Familial gastrointestinal stromal tumor syndrome: phenotypic and molecular features in a kindred.

PURPOSE: Members of a family with hereditary gastrointestinal stromal tumors (GISTs) and a germline KIT oncogene mutation were evaluated for other potential syndrome manifestations. A tumor from the proband was analyzed to compare features with sporadic GISTs. PATIENTS AND METHODS: Members of a kindred in which six relatives in four consecutive generations comprised an autosomal dominant pattern of documented GISTs and cutaneous lesions underwent physical examination, imaging studies, and germline KIT analysis. A recurrent GIST from the proband was studied using microarray, karyotypic, immunohistochemical, and immunoblotting techniques. RESULTS: In addition to evidence of multiple GISTs, lentigines, malignant melanoma, and an angioleiomyoma were identified in relatives. A previously reported gain-of-function missense mutation in KIT exon 11 (T --> C) that results in a V559A substitution within the juxtamembrane domain was identified in three family members. The proband's recurrent gastric GIST had a 44,XY-14,-22 karyotype and immunohistochemical evidence of strong diffuse cytoplasmic KIT expression without expression of actin, desmin, or S-100. Immunoblotting showed strong expression of phosphorylated KIT and downstream signaling intermediates (AKT and MAPK) at levels comparable with those reported in sporadic GISTs. cDNA array profiling demonstrated clustering with sporadic GISTs, and expression of GIST markers comparable to sporadic GISTs. CONCLUSION: These studies provide the first evidence that gene expression and mechanisms of cytogenetic progression and cell signaling are indistinguishable in familial and sporadic GISTs. Current investigations of molecularly targeted therapies in GIST patients provide opportunities to increase the understanding of features of the hereditary syndrome, and risk factors and molecular pathways of the neoplastic phenotypes.     

MYC amplification and polysomy 8 in chondrosarcoma: array comparative genomic hybridization, fluorescent in situ hybridization, and association with outcome.

PURPOSE: To identify recurrent regions of genomic gain or loss in chondrosarcoma in a clinically relevant and statistically valid fashion. Materials and METHODS: Array comparative genomic hybridization (CGH) results of 15 frozen tumor samples of high-grade chondrosarcoma for chromosome 8 are presented. A separate subset of 116 cartilaginous tumors with outcome data was used for validation. RESULTS: Array CGH identified gain at 8q24.12-q24.13, the region of the MYC (c-Myc) oncogene, as a frequent change in high-grade chondrosarcoma. In the validation arm of 116 cartilaginous tumors, MYC was frequently amplified in G2 (15%), G3 (20%), and dedifferentiated (21%) chondrosarcomas. No amplification was identified in samples of enchondroma and grade 1 chondrosarcoma. In samples without MYC amplification, polysomy 8 was a frequent finding in grade 1 (18%), grade 2 (31%), grade 3 (80%), and dedifferentiated (29%) chondrosarcomas, but was not found in any samples of enchondroma. MYC protein expression was identified in all samples with amplification, but was also frequent in the remaining samples without amplification or polysomy 8. Kaplan-Meier survival curves for overall survival showed a statistically significant difference for patients with MYC amplification or polysomy 8 (P = .034). Univariate analysis involving Cox proportional hazards models showed that grade (P = .003), polysomy 8 (P = .045), and MYC amplification (P = .053) correlated with shorter overall survival. By multivariate analysis, grade of chondrosarcoma (P = .026) was the only factor to reach statistical significance. CONCLUSION: MYC amplification and polysomy 8 can be used as markers of prognostic importance in chondrosarcoma. Molecular targeting of MYC expression may have therapeutic potential in the future for subsets of chondrosarcoma.     

Differences in FMO2*1 allelic frequency between Hispanics of Puerto Rican and Mexican descent.

A polymorphism for the phase I drug-metabolizing enzyme, flavin-containing monooxygenase isoform 2 (FMO2), encoding either truncated inactive protein, FMO2X472 (FMO2.2A), or full-length active enzyme, FMO2Q472 (FMO2.1), is known and exhibits significant interethnic differences in allelic frequency. FMO2 is the major or sole FMO isoform expressed in the lung of most mammals, including nonhuman primates. To date, FMO2.1 has been found only in African-American and Hispanic populations, rendering individuals with this allele subject to drug metabolism that is potentially different from that of the general population. Approximately 26% of African-Americans (n = 180) possess the FMO2*1 allele. In preliminary studies, we initially estimated that 5% of Hispanics (n = 40) have the FMO2*1 allele, but access to large cohorts of individuals of defined national origin has allowed us to determine the occurrence among Mexican-American and Puerto Rican-American groups. We used allele-specific genotyping to detect FMO2*1 from 632 Hispanic individuals, including 280 individuals of Mexican origin and 327 individuals of Puerto Rican origin. Statistical analysis indicated that results from Mexican (five sample sources) and Puerto Rican (three sample sources) samples were consistent with the hypothesis of homogeneity within each group from different sources. Data were subsequently pooled across sources to test for evidence of a difference in occurrence of FMO2*1 between ethnic groups. There was strong evidence (p = 0.0066) that FMO2*1 is more common among Puerto Ricans (7%) than among individuals of Mexican descent (2%). The overall occurrence of FMO2*1 among Hispanics of all origins is estimated to be between 2 and 7%.     

