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Shin et al. identify TBC1D23 as an adaptor that interacts both with golgins and endosomal WASH and is required for the delivery of endosome-derived vesicles to the trans -Golgi. The specificity of membrane traffic involves tethers at destination organelles that selectively capture incoming transport vesicles to allow SNAREs on opposing membranes to then assemble and drive fusion 1 , 2 . Tethers include both protein complexes and long coiled-coil proteins, although how they contribute to specificity remains unclear 3 , 4 . The golgin coiled-coil proteins at the Golgi apparatus capture vesicles from different origins, but the vesicle-specific molecular cues that they recognize are unknown 5 , 6 , 7 , 8 . Vesicle tethering is typically a transient process and therefore is challenging to interrogate in vivo . Thus, we have used a system in which an ectopic golgin causes vesicles to accumulate in a tethered state. By applying proximity biotinylation to the golgin-captured vesicles, we identify TBC1D23, an apparently catalytically inactive member of a family of Rab GTPase-activating proteins (GAPs), as a vesicle–golgin adaptor that is required for endosome-to-Golgi trafficking. The Rab GAP domain of TBC1D23 binds to a conserved motif at the tip of golgin-245 and golgin-97 at the trans -Golgi, while the C terminus binds to the WASH complex on endosome-derived vesicles. Thus, TBC1D23 is a specificity determinant that links the vesicle to the target membrane during endosome-to-Golgi trafficking.

Abstract BACKGROUND Increasing prevalence of metastatic disease has been accompanied by increasing rates of surgical intervention. Current tools have poor to fair predictive performance for intermediate (90-d) and long-term (1-yr) mortality. OBJECTIVE To develop predictive algorithms for spinal metastatic disease at these time points and to provide patient-specific explanations of the predictions generated by these algorithms. METHODS Retrospective review was conducted at 2 large academic medical centers to identify patients undergoing initial operative management for spinal metastatic disease between January 2000 and December 2016. Five models (penalized logistic regression, random forest, stochastic gradient boosting, neural network, and support vector machine) were developed to predict 90-d and 1-yr mortality. RESULTS Overall, 732 patients were identified with 90-d and 1-yr mortality rates of 181 (25.1%) and 385 (54.3%), respectively. The stochastic gradient boosting algorithm had the best performance for 90-d mortality and 1-yr mortality. On global variable importance assessment, albumin, primary tumor histology, and performance status were the 3 most important predictors of 90-d mortality. The final models were incorporated into an open access web application able to provide predictions as well as patient-specific explanations of the results generated by the algorithms. The application can be found at https://sorg-apps.shinyapps.io/spinemetssurvival/ CONCLUSION Preoperative estimation of 90-d and 1-yr mortality was achieved with assessment of more flexible modeling techniques such as machine learning. Integration of these models into applications and patient-centered explanations of predictions represent opportunities for incorporation into healthcare systems as decision tools in the future.

Intracellular traffic between compartments of the secretory and endocytic pathways is mediated by vesicle-based carriers. The proteomes of carriers destined for many organelles are ill-defined because the vesicular intermediates are transient, low-abundance and difficult to purify. Here, we combine vesicle relocalisation with organelle proteomics and Bayesian analysis to define the content of different endosome-derived vesicles destined for the trans-Golgi network (TGN). The golgin coiled-coil proteins golgin-97 and GCC88, shown previously to capture endosome-derived vesicles at the TGN, were individually relocalised to mitochondria and the content of the subsequently re-routed vesicles was determined by organelle proteomics. Our findings reveal 45 integral and 51 peripheral membrane proteins re-routed by golgin-97, evidence for a distinct class of vesicles shared by golgin-97 and GCC88, and various cargoes specific to individual golgins. These results illustrate a general strategy for analysing intracellular sub-proteomes by combining acute cellular re-wiring with high-resolution spatial proteomics. The vesicles that transport proteins between intracellular organelles are small, short-lived, and elusive. Here, the authors show that capture of these vesicles through relocalizing tethers to mitochondria allows their contents to be characterised by organelle proteomics.

Abstract BACKGROUND Preoperative prognostication of short-term postoperative mortality in patients with spinal metastatic disease can improve shared decision making around end-of-life care. OBJECTIVE To (1) develop machine learning algorithms for prediction of short-term mortality and (2) deploy these models in an open access web application. METHODS The American College of Surgeons, National Surgical Quality Improvement Program was used to identify patients that underwent operative intervention for metastatic disease. Four machine learning algorithms were developed, and the algorithm with the best performance across discrimination, calibration, and overall performance was integrated into an open access web application. RESULTS The 30-d mortality for the 1790 patients undergoing surgery for spinal metastatic disease was 8.49%. Preoperative factors used for prognostication were albumin, functional status, white blood cell count, hematocrit, alkaline phosphatase, spinal location (cervical, thoracic, lumbosacral), and severity of comorbid systemic disease (American Society of Anesthesiologist Class). In this population, machine learning algorithms developed to predict 30-d mortality performed well on discrimination (c-statistic), calibration (assessed by calibration slope and intercept), Brier score, and decision analysis. An open access web application was developed for the best performing model and this web application can be found here: https://sorg-apps.shinyapps.io/spinemets/. CONCLUSION Machine learning algorithms are promising for prediction of postoperative outcomes in spinal oncology and these algorithms can be integrated into clinically useful decision tools. As the volume of data in oncology continues to grow, creation of learning systems and deployment of these systems as accessible tools may significantly enhance prognostication and management.

