DeltaMSI: artificial intelligence-based modeling of microsatellite instability scoring on next-generation sequencing data.

BACKGROUND: DNA mismatch repair deficiency (dMMR) testing is crucial for detection of microsatellite unstable (MSI) tumors. MSI is detected by aberrant indel length distributions of microsatellite markers, either by visual inspection of PCR-fragment length profiles or by automated bioinformatic scoring on next-generation sequencing (NGS) data. The former is time-consuming and low-throughput while the latter typically relies on simplified binary scoring of a single parameter of the indel distribution. The purpose of this study was to use machine learning to process the full complexity of indel distributions and integrate it into a robust script for screening of dMMR on small gene panel-based NGS data of clinical tumor samples without paired normal tissue. METHODS: Scikit-learn was used to train 7 models on normalized read depth data of 36 microsatellite loci in a cohort of 133 MMR proficient (pMMR) and 46 dMMR tumor samples, taking loss of MLH1/MSH2/PMS2/MSH6 protein expression as reference method. After selection of the optimal model and microsatellite panel the two top-performing models per locus (logistic regression and support vector machine) were integrated into a novel script (DeltaMSI) for combined prediction of MSI status on 28 marker loci at sample level. Diagnostic performance of DeltaMSI was compared to that of mSINGS, a widely used script for MSI detection on unpaired tumor samples. The robustness of DeltaMSI was evaluated on 1072 unselected, consecutive solid tumor samples in a real-world setting sequenced using capture chemistry, and 116 solid tumor samples sequenced by amplicon chemistry. Likelihood ratios were used to select result intervals with clinical validity. RESULTS: DeltaMSI achieved higher robustness at equal diagnostic power (AUC = 0.950; 95% CI 0.910-0.975) as compared to mSINGS (AUC = 0.876; 95% CI 0.823-0.918). Its sensitivity of 90% at 100% specificity indicated its clinical potential for high-throughput MSI screening in all tumor types. Clinical Trial Number/IRB B1172020000040, Ethical Committee, AZ Delta General Hospital.

Cycle Threshold Probability Score for Immediate and Sensitive Detection of B.1.351 SARS-CoV-2 Lineage.

BACKGROUND: Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern associated with immune escape is important to safeguard vaccination efficacy. We describe the potential of delayed N gene amplification in the Allplex SARS-CoV-2 Assay (Seegene) for screening of the B.1.351 (20H/501.V2, variant of concern 2 [VOC.V2], South African SARS-CoV-2 variant) lineage. METHODS: In a study cohort of 397 consecutive polymerase chain reaction-positive samples genotyped by whole-genome sequencing, amplification curves of E/N/S-RdRP targets indicated delayedN vs E gene amplification characteristic of B.1.351. Logistic regression was used to calculate a VOC.V2 probability score that was evaluated as a separate screening test in an independent validation cohort vs sequencing. RESULTS: B.1.351 showed a proportionally delayed amplification of the  N vs E gene. In logistic regression, only N and E gene cycle thresholds independently contributed to B.1.351 prediction, allowing calculation of a VOC.V2 probability score with an area under the curve of 0.94. At an optimal dichotomous cutoff point of 0.12, the VOC.V2 probability score achieved 98.7% sensitivity at 79.9% specificity, resulting in a negative predictive value (NPV) of 99.6% and a positive predictive value of 54.6%. The probability of B.1.351 increased with an increasing VOC.V2 probability score, achieving a likelihood ratio of 12.01 above 0.5. A near-maximal NPV was confirmed in 153 consecutive validation samples. CONCLUSIONS: Delayed N vs E gene amplification in the Allplex SARS-CoV-2 Assay can be used for fast and highly sensitive screening of B.1.351.

Comparison of microsatellite instability detection by immunohistochemistry and molecular techniques in colorectal and endometrial cancer.

DNA mismatch repair deficiency (dMMR) testing is crucial for diagnosing Lynch syndrome and detection of microsatellite unstable (MSI) tumors eligible for immunotherapy. The aim of this study was to compare the relative diagnostic performance of three molecular MSI assays: polymerase chain reaction (PCR), MSI testing by Idylla and next-generation-sequencing (NGS) on 49 tumor samples (28 colorectal and 21 endometrial adenocarcinomas) versus immunohistochemistry (IHC). Discrepancies were investigated by MLH1 methylation analysis and integrated with germline results if available. Overall, the molecular assays achieved equivalent diagnostic performance for MSI detection with area under the ROC curves (AUC) of respectively 0.91 for Idylla and PCR, and 0.93 for NGS. In colorectal cancers with tumor cell percentages ≥ 30% all three molecular assays achieved 100% sensitivity and specificity (AUC = 1) versus IHC. Also, in endometrial cancers, all three molecular assays showed equivalent diagnostic performance, albeit at a clearly lower sensitivity ranging from 58% for Idylla to 75% for NGS, corresponding to negative predictive values from 78 to 86%. PCR, Idylla and NGS show similar diagnostic performance for dMMR detection in colorectal and endometrial cancers. Molecular MSI analysis has lower sensitivity for dMMR detection in endometrial cancer indicating that combined use of both IHC and molecular methods is recommended.Clinical Trial Number/IRB: B1172020000040, Ethical Committee, AZ Delta General Hospital.

Humoral Immune Response to SARS-CoV-2.

OBJECTIVES: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serology tests are clinically useful to document prior SARS-CoV-2 infections. Data are urgently needed to select assays with optimal sensitivity at acceptable specificity for antibody detection. METHODS: A comparative evaluation was performed of 7 commercial SARS-CoV-2 serology assays on 171 sera from 135 subjects with polymerase chain reaction-confirmed SARS-CoV-2 infection (71 hospitalized patients and 64 paucisymptomatic individuals). Kinetics of IgA/IgM/IgG seroconversion to viral N and S protein epitopes were studied from 0 to 54 days after onset of symptoms. Cross-reactivity was verified on 57 prepandemic samples. RESULTS: Wantai SARS-COV-2 Ab ELISA and Orient Gene COVID-19 IgG/IgM Rapid Test showed superior overall sensitivity for detection of SARS-CoV-2 antibodies. Elecsys Anti-SARS-CoV-2 assay and EUROIMMUN Anti-SARS-CoV-2 combined IgG/IgA showed acceptable sensitivity (>95%) vs the consensus result of all assays from 10 days post onset of symptoms. Wantai SARS-COV-2 Ab ELISA, Elecsys Anti-SARS-CoV-2 assay, and Innovita 2019-nCoV Ab rapid test showed least cross-reactivity, resulting in an optimal analytical specificity greater than 98%. CONCLUSIONS: Wantai SARS-COV-2 Ab ELISA and Elecsys Anti-SARS-CoV-2 assays are suitable for sensitive and specific detection of SARS-CoV-2 antibodies from 10 days after onset of symptoms.