazid (INH)-resistant mutations. The ddPCR assay consisted of three reactions: reaction A detects mutations at katG S315; reaction B detects inhA promoter mutations; and reaction C detects ahpC promoter mutations. All reactions could quantify 1%-50% of mutants in the presence of the wild-type, ranging from 100 to 50,000 copies/reaction. Clinical evaluation with 338 clinical isolates yielded clinical sensitivity of 94.5% (95% confidence interval [CI] = 89.1%-97.3%) and clinical specificity of 97.6% (95% CI = 94.6%-99.0%) compared with the traditional drug susceptibility testing (DST). Further clinical evaluation using 194 nucleic acid-positive MTB sputum samples revealed clinical sensitivity of 87.8% (95% CI = 75.8%-94.3%) and clinical specificity of 96.5% (95% CI = 92.2%-98.5%) in comparison with DST. All the mutant and heteroresistant samples detected by the ddPCR assay but susceptible by DST were confirmed by combined molecular assays, including Sanger sequencing, mutant-enriched Sanger sequencing and a commercial melting curve analysis-based assay. Finally, the ddPCR assay was used to monitor longitudinally the INH-resistance status and the bacterial load in nine patients undergoing treatment. Overall, the developed ddPCR assay could be an indispensable tool for quantification of INH-resistant mutations in MTB and bacterial loads in patients.

Development, Validation, and Application of Reverse Transcription Real-Time and Droplet Digital PCR Assays for the Detection of the Potyviruses Watermelon Mosaic Virus and Zucchini Yellow Mosaic Virus in Cucurbits

Among the cucurbit-infecting viruses, watermelon mosaic virus (WMV) and zucchini yellow mosaic virus (ZYMV) (Potyvirus: Potyviridae) are responsible for severe symptoms on cucumber, melon, watermelon, and zucchini cultivations worldwide. In this study, reverse transcription real-time PCR (real-time RT-PCR) and droplet-digital PCR (RT-ddPCR) assays targeting the coat protein (CP) genes of WMV and ZYMV were developed and validated according to the international standards of plant pest diagnosis (EPPO PM 7/98 (5)). First, the diagnostic performance of WMV-CP and ZYMV-CP real-time RT-PCRs was evaluated, and the assays displayed an analytical sensitivity of 10^-5 and 10^-3, respectively. The tests also showed an optimal repeatability, reproducibility and analytical specificity, and were reliable for the virus detection in naturally infected samples and across a wide range of cucurbit hosts. Based on these results, the real-time RT-PCR reactions were adapted to set up RT-ddPCR assays. These were the first RT-ddPCR assays aiming at the detection and quantification of WMV and ZYMV and showed a high sensitivity, being able to detect until 9 and 8 copies/µL of WMV or ZYMV, respectively. The RT-ddPCRs allowed the direct estimation of the virus concentrations and opened to a broad range of applications in disease management, such as the evaluation of partial resistance in breeding processes, identification of antagonistic/synergistic events, and studies on the implementation of natural compounds in the integrated management strategies.

Development of multiplex drop-off digital PCR assays for hotspot mutation detection of KRAS, NRAS, BRAF and PIK3CA in the plasma of colorectal cancer patients

The detection of mutations in KRAS, NRAS, BRAF and PIK3CA has become essential in treatment management of metastatic colorectal cancer (mCRC), with the approval of new targeted therapies. We developed novel multiplex drop-off digital PCR (MDO-dPCR) assays, by combining amplitude-/ratio-based multiplexing with drop-off/double drop-off strategies, which allow for detection of at least 69 most frequent hotspot mutations in all four genes with only three reactions. We assessed the analytical performance of the assays using synthetic oligonucleotides, further validated on plasma cfDNA samples from a large cohort of CRC patients and compared with next generation sequencing (NGS) data. The MDO-dPCR assays showed a high sensitivity with a limit of detection (LOD) ranging from 0.084 to 0.182% in mutant allelic frequency (MAF). The screening of plasma cfDNAs from 106 CRC patients identified mutations in 42.45% of them, with a sensitivity of 95.24%, a specificity of 98.53% and an accuracy of 96.98% for mutation detection and a strong correlation of measured MAFs as compared to NGS results. The high sensitivity and comprehensive mutation coverage of the MDO-dPCR assays make them suitable for rapid and cost-effective detection of KRAS, NRAS, BRAF and PIK3CA mutations in the plasma of CRC patients, and could be useful in early response assessment and longitudinal disease monitoring.

