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Gnathic fibro-osseous lesions are a diverse group of disease processes which share overlapping microscopic features characterized by fibroblastic stroma with variable cellularity and a range of bone forming pathological processes leading to woven, sclerotic and cementum-like structures. Some of the lesions are unique to craniofacial location and a combination of clinical, radiological and pathological correlation is often necessary for diagnostic accuracy. Gnathic osteosarcomas are rare tumors with differences in age distribution and behavior as compared to osteosarcoma of long bones. This review will discuss the clinicopathological and radiological features of gnathic fibro-osseous lesions and osteosarcoma with updates on current genetics and molecular pathogenesis.

PurposeEwing sarcoma (ES) is a primitive sarcoma defined by EWSR1-ETS fusions as the primary driver alteration. To better define the landscape of cooperating secondary genetic alterations in ES, we analyzed clinical genomic profiling data of 113 patients with ES, a cohort including more adult patients (> 18 years) and more patients with advanced stage at presentation than previous genomic cohorts.MethodsThe data set consisted of patients with ES prospectively tested with the US Food and Drug Administration-cleared Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets large panel, hybrid capture-based next-generation sequencing assay. To assess the functional significance of ERF loss, we generated ES cell lines with increased expression of ERF and lines with knockdown of ERF. We assessed cell viability, clonogenic growth, and motility in these ES lines and performed transcriptomic and epigenetic analyses. Finally, we validated our findings in vivo using cell line xenografts.ResultsNovel subsets were defined by recurrent secondary alterations in ERF, which encodes an ETS domain transcriptional repressor, in 7% of patients (five truncating mutations, one deep deletion, and two missense mutations) and in FGFR1 in another 2.7% (one amplification and two known activating mutations). ERF alterations were nonoverlapping with STAG2 alterations. In vitro, increased expression of ERF decreased tumor cell growth, colony formation, and motility in two ES cell lines, whereas ERF loss induced cellular proliferation and clonogenic growth. Transcriptomic analysis of cell lines with ERF loss revealed an increased expression of genes and pathways associated with aggressive tumor biology, and epigenetic, chromatin-based studies revealed that ERF competes with EWSR1-FLI1 at ETS-binding sites.ConclusionOur findings open avenues to new insights into ES pathobiology and to novel therapeutic approaches in a subset of patients with ES.

Context.—The diagnosis and clinical management of patients with diffuse gliomas (DGs) have evolved rapidly over the past decade with the emergence of molecular biomarkers that are used to classify, stratify risk, and predict treatment response for optimal clinical care.Objective.—To develop evidence-based recommendations for informing molecular biomarker testing for pediatric and adult patients with DGs and provide guidance for appropriate laboratory test and biomarker selection for optimal diagnosis, risk stratification, and prediction.Design.—The College of American Pathologists convened an expert panel to perform a systematic review of the literature and develop recommendations. A systematic review of literature was conducted to address the overarching question, "What ancillary tests are needed to classify DGs and sufficiently inform the clinical management of patients?" Recommendations were derived from quality of evidence, open comment feedback, and expert panel consensus.Results.—Thirteen recommendations and 3 good practice statements were established to guide pathologists and treating physicians on the most appropriate methods and molecular biomarkers to include in laboratory testing to inform clinical management of patients with DGs.Conclusions.—Evidence-based incorporation of laboratory results from molecular biomarker testing into integrated diagnoses of DGs provides reproducible and clinically meaningful information for patient management.

Context.—The diagnosis and clinical management of patients with diffuse gliomas (DGs) have evolved rapidly over the past decade with the emergence of molecular biomarkers that are used to classify, stratify risk, and predict treatment response for optimal clinical care. Objective.—To develop evidence-based recommendations for informing molecular biomarker testing for pediatric and adult patients with DGs and provide guidance for appropriate laboratory test and biomarker selection for optimal diagnosis, risk stratification, and prediction. Design.—The College of American Pathologists convened an expert panel to perform a systematic review of the literature and develop recommendations. A systematic review of literature was conducted to address the overarching question, ‘‘What ancillary tests are needed to classify DGs and sufficiently inform the clinical management of patients?’’ Recommendations were derived from quality of evidence, open comment feedback, and expert panel consensus. Results.—Thirteen recommendations and 3 good practice statements were established to guide pathologists and treating physicians on the most appropriate methods and molecular biomarkers to include in laboratory testing to inform clinical management of patients with DGs. Conclusions.—Evidence-based incorporation of laboratory results from molecular biomarker testing into integrated diagnoses of DGs provides reproducible and clinically meaningful information for patient management.

