Assessment of Bone Marrow Involvement in B-Cell non-Hodgkin Lymphoma Using Immunoglobulin Gene Rearrangement Analysis with Next-Generation Sequencing.

BACKGROUND: Assessment of bone marrow involvement (BMI) in non-Hodgkin lymphoma (NHL) is crucial for determining patient prognosis and treatment strategy. We assessed the prognostic value of next-generation sequencing (NGS)-based immunoglobulin (Ig) gene clonality analysis as an ancillary test for BMI evaluation in NHL. METHODS: A retrospective cohort of 124 patients newly diagnosed with B-cell NHL between 2019 and 2022 was included. NGS-based Ig clonality analysis was conducted using LymphoTrak IGH FR1 Assay and IGK Assay (Invivoscribe Technologies, San Diego, CA, USA) on BM aspirate samples, and the results were compared with those of histopathological BMI (hBMI). RESULTS: Among the 124 patients, hBMI was detected in 16.9% (n = 21). The overall agreement of BMI between Ig clonality analyses and histopathological analysis for IGH, IGK, and either IGH or IGK was 86.3%, 92.7%, and 90.3%. The highest positive percent agreement was observed with clonal rearrangements of either IGH or IGK gene (90.5%), while the highest negative percent agreement was observed with clonal rearrangement of IGK gene (96.1%). For the prediction of hBMI, positive prediction value ranged between 59.1% and 80.0% and the negative prediction value ranged between 91.3% and 97.9%. CONCLUSION: NGS-based clonality analysis is an analytic platform with a substantial overall agreement with histopathological analysis. Assessment of both IGH and IGK genes for the clonal rearrangement analysis could be considered for the optimal diagnostic performance of BMI detection in B-cell NHL.

Identification of a Complex Karyotype Signature with Clinical Implications in AML and MDS-EB Using Gene Expression Profiling.

Complex karyotype (CK) is associated with a poor prognosis in both acute myeloid leukemia (AML) and myelodysplastic syndrome with excess blasts (MDS-EB). Transcriptomic analyses have improved our understanding of the disease and risk stratification of myeloid neoplasms; however, CK-specific gene expression signatures have been rarely investigated. In this study, we developed and validated a CK-specific gene expression signature. Differential gene expression analysis between the CK and non-CK groups using data from 348 patients with AML and MDS-EB from four cohorts revealed enrichment of the downregulated genes localized on chromosome 5q or 7q, suggesting that haploinsufficiency due to the deletion of these chromosomes possibly underlies CK pathogenesis. We built a robust transcriptional model for CK prediction using LASSO regression for gene subset selection and validated it using the leave-one-out cross-validation method for fitting the logistic regression model. We established a 10-gene CK signature (CKS) predictive of CK with high predictive accuracy (accuracy 94.22%; AUC 0.977). CKS was significantly associated with shorter overall survival in three independent cohorts, and was comparable to that of previously established risk stratification models for AML. Furthermore, we explored of therapeutic targets among the genes comprising CKS and identified the dysregulated expression of superoxide dismutase 1 (SOD1) gene, which is potentially amenable to SOD1 inhibitors.

Implications of the 5th Edition of the World Health Organization Classification and International Consensus Classification of Myeloid Neoplasm in Myelodysplastic Syndrome With Excess Blasts and Acute Myeloid Leukemia.

The fifth edition of the WHO classification (2022 WHO) and the International Consensus Classification (2022 ICC) of myeloid neoplasms have been recently published. We reviewed the changes in the diagnosis distribution in patients with MDS with excess blasts (MDS-EB) or AML using both classifications. Forty-seven patients previously diagnosed as having AML or MDS-EB with available mutation analysis data, including targeted next-generation and RNA-sequencing data, were included. We reclassified 15 (31.9%) and 27 (57.4%) patients based on the 2022 WHO and 2022 ICC, respectively. One patient was reclassified as having a translocation categorized as a rare recurring translocation in both classifications. Reclassification was mostly due to the addition of mutation-based diagnostic criteria (i.e., AML, myelodysplasia-related) or a new entity associated with TP53 mutation. In both classifications, MDS diagnosis required the confirmation of multi-hit TP53 alterations. Among 14 patients with TP53 mutations, 11 harbored multi-hit TP53 alterations, including four with TP53 mutations and loss of heterozygosity. Adverse prognosis was associated with multi-hit TP53 alterations (P=0.009) in patients with MDS-EB, emphasizing the importance of detecting the mutations at diagnosis. The implementation of these classifications may lead to the identification of different subtypes from previously heterogeneous diagnostic categories based on genetic characteristics.

