Purpose: Zinc finger protein 639 (ZNF639) is often found within the overlapping amplicon of PIK3CA, and previous studies suggest its involvement in the pathogenesis of esophageal and oral squamous cell carcinomas. However, its expression and significance in breast cancer remain uncharacterized. Methods: Immunohistochemical analysis of ZNF639 was performed using tissue microarrays.Functional studies, including colony formation, Transwell cell migration, and in vivo metastasis, were conducted on breast tumor cells with ZNF639 knockdown via small interfering RNA transfection. Results: Reduced ZNF639 immunoreactivity was observed in 82% of the breast cancer samples, independent of hormone receptor and human epidermal growth factor receptor 2 status. In multivariate Cox regression analyses, ZNF639 expression was associated with favorable survival outcomes, including recurrence-free survival (hazard ratio, 0.35; 95% confidence interval [CI], 0.14–0.89) and overall survival (hazard ratio, 0.41; 95% CI, 0.16– 1.05). ZNF639 knockdown increased clonogenicity, cell motility, and lung metastasis in NOD/ SCID mice. Following the ZNF639 knockdown, the expression of Snail1, vimentin, and C-C chemokine ligand 20 (CCL20) was upregulated, and the changes in cell phenotype mediated by ZNF639 were reversed by the subsequent knockdown of CCL20. Conclusion Low ZNF639 expression is a novel prognostic factor for recurrence-free survival in patients with breast cancer.

Primary ciliary dyskinesia (PCD) is a clinically rare, genetically and phenotypically heterogeneous condition characterized by chronic respiratory tract infections, male infertility, tympanitis, and laterality abnormalities. PCD is typically resulted from variants in genes encoding assembly or structural proteins that are indispensable for the movement of motile cilia. Here, we identified a novel nonsense mutation, c.466G>T, in cilia- and flagella-associated protein 300 ( CFAP300 ) resulting in a stop codon (p.Glu156*) through whole-exome sequencing (WES). The proband had a PCD phenotype with laterality defects and immotile sperm flagella displaying a combined loss of the inner dynein arm (IDA) and outer dynein arm (ODA). Bioinformatic programs predicted that the mutation is deleterious. Successful pregnancy was achieved through intracytoplasmic sperm injection (ICSI). Our results expand the spectrum of CFAP300 variants in PCD and provide reproductive guidance for infertile couples suffering from PCD caused by them.
Adult ; Female ; Humans ; Male ; Pregnancy ; China ; Ciliary Motility Disorders/genetics* ; Codon, Nonsense ; East Asian People/genetics* ; Exome Sequencing ; Homozygote ; Infertility, Male/genetics* ; Kartagener Syndrome/genetics* ; Pedigree ; Sperm Injections, Intracytoplasmic ; Cytoskeletal Proteins/genetics*

OBJECTIVES: To investigate the prognostic value of molecular minimal residual disease (Mol-MRD) monitored before and after allogeneic hematopoietic stem cell transplantation (HSCT) in pediatric acute myeloid leukemia (AML). METHODS: Clinical data of 71 pediatric AML patients who underwent HSCT between August 2016 and December 2023 were analyzed. Mol-MRD levels were dynamically monitored in MRD-positive patients, and survival outcomes were evaluated. RESULTS: No significant difference in the 3-year overall survival (OS) rate was observed between patients with pre-HSCT Mol-MRD ≥0.01% and <0.01% (77.3% ± 8.9% vs 80.4% ± 7.9%, P=0.705). However, patients with pre-HSCT Mol-MRD <1.75% had a significantly higher 3-year OS rate than those with Mol-MRD ≥1.75% (86.6% ± 5.6% vs 44.4% ± 16.6%, P=0.020). The median Mol-MRD level in long-term survivors was significantly lower than in non-survivors [0.61% (range: 0.04%-51.58%)] vs 10.60% (range: 1.90%-19.75%), P=0.035]. Concurrent flow cytometry-based MRD positivity was significantly higher in non-survivors (80% vs 24%, P=0.039). There was no significant difference in the 3-year overall survival rate between patients with Mol-MRD ≥0.01% and those with <0.01% at 30 days post-HSCT (P=0.527). For children with Mol-MRD <0.22% at 30 days post-HSCT, the 3-year overall survival rate was 80.4% ± 5.9%, showing no significant difference compared to those with molecular negativity (87.0% ± 7.0%) (P=0.523). CONCLUSIONS Patients with pre-HSCT Mol-MRD <1.75% or post-HSCT Mol-MRD <0.22% may achieve long-term survival outcomes comparable to Mol-MRD-negative cases through HSCT and targeted interventions.
Humans ; Hematopoietic Stem Cell Transplantation ; Neoplasm, Residual ; Leukemia, Myeloid, Acute/genetics* ; Child ; Male ; Female ; Child, Preschool ; Prognosis ; Adolescent ; Infant ; Transplantation, Homologous

OBJECTIVES: To study clinical manifestations and gene mutation features of neonates with centronuclear myopathy. METHODS: A retrospective analysis was conducted on the medical data of 5 neonates with centronuclear myopathy diagnosed in the Neonatal Intensive Care Unit of Children's Hospital, Zhejiang University School of Medicine from January 2020 to August 2024. The data included gender, gestational age, birth weight, Apgar score, clinical manifestations, creatine kinase level, electromyography, genetic testing results and the outcomes of the infants. RESULTS: All 5 male neonates had a history of postpartum asphyxia and resuscitation. They all presented with hypotonia, myasthenia, and respiratory failure; two neonates also had swallowing dysfunction. Of the five neonates, three had normal creatine kinase levels, while two had slightly elevated levels. Electromyography was performed for three neonates, among whom two had myogenic damage. MTM1 gene mutations were identified by genetic testing in all five neonates, including two nonsense mutations and three missense mutations, among which one variant had not been previously reported. Four mutations were inherited from the mother, and the other one was a de novo mutation. The five neonates showed no clinical improvement following treatment, failed weaning from mechanical ventilation, and ultimately died after withdrawal of life-sustaining therapy. CONCLUSIONS Centronuclear myopathy caused by MTM1 gene mutation often has a severe phenotype and a poor prognosis, and it should be considered for neonates with hypotonia and myasthenia after birth. Genetic testing should be performed as soon as possible.
Humans ; Myopathies, Structural, Congenital/genetics* ; Male ; Infant, Newborn ; Retrospective Studies ; Mutation ; Female ; Protein Tyrosine Phosphatases, Non-Receptor/genetics*

OBJECTIVE: To analyze the molecular genetic spectrum of children with acute myeloid leukemia (AML), and explore its correlation with clinical characteristics and prognosis. METHODS: The clinical and molecular genetic data of 116 children with newly diagnosed AML in Wuhan Children's Hospital from September 2015 to August 2022 were retrospectively analyzed. The Fisher's exact test was used to analyze the correlation of gene mutations with clinical features, and Kaplan-Meier curve was used to analyze the influences of gene mutations on the prognosis. RESULTS: NRAS (22%), KRAS (14.9%), and KIT (14.7%) mutations were the most common genetic abnormalities in 116 children with AML. Children with KIT, CEBPA and GATA2 mutations showed a higher median onset-age than those without mutations (all P < 0.05). Children with FLT3-ITD mutation exhibited a higher white blood cell count at initial diagnosis compared to those without mutations (P < 0.05). Children with ASXL2 mutation had lower platelet count and hemoglobin at initial diagnosis than those without mutations (both P < 0.05). KIT mutations were often co-occurred with t(8;21)(q22;q22). There was no significant relationship between gene mutation and minimal residual disease (MRD) remission rate after the first and second induction therapy (P >0.05). KIT and NRAS mutations were not associated with prognosis significantly (P >0.05). The overall survival (OS) rates of children with CEBPA and FLT3-ITD mutations were superior to those without mutations, but the differences were not statistically significant (P >0.05). The 3-year OS rate of 61 children treated by allogeneic hematopoietic stem cell transplantation was 89.8%, which was significantly higher than 55.2% of those only treated by chemotherapy (P < 0.001). CONCLUSIONS Gene mutations are common in children with AML, and next-generation sequencing can significantly improve the detection rate of gene mutations, which can guide the risk stratification therapy. In addition, FLT3-ITD and KIT mutations may no longer be poor prognostic factors.
Humans ; Leukemia, Myeloid, Acute/genetics* ; Mutation ; Prognosis ; Retrospective Studies ; fms-Like Tyrosine Kinase 3/genetics* ; Child ; Proto-Oncogene Proteins c-kit/genetics* ; Male ; Female ; CCAAT-Enhancer-Binding Proteins/genetics* ; Membrane Proteins/genetics* ; Child, Preschool ; Adolescent ; GATA2 Transcription Factor/genetics* ; GTP Phosphohydrolases/genetics* ; Proto-Oncogene Proteins p21(ras)/genetics*

