Headaches and hemiparesis in an immunocompetent inmate

This is a case of a 22 year-old African American male inmate with no significant past medical history who regularly cleaned moldy bathrooms and showers during his incarceration. The patient presented with progressive development of left-sided weakness, dizziness, headaches, and vomiting over a two month period. In summary, we report this case to boost awareness of the potential for CNS phaeohyphomycosis infection to present as a clinical and radioimaging mimic of high grade glioma. Our patient, a previously healthy adult, is one of less than a dozen cases of cerebral phaeohyphomycosis due to Bipolaris documented in the literature, and is only the second patient to present with imaging features very suggestive of high grade infiltrative glioma

Future paradigms for precision oncology

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Cauda Canis: Variation of a Tinel’s Sign for a Sciatic Nerve Tumor

A patient with a prior history of intradural schwannoma and disc herniation presented with radicular pain after being hit in the thigh by a dog’s tail. She was worked up and found to have a tumor of her right sciatic nerve. The tumor was resected and histology was consistent with schwannoma. The dog’s tail acted as a Tinel’s sign maneuver and led to timely identification of her peripheral nerve tumor. Peripheral nerve schwannomas can present in unusual forms, and Tinel’s maneuver may be a useful tool in diagnosis

Spatial Transcriptomic Analysis of Focal and Normal Areas of Myocyte Disarray in Human Hypertrophic Cardiomyopathy

Hypertrophic Cardiomyopathy (HCM) is a common inherited disorder that can lead to heart failure and sudden cardiac death, characterized at the histological level by focal areas of myocyte disarray, hypertrophy and fibrosis, and only a few disease-targeted therapies exist. To identify the focal and spatially restricted alterations in the transcriptional pathways and reveal novel therapeutic targets, we performed a spatial transcriptomic analysis of the areas of focal myocyte disarray compared to areas of normal tissue using a commercially available platform (GeoMx, nanoString). We analyzed surgical myectomy tissue from four patients with HCM and the control interventricular septum tissue from two unused organ donor hearts that were free of cardiovascular disease. Histological sections were reviewed by an expert pathologist, and 72 focal areas with varying degrees of myocyte disarray (normal, mild, moderate, severe) were chosen for analysis. Areas of interest were interrogated with the Human Cancer Transcriptome Atlas designed to profile 1800 transcripts. Differential expression analysis revealed significant changes in gene expression between HCM and the control tissue, and functional enrichment analysis indicated that these genes were primarily involved in interferon production and mitochondrial energetics. Within the HCM tissue, differentially expressed genes between areas of normal and severe disarray were enriched for genes related to mitochondrial energetics and the extracellular matrix in severe disarray. An analysis of the gene expression of the ligand–receptor pair revealed that the HCM tissue exhibited downregulation of platelet-derived growth factor (PDGF), NOTCH, junctional adhesion molecule, and CD46 signaling while showing upregulation of fibronectin, CD99, cadherin, and amyloid precursor protein signaling. A deconvolution analysis utilizing the matched single nuclei RNA-sequencing (snRNA-seq) data to determine cell type composition in areas of interest revealed significant differences in fibroblast and vascular cell composition in areas of severe disarray when compared to normal areas in HCM samples. Cell composition in the normal areas of the control tissue was also divergent from the normal areas in HCM samples, which was consistent with the differential expression results. Overall, our data identify novel and potential disease-modifying targets for therapy in HCM

Spinal Intradural, Extramedullary Ependymoma with Astrocytoma Component: A Case Report and Review of the Literature

Ependymomas are common spinal lesions, with the vast majority arising in an intramedullary location. Several cases have been described in the literature of ependymomas in an intradural, extramedullary location. The authors present a case of a 56-year-old female who presented with several weeks of lower back pain and weakness. MRI revealed an intradural, extramedullary enhancing mass at L1-L2. The mass was successfully resected surgically. Pathologic evaluation revealed a low grade glioma with components of both ependymoma and pilocytic astrocytoma with MUTYH G382D mutation. Extramedullary ependymomas are very rare tumors. To the authors’ knowledge, this is the first case of ependymoma/astrocytoma collision tumors described in an extramedullary location