Systemic assessment is a pillar in the neurological, oncological, mechanical, and systemic (NOMS) decision-making framework for the treatment of patients with spinal metastatic disease. Despite this importance, emerging evidence relating systemic considerations to clinical outcomes following surgery for spinal metastatic disease has not been comprehensively summarised. We aimed to conduct a scoping literature review of this broad topic. We searched MEDLINE, Embase, Scopus, Cochrane Central Register of Controlled Trials, Web of Science, and CINAHL databases from Jan 1, 2000, to July 31, 2021. 61 articles were included, accounting for a total of 22 335 patients. Preoperative systemic variables negatively associated with postoperative clinical outcomes included demographics (eg, older age [>60 years], Black race, male sex, low or elevated body-mass index, and smoking status), medical comorbidities (eg, cardiac, pulmonary, hepatic, renal, endocrine, vascular, and rheumatological), biochemical abnormalities (eg, hypoalbuminaemia, atypical blood cell counts, and elevated C-reactive protein concentration), low muscle mass, generalised motor weakness (American Spinal Cord Injury Association Impairment Scale grade and Frankel grade) and poor ambulation, reduced performance status, and systemic disease burden. This is the first comprehensive scoping review to broadly summarise emerging evidence relevant to the systemic assessment component of the widely used NOMS framework for spinal metastatic disease decision making. Medical, surgical, and radiation oncologists can consider these findings when prognosticating spinal metastatic disease-related surgical outcomes on the basis of patients’ systemic condition. These factors might inform a shared decision-making approach with patients and their families.

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer in adults. When ccRCC is localized to the kidney, surgical resection or ablation of the tumor is often curative. However, in the metastatic setting, ccRCC remains a highly lethal disease. Here we use fresh patient samples that include treatment-naive primary tumor tissue, matched adjacent normal kidney tissue, as well as tumor samples collected from patients with bone metastases. Single-cell transcriptomic analysis of tumor cells from the primary tumors reveals a distinct transcriptional signature that is predictive of metastatic potential and patient survival. Analysis of supporting stromal cells within the tumor environment demonstrates vascular remodeling within the endothelial cells. An in silico cell-to-cell interaction analysis highlights the CXCL9/CXCL10-CXCR3 axis and the CD70-CD27 axis as potential therapeutic targets. Our findings provide biological insights into the interplay between tumor cells and the ccRCC microenvironment. Metastatic clear cell renal cell carcinoma has a poor prognosis. Here, the authors use single cell RNA-seq to show a distinct gene expression signature in the primary tumour of metastatic patients, and highlights immune cell receptor interactions as potential therapeutic targets.

Recognition of lipids by proteins is important for their targeting and activation in many signaling pathways, but the mechanisms that regulate such interactions are largely unknown. Here, we found that binding of proteins to the ubiquitous signaling lipid phosphatidic acid (PA) depended on intracellular pH and the protonation state of its phosphate headgroup. In yeast, a rapid decrease in intracellular pH in response to glucose starvation regulated binding of PA to a transcription factor, Opi1, that coordinately repressed phospholipid metabolic genes. This enabled coupling of membrane biogenesis to nutrient availability.

Purpose To evaluate patient selection criteria, methodology, safety and clinical outcomes of stereotactic body radiotherapy (SBRT) for treatment of vertebral metastases. Materials and methods Eight centers from the United States (n = 5), Canada (n = 2) and Germany (n = 1) participated in the retrospective study and analyzed 301 patients with 387 vertebral metastases. No patient had been exposed to prior radiation at the treatment site. All patients were treated with linac-based SBRT using cone-beam CT image-guidance and online correction of set-up errors in six degrees of freedom. Results 387 spinal metastases were treated and the median follow-up was 11.8 months. The median number of consecutive vertebrae treated in a single volume was one (range, 1-6), and the median total dose was 24 Gy (range 8-60 Gy) in 3 fractions (range 1-20). The median EQD2 10 was 38 Gy (range 12-81 Gy). Median overall survival (OS) was 19.5 months and local tumor control (LC) at two years was 83.9%. On multivariate analysis for OS, male sex (p < 0.001; HR = 0.44), performance status <90 (p < 0.001; HR = 0.46), presence of visceral metastases (p = 0.007; HR = 0.50), uncontrolled systemic disease (p = 0.007; HR = 0.45), >1 vertebra treated with SBRT (p = 0.04; HR = 0.62) were correlated with worse outcomes. For LC, an interval between primary diagnosis of cancer and SBRT of ≤30 months (p = 0.01; HR = 0.27) and histology of primary disease (NSCLC, renal cell cancer, melanoma, other) (p = 0.01; HR = 0.21) were correlated with worse LC. Vertebral compression fractures progressed and developed de novo in 4.1% and 3.6%, respectively. Other adverse events were rare and no radiation induced myelopathy reported. Conclusions This multi-institutional cohort study reports high rates of efficacy with spine SBRT. At this time the optimal fractionation within high dose practice is unknown.

