Pan-cancer proteogenomics connects oncogenic drivers to functional states.

Cancer driver events refer to key genetic aberrations that drive oncogenesis; however, their exact molecular mechanisms remain insufficiently understood. Here, our multi-omics pan-cancer analysis uncovers insights into the impacts of cancer drivers by identifying their significant cis-effects and distal trans-effects quantified at the RNA, protein, and phosphoprotein levels. Salient observations include the association of point mutations and copy-number alterations with the rewiring of protein interaction networks, and notably, most cancer genes converge toward similar molecular states denoted by sequence-based kinase activity profiles. A correlation between predicted neoantigen burden and measured T cell infiltration suggests potential vulnerabilities for immunotherapies. Patterns of cancer hallmarks vary by polygenic protein abundance ranging from uniform to heterogeneous. Overall, our work demonstrates the value of comprehensive proteogenomics in understanding the functional states of oncogenic drivers and their links to cancer development, surpassing the limitations of studying individual cancer types.

Proteogenomic characterization of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor patient survival. Toward understanding the underlying molecular alterations that drive PDAC oncogenesis, we conducted comprehensive proteogenomic analysis of 140 pancreatic cancers, 67 normal adjacent tissues, and 9 normal pancreatic ductal tissues. Proteomic, phosphoproteomic, and glycoproteomic analyses were used to characterize proteins and their modifications. In addition, whole-genome sequencing, whole-exome sequencing, methylation, RNA sequencing (RNA-seq), and microRNA sequencing (miRNA-seq) were performed on the same tissues to facilitate an integrated proteogenomic analysis and determine the impact of genomic alterations on protein expression, signaling pathways, and post-translational modifications. To ensure robust downstream analyses, tumor neoplastic cellularity was assessed via multiple orthogonal strategies using molecular features and verified via pathological estimation of tumor cellularity based on histological review. This integrated proteogenomic characterization of PDAC will serve as a valuable resource for the community, paving the way for early detection and identification of novel therapeutic targets.

A proteogenomic portrait of lung squamous cell carcinoma.

Lung squamous cell carcinoma (LSCC) remains a leading cause of cancer death with few therapeutic options. We characterized the proteogenomic landscape of LSCC, providing a deeper exposition of LSCC biology with potential therapeutic implications. We identify NSD3 as an alternative driver in FGFR1-amplified tumors and low-p63 tumors overexpressing the therapeutic target survivin. SOX2 is considered undruggable, but our analyses provide rationale for exploring chromatin modifiers such as LSD1 and EZH2 to target SOX2-overexpressing tumors. Our data support complex regulation of metabolic pathways by crosstalk between post-translational modifications including ubiquitylation. Numerous immune-related proteogenomic observations suggest directions for further investigation. Proteogenomic dissection of CDKN2A mutations argue for more nuanced assessment of RB1 protein expression and phosphorylation before declaring CDK4/6 inhibition unsuccessful. Finally, triangulation between LSCC, LUAD, and HNSCC identified both unique and common therapeutic vulnerabilities. These observations and proteogenomics data resources may guide research into the biology and treatment of LSCC.

Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma.

To explore the biology of lung adenocarcinoma (LUAD) and identify new therapeutic opportunities, we performed comprehensive proteogenomic characterization of 110 tumors and 101 matched normal adjacent tissues (NATs) incorporating genomics, epigenomics, deep-scale proteomics, phosphoproteomics, and acetylproteomics. Multi-omics clustering revealed four subgroups defined by key driver mutations, country, and gender. Proteomic and phosphoproteomic data illuminated biology downstream of copy number aberrations, somatic mutations, and fusions and identified therapeutic vulnerabilities associated with driver events involving KRAS, EGFR, and ALK. Immune subtyping revealed a complex landscape, reinforced the association of STK11 with immune-cold behavior, and underscored a potential immunosuppressive role of neutrophil degranulation. Smoking-associated LUADs showed correlation with other environmental exposure signatures and a field effect in NATs. Matched NATs allowed identification of differentially expressed proteins with potential diagnostic and therapeutic utility. This proteogenomics dataset represents a unique public resource for researchers and clinicians seeking to better understand and treat lung adenocarcinomas.