Evidence of depot‐specific regulation of all‐trans‐retinoic acid biosynthesis in human adipose tissue

The prevalence of obesity continues to rise, underscoring the need to better understand the pathways mediating adipose tissue (AT) expansion. All‐trans‐retinoic acid (atRA), a bioactive vitamin A metabolite, regulates adipogenesis and energy metabolism, and, in rodent studies, aberrant vitamin A metabolism appears a key facet of metabolic dysregulation. The relevance of these findings to human disease is unknown, as are the specific enzymes implicated in vitamin A metabolism within human AT. We hypothesized that in human AT, family 1A aldehyde dehydrogenase (ALDH1A) enzymes contribute to atRA biosynthesis in a depot‐specific manner. To test this hypothesis, parallel samples of subcutaneous and omental AT from participants (n = 15) were collected during elective abdominal surgeries to quantify atRA biosynthesis and key atRA synthesizing enzymes. ALDH1A1 was the most abundant ALDH1A isoform in both AT depots with expression approximately twofold higher in omental than subcutaneous AT. ALDH1A2 was detected only in omental AT. Formation velocity of atRA was approximately threefold higher (p = 0.0001) in omental AT (9.8 [7.6, 11.2]) pmol/min/mg) than subcutaneous AT (3.2 [2.1, 4.0] pmol/min/mg) and correlated with ALDH1A2 expression in omental AT (β‐coefficient = 3.07, p = 0.0007) and with ALDH1A1 expression in subcutaneous AT (β‐coefficient = 0.13, p = 0.003). Despite a positive correlation between body mass index (BMI) and omental ALDH1A1 protein expression (Spearman r = 0.65, p = 0.01), BMI did not correlate with atRA formation. Our findings suggest that ALDH1A2 is the primary mediator of atRA formation in omental AT, whereas ALDH1A1 is the principal atRA‐synthesizing enzyme in subcutaneous AT. These data highlight AT depot as a critical variable for defining the roles of retinoids in human AT biology.

Study Highlights

• WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC?

Rodent data suggest that dysregulated production of all‐trans‐retinoic acid (atRA), the primary bioactive metabolite of vitamin A, may contribute to body weight gain and its complications. However, the key enzymes responsible for atRA biosynthesis in human adipose tissue have not been identified, nor has the relationship between body weight and adipose tissue atRA biosynthesis been evaluated in humans.

• WHAT QUESTION DID THIS STUDY ADDRESS?

This study sought to identify the key enzymes involved in atRA biosynthesis in human omental and subcutaneous adipose tissue. This study also quantified atRA formation velocity and explored the potential relationship between body mass index (BMI) and atRA biosynthesis in both adipose tissue depots.

• WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE?

This study establishes that among the aldehyde dehydrogenase (ALDH) isoforms, ALDH1A1 and ALDH1A2 both contribute to atRA biosynthesis in human omental adipose tissue, whereas only ALDH1A1 contributes to atRA biosynthesis in subcutaneous adipose tissue. Both ALDH1A1 expression and atRA formation velocity are substantially higher in omental than subcutaneous adipose tissue. Omental ALDH1A1 protein expression exhibits a positive correlation with BMI, but atRA formation velocity in both omental and subcutaneous adipose tissue shows no correlation with BMI. Thus, these findings highlight discrepancies between human and rodent adipose tissue biology and, moreover, reveal depot‐specific regulation of vitamin A metabolism in human adipose tissue.

• HOW MIGHT THIS CHANGE CLINICAL PHARMACOLOGY OR TRANSLATIONAL SCIENCE?

This line of research ultimately is intended to define the roles of vitamin A metabolites in the regulation of tissue remodeling and energy partitioning in human adipose tissue. This knowledge could contribute to the delineation of mechanisms underlying progressive obesity and its complications.     

