Journal of Molecular Diagnostics最新文献

The molecular diagnosis of mismatch repair–deficient cancer syndromes is hampered by difficulties in sequencing the PMS2 gene, mainly owing to the PMS2CL pseudogene. Next-generation sequencing short reads cannot be mapped unambiguously by standard pipelines, compromising variant calling accuracy. This study aimed to provide a refined bioinformatic pipeline for PMS2 mutational analysis and explore PMS2 germline pathogenic variant prevalence in an unselected hereditary cancer (HC) cohort. PMS2 mutational analysis was optimized using two cohorts: 192 unselected HC patients for assessing the allelic ratio of paralogous sequence variants, and 13 samples enriched with PMS2 (likely) pathogenic variants screened previously by long-range genomic DNA PCR amplification. Reads were forced to align with the PMS2 reference sequence, except those corresponding to exon 11, where only those intersecting gene-specific invariant positions were considered. Afterward, the refined pipeline's accuracy was validated in a cohort of 40 patients and used to screen 5619 HC patients. Compared with our routine diagnostic pipeline, the PMS2_vaR pipeline showed increased technical sensitivity (0.853 to 0.956, respectively) in the validation cohort, identifying all previously PMS2 pathogenic variants found by long-range genomic DNA PCR amplification. Fifteen HC cohort samples carried a pathogenic PMS2 variant (15 of 5619; 0.285%), doubling the estimated prevalence in the general population. The refined open-source approach improved PMS2 mutational analysis accuracy, allowing its inclusion in the routine next-generation sequencing pipeline streamlining PMS2 screening.

This study evaluated the performance of cobas MTB and cobas MTB-RIF/INH for the diagnosis of tuberculosis and detection of rifampicin (RIF) and isoniazid (INH) resistance. Adults presenting with pulmonary tuberculosis symptoms were recruited in South Africa, Moldova, and India. Performance of cobas MTB was assessed against culture, whereas cobas MTB-RIF/INH was assessed using phenotypic drug susceptibility testing and whole-genome sequencing as composite reference standards. Xpert MTB/RIF (Xpert) or Xpert MTB/RIF Ultra (Ultra) was used as a comparator. The overall sensitivity and specificity of cobas MTB were 95% (95% CI, 93%–96%) and 96% (95% CI, 95%–97%). Among smear-negatives, the sensitivity of cobas MTB was 75% (95% CI, 66%–83%). Among participants tested with both cobas MTB and Xpert, sensitivity was 96% (95% CI, 94%–97%) for cobas MTB and 95% (95% CI, 93%–97%) for Xpert. Among participants tested with both cobas MTB and Ultra, sensitivity was 88% (95% CI, 81%–92%) for cobas MTB and 89% (95% CI, 83%–93%) for Ultra. Sensitivity and specificity of cobas MTB-RIF/INH for RIF and INH detection were 90% (95% CI, 84%–94%) and 100% (95% CI, 99%–100%), and 89% (95% CI, 84%–93%) and 99.5% (95% CI, 98%–100%), respectively. The cobas MTB and cobas MTB-RIF/INH assays exhibited high performance in a diverse population and present a suitable option for molecular detection of tuberculosis and RIF and INH resistance.

The multitarget stool RNA (mt-sRNA) test (ColoSense) is a noninvasive diagnostic test that screens for colorectal cancer and advanced adenomas in average-risk individuals aged 45 years and older. The mt-sRNA test incorporates a commercially available fecal immunochemical test, concentration of eight RNA transcripts, and participant-reported smoking status. As part of the CRC-PREVENT (Colorectal Cancer and Pre-Cancerous Adenoma Non-Invasive Detection Test) clinical trial, 12 analytical validation studies were conducted to assess analytical sensitivity, linearity, precision, interfering substances, cross-reactivity, carry-over, cross-contamination, and robustness. Analytical validation of the mt-sRNA test demonstrated limit of blank, limit of detection, and limit of quantification of <0.6, <0.7, and ≤2.5 copies/μL for all markers, respectively. The mt-sRNA test demonstrated linearity between 2.5 and 2500 copies/μL, and <20% coefficient of variation, and/or ≥95% concordance with regard to precision, interfering substances, carry-over, cross-contamination, and robustness. There was no significant impact of cross-reactivity from non–colorectal cancer diseases. These data provide a framework for laboratories to complete analytical validation for RNA-based panels that require premarket approval as a class III medical device from the US Food and Drug Administration.

