An Automated Correction Algorithm (ALPACA) for ddPCR Data Using Adaptive Limit of Blank and Correction of False Positive Events Improves Specificity of Mutation Detection

Early Diagnostic Markers for Esophageal Squamous Cell Carcinoma: CNA Gene Identification and cfDNA Detection

The high mortality rate of esophageal squamous cell carcinoma (ESCC) is exacerbated by the absence of early diagnostic markers. The pronounced heterogeneity of mutations in ESCC renders copy number alterations (CNAs) more prevalent among patients. The identification of CNA genes within esophageal squamous dysplasia (ESD), a precancerous stage of ESCC, is crucial for advancing early detection efforts. Utilization of liquid biopsies via droplet-based digital PCR (ddPCR) offers a novel strategy for detecting incipient tumor traces. This study undertook a thorough investigation of CNA profiles across ESCC development stages, integrating data from existing databases and prior investigations to pinpoint and confirm CNA markers conducive to early detection of ESCC. Targeted sequencing was employed to select potential early detection genes, followed by the establishment of prediction models for ESCC early detection using ddPCR. Our analysis reveals widespread CNAs during the ESD stage, mirroring the CNA landscape observed in ESCC. A total of 40 CNA genes were identified as highly frequent in both ESCC and ESD lesions, through a comprehensive gene-level CNA analysis encompassing ESD and ESCC tissues, ESCC cell lines, and pan-cancer datasets. Subsequent validation of five candidate markers via ddPCR underscored the efficacy of combined predictive models-encompassing PIK3CA, SOX2, EGFR, MYC, and CCND1-in early ESCC screening, as evidenced by the area under the curve (AUC) values exceeding 0.92 (p<0.0001) across various detection contexts. The findings highlight the significant utility of CNA genes in the early screening of ESCC, presenting robust models that could facilitate early detection, broad-scale population screening, and adjunctive diagnosis.

Unraveling the potential clinical utility of circulating tumor DNA detection in colorectal cancer-evaluation in a nationwide Danish cohort

BACKGROUND

Increasingly, circulating tumor DNA (ctDNA) is proposed as a tool for minimal residual disease (MRD) assessment. Digital PCR (dPCR) offers low analysis costs and turnaround times of less than a day, making it ripe for clinical implementation. Here, we used tumor-informed dPCR for ctDNA detection in a large colorectal cancer (CRC) cohort to evaluate the potential for post-operative risk assessment and serial monitoring, and how the metastatic site may impact ctDNA detection. Additionally, we assessed how altering the ctDNA-calling algorithm could customize performance for different clinical settings.

PATIENTS AND METHODS

Stage II-III CRC patients (N = 851) treated with a curative intent were recruited. Based on whole-exome sequencing on matched tumor and germline DNA, a mutational target was selected for dPCR analysis. Plasma samples (8 ml) were collected within 60 days after operation and-for a patient subset (n = 246)-every 3-4 months for up to 36 months. Single-target dPCR was used for ctDNA detection.

RESULTS

Both post-operative and serial ctDNA detection were prognostic of recurrence [hazard ratio (HR) = 11.3, 95% confidence interval (CI) 7.8-16.4, P < 0.001; HR = 30.7, 95% CI 20.2-46.7, P < 0.001], with a cumulative ctDNA detection rate of 87% at the end of sample collection in recurrence patients. The ctDNA growth rate was prognostic of survival (HR = 2.6, 95% CI 1.5-4.4, P = 0.001). In recurrence patients, post-operative ctDNA detection was challenging for lung metastases (4/21 detected) and peritoneal metastases (2/10 detected). By modifying the cut-off for calling a sample ctDNA positive, we were able to adjust the sensitivity and specificity of our test for different clinical contexts.

CONCLUSIONS

The presented results from 851 stage II-III CRC patients demonstrate that our personalized dPCR approach effectively detects MRD after operation and shows promise for serial ctDNA detection for recurrence surveillance. The ability to adjust sensitivity and specificity shows exciting potential to customize the ctDNA caller for specific clinical settings.

