Using next-generation sequencing technology, we analysed 17-locus typing data from 10,059 healthy Chinese individuals to establish common and well-documented categories for HLA-E, -F, -G, -H, MICA and MICB alleles. In total, we identified 8 HLA-E, 5 HLA-F, 8 HLA-G, 15 HLA-H, 39 MICA and 27 MICB alleles. Alleles with frequencies greater than 10% included E*01:03, E*01:01, F*01:01, G*01:01, G*01:04, H*01:01, H*02:07, MICA*010:01, MICA*002:01, MICA*008:04, MICA*008:01, MICB*005:02 and MICB*002:01. Among the globally common alleles E*01:03 and E*01:01, E*01:03 was more prevalent than E*01:01 in Chinese and East Asian populations, whereas the opposite pattern was observed in African, European, Admixed American and South Asian populations. Subsequently, we identified 24 types of 17-locus homozygous haplotypes. Although these homozygotes were present in only 0.53% of individuals, their cumulative haplotype frequency reached 12.57%. As the number of loci increased from 3 to 17, the homozygosity carrier rate declined from 1.46% to 0.53%, with a pronounced decrease observed after inclusion of the DPB1 locus. Notably, most of the homozygotes identified in this study had not been reported in the 18th International HLA & Immunogenetics Workshop. For example, 26 of 27 types of 11-locus homozygotes were previously unrecorded. The establishment of a database for HLA-E, -F, -G, -H, MICA and MICB alleles, as well as the distribution of homozygotes in the Chinese population, will provide valuable resources for genetic research, disease susceptibility, transplantation and cell therapy.

AIM:Observational studies have suggested an association between celiac disease and thyroid dysfunction, but their causal relationship has not yet been established. METHODS:Summary statistics for celiac disease were retrieved from the FinnGen Consortium, thyroid hormone and antibody data were obtained from the ThyroidOmics Consortium, and genetic variants associated with hyperthyroidism and hypothyroidism were sourced from the UK Biobank. MR statistical analyses used the inverse variance weighted algorithm, followed by various sensitivity analyses and reliability evaluations. RESULTS:Genetic proxied celiac disease was significantly associated with increased free thyroxine (FT4) and thyroid peroxidase antibody (TPOAb) levels and decreased free triiodothyronine (FT3)/FT4 ratio, whereas the causality of this common enteropathy on thyroid stimulating hormone (TSH), FT3, total triiodothyronine (TT3), and TT3/FT4 ratio (and vice versa) is unfounded. Moreover, the findings of MR analysis tend to favor the causality of celiac disease for hyperthyroidism, but not hypothyroidism. CONCLUSION:By leveraging large GWAS consortia datasets, our MR study indicates that the genetic liability to celiac disease is suggestively detrimental to the homeostasis of FT4 and TPOAb levels and FT3/FT4 ratio. Our findings provide caution regarding the risk of hyperthyroidism but not hypothyroidism for individuals suffering from celiac disease.

Natural killer (NK) cells are the primary innate lymphoid cells responsible for antiviral defense and tumor immunosurveillance. However, further clarification is needed on how to prevent their over-activation and maintain their quiescence during development. In this study, we present evidence that liver kinase B1 (Lkb1) functions as a critical metabolic checkpoint, regulating NK cell survival and preserving their effective tumor immunosurveillance capabilities. Genetic ablation of Lkb1 led to mitochondrial dysfunction and impaired autophagy, resulting in reactive oxygen species (ROS)-dependent cell death. Additionally, Lkb1 deficiency disrupted iron homeostasis, causing iron overload and the subsequent accumulation of cytotoxic lipid ROS. Targeted interventions aimed at inhibiting ROS accumulation or iron overload significantly rescued the survival defect in Lkb1-deficient NK cells. Notably, these regulatory functions could not be rescued by pharmacologic AMPK activation or mTORC1 inhibition. Furthermore, the deletion of Lkb1 increased the expression of inhibitory receptors PD-1 and TIGIT, further impairing NK cell-mediated tumor surveillance. Our investigation collectively highlights the critical role of Lkb1 in maintaining NK cell quiescence through the coordinated regulation of metabolic fitness and redox balance, offering new insights into the metabolic programming of NK cell development and function.

Here, the Chinese catalogue of common and well-documented (CWD) HLA alleles was updated on the basis of the database of more than 2 million unrelated volunteer donors in the China Marrow Donor Program (CMDP), and the Chinese common, intermediate and well-Documented (CIWD) 2025 catalogue was also formed according to the new criteria of CIWD 3.0.0. The previous China CWD 2018 catalogue designated 676 alleles at the HLA-A, -B, -C, -DRB1 and -DQB1 loci as being CWD, whereas China CWD 2025 catalogue designates 1144 alleles at the HLA-A, -B, -C, -DRB1 and -DQB1 loci as being CWD. In particular, the classification of detailed alleles, including HLA-B*15:58, HLA-C*17:01, HLA-DRB1*08:01 and HLA-DRB1*11:06, differs from that in the previous China CWD 2018. China CWD 2025 catalogue captured all the WD alleles of China CWD 2018 except for HLA-B*15:58 and HLA-DRB1*08:01. A total of 195 common alleles, 25 intermediate alleles and 167 well-documented alleles of five HLA loci were identical to those in CIWD 3.0.0 catalogue. The China CIWD 2025 catalogue still represents unique HLA genetic diversity in the Chinese population and serves as an effective supplement to CIWD 3.0.0.

To the Editor: Previous studies have reported the increased frequency of human leukocyte antigen (HLA) alleles in patients with hematological diseases, including acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), myelodysplastic syndrome (MDS), and aplastic anemia (AA).[1] However, there is currently a lack of large-sample research analyzing HLA blocks and haplotypes in relation to hematological diseases. HLA is inherited in the form of haplotypes, and there is a strong linkage disequilibrium between adjacent HLA loci on chromosomes. HLA-A is located within the alpha block; HLA-B and C are located within the beta block; HLA-DRB1, DQB1, DRB3/4/5, and DQA1 are located within the delta block; and HLA-DPA1 and DPB1 are located within the epsilon block. When the frequencies of HLA alleles increase, the alleles at other loci linked within the same block or haplotype may also exhibit increased frequencies. This study aimed to analyze whether alleles with increased frequency are located within the same block or haplotype, and to investigate whether HLA block analysis or haplotype analysis is more meaningful for association studies of hematological diseases. In this study, 3546 hematological disease patients from southeastern China were enrolled who had undergone high-resolution HLA typing at the Department of HLA Laboratory between April 2019 and July 2022. This study was approved by the Ethics Committee of the First Affiliated Hospital of Soochow University (Approval Number: 2020 Ethics Approval [Declaration] No.322). Informed consent was obtained from all participants. A total of 1623 AML, 929 ALL, 493 MDS, and 501 AA cases were included for allele frequency (AF) analysis. Additionally, 1217 AML, 749 ALL, 355 MDS, and 425 AA patients with five-locus haplotypes (HLA-A~B~C~DRB1~DQB1) were included, as well as 610 AML, 370 ALL, 195 MDS, and 192 AA patients with nine-locus haplotypes (HLA-A~B~C~DRB1~DQB1~DRB3/4/5~DQA1~DPA1~DPB1) for block and haplotype analysis. The beta block (HLA-B~C) and delta block (HLA-DRB1~DQB1) analyses were based on the five-locus haplotypes, while the delta block (HLA-DRB3/4/5~DRB1~DQA1~DQB1) and epsilon block (HLA-DPA1~DPB1) analyses were based on the nine-locus haplotype. The control group comprised the data from the common and well-documented allele list version 2.2 (CWD v2.2) for the HLA-A, B, C, DRB1, and DQB1 loci released by the China Marrow Donor Program,[2] the CWD data for the HLA-DRB3/4/5, DQA1, DPA1, and DPB1 loci established in our laboratory, and published five-locus and nine-locus haplotype data from our laboratory.[3,4] Next-generation sequencing was employed to perform HLA high-resolution genotyping at the HLA-A, B, C, DRB1, DQB1, DPB1, DQA1, DPA1, and DRB3/4/5 loci. HLA gene data analysis software (software copyright number: 2022SR1412487) was utilized to calculate the AFs, block frequencies (BFs), and haplotype frequencies (HFs) of patients. Statistical analysis was performed using R (v4.2.2, Vienna, Austria), and a chi-squared test was conducted to compare the AFs, BFs, and HFs between case and control groups. An odds ratio (OR) greater than 1 indicated that the allele was a susceptibility factor for the disease. To address multiple testing, Bonferroni-corrected P-value (Pc) <0.05 was considered statistically significant. HLA-A*02:07, A*11:01, A*30:01, B*38:02, B*46:01, C*01:02, DRB1*09:01, DRB1*12:02, DQB1*03:03, DQA1*01:04, DQA1*03:01, DRB3*01:01, DRB3*02:02, and DPB1*05:01 showed increased frequencies in AML patients compared with the control group. HLA-A*02:07, B*13:02, B*46:01, C*01:02, DRB1*04:06, DRB1*09:01, DQB1*02:02, DQB1*03:03, and DQA1*03:01 exhibited elevated frequencies in ALL patients compared with the control group. HLA-A*02:01, A*02:06, B*15:11, C*03:03, C*14:03, DQB1*04:01, DQB1*06:04, DQA1*03:03, DRB3*01:01, and DPB1*04:02 showed higher frequencies in MDS patients compared with the control group. The frequencies of HLA-A*02:01, A*02:06, A*30:01, B*13:02, B*40:02, B*46:01, B*54:01, C*01:02, DRB1*09:01, DRB1*15:01, DQB1*03:03, DQB1*06:02, DQA1*03:02, and DRB4*01:03 in AA patients were higher than those in the control group [Supplementary Table 1, https://links.lww.com/CM9/C359]. Following Bonferroni correction, HLA-A*11:01, C*01:02, DRB1*09:01, and DQA1*03:01 in AML patients; HLA-B*46:01, B*13:02, C*01:02, DRB1*09:01, and DQB1*03:03 in ALL patients; HLA-DQA1*03:03 and DRB3*01:01 within the MDS patients; and HLA-B*40:02, B*46:01, C*01:02, DRB1*09:01, DQB1*03:03, and DQB1*06:02 in the AA patients all continued to show elevated frequencies with statistical significance [Figure 1A]. This study found that HLA-A*02:01, A*02:06, DRB1*09:01, DQB1*03:03, DRB1*15:01, and DQB1*06:02 exhibited elevated frequencies in AA patients, while HLA-A*02:01 and DQB1*06:02 exhibited elevated frequencies in MDS patients, consistent with previous reports.[1]Figure 1: Summary of HLA alleles (A), blocks (B), and haplotypes (C) with significantly increased frequency in AML (a), ALL (b), MDS (c), and AA (d). The enlarged and bolded a/b/c/d indicates HLA alleles/blocks/haplotypes with Pc <0.05 after Bonferroni correction. In haplotypes (C), bold alleles show increased frequency, thick wireframes denote frequency-increased blocks. AA: Aplastic anemia; ALL: Acute lymphoblastic leukemia; AML: Acute myeloid leukemia; HLA: Human leukocyte antigen; MDS: Myelodysplastic syndrome.The blocks HLA-B*15:02~C*08:01, B*46:01~C*01:02, B*52:01~C*12:02, and DRB1*12:02~DQB1*03:01 showed higher frequencies in AML patients compared with the control group. The blocks HLA-B*38:02~C*07:02, DRB1*15:01~DQB1*06:01, DRB1*16:02~DQB1*05:02, DRB1*14:54~DQB1*05:02, and DPA1*02:02~DPB1*05:01 showed increased frequencies in ALL patients compared with the control group. The blocks HLA-DRB1*15:01~DQB1*06:02 and DRB1*13:01~DQB1*06:03 were observed to have elevated frequencies in MDS patients compared with the controls. The blocks HLA-B*13:01~C*03:04, DRB1*09:01~DQB1*03:03, DRB1*15:01~DQB1*06:02, DRB5*01:01~DRB1*15:01~DQA1*01:02~DQB1*06:02, and DPA1*02:01~DPB1*17:01 exhibited higher frequencies in AA patients than in the controls [Supplementary Table 2, https://links.lww.com/CM9/C359]. After Bonferroni correction, only the AML and AA groups retained statistically significant blocks. In AML patients, the HLA-B*15:02~C*08:01 and DRB1*12:02~DQB1*03:01 blocks remained statistically significant, while the statistically significant blocks in the AA patients included HLA-DRB1*09:01~DQB1*03:03, DRB1*15:01~DQB1*06:02, and DRB5*01:01~DRB1*15:01~DQA1*01:02~DQB1*06:02 [Figure 1B]. This study found that the frequency of HLA-DRB1*15:01~DQB1*06:02 increased in AA patients, which is consistent with previous reports.