Project description:Background:To evaluate the association of multiparametric and multiregional MRI-features with key molecular characteristics in patients with newly-diagnosed glioblastoma. Methods:Retrospective data evaluation was approved by the local ethics committee of the University of Heidelberg (ethics approval number: S-320/2012) and informed consent was waived. Preoperative MRI-features were correlated with key molecular characteristics within a single-institutional cohort of 152 patients with newly-diagnosed glioblastoma. Preoperative MRI-features (n=31) included multiparametric (anatomical, diffusion-, perfusion-, and susceptibility-weighted images) and multiregional (contrast enhancing and non-enhancing FLAIR-hyperintense) information with (histogram) quantification of tumor volumes, volume ratios, apparent diffusion coefficients, cerebral blood flow / volume (CBF / CBV) and intratumoral susceptibility signals. Molecular characteristics determined with the Illumina Infinium HumanMethylation450 array included global DNA-methylation subgroups (e.g. mesenchymal (MES), RTK I “PGFRA”, RTK II “classic”), MGMT-promoter methylation status and hallmark copy-number-variations (EGFR-, PDGFRA-, MDM4- and CDK4-amplification; PTEN-, CDKN2A-, NF1- and RB1-loss). Univariate analyses (voxel-lesion-symptom-mapping for tumor location, Wilcoxon-test for all other MRI-features) as well as machine-learning models were applied to study the strength of association and discriminative value of MRI-features for predicting underlying molecular characteristics. Results: There was no tumor location predilection for any of the assessed molecular parameters (permutation-adjusted p>0.05 each). Univariate imaging parameter associations were noted for EGFR amplification and CDKN2A loss, both demonstrating increased nrCBV and nrCBF values (performance of these parameters, as assessed by the area under the ROC curve ranged from 63 to 69%, FDR-adjusted p<0.05, respectively). Subjecting all MRI-features to machine-learning-based classification allowed to predict EGFR amplification status and the RTK II “classic” GB subgroup with a moderate, yet significantly greater accuracy (63% for EGFR [p<0.01] and 61% for RTK II [p=0.01]) than the prediction by chance, whereas prediction accuracy for all other molecular parameters was non-significant (p>0.05, all models). Conclusions: In summary, we found univariate associations between established MRI-features and molecular characteristics, however not of sufficient strength to allow the generation of machine-learning classification models for reliable and clinically meaningful prediction of the assessed molecular characteristics in patients with newly-diagnosed glioblastoma.

Project description:Purpose: Authentic preclinical models of renal cell carcinoma (RCC) are lacking. We aimed to establish and characterize primary RCC cultures and demonstrate the feasibility of evaluating drug responses in vitro and in vivo. Materials and Methods: Previously published methodology, with minor modifications, was used to establish, cryopreserve, and serially passage RCC cells from nephrectomy and tumorgraft specimens. Cells were characterized for immuno- and molecular phenotype by immunochemistry, DNA sequencing and gene expression profiling. Tumorigenic potential was evaluated by implanting cells under the renal capsule of immunocompromised mice. The ability to monitor xenograft growth by magnetic resonance imaging (MRI) was investigated. Responses to a tyrosine kinase inhibitor (TKI) and an mTOR inhibitor were measured. Results: Primary cultures were successfully established from 11 clear cell and 1 chromophobe RCC, cryopreserved and serially passaged. Retention of immuno- and molecular phenotypes was demonstrated. Cultured cells formed xenografts in mice that could be measured by MRI. Patient-specific responses to drugs were observed in vitro and response to an TKI was confirmed in vivo. Conclusions: Our study is the first to show the derivation of primary cultures from RCC tumorgrafts, and to demonstrate the ability of primary RCC cultures to generate xenografts in mice. Our results suggest the feasibility of establishing large, well-annotated banks of RCC primary cultures for high-throughput drug screening in vitro and validation in vivo, providing a versatile platform together with xenografts and patient-derived precision-cut tissue slice tumorgrafts we developed previously for precilinical studies of RCC. Microarray analyses were performed to compare the gene expression profile of one of the primary cultures (case 7) to its parental tumor and tissue slice tumorgrafts in the study. Tissue slice grafts and parent tumors were preserved in Allprotect tissue reagent (Qiagen, Valencia, CA) at -20Â°C prior to RNA extraction using an AllPrep DNA/RNA/Protein Mini Kit (Qiagen, Valencia, CA). The quality of RNA was determined using an Agilent 2100 Bioanalyzer (Agilent Biotechnologies, Santa Clara, CA). Microarray hybridization was performed using Illumina Human HT-12 v4 Beadchips (Illumina Inc., San Diego, CA) according to the manufacturerâ??s directions. Expression data was rank invariant normalized using BeadStudio software (Illumina Inc.).

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Renal habitat WXS

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