One-year Outcome Evaluation after Interspinous Implantation for Degenerative Spinal Stenosis with Segmental Instability

The authors hypothesized that the placement of the interspinous implant would show a similar clinical outcome to the posterior lumbar interbody fusion (PLIF) in patients having spinal stenosis with mild segmental instability and that this method would be superior to PLIF without significantly affecting degeneration at the adjacent segments. Forty two adult patients having degenerative spinal stenosis with mild segmental instabilit who underwent implantation of Coflex™ (Spine motion, Germany) or PLIF at L4-5 between January 2000 and December 2003 were consecutively selected and studied for one-year clinical outcome. At 12 months after surgery, both groups showed a significant improvement in the visual analogue scale score and Oswestry disability index score for both lower extremity pain and low back pain. However, the range of motion at the upper adjacent segments (L3-4) increased significantly after surgery in the PLIF group, which was not manifested in the Coflex™ group during the follow-up. The authors assumed that interspinous implantation can be an alternative treatment for the spinal stenosis with segmental instability in selected conditions posing less stress on the superior adjacent level than PLIF

Patient-Specific Orthotopic Glioblastoma Xenograft Models Recapitulate the Histopathology and Biology of Human Glioblastomas In Situ

SummaryFrequent discrepancies between preclinical and clinical results of anticancer agents demand a reliable translational platform that can precisely recapitulate the biology of human cancers. Another critical unmet need is the ability to predict therapeutic responses for individual patients. Toward this goal, we have established a library of orthotopic glioblastoma (GBM) xenograft models using surgical samples of GBM patients. These patient-specific GBM xenograft tumors recapitulate histopathological properties and maintain genomic characteristics of parental GBMs in situ. Furthermore, in vivo irradiation, chemotherapy, and targeted therapy of these xenograft tumors mimic the treatment response of parental GBMs. We also found that establishment of orthotopic xenograft models portends poor prognosis of GBM patients and identified the gene signatures and pathways signatures associated with the clinical aggressiveness of GBMs. Together, the patient-specific orthotopic GBM xenograft library represent the preclinically and clinically valuable “patient tumor’s phenocopy” that represents molecular and functional heterogeneity of GBMs

Transcriptional regulatory networks of tumor-associated macrophages that drive malignancy in mesenchymal glioblastoma.

BACKGROUND: Glioblastoma (GBM) is a complex disease with extensive molecular and transcriptional heterogeneity. GBM can be subcategorized into four distinct subtypes; tumors that shift towards the mesenchymal phenotype upon recurrence are generally associated with treatment resistance, unfavorable prognosis, and the infiltration of pro-tumorigenic macrophages. RESULTS: We explore the transcriptional regulatory networks of mesenchymal-associated tumor-associated macrophages (MA-TAMs), which drive the malignant phenotypic state of GBM, and identify macrophage receptor with collagenous structure (MARCO) as the most highly differentially expressed gene. MARCO CONCLUSIONS: Collectively, our study characterizes the global transcriptional profile of TAMs driving mesenchymal GBM pathogenesis, providing potential therapeutic targets for improving the effectiveness of GBM immunotherapy

Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild-type primary glioblastoma

Background Although temozolomide (TMZ) has been used as a standard adjuvant chemotherapeutic agent for primary glioblastoma (GBM), treating isocitrate dehydrogenase wild-type (IDH-wt) cases remains challenging due to intrinsic and acquired drug resistance. Therefore, elucidation of the molecular mechanisms of TMZ resistance is critical for its precision application. Methods We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy. Results In vitro TMZ sensitivity of patient-derived GSCs classified patients into groups with different survival outcomes (P = 1.12e−4 for progression-free survival (PFS) and 3.63e−4 for overall survival (OS)). Moreover, we found that elevated gene expression of EGR4, PAPPA, LRRC3, and ANXA3 was associated to intrinsic TMZ resistance. In addition, other features such as 5-aminolevulinic acid negative, mesenchymal/proneural expression subtypes, and hypermutation phenomena were prone to promote TMZ resistance. In contrast, concurrent copy-number-alteration in PTEN, EGFR, and CDKN2A/B was more frequent in TMZ-sensitive samples (Fishers exact P = 0.0102), subsequently consolidated by multi-sector sequencing analyses. Integrating all features, we trained a ML tool to segregate TMZ-resistant and sensitive groups. Notably, our method segregated IDH-wt GBM patients from The Cancer Genome Atlas (TCGA) into two groups with divergent survival outcomes (P = 4.58e−4 for PFS and 3.66e−4 for OS). Furthermore, we showed a highly heterogeneous TMZ-response pattern within each GBM patient usingin vitro TMZ screening and genomic characterization of multisector GSCs. Lastly, the prediction model that evaluates the TMZ efficacy for primary IDH-wt GBMs was developed into a webserver for public usage (http://www.wang-lab-hkust.com:3838/TMZEP) Conclusions We identified molecular characteristics associated to TMZ sensitivity, and illustrate the potential clinical value of a ML model trained from pharmacogenomic profiling of patient-derived GSC against IDH-wt GBMs