Whole genome and whole transcriptome sequencing (WGTS) can accurately distinguish B-cell acute lymphoblastic leukemia (B-ALL) genomic subtypes. However, whether this is economically viable remains unclear. This study compared the direct costs and molecular subtype classification yield using different testing strategies for WGTS in adolescent and young adult/adult patients with B-ALL. These approaches were: (1) combined BCR::ABL1 by fluorescence in situ hybridization (FISH) + WGTS for all patients; and (2) sequential BCR::ABL1 FISH + WGTS contingent on initial BCR::ABL1 FISH test outcome. The cost of routine diagnostic testing was estimated using Medicare or hospital fees, and the additional cost of WGTS was evaluated from the health care provider perspective using time-driven activity-based costing with resource identification elicited from experts. Molecular subtype classification yield data were derived from literature sources. Parameter uncertainty was assessed through deterministic sensitivity analysis; additional scenario analyses were performed. The total per patient cost of WGTS was $4319 (all costs reported in US dollars); consumables accounted for 74% of the overall cost, primarily driven by sequencing-related consumables. The incremental cost per additional patient categorized into molecular subtype was $8498 for combined BCR::ABL1 FISH + WGTS for all patients and $5656 for initial BCR::ABL1 FISH + WGTS for select patients compared with routine diagnostic testing. A reduction in the consumable costs of WGTS or an increase in the yield of molecular subtype classification is favorable.

Tumor mutational burden (TMB) has been recognized as a predictive biomarker for immunotherapy response in several tumor types. Several laboratories offer TMB testing, but there is significant variation in how TMB is calculated, reported, and interpreted among laboratories. TMB standardization efforts are underway, but no published guidance for TMB validation and reporting is currently available. Recognizing the current challenges of clinical TMB testing, the Association for Molecular Pathology convened a multidisciplinary collaborative working group with representation from the American Society of Clinical Oncology, the College of American Pathologists, and the Society for the Immunotherapy of Cancer to review the laboratory practices surrounding TMB and develop recommendations for the analytical validation and reporting of TMB testing based on survey data, literature review, and expert consensus. These recommendations encompass pre-analytical, analytical, and postanalytical factors of TMB analysis, and they emphasize the relevance of comprehensive methodological descriptions to allow comparability between assays.

Next-generation sequencing (NGS) has proven clinical utility on disease management and serves as an important tool for genomic surveillance. Currently, hurdles surrounding its implementation, namely the complex and demanding analytical workflows, have impeded its widespread use in many laboratories. To address this challenge, the UCLA Molecular Microbiology and Pathogen Genomics Laboratory evaluated the performance of the Tecan MagicPrep NGS system, a commercial automated solution for library preparation for clinical whole-genome sequencing assays, against the Illumina Nextera DNA Flex Library Prep. Using 35 unique organisms (28 bacteria and 7 fungi) for various clinical applications, including microbial identification and genomic characterization, we compared the quantity and quality of the prepared libraries and the resulting sequences, and concordance of the overall results. We also assessed the impact of its implementation on laboratory workflow. The MagicPrep NGS produced higher library concentrations with smaller sizes, and correspondingly, higher molarity. Quality metrics of the sequences, however, demonstrated no significant impact on the overall results, producing 100% concordance with the reference method. Importantly, workflow analysis showed 5 hours less hands-on time per run with more flexibility. This evaluation study indicates that performance of the MagicPrep NGS is comparable to the Nextera DNA Flex with the added benefit of improving workflow efficiency and reducing labor for performing routine clinical microbial whole-genome sequencing tests.

This study describes the validation of a clinical RNA expression panel with evaluation of concordance between gene copy gain by a next-generation sequencing (NGS) assay and high gene expression by an RNA expression panel. The RNA Salah Targeted Expression Panel (RNA STEP) was designed with input from oncologists to include 204 genes with utility for clinical trial prescreening and therapy selection. RNA STEP was validated with the nanoString platform using remnant formalin-fixed, paraffin-embedded–derived RNA from 102 patients previously tested with a validated clinical NGS panel. The repeatability, reproducibility, and concordance of RNA STEP results with NGS results were evaluated. RNA STEP demonstrated high repeatability and reproducibility, with excellent correlation (r > 0.97, P < 0.0001) for all comparisons. Comparison of RNA STEP high gene expression (log2 ratio ≥ 2) versus NGS DNA-based gene copy number gain (copies ≥ 5) for 38 mutually covered genes revealed an accuracy of 93.0% with a positive percentage agreement of 69.4% and negative percentage agreement of 93.8%. Moderate correlation was observed between platforms (r = 0.53, P < 0.0001). Concordance between high gene expression and gene copy number gain varied by specific gene, and some genes had higher accuracy between assays. Clinical implementation of RNA STEP provides gene expression data complementary to NGS and offers a tool for prescreening patients for clinical trials.

Gene expression analysis is pivotal in cancer research and clinical practice. Although traditional methods lack spatial context, RNA in situ hybridization (RNA-ISH) is a powerful technique that retains spatial tissue information. Here, RNAscope score, RT–droplet digital PCR, and automated QuantISH and QuPath were used for quantifying RNA-ISH expression values from formalin-fixed, paraffin-embedded samples. The methods were compared using high-grade serous ovarian carcinoma samples, focusing on CCNE1, WFDC2, and PPIB genes. The findings demonstrate good concordance between automated methods and RNAscope, with RT–droplet digital PCR showing less concordance. Additionally, QuantISH exhibits robust performance, even for low-expressed genes like CCNE1, showcasing its modular design and enhancing accessibility as a viable alternative for gene expression analysis.