A human neural crest model reveals the developmental impact of neuroblastoma-associated chromosomal aberrations.

Early childhood tumours arise from transformed embryonic cells, which often carry large copy number alterations (CNA). However, it remains unclear how CNAs contribute to embryonic tumourigenesis due to a lack of suitable models. Here we employ female human embryonic stem cell (hESC) differentiation and single-cell transcriptome and epigenome analysis to assess the effects of chromosome 17q/1q gains, which are prevalent in the embryonal tumour neuroblastoma (NB). We show that CNAs impair the specification of trunk neural crest (NC) cells and their sympathoadrenal derivatives, the putative cells-of-origin of NB. This effect is exacerbated upon overexpression of MYCN, whose amplification co-occurs with CNAs in NB. Moreover, CNAs potentiate the pro-tumourigenic effects of MYCN and mutant NC cells resemble NB cells in tumours. These changes correlate with a stepwise aberration of developmental transcription factor networks. Together, our results sketch a mechanistic framework for the CNA-driven initiation of embryonal tumours.

Comparative transcriptomics coupled to developmental grading via transgenic zebrafish reporter strains identifies conserved features in neutrophil maturation.

Neutrophils are evolutionarily conserved innate immune cells playing pivotal roles in host defense. Zebrafish models have contributed substantially to our understanding of neutrophil functions but similarities to human neutrophil maturation have not been systematically characterized, which limits their applicability to studying human disease. Here we show, by generating and analysing transgenic zebrafish strains representing distinct neutrophil differentiation stages, a high-resolution transcriptional profile of neutrophil maturation. We link gene expression at each stage to characteristic transcription factors, including C/ebp-ß, which is important for late neutrophil maturation. Cross-species comparison of zebrafish, mouse, and human samples confirms high molecular similarity of immature stages and discriminates zebrafish-specific from pan-species gene signatures. Applying the pan-species neutrophil maturation signature to RNA-sequencing data from human neuroblastoma patients reveals association between metastatic tumor cell infiltration in the bone marrow and an overall increase in mature neutrophils. Our detailed neutrophil maturation atlas thus provides a valuable resource for studying neutrophil function at different stages across species in health and disease.

Single-cell transcriptomics and epigenomics unravel the role of monocytes in neuroblastoma bone marrow metastasis.

Metastasis is the major cause of cancer-related deaths. Neuroblastoma (NB), a childhood tumor has been molecularly defined at the primary cancer site, however, the bone marrow (BM) as the metastatic niche of NB is poorly characterized. Here we perform single-cell transcriptomic and epigenomic profiling of BM aspirates from 11 subjects spanning three major NB subtypes and compare these to five age-matched and metastasis-free BM, followed by in-depth single cell analyses of tissue diversity and cell-cell interactions, as well as functional validation. We show that cellular plasticity of NB tumor cells is conserved upon metastasis and tumor cell type composition is NB subtype-dependent. NB cells signal to the BM microenvironment, rewiring via macrophage mgration inhibitory factor and midkine signaling specifically monocytes, which exhibit M1 and M2 features, are marked by activation of pro- and anti-inflammatory programs, and express tumor-promoting factors, reminiscent of tumor-associated macrophages. The interactions and pathways characterized in our study provide the basis for therapeutic approaches that target tumor-to-microenvironment interactions.

Mutational spectrum of ATRX aberrations in neuroblastoma and associated patient and tumor characteristics.

Neuroblastoma is the most common extracranial solid tumor in children. The chromatin remodeler ATRX is frequently mutated in high-risk patients with a poor prognosis. Although many studies have reported ATRX aberrations and the associated clinical characteristics in neuroblastoma, a comprehensive overview is currently lacking. In this study, we extensively characterize the mutational spectrum of ATRX aberrations in neuroblastoma tumors reported in previous studies and present an overview of patient and tumor characteristics. We collected the data of a total of 127 neuroblastoma patients and three cell lines with ATRX aberrations originating from 20 papers. We subdivide the ATRX aberrations into nonsense, missense, and multiexon deletions (MEDs) and show that 68% of them are MEDs. Of these MEDs, 75% are predicted to be in-frame. Furthermore, we identify a missense mutational hotspot region in the helicase domain. We also confirm that all three ATRX mutation types are more often identified in patients diagnosed at an older age, but still approximately 40% of the patients are aged 5 years or younger at diagnosis. Surprisingly, we found that 11q deletions are enriched in neuroblastomas with ATRX deletions compared to a reference cohort, but not in neuroblastomas with ATRX point mutations. Taken together, our data emphasizes a distinct ATRX mutation spectrum in neuroblastoma, which should be considered when studying molecular phenotypes and therapeutic strategies.

Evaluation of Deep Learning Architectures for Complex Immunofluorescence Nuclear Image Segmentation.

Separating and labeling each nuclear instance (instance-aware segmentation) is the key challenge in nuclear image segmentation. Deep Convolutional Neural Networks have been demonstrated to solve nuclear image segmentation tasks across different imaging modalities, but a systematic comparison on complex immunofluorescence images has not been performed. Deep learning based segmentation requires annotated datasets for training, but annotated fluorescence nuclear image datasets are rare and of limited size and complexity. In this work, we evaluate and compare the segmentation effectiveness of multiple deep learning architectures (U-Net, U-Net ResNet, Cellpose, Mask R-CNN, KG instance segmentation) and two conventional algorithms (Iterative h-min based watershed, Attributed relational graphs) on complex fluorescence nuclear images of various types. We propose and evaluate a novel strategy to create artificial images to extend the training set. Results show that instance-aware segmentation architectures and Cellpose outperform the U-Net architectures and conventional methods on complex images in terms of F1 scores, while the U-Net architectures achieve overall higher mean Dice scores. Training with additional artificially generated images improves recall and F1 scores for complex images, thereby leading to top F1 scores for three out of five sample preparation types. Mask R-CNN trained on artificial images achieves the overall highest F1 score on complex images of similar conditions to the training set images while Cellpose achieves the overall highest F1 score on complex images of new imaging conditions. We provide quantitative results demonstrating that images annotated by under-graduates are sufficient for training instance-aware segmentation architectures to efficiently segment complex fluorescence nuclear images.

Targeting aggressive osteosarcoma with a peptidase-enhanced cytotoxic melphalan flufenamide.

BACKGROUND: Low survival rates in metastatic high-grade osteosarcoma (HGOS) have remained stagnant for the last three decades. This study aims to investigate the role of aminopeptidase N (ANPEP) in HGOS progression and its targeting with a novel lipophilic peptidase-enhanced cytotoxic compound melphalan flufenamide (melflufen) in HGOS. METHODS: Meta-analysis of publicly available gene expression datasets was performed to determine the impact of ANPEP gene expression on metastasis-free survival of HGOS patients. The efficacy of standard-of-care anti-neoplastic drugs and a lipophilic peptidase-enhanced cytotoxic conjugate melflufen was investigated in patient-derived HGOS ex vivo models and cell lines. The kinetics of apoptosis and necrosis induced by melflufen and doxorubicin were compared. Anti-neoplastic effects of melflufen were investigated in vivo. RESULTS: Elevated ANPEP expression in diagnostic biopsies of HGOS patients was found to significantly reduce metastasis-free survival. In drug sensitivity assays, melflufen has shown an anti-proliferative effect in HGOS ex vivo samples and cell lines, including those resistant to methotrexate, etoposide, doxorubicin, and PARP inhibitors. Further, HGOS cells treated with melflufen displayed a rapid induction of apoptosis and this sensitivity correlated with high expression of ANPEP. In combination treatments, melflufen demonstrated synergy with doxorubicin in killing HGOS cells. Finally, Melflufen displayed anti-tumor growth and anti-metastatic effects in vivo. CONCLUSION: This study may pave the way for use of melflufen as an adjuvant to doxorubicin in improving the therapeutic efficacy for the treatment of metastatic HGOS.

An annotated fluorescence image dataset for training nuclear segmentation methods.

Fully-automated nuclear image segmentation is the prerequisite to ensure statistically significant, quantitative analyses of tissue preparations,applied in digital pathology or quantitative microscopy. The design of segmentation methods that work independently of the tissue type or preparation is complex, due to variations in nuclear morphology, staining intensity, cell density and nuclei aggregations. Machine learning-based segmentation methods can overcome these challenges, however high quality expert-annotated images are required for training. Currently, the limited number of annotated fluorescence image datasets publicly available do not cover a broad range of tissues and preparations. We present a comprehensive, annotated dataset including tightly aggregated nuclei of multiple tissues for the training of machine learning-based nuclear segmentation algorithms. The proposed dataset covers sample preparation methods frequently used in quantitative immunofluorescence microscopy. We demonstrate the heterogeneity of the dataset with respect to multiple parameters such as magnification, modality, signal-to-noise ratio and diagnosis. Based on a suggested split into training and test sets and additional single-nuclei expert annotations, machine learning-based image segmentation methods can be trained and evaluated.