Parafoveal and Peripapillary Perfusion Predict Visual Field Recovery in Chiasmal Compression due to Pituitary Tumors

Background: To evaluate the potential of vessel density alterations for predicting postoperative visual field (VF) improvement in chiasmal compression using optical coherence tomography angiography (OCT-A). Methods: The study investigated 57 eyes of 57 patients diagnosed with pituitary tumors and 42 eyes of 42 age and refractive error matched controls. All eyes with chiasmal compression for which preoperative optical coherence tomography (OCT) and OCT-A, and pre- and postoperative VF data were available. Preoperative vessel densities of superficial retinal capillary plexus (SRCP), deep retinal capillary plexus (DRCP), and radial peripapillary capillary (RPC) segment were utilized by OCT-A. Results: Preoperative peripapillary retinal nerve fiber layer and ganglion cell layer complex thickness and vessel densities of SRCP and RPC segments in eyes with chiasmal compression were significantly reduced compared with healthy controls (p < 0.001, p < 0.001, p = 0.007, and p = 0.020, respectively). In multivariate regression analysis, preoperative perimetric mean deviation (MD) (p = 0.002) and vessel density of SRCP (p = 0.025) were correlated significantly with postoperative perimetric MD. Spearman’s correlation analysis revealed significant correlations between preoperative MD on perimetry (r = 0.443, p = 0.001), vessel densities of SRCP (r = 0.288, p = 0.035) and RPC segment (r = 0.347, p = 0.009), and postoperative perimetric MD. Conclusions: Structural degeneration referred to as microvascular alterations measured by OCT-A and preoperative VF defects were associated with worse postoperative VF prognosis. Parafoveal and peripapillary vessel densities may serve as a sensitive, structural prognostic factors in the preoperative judgement of chiasmal compression

Comparison of Graft Materials in Multilayer Reconstruction with Nasoseptal Flap for High-Flow CSF Leak during Endoscopic Skull Base Surgery

Cerebrospinal fluid (CSF) leak is a crucial complication after endoscopic skull base surgery. Therefore, multilayer reconstruction with grafts is as essential as a reconstruction with pedicled flaps. Although widely used, the multilayer technique with autologous fascia lata has drawbacks, such as additional wound and donor site complications. We compared acellular dermal graft and banked homologous fascia lata graft (alternative grafts) with autologous fascia lata graft for high-flow CSF leak repair. We retrospectively enrolled 193 subjects who underwent endoscopic skull base reconstruction with multilayer fascial grafts and nasoseptal flap for high-flow CSF leaks from November 2014 to February 2020 at a single institution. Acellular dermal matrix (ADM), banked homologous fascia lata, and autologous fascia lata were used in 48 (24.9%), 102 (52.8%), and 43 (22.3%) patients, respectively. Postoperative CSF leaks occurred in 23 (11.9%) patients and meningitis in 8 (4.1%). There was no significant difference in postoperative CSF leak (p = 0.36) and meningitis (p = 0.17) across the graft groups. Additionally, we could not find out contributing risk factors for postoperative CSF leak and meningitis. ADM and banked homologous fascia lata are non-inferior to autologous fascia lata for endoscopic skull base reconstruction in water-tight reconstruction or safety without additional donor site morbidities

Radiomics features to distinguish glioblastoma from primary central nervous system lymphoma on multi-parametric MRI

Retrospective evaluation of data was approved by the local ethics committee and informed consent was waived. A total of 143 patients (two independent cohorts for discovery [n = 86; glioblastoma = 49, PCNSL = 37] and validation [n = 57; glioblastoma = 29, PCNSL = 28]) with newly diagnosed glioblastoma and PCNSL were subjected to radiomics analysis using the multi-parametric MRI (contrast-enhanced T1-weighted imaging, T2-weighted imaging, and diffusion-weighted imaging). Radiomics analyses were performed for two types of regions of interest (ROI) covering contrast-enhancing tumor and whole (enhancing or non-enhancing) tumor plus peritumoral edema. A total of 127 radiomics features were calculated. Feature selection was performed to identify the most discriminating features for every MR image in the discovery cohort. The identified features were used to calculate radiomics scores, which were later used in logistic regression to distinguish between PCNSL and glioblastoma. The classification model was further tested on the independent validation cohort. Results Fifteen features were selected as significant features in the discovery cohort. Using the identified features and calculated radiomics scores, the logistic regression-based classifier yielded an area under the curve (AUC) of 0.979, sensitivity of 0.938, and specificity of 0.944 in the discovery cohort to distinguish between glioblastoma and PCNSL. A similarly high rate of performance was observed in the validation cohort (AUC = 0.956) (c) Springer-Verlag GmbH Germany, part of Springer Nature 201