Human repair-related Schwann cells adopt functions of antigen-presenting cells in vitro.

The plastic potential of Schwann cells (SCs) is increasingly recognized to play a role after nerve injury and in diseases of the peripheral nervous system. Reports on the interaction between immune cells and SCs indicate their involvement in inflammatory processes. However, the immunocompetence of human SCs has been primarily deduced from neuropathies, but whether after nerve injury SCs directly regulate an adaptive immune response is unknown. Here, we performed comprehensive analysis of immunomodulatory capacities of human repair-related SCs (hrSCs), which recapitulate SC response to nerve injury in vitro. We used our well-established culture model of primary hrSCs from human peripheral nerves and analyzed the transcriptome, secretome, and cell surface proteins for pathways and markers relevant in innate and adaptive immunity, performed phagocytosis assays, and monitored T-cell subset activation in allogeneic co-cultures. Our findings show that hrSCs are phagocytic, which is in line with high MHCII expression. Furthermore, hrSCs express co-regulatory proteins, such as CD40, CD80, B7H3, CD58, CD86, and HVEM, release a plethora of chemoattractants, matrix remodeling proteins and pro- as well as anti-inflammatory cytokines, and upregulate the T-cell inhibiting PD-L1 molecule upon pro-inflammatory stimulation with IFNγ. In contrast to monocytes, hrSC alone are not sufficient to trigger allogenic CD4+ and CD8+ T-cells, but limit number and activation status of exogenously activated T-cells. This study demonstrates that hrSCs possess features and functions typical for professional antigen-presenting cells in vitro, and suggest a new role of these cells as negative regulators of T-cell immunity during nerve regeneration.

Amplification of CDK4 and MDM2: a detailed study of a high-risk neuroblastoma subgroup.

In neuroblastoma, MYCN amplification and 11q-deletion are important, although incomplete, markers of high-risk disease. It is therefore relevant to characterize additional alterations that can function as prognostic and/or predictive markers. Using SNP-microarrays, a group of neuroblastoma patients showing amplification of one or multiple 12q loci was identified. Two loci containing CDK4 and MDM2 were commonly co-amplified, although amplification of either locus in the absence of the other was observed. Pharmacological inhibition of CDK4/6 with ribociclib or abemaciclib decreased proliferation in a broad set of neuroblastoma cell lines, including CDK4/MDM2-amplified, whereas MDM2 inhibition by Nutlin-3a was only effective in p53wild-type cells. Combined CDK4/MDM2 targeting had an additive effect in p53wild-type cell lines, while no or negative additive effect was observed in p53mutated cells. Most 12q-amplified primary tumors were of abdominal origin, including those of intrarenal origin initially suspected of being Wilms' tumor. An atypical metastatic pattern was also observed with low degree of bone marrow involvement, favoring other sites such as the lungs. Here we present detailed biological data of an aggressive neuroblastoma subgroup hallmarked by 12q amplification and atypical clinical presentation for which our in vitro studies indicate that CDK4 and/or MDM2 inhibition also could be beneficial.

Spatial and temporal intratumour heterogeneity has potential consequences for single biopsy-based neuroblastoma treatment decisions.

Intratumour heterogeneity is a major cause of treatment failure in cancer. We present in-depth analyses combining transcriptomic and genomic profiling with ultra-deep targeted sequencing of multiregional biopsies in 10 patients with neuroblastoma, a devastating childhood tumour. We observe high spatial and temporal heterogeneity in somatic mutations and somatic copy-number alterations which are reflected on the transcriptomic level. Mutations in some druggable target genes including ALK and FGFR1 are heterogeneous at diagnosis and/or relapse, raising the issue whether current target prioritization and molecular risk stratification procedures in single biopsies are sufficiently reliable for therapy decisions. The genetic heterogeneity in gene mutations and chromosome aberrations observed in deep analyses from patient courses suggest clonal evolution before treatment and under treatment pressure, and support early emergence of metastatic clones and ongoing chromosomal instability during disease evolution. We report continuous clonal evolution on mutational and copy number levels in neuroblastoma, and detail its implications for therapy selection, risk stratification and therapy resistance.

Landscape of Bone Marrow Metastasis in Human Neuroblastoma Unraveled by Transcriptomics and Deep Multiplex Imaging.

While the bone marrow attracts tumor cells in many solid cancers leading to poor outcome in affected patients, comprehensive analyses of bone marrow metastases have not been performed on a single-cell level. We here set out to capture tumor heterogeneity and unravel microenvironmental changes in neuroblastoma, a solid cancer with bone marrow involvement. To this end, we employed a multi-omics data mining approach to define a multiplex imaging panel and developed DeepFLEX, a pipeline for subsequent multiplex image analysis, whereby we constructed a single-cell atlas of over 35,000 disseminated tumor cells (DTCs) and cells of their microenvironment in the metastatic bone marrow niche. Further, we independently profiled the transcriptome of a cohort of 38 patients with and without bone marrow metastasis. Our results revealed vast diversity among DTCs and suggest that FAIM2 can act as a complementary marker to capture DTC heterogeneity. Importantly, we demonstrate that malignant bone marrow infiltration is associated with an inflammatory response and at the same time the presence of immuno-suppressive cell types, most prominently an immature neutrophil/granulocytic myeloid-derived suppressor-like cell type. The presented findings indicate that metastatic tumor cells shape the bone marrow microenvironment, warranting deeper investigations of spatio-temporal dynamics at the single-cell level and their clinical relevance.

Multimodal analysis of cell-free DNA whole-genome sequencing for pediatric cancers with low mutational burden.

