[Objective] To compare next generation sequencing (NGS) library construction technology between probe hybridization capture and amplicon methods, and analyze the influencing factors of HLA genotyping resolution level and its prospects in clinical applications. [Methods] A total of 207 clinical samples with known typing results and samples from the proficiency testing plan were selected. The conformity rate of HLA genotyping results, allele coverage and typing data analysis indicators were confirmed, and the effects of two library construction methods on the level of HLA genotyping discrimination were compared. [Results] The concordance rate of 207 samples with the feedback results of PT or prior well-characterized HLA genotypes was 100%. Among them, 91 samples were captured using hybridization probe capture method. Compared with the original amplicon method, the hybridization probe capture method can distinguish the alleles of DRB1 and DPB1 that cannot be determined in 13 samples. The allelic imbalance of DRB1, DPA1, and DQB1 loci in 6 samples was resolved. Three samples were found to have missed detection of alleles at the DQA1 and DQB1 loci. [Conclusion] The performance indicators of hybridization probe capture and amplicon performance confirmation meet the requirements of clinical detection of HLA genotyping, which provides an experimental method and basis for clinical application.

【Objective】 To explore the risk factors for the production of anti-HLA antibodies in patients with hematological diseases before hematopoietic stemcell transplantation. 【Methods】 The results and clinical data of 1 008 patients with hematological diseases in our hospital who underwent anti-HLA antibody testing were collected by using Luminex technology platform before transplantation from 2016 to 2018 for statistical analysis. 【Results】 The total positive rate of anti-HLA antibodies in 1 008 patients was 24.08%. Multivariate analysis showed that independent risk factors associated with the production of anti-HLA antibodies included age≥30 years old(P=0.046, OR1.467, 95%CI1.007-2.136), time from disease diagnosis to antibody testing≥41 days(P=0.000, OR1.830, 95%CI1.306-2.565), initial platelet count<20×10⁹/L(P=0.020, OR1.543, 95%CI1.072-2.220), prior pregnancy(P=0.000, OR5.187, 95%CI3.689-7.293), transfusions before admission(P=0.001, OR1.762, 95%CI1.257-2.470)and total platelet transfusion volumes after admission≥30 U(P=0.000, OR2.352, 95%CI1.638-3.376). Age ≥30 years old(P=0.023, OR=1.839, 95%CI1.088-3.108)and prior pregnancy(P=0.042, OR=5.258, 95%CI1.062-26.038)are associated with the production of anti-HLA class Ⅰ and class Ⅱ antibodies, respectively. The time from disease diagnosis to antibody testing≥41 days(P=0.000, OR=2.873, 95%CI1.612-5.119), initial platelet count<20×10⁹/L(P=0.008, OR=2.164, 95%CI1.225-3.822), prior pregnancy(P=0.002, OR=6.734, 95%CI1.993-22.751), transfusions before admission(P=0.001, OR=2.746, 95%CI1.531-4.925)and total platelet transfusion volumes after admission>30 U(P=0.006, OR=3.459, 95%CI1.416-8.451)are associated with the production of anti-HLA class Ⅰ and Ⅱ antibodies. 【Conclusion】 Older age, longer course of disease, lower PLT count, history of pregnancy and blood transfusion, and higher total amount of PLT transfusion are risk factors which affect the production of anti-HLA antibodies.Therefore, it is advisable to test for anti-HLA antibodies according to the situation before transplantation, which is of great value in guiding donor selection, monitoring antibody changes and improving transplant prognosis.