Utility of droplet digital polymerase chain reaction for TERT and BRAF mutational profiling of thyroid nodules

Background

Mutations involving BRAF and TERT are important predictors of disease severity in thyroid cancer, but molecular testing is limited by cost and lack of adequate tissue sample. This study aimed to assess the utility of BRAFV600E and TERT testing using droplet digital PCR (ddPCR) as a diagnostic and prognostic tool for thyroid fine needle aspirate biopsy (FNAB).

Methods

Patients with thyroid nodules were prospectively enrolled from March 2015 to September 2018. Pre-operative FNAB was collected for standard cytology and molecular testing. BRAFV600E and TERT levels were analyzed by ddPCR. Cytology (Bethesda system) and ddPCR results were correlated to surgical pathology.

Results

A total of 222 patients were enrolled, of which 124 received thyroid surgery. Pre-operative cytology alone with Bethesda ≥5 was 100% specific and 70% sensitive for malignancy on final surgical pathology. BRAFV600E positivity or TERT overexpression was 100% specific and 60.0% sensitive. Combining cytology (Bethesda ≥5) with BRAFV600E and TERT testing increased the sensitivity of a malignant diagnosis to 80.0%. High TERT levels and/or BRAFV600E was associated with aggressive or advanced stage pathology.

Conclusions

Combining cytology with ddPCR analysis of BRAFV600E and TERT can improve the diagnostic accuracy of thyroid FNAB, and help predict aggressive pathology.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08810-8.

Double Drop-Off Droplet Digital PCR: A Novel, Versatile Tool for Mutation Screening and Residual Disease Monitoring in Acute Myeloid Leukemia Using Cellular or Cell-Free DNA

In acute myeloid leukemia (AML), somatic gene mutations are important prognostic markers and increasingly constitute therapeutic targets. Therefore, robust, sensitive, and fast diagnostic assays are needed. Current techniques for mutation screening and quantification, including next-generation sequencing and quantitative PCR, each have weaknesses that leave a need for novel diagnostic tools. We established double drop-off digital droplet PCR (DDO-ddPCR) assays for gene mutations in NPM1, IDH2, and NRAS, which can detect and quantify diverse alterations at two nearby hotspot regions present in these genes. These assays can be used for mutation screening as well as quantification and sequential monitoring. The assays were validated against next-generation sequencing and existing ddPCR assays and achieved high concordance with an overall sensitivity comparable to conventional digital PCR. In addition, the feasibility of detecting and monitoring genetic alterations in peripheral blood cell-free DNA (cfDNA) of patients with AML by DDO-ddPCR was studied. cfDNA analysis was found to have similar sensitivity compared to quantitative PCR-based analysis of peripheral blood. Finally, the cfDNA-based digital PCR in several clinical scenarios was found to be useful in long-term monitoring of target-specific therapy, early response assessment during induction chemotherapy, and identification of mutations in patients with extramedullary disease. Thus, DDO-ddPCR-based cfDNA analysis may complement existing genetic tools for diagnosis and disease monitoring in AML.

