Annals of Laboratory Medicine最新文献

Background: NUP98 rearrangements (NUP98r), associated with various hematologic malignancies, involve more than 30 partner genes. Despite their clinical significance, reports on the clinicopathological characteristics of rare NUP98r remain limited. We investigated the characteristics of patients with myeloid neoplasms harboring NUP98r among those identified as having 11p15 translocation in chromosomal analysis.

Methods: We retrospectively reviewed results from bone marrow chromosomal analyses conducted between 2011 and 2023 and identified 15 patients with 11p15 translocation. Subsequently, NUP98r were evaluated using FISH and/or reverse transcription PCR, and clinical and laboratory data of the patients were analyzed.

Results: NUP98r were identified in 11 patients initially diagnosed as having AML (N=8), myelodysplastic syndrome (N=2), or chronic myelomonocytic leukemia (N=1), with a median age of 44 yrs (range, 4-77 yrs). Three patients had a history of chemotherapy. In total, five NUP98 fusions were identified: NUP98::DDX10 (N=3), NUP98::HOXA9 (N=2), NUP98::PSIP1 (N=2), NUP98::PRRX1 (N=1), and NUP98::HOXC11 (N=1). Patients with NUP98r exhibited a poor prognosis, with a median overall survival of 12.0 months (95% confidence interval [CI], 3.4-29.6 months) and a 5-yr overall survival rate of 18.2% (95% CI, 5.2%-63.7%).

Conclusions: Our study revealed the clinical and genetic characteristics of patients with myeloid neoplasms harboring rare and non-cryptic NUP98r. Given its association with poor prognosis, a comprehensive evaluation is crucial for identifying previously underdiagnosed NUP98r in patients with myeloid neoplasms.

Background: Bacteroides fragilis group (BFG) isolates are the most frequently isolated gram-negative anaerobic bacteria and exhibit higher levels of antimicrobial resistance than other anaerobic bacteria. Reliable susceptibility testing is needed because of reports of resistance to the most active antibiotics. Recently, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) introduced disk zone diameter breakpoints. We evaluated the disk diffusion test (DDT) for susceptibility testing of BFG isolates compared with the agar dilution method.

Methods: In total, 150 BFG isolates were collected from three institutes in Korea. The agar dilution method was conducted according to the CLSI guidelines. DDT was performed following the EUCAST guideline. Fastidious anaerobe agar supplemented with 5% defibrinated horse blood was used as the culture medium. Nine antimicrobials were evaluated: penicillin, cefoxitin, cefotetan, imipenem, meropenem, piperacillin-tazobactam, clindamycin, moxifloxacin, and metronidazole.

Results: The categorical agreement (CA) between the two methods was >90.0% for imipenem, meropenem, clindamycin, and metronidazole. However, the CA for piperacillintazobactam was low, at 83.2%. Major errors were found: 5.4% for imipenem, 7.4% for meropenem, and 12.8% for piperacillin-tazobactam. All minor errors were <10%. We propose using the area of technical uncertainty (ATU) zone-overlapping area for susceptible and resistant strains to reduce errors in the DDT. Outside the ATU, the CAs of cefoxitin, cefotetan, and piperacillin-tazobactam were >90.0%, whereas that of moxifloxacin was increased to 88.5%.

Conclusions: The DDT can be a useful alternative antimicrobial susceptibility test for BFG isolates when using the ATU zone to reduce errors.

We explored the utility of cerebrospinal fluid (CSF) circulating tumor DNA (ctDNA) sequencing as a noninvasive diagnostic tool for detecting central nervous system (CNS) involvement in patients with diffuse large B-cell lymphoma (DLBCL). Secondary CNS involvement in DLBCL, although rare (~5% of cases), presents diagnostic and prognostic challenges during systemic disease progression or relapse. Effective treatment is impeded by the blood-brain barrier. This was a prospective cohort study (Samsung Lymphoma Cohort Study III) involving 17 patients with confirmed CNS involvement. High-throughput sequencing was conducted using targeted gene panels designed to detect low-frequency variants and copy number alterations pertinent to lymphomas in ctDNA extracted from archived CSF samples. Despite challenges such as low DNA concentrations affecting library construction, the overall variant detection rate was 76%. Detected variants included those in genes commonly implicated in CNS lymphoma, such as MYD88. The study highlights the potential of CSF ctDNA sequencing to identify CNS involvement in DLBCL, providing a promising alternative to more invasive diagnostic methods such as brain biopsy, which are not always feasible. Further validation is necessary to establish the clinical utility of this method, which could significantly enhance the management and outcomes of DLBCL patients with suspected CNS involvement.

With Industry 4.0, big data and artificial intelligence have become paramount in the field of medicine. Electronic health records, the primary source of medical data, are not collected for research purposes but represent real-world data; therefore, they have various constraints. Although structured, laboratory data often contain unstandardized terminology or missing information. The major challenge lies in the lack of standardization of test results in terms of metrology, which complicates comparisons across laboratories. In this review, we delve into the essential components necessary for integrating real-world laboratory data into high-quality big data, including the standardization of terminology, data formats, equations, and the harmonization and standardization of results. Moreover, we address the transference and adjustment of laboratory results, along with the certification for quality of laboratory data. By discussing these critical aspects, we seek to shed light on the challenges and opportunities inherent to utilizing real-world laboratory data within the framework of healthcare big data and artificial intelligence.

Background: In 2022, the WHO and International Consensus Classification (ICC) published diagnostic criteria for myelodysplastic neoplasms (MDSs). We examined the influence of the revised diagnostic criteria on classifying MDSs in a large population.