Objective:To establish a linkage prediction model for human leukocyte antigen (HLA) DPA1-DPB1 and validate it by using clinical data and follow-up data from unrelated allogeneic hematopoietic stem cell transplantation donors and recipients, and to explore the clinical application value of the prediction model in transplantation prognosis.Methods:This is a retrospective study. Leveraging the artificial neural network algorithm of NetMHCⅡpan and the DPA1-DPB1 haplotype linkage database of the Chinese population established in our previous research, and incorporating the amino acid FASTA data of DPA1-DPB1 of all known sequences newly published by the Latest International Immunogenetics/Human Leukocyte Antigens, 47 DPA1-DPB1 linkage models were established. Employing next-generation sequencing technology based on the hybridization capture library construction method, HLA genotyping tests for HLA-A, -B, -C, DRB1, DQB1, DQA1, DRB3/4/5, DPB1, and DPA1 (9 loci) were performed on 250 donor-recipients pairs who underwent unrelated-donor hematopoietic stem cell transplantation in the Department of Hematology of the First Affiliated Hospital of Soochow University between January 2016 and September 2021. HLA typing data and clinical information of transplant donors and recipients were retrospectively analyzed to assess and predict the impact of permissive and non-permissive linkage mismatches of DPA1-DPB1 on transplantation prognosis. The Kaplan-Meier method with the log-rank test was applied to compare the survival curves of overall survival (OS) rates between different groups. Additionally, a competing risks model was utilized to compare the cumulative incidence of grade Ⅱ-Ⅳ acute graft-versus-host disease and non-relapse mortality (NRM) across groups. The area under the receiver operating characteristic curve was employed to compare the predictive performance of the established prediction model with that of the T-cell epitope (TCE) model.Results:According to the different hydrophilic and hydrophobic properties of amino acids, the DPA1-DPB1 linkage model is categorized into types Ⅰ-Ⅳ: type I consists of 6 hydrophobic types at P1-P8 plus hydrophilic type at P9; type Ⅱ includes 17 hydrophobic types; type Ⅲ comprises 9 amphiphilic types; and type Ⅳ consists of 15 hydrophilic types. According to the prediction model, DPA1-matched and DPB1-mismatched donor-recipient cases were classed into P1-matched or P1-mismatched groups. Compared with fully matched DPA1 and DPB1 cases, P1-mismatched patients had a 2-year OS rate of 75% (12/16) versus 96.2%(25/26) (χ2=4.13, P=0.04), and a NRM rate of 4/16 versus 0 (χ2=7.05, P<0.01). However, there was no statistically significant difference in the 2-year OS and NRM rates compared to DPA1 and DPB1 cases ( P>0.05). The prediction model established in this study demonstrated a larger area under the receiver operating characteristic curve for predicting the 2-year OS rate compared with the DPB1 TCE model ( Z=0.71, P=0.48). In donor-recipient cases where both DPA1 and DPB1 were mismatched, the 2-year OS rates decreased and the NRM increased in both P1-matched and P1-mismatched cases compared with fully matched DPA1 and DPB1. Moreover, P1-mismatched patients had a worse prognosis compared to P1-matched patients. Conclusion:The DPA1-DPB1 linkage prediction model established based on high-throughput next-generation sequencing technology can be used to predict the impact of HLA-DP mismatches on OS and NRM in transplantation, and the prediction performance is superior to the TCE model.

Background: SM-like (LSM) genes a family of RNA-binding proteins, are involved in mRNA regulation and can function as oncogenes by altering mRNA stability. However, their roles in B-cell progression and tumorigenesis remain poorly understood. Methods: We analyzed gene expression profiles and overall survival data of 123 patients with mantle cell lymphoma (MCL). The LSM index was developed to assess its potential as a prognostic marker of MCL survival. Results: Five of the eight LSM genes were identified as potential prognostic markers for survival in MCL, with particular emphasis on the LSM.index. The expression levels of these LSM genes demonstrated their potential utility as classifiers of MCL. The LSM.index-high group exhibited both poorer survival rates and lower RNA levels than did the overall transcript profile. Notably, LSM1 and LSM8 were overexpressed in the LSM.index-high group, with LSM1 showing 2.5-fold increase (p < 0.001) and LSM8 depicting 1.8-fold increase (p < 0.01) than those in the LSM.index-low group.Furthermore, elevated LSM gene expression was associated with increased cell division and RNA splicing pathway activity. Conclusions The LSM.index demonstrates potential as a prognostic marker for survival in patients with MCL. Elevated expression of LSM genes, particularly LSM1 and LSM8, may be linked to poor survival outcomes through their involvement in cell division and RNA splicing pathways. These findings suggest that LSM genes may contribute to the aggressive behavior of MCL and represent potential targets for therapeutic interventions.

Background: SM-like (LSM) genes a family of RNA-binding proteins, are involved in mRNA regulation and can function as oncogenes by altering mRNA stability. However, their roles in B-cell progression and tumorigenesis remain poorly understood. Methods: We analyzed gene expression profiles and overall survival data of 123 patients with mantle cell lymphoma (MCL). The LSM index was developed to assess its potential as a prognostic marker of MCL survival. Results: Five of the eight LSM genes were identified as potential prognostic markers for survival in MCL, with particular emphasis on the LSM.index. The expression levels of these LSM genes demonstrated their potential utility as classifiers of MCL. The LSM.index-high group exhibited both poorer survival rates and lower RNA levels than did the overall transcript profile. Notably, LSM1 and LSM8 were overexpressed in the LSM.index-high group, with LSM1 showing 2.5-fold increase (p < 0.001) and LSM8 depicting 1.8-fold increase (p < 0.01) than those in the LSM.index-low group.Furthermore, elevated LSM gene expression was associated with increased cell division and RNA splicing pathway activity. Conclusions The LSM.index demonstrates potential as a prognostic marker for survival in patients with MCL. Elevated expression of LSM genes, particularly LSM1 and LSM8, may be linked to poor survival outcomes through their involvement in cell division and RNA splicing pathways. These findings suggest that LSM genes may contribute to the aggressive behavior of MCL and represent potential targets for therapeutic interventions.