Proteogenomic Characterization of Endometrial Carcinoma.

We undertook a comprehensive proteogenomic characterization of 95 prospectively collected endometrial carcinomas, comprising 83 endometrioid and 12 serous tumors. This analysis revealed possible new consequences of perturbations to the p53 and Wnt/ß-catenin pathways, identified a potential role for circRNAs in the epithelial-mesenchymal transition, and provided new information about proteomic markers of clinical and genomic tumor subgroups, including relationships to known druggable pathways. An extensive genome-wide acetylation survey yielded insights into regulatory mechanisms linking Wnt signaling and histone acetylation. We also characterized aspects of the tumor immune landscape, including immunogenic alterations, neoantigens, common cancer/testis antigens, and the immune microenvironment, all of which can inform immunotherapy decisions. Collectively, our multi-omic analyses provide a valuable resource for researchers and clinicians, identify new molecular associations of potential mechanistic significance in the development of endometrial cancers, and suggest novel approaches for identifying potential therapeutic targets.

Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma.

To elucidate the deregulated functional modules that drive clear cell renal cell carcinoma (ccRCC), we performed comprehensive genomic, epigenomic, transcriptomic, proteomic, and phosphoproteomic characterization of treatment-naive ccRCC and paired normal adjacent tissue samples. Genomic analyses identified a distinct molecular subgroup associated with genomic instability. Integration of proteogenomic measurements uniquely identified protein dysregulation of cellular mechanisms impacted by genomic alterations, including oxidative phosphorylation-related metabolism, protein translation processes, and phospho-signaling modules. To assess the degree of immune infiltration in individual tumors, we identified microenvironment cell signatures that delineated four immune-based ccRCC subtypes characterized by distinct cellular pathways. This study reports a large-scale proteogenomic analysis of ccRCC to discern the functional impact of genomic alterations and provides evidence for rational treatment selection stemming from ccRCC pathobiology.

Polysaccharide-Based Composite Hydrogel with Hierarchical Microstructure for Enhanced Vascularization and Skull Regeneration.

Critical-size skull defects caused by trauma, infection, and tumor resection raise great demands for efficient bone substitutes. Herein, a hybrid cross-linked hierarchical microporous hydrogel scaffold (PHCLS) was successfully assembled by a multistep procedure, which involved (i) the preparation of poly(lactic-co-glycolic)/nanohydroxyapatite (PLGA-HAP) porous microspheres, (ii) embedding the spheres in a solution of dopamine-modified hyaluronic acid and collagen I (Col I) and cross-linking via dopamine polyphenols binding to (i) Col I amino groups (via Michael addition) and (ii) PLGA-HAP (via calcium ion chelation). The introduction of PLGA-HAP not only improved the diversity of pore size and pore communication inside the matrix but also greatly enhanced the compressive strength (5.24-fold, 77.5 kPa) and degradation properties to construct a more stable mechanical structure. In particular, the PHCLS (200 mg, nHAP) promoted the proliferation, infiltration, and angiogenic differentiation of bone marrow mesenchymal stem cells in vitro, as well as significant ectopic angiogenesis and mineralization with a storage modulus enhancement of 2.5-fold after 30 days. Meanwhile, the appropriate matrix microenvironment initiated angiogenesis and early osteogenesis by accelerating endogenous stem cell recruitment in situ. Together, the PHCLS allowed substantial skull reconstruction in the rabbit cranial defect model, achieving 85.2% breaking load strength and 84.5% bone volume fractions in comparison to the natural cranium, 12 weeks after implantation. Overall, this study reveals that the hierarchical microporous hydrogel scaffold provides a promising strategy for skull defect treatment.

High-Proportion Blue Light Irradiation at the End-of-Production Stage Promotes the Biosynthesis and Recycling of Ascorbate in Lettuce.