[5] The five-locus haplotype HLA-A*11:01~B*15:02~C*08:01~DRB1*12:02~DQB1*03:01 exhibited higher frequency in the AML patients compared with the control group. The HLA-A*02:01~B*46:01~C*01:02~DRB1*09:01~DQB1*03:03, A*02:03~B*38:02~C*07:02~DRB1*16:02~DQB1*05:02, and A*11:01~B*13:01~C*03:04~DRB1*15:01~DQB1*06:01 haplotypes showed significantly higher frequencies in ALL patients than in the control group. The HLA-A*02:01~B*40:01~C*07:02~DRB1*09:01~DQB1*03:03 haplotype exhibited increased frequency in MDS patients compared with the control group. In AA patients, the haplotypes HLA-A*02:01~B*46:01~C*01:02~DRB1*09:01~DQB1*03:03 and A*11:01~B*46:01~C*01:02~DRB1*09:01~DQB1*03:03 exhibited elevated frequencies compared with the control group [Supplementary Table 3, https://links.lww.com/CM9/C359]. The nine-locus haplotype HLA-A*02:01~B*40:01~C*07:02~DRB1*09:01~DQB1*03:03~DRB4*01:03~DQA1*03:02~DPA1*02:02~DPB1*05:01 showed elevated frequency in MDS patients in comparison to the control group. HLA-A*02:07~B*46:01~C*01:02~DRB1*08:03~DQB1*06:01~DRB3/4/5*NP~DQA1*01:03~DPA1*02:02~DPB1*02:02 showed higher frequency in AA patients than in control group [Supplementary Table 4, https://links.lww.com/CM9/C359]. After Bonferroni correction, only HLA-A*11:01~B*46:01~C*01:02~DRB1*09:01~DQB1*03:03 in AA patients exhibited a significantly higher frequency. However, the alleles and blocks with increased frequencies observed in this study, which form the haplotype HLA-A*11:01~B*15:02~C*08:01~DRB1*12:02~DQB1*03:01 in AML and the haplotype HLA-A*02:01~B*46:01~C*01:02~DRB1*09:01~DQB1*03:03 in AA, showed statistically significant differences. Haplotypes with increased frequency for both five-locus and nine-locus haplotypes, or haplotypes with frequency-increased alleles and blocks in HLA class I and class II, are considered potentially associated with hematological diseases. These HLA haplotypes are summarized in Figure 1C. In this study, HLA alleles, blocks, and haplotypes with increased frequencies were observed in a large sample of AML, ALL, MDS, and AA patients from the Chinese Han population. AML and AA patients exhibited frequency-increased alleles and blocks, and the haplotypes composed of these alleles and blocks also showed elevated frequencies. Some of the alleles with increased frequencies in MDS and AA patients in this study were consistent with previous reports.[1] However, this study found additional alleles that may be associated with hematological diseases, including HLA-DRB1*12:02 in AML patients, HLA-DRB1*09:01 and DQB1*03:03 in ALL patients, and HLA-B*46:01 and C*01:02, which exhibited significantly increased frequency in ALL and AA patients. In addition, some of the alleles discovered in this study were inconsistent with previous reports. For example, HLA-A*11:01 was observed to have an increased frequency in AML patients in this study, whereas a previous study by Wang et al[1] found that its frequency was lower than that in the CWD data. Based on previous reports, this study found increased frequencies of some blocks and haplotypes composed of alleles with elevated frequencies, an unreported finding. In AML patients, a haplotype HLA-A*11:01~B*15:02~C*08:01~DRB1*12:02~ DQB1*03:01 showed increased frequency, with elevated allele or block frequencies at all its loci. Although previous work identified many increased allele frequencies in AA patients, this study first found that the block HLA-DRB1*09:01~DQB1*03:03 and the haplotype HLA-A*02:01~B*46:01~C*01:02~DQB1*09:01~DQB1*03:03, composed of some of these alleles, are over-represented in AA patients. Therefore, HLA distribution differences between AML/AA patients and healthy individuals are more likely due to haplotype distribution differences. Combined block and haplotype analysis is more valuable than allele analysis alone. In addition, unlike MDS and AA, this study's AML and ALL findings conflicted with past reports, maybe because of sample size diffs or diverse gene changes in patients. Compared with AA patients, leukemia patients at initial diagnosis have highly inconsistent genetic mutations and fusion genes, and HLA distribution may vary among those with different genetic changes. Therefore, HLA analysis results for leukemia patients without gene change stratification vary greatly between studies. To further investigate the correlations between HLA and hematological diseases, we analyzed how HLA alleles/blocks relate to immunology and gene mutations of AML and ALL patients at our hospital. Among AML patients with the RUNX1 mutation, the HLA-DRB1*12:02 allele was more common. In ALL patients, B-ALL (not T-ALL) had higher frequencies of alleles HLA-DRB1*09:01, DQB1*03:03 and the block HLA-DRB1*09:01~DQB1*03:03. These