Background: SM-like (LSM) genes a family of RNA-binding proteins, are involved in mRNA regulation and can function as oncogenes by altering mRNA stability. However, their roles in B-cell progression and tumorigenesis remain poorly understood. Methods: We analyzed gene expression profiles and overall survival data of 123 patients with mantle cell lymphoma (MCL). The LSM index was developed to assess its potential as a prognostic marker of MCL survival. Results: Five of the eight LSM genes were identified as potential prognostic markers for survival in MCL, with particular emphasis on the LSM.index. The expression levels of these LSM genes demonstrated their potential utility as classifiers of MCL. The LSM.index-high group exhibited both poorer survival rates and lower RNA levels than did the overall transcript profile. Notably, LSM1 and LSM8 were overexpressed in the LSM.index-high group, with LSM1 showing 2.5-fold increase (p < 0.001) and LSM8 depicting 1.8-fold increase (p < 0.01) than those in the LSM.index-low group.Furthermore, elevated LSM gene expression was associated with increased cell division and RNA splicing pathway activity. Conclusions The LSM.index demonstrates potential as a prognostic marker for survival in patients with MCL. Elevated expression of LSM genes, particularly LSM1 and LSM8, may be linked to poor survival outcomes through their involvement in cell division and RNA splicing pathways. These findings suggest that LSM genes may contribute to the aggressive behavior of MCL and represent potential targets for therapeutic interventions.

Objective The aim of this study was to identify macrophage related genes(MRGs)in liver cancer and construct a prognostic risk prediction model for liver cancer.Methods The liver cancer scRNA-seq data from the GEO database were down-loaded to identify genes specifically expressed in macrophages as MRGs.The GO and KEGG functional enrichment analyses on MRGs were conducted.In the TCGA-LIHC dataset of the TCGA database,multiple random sampling single factor Cox regression for single-factor Cox regression,LASSO regression,and multivariate Cox regression analyses were employed to identify MRGs for liver cancer prognosis prediction,and a liver cancer prognostic prediction model was constructed.Results The results obtained 8 major cell types,including those containing macrophages through clustering using scRNA-seq data from the GEO database.The proportion of macrophages in the immune microenvironment of liver cancer was significantly higher than that of normal tissues(P=0.016),and genes such as SPP1,RNASE1,and MMP9 were highly expressed.Multiple metabolic pathways,including purine metabolism,citric acid cycle,and drug metabolism cytochrome P450 were activated in liver cancer-associated macrophages.This study identified 777 MRGs from liver cancer scRNA-seq(LogFC＞0.25,P＜0.05),which mainly involved in functions such as actin binding and regula-tion of immune receptor activity.Seven MRGs,including ATP1B3,ATP6V0B,HBEGF,KLF2,NR1H3,RAB10,and SPP1 were select-ed from the 169 stable prognostic genes(P＜0.05)for the construction of the prognosis model.The AUC values for the 1,3,and 5-year survival outcomes of the model in the TCGA liver cancer cohort were 0.791,0.791,and 0.751,respectively.In the validation ICGC cohort,they were 0.614,0.682,and 0.688,respectively,demonstrating good predictive performance.In liver cancer patients with high prognosis risk scores,the expression of macrophages M0,neutrophils,and regulatory T cells was higher(P＜0.05),and im-munosuppression and immune activation coexisted.Conclusion Liver cancer MRGs can serve as potential biomarkers for predicting the prognosis of liver cancer patients.These liver cancer MRGs are mainly associated with actin binding,immune receptor activity,and infiltration of various immune cells.