Introduction Intramedullary spinal cord tumors (IMSCTs) account for 2–4% of all primary CNS tumors. Given their low prevalence and the intricacy of their diagnosis and management, it is critical to address the surrounding racial and socioeconomic factors that impact the care of patients with IMSCTs. This study aimed to investigate the association between race and socioeconomic factors with overall 5 year mortality following the resection of IMSCTs. Methods The study used the National Cancer Database to retrospectively analyze patients who underwent resection of IMSCTs from 2004 to 2017. Patients were divided into four cohorts by race/ethnicity, facility type, insurance, median income quartiles, and living area. The primary outcome of interest was 5 year survival, and secondary outcomes included postoperative length of stay and 30 day readmission. Descriptive and multivariable analyses were used to identify independent factors associated with mortality, with statistical significance assessed at a 2-sided p < 0.05. Results We evaluated the patient characteristics and outcomes for 8,028 patients who underwent surgical treatment for IMSCTs between 2004 and 2017. Most patients were white males (52.4%) with a mean age of 44 years where 7.17% of patients were Black, 7.6% were Hispanic, and 3% were Asian. Most were treated in an academic/research program (72.4%) and had private insurance (69.2%). Black patients had a higher odd of 5 year mortality (OR 1.4; 95% CI 1.1 to 1.77; p  =  0.04) compared to white patients, while no significant differences in mortality were observed among other races. Factors associated with lower odds of mortality included being female (OR 0.89; 95% CI 0.78 to 1.02; p  <  0.01), receiving treatment in an academic/research program (OR 0.51; 95% CI 0.33 to 0.79; p  =  0.04), having private insurance (OR 0.65; 95% CI 0.45 to 0.93; p  =  0.02), and having higher income quartiles (OR 0.77; 95% CI 0.62 to 0.96; p  =  0.02). Conclusion Our study sheds light on the healthcare disparities that exist in the surgical management of IMSCTs. Our findings indicate that race, sex, socioeconomic status, and treatment facility are independent predictors of 5 year mortality, with Black patients, males, those with lower socioeconomic status, and those treated at non-academic centers experiencing significantly higher mortality rates. These alarming disparities underscore the urgent need for policymakers and researchers to address the underlying factors contributing to these discrepancies and provide equal access to high-quality surgical care for patients with IMSCTs.

Malnutrition, common in the elderly, may adversely affect healthcare outcomes. In spine surgery, malnutrition is associated with higher rates of perioperative complications, unplanned readmission, and prolonged length of stay (LOS). The aim of this study was to determine the effect of malnutrition on adverse events (AEs), unplanned readmission, and LOS in patients undergoing spine surgery for spondylolisthesis. A retrospective cohort study was performed using the American College of Surgeons National Surgical Quality Improvement Program database from 2010 to 2016. Adult patients who underwent posterior decompression or fusion for spondylolisthesis were identified using the ICD-9-CM coding systems. Patients were divided into two cohorts based on preoperative serum albumin levels. propensity-score (PS) matching was used to create an age- and sex-matched Nourished cohort. Patient demographics, comorbidities, LOS, and postoperative complications were collected. Multivariate logistic regression analysis was performed to identify predictors of prolonged LOS, unplanned readmission, and AEs. Of the 2196 patients identified, 4.5% were malnourished. Patients in the Malnourished cohort were found to have significantly longer average LOS (Malnourished: 4.51 ± 3.1 days vs PS-Matched Not Nourished: 3.7 ± 3.7, p = 0.002), higher rates of AEs (Malnourished: 14.3% vs PS-Matched Nourished: 5.8%, p = 0.007), reoperation (Malnourished: 8.4% vs PS-Matched Nourished: 3.2%, p = 0.026), and unplanned readmission (Malnourished: 15.3% vs PS-Matched Nourished: 6.1%, p = 0.003). On multivariate analysis considering only preoperative data, malnutrition was a significant independent predictor of AEs [OR: 2.13, CI (1.02, 4.46), p = 0.045]. However, after correcting for the occurrence of AEs, malnutrition was not associated with total LOS [aRR: 0.29, CI (−0.37, 0.95), p = 0.392] or 30-day unplanned readmissions [aOR: 2.24, CI (0.89, 5.60), p = 0.086]. Our study found that malnourished patients undergoing lumbar fusion for spondylolisthesis have significantly higher rates of AEs, unplanned readmission, and prolonged LOS than nourished patients. Further studies are necessary to corroborate our findings. •Malnutrition is associated with poor postoperative outcomes in spine surgery.•Poor outcomes include prolonged LOS, costs, adverse events, and readmission.•We examined the impact of malnutrition on spondylolisthesis surgery outcomes.•We found that malnourishment was associated with worse postoperative outcomes.•Malnutrition may be a driver of AEs in spondylolisthesis patients.