An evaluation of the effect of bortezomib on radiation-induced urinary bladder dysfunction.

PURPOSE: The urinary bladder is one major organ at risk in radiotherapy of pelvic malignancies. The radiation response manifests in early and chronic changes in bladder function. These are based on inflammatory effects and changes in urothelial cell function and proliferation. This study evaluates the effect of bortezomib as an anti-proliferative and anti-inflammatory compound in an established mouse bladder model. The early radiation-induced bladder dysfunction in the mouse occurs in two phases during the first month after irradiation (phase I: day 0-15, phase II: days 16-30). MATERIALS AND METHODS: Daily bortezomib injections (0.02 mg/ml, subcutaneously) were administered between days 0-15 or 15-30 in separate groups. Single graded radiation doses were administered in five dose groups. Cystometry was carried out before (individual control) and during the first month after irradiation. When bladder capacity was decreased by ≥50%, mice were considered as responders. Statistical analysis was performed by the SPSS software version 24. RESULTS: Daily bortezomib injections between days 0-15 resulted in a significant decrease in responders for phase I. There was no significant effect with daily bortezomib injections between days 16-30. CONCLUSION: Two separate waves of acute radiation-induced urinary bladder dysfunction have distinct mechanisms that need further biological studies.

DeepSNP: An End-to-End Deep Neural Network with Attention-Based Localization for Breakpoint Detection in Single-Nucleotide Polymorphism Array Genomic Data.

Clinical decision-making in cancer and other diseases relies on timely and cost-effective genome-wide testing. Classical bioinformatic algorithms, such as Rawcopy, can support genomic analysis by calling genomic breakpoints and copy-number variations (CNVs), but often require manual data curation, which is error prone, time-consuming, and thus substantially increasing costs of genomic testing and hampering timely delivery of test results to the treating physician. We aimed to investigate whether deep learning algorithms can be used to learn from genome-wide single-nucleotide polymorphism array (SNPa) data and improve state-of-the-art algorithms. We developed, applied, and validated a novel deep neural network (DNN), DeepSNP. A manually curated data set of 50 SNPa analyses was used as truth-set. We show that DeepSNP can learn from SNPa data and classify the presence or absence of genomic breakpoints within large genomic windows with high precision and recall. DeepSNP was compared with well-known neural network models as well as with Rawcopy. Moreover, the use of a localization unit indicates the ability to pinpoint genomic breakpoints despite their exact location not being provided while training. DeepSNP results demonstrate the potential of DNN architectures to learn from genomic SNPa data and encourage further adaptation for CNV detection in SNPa and other genomic data types.

Systemic administration of heparin ameliorates radiation-induced oral mucositis-preclinical studies in mice.

PURPOSE: The present study investigates the impact of systemic application of heparins on the manifestation of radiation-induced oral mucositis in a well-established mouse model. MATERIALS AND METHODS: Male C3H/Neu mice were irradiated with either single-dose or fractionated irradiation protocols with 5â€¯× 3 Gy/week, given over one (days 0-4) or two (days 0-4, 7-11) weeks. All fractionation protocols were concluded by a local test irradiation (day 7/14) using graded doses to generate complete dose-effect curves. Daily doses of unfractionated or low molecular weight heparin (40 or 200 I.U./mouse, respectively) were applied subcutaneously over varying time intervals. The incidence and the time course of mucosal ulceration, corresponding to confluent mucositis in patients (RTOG/EORTC grade 3), were analysed as clinically relevant endpoints. RESULTS: Systemic application of heparins significantly increased the iso-effective doses for the induction of mucosal ulceration, particularly in combination with fractionated irradiation protocols. Moreover, a tentative prolongation of the latent time and a pronounced reduction of the ulcer duration were observed. CONCLUSION: These data provide the first evidence for a protective and/or mitigative effect of heparins for radiation-induced oral mucositis. Further studies are ongoing investigating the underlying mechanism.

Early inflammatory changes in radiation-induced oral mucositis : Effect of pentoxifylline in a mouse model.

