Entwicklung neuer Therapiekonzepte im myxoiden Liposarkom : Die Rolle von Fibroblastenwachstumsfaktor-Rezeptoren und microRNAs

Myxoide Liposarkome gehören zu den häufigsten Weichgewebssarkomen. Ihre Pathogenese ist aber bislang nur unvollständig verstanden und es stehen keine zielgerichteten Therapien zur Verfügung. Die für myxoide Liposarkome charakteristische Translokation führt zur Bildung eines onkogenen Fusionsproteins, das als aberranter Transkriptionsfaktor wirkt, so dass in dieser Tumorentität die Expression vieler Gene verändert ist. Daher wurden im Rahmen dieser Arbeit auf der Grundlage von whole-genome und microRNA Microarrayanalysen differentiell exprimierte Kandidatengene und -microRNAs identifiziert, validiert und funktionell charakterisiert. In den whole-genome Microarrays wurde u.a. eine Überexpression des Fibroblastenwachstumsfaktor-RezeptorsFGFR2 in myxoiden Liposarkomen im Vergleich zu normalem Fettgewebe detektiert. Fibroblastenwachstumsfaktor-Rezeptoren (FGFR) sind von enormer klinischer Bedeutung und werden bereits in anderen Tumorentitäten als therapeutische Zielstrukturen genutzt. Daher wurde die funktionelle Relevanz des FGFR-Signalwegs in den myxoiden Liposarkomzelllinien MLS 402 und MLS 1765 untersucht. Dabei führte der siRNA-vermittelte knock-down von FGF-Rezeptoren bzw. die Behandlung mit spezifischen FGFR-Tyrosinkinaseinhibitoren zur Reduktion der Zellviabilität, einer Induktion von Apoptose und einer verlangsamten zellulären Migration. Die FGFR-Inhibitoren wurden auch in Kombination mit dem für myxoide Liposarkome zugelassenen Chemotherapeutikum Trabectedin angewendet. Dabei bewirkte die zusätzliche Gabe von FGFR-Inhibitoren eine stärkere Abnahme der Viabilität, Induktion von Apoptose und Verlangsamung der Migration als Trabectedin alleine. Des Weiteren wurden die Daten der whole-genome und microRNA Microarrays integriert und mit Hilfe des bioinformatischen Modells BIRTA gemeinsam ausgewertet, so dass microRNAs mit differentieller Aktivität identifiziert werden konnten. Für ausgewählte microRNAs mit differentieller Expression und Aktivität wurden funktionelle Studien mit entsprechenden microRNA-Imitatoren in den myxoiden Liposarkomzelllinien MLS 402 und MLS 1765 angeschlossen. Dabei zeigten insbesondere die microRNAs miR-141, miR-145 und miR-200a eindeutig tumorsuppressorische Eigenschaften. Im Einklang mit ihrer Herunterregulation in Primärtumoren führte die Transfektion dieser microRNAs in beiden MLS-Zelllinien zu einer Abnahme der Viabilität sowie einer Induktion von Apoptose. Im Rahmen dieser Arbeit wurden so neue Kandidatengene und -microRNAs in myxoiden Liposarkomen identifiziert, die zur Pathogenese der Tumoren beitragen und therapeutische Zielstrukturen darstellen. Über die Beteiligung von microRNAs in dieser Tumorentität lagen bislang kaum Daten vor, so dass diese Arbeit hier neue Schlüsselstellen in der Molekularpathologie myxoider Liposarkome aufdecken konnte. Zudem wurde erstmals eine funktionelle Rolle des FGFR-Signalwegs im myxoiden Liposarkom dargestellt und so die Basis für neue zielgerichtete Therapieansätze mit FGFR-Inhibitoren geschaffen

PD-L1 Dependent Immunogenic Landscape in Hot Lung Adenocarcinomas Identified by Transcriptome Analysis

Background: Lung cancer is the most frequent cause of cancer-related deaths worldwide. The clinical development of immune checkpoint blockade has dramatically changed the treatment paradigm for patients with lung cancer. Yet, an improved understanding of PD-1/PD-L1 checkpoint blockade- responsive biology is warranted. Methods: We aimed to identify the landscape of immune cell infiltration in primary lung adenocarcinoma (LUAD) in the context of tumoral PD-L1 expression and the extent of immune infiltration ("hot" vs. "cold" phenotype). The study comprises LUAD cases (n = 138) with "hot" (≥150 lymphocytes/HPF) and "cold" (<150 lymphocytes/HPF) tumor immune phenotype and positive (>50%) and negative (<1%) tumor PD-L1 expression, respectively. Tumor samples were immunohistochemically analyzed for expression of PD-L1, CD4, and CD8, and further investigated by transcriptome analysis. Results: Gene set enrichment analysis defined complement, IL-JAK-STAT signaling, KRAS signaling, inflammatory response, TNF-alpha signaling, interferon-gamma response, interferon-alpha response, and allograft rejection as significantly upregulated pathways in the PD-L1-positive hot subgroup. Additionally, we demonstrated that STAT1 is upregulated in the PD-L1-positive hot subgroup and KIT in the PD-L1-negative hot subgroup. Conclusion: The presented study illustrates novel aspects of PD-L1 regulation, with potential biological relevance, as well as relevance for immunotherapy response stratification

Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states

Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer’s disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, ‘shape connections’ between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus

Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer’s Disease using structural MR and FDG-PET images

Alzheimer’s Disease (AD) is a progressive neurodegenerative disease where biomarkers for disease based on pathophysiology may be able to provide objective measures for disease diagnosis and staging. Neuroimaging scans acquired from MRI and metabolism images obtained by FDG-PET provide in-vivo measurements of structure and function (glucose metabolism) in a living brain. It is hypothesized that combining multiple different image modalities providing complementary information could help improve early diagnosis of AD. In this paper, we propose a novel deep-learning-based framework to discriminate individuals with AD utilizing a multimodal and multiscale deep neural network. Our method delivers 82.4% accuracy in identifying the individuals with mild cognitive impairment (MCI) who will convert to AD at 3 years prior to conversion (86.4% combined accuracy for conversion within 1–3 years), a 94.23% sensitivity in classifying individuals with clinical diagnosis of probable AD, and a 86.3% specificity in classifying non-demented controls improving upon results in published literature

The impact of PICALM genetic variations on reserve capacity of posterior cingulate in AD continuum

Phosphatidylinositolbinding clathrin assembly protein (PICALM) gene is one novel genetic player associated with late-onset Alzheimer’s disease (LOAD), based on recent genome wide association studies (GWAS). However, how it affects AD occurrence is still unknown. Brain reserve hypothesis highlights the tolerant capacities of brain as a passive means to fight against neurodegenerations. Here, we took the baseline volume and/or thickness of LOAD-associated brain regions as proxies of brain reserve capacities and investigated whether PICALM genetic variations can influence the baseline reserve capacities and the longitudinal atrophy rate of these specific regions using data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. In mixed population, we found that brain region significantly affected by PICALM genetic variations was majorly restricted to posterior cingulate. In sub-population analysis, we found that one PICALM variation (C allele of rs642949) was associated with larger baseline thickness of posterior cingulate in health. We found seven variations in health and two variations (rs543293 and rs592297) in individuals with mild cognitive impairment were associated with slower atrophy rate of posterior cingulate. Our study provided preliminary evidences supporting that PICALM variations render protections by facilitating reserve capacities of posterior cingulate in non-demented elderly

Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease

Quantitative 18F-AV1451 Brain Tau PET Imaging in Cognitively Normal Older Adults, Mild Cognitive Impairment, and Alzheimer's Disease Patients

Recent developments of tau Positron Emission Tomography (PET) allows assessment of regional neurofibrillary tangles (NFTs) deposition in human brain. Among the tau PET molecular probes, 18F-AV1451 is characterized by high selectivity for pathologic tau aggregates over amyloid plaques, limited non-specific binding in white and gray matter, and confined off-target binding. The objectives of the study are (1) to quantitatively characterize regional brain tau deposition measured by 18F-AV1451 PET in cognitively normal older adults (CN), mild cognitive impairment (MCI), and AD participants; (2) to evaluate the correlations between cerebrospinal fluid (CSF) biomarkers or Mini-Mental State Examination (MMSE) and 18F-AV1451 PET standardized uptake value ratio (SUVR); and (3) to evaluate the partial volume effects on 18F-AV1451 brain uptake.Methods: The study included total 115 participants (CN = 49, MCI = 58, and AD = 8) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed 18F-AV1451 PET images, structural MRIs, and demographic and clinical assessments were downloaded from the ADNI database. A reblurred Van Cittertiteration method was used for voxelwise partial volume correction (PVC) on PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. The parametric images of 18F-AV1451 SUVR relative to cerebellum were calculated. The ROI SUVR measurements from PVC and non-PVC SUVR images were compared. The correlation between ROI 18F-AV1451 SUVR and the measurements of MMSE, CSF total tau (t-tau), and phosphorylated tau (p-tau) were also assessed.Results:18F-AV1451 prominently specific binding was found in the amygdala, entorhinal cortex, parahippocampus, fusiform, posterior cingulate, temporal, parietal, and frontal brain regions. Most regional SUVRs showed significantly higher uptake of 18F-AV1451 in AD than MCI and CN participants. SUVRs of small regions like amygdala, entorhinal cortex and parahippocampus were statistically improved by PVC in all groups (p < 0.01). Although there was an increasing tendency of 18F-AV-1451 SUVRs in MCI group compared with CN group, no significant difference of 18F-AV1451 deposition was found between CN and MCI brains with or without PVC (p > 0.05). Declined MMSE score was observed with increasing 18F-AV1451 binding in amygdala, entorhinal cortex, parahippocampus, and fusiform. CSF p-tau was positively correlated with 18F-AV1451 deposition. PVC improved the results of 18F-AV-1451 tau deposition and correlation studies in small brain regions.Conclusion: The typical deposition of 18F-AV1451 tau PET imaging in AD brain was found in amygdala, entorhinal cortex, fusiform and parahippocampus, and these regions were strongly associated with cognitive impairment and CSF biomarkers. Although more deposition was observed in MCI group, the 18F-AV-1451 PET imaging could not differentiate the MCI patients from CN population. More tau deposition related to decreased MMSE score and increased level of CSF p-tau, especially in ROIs of amygdala, entorhinal cortex and parahippocampus. PVC did improve the results of tau deposition and correlation studies in small brain regions and suggest to be routinely used in 18F-AV1451 tau PET quantification

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts