Human Mutation最新文献

Numerous studies have emphasized the importance of the ubiquitin–proteasome system (UPS) in the malignant progression of ovarian cancer (OC). However, whether ubiquitination-related genes (UbRGs) can be used to predict the prognosis of OC remains to be revealed. Patients with OC were divided into two clusters based on the expression of UbRGs, and prognosis was compared between the two clusters. A prognostic model was established based on UbRGs, and its predictive efficiency was validated using Kaplan–Meier (K–M) curves, receiver operating characteristic (ROC) curves, and a nomogram. Immune infiltration and gene mutation analyses were used to examine the effects of UbRGs on the prognosis of OC. The prognostic model served as a valid and independent predictor of OC prognosis. Immune infiltration revealed that the unique immune microenvironment of OC was regulated by UbRGs. Gene mutation analysis indicates that UbRGs likely influence OC malignant behavior by modulating gene mutation patterns. In addition, Ube2j1 was found to play an important role in regulating the malignant progression of OC. Furthermore, the mechanism by which Ube2j1 modulates the OC phenotype and reshapes its immune microenvironment via the JAK2/STAT3/PD-L1 pathway was elucidated, providing novel insights into the potential for ubiquitination-based immunotherapy in OC. This study provides novel insights into precision immunotherapy based on UbRGs in OC. The UbRGs-based prognostic model may help to provide novel insights for the application of ubiquitination-based immunotherapy in OC.

Background: Heterogenized sphingolipid metabolism (SM) drives osteosarcoma tumorigenesis and its tumor-promoting microenvironment. State-of-the-art bioinformatic tools, such as machine learning, are essential for dissecting the prognostic value of SM by investigating its molecular and cellular mechanisms.

Methods: A tailored machine learning pipeline was established by integrating Cox regression, 5-fold cross-validation, Elastic Net, eXtreme Gradient Boosting (XGBoost), and Bayesian optimization (for hyperparameters tuning) to foster an SM Elastic Net-XGBoost (SNEX) prognostic model, interpreted by the Shapley additive explanations (SHAP) algorithm. The alterations in molecular pathways and immune microenvironment–driven unfavorable prognosis of SNEX-identified high-risk osteosarcoma were further investigated. The SNEX predicted results have also been clinically and experimentally validated.

Results: We identified 22 critical SM prognostic genes for Bayesian-optimized SNEX. This model provided outstanding estimates of the prognoses of osteosarcoma patients (C-index of 1.000). Its robustness was confirmed in the independent test set with a high area under the curve (AUC) of 0.875 at 1 year, 0.930 at 3 years, and 0.930 at 5 years. SNEX also significantly outperformed all previous genetic prognostic signatures with a significantly higher net benefit of decision curves and higher AUCs. ACTA2 was the most pivotal gene critical to the negative prediction of SNEX, while BNIP3 was for positive prediction. Mechanistically, SNEX-identified high-risk osteosarcoma suffered unfavorable prognoses due to dysregulation of many critical metabolic/inflammatory/immune biologic processes and immunosuppressive microenvironment, with reduced infiltration of 14 types of immune cells (macrophages, CD8+ T cells, NK cells, etc.). Notably, SNEX highlighted TERT as the most remarkable SM prognostic gene. Clinical osteosarcomas with high expression of TERT exhibited more significant malignant characteristics than others, as evidenced by their higher proliferation efficiency. In addition, all the experiments in vitro and in vivo validated that inhibiting TERT abundance reduces the proliferation, invasion, and migration capabilities of osteosarcoma cells.

Conclusions: This study is a first-hand report employing a tailored machine-learning pipeline for dissecting the prognostic value and roles of SM in osteosarcoma. The present study fostered a SNEX for risk-stratification with outstanding accuracy and offered deep insights into SM-mediated pathways and microenvironment dysregulation in osteosarcoma.

Sepsis is a life-threatening condition triggered by infection, resulting in widespread inflammation, immune dysfunction, and multiorgan failure. Despite advances in medical science, early detection, treatment, and prognosis remain significant challenges. In this study, we investigated the expression and functional role of ZDHHC19, a palmitoyltransferase enzyme, in sepsis. Our results demonstrate that ZDHHC19 is significantly upregulated in neutrophils during sepsis and correlates with inflammatory pathways critical to disease progression. High ZDHHC19 expression was associated with increased activation of immune-inflammatory processes such as collagen metabolism, myeloid cell activation, and cell adhesion, while suppressing antigen presentation. Additionally, ZDHHC19 expression was linked to poor patient prognosis, with higher levels correlating with increased mortality and sepsis shock. Using advanced computational tools, including XGBoost for machine learning-based core gene selection and CellChat for cell communication analysis, we identified key regulatory networks modulated by ZDHHC19, revealing its pivotal role in immune dysregulation. These findings suggest that ZDHHC19 may serve as a potential biomarker for the diagnosis and prognosis of sepsis and open new avenues for targeted therapeutic interventions aimed at modulating immune responses in this condition.