IMPemBra: a phase 2 study comparing pembrolizumab with intermittent/short-term dual MAPK pathway inhibition plus pembrolizumab in patients with melanoma harboring the BRAFV600 mutation

BACKGROUND

Continuous combination of MAPK pathway inhibition (MAPKi) and anti-programmed death-(ligand) 1 (PD-(L)1) showed high response rates, but only limited improvement in progression-free survival (PFS) at the cost of a high frequency of treatment-related adverse events (TRAE) in patients with BRAF^V600-mutated melanoma. Short-term MAPKi induces T-cell infiltration in patients and is synergistic with anti-programmed death-1 (PD-1) in a preclinical melanoma mouse model. The aim of this phase 2b trial was to identify an optimal regimen of short-term MAPKi with dabrafenib plus trametinib in combination with pembrolizumab.

METHODS

Patients with treatment-naïve BRAF^V600E/K-mutant advanced melanoma started pembrolizumab 200 mg every 3 weeks. In week 6, patients were randomized to continue pembrolizumab only (cohort 1), or to receive, in addition, intermittent dabrafenib 150 mg two times per day plus trametinib 2 mg one time per day for two cycles of 1 week (cohort 2), two cycles of 2 weeks (cohort 3), or continuously for 6 weeks (cohort 4). All cohorts continued pembrolizumab for up to 2 years. Primary endpoints were safety and treatment-adherence. Secondary endpoints were objective response rate (ORR) at week 6, 12, 18 and PFS.

RESULTS

Between June 2016 and August 2018, 33 patients with advanced melanoma have been included and 32 were randomized. Grade 3-4 TRAE were observed in 12%, 12%, 50%, and 63% of patients in cohort 1, 2, 3, and 4, respectively. All planned targeted therapy was given in 88%, 63%, and 38% of patients in cohort 2, 3, and 4. ORR at week 6, 12, and 18 were 38%, 63%, and 63% in cohort 1; 25%, 63%, and 75% in cohort 2; 25%, 50%, and 75% in cohort 3; and 0%, 63%, and 50% in cohort 4. After a median follow-up of 43.5 months, median PFS was 10.6 months for pembrolizumab monotherapy and not reached for patients treated with pembrolizumab and intermittent dabrafenib and trametinib (p=0.17). The 2-year and 3-year landmark PFS were both 25% for cohort 1, both 63% for cohort 2, 50% and 38% for cohort 3 and 75% and 60% for cohort 4.

CONCLUSIONS

The combination of pembrolizumab plus intermittent dabrafenib and trametinib seems more feasible and tolerable than continuous triple therapy. The efficacy is promising and appears to be favorable over pembrolizumab monotherapy.

TRIAL REGISTRATION NUMBER

NCT02625337.

Enzymatic Methods for Mutation Detection in Cancer Samples and Liquid Biopsies

Low-level tumor somatic DNA mutations in tissue and liquid biopsies obtained from cancer patients can have profound implications for development of metastasis, prognosis, choice of treatment, follow-up, or early cancer detection. Unless detected, such low-frequency DNA alterations can misinform patient management decisions or become missed opportunities for personalized medicine. Next-generation sequencing technologies and digital-PCR can resolve low-level mutations but require access to specialized instrumentation, time, and resources. Enzymatic-based approaches to detection of low-level mutations provide a simple, straightforward, and affordable alternative to enrich and detect such alterations and is broadly available to low-resource laboratory settings. This review summarizes the traditional uses of enzymatic mutation detection and describes the latest exciting developments, potential, and applications with specific reference to the field of liquid biopsy in cancer.