Copy Number Variation and Rearrangements Assessment in Cancer: Comparison of Droplet Digital PCR with the Current Approaches

The cytogenetic and molecular assessment of deletions, amplifications and rearrangements are key aspects in the diagnosis and therapy of cancer. Not only the initial evaluation and classification of the disease, but also the follow-up of the tumor rely on these laboratory approaches. The therapeutic choice can be guided by the results of the laboratory testing. Genetic deletions and/or amplifications directly affect the susceptibility or the resistance to specific therapies. In an era of personalized medicine, the correct and reliable molecular characterization of the disease, also during the therapeutic path, acquires a pivotal role. Molecular assays like multiplex ligation-dependent probe amplification and droplet digital PCR represent exceptional tools for a sensitive and reliable detection of genetic alterations and deserve a role in molecular oncology. In this manuscript we provide a technical comparison of these two approaches with the golden standard represented by fluorescence in situ hybridization. We also describe some relevant targets currently evaluated with these techniques in solid and hematologic tumors.

Detection of Somatic Mutations with ddPCR from Liquid Biopsy of Colorectal Cancer Patients

Liquid biopsy and cell-free DNA (cfDNA) show great promise in cancer diagnostics. In this study, we designed a custom droplet digital PCR (ddPCR) assay for the quantification and quality control of cfDNA isolated from serum. The assay was validated on a group of locally advanced colorectal cancer (CRC) patients and two control groups-patients with hemorrhoids and healthy individuals. The assay shows a high correlation with Qubit measurement (r = 0.976) but offers a higher dynamic range. Mean concentrations of cfDNA were 12.36 ng/µL, 5.17 ng/µL, and 0.29 ng/µL for CRC, hemorrhoid patients, and healthy controls, respectively. The quality of cfDNA was assessed with the measurement of B-cell DNA contamination. On a subset of CRC patients, we compared the mutation status on KRAS (G12A, G12D, G12V, G13D) and BRAF (V600E) genes in the primary tumor and cfDNA isolated from the serum. A total of 70.6% of primary tumor samples were mutated, and the mean fractional abundance of mutations was 9.50%. The matching serum samples were mutated in 38% cases with an average fractional abundance of 0.23%. We conclude that any decisions based solely on the amount of cfDNA present in patient serum must be interpreted carefully and in the context of co-morbidities. This study explores the potential of ddPCR somatic mutations detection from liquid biopsy as a supplement to tissue biopsy in targeted personalized CRC patient management.

High-Accuracy Determination of Microsatellite Instability Compatible with Liquid Biopsies

BACKGROUND

Microsatellite instability (MSI) has recently emerged as a predictive pan-tumor biomarker of immunotherapy efficacy, stimulating the development of diagnostic tools compatible with large-scale screening of patients. In this context, noninvasive detection of MSI from circulating tumor DNA stands as a promising diagnostic and posttreatment monitoring tool.

METHODS

We developed drop-off droplet-digital PCR (ddPCR) assays targeting BAT-26, activin A receptor type 2A (ACVR2A), and defensin beta 105A/B (DEFB105A/B) microsatellite markers. Performances of the assays were measured on reconstitution experiments of various mutant allelic fractions, on 185 tumor samples with known MSI status, and on 72 blood samples collected from 42 patients with advanced colorectal or endometrial cancers before and/or during therapy.

RESULTS

The 3 ddPCR assays reached analytical sensitivity <0.1% variant allelic frequency and could reliably detect and quantify MSI in both tumor and body fluid samples. High concordance between MSI status determination by the three-marker ddPCR test and the reference pentaplex method were observed (100% for colorectal tumors and 93% for other tumor types). Moreover, the 3 assays showed correlations with r ≥ 0.99 with other circulating tumor DNA markers and their dynamic during treatment correlated well with clinical response.

CONCLUSIONS

This innovative approach for MSI detection provides a noninvasive, cost-effective, and fast diagnostic tool, well suited for large-scale screening of patients that may benefit from immunotherapy agents, as well as for monitoring treatment responses.