HLA alleles and block, which differ in genetic changes, may aid leukemia prognosis. They're also important components of haplotypes associated with hematological diseases here. These findings may help understand how HLA affects hematological diseases and prognosis. In summary, this study outlined the distribution characteristics of HLA in Han Chinese patients with AML, ALL, MDS, and AA in southeast China, providing a basis for further research on the correlation between HLA and risk stratification, clinical treatment, and transplantation prognosis in these four hematologic diseases. Conflicts of Interest None. Funding This work was supported by the National Natural Science Foundation of China (No. 82070180).

Background Screening of malignant hematological diseases is of great importance for their diagnosis and subsequent treatment. This study constructed an optimal screening model for malignant hematological diseases based on routine blood cell parameters. Methods The venous blood samples of 1751 patients collected from 10 tertiary hospitals in China were divided into a training set (1223 cases) and a validation set (528 cases). In addition to the clinical diagnostic information of the samples in the training set, 26 blood cell parameters including morphological parameters were selected using manual screening and filtering to construct eight machine learning models. These models were used to identify hematological malignancies among the validation set. Results Comparison of the discrimination, calibration and clinical detection performance of the eight machine learning models revealed that the artificial neural network (ANN) model performed the optimal in identifying malignant haematological diseases in the validation set (528 cases), with an area under the receiver operating characteristic curve (AUC), accuracy, sensitivity and specificity of 0.906, 0.857, 0.832 and 0.884, respectively. Conclusion The ANN model constructed can be used for screening of malignant hematological diseases, especially in primary hospitals that lack comprehensive diagnosis, and this ANN model will help patients to get diagnosis and treatment of malignant hematological diseases as early as possible.

BACKGROUND:Radiation-induced liver injury (RILI) poses a significant challenge in abdomino-pelvic tumor radiotherapy, adversely impacting normal liver tissues. This study explores the role of Tmprss6, a gene encoding Matriptase2, in acute RILI development and its impact on hepatocyte apoptosis. METHODS:A RILI model was established using 30 Gy total liver irradiation in C57BL/6J mice. Expression of Tmprss6 and hepcidin post radiation was detected by immunohistochemistry staining, Western blot and quantitative real-time PCR. Tmprss6 knockout mice were established to demonstrate the contribution of Tmprss6 to RILI. The molecular response within the liver after Tmprss6 knockdown was investigated using Transcriptomics sequencing. RESULTS:Disruptions in the Matriptase2-hepcidin axis emerge post-total liver radiation, marked by decreased Matriptase2 levels and heightened hepcidin levels. Tmprss6 knockout exacerbates RILI, evident in reduced mouse survival, increased liver damage, and elevated serum levels of aminotransferases. Additionally, Tmprss6 deletion increases inflammatory cytokines and malondialdehyde level while diminishing liver antioxidant capacity. Gene expression profiling reveals shifts in inflammation, apoptosis, and p53 signaling pathways upon Tmprss6 deletion. In vitro experiments, utilizing the AKT inhibitor AZD5363, demonstrate its effectiveness in reversing impediments caused by Tmprss6 silencing post-radiation. AZD5363 effectively restores suppressed cell proliferation, mitigates heightened cell apoptosis, and counters the elevated p53 expression induced by Tmprss6 depletion. This underscores the partial mediation of Tmprss6's protective role through the PI3K-AKT signaling. CONCLUSIONS:This study unveils intricate mechanistic pathways activated by Tmprss6 silencing, amplifying p53 expression, facilitating hepatocyte apoptosis, and accelerating RILI progression, which providing nuanced insights into the multifaceted involvement of Tmprss6 in RILI.

