Citations

Currently available bioinformatics tools to identify BGCs from metagenomic sequencing data are limited in their predictive capability or ease of use to even computationally oriented researchers. We present an automated computational pipeline called TaxiBGC, which predicts experimentally characterized BGCs (and infers their known SMs) in shotgun metagenomes by first considering the microbial species source.

Abstract B-cell lymphoma is a potential cause of spinal cord compression that presents with nonspecific symptoms and inconsistent imaging findings. Surgical decompression is a mainstay for both diagnosis and management especially in patients with acute neurologic deficits; however, the long-term efficacy of intervention is still unclear. We perform a systematic review of the clinical symptoms, radiographic findings, and outcome after spinal decompression in B-cell lymphoma. The databases of Medline, PubMed, and the Cochrane Database of Systemic Reviews were queried for all articles reporting spinal B-cell lymphoma. Data on presenting symptoms, histological markers, treatment and survival outcomes were extracted. Bivariate and Multivariate Cox survival regression models and Kaplan-Meier curves were generated using R software survival package. In total, 57 studies were included with 72 patients diagnosed with spinal B-cell lymphoma. Mean age was 56.22 (IQR: 45.00-70.25) with 68% of patients being male and 4.2% of patients being immunocompromised. Back pain was the most common symptom (74%) with B symptoms and cauda equina symptoms present in only 6% and 29% respectively. Mean length of symptoms before presentation was 3.81 months (IQR: 0.45-3.25). The most common location was the thoracic spine (53%), with a majority of the lesions being hyperintense (28%) on T2 MRI. Surgical resection was performed in 83% of patients. Symptoms improved in 88% of patients after surgery and 80% of patients treated nonoperatively. OS at one- and five-years was 85% (95% CI: 0.749-0.953; n=72) and 66% (95% CI: 0.512-0.847; n=72), respectively. Age > 70 was associated with poorer OS in bivariate (HR 4.07 [95% CI: 1.328-12.46], p < 0.01; n=72) and multivariate analysis (HR 3.829 [95% CI: 1.158-12.662], p < 0.03; n=72). Primary spinal B-cell lymphoma can have a variety of presentations. Both surgery and nonoperative management may have similar improvement in symptoms. Age > 70 appears to confer poorer OS.

Abstract Glioblastoma (GBM) is an incurable brain cancer which is associated with severe peripheral immune suppression. Using experimental GBM, we recently determined that peripheral immunosuppression involves thymic atrophy, stunted T cell proliferation, and release of circulating factors that inhibit immune responses. RNA sequencing and proteomic studies have determined that transcripts and protein levels of Serpina3n are upregulated in the brain and serum of GBM patients and correlates with poor prognosis. We determined Serpina3n is a highly upregulated gene in the brain and the thymus of glioma-bearing mice using RNA sequencing technologies. Proteomic analysis of serum from glioma-bearing mice identified an upregulation of pathways associated with the extracellular expression of Serpina3n. We therefore sought to determine the role of Serpina3n in peripheral immunosuppression in GL261 glioma harboring wild type and Serpina3n knockout mice. Glioma implantation in Serpina3n knockout mice resulted in similar survival and peripheral immunosuppression compared to controls. Western blotting experiments confirmed that Serpina3n is expressed and secreted by GL261 gliomas isolated from WT and Serpina3n knockout mouse brains. Together this data suggests that tumor-derived, but not host derived, Serpina3n needs to be evaluated as a putative factor associated with peripheral immunosuppression.

Abstract Glioblastoma (GBM) is an incurable and aggressive form of brain cancer that is associated with severe peripheral immunosuppression. This immunosuppression is a critical barrier to patient survival and the success of immune modulatory therapies. Using the murine GL261 model of GBM, we recapitulated major features of peripheral immunosuppression observed in patients including T cell lymphopenia. We determined that peripheral immunosuppression in GBM is multifaceted and involves release of novel non-steroidal soluble factors with large molecular weight that are found in sera of glioma-bearing mice. These high molecular weight species potently inhibits T cell proliferation in vitro despite the presence of strong T cell stimulation. Our goal was to determine the identity of the immunosuppressive species in serum of glioma-bearing mice. We performed state-of-the-art comparative high throughput mass spectrometry on fractionated and multiplexed sera isolated from control and glioma-bearing mice. This proteomics analysis demonstrated histones as a top highly abundant protein in serum of glioma-bearing mice compared to naïve controls. Cell-free DNA has been recently identified as an immune suppressive factor in circulation and can be bound to histones. We, therefore, assessed cell-free DNA levels in the serum of glioma-bearing mice. We determined that sera isolated from glioma-bearing mice harbor significantly higher concentrations of double stranded and single stranded cell-free DNA compared to healthy controls. Reducing the DNA content in serum, using DNAse treatment, partially improved the defect in T cell proliferation observed when T cells are exposed to serum isolated from glioma-bearing mice. These data indicate that heighted levels of circulating DNA in serum contributes to peripheral immunosuppression in GBM. These findings provide a tractable approach to investigate the cellular source and immunosuppressive effects of cell-free DNA in murine models of GBM and to devise strategies to reverse immunosuppression with the hope of improving outcomes in patients.

AbstractBackgroundThe growing adoption of magnetic resonance imaging (MRI)‐guided radiation therapy (RT) platforms and a focus on MRI‐only RT workflows have brought the technical challenge of synthetic computed tomography (sCT) reconstruction to the forefront. Unpaired‐data deep learning‐based approaches to the problem offer the attractive characteristic of not requiring paired training data, but the gap between paired‐ and unpaired‐data results can be limiting.PurposeWe present two distinct approaches aimed at improving unpaired‐data sCT reconstruction results: a cascade ensemble that combines multiple models and a personalized training strategy originally designed for the paired‐data setting.MethodsComparisons are made between the following models: (1) the paired‐data fully convolutional DenseNet (FCDN), (2) the FCDN with the Intentional Deep Overfit Learning (IDOL) personalized training strategy, (3) the unpaired‐data CycleGAN, (4) the CycleGAN with the IDOL training strategy, and (5) the CycleGAN as an intermediate model in a cascade ensemble approach. Evaluation of the various models over 25 total patients is carried out using a five‐fold cross‐validation scheme, with the patient‐specific IDOL models being trained for the five patients of fold 3, chosen at random.ResultsIn both the paired‐ and unpaired‐data settings, adopting the IDOL training strategy led to improvements in the mean absolute error (MAE) between true CT images and sCT outputs within the body contour (mean improvement, paired‐ and unpaired‐data approaches, respectively: 38%, 9%) and in regions of bone (52%, 5%), the peak signal‐to‐noise ratio (PSNR; 15%, 7%), and the structural similarity index (SSIM; 6%, <1%). The ensemble approach offered additional benefits over the IDOL approach in all three metrics (mean improvement over unpaired‐data approach in fold 3; MAE: 20%; bone MAE: 16%; PSNR: 10%; SSIM: 2%), and differences in body MAE between the ensemble approach and the paired‐data approach are statistically insignificant.ConclusionsWe have demonstrated that both a cascade ensemble approach and a personalized training strategy designed initially for the paired‐data setting offer significant improvements in image quality metrics for the unpaired‐data sCT reconstruction task. Closing the gap between paired‐ and unpaired‐data approaches is a step toward fully enabling these powerful and attractive unpaired‐data frameworks.