A Case of Type 1 Triallelic Patterns at D5S818, D18S51, D6S1043, and FGA Demonstrated by Short Tandem Repeat Analysis.

The triallelic pattern of short tandem repeat (STR) is rare; especially, the case where this pattern exists at 4 loci has not been reported. Here, we report the type 1 triallelic patterns at D5S818, D18S51, D6S1043, and FGA from a Chinese family, which were observed during our routine chimerism assays. Before hematopoietic stem cell transplantation, the blood sample of the certain patient was analyzed by performing chimerism analysis. A preliminary STR analysis was also performed on the samples of the patient's parents. STR signal data illustrated that the sum of the peak chart areas of the two types inherited from the father was basically the same as that of the mother, belonging to the type 1 triallelic pattern. In addition, the patient's elder sister's STR result appeared to be normal. Altogether, we presented a pedigree, in which the triallelic pattern was linked by inheritance in the family. This is the first reported case of the triallelic pattern at D5S818, D18S51, D6S1043, and FGA all around the world. We hope that in the future there will be any tools to achieve accurate verification against this possibility.

Distribution of killer cell immunoglobulin-like receptor (KIR) genes in a large, multi-centre cohort of Chinese donors.

BACKGROUND: The killer cell immunoglobulin-like receptor (KIR), which mediates the killing function of NK cells, is an attractive candidate for adoptive cellular therapy. The ethnic distribution for China provides a unique opportunity to investigate KIR gene distribution. AIM: The aim of this study was to explore the relationship between population history and the rapidly evolving KIR genetic diversity. SUBJECTS AND METHODS: 8050 Chinese donors from 184 hospitals were included to analyse frequency, haplotype, and B-content data of 16 KIR genes, by PCR-SSP for KIR genotyping. RESULTS: KIR gene carrier frequencies were found similar to those observed in other studies on Han, but different from Thais, Japanese, Africans, and populations of West Eurasian ancestry. High-frequency KIR genotype profiles found in the present population were consistent with other studies on Han populations but different from those conducted on other cohorts. The majority of our cohort carried group A KIR gene motifs. Additionally, populations with similar geographic locations in China were shown clustered together, while Hainan and Xinjiang provinces were slightly separated from these. CONCLUSION: The distribution of KIR genes varies by geographic region, and different ethnic groups may be a confounding factor of KIR diversity.

A case of acute lung injury in a peripheral blood stem cell donor mobilized with pegylated recombinant human granulocyte colony-stimulating factor.

Pegylated recombinant human granulocyte colony-stimulating factor (PEG-rhG-CSF) has been introduced for the mobilization of peripheral blood stem cells (PBSCs). However, no cases of acute lung injury (ALI) in healthy donors have been reported, and the underlying mechanisms remain poorly understood. We first reported a case of ALI caused by PEG-rhG-CSF in a healthy Chinese donor, characterized by hemoptysis, hypoxemia, and patchy shadows. Ultimately, hormone administration, planned PBSC collection, leukocyte debridement, and planned PBSC collection resulted in active control of the donor's ALI. The donor's symptoms improved without any adverse effects, and the PBSC collection proceeded without incident. Over time, the lung lesion was gradually absorbed and eventually returned to normal. PEG-rhG-CSF may contribute to ALI in healthy donors via mechanisms involving neutrophil aggregation, adhesion, and the release of inflammatory mediators in the lung. This case report examines the clinical manifestations, treatment, and mechanism of lung injury induced by PEG-rhG-CSF-mobilized PBSCs.

Investigation of HLA susceptibility alleles and genotypes with hematological disease among Chinese Han population.

Several genes involved in the pathogenesis have been identified, with the human leukocyte antigen (HLA) system playing an essential role. However, the relationship between HLA and a cluster of hematological diseases has received little attention in China. Blood samples (n = 123913) from 43568 patients and 80345 individuals without known pathology were genotyped for HLA class I and II using sequencing-based typing. We discovered that HLA-A*11:01, B*40:01, C*01:02, DQB1*03:01, and DRB1*09:01 were prevalent in China. Furthermore, three high-frequency alleles (DQB1*03:01, DQB1*06:02, and DRB1*15:01) were found to be hazardous in malignant hematologic diseases when compared to controls. In addition, for benign hematologic disorders, 7 high-frequency risk alleles (A*01:01, B*46:01, C*01:02, DQB1*03:03, DQB1*05:02, DRB1*09:01, and DRB1*14:54) and 8 high-frequency susceptible genotypes (A*11:01-A*11:01, B*46:01-B*58:01, B*46:01-B*46:01, C*01:02-C*03:04, DQB1*03:01-DQB1*05:02, DQB1*03:03-DQB1*06:01, DRB1*09:01-DRB1*15:01, and DRB1*14:54-DRB1*15:01) were observed. To summarize, our findings indicate the association between HLA alleles/genotypes and a variety of hematological disorders, which is critical for disease surveillance.