Improved outcome in HLA-identical sibling hematopoietic stem-cell transplantation for acute myelogenous leukemia predicted by KIR and HLA genotypes

Inhibitory killer immunoglobulin (Ig)-like receptors (KIRs) recognize HLA-C and -B epitopes on target cells, thereby regulating natural killer (NK) cell activity. In 178 patients receiving T-cell-depleted HLA-identical sibling transplants for acute myelogenous leukemia (AML), chronic myelogenous leukemia (CML), acute lymphoblastic leukemia (ALL), or myelodysplastic syndrome (MDS), analysis of donor KIR genotype with HLA genotype demonstrated that 62.9% of the patients lacked an HLA ligand for donor-inhibitory KIR. Lack of HLA ligand for donor-inhibitory KIR (missing KIR ligand) had no effect on disease-free survival (DFS), overall survival (OS), or relapse in patients receiving transplants for CML and ALL. In patients with AML and MDS, however, there was a significant missing KIR ligand effect on DFS (P = .014; hazard ratio [HR], 0.53; 95% confidence interval [95% CI], 0.28-0.88) and OS (P = .03; HR, 0.53; 95% CI, 0.3-0.93). Incidence of relapse was also lower in patients with AML and MDS who lacked the HLA ligand for donor-inhibitory KIR (P = .04; HR, 0.41; 95% CI, 0.18-0.97). AML and MDS patients lacking 2 HLA ligands for donor-inhibitory KIR had the highest DFS (P = .002) and OS (P = .003). There was no significant contribution of donor-activating KIR to transplantation outcome in these patients. These data indicate that the absence of class I ligand in the recipient for donor-inhibitory KIR can be a prognostic factor for transplantation outcome in HLA-identical sibling transplantation and that the lack of HLA-C or -B ligands for donor-inhibitory KIR can contribute to improved outcomes for patients with AML and MDS. (Blood. 2005;105:4878-4884

Machine Learning Quantification of Amyloid Deposits in Histological Images of Ligamentum Flavum

Wild-type transthyretin amyloidosis (ATTRwt) is an underdiagnosed and potentially fatal disease. Interestingly, ATTRwt deposits have been found to deposit in the ligamentum flavum (LF) of patients with lumbar spinal stenosis before the development of systemic and cardiac amyloidosis. In order to study this phenomenon and its possible relationship with LF thickening and systemic amyloidosis, a precise method of quantifying amyloid deposits in histological slides of LF is critical. However, such a method is currently unavailable. Here, we present a machine learning quantification method with Trainable Weka Segmentation (TWS) to assess amyloid deposition in histological slides of LF. Images of ligamentum flavum specimens stained with Congo red are obtained from spinal stenosis patients undergoing laminectomies and confirmed to be positive for ATTRwt. Amyloid deposits in these specimens are classified and quantified by TWS through training the algorithm via user-directed annotations on images of LF. TWS can also be automated through exposure to a set of training images with user-directed annotations, and then applied] to a set of new images without additional annotations. Additional methods of color thresholding and manual segmentation are also used on these images for comparison to TWS. We develop the use of TWS in images of LF and demonstrate its potential for automated quantification. TWS is strongly correlated with manual segmentation in the training set of images with user-directed annotations (R = 0.98; p = 0.0033) as well as in the application set of images where TWS was automated (R = 0.94; p = 0.016). Color thresholding was weakly correlated with manual segmentation in the training set of images (R = 0.78; p = 0.12) and in the application set of images (R = 0.65; p = 0.23). TWS machine learning closely correlates with the gold-standard comparator of manual segmentation and outperforms the color thresholding method. This novel machine learning method to quantify amyloid deposition in histological slides of ligamentum flavum is a precise, objective, accessible, high throughput, and powerful tool that will hopefully pave the way towards future research and clinical applications