[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.

622 Background: Cholangiocarcinoma (CCA) is a highly malignant biliary tumor characterized by frequent perineural invasion (PNI), which is associated with a poor prognosis; however, the underlying mechanisms remain unclear. G-protein-coupled receptor 120 (GPR120) has been implicated in the development of various tumors, while nerve growth factor (NGF) has a strong correlation with PNI. This study aims to elucidate the role of GPR120 in the production of NGF and to investigate the mechanisms by which PNI is induced in CCA. Methods: We conducted a retrospective review of medical records for 386 patients with cholangiocarcinoma (CCA), including both extrahepatic (ECC) and intrahepatic (ICC) types, who underwent curative resection at the Department of General Surgery, First Affiliated Hospital of Soochow University, between January 2015 and December 2021. NGF and GPR120 expression were assessed in 60 paraffin-embedded archived CCA tissue samples via immunohistochemical staining (IHC), with an additional 60 normal bile duct samples serving as controls. All tissues were sourced from the aforementioned 386 patients, none of whom received preoperative treatment. Tumors were staged according to AJCC classification. Western blot analysis was employed to evaluate NGF and GPR120 expression in CCA cell lines (QBC 939, RBE, HUCCT-1, and HCCC-9810). To assess the invasion and migration capabilities of CCA cell lines, QBC 939 and HCCC-9810 were treated with TUG-891 (a GPR120 agonist) and AH7614 (a GPR120 inhibitor). Results: Both GPR120 and NGF were found to be upregulated in CCA tissues, correlating with aggressive clinicopathological features. IHC staining revealed cytoplasmic localization of GPR120 and NGF, with significantly higher expression in cancerous tissues compared to adjacent noncancerous samples. Among the 386 patients, PNI was observed in 339 (87.8%). PNI correlated with tumor diameter, CA 19-9 levels, TNM stage, preoperative bilirubin levels, tumor differentiation, and preoperative drainage. Notably, GPR120 expression increased in poorly differentiated tumors and advanced clinical stages, indicating a clinical association with CCA progression. In vitro studies demonstrated that GPR120 promoted invasion and migration in the QBC 939 and HCCC-9810 cell lines. Western blot analysis confirmed elevated GPR120 levels in these lines, which also exhibited higher NGF expression. The GPR120 inhibitor AH7614 significantly reduced invasion in QBC 939 and HCCC-9810 cells, while the GPR120 agonist TUG-891 showed no effect on any of the CCA cell lines tested. Conclusions: GPR120 and NGF are implicated in perineural invasion (PNI) in CCA, with a notable correlation between GPR120 and NGF in the context of PNI occurrence.

Hepatocellular carcinoma (HCC), a globally prevalent form of cancer, is featured by aggressive growth and early metastasis. Elucidating the underlying mechanism and identifying the effective therapy are critical for advanced HCC patients. In the study, we detect that KRT80 was upregulated in HCC samples. HCC patients with higher KRT80 are associated with worse overall survival after surgery. Gain-of and loss-of function studies show that KRT80 enhanced HCC cells proliferation, migration, invasion, and angiogenesis, whereas its silencing abolishes the effects in vivo and in vitro. Mechanistic investigation shows that KRT80 may function as an independent prognostic risk factor and act as an oncogene by influencing EMT and modulating the PI3K/AKT signaling pathway. Together, these findings suggest that KRT80 may be a potential oncogene and a good indicator in predicting prognosis. Targeting KRT80 can offer new insights into the prevention and treatment of HCC.