Ascorbate (AsA), an essential antioxidant for both plants and the human body, plays a vital role in maintaining proper functionality. Light plays an important role in metabolism of AsA in horticultural plants. Our previous research has revealed that subjecting lettuce to high light irradiation (HLI) (500 µmol·m-2·s-1) at the end-of-production (EOP) stage effectively enhances AsA levels, while the optimal light quality for AsA accumulation is still unknown. In this study, four combinations of red (R) and blue (B) light spectra with the ratio of 1:1 (1R1B), 2:1 (2R1B), 3:1 (3R1B), and 4:1 (4R1B) were applied to investigate the biosynthesis and recycling of AsA in lettuce. The results demonstrated that the AsA/total-AsA content in lettuce leaves was notably augmented upon exposure to 1R1B and 2R1B. Interestingly, AsA levels across all treatments increased rapidly at the early stage (2-8 h) of irradiation, while they increased slowly at the late stage (8-16 h). The activity of L-galactono-1,4-lactone dehydrogenase was augmented under 1R1B treatment, which is pivotal to AsA production. Additionally, the activities of enzymes key to AsA cycling were enhanced by 1R1B and 2R1B treatments, including ascorbate peroxidase, dehydroascorbate reductase, and monodehydroascorbate reductase. Notably, hydrogen peroxide and malondialdehyde accumulation increased dramatically following 16 h of 1R1B and 2R1B treatments. In addition, although soluble sugar and starch contents were enhanced by EOP-HLI, this effect was comparatively subdued under the 1R1B treatment. Overall, these results indicated that AsA accumulation was improved by irradiation with a blue light proportion of over 50% in lettuce, aligning with the heightened activities of key enzymes responsible for AsA synthesis, as well as the accrual of hydrogen peroxide. The effective strategy holds the potential to enhance the nutritional quality of lettuce while bolstering its antioxidant defenses.

Systematic analysis of the sugar accumulation mechanism in sucrose- and hexose- accumulating cherry tomato fruits.

BACKGROUND: Sugar content is an important indicator of fruit quality. Except for a few wild tomato species that accumulate sucrose in the fruits, most cultivated tomato species accumulate hexose. Although several studies have focused on wild sucrose-accumulating tomato, the sucrose accumulation mechanism is still unclear. RESULTS: Here, two homozygous inbred cherry tomato lines ('TB0023' and 'TB0278', which accumulated sucrose and hexose, respectively) were selected to analyze the sugar accumulation mechanism. Carbohydrate analysis, cytological observation, gene expression and enzyme activity analysis and proteomics methods were used in this study. The results indicated that glucose and fructose were absolutely dominant in the soluble sugar content of hexose-accumulating cherry tomato fruit, while sucrose and a certain proportion of hexose were the main forms of soluble sugar in sucrose-accumulating cherry tomato fruit. The phloem unloading pathway of the hexose-accumulating cherry tomato fruit switched from symplastic to apoplastic during fruit development, and the sucrose-accumulating cherry tomato probably had a mixed unloading pathway involving the symplastic and apoplastic. High activity of acid invertase (AI), sucrose phosphate synthase (SPS), sucrose synthase (SS) and sugar transporters LeSUT1, SlSWEET2a and SlSWEET12c were important factors for hexose accumulation in the hexose-accumulating cherry tomato fruit, while LeSUT2, SPS, SS, SlSWEET1b, SlSWEET5b, SlSWEET11b, SlSWEET7a, SlSWEET14 were responsible for solute sugar accumulation in the sucrose-accumulating cherry tomato. CONCLUSIONS: This study provides detailed evidence for elucidation of the tomato sugar accumulation mechanism from the perspective of cell structure, physiology and molecular biology, providing a theoretical basis for the improvement of tomato quality and aiding the utilization of tomato genetic resources.

Prediction of Maternal Hemorrhage Using Machine Learning: Retrospective Cohort Study.