Osteosarcoma is the most common primary bone cancer whose standard treatment includes pre-operative chemotherapy followed by resection. Chemotherapy response is used for predicting prognosis and further management of patients. Necrosis is routinely assessed post-chemotherapy from histology slides on resection specimens where necrosis ratio is defined as the ratio of necrotic tumor to overall tumor. Patients with necrosis ratio >=90% are known to have better outcome. Manual microscopic review of necrosis ratio from multiple glass slides is semi-quantitative and can have intra- and inter-observer variability. We propose an objective and reproducible deep learning-based approach to estimate necrosis ratio with outcome prediction from scanned hematoxylin and eosin whole slide images. We collected 103 osteosarcoma cases with 3134 WSIs to train our deep learning model, to validate necrosis ratio assessment, and to evaluate outcome prediction. We trained Deep Multi-Magnification Network to segment multiple tissue subtypes including viable tumor and necrotic tumor in pixel-level and to calculate case-level necrosis ratio from multiple WSIs. We showed necrosis ratio estimated by our segmentation model highly correlates with necrosis ratio from pathology reports manually assessed by experts where mean absolute differences for Grades IV (100%), III (>=90%), and II (>=50% and <90%) necrosis response are 4.4%, 4.5%, and 17.8%, respectively. We successfully stratified patients to predict overall survival with p=10^-6 and progression-free survival with p=0.012. Our reproducible approach without variability enabled us to tune cutoff thresholds, specifically for our model and our data set, to 80% for OS and 60% for PFS. Our study indicates deep learning can support pathologists as an objective tool to analyze osteosarcoma from histology for assessing treatment response and predicting patient outcome.

Osteosarcoma is the most common malignant primary bone tumor. Standard treatment includes pre-operative chemotherapy followed by surgical resection. The response to treatment as measured by ratio of necrotic tumor area to overall tumor area is a known prognostic factor for overall survival. This assessment is currently done manually by pathologists by looking at glass slides under the microscope which may not be reproducible due to its subjective nature. Convolutional neural networks (CNNs) can be used for automated segmentation of viable and necrotic tumor on osteosarcoma whole slide images. One bottleneck for supervised learning is that large amounts of accurate annotations are required for training which is a time-consuming and expensive process. In this paper, we describe Deep Interactive Learning (DIaL) as an efficient labeling approach for training CNNs. After an initial labeling step is done, annotators only need to correct mislabeled regions from previous segmentation predictions to improve the CNN model until the satisfactory predictions are achieved. Our experiments show that our CNN model trained by only 7 hours of annotation using DIaL can successfully estimate ratios of necrosis within expected inter-observer variation rate for non-standardized manual surgical pathology task., Comment: Accepted at MICCAI 2020

Background: The establishment of whole-slide imaging (WSI) as a medical diagnostic device allows that pathologists may evaluate mitotic activity with this new technology. Furthermore, the image digitalization provides an opportunity to develop algorithms for automatic quantifications, ideally leading to improved reproducibility as compared to the naked eye examination by pathologists. In order to implement them effectively, accuracy of mitotic figure detection using WSI should be investigated. In this study, we aimed to measure pathologist performance in detecting mitotic figures (MFs) using multiple platforms (multiple scanners) and compare the results with those obtained using a brightfield microscope. Methods: Four slides of canine oral melanoma were prepared and digitized using 4 WSI scanners. In these slides, 40 regions of interest (ROIs) were demarcated, and five observers identified the MFs using different viewing modes: microscopy and WSI. We evaluated the inter- and intra-observer agreements between modes with Cohen’s Kappa and determined “true” MFs with a consensus panel. We then assessed the accuracy (agreement with truth) using the average of sensitivity and specificity. Results: In the 40 ROIs, 155 candidate MFs were detected by five pathologists; 74 of them were determined to be true MFs. Inter- and intra-observer agreement was mostly “substantial” or greater (Kappa?=?0.594?0.939). Accuracy was between 0.632 and 0.843 across all readers and modes. After averaging over readers for each modality, we found that mitosis detection accuracy for 3 of the 4 WSI scanners was significantly less than that of the microscope (p =?0.002, 0.012, and 0.001). Conclusions: This study is the first to compare WSIs and microscopy in detecting MFs at the level of individual cells. Our results suggest that WSI can be used for mitotic cell detection and offers similar reproducibility to the microscope, with slightly less accuracy., Diagnostic Pathology, 14(1), art.no.65; 2019

BackgroundChromosomal instability is associated with earlier progression in isocitrate dehydrogenase (IDH)-mutated astrocytomas. Here we evaluated the prognostic significance of polysomy in gliomas tested for 1p/19q status.MethodsWe analyzed 412 histologic oligodendroglial tumors with use of 1p/19q testing at 8 institutions from 1996 to 2013; fluorescence in situ hybridization (FISH) for 1p/19q was performed. Polysomy was defined as more than two 1q and 19p signals in cells. Tumors were divided into groups on the basis of their 1p/19q status and polysomy and were compared for progression-free survival (PFS) and overall survival (OS).ResultsIn our cohort, 333 tumors (81%) had 1p/19q loss; of these, 195 (59%) had concurrent polysomy and 138 (41%) lacked polysomy, 79 (19%) had 1p/19q maintenance; of these, 30 (38%) had concurrent polysomy and 49 (62%) lacked polysomy. In agreement with prior studies, the group with 1p/19q loss had significantly better PFS and OS than did the group with 1p/19q maintenance (P < 0.0001 each). Patients with 1p/19q loss and polysomy showed significantly shorter PFS survival than patients with 1p/19q codeletion only (P < 0.0001), but longer PFS and OS than patients with 1p/19q maintenance (P < 0.01 and P < 0.0001). There was no difference in survival between tumors with >30% polysomic cells and those with <30% polysomic cells. Polysomy had no prognostic significance on PFS or OS in patients with 1p/19q maintenance.ConclusionsThe presence of polysomy in oligodendroglial tumors with codeletion of 1p/19q predicts early recurrence and short survival in patients with 1p/19q codeleted tumors.