Methods: We retrieved an open-source pre-existing dataset from cBioPortal and included 2,454 patients with MDS in this study. Patients were reclassified based on the new diagnostic 2022 WHO and ICC criteria. Survival analysis was performed using Cox regression to validate the new criteria and to assess risk factors.

Results: Based on the 2022 WHO criteria, 1.4% of patients were reclassified as having AML. The 2022 WHO criteria provide a superior prognostic/diagnostic model to the 2017 WHO criteria (Akaike information criterion, 14,152 vs. 14,516; concordance index, 0.705 vs. 0.681). For classifying MDS with low blast counts and SF3B1 mutation, a variant allele frequency cut-off of 5% (2022 WHO criteria) and the absence of RUNX1 co-mutation (2022 ICC criteria) are diagnostically relevant. For classifying MDSs with mutated TP53, a blast count cut-off of 10% (2022 ICC criteria) and multi-hit TP53 (2022 WHO criteria) are independent risk factors in cases with ≥ 10% blasts.

Conclusions: Our findings support the refinements of the new WHO criteria. We recommend the complementary use of the new WHO and ICC criteria in classifying SF3B1- and TP53-mutated MDSs for better survival prediction.

Background: Mass spectrometry (MS) methods exhibit higher accuracy and comparability in measuring serum C-peptide concentrations than immunoassays. We developed and validated a novel isotope dilution-ultraperformance liquid chromatography-tandem MS (ID-UPLC-MS/MS) assay to measure serum C-peptide concentrations.

Methods: Sample pretreatment involved solid-phase extraction, ion-exchange solid-phase extraction, and derivatization with 6-aminoquinolyl-N-hydroxysuccinimidylcarbamate (Cayman Chemical, Ann Arbor, Michigan, USA). We used an ExionLC UPLC system (Sciex, Framingham, MA, USA) and a Sciex Triple Quad 6500+ MS/MS system (Sciex) for electrospray ionization in positive-ion mode with multiple charge states of [M+3H]3+ and multiple reaction monitoring transitions. The total run time was 50 mins, and the flow rate was 0.20 mL/min. We evaluated the precision, trueness, linearity, lower limit of quantitation (LLOQ), carryover, and matrix effects. Method comparison with electrochemiluminescence immunoassay (ECLIA) was performed in 138 clinical specimens.

Results: The intra- and inter-run precision coefficients of variation were <5% and the bias values for trueness were <4%, which were all acceptable. The verified linear interval was 0.050-15 ng/mL, and the LLOQ was 0.050 ng/mL. No significant carryover or matrix effects were observed. The correlation between this ID-UPLC-MS/MS method and ECLIA was good (R=0.995, slope=1.564); however, the ECLIA showed a positive bias (51.8%).

Conclusions: The developed ID-UPLC-MS/MS assay shows acceptable performance in measuring serum C-peptide concentrations. This will be useful in situations requiring accurate measurement of serum C-peptide in clinical laboratories.

Machine learning (ML) is currently being widely studied and applied in data analysis and prediction in various fields, including laboratory medicine. To comprehensively evaluate the application of ML in laboratory medicine, we reviewed the literature on ML applications in laboratory medicine published between February 2014 and March 2024. A PubMed search using a search string yielded 779 articles on the topic, among which 144 articles were selected for this review. These articles were analyzed to extract and categorize related fields within laboratory medicine, research objectives, specimen types, data types, ML models, evaluation metrics, and sample sizes. Sankey diagrams and pie charts were used to illustrate the relationships between categories and the proportions within each category. We found that most studies involving the application of ML in laboratory medicine were designed to improve efficiency through automation or expand the roles of clinical laboratories. The most common ML models used are convolutional neural networks, multilayer perceptrons, and tree-based models, which are primarily selected based on the type of input data. Our findings suggest that, as the technology evolves, ML will rise in prominence in laboratory medicine as a tool for expanding research activities. Nonetheless, expertise in ML applications should be improved to effectively utilize this technology.

Background: Detecting monoclonal protein (M-protein), a hallmark of plasma cell disorders, traditionally relies on methods such as protein electrophoresis, immune-electrophoresis, and immunofixation electrophoresis (IFE). Mass spectrometry (MS)-based methods, such as matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) and electrospray ionization-quadrupole time-of-flight (ESI-qTOF) MS, have emerged as sensitive methods. We explored the M-protein-detection efficacies of different MS techniques.

Methods: To isolate immunoglobulin and light chain proteins, six types of beads (IgG, IgA, IgM, kappa, lambda, and mixed kappa and lambda) were used to prepare samples along with CaptureSelect nanobody affinity beads (NBs). After purification, both MALDI-TOF MS and liquid chromatography coupled with Synapt G2 ESI-qTOF high-resolution MS analysis were performed. We purified 25 normal and 25 abnormal IFE samples using NBs and MALDI-TOF MS (NB-MALDI-TOF).

Results: Abnormal samples showed monoclonal peaks, whereas normal samples showed polyclonal peaks. The IgG and mixed kappa and lambda beads showed monoclonal peaks following the use of daratumumab (an IgG/kappa type of monoclonal antibody) with both MALDI-TOF and ESI-qTOF MS analysis. The limits of detection for MALDI-TOF MS and ESI-qTOF MS were established as 0.1 g/dL and 0.025 g/dL, respectively. NB-MALDI-TOF and IFE exhibited comparable sensitivity and specificity (92% and 92%, respectively).

Conclusions: NBs for M-protein detection, particularly with mixed kappa-lambda beads, identified monoclonal peaks with both MALDI-TOF and ESI-qTOF analyses. Qualitative analysis using MALDI-TOF yielded results comparable with that of IFE. NB-MALDI-TOF might be used as an alternative method to replace conventional tests (such as IFE) to detect M-protein with high sensitivity.