BACKGROUND: Postpartum hemorrhage remains one of the largest causes of maternal morbidity and mortality in the United States. OBJECTIVE: The aim of this paper is to use machine learning techniques to identify patients at risk for postpartum hemorrhage at obstetric delivery. METHODS: Women aged 18 to 55 years delivering at a major academic center from July 2013 to October 2018 were included for analysis (N=30,867). A total of 497 variables were collected from the electronic medical record including the following: demographic information; obstetric, medical, surgical, and family history; vital signs; laboratory results; labor medication exposures; and delivery outcomes. Postpartum hemorrhage was defined as a blood loss of ≥1000 mL at the time of delivery, regardless of delivery method, with 2179 (7.1%) positive cases observed. Supervised learning with regression-, tree-, and kernel-based machine learning methods was used to create classification models based upon training (21,606/30,867, 70%) and validation (4630/30,867, 15%) cohorts. Models were tuned using feature selection algorithms and domain knowledge. An independent test cohort (4631/30,867, 15%) determined final performance by assessing for accuracy, area under the receiver operating curve (AUROC), and sensitivity for proper classification of postpartum hemorrhage. Separate models were created using all collected data versus models limited to data available prior to the second stage of labor or at the time of decision to proceed with cesarean delivery. Additional models examined patients by mode of delivery. RESULTS: Gradient boosted decision trees achieved the best discrimination in the overall model. The model including all data mildly outperformed the second stage model (AUROC 0.979, 95% CI 0.971-0.986 vs AUROC 0.955, 95% CI 0.939-0.970). Optimal model accuracy was 98.1% with a sensitivity of 0.763 for positive prediction of postpartum hemorrhage. The second stage model achieved an accuracy of 98.0% with a sensitivity of 0.737. Other selected algorithms returned models that performed with decreased discrimination. Models stratified by mode of delivery achieved good to excellent discrimination but lacked the sensitivity necessary for clinical applicability. CONCLUSIONS: Machine learning methods can be used to identify women at risk for postpartum hemorrhage who may benefit from individualized preventative measures. Models limited to data available prior to delivery perform nearly as well as those with more complete data sets, supporting their potential utility in the clinical setting. Further work is necessary to create successful models based upon mode of delivery and to validate the findings of this study. An unbiased approach to hemorrhage risk prediction may be superior to human risk assessment and represents an area for future research.

Analog transmission of action potential fine structure in spiral ganglion axons.

Action potential waveforms generated at the axon initial segment (AIS) are specialized between and within neuronal classes. But is the fine structure of each electrical event retained when transmitted along myelinated axons or is it rapidly and uniformly transmitted to be modified again at the axon terminal? To address this issue, action potential axonal transmission was evaluated in a class of primary sensory afferents that possess numerous types of voltage-gated ion channels underlying a complex repertoire of endogenous firing patterns. In addition to their signature intrinsic electrophysiological heterogeneity, spiral ganglion neurons are uniquely designed. The bipolar, myelinated somata of type I neurons are located within the conduction pathway, requiring that action potentials generated at the first heminode must be conducted through their electrically excitable membrane. We used this unusual axonal-like morphology to serve as a window into action potential transmission to compare locally evoked action potential profiles to those generated peripherally at their glutamatergic synaptic connections with hair cell receptors. These comparisons showed that the distinctively shaped somatic action potentials were highly correlated with the nodally generated, invading ones for each neuron. This result indicates that the fine structure of the action potential waveform is maintained axonally, thus supporting the concept that analog signaling is incorporated into each digitally transmitted action potential in the specialized primary auditory afferents.NEW & NOTEWORTHY Diverse action potential shapes and kinetics resulting from dynamic heterogeneity in spiral ganglion neurons are axonally transmitted as multiplexed signals that retain the fine structure of each distinctive waveform within a digital code.

Increased neuronal activity in motor cortex reveals prominent calcium dyshomeostasis in tauopathy mice.