To analyse the effect of HLA‐DPA1 and HLA‐DPB1 allelic mismatches on the outcomes of unrelated donor haematopoietic stem cell transplantation (URD‐HSCT), we collected 258 recipients with haematological disease who underwent HLA‐10/10 matched URD‐HSCT. HLA‐A, ‐B, ‐C, ‐DRB1, ‐DQB1, ‐DRB3/4/5, ‐DQA1, ‐DPA1 and ‐DPB1 typing was performed for the donors and recipients using next‐generation sequencing (NGS) technology. After excluding 8 cases with DQA1 or DRB3/4/5 mismatches, we included 250 cases with HLA‐14/14 matching for further analysis. Our results showed that the proportion of matched DPA1 and DPB1 alleles was only 10.4% (26/250). The remaining 89.6% of donors and recipients demonstrated DPA1 or DPB1 mismatch. In the DPA1 matched and DPB1 mismatched group, accounting for 18.8% (47/250) of the cohort, DPB1*02:01/DPB1*03:01 allelic mismatches were associated with decreased 2‐year OS and increased NRM. DPB1*02:02/DPB1*05:01 and DPB1*02:01/DPB1*05:01 mismatches showed no impact on outcomes. Moreover, the specific allelic mismatches observed were consistent with the DPB1 T‐cell epitope (TCE) classification as permissive and non‐permissive. We innovatively established an analysis method for DPA1 ~ DPB1 linkage mismatch for cases with both DPA1 and DPB1 mismatched, accounting for 70% (175/250) of the total. DPA1*02:02 ~ DPB1*05:01/DPA1*02:01 ~ DPB1*17:01 linkage mismatches were associated with lower 2‐year OS, especially among AML/MDS recipients. DPA1*02:02 ~ DPB1*05:01/DPA1*01:03 ~ DPB1*02:01 linkage mismatches showed no impact on outcomes. In conclusion, applying the DPA1 ~ DPB1 linkage mismatch analysis approach can identify different types of mismatches affecting transplant outcomes and provide valuable insight for selecting optimal donors for AML/MDS and ALL recipients.

Patients with abdominopelvic cancer undergoing radiotherapy commonly develop radiation-induced intestinal injury (RIII); however, its underlying pathogenesis remains elusive. The von Willebrand factor (vWF)/a disintegrin and metalloproteinase with a thrombospondin type 1 motif, member 13 (ADAMTS13) axis has been implicated in thrombosis, inflammation, and oxidative stress. However, its role in RIII remains unclear. In this study, the effect of radiation on vWF and ADAMTS13 expression was firstly evaluated in patients with cervical cancer undergoing radiotherapy and C57BL/6J mice exposed to different doses of total abdominal irradiation. Then, mice with the specific deletion of vWF in the platelets and endothelium were established to demonstrate the contribution of vWF to RIII. Additionally, the radioprotective effect of recombinant human (rh) ADAMTS13 against RIII was assessed. Results showed that both the patients with cervical cancer undergoing radiotherapy and RIII mouse model exhibited increased vWF levels and decreased ADAMTS13 levels. The knockout of platelet- and endothelium-derived vWF rectified the vWF/ADAMTS13 axis imbalance; improved intestinal structural damage; increased crypt epithelial cell proliferation; and reduced radiation-induced apoptosis, inflammation, and oxidative stress, thereby alleviating RIII. Administration of rhADAMTS13 could equally alleviate RIII. Our results demonstrated that abdominal irradiation affected the balance of the vWF/ADAMTS13 axis. vWF exerted a deleterious role and ADAMTS13 exhibited a protective role in RIII progression. rhADAMTS13 has the potential to be developed into a radioprotective agent.

IntroductionClinical metagenomic next-generation sequencing (mNGS) has proven to be a powerful diagnostic tool in pathogen detection. However, its clinical utility has not been thoroughly evaluated.MethodsIn this single-center prospective study at the First Affiliated Hospital of Soochow University, a total of 228 samples from 215 patients suspected of having acute or chronic infections between June 2018 and December 2018 were studied. Samples that met the mNGS quality control (QC) criteria (N = 201) were simultaneously analyzed using conventional tests (CTs), including multiple clinical microbiological tests and real-time PCR (if applicable).ResultsPathogen detection results of mNGS in the 201 QC-passed samples were compared to CTs and exhibited a sensitivity of 98.8%, specificity of 38.5%, and accuracy of 87.1%. Specifically, 109 out of 160 (68.1%) CT+/mNGS+ samples exhibited concordant results at the species/genus level, 25 samples (15.6%) showed overlapping results, while the remaining 26 samples (16.3%) had discordant results between the CT and mNGS assays. In addition, mNGS could identify pathogens at the species level, whereas only the genera of some pathogens could be identified by CT. In this cohort, mNGS results were used to guide treatment plans in 24 out of 41 cases that had available follow-up information, and the symptoms were improved in over 70% (17/24) of them.ConclusionOur data demonstrated the analytic performance of our mNGS pipeline for pathogen detection using a large clinical cohort and strongly supports the notion that in clinical practice, mNGS represents a valuable supplementary tool to CTs to rapidly determine etiological factors of various types of infection and to guide treatment decision-making.