Detection of various freshwater cyanobacterial toxins using ultra-performance liquid chromatography tandem mass spectrometry

Several freshwater cyanobacteria species have the capability to produce toxic compounds, frequently referred to as cyanotoxins. The most prevalent of these cyanotoxins is microcystin LR. Recognizing the potential health risk, France, Italy, Poland, Australia, Canada, and Brazil have set either standards or guidelines for the amount of microcystin LR permissible in drinking water based on the World Health Organization guideline of one μg/L of microcystin LR. Recently, the United States Environmental Protection Agency has begun to evaluate the occurrence and health effects of cyanotoxins and their susceptibility to water treatment under the Safe Drinking Water Act through the Contaminant Candidate List (CCL). A recent update of the Contaminant Candidate List focuses research and data collection on the cyanotoxins microcystin LR, anatoxin-a, and cylindrospermopsin.Liquid Chromatography/Tandem-Mass Spectrometry (LC/MS/MS) is a powerful tool for the analysis of various analytes in a wide variety of matrices because of its sensitivity and selectivity. The use of smaller column media (sub 2 μm particles) was investigated to both improve the speed, sensitivity and resolution, and to quantify the CCL cyanotoxins, in a single analysis, using Ultra-Performance Liquid Chromatography (UPLC^®) combined with tandem mass spectrometry. Natural waters and spiked samples were analyzed to show proof-of-performance. The presented method was able to clearly resolve each of the cyanotoxins in less than eight minutes with specificity and high spike recoveries.     

Integrated decision strategies for skin sensitization hazard

One of the top priorities of the Interagency Coordinating Committee for the Validation of Alternative Methods (ICCVAM) is the identification and evaluation of non‐animal alternatives for skin sensitization testing. Although skin sensitization is a complex process, the key biological events of the process have been well characterized in an adverse outcome pathway (AOP) proposed by the Organisation for Economic Co‐operation and Development (OECD). Accordingly, ICCVAM is working to develop integrated decision strategies based on the AOP using in vitro, in chemico and in silico information. Data were compiled for 120 substances tested in the murine local lymph node assay (LLNA), direct peptide reactivity assay (DPRA), human cell line activation test (h‐CLAT) and KeratinoSens assay. Data for six physicochemical properties, which may affect skin penetration, were also collected, and skin sensitization read‐across predictions were performed using OECD QSAR Toolbox. All data were combined into a variety of potential integrated decision strategies to predict LLNA outcomes using a training set of 94 substances and an external test set of 26 substances. Fifty‐four models were built using multiple combinations of machine learning approaches and predictor variables. The seven models with the highest accuracy (89–96% for the test set and 96–99% for the training set) for predicting LLNA outcomes used a support vector machine (SVM) approach with different combinations of predictor variables. The performance statistics of the SVM models were higher than any of the non‐animal tests alone and higher than simple test battery approaches using these methods. These data suggest that computational approaches are promising tools to effectively integrate data sources to identify potential skin sensitizers without animal testing. Published 2016. This article has been contributed to by US Government employees and their work is in the public domain in the USA.     

Evaluation of federated learning variations for COVID-19 diagnosis using chest radiographs from 42 US and European hospitals

ObjectiveFederated learning (FL) allows multiple distributed data holders to collaboratively learn a shared model without data sharing. However, individual health system data are heterogeneous. “Personalized” FL variations have been developed to counter data heterogeneity, but few have been evaluated using real-world healthcare data. The purpose of this study is to investigate the performance of a single-site versus a 3-client federated model using a previously described Coronavirus Disease 19 (COVID-19) diagnostic model. Additionally, to investigate the effect of system heterogeneity, we evaluate the performance of 4 FL variations.Materials and methodsWe leverage a FL healthcare collaborative including data from 5 international healthcare systems (US and Europe) encompassing 42 hospitals. We implemented a COVID-19 computer vision diagnosis system using the Federated Averaging (FedAvg) algorithm implemented on Clara Train SDK 4.0. To study the effect of data heterogeneity, training data was pooled from 3 systems locally and federation was simulated. We compared a centralized/pooled model, versus FedAvg, and 3 personalized FL variations (FedProx, FedBN, and FedAMP).ResultsWe observed comparable model performance with respect to internal validation (local model: AUROC 0.94 vs FedAvg: 0.95, P = .5) and improved model generalizability with the FedAvg model (P < .05). When investigating the effects of model heterogeneity, we observed poor performance with FedAvg on internal validation as compared to personalized FL algorithms. FedAvg did have improved generalizability compared to personalized FL algorithms. On average, FedBN had the best rank performance on internal and external validation.ConclusionFedAvg can significantly improve the generalization of the model compared to other personalization FL algorithms; however, at the cost of poor internal validity. Personalized FL may offer an opportunity to develop both internal and externally validated algorithms.