Wilson disease is a disorder of copper (Cu) homeostasis caused by the malfunction of Cu transporter ATP7B and associated Cu accumulation in tissues. The existence of over 700 disease-associated variants in the ATP7B gene and a broad spectrum of disease manifestations complicate the analysis of genotype–phenotype correlations and the development of better treatments for this disorder. To assist such studies, we screen 101 variants of ATP7B for expression and Cu transport activity in human fibroblasts lacking active ATP-dependent Cu transporters. The ClinVar database classified 59 of these as variants of uncertain significance or having conflicting pathogenicity classifications; six variants were not in the database. Thirty-three of the variants have been previously characterized by other assays. Only three variants (S657R, G1061E, and G1266R) resulted in the complete inactivation of Cu transport. The in silico analysis of these mutants was used to rationalize this drastic effect on ATP7B activity. The remaining ATP7B variants showed a range of Cu transport activities. Coexpression of variants with different properties yielded activity values different from the simple average. The advantages and limitations of this functional screen are discussed.

Pulmonary arterial hypertension (PAH) is a rare disease that can be caused by pathogenic variants, most frequently in the bone Morphogenetic Protein Receptor Type 2 (BMPR2) gene. We formed a ClinGen variant curation expert panel to devise guidelines for the clinical interpretation of BMPR2 variants identified in PAH patients. The general ACMG/AMP variant classification criteria were refined for PAH and adapted to BMPR2 following ClinGen procedures. Subsequently, these specifications were tested independently by three members of the curation expert panel on 28 representative BMPR2 variants selected from ClinVar and then presented and discussed in the plenum. Application of the final BMPR2 variant specifications resolved six of nine variants (66%) where multiple ClinVar classifications included a variant of uncertain significance, with all six being reclassified as Benign or Likely Benign. Four splice site variants underwent clinically consequential reclassification based on the presence or absence of supporting mRNA splicing data. These variant specifications provide an international framework and a valuable tool for BMPR2 variant classification that can be applied to increase confidence and consistency in BMPR2 interpretation for diagnostic laboratories, clinical providers, and patients.

Enzalutamide is classified as a novel antiandrogen medication; however, the majority of patients ultimately develop resistance to it. Consequently, conducting an in-depth investigation into potential targets of enzalutamide is essential for addressing the drug resistance observed in patients and for facilitating the discovery of new therapeutic targets. The SwissTargetPrediction database was used to identify targets linked to enzalutamide and to assess these targets in the prostate adenocarcinoma (PRAD) dataset sourced from the TCGA database. By employing various datasets and applying different machine learning methods for clustering, researchers constructed and validated both diagnostic and prognostic models for PRAD. A correlation analysis with the androgen receptor revealed TDP1 as the gene most significantly associated with enzalutamide. In addition, this study examined the relationship between TDP1 and immune infiltration. The expression levels of TDP1 and its prognostic correlation in PRAD patients were validated through immunofluorescence staining of 60 PRAD tissue specimens. Cluster analysis revealed a notable correlation among the 24 genes related to enzalutamide with regard to both prognosis and immune infiltration in PRAD patients. The diagnostic model, which incorporates various machine learning techniques, exhibits robust predictive ability for PRAD diagnosis, while the prognostic model employing the LASSO algorithm has also shown encouraging outcomes. Among the various prognostic genes linked to enzalutamide, TDP1 stands out as an important indicator of prognosis. Furthermore, immunofluorescence experiments confirmed that an increased expression of TDP1 is associated with a worse prognosis in patients with PRAD. Our results underscore the substantial potential of TDP1 as a novel diagnostic and prognostic biomarker for individuals diagnosed with PRAD.

Bloom syndrome (BS) is a rare genetic disorder associated with an elevated risk of cancer. In a national multicentre study, nine paediatric patients with BS and cancer were analysed. Median age at cancer diagnosis was 12 years. Four of the nine patients were diagnosed with BS prior to cancer detection. Six presented with solid tumours, whilst three had haematological malignancies. Six received polychemotherapy, often with dose reductions. Complications included prolonged aplasia, sepsis and early treatment discontinuation. Two patients received radiotherapy. Four relapsed, and four died, including one toxic death. However, five achieved remission, highlighting the possibility of curative treatment despite significant toxicities.