Evaluating the quantity, quality and size distribution of cell-free DNA by multiplex droplet digital PCR

Cell-free DNA (cfDNA) has become a comprehensive biomarker in the fields of non-invasive cancer detection and monitoring, organ transplantation, prenatal genetic testing and pathogen detection. While cfDNA samples can be obtained using a broad variety of approaches, there is an urgent need to standardize analytical tools aimed at assessing its basic properties. Typical methods to determine the yield and fragment size distribution of cfDNA samples are usually either blind to genomic DNA contamination or the presence of enzymatic inhibitors, which can confound and undermine downstream analyses. Here, we present a novel droplet digital PCR assay to identify suboptimal samples and aberrant cfDNA size distributions, the latter typically associated with high levels of circulating tumour DNA (ctDNA). Our assay was designed to promiscuously cross-amplify members of the human olfactory receptor (OR) gene family and includes a customizable diploid locus for the determination of absolute cfDNA concentrations. We demonstrate here the utility of our assay to estimate the yield and quality of cfDNA extracts and deduce fragment size distributions that correlate well with those inferred by capillary electrophoresis and high throughput sequencing. The assay described herein is a powerful tool to establish quality controls and stratify cfDNA samples based on presumed ctDNA levels, then facilitating the implementation of robust, cost-effective and standardized analytical workflows into clinical practice.

Multiplex-invasive reaction-assisted qPCR for quantitatively detecting the abundance of EGFR exon 19 deletions in cfDNA

Exon 19 deletions (19-Del) on the epidermal growth factor receptor (EGFR) gene are vital biomarkers for guiding tyrosine kinase inhibitor (TKI) treatment and the diagnosis of non-small cell lung cancer (NSCLC). However, it is difficult for conventional qPCR to quantitatively detect all 19-Del targets of EGFR, especially for cfDNA samples. Herein, a multiplex invasive reaction-assisted qPCR was proposed by employing a multiplex invasive reaction to distinguish 19-Del DNA targets from wild DNA targets and report them with different fluorescence signals in each PCR cycle. As all 19-Del targets have the same amplification efficiency and very similar invasive reaction efficiencies, the 19-Del abundance in a sample could be quantified by using the difference between the Ct values (ΔCt) of the deletion targets and the wild targets without the requirement of a standard calibration curve. Combining the high sensitivity of PCR and the high specificity of the invasive reaction, this method can detect 10 copies of the deletion targets and lower than 0.1% deletion abundance. The results were 100% consistent with ARMS-PCR for the 38 tumor tissues tested and were in good agreement with next-generation sequencing for quantifying the abundance of EGFR 19-Del in 15 cfDNA samples, showing the great potential of the method for liquid biopsies.

A single droplet digital PCR for ESR1 activating mutations detection in plasma

Activating mutations in the estrogen receptor 1 (ESR1) gene confer resistance to aromatase inhibitors (AI), and may be targeted by selective estrogen receptor downregulators. We designed a multiplex droplet digital PCR (ddPCR), which combines a drop-off assay, targeting the clustered hotspot mutations found in exon 8, with an unconventional assay interrogating the E380Q mutation in exon 5. We assessed its sensitivity in vitro using synthetic oligonucleotides, harboring E380Q, L536R, Y537C, Y537N, Y537S, or D538G mutations. Further validation was performed on plasma samples from a prospective study and compared with next generation sequencing (NGS) data. The multiplex ESR1-ddPCR showed a high sensitivity with a limit of detection ranging from 0.07 to 0.19% in mutant allele frequency. The screening of plasma samples from patients with AI-resistant metastatic breast cancer identified ESR1 mutations in 29% of them, all mutations being confirmed by NGS. In addition, this test identifies patients harboring polyclonal alterations. Furthermore, the monitoring of circulating tumor DNA using this technique during treatment follow-up predicts the clinical benefit of palbociclib-fulvestrant. The multiplex ESR1-ddPCR detects, in a single reaction, the most frequent ESR1 activating mutations with good sensitivity. This method allows real-time liquid biopsy for ESR1 mutation monitoring in large cohorts of patients.