Objective:Establish the decision threshold value of mean fluorescence intensity of anti-human leukocyte antigen(HLA)antibody through statistical analyzing the results of international proficiency testing(PT)organized by American Society for Histocompatibility and Immunogenetics(ASHI).Methods:Single antigen reagent and liquid chip(Luminex)technique were used to detect anti-HLA antibody. A retrospective analysis of the HLA antibody PT results of 55 quality control samples from 11 times organized by ASHI from 2012 to 2019 was reviewed.Results:Among 79 kinds of HLA-I antibodies, 21, 43 and 15 types of HLA-A, B and Cw antibodies were detected respectively, while among 44 kinds of HLA-Ⅱ antibodies, 18, 7 and 19 types of HLA-DRB1, DQB1 and DPB1 antibodies were detected respectively. After analyzing the MFI detection value of different specific antibodies in each PT samples at our laboratory and the coincidence rate of the negative / positive results judged by ASHI through summarizing the results of multicenter participating in the same period, MFI values of HLA antibody were arranged from high to low into the intervals of possible saturation value, positive decision value, positive judgment threshold value, suspicious positive reference value and suspicious negative reference value , according to the coincidence rate of 95%, 90%, 80%, 79%~50% and <50%.Thus, the decision limit value table of HLA specific antibody at our laboratory was established. And 42 kinds of HLA antibody types were detected with complete data.When the MFI values of various HLA-I or HLA-Ⅱ antibodies are found to be 80% or more in the table, it can be used to judge the detection of HLA antibodies. When HLA antibody MFI value reaches the positive decision value, it may have a certain guiding significance for clinical diagnosis and treatment. And when antibody MFI value reaches the saturation value and lies in the suspicious positive or suspicious negative reference threshold, it just suggests that the clinical need for dynamic follow-up of anti-HLA antibody detection.Conclusions:The decision limit value of MFI of laboratory HLA antibody is established based on the international PT experimental results, which is of reference value for the interpretation of experimental results and clinical diagnosis and treatment. A transplant ation center should pay attention to the quality control of comparison test between laboratories in the detection of HLA antibodies.

Objective: To analyze family-based haplotype frequencies of HLA-A, -B, -C, -DRB1 and -DQB1 genes and their clinical significance. Methods: The data of HLA genotyping in 3568 families undergoing related haploidentical transplantation between 2012 and 2017 at the First Affiliated Hospital of Soochow University were retrospectively evaluated. The HLA genotyping was performed by PCR amplification with sequence-based typing (PCR-SBT) and sequence-specific oligonucleotide probe (PCR-SSOP) methods. The family genetic analysis and haplotype frequencies were also investigated. Results: All the families were divided into 3 groups, including group1 of 1 422 entire families; group2 of 1 310 patients and either of their parents or one of their children; group3 of 836 patients and their HLA≥5/10 matched sibling donors. In the haplotypes with frequencies greater than 0.1% in group1+ group2, the frequency of A*11∶01-B*40∶01-C*03∶04-DRB1*11∶01-DQB1*03∶01, A*02∶07-B*51∶01-C*14∶02-DRB1*09:01-DQB1*03∶03 were significantly different between group1 and group2 (P=0.029, 0.033) . The frequency of A*11∶01-B*46∶01-C*01∶02∶01G-DRB1*09∶01-DQB1*03∶03 was significantly different between group1 and group3 (P=0.035) . The frequency of A*02∶01-B*40∶01-C*07∶02-DRB1*09∶01-DQB1*03∶03 was significantly different between group1 and group2 (P=0.034) , or group1 and group3 (P=0.034) . The frequency of A*24∶02-B*13∶01-C*03∶04-DRB1*12∶02-DQB1*03:01 was significantly different between group2 and group3 (P=0.046) . Conclusion In this study, we summarize the prevalence of haplotype frequencies in terms of HLA-A, -B, -C, -DRB1 and-DQB1. Based on the database of family haplotype analysis, patients and donor candidates are sorted with matched HLA genotype while unmatched HLA haplotype. Even in patients without entire family information, HLA haplotype analysis assists in choosing the optimal related or unrelated donors.

Objective To study the effect of psychological intervention combined with the analysis of Budesonide and Formoterol Fumarate Powder for Inhalation in treatment of chronic obstructive pulmonary disease. Methods 100 patients with chronic obstructive pulmonary disease treated in our hospital from February 2015 to March 2016 were selected and randomly divided into the control group and the experimental group, with 50 patients in each group. The control group was treated with the Budesonide and Formoterol Fumarate Powder for Inhalation treatment,the experimental group on the basis of psychological intervention on the mental status of patients and patients,strengthen communication and exchanges, increase confidence in the treatment and the treatment compliance of patients. Results After treatment, the SGRQ score of the experimental group was (57.33±16.81), and the score of the control group was (43.86±12.68) points, with statistical difference (P<0.05). The scores of depression and anxiety in the experimental group were significantly better than those in the control group,with statistical difference(P<0.05). Conclusion Budesonide and Formoterol Fumarate Powder for Inhalation combined with mental intervention in the treatment of chronic obstructive pulmonary disease can significantly improve the patients, improve the quality of life, help patients recover as soon as possible, has clinical significance.