SLC35A1-CDG is a very rare type of congenital disorders of glycosylation (CDG) with only five cases known to date. Here, we review the literature and present new data from a sixth patient carrying the uncharacterized variant c.133A>G; p.Thr45Ala in the SLC35A1 gene. In addition to known clinical symptoms of SLC35A1-CDG, the patient presents with failure to thrive, short stature, café-au-lait spot, and preauricular ear tag. Even though examination of CDG markers transferrin (Tf), alpha-1-antitrypsin (A1AT), and apolipoprotein CIII (ApoCIII) revealed no abnormalities in serum, the patient’s fibroblasts showed significant alterations of protein expression or glycosylation of ICAM1, GP130, and TGN46 as well as differences in staining signals of lectins MAL-I, RCAI, and SNA and deviations in LC-MS analysis of total cellular N-glycans. Transfection of CRISPR/Cas9 generated SLC35A1 HEK293 knockout cells with either wild-type SLC35A1 or the c.133A>G variant restored the cellular CMP-Neu5Ac to wild-type levels, making a direct effect of p.Thr45Ala on the function of the transporter unlikely. Instead, our results imply that the residual transporter activity of 65% is caused by a decreased stability of the mutated SLC35A1 protein. Since O-GlcNAcylation was affected as well, energy and lipid homeostasis were analyzed and found to be significantly altered. Notably, proliferation and glycosylation of the SLC35A1-deficient patient fibroblasts were enhanced by supplementation of the cell culture medium with 10 mM GlcNAc.

Cardiac arrest (CA) prevention continues to be a substantial hurdle for global public health. Although dyslipidemia and 25-hydroxyvitamin D (25(OH)D) insufficiency are recognized contributing factors for cardiovascular disease (CVD), their causal relationship with CA risk is still uncertain. Here, we explored these correlations and pinpointed possible therapeutic targets for CA prevention though Mendelian randomization (MR). Both two-sample and multivariable MR analysis methods were conducted to assess how serum lipid traits and 25(OH)D influence the susceptibility to develop CA. Nine thousand nine hundred eighty-eight participants in total from the National Health and Nutrition Examination Survey (NHANES) engaged in validating the relationship between the concentrations of 25(OH)D and cardiovascular mortality in individuals with dyslipidemia. The integration of MR with expression quantitative trait locus (eQTL) analysis enabled the identification of druggable targets, and molecular docking was used to screen small molecules, which were subsequently validated in animal models. The MR results revealed that both elevated levels of low-density lipoprotein cholesterol (LDL-C) and apolipoprotein B (ApoB), as well as triglycerides (TGs), significantly contributed to an increased CA risk (p < 0.05). Conversely, higher amounts of apolipoprotein A1 (ApoA1), high-density lipoprotein cholesterol (HDL-C), and 25(OH)D were causally contributing to a decreased risk of CA (p < 0.05). A bidirectional causal relationship was observed among LDL-C, TG, ApoB, and 25(OH)D levels. Mediation MR suggests that dyslipidemia and low 25(OH)D status could potentially elevate the CA risk through pathways involving myocardial infarction, diabetes, and hypertension. NHANES data confirmed that higher 25(OH)D were tied to decreased risks of all-cause and CVD death among those with dyslipidemia (p < 0.01). Notably, chromobox 6 (CBX6), negatively associated with CA risk (OR = 0.87, 95% CI: 0.78–0.99, p = 0.029), was determined to be a target of both sanguinarine and lycorine, which improved lipid profiles and 25(OH)D in mice. In conclusion, dyslipidemia and low 25(OH)D status are causally related to CA risk, they appear to interact, and their coexistence may confer a higher risk of CVD mortality. Compounds targeting specific genes can both improve dyslipidemia and elevate 25(OH)D levels, thereby exhibiting potential therapeutic effects for preventing CA. Overall, this study enhances our understanding of the underlying mechanisms linking dyslipidemia, 25(OH)D deficiency, and CA and offers new perspectives for prevention.

Background: Some 234 mutations in the small SOD1 gene have been reported to cause amyotrophic lateral sclerosis. However, the pathogenic mechanisms, particularly of those mutations affecting polypeptide length, are contested. It is presently unknown whether all reported nonsense mutations in SOD1 are causative for ALS. The emergence of promising new anti-SOD1 drugs has made it imperative to gain further insight into clinical–genetic aspects of ALS for deciding which patients to treat in clinical practice and include in drug trials.

Objective: This study is aimed at comprehensively analyzing the clinical phenotypes associated with ALS-causing SOD1 mutations that alter the polypeptide length. The specific focus is on the age at which symptoms manifest and the survival duration.

Methods: Data were collected from web databases, published reports, conference presentations, and personal communications up to November 2023. The clinical endpoints, including age at symptom onset and age at death, were subjected to survival analysis. Comparative analyses were performed between frameshift and nonframeshift variants.

Results: A cohort of 146 ALS patients harboring 38 different nonmissense SOD1 variants was analyzed. The mean age of disease onset was 46.9 years, with a mean survival duration of 49 months. Significant heterogeneity was observed in clinical outcomes, with earlier disease onset and reduced survival associated with specific mutations. Notably, frameshift mutations proximal to the N-terminus showed a higher risk of early ALS onset compared to more distal mutations.

Conclusions: The clinical phenotypes of ALS patients with nonmissense SOD1 mutations are highly variable and dependent on the specific mutation. These findings underscore the necessity of including diverse SOD1 mutation carriers in therapeutic trials and suggest that both loss-of-function and gain-of-function mechanisms may contribute to ALS pathology.