Identification of immune-related genes and development of a prognostic model in mantle cell lymphoma.

Background: The immune landscape, prognostic model, and molecular variations of mantle cell lymphoma (MCL) remain unclear. Hence, an integrated bioinformatics analysis of MCL datasets is required for the development of immunotherapy and the optimization of targeted therapies. Methods: Data were obtained from the Gene Expression Omnibus (GEO) database (GSE32018, GSE45717 and GSE93291). The differentially expressed immune-related genes were selected, and the hub genes were screened by three machine learning algorithms, followed by enrichment and correlation analyses. Next, MCL molecular clusters based on the hub genes were identified by K-Means clustering, the probably approximately correct (PAC) algorithm, and principal component analysis (PCA). The landscape of immune cell infiltration and immune checkpoint molecules in distinct clusters was explored by single-sample gene-set enrichment analysis (ssGSEA) as well as the CIBERSORT and xCell algorithms. The prognostic genes and prognostic risk score model for MCL clusters were identified by least absolute shrinkage and selection operator (LASSO)-Cox analysis and cross-validation for lambda. Correlation analysis was performed to explore the correlation between the screened prognostic genes and immune cells or immune checkpoint molecules. Results: Four immune-related hub genes (CD247, CD3E, CD4, and GATA3) were screened in MCL, mainly enriched in the T-cell receptor signaling pathway. Based on the hub genes, two MCL molecular clusters were recognized. The cluster 2 group had a significantly worse overall survival (OS), with down-regulated hub genes, and a variety of activated immune effector cells declined. The majority of immune checkpoint molecules had also decreased. An efficient prognostic model was established, including six prognostic genes (LGALS2, LAMP3, ICOS, FCAMR, IGFBP4, and C1QA) differentially expressed between two MCL clusters. Patients with a higher risk score in the prognostic model had a poor prognosis. Furthermore, most types of immune cells and a range of immune checkpoint molecules were positively correlated with the prognostic genes. Conclusions: Our study identified distinct molecular clusters based on the immune-related hub genes, and showed that the prognostic model affected the prognosis of MCL patients. These hub genes, modulated immune cells, and immune checkpoint molecules might be involved in oncogenesis and could be potential prognostic biomarkers in MCL.

[Analysis of Non-genetic Factors Influencing the Overall Survival of Multiple Myeloma Patients].

OBJECTIVE: To explore the non-genetic factors of overall survival in patients with multiple myeloma (MM). METHODS: Kaplan-Meier survival curve, Log-rank test and Cox regression model were used to carry out univariate and multivariate retrospective analysis on clinical and laboratory parameters of 51 patients who were newly diagnosed with MM and had complete follow-up data in the Department of Hematology, the Affiliated Jiangning Hospital of Nanjing Medical University from November 2011 to October 2019. RESULTS: Fifty-one patients included 29 males and 22 females. Followed up to December 2019, 21 cases died and 30 cases survived. The univariate analysis showed that the overall survival time of the patients was influenced by age, disease stage, standard treatment, new drugs, maintenance treatment, hypercalcemia, globulin, albumin, and hemoglobin. The overall survival time of patients with age <65 years old, ISS stage I and II, standardized treatment, new drugs, normal or below normal blood calcium, normal or below normal globulin, albumin ≥35 g/L or hemoglobin ≥100 g/L was prolonged significantly (P<0.05). The multivariate analysis showed that maintenance treatment, hypercalcemia (≥2.6 mmol/L), and hemoglobin (<100 g/L) were independent risk factors influencing the prognosis of MM patients. CONCLUSION: Patients with blood calcium ≥2.6 mmol/L, hemoglobin <100 g/L, and who do not undergo regular maintenance therapy show a poor prognosis.

[Analysis of Transfusion Therapy Effectiveness in Patients with Myelodysplastic Syndrome].

OBJECTIVE: To investigate the transfusion effectiveness of suspended leucocyte depleted red blood cells (sld RBC) and fresh and irradiated apheresis platelets (fia Plt) in patients with myelodysplastic syndromes (MDS), and to explore the causes and mechanisms of ineffective platelet transfusion in patients with MDS. METHODS: Clinical data of 37 patients with confirmed MDS (WHO standard) such as the sex, age, Hb levels, Plt count, hemorrhage and coagulation functions, TEG and so on, were retrospectively analyzed. RESULTS: Among the 37 patients, 15 patients (40.5%) received only sld RBC transfusion, 9 patients (24.3%) received only fia Plt transfusion, and 13 patients (35.1%) received both transfusion. Among the 15 patients with only red blood cell transfusion, 3 patients were ineffective and the ineffectual transfusion rate was 20.0%. Among the 9 patients with only received platelet transfusion, 5 patients were ineffective and the ineffectual transfusion rate was 55.6%, there were significant statistical differences between the two groups (P﹤0.01). The red blood cell transfusion ineffective were 3 patients (23.1%) , the platelet transfusion ineffective were 8 patients (61.5%) and the both transfusion ineffective were 2 patients (15.4%) among the patients both transfusion . The positive rate of platelet antibody in MDS patients with ineffective platelet transfusion was 23.1%. Compared with the normal control group, Human P selectin (P-SelectinCD62P) (P＜0.001) and human anti-thrombin 3 antibody (AT-III Ab) (P＜0.001) significantly increased and human tissue factor pathway inhibitor (TFPI) significantly decreased (P＜0.05) in MDS patients with ineffective platelet transfusion. CONCLUSION: In the process of component transfusion for MDS patients, compared with the transfusion of red blood cells, the inefficiencies of platelet transfusion significantly increased, mainly due to the disorder of blood coagulation and the generation of platelet antibodies in MDS patients with ineffective platelet transfusion. Compared with the normal control group, human P selectin and human anti-thrombin 3 antibody significantly increase and human tissue factor pathway inhibitor significantly decreases in MDS patients with ineffective platelet transfusion. Human P selectin, human anti-thrombin 3 antibody and human tissue factor pathway inhibitor in molecular markers and fibrinolytic markers can be used as indicators of platelet transfusion time and efficiency in patients with MDS.