Perturbed neuronal Ca2+ homeostasis is implicated in Alzheimer's disease, which has primarily been demonstrated in mice with amyloid-ß deposits but to a lesser and more variable extent in tauopathy models. In this study, we injected AAV to express Ca2+ indicator in layer II/III motor cortex neurons and measured neuronal Ca2+ activity by two photon imaging in awake transgenic JNPL3 tauopathy and wild-type mice. Various biochemical measurements were conducted in postmortem mouse brains for mechanistic insight and a group of animals received two intravenous injections of a tau monoclonal antibody spaced by four days to test whether the Ca2+ dyshomeostasis was related to pathological tau protein. Under running conditions, we found abnormal neuronal Ca2+ activity in tauopathy mice compared to age-matched wild-type mice with higher frequency of Ca2+ transients, lower amplitude of peak Ca2+ transients and lower total Ca2+ activity in layer II/III motor cortex neurons. While at resting conditions, only Ca2+ frequency was increased. Brain levels of soluble pathological tau correlated better than insoluble tau levels with the degree of Ca2+ dysfunction in tauopathy mice. Furthermore, tau monoclonal antibody 4E6 partially rescued Ca2+ activity abnormalities in tauopathy mice after two intravenous injections and decreased soluble pathological tau protein within the brain. This correlation and antibody effects strongly suggest that the neuronal Ca2+ dyshomeostasis is causally linked to pathological tau protein. These findings also reveal more pronounced neuronal Ca2+ dysregulation in tauopathy mice than previously reported by two-photon imaging that can be partially corrected with an acute tau antibody treatment.

Extracting Pathway-level Signatures from Proteogenomic Data in Breast Cancer Using Independent Component Analysis.

Recent advances in the multi-omics characterization necessitate knowledge integration across different data types that go beyond individual biomarker discovery. In this study, we apply independent component analysis (ICA) to human breast cancer proteogenomics data to retrieve mechanistic information. We show that as an unsupervised feature extraction method, ICA was able to construct signatures with known biological relevance on both transcriptome and proteome levels. Moreover, proteome and transcriptome signatures can be associated by their respective correlation with patient clinical features, providing an integrated description of phenotype-related biological processes. Our results demonstrate that the application of ICA to proteogenomics data could lead to pathway-level knowledge discovery. Potential extension of this approach to other data and cancer types may contribute to pan-cancer integration of multi-omics information.

Primary cerebellar glioblastomas in children: clinical presentation and management.

Pediatric cerebellar glioblastomas (pcGBMs) are rare and their characteristics remain ill-defined. We conducted a retrospective analysis of pediatric cerebellar glioblastomas who underwent surgery from 2008 to 2019 in our department. Besides, we performed a literature review of the literature data on pcGBMs. Ten children with mean age of 9.4 years were included. During the follow-up, six patients died with mean survival time of 11.7 months, four patients survived with mean follow-up of 28 months. Seven patients underwent molecular analysis, no patients detected IDH1 mutations, four patients (57.1%) had H3K27M mutations, and two patients (28.6%) had MGMT promoter methylation. The literature review identified 38 pcGBMs cases (including ours), with mean age of 8.84 ± 4.20 years (range, 1-16 years). Increased ICP was the commonest sign. Eighteen (47.4%) patients underwent GTR and fifteen (45.5%) patients received STR. Postoperative radiation (RT) was conducted in 28 patients (75.7%) and 23 patients (65.7%) received chemotherapy. During the follow-up, 25 patients died with mean survival time of 12.21 months and 11 patients survived with average follow-up of 29.3 months. Kaplan-Meier survival depicted chemotherapy (P < 0.001) or radiation (P < 0.001) had positive impact on overall survival. Multivariate analysis revealed chemotherapy was a significant predictor of survival with a hazard ratio of 3.264 (P = 0.038). Our study found mean overall survival time for pcGBMs patients was 12.21 months. PcGBMs may have distinct molecular features, with higher incidence of H3K27M mutation and were always IDH1 wild-type. We recommend the routine postoperative radiotherapy and chemotherapy in pcGBMs.

Predictive Modeling of Morbidity and Mortality in Patients Hospitalized With COVID-19 and its Clinical Implications: Algorithm Development and Interpretation.