Comparing single-target and multi-target approaches for postoperative circulating tumor DNA detection in stage II-III colorectal cancer patients

Circulating tumour DNA (ctDNA) detection for postoperative risk stratification in cancer patients has great clinical potential. However, low ctDNA abundances complicates detection. Multitarget (MT) detection strategies have been developed to increase sensitivity. Yet, empirical evidence supporting performance gains of MT vs. single‐target (ST) strategies in a postoperative setting is limited. We compared ctDNA detection in 379 paired plasma samples from 112 stage II–III colorectal cancer patients by ST digital PCR and MT sequencing of 16 patient‐specific variants. The strategies exhibited good concordance (90%, Cohen's Kappa 0.79), with highly correlated ctDNA quantifications (Pearson r = 0.985). A difference was observed in ctDNA detection preoperatively (ST 72/92, MT 88/92). However, no difference was observed immediately after surgery in recurrence (ST 11/22, MT 10/22) or nonrecurrence (both 2/34) patients. In serial samples, detection was similar within recurrence (ST 13/16, MT 14/16) and nonrecurrence (ST 3/49, MT 1/49) patients. Both approaches yielded similar lead times to standard‐of‐care radiology (ST 4.0 months, MT 4.1 months). Our findings do not support significant performance gains of the MT strategy over the ST strategy for postoperative ctDNA detection.

Error Characterization and Statistical Modeling Improves Circulating Tumor DNA Detection by Droplet Digital PCR

BACKGROUND

Droplet digital PCR (ddPCR) is a widely used and sensitive application for circulating tumor DNA (ctDNA) detection. As ctDNA is often found in low abundance, methods to separate low-signal readouts from noise are necessary. We aimed to characterize the ddPCR-generated noise and, informed by this, create a sensitive and specific ctDNA caller.

METHODS

We built 2 novel complimentary ctDNA calling methods: dynamic limit of blank and concentration and assay-specific tumor load estimator (CASTLE). Both methods are informed by empirically established assay-specific noise profiles. Here, we characterized noise for 70 mutation-detecting ddPCR assays by applying each assay to 95 nonmutated samples. Using these profiles, the performance of the 2 new methods was assessed in a total of 9447 negative/positive reference samples and in 1311 real-life plasma samples from colorectal cancer patients. Lastly, performances were compared to 7 literature-established calling methods.

RESULTS

For many assays, noise increased proportionally with the DNA input amount. Assays targeting transition base changes were more error-prone than transversion-targeting assays. Both our calling methods successfully accounted for the additional noise in transition assays and showed consistently high performance regardless of DNA input amount. Calling methods that were not noise-informed performed less well than noise-informed methods. CASTLE was the only calling method providing a statistical estimate of the noise-corrected mutation level and call certainty.

CONCLUSIONS

Accurate error modeling is necessary for sensitive and specific ctDNA detection by ddPCR. Accounting for DNA input amounts ensures specific detection regardless of the sample-specific DNA concentration. Our results demonstrate CASTLE as a powerful tool for ctDNA calling using ddPCR.

Accurate detection and quantification of SARS-CoV-2 genomic and subgenomic mRNAs by ddPCR and meta-transcriptomics analysis

SARS-CoV-2 replication requires the synthesis of a set of structural proteins expressed through discontinuous transcription of ten subgenomic mRNAs (sgmRNAs). Here, we have fine-tuned droplet digital PCR (ddPCR) assays to accurately detect and quantify SARS-CoV-2 genomic ORF1ab and sgmRNAs for the nucleocapsid (N) and spike (S) proteins. We analyzed 166 RNA samples from anonymized SARS-CoV-2 positive subjects and we observed a recurrent and characteristic pattern of sgmRNAs expression in relation to the total viral RNA content. Additionally, expression profiles of sgmRNAs, as determined by meta-transcriptomics sequencing of a subset of 110 RNA samples, were highly correlated with those obtained by ddPCR. By providing a comprehensive and dynamic snapshot of the levels of SARS-CoV-2 sgmRNAs in infected individuals, our results may contribute a better understanding of the dynamics of transcription and expression of the genome of SARS-CoV-2 and facilitate the development of more accurate molecular diagnostic tools for the stratification of COVID-19 patients.

Oranger et al use digital droplet PCR to develop an assay that provides a dynamic snapshot of the levels of SARS-CoV-2 sub-genomic messanger RNA in infected individuals. This has the potential to improve diagnostic accuracy for COVID-19