PURPOSE: Early inflammation is a major factor of mucosal reactions to radiotherapy. Pentoxifylline administration resulted in a significant amelioration of radiation-induced oral mucositis in the mouse tongue model. The underlying mechanisms may be related to the immunomodulatory properties of the drug. The present study hence focuses on the manifestation of early inflammatory changes in mouse tongue during daily fractionated irradiation and their potential modulation by pentoxifylline. MATERIALS AND METHODS: Daily fractionated irradiation with 5 fractions of 3 Gy/week (days 0-4, 7-11) was given to the snouts of mice. Groups of 3 animals per day were euthanized every second day between day 0 and 14. Pentoxifylline (15 mg/kg, s. c.) was administered daily from day 5 to the day before sacrifice. The expression of the inflammatory proteins TNFα, NF-κB, and IL-1ß were analysed. RESULTS: Fractionated irradiation increased the expression of all inflammatory markers. Pentoxifylline significantly reduced the expression of TNFα and IL-1ß, but not NF-κB. CONCLUSION: Early inflammation, as indicated by the expression of the inflammatory markers TNFα, NF-κB, and IL-1ß, is an essential component of early radiogenic oral mucositis. Pentoxifylline differentially modulated the expression of different inflammatory markers. The mucoprotective effect of pentoxifylline does not appear to be based on modulation of NF-κB-associated inflammation.

Local hypoxia in oral mucosa (mouse) during daily fractionated irradiation - Effect of pentoxifylline.

PURPOSE: A significant reduction of radiation-induced oral mucositis by systemic application of pentoxifylline has been demonstrated in a mouse tongue model. However, the underlying mechanisms remain unclear. The present study focuses on the development of local hypoxia in mouse tongue during daily fractionated irradiation and a potential modulation by pentoxifylline. MATERIALS AND METHODS: Daily fractionated irradiation with 5×3Gy/week (days 0-4, 7-11) was given to the snouts of mice. Groups of 3 animals per day were sacrificed between day 0 and 14. Pentoxifylline (15mg/kg, s.c.) was administered daily from day -5 to the day before the mice were sacrificed. The expression of intrinsic hypoxia markers HIF-1α and GLUT1 in the epithelium of the lower tongue surface was analysed by immunohistochemistry in 3 animals per day; the percentage of positive epithelial cells and the staining intensity were analysed as endpoints. RESULTS: Compared to untreated control tissue, fractionated irradiation resulted in a progressive increase in the expression of both hypoxia markers. This effect was significantly reduced by pentoxifylline. CONCLUSION: An early onset of local hypoxia occurs during fractionated irradiation in mouse tongue epithelium. The effect is markedly reduced by the mucoprotective agent pentoxifylline, suggesting a mucositis-promoting role of hypoxia; this, however, deserves further investigation.

Modulation of radiation-induced oral mucositis by pentoxifylline: preclinical studies.

BACKGROUND AND PURPOSE: Oral mucositis is a frequent early side effect of radio(chemo)therapy of head-and-neck malignancies. The epithelial radiation response is accompanied by inflammatory reactions; their interaction with epithelial processes remains unclear. The aim of the present study was to investigate the effect of pentoxifylline (PTX) on the oral mucosal radiation response in the mouse tongue model. MATERIALS AND METHODS: Irradiation comprised fractionation (5 fractions of 3 Gy/week) over 1 (days 0-4) or 2 weeks (days 0-4, 7-11), followed by graded local top-up doses (day 7/14), in order to generate complete dose-effect curves. PTX (15 mg/kg subcutaneously) was applied once daily over varying time intervals. Ulceration of mouse tongue epithelium, corresponding to confluent mucositis, was analyzed as the clinically relevant endpoint. RESULTS: With fractionated irradiation over 1 week, PTX administration significantly reduced the incidence of mucosal reactions when initiated before (day-5) the onset of fractionation; a trend was observed for start of PTX treatment on day 0. Similarly, PTX treatment combined with 2 weeks of fractionation had a significant effect on ulcer incidence in all but one experiment. This clearly illustrates the potential of PTX to ameliorate oral mucositis during daily fractionated irradiation. CONCLUSION: PTX resulted in a significant reduction of oral mucositis during fractionated irradiation, which may be attributed to stimulation of mucosal repopulation processes. The biological basis of this effect, however, needs to be clarified in further, detailed mechanistic studies.

Dosimetric challenges of small animal irradiation with a commercial X-ray unit.

