Accumulation of circulating myeloid-derived suppressor cell subsets: predicting poor clinical efficacy and prognosis through T cell suppression in non-Hodgkin's lymphoma.

Myeloid-derived suppressor cells (MDSCs) are implicated in the regulation of immune responses closely associated with poor clinical outcomes in cancer. However, the MDSC subtypes in non-Hodgkin's lymphoma (NHL) have not been systematically investigated. So, we investigated the percentage of MDSC subsets in 78 newly diagnosed NHL patients by flow cytometry. The results showed that all MDSC subsets increased in NHL patients compared with healthy donors. Notably, MDSCs, monocytic MDSCs, and CD14 + CD66b + MDSCs significantly increased in NHL patients compared with those with lymphadenitis donors. polymorphonuclear MDSCs (PMN-MDSCs), early-stage MDSCs (e-MDSCs), and the International Prognostic Index were independent risk factors for poor clinical efficacy and were involved in constructing the nomogram for predicting clinical efficacy. Progression-free survival (PFS) was significantly shorter in patients with high level of MDSC subsets, and PMN-MDSCs emerged as an independent prognostic factor for PFS. PMN-MDSCs, e-MDSCs, and the International Prognostic Index were involved in constructing the nomogram for predicting PFS. Patients with a higher percentage of MDSCs, PMN-MDSCs, e-MDSCs, and CD14 + CD66b + MDSCs experienced a shorter overall survival compared with those with lower percentages. In addition, research on mechanisms found that T cell function was suppressed and mediated by the expansion of MDSCs via involving arginase-1 and interleukin-10 in vitro and in vivo. In conclusion, our study demonstrates that the increased circulating MDSC subsets predict poor clinical efficacy and prognosis in NHL, potentially involving T cell suppression through MDSC subset expansion. These findings indicate the potential of MDSC subsets as comprehensive diagnostic, prognostic biomarkers, and therapeutic targets for NHL.

[Analysis of High-Risk Clinical Factors of Early Death in Secondary Hemophagocytic Lymphohistiocytosis].

OBJECTIVE: To explore the high-risk clinical factors of early death in patients with secondary hemophagocytic lymphohistiocytosis (sHLH), and further identify the clinical factors related to the rapid progression of sHLH in the short term. METHODS: The clinical manifestations, laboratory examination and prognosis of sHLH patients were retrospectively analyzed. Continuous variables were grouped by median, univariate and multivariate Cox regression analysis and Kaplan-Meier survival curve were used to explore the risk factors affecting early death of sHLH. Then, a nomogram model was established with independent risk factors, Bootstrap resampling method was used for verification, and consistency index (C-index) and calibration curve were used to detect the prediction accuracy. RESULTS: A total of 126 sHLH patients were enrolled, with a median age of 48.5(16-88) years, including 74 males and 52 females. Fifty-five patients (43.6%) died within 30 days, including 39 males and 16 females. Univariate regression analysis showed that lymphocyte count <0.45×109/L, platelet count (PLT) <39.5×109/L, prothrombin time (PT)≥13.3 s, activated partial thromboplastin time (APTT)≥39.7 s, albumin (ALB) <25.9 g/L, lactate dehydrogenase (LDH)≥811 U/L, creatinine (Cr) ≥67 µmol/L and procalcitonin (PCT)≥0.61 ng/ml were risk factors for death within 30 days in sHLH patients. Multivariate regression analysis showed that lymphocyte count <0.45×109/L, APTT≥39.7 s and ALB <25.9 g/L were independent risk factors for death within 30 days in sHLH patients. A nomogram model was established based on the above three risk factors, its C-index was 0.683, and the calibration chart showed good agreement between the observed and predicted values of sHLH. CONCLUSIONS: Lymphopenia, prolonged APTT, and hypoalbuminemia are risk factors for early death of sHLH patients. Early identification and positive intervention are expected to reduce early mortality in sHLH patients. The nomogram model based on the above risk factors provides a method for clinicians to evaluate sHLH.

How to detect the rare BCR-ABL (e14a3) transcript: A case report and literature review.

The Philadelphia (Ph; BCR-ABL) chromosome originates from a translocation event between chromosomes 9 and 22, and results in the BCR-ABL fusion gene. In chronic myelogenous leukemia (CML), the BCR-ABL gene is mainly coded for by a major breakpoint cluster region (M-bcr, e13a2 and e14a2). However, in some patients, BCR-ABL genes are encoded by a minor (m)-bcr, e1a2, and a micro (µ)-bcr region, e19a2. These transcripts revealed a different clinical course. The present study described a CML patient whose cytogenetics and FISH analyses of bone marrow revealed a karyotype of 46, XY t(9,22) (q34;q11), while the commercial kits of quantitative PCR (qPCR) failed to detect the BCR-ABL fusion gene. Further multiplex Reverse transcription-PCR (RT-PCR) and sequencing analyses identified a rare e14a3 (b3a3) fusion transcript.

Neutrophil CD64 Index as a superior biomarker for early diagnosis of infection in febrile patients in the hematology department.

BACKGROUND: In the hematology department, the availability of biomarkers for early detection of infection is difficult to obtain. The present study aimed to compare the diagnostic values of neutrophil CD64 Index, procalcitonin (PCT), interleukin-6 (IL-6) and C-reactive protein (CRP) and to determine whether the combined analysis of these biomarkers offer stronger predictive power in the diagnosis for the infection of febrile patients. METHODS: Neutrophil CD64 Index, PCT, IL-6 and CRP levels were determined in 356 febrile patients in the hematology ward from May 2013 to May 2015. Sensitivity, specificity, positive and negative likelihood ratios, positive and negative predictive values, receiver operating characteristic (ROC) areas under the curve (AUC), and logistic regression analysis were determined to evaluate the diagnostic values of these biomarkers. RESULTS: The levels of the four biomarkers were higher in the infection patients (p<0.001), and the PCT and IL-6 were higher in the patients with positive microbial blood culture (p<0.01). The neutrophil CD64 Index, PCT, IL-6, CRP had AUCs of 0.95, 0.83, 0.75 and 0.73, respectively. The best cut-off value of the neutrophil CD64 Index to detect infections was 5.06, with high specificity (87.5%) and sensitivity (88.4%). Furthermore, neutrophil CD64 Index, PCT and IL-6 offered the best combination of diagnosis with sensitivity of 93.9% and an AUC of 0.95. In addition, the neutrophil CD64 Index may have a special value to assist the physician to diagnose infection in the neutropenic patients with fever. CONCLUSIONS: The neutrophil CD64 Index is useful for early identification of infections in febrile patients in the hematology department. The combined analysis of the CD64 Index, PCT and IL-6 could further improve its sensitivity.