BACKGROUND: The COVID-19 pandemic began in early 2021 and placed significant strains on health care systems worldwide. There remains a compelling need to analyze factors that are predictive for patients at elevated risk of morbidity and mortality. OBJECTIVE: The goal of this retrospective study of patients who tested positive with COVID-19 and were treated at NYU (New York University) Langone Health was to identify clinical markers predictive of disease severity in order to assist in clinical decision triage and to provide additional biological insights into disease progression. METHODS: The clinical activity of 3740 patients at NYU Langone Hospital was obtained between January and August 2020; patient data were deidentified. Models were trained on clinical data during different parts of their hospital stay to predict three clinical outcomes: deceased, ventilated, or admitted to the intensive care unit (ICU). RESULTS: The XGBoost (eXtreme Gradient Boosting) model that was trained on clinical data from the final 24 hours excelled at predicting mortality (area under the curve [AUC]=0.92; specificity=86%; and sensitivity=85%). Respiration rate was the most important feature, followed by SpO2 (peripheral oxygen saturation) and being aged 75 years and over. Performance of this model to predict the deceased outcome extended 5 days prior, with AUC=0.81, specificity=70%, and sensitivity=75%. When only using clinical data from the first 24 hours, AUCs of 0.79, 0.80, and 0.77 were obtained for deceased, ventilated, or ICU-admitted outcomes, respectively. Although respiration rate and SpO2 levels offered the highest feature importance, other canonical markers, including diabetic history, age, and temperature, offered minimal gain. When lab values were incorporated, prediction of mortality benefited the most from blood urea nitrogen and lactate dehydrogenase (LDH). Features that were predictive of morbidity included LDH, calcium, glucose, and C-reactive protein. CONCLUSIONS: Together, this work summarizes efforts to systematically examine the importance of a wide range of features across different endpoint outcomes and at different hospitalization time points.

Lead recovery from spent lead acid battery paste by hydrometallurgical conversion and thermal degradation.

Spent lead paste is the main component in lead-acid batteries reaching end of life. It contains about 55% lead sulphate and 35% lead dioxide, as well as minor amounts of lead oxide. It is necessary to recycle spent lead paste with minimal pollution and low energy consumption instead of the conventional smelting method. In this study, a novel approach involving hydrometallurgical desulphurisation and thermal degradation is developed to recover lead as PbO products from spent lead acid batteries. First, the desulphurisation effects and phase compositions of products with different transforming agents were compared, and the optimum conditions using (NH4)2CO3 as a transforming agent were determined. And then, the thermal degradation processes of both precursors lead carbonate and lead dioxide were investigated to prepare α-PbO, Pb3O4, and ß-PbO products in argon and air atmospheres, respectively. Both the desulphurisation precursors and the calcination products were characterised by thermogravimetry and differential scanning calorimetry, X-ray diffraction, and scanning electron microscopy. The results showed that the lead oxide products were prepared, including α-PbO at 450°C in argon, Pb3O4 and ß-PbO at 480°C and 620°C in air, respectively.

Superoxide dismutase coding of gene polymorphisms associated with susceptibility to Parkinson's disease.

Oxidative stress linked to the etiology of Parkinson's disease, which is characterized by chronic and progressive neurodegeneration of dopamine neurons. Superoxide dismutase enzymes (SODs) regarded as the first line of defense against oxidative damage. This study assessed the potential associations of gene polymorphisms in SOD1 (encoding Cu/Zn-SOD), SOD2 (encoding Mn-SOD) and SOD3 (encoding extracellular-SOD) with susceptibility to Parkinson's disease. A case-control study, including Parkinson's disease cases (n = 356) and controls (n = 370). Single nucleotide polymorphisms of SOD1 (rs2070424 A/G), SOD2 (rs4880 T/C) and SOD3 (rs1799895, C/G) were genotyped. Results indicated that AG or GG genotype carriers in SOD1 had a much greater risk of Parkinson's disease compared to corresponding AA genotypes, and allele G carriers had increased risk versus allele A carriers in the single nucleotide polymorphism (rs2070424 A/G) in SOD1. Further, TC or CC genotype carriers in SOD2 had a much higher risk of Parkinson's disease compared with corresponding TT genotypes, and the C carriers had an increased risk over allele T carriers in the single nucleotide polymorphism (rs4880 T/C) in SOD2. Together, carrying allele G in the single nucleotide polymorphism (rs2070424 A/G) in SOD1, or allele C in the single nucleotide polymorphism (rs4880 T/C) in SOD2, enhances genetic susceptibility to Parkinson's disease.