OBJECTIVE: To analyze the effect of COVID-19 infection on the mobilization and collection of autologous peripheral blood stem cells in patients with multiple myeloma. METHODS: The general baseline data, treatment factors before mobilization collection, collection status, and treatment overview after collection of autologous peripheral blood stem cells at Beijing Chaoyang Hospital affiliated with Capital Medical University from January 1, 2020 to July 15, 2023 were analyzed. RESULTS: 269 patients underwent mobilization and collection of autologous peripheral blood stem cells. Among them, 32 cases with COVID-19 infection history (COVID-19 group) and 237 cases without COVID-19 infection history (non-COVID-19 group). In the COVID-19 group, 17 cases were treated with chemotherapy (etoposide)+G-CSF, and 15 cases were treated with plerixafor +G-CSF. In the non-COVID-19 group, 214 cases were treated with chemotherapy +G-CSF, 17 cases were treated with plerixafor +G-CSF, and 6 cases were treated with chemotherapy + plerixafor +G-CSF. The number of CD34⁺ cells, collection success rate, and excellence rate in the COVID-19 group and the non-COVID-19 group were ［5.52 (0.94-26.87) vs 4.80 (0.53-37.20)］×10⁶/kg (P =0.610), (93.8% vs 85.2%) (P =0.275), (62.5% vs 49.4%) (P =0.190), respectively. Among 113 patients mobilized with etoposide +G-CSF, the number of CD34⁺ cells, success rate, and excellence rate collected from COVID-19 infection (17 cases) and non-COVID-19 infection (96 cases) were ［7.54 (2.66-26.87) vs 7.78 (2.26-37.20)］×10⁶/kg (P =0.847), (100.0% vs 100.0%) (no P value), (82.4% vs 86.5%) (P =0.655), respectively. Among 32 patients mobilized by plerixafor +G-CSF, the number of CD34⁺ cells, success rate and excellence rate of COVID-19 infection (15 cases) and non-COVID-19 infection (17 cases) were ［3.82 (0.94-7.27) vs 4.11 (0.53-9.05)］×10⁶/kg (P =0.821), (86.7% vs 88.2%) (P =0.893), (40.0% vs 35.3%) (P =0.784), respectively. In 32 patients with COVID-19 infection, the number of CD34⁺ cells collected by etoposide +G-CSF (17 cases) and plerixafor +G-CSF (15 cases), as well as the success rate and excellence rate were ［7.54 (2.66-26.87) vs 3.82(0.94-7.27)］×10⁶/kg (P =0.004), (100.0% vs 86.7%) (P =0.120), (82.4% vs 40.0%) (P =0.014), respectively. By 2023.7.31, 232 patients (86.2%, 232/269) had received transplantation, including 24 patients in the COVID-19 group and 208 patients in the non-COVID-19 group. The median number of CD34⁺ cells infused in the two groups was ［3.67 (2.50-13.44) vs 3.11(1.12-19.89)］×10⁶/kg (P =0.058), the median days of neutrophil engraftment ［11(9-13) vs 11(9-17)］ (P =0.674), the median days of platelet engraftment ［11(0-23), 12(0-43)］ (P =0.279), respectively. CONCLUSION The history of COVID-19 infection did not affect the PBSC mobilization, collection and transplantation of patients with myeloma. In patients with COVID-19 infection, the results of chemotherapy mobilization with etoposide seems to be better than that of plerixafor mobilization, but further research is needed to clarify.
Humans ; COVID-19/complications* ; Multiple Myeloma/complications* ; Hematopoietic Stem Cell Mobilization ; Transplantation, Autologous ; Granulocyte Colony-Stimulating Factor/therapeutic use* ; Peripheral Blood Stem Cell Transplantation ; SARS-CoV-2 ; Middle Aged ; Peripheral Blood Stem Cells ; Male ; Female ; Cyclams ; Benzylamines

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.