Performance evaluation and clinical impact of the Oncomine Myeloid Research Assay for gene expression analysis in myeloid haematologic malignancies.

AIM: Gene expression analysis facilitates the detection of diagnostic and prognostic biomarkers for myeloid haematological malignancies. The Oncomine Myeloid Research Assay (OMA; Thermo Fisher Scientific, Massachusetts, USA) provides a comprehensive analysis of gene expression of five target genes, along with gene alteration and fusion. Here, we present the performance of the OMA for gene expression analysis. METHODS: In total, 53 RNA samples from patients diagnosed with acute myeloid leukaemia (AML) or myelodysplastic syndrome were included. Of these 53 samples, 3 were evaluated for reproducibility and 50 were evaluated for comparison with RNA-sequencing (RNA-seq). The prognostic impact of the gene expression profile produced by both OMA and RNA-seq in AML was investigated using follow-up data from 33 patients with AML. RESULTS: The OMA showed good intrarun and interrun reproducibility. Compared with the RNA-seq results, high correlations were found in BAALC, MECOM and WT1 (all r>0.9), with moderate correlations in MYC (r=0.75, p<0.001) and SMC1A (r=0.42, p=0.002). The agreement between OMA and RNA-seq in classifying the dysregulated expression group was almost perfect, except for SMC1A (κ=0.175). Among these five genes, only BAALC showed a significant clinical impact in patients with AML. Patients with high BAALC expression showed significantly shorter overall survival based on both OMA (p=0.037) and RNA-seq (p=0.003). CONCLUSIONS: OMA gene expression analysis offers reproducible and accurate gene expression data for most targeted genes and demonstrates the utility of BAALC expression as a prognostic marker in AML.

Association between Breastfeeding and Prevalence of Diabetes in Korean Parous Women: The Korea National Health and Nutrition Examination Survey, 2010-2014.

BACKGROUND: It is well known that breastfeeding has a significant impact on the health of mothers and children. With the growing importance of breastfeeding, the present study aimed to investigate the relationship between breastfeeding and the prevalence of diabetes in Korean parous women. METHODS: The data of 5,448 premenopausal parous women aged 20-49 years who agreed to participate in the 5th- 6th Korea National Health and Nutrition Examination Survey were analyzed in this study. Control group included women who had not breastfed. The subjects who had breastfed were classified into three groups based on the duration of breastfeeding: 0-6 months, 6-12 months, and >12 months. The variables included age, body mass index, education level, income, alcohol drinking, smoking, family history of diabetes, use of oral contraceptives, the number of pregnancies, and regular exercise. RESULTS: Among the subjects, the prevalence of diabetes was significantly lower in women who had breastfed compared to those who had not, with an odds ratio of 0.534 (95% confidence interval [CI], 0.289-0.976) in women who breastfed for 0-6 months and 0.575 (95% CI, 0.321-0.990) in women who breastfed for 6-12 months (both P<0.05). CONCLUSION: The present study found a reduced prevalence of diabetes in women who had breastfed compared to those who had not. However, no association between the duration of breastfeeding and the prevalence of diabetes could be found.

Relationship between Marital Status and Metabolic Syndrome in Korean Middle-Aged Women: The Sixth Korea National Health and Nutrition Examination Survey (2013-2014).

BACKGROUND: This study aimed to investigate the relationship between marital status and the incidence of metabolic syndrome in Korean middle-aged women. METHODS: Based on data from the sixth Korea National Health and Nutrition Examination Survey (2013-2014), 3,225 women aged 40-69 years were subjected to the analysis. Marital status was categorized as married, unmarried, separated, widowed, or divorced. The odds ratios (ORs) for metabolic syndrome were calculated based on marital status. After adjustment for age, income level, education level, alcohol intake, smoking status, leisure physical activity, menopause status, daily calories, and fat intake, changes in the OR for metabolic syndrome based on marital status were examined by multivariate logistic regression analysis. RESULTS: The OR for metabolic syndrome in the widowed group to the married group was 4.818 (95% confidence interval [CI], 3.861-6.002; P<0.001) and that after adjustment of age, economic level, education level, alcohol intake, smoking status, physical activity, menopause status, total daily calories, and fat intake was 2.141 (CI, 1.432-3.199; P<0.001), both of which were statistically significant. The OR for metabolic syndrome in the unmarried group to the married group was 0.246 (CI, 0.141-0.431; P<0.001) after adjustment of all components. On the contrary, the ORs of the separated group and the divorced group to the married group were not significant. CONCLUSION: In comparison with the married middle-aged group, the widowed middle-aged group tended to have a higher risk of metabolic syndrome, which is speculated to be related to socioeconomic factors and health behavior.