Validation of Circulating Tumor DNA Assays for Detection of Metastatic Melanoma

The detection of cell-free, circulating tumor DNA (ctDNA) in the blood of patients with solid tumors is often referred to as "liquid biopsy." ctDNA is particularly attractive as a candidate biomarker in the blood. It is relatively stable after blood collection, can be easily purified, and can be quantitatively measured with high sensitivity and specificity using advanced technologies. Current liquid biopsy research has focused on detecting and quantifying ctDNA to (1) diagnose and characterize mutations in a patient's cancer to help select the appropriate treatment; (2) predict clinical outcomes associated with different treatments; and (3) monitor the response and/or progression of a patient's disease. The diagnostic use of liquid biopsies is probably greatest in tumors where the difficulty and/or risk of obtaining a tissue specimen for molecular diagnostics is high (e.g., lung, colon). In metastatic melanoma, however, obtaining a tissue sample for molecular diagnostics is not typically a major obstacle to patient care plans; rather predicting treatment outcomes and monitoring a patient's disease course during therapy are considered the current priorities for this cancer type. In this chapter we describe an approach to the validation of ctDNA detection assays for melanoma, focusing primarily on analytical validation, and provide methods to guide the use of droplet digital PCR assays for measuring ctDNA levels in plasma samples.

A density-watershed algorithm (DWA) method for robust, accurate and automatic classification of dual-fluorescence and four-cluster droplet digital PCR data

Droplet digital PCR (ddPCR) is a single-molecule amplification technology with broad applications in precision medicine and clinical diagnosis. Dual-fluorescence and four-cluster ddPCR (two/four-ddPCR) assay is an effective way to quantify copy numbers. Currently, two/four-ddPCR data are usually classified with manual thresholds. For clinical applications, automatic and accurate methods are required to avoid subjectivity in diagnosis. Although there are some automatic classification algorithms, their accuracy and robustness still need to be improved to meet the needs of clinical diagnosis. Therefore, a new method is in high demand to automatically classify two/four-ddPCR data in an accurate and robust way. Here, a novel density-watershed algorithm (DWA) method was developed for the accurate, automatic and unsupervised classification of two/four-ddPCR data. First, data gridding was applied to a scatter plot of the fluorescence signal intensity to calculate data densities. Based on the data densities, the watershed algorithm was used to divide the gridded scatter plot into isolated regions automatically. Next, an optimal cluster pattern was determined based on these isolated regions, and excess regions were merged. Finally, the two/four-ddPCR data were classified based on the merged regions, and DNA template copy numbers were calculated accordingly. Using the DWA method for the quantification of both wild types and mutants of epidermal growth factor receptor (EGFR) L858R and T790M, the classification results were highly consistent with expectations, and significantly better than commonly-used automatic algorithms for now. The computed template copy numbers scaled proportionally to the relative concentration of input templates (r2 > 0.998) in four orders of magnitude with a good reproducibility, and achieved a limit of detection over 40 times lower than the commonly-used automatic algorithms. Furthermore, the DWA method was validated on 254 clinical DNA samples derived from frozen tissues, formalin-fixed paraffin-embedded tissues and peripheral blood. In most cases, the DWA method derived accurate and valid classification results. This highly effective DWA method may be widely used for automatically classifying two/four-ddPCR data, and it will greatly promote the application of ddPCR in clinical diagnosis.