INTRODUCTION: A commercial X-ray unit was recently installed at the Medical University Vienna for partial and whole body irradiation of small experimental animals. For 200 kV X-rays the dose deviations with respect to the reference dose measured in the geometrical center of the potential available field size was investigated for various experimental setup plates used for mouse irradiations. Furthermore, the HVL was measured in mm Al and mm Cu at 200 kV for two types of filtration. MATERIAL AND METHODS: Three different setup constructions for small animal irradiation were dosimetrically characterized, covering field sizes from 9×20 mm2 to 210×200 mm2. Different types of detectors were investigated. Additionally LiF:MG,Ti TLD chips were used for mouse in-vivo dosimetry. RESULTS: The use of an additional 0.5 mm Cu filter reduced the deviation of the dose between each irradiation position on the setup plates. Multiple animals were irradiated at the same time using an individual setup plate for each experimental purpose. The dose deviations of each irradiation position to the center was measured to be ±4% or better. The depth dose curve measured in a solid water phantom was more pronounced for smaller field sizes. The comparison between estimated dose and measured dose in a PMMA phantom regarding the dose decline yielded in a difference of 3.9% at 20 mm depth. In-vivo measurements in a mouse snouts irradiation model confirmed the reference dosimetry, accomplished in PMMA phantoms, in terms of administered dose and deviation within different points of measurement. DISCUSSION AND CONCLUSION: The outlined experiments dealt with a wide variety of dosimetric challenges during the installation of a new X-ray unit in the laboratory. The depth dose profiles measured for different field sizes were in good agreement with literature data. Different field sizes and spatial arrangement of the animals (depending on each purpose) provide additional challenges for the dosimetric measurements. Thorough dosimetric commissioning has to be performed before a new experimental setup is approved for biological experiments.

Sequence-based high resolution chromosomal comparative genomic hybridization (CGH).

We aimed to devise an appropriate method to directly link the fluorescence profile of chromosomal copy number alterations detected by chromosomal comparative genomic hybridization (cCGH) or any other hybridization or staining information with the genome sequence data. Our goal was to establish an internal anchoring system that could facilitate profile alignment and thus increase the resolution of cCGH. We were able to achieve the alignment of chromosomes with gene mapping data by superimposition of (a) the fluorescence intensity pattern of a sequence-specific fluorochrome (GGCC binding specificity), (b) the cCGH fluorescence intensity profile of individual chromosomes, and (c) the GGCC motif density profile extracted from a genome sequence database. The adjustment of these three pieces of information allowed us to precisely localize, in cytobands and mega base pairs (Mb), regions of genomic alterations such as gene amplifications, gains, or losses. The combined visualization of sequence information and cCGH data together with application of the Warp tool, presented here, considerably improves the cCGH accuracy by increasing its resolution from 10 to 20 Mb to less than 2 Mb.

Genes proximal and distal to MYCN are highly expressed in human neuroblastoma as visualized by comparative expressed sequence hybridization.

MYCN amplification is associated with poor prognosis in neuroblastoma disease. To improve our understanding of the influence of the MYCN amplicon and its corresponding expression, we investigated the 2p expression pattern of MYCN amplified (n = 13) and nonamplified (n = 4) cell lines and corresponding primary tumors (n = 3) using the comparative expressed sequence hybridization technique. All but one MYCN amplified cell line displayed overexpression at 2p. Expression peaks were observed frequently at 2pter and less frequently at 2p24 (MYCN locus), 2p23.3-23.2, and/or 2p23.1. Importantly, cell lines and two corresponding primary tumors displayed expression peaks at similar loci. No significant 2p24 expression level was observed for those cell lines displaying a low amplification rate (n = 3) by comparative genomic hybridization. Only the cell lines with an enhanced peak at 2p23.2-23.3 displayed coamplification of the ALK gene (2p23.2), reported to be associated with unfavorable prognosis. Finally, two of four cell lines without MYCN amplification, both derived from patients with poor outcome, also showed an expression peak at 2p23.2. These data indicate that, besides MYCN, other genes proximal and distal to MYCN are highly expressed in neuroblastoma. The prognostic significance of expression peaks at 2p23.2-23.3, independent of MYCN and ALK status, remains to be investigated.

A new platform linking chromosomal and sequence information.

We have tested whether a direct correlation of sequence information and staining properties of chromosomes is possible and whether this combined information can be used to precisely map any position on the chromosome. Despite huge differences of compaction between the naked DNA and the DNA packed in chromosomes we found a striking correlation when visualizing the GGCC density on both levels. Software was developed that allows one to superimpose chromosomal fluorescence intensity profiles generated by chromolysin A3 (CMA3) staining with GGCC density extracted from the Ensembl database. Thus, any position along the chromosome can be defined in megabase pairs (Mb) besides the cytoband information, enabling direct alignment of chromosomal information with the sequence data. The mapping tool was validated using 13 different BAC clones, resulting in a mean difference from Ensembl data of 2 Mb (ranging from 0.79 to 3.57 Mb). Our results indicate that the sequence density information and information gained with sequence-specific fluorochromes are superimposable. Thus, the visualized GGCC motif density along the chromosome (sequence bands) provides a unique platform for comparing different types of genomic information.