Genomic and phenotypic characterization of a broad panel of patient-derived xenografts reflects the diversity of glioblastoma

Purpose: Glioblastoma is the most frequent and lethal primary brain tumor. Development of novel therapies relies on the availability of relevant preclinical models. We have established a panel of 96 glioblastoma patient-derived xenografts (PDX) and undertaken its genomic and phenotypic characterization. Experimental Design: PDXs were established from glioblastoma, IDH-wildtype (n \ubc 93), glioblastoma, IDH-mutant (n \ubc 2), diffuse midline glioma, H3 K27M-mutant (n \ubc 1), and both primary (n \ubc 60) and recurrent (n \ubc 34) tumors. Tumor growth rates, histopathology, and treatment response were characterized. Integrated molecular profiling was performed by whole-exome sequencing (WES, n \ubc 83), RNA-sequencing (n \ubc 68), and genome-wide methylation profiling (n \ubc 76). WES data from 24 patient tumors was compared with derivative models. Results: PDXs recapitulate many key phenotypic and molecular features of patient tumors. Orthotopic PDXs show characteristic tumor morphology and invasion patterns, but largely lack microvascular proliferation and necrosis. PDXs capture common and rare molecular drivers, including alterations of TERT, EGFR, PTEN, TP53, BRAF, and IDH1, most at frequencies comparable with human glioblastoma. However, PDGFRA amplification was absent. RNA-sequencing and genome-wide methylation profiling demonstrated broad representation of glioblastoma molecular subtypes. MGMT promoter methylation correlated with increased survival in response to temozolomide. WES of 24 matched patient tumors showed preservation of most genetic driver alterations, including EGFR amplification. However, in four patient-PDX pairs, driver alterations were gained or lost on engraftment, consistent with clonal selection. Conclusions: Our PDX panel captures the molecular heterogeneity of glioblastoma and recapitulates many salient genetic and phenotypic features. All models and genomic data are openly available to investigators

Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge

Contains fulltext : 179531.pdf (Publisher’s version ) (Closed access)Automatic detection of pulmonary nodules in thoracic computed tomography (CT) scans has been an active area of research for the last two decades. However, there have only been few studies that provide a comparative performance evaluation of different systems on a common database. We have therefore set up the LUNA16 challenge, an objective evaluation framework for automatic nodule detection algorithms using the largest publicly available reference database of chest CT scans, the LIDC-IDRI data set. In LUNA16, participants develop their algorithm and upload their predictions on 888 CT scans in one of the two tracks: 1) the complete nodule detection track where a complete CAD system should be developed, or 2) the false positive reduction track where a provided set of nodule candidates should be classified. This paper describes the setup of LUNA16 and presents the results of the challenge so far. Moreover, the impact of combining individual systems on the detection performance was also investigated. It was observed that the leading solutions employed convolutional networks and used the provided set of nodule candidates. The combination of these solutions achieved an excellent sensitivity of over 95% at fewer than 1.0 false positives per scan. This highlights the potential of combining algorithms to improve the detection performance. Our observer study with four expert readers has shown that the best system detects nodules that were missed by expert readers who originally annotated the LIDC-IDRI data. We released this set of additional nodules for further development of CAD systems.13 p

Specification of Actin Filament Function and Molecular Composition by Tropomyosin Isoforms

The specific functions of greater than 40 vertebrate nonmuscle tropomyosins (Tms) are poorly understood. In this article we have tested the ability of two Tm isoforms, TmBr3 and the human homologue of Tm5 (hTM5(NM1)), to regulate actin filament function. We found that these Tms can differentially alter actin filament organization, cell size, and shape. hTm5(NM1) was able to recruit myosin II into stress fibers, which resulted in decreased lamellipodia and cellular migration. In contrast, TmBr3 transfection induced lamellipodial formation, increased cellular migration, and reduced stress fibers. Based on coimmunoprecipitation and colocalization studies, TmBr3 appeared to be associated with actin-depolymerizing factor/cofilin (ADF)-bound actin filaments. Additionally, the Tms can specifically regulate the incorporation of other Tms into actin filaments, suggesting that selective dimerization may also be involved in the control of actin filament organization. We conclude that Tm isoforms can be used to specify the functional properties and molecular composition of actin filaments and that spatial segregation of isoforms may lead to localized specialization of actin filament function