Demographic trends and KRAS/BRAFV600E mutations in colorectal cancer patients of South China: A single-site report

The incidence of colorectal cancer (CRC) is increasing in China. Here, we aimed to evaluate the latest demographic trends and KRAS/BRAF mutations status of Chinese CRC. Five thousand five hundred and forty-six CRC patients diagnosed from 2010 to 2017 were involved. KRAS exon 2 and BRAF^V600E mutations were detected by Sanger sequencing and high-resolution melting analysis or allelic-specific probe method. Gene mutation profiles and clinicopathologic characteristics of 5495 patients were analyzed. The joinpoint regression model was used to predict the demographic data in 2018. We found KRAS exon 2 and BRAF^V600E mutation rates were 37.7 and 2.8% in CRC patients. Tumors with KRAS exon 2 mutations were more likely to be present in female and patients aged older than 75 years, right colon and have well-differentiated histology. Tumors with BRAF^V600E mutations were more likely to be present in the female, right colon and have poorly differentiated histology. From 2010 to 2017, the percentage of colon cancer and tubular adenocarcinoma in CRC increased substantially (from 39.3 to 51.8%, from 78.6 to 93.4%, respectively). The percentage of right colon cancer increased from 18.3 to 20.5%, which predictively may keep at 22.6% in 2018. The rise trends for patients with moderate differentiation tumor or KRAS exon 2 mutated tumor were apparent (from 50.3 to 78.6%, from 32.8 to 39.7%, respectively). In conclusion, in recent 8 years, there is a shift to the colon, especially right colon in the incidence of Chinese CRC. Moreover tubular adenocarcinoma is becoming the primary histology type.

Single Droplet Digital Polymerase Chain Reaction for Comprehensive and Simultaneous Detection of Mutations in Hotspot Regions

Droplet digital polymerase chain reaction (ddPCR) is a highly sensitive quantitative polymerase chain reaction (PCR) method based on sample fractionation into thousands of nano-sized water-in-oil individual reactions. Recently, ddPCR has become one of the most accurate and sensitive tools for circulating tumor DNA (ctDNA) detection. One of the major limitations of the standard ddPCR technique is the restricted number of mutations that can be screened per reaction, as specific hydrolysis probes recognizing each possible allelic version are required. An alternative methodology, the drop-off ddPCR, increases throughput, since it requires only a single pair of probes to detect and quantify potentially all genetic alterations in the targeted region. Drop-off ddPCR displays comparable sensitivity to conventional ddPCR assays with the advantage of detecting a greater number of mutations in a single reaction. It is cost-effective, conserves precious sample material, and can also be used as a discovery tool when mutations are not known a priori.

Analytic and clinical validity of thyroid nodule mutational profiling using droplet digital polymerase chain reaction

BACKGROUND

Recent guidelines for the management of thyroid nodules incorporate mutation testing as an adjunct for surgical decision-making, however current tests are costly with limited accuracy. Droplet digital PCR (ddPCR) is an ultrasensitive method of nucleic acid detection that is particularly useful for identifying gene mutations. This study aimed to assess the analytic and clinical validity of RAS and BRAF ddPCR mutational testing as a diagnostic tool for thyroid fine needle aspirate biopsy (FNAB).

METHODS

Patients with thyroid nodules meeting indication for FNAB were prospectively enrolled from March 2015 to September 2017. In addition to clinical protocol, an additional FNAB was obtained for ddPCR. Optimized ddPCR probes were used to detect mutations including HRASG12 V, HRASQ61K, HRASQ61R, NRASQ61R, NRASQ61K and BRAFV600E. The diagnostic performance of BRAF and RAS mutations was assessed individually or in combination with Bethesda classification against final surgical pathology.

RESULTS

A total of 208 patients underwent FNAB and mutational testing with the following Bethesda cytologic classification: 26.9% non-diagnostic, 55.2% benign, 5.3% FLUS/AUS, 2.9% FN/SPN, 2.4% SFM and 7.2% malignant. Adequate RNA was obtained from 91.3% (190) FNABs from which mutations were identified in 21.1% of HRAS, 11.5% of NRAS and 7.4% of BRAF. Malignant cytology or BRAFV600E was 100% specific for malignancy. Combining cytology with ddPCR BRAF600E mutations testing increased the sensitivity of Bethesda classification from 41.7 to 75%. Combined BRAFV600E and Bethesda results had a positive predictive value (PPV) of 100% and negative predictive value (NPV) of 89.7% for thyroid malignancy in our cohort.