Pediatric central nervous system hemangioblastomas: different from adult forms? A retrospective series of 25 cases.

BACKGROUND: Pediatric hemangioblastomas are rare, and the clinical features, timing of surgical intervention, optimal treatment, and clinical outcomes are still unclear. METHODS: We performed a retrospective study of all patients with CNS hemangioblastomas who were treated at West China Hospital from January 2003 to March 2015. Patients under the age of 16 years were included in the study. The medical records of these patients were reviewed and statistically analyzed. RESULTS: Twenty-five children (15 females and ten males, [mean age 12.6 ± 4.7 years, range 1-16 years]) presented with hemangioblastomas. Tumors were detected in the cerebellum, brainstem, and spinal cord in 40, 28, and 32% of patients, respectively. Sixteen children (64%) had VHL syndrome. The most frequent symptoms were those related to increased intracranial pressure. The mean duration of symptoms was 1.5 ± 2.1 months. Preoperative hydrocephalus was noted in 11 children (44%). Gross total resection was achieved in all children. Clinical symptoms improved in 19 children (76%), unchanged in four children (16%), and aggravated in two children (8%), respectively. The mean follow-up was 44.5 ± 32.3 months. Five patients (20%) experienced disease progression. Using univariate analysis, both tumor-associated cysts (P = 0.027) and VHL disease (P = 0.032) were significantly related to postoperative outcomes. CONCLUSIONS: Pediatric hemangioblastomas have many different clinical features compared with adult cases. A high degree of suspicion for VHL disease should be raised in pediatric hemangioblastomas. Despite many challenges involved, surgical outcomes for pediatric hemangioblastomas are favorable. Lifelong follow-up is mandatory to detect the disease progression.

Nerve atrophy in trigeminal neuralgia due to neurovascular compression and its association with surgical outcomes after microvascular decompression.

BACKGROUND: Idiopathic trigeminal neuralgia (TN) is caused by neurovascular compression and is often related to morphological changes in the trigeminal nerve. The aim of this study was to quantitatively measure atrophic changes of trigeminal nerves in patients with TN, and to further investigate whether nerve atrophy affected the efficacy of microvascular decompression (MVD). METHODS: We conducted a prospective case-control study of 60 consecutive patients with TN and 30 sex- and age-matched healthy controls. All subjects underwent high-resolution three-dimensional MRI. The volume of the cisternal segment of trigeminal nerves was measured and compared using 3D Slicer software. Patients with TN underwent primary MVD and regular follow-up for at least 2 years. Associations of nerve atrophy with patient characteristics and operative outcomes were analyzed. RESULTS: The mean volume of the affected trigeminal nerve was significantly reduced in comparison to that of the nonaffected side (65.8 ± 21.1 versus 77.9 ± 19.3 mm3, P = 0.001) and controls (65.8 ± 21.1 versus 74.7 ± 16.5 mm3, P = 0.003). Fifty-two patients (86.7%) achieved complete pain relief without medication immediately after surgery, and 77.6% of patients were complete pain relief at the 2-year follow-up. The Spearman correlation test showed that there was a positive correlation (r = 0.46, P = 0.018) between the degree of trigeminal nerve indentation and nerve atrophy. In multivariate logistic regression analysis, two factors, indentation on nerve root (OR = 2.968, P = 0.022) and degree of nerve atrophy (OR = 1.18, P = 0.035), were associated with the long-term outcome. CONCLUSIONS: TN is associated with atrophy on the affected nerve. Furthermore, greater nerve atrophy is associated with more severe trigeminal nerve indentation and better long-term outcome following MVD.