Comprehensive analysis of immune-related lncRNAs in AML patients uncovers potential therapeutic targets and prognostic biomarkers.

Purpose: The objective of this study was to provide theoretically feasible strategies by understanding the relationship between the immune microenvironment and the diagnosis and prognosis of AML patients. To this end, we built a ceRNA network with lncRNAs as the core and analyzed the related lncRNAs in the immune microenvironment by bioinformatics analysis. Methods: AML transcriptome expression data and immune-related gene sets were obtained from TCGA and ImmPort. Utilizing Pearson correlation analysis, differentially expressed immune-related lncRNAs were identified. Then, the LASSO-Cox regression analysis was performed to generate a risk signature consisting immune-related lncRNAs. Accuracy of signature in predicting patient survival was evaluated using univariate and multivariate analysis. Next, GO and KEGG gene enrichment and ssGSEA were carried out for pathway enrichment analysis of 183 differentially expressed genes, followed by drug sensitivity and immune infiltration analysis with pRRophetic and CIBERSORT, respectively. Cytoscape was used to construct the ceRNA network for these lncRNAs. Results: 816 common lncRNAs were selected to acquire the components related to prognosis. The final risk signature established by multivariate Cox and stepwise regression analysis contained 12 lncRNAs engaged in tumor apoptotic and metastatic processes: LINC02595, HCP5, AC020934.2, AC008770.3, LINC01770, AC092718.4, AL589863.1, AC131097.4, AC012368.1, C1RL-AS1, STARD4-AS1, and AC243960.1. Based on this predictive model, high-risk patients exhibited lower overall survival rates than low-risk patients. Signature lncRNAs showed significant correlation with tumor-infiltrating immune cells. In addition, significant differences in PD-1/PD-L1 expression and bleomycin/paclitaxel sensitivity were observed between risk groups. Conclusion: LncRNAs related to immune microenvironment were prospective prognostic and therapeutic options for AML.

The novel HLA-DQB1*06:475 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-DQB1*06:475 differs from HLA-DQB1*06:35 by one nucleotide in exon 2.

The novel HLA-A*30:01:24 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-A*30:01:24 differs from HLA-A*30:01:01:01 by one nucleotide in exon 3.

The novel HLA-C*04:490 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-C*04:490 differs from HLA-C*04:01:01:01 by one nucleotide in exon 3.

The novel HLA-C*03:04:74 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-C*03:04:74 differs from HLA-C*03:04:01:01 by one nucleotide in exon 6.

The novel HLA-B*35:563 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-B*35:563 differs from HLA-B*35:03:01:01 by one nucleotide in exon 4.

The novel HLA-B*15:638 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-B*15:638 differs from HLA-B*15:01:01:01 by one nucleotide in exon 2.

The novel HLA-DQB1*03:03:29 allele, identified by sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-DQB1*03:03:29 differs from HLA-DQB1*03:03:02:01 by one nucleotide in exon 2.

The novel HLA-C*15:02:58 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-C*15:02:58 differs from HLA-C*15:02:01:01 by one nucleotide in exon 1.

The novel HLA-A*02:1075 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-A*02:1075 differs from HLA-A*02:07:01:01 by one nucleotide in exon 5.

The novel HLA-C*07:1029 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-C*07:1029 differs from HLA-C*07:02:01:01 by one nucleotide in exon 5.

The novel HLA-B*35:568 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-B*35:568 differs from HLA-B*35:03:01:01 by one nucleotide in exon 4.

The novel HLA-A*02:07:22 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-A*02:07:22 differs from HLA-A*02:07:01:01 by one nucleotide in exon 3.

The novel HLA-DRB1*12:01:12 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-DRB1*12:01:12 differs from HLA-DRB1*12:01:01:01 by one nucleotide in exon 2.

The novel HLA-C*01:239 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-C*01:239 differs from HLA-C*01:02:01:01 by one nucleotide in exon 4.

The novel HLA-B*13:176 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-B*13:176 differs from HLA-B*13:02:01:01 by one nucleotide in exon 1.