Background:Abnormally changed steroid hormones during pregnancy are closely related to the pathological process of gestational diabetes mellitus (GDM). Our aim was to systematically profile the metabolic alteration of circulating steroid hormones in GDM women and screen for risk factors.Methods:This study was a case-control study with data measured from 40 GDM women and 70 healthy pregnant women during their 24-28 gestational weeks. 36 kinds of steroid hormones, including 3 kinds of corticosteroids, 2 kinds of progestins, 5 kinds of androgens and 26 kinds of downstream estrogens in serum were systematically measured using a combined sensitive UPLC-MS/MS method. The flux of different metabolic pathways of steroid hormones was analyzed. Logistic regression and ROC curve model analyses were performed to identify potential steroid markers closely associated with GDM development.Results:Serum corticosteroids, progestins and almost all the estrogen metabolites via 16-pathway from parent estrogens were higher in GDM women compared with healthy controls. Most of the estrogen metabolites via 4-pathway and more than half of the metabolites via 2-pathway were not significantly different. 16α-hydroxyestrone (16OHE1), estrone-glucuronide/sulfate (E1-G/S) and the ratio of total 2-pathway estrogens to total estrogens were screened as three indicators closely related to the risk of GDM development. The adjusted odds ratios of GDM for the highest quartile compared with the lowest were 72.22 (95% CI 11.27-462.71, P trend <0.001) for 16OHE1 and 6.28 (95% CI 1.74-22.71, P trend <0.05) for E1-G/S. The ratio of 2-pathway estrogens to total estrogens was negatively associated with the risk of GDM.Conclusion:The whole metabolic flux from cholesterol to downstream steroid hormones increased in GDM condition. The most significant changes were observed in the 16-pathway metabolism of estrogens, rather than the 2- or 4-pathway or other types of steroid hormones. 16OHE1 may be a strong marker associated with the risk for GDM.

IntroductionLittle attention has been given to the factors associated with basilar artery (BA) dolichosis. This study aims to elucidate the prevalence and associated factors of BA dolichosis in patients with acute cerebral infarction (ACI).MethodsWe collected the clinical and laboratory data of 719 patients with ACI admitted to our department. Magnetic resonance angiography was used to evaluate the geometric parameters of the BA and intracranial vertebral arteries (VAs). A BA curve length > 29.5 mm or bending length (BL) > 10 mm was identified as BA dolichosis. Univariate and multivariate logistic regression were performed to determine the factors associated with BA dolichosis.ResultsAmong 719 patients with ACI, 238 (33.1%) demonstrated BA dolichosis, including 226 (31.4%) with simple BA dolichosis and 12 (1.7%) with basilar artery dolichoectasia (BADE). Pearson correlation analyses showed that BA curve length was positively correlated with BL (r = 0.605). Multivariate logistic regression analysis demonstrated that current smoking (OR = 1.50, 95% CI: 1.02–2.21, p = 0.039), diabetes mellitus (OR = 1.66, 95% CI: 1.14–2.41, p = 0.008), BA diameter (OR = 3.04, 95% CI: 2.23–4.13, p < 0.001), BA bending (OR = 4.24, 95% CI: 2.91–6.17, p < 0.001) and BL (OR = 1.45, 95% CI: 1.36–1.55, p < 0.001) were significantly associated with BA dolichosis.ConclusionThis study suggests that BA dolichosis was common in patients with ACI, and the morphological parameters of the vertebrobasilar artery and acquired risk factors (including smoking and diabetes) were risk factors for BA dolichosis.