CONCLUSIONS

DdPCR offers a novel and ultrasensitive method of detecting RAS and BRAF mutations from thyroid FNABs. BRAFV600E mutation testing by ddPCR may serve as a useful adjunct to increase sensitivity and specificity of thyroid FNAB.

Multiple Hotspot Mutations Scanning by Single Droplet Digital PCR

BACKGROUND

Progress in the liquid biopsy field, combined with the development of droplet digital PCR (ddPCR), has enabled noninvasive monitoring of mutations with high detection accuracy. However, current assays detect a restricted number of mutations per reaction. ddPCR is a recognized method for detecting alterations previously characterized in tumor tissues, but its use as a discovery tool when the mutation is unknown a priori remains limited.

METHODS

We established 2 ddPCR assays detecting all genomic alterations within KRAS exon 2 and EGFR exon 19 mutation hotspots, which are of clinical importance in colorectal and lung cancer, with use of a unique pair of TaqMan® oligoprobes. The KRAS assay scanned for the 7 most common mutations in codons 12/13 but also all other mutations found in that region. The EGFR assay screened for all in-frame deletions of exon 19, which are frequent EGFR-activating events.

RESULTS

The KRAS and EGFR assays were highly specific and both reached a limit of detection of &lt;0.1% in mutant allele frequency. We further validated their performance on multiple plasma and formalin-fixed and paraffin-embedded tumor samples harboring a panel of different KRAS or EGFR mutations.

CONCLUSIONS

This method presents the advantage of detecting a higher number of mutations with single-reaction ddPCRs while consuming a minimum of patient sample. This is particularly useful in the context of liquid biopsy because the amount of circulating tumor DNA is often low. This method should be useful as a discovery tool when the tumor tissue is unavailable or to monitor disease during therapy.

Robust Multiplexed Clustering and Denoising of Digital PCR Assays by Data Gridding

Digital PCR (dPCR) relies on the analysis of individual partitions to accurately quantify nucleic acid species. The most widely used analysis method requires manual clustering through individual visual inspection. Some automated analysis methods have emerged but do not robustly account for multiplexed targets, low target concentration, and assay noise. In this study, we describe an open source analysis software called Calico that uses "data gridding" to increase the sensitivity of clustering toward small clusters. Our workflow also generates quality score metrics in order to gauge and filter individual assay partitions by how well they were classified. We applied our analysis algorithm to multiplexed droplet-based digital PCR data sets in both EvaGreen and probes-based schemes, and targeted the oncogenic BRAF V600E and KRAS G12D mutations. We demonstrate an automated clustering sensitivity of down to 0.1% mutant fraction and filtering of artifactual assay partitions from low quality DNA samples. Overall, we demonstrate a vastly improved approach to analyzing ddPCR data that can be applied to clinical use, where automation and reproducibility are critical.

Digital PCR Improves Mutation Analysis in Pancreas Fine Needle Aspiration Biopsy Specimens

Applications of precision oncology strategies rely on accurate tumor genotyping from clinically available specimens. Fine needle aspirations (FNA) are frequently obtained in cancer management and often represent the only source of tumor tissues for patients with metastatic or locally advanced diseases. However, FNAs obtained from pancreas ductal adenocarcinoma (PDAC) are often limited in cellularity and/or tumor cell purity, precluding accurate tumor genotyping in many cases. Digital PCR (dPCR) is a technology with exceptional sensitivity and low DNA template requirement, characteristics that are necessary for analyzing PDAC FNA samples. In the current study, we sought to evaluate dPCR as a mutation analysis tool for pancreas FNA specimens. To this end, we analyzed alterations in the KRAS gene in pancreas FNAs using dPCR. The sensitivity of dPCR mutation analysis was first determined using serial dilution cell spiking studies. Single-cell laser-microdissection (LMD) was then utilized to identify the minimal number of tumor cells needed for mutation detection. Lastly, dPCR mutation analysis was performed on 44 pancreas FNAs (34 formalin-fixed paraffin-embedded (FFPE) and 10 fresh (non-fixed)), including samples highly limited in cellularity (100 cells) and tumor cell purity (1%). We found dPCR to detect mutations with allele frequencies as low as 0.17%. Additionally, a single tumor cell could be detected within an abundance of normal cells. Using clinical FNA samples, dPCR mutation analysis was successful in all preoperative FNA biopsies tested, and its accuracy was confirmed via comparison with resected tumor specimens. Moreover, dPCR revealed additional KRAS mutations representing minor subclones within a tumor that were not detected by the current clinical gold standard method of Sanger sequencing. In conclusion, dPCR performs sensitive and accurate mutation analysis in pancreas FNAs, detecting not only the dominant mutation subtype, but also the additional rare mutation subtypes representing tumor heterogeneity.

A Robust Protocol for Using Multiplexed Droplet Digital PCR to Quantify Somatic Copy Number Alterations in Clinical Tissue Specimens

The ability of droplet digital PCR (ddPCR) to accurately determine the concentrations of amplifiable targets makes it a promising platform for measuring copy number alterations (CNAs) in genomic biomarkers. However, its application to clinical samples, particularly formalin-fixed paraffin-embedded specimens, will require strategies to reliably determine CNAs in DNA of limited quantity and quality. When applied to cancerous tissue, those methods must also account for global genetic instability and the associated probability that the abundance(s) of one or more chosen reference loci do not represent the average ploidy of cells comprising the specimen. Here we present an experimental design strategy and associated data analysis tool that enables accurate determination of CNAs in a panel of biomarkers using multiplexed ddPCR. The method includes strategies to optimize primer and probes design to cleanly segregate droplets in the data output from reaction wells amplifying multiple independent templates, and to correct for bias from artifacts such as DNA fragmentation. We demonstrate how a panel of reference loci can be used to determine a stable CNA-neutral benchmark. These innovations, when taken together, provide a comprehensive strategy that can be used to reliably detect biomarker CNAs in DNA extracted from either frozen or FFPE tissue biopsies.

ddpcr: an R package and web application for analysis of droplet digital PCR data

Droplet digital polymerase chain reaction (ddPCR) is a novel platform for exact quantification of DNA which holds great promise in clinical diagnostics. It is increasingly popular due to its digital nature, which provides more accurate quantification and higher sensitivity than traditional real-time PCR. However, clinical adoption has been slowed in part by the lack of software tools available for analyzing ddPCR data. Here, we present ddpcr – a new R package for ddPCR visualization and analysis. In addition, ddpcr includes a web application (powered by the Shiny R package) that allows users to analyze ddPCR data using an interactive graphical interface.

Initial Diagnosis of ALK-Positive Non-Small-Cell Lung Cancer Based on Analysis of ALK Status Utilizing Droplet Digital PCR

We describe a novel droplet digital PCR (ddPCR) assay capable of detecting genomic alterations associated with inversion translocations. It is applied here to detection of rearrangements in the anaplastic lymphoma kinase (ALK) gene associated with ALK-positive non-small-cell lung cancer (NSCLC). NSCLC patients may carry a nonreciprocal translocation on human chromosome 2, in which synchronized double stranded breaks (DSB) within the echinoderm microtubule-associated protein-like 4 (EML4) gene and ALK lead to an inversion of genetic material that forms the non-natural gene fusion EML4-ALK encoding a constitutively active tyrosine kinase that is associated with 3 to 7% of all NSCLCs. Detection of ALK rearrangements is currently achieved in clinics through direct visualization via a fluorescent in situ hybridization (FISH) assay, which can detect those rearrangements to a limit of detection (LOD) of ca. 15%. We show that the ddPCR assay presented here provides a LOD of 0.25% at lower cost and with faster turnaround times.