Sequencing of cell-free DNA in the blood of cancer patients (liquid biopsy) provides attractive opportunities for early diagnosis, assessment of treatment response, and minimally invasive disease monitoring. To unlock liquid biopsy analysis for pediatric tumors with few genetic aberrations, we introduce an integrated genetic/epigenetic analysis method and demonstrate its utility on 241 deep whole-genome sequencing profiles of 95 patients with Ewing sarcoma and 31 patients with other pediatric sarcomas. Our method achieves sensitive detection and classification of circulating tumor DNA in peripheral blood independent of any genetic alterations. Moreover, we benchmark different metrics for cell-free DNA fragmentation analysis, and we introduce the LIQUORICE algorithm for detecting circulating tumor DNA based on cancer-specific chromatin signatures. Finally, we combine several fragmentation-based metrics into an integrated machine learning classifier for liquid biopsy analysis that exploits widespread epigenetic deregulation and is tailored to cancers with low mutation rates. Clinical associations highlight the potential value of cfDNA fragmentation patterns as prognostic biomarkers in Ewing sarcoma. In summary, our study provides a comprehensive analysis of circulating tumor DNA beyond recurrent genetic aberrations, and it renders the benefits of liquid biopsy more readily accessible for childhood cancers.

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.

Schwann cell plasticity regulates neuroblastic tumor cell differentiation via epidermal growth factor-like protein 8.

Adult Schwann cells (SCs) possess an inherent plastic potential. This plasticity allows SCs to acquire repair-specific functions essential for peripheral nerve regeneration. Here, we investigate whether stromal SCs in benign-behaving peripheral neuroblastic tumors adopt a similar cellular state. We profile ganglioneuromas and neuroblastomas, rich and poor in SC stroma, respectively, and peripheral nerves after injury, rich in repair SCs. Indeed, stromal SCs in ganglioneuromas and repair SCs share the expression of nerve repair-associated genes. Neuroblastoma cells, derived from aggressive tumors, respond to primary repair-related SCs and their secretome with increased neuronal differentiation and reduced proliferation. Within the pool of secreted stromal and repair SC factors, we identify EGFL8, a matricellular protein with so far undescribed function, to act as neuritogen and to rewire cellular signaling by activating kinases involved in neurogenesis. In summary, we report that human SCs undergo a similar adaptive response in two patho-physiologically distinct situations, peripheral nerve injury and tumor development.

Long-Term Outcome and Role of Biology within Risk-Adapted Treatment Strategies: The Austrian Neuroblastoma Trial A-NB94.

We evaluated long-term outcome and genomic profiles in the Austrian Neuroblastoma Trial A-NB94 which applied a risk-adapted strategy of treatment (RAST) using stage, age and MYCN amplification (MNA) status for stratification. RAST ranged from surgery only to intensity-adjusted chemotherapy, single or multiple courses of high-dose chemotherapy (HDT) followed by autologous stem cell rescue depending on response to induction chemotherapy, and irradiation to the primary tumor site. Segmental chromosomal alterations (SCAs) were investigated retrospectively using multi- and pan-genomic techniques. The A-NB94 trial enrolled 163 patients. Patients with localized disease had an excellent ten-year (10y) event free survival (EFS) and overall survival (OS) of 99 ± 1% and 93 ± 2% whilst it was 80 ± 13% and 90 ± 9% for infants with stage 4S and for infants with stage 4 non-MNA disease both 83 ± 15%. Stage 4 patients either >12 months or ≤12 months but with MNA had a 10y-EFS and OS of 45 ± 8% and 47 ± 8%, respectively. SCAs were present in increasing frequencies according to stage and age: in 29% of localized tumors but in 92% of stage 4 tumors (p < 0.001), and in 39% of patients ≤ 12 months but in 63% of patients > 12 months (p < 0.001). RAST successfully reduced chemotherapy exposure in low- and intermediate-risk patients with excellent long-term results while the outcome of high-risk disease met contemporary trials.

Age Dependency of the Prognostic Impact of Tumor Genomics in Localized Resectable MYCN-Nonamplified Neuroblastomas. Report From the SIOPEN Biology Group on the LNESG Trials and a COG Validation Group.

PURPOSE: For localized, resectable neuroblastoma without MYCN amplification, surgery only is recommended even if incomplete. However, it is not known whether the genomic background of these tumors may influence outcome. PATIENTS AND METHODS: Diagnostic samples were obtained from 317 tumors, International Neuroblastoma Staging System stages 1/2A/2B, from 3 cohorts: Localized Neuroblastoma European Study Group I/II and Children's Oncology Group. Genomic data were analyzed using multi- and pangenomic techniques and fluorescence in-situ hybridization in 2 age groups (cutoff age, 18 months) and were quality controlled by the International Society of Pediatric Oncology European Neuroblastoma (SIOPEN) Biology Group. RESULTS: Patients with stage 1 tumors had an excellent outcome (5-year event-free survival [EFS] ± standard deviation [SD], 95% ± 2%; 5-year overall survival [OS], 99% ± 1%). In contrast, patients with stage 2 tumors had a reduced EFS in both age groups (5-year EFS ± SD, 84% ± 3% in patients < 18 months of age and 75% ± 7% in patients ≥ 18 months of age). However, OS was significantly decreased only in the latter group (5-year OS ± SD in < 18months and ≥ 18months, 96% ± 2% and 81% ± 7%, respectively; P = .001). In < 18months, relapses occurred independent of segmental chromosome aberrations (SCAs); only 1p loss decreased EFS (5-year EFS ± SD in patients 1p loss and no 1p loss, 62% ± 13% and 87% ± 3%, respectively; P = .019) but not OS (5-year OS ± SD, 92% ± 8% and 97% ± 2%, respectively). In patients ≥ 18 months, only SCAs led to relapse and death, with 11q loss as the strongest marker (11q loss and no 11q loss: 5-year EFS ± SD, 48% ± 16% and 85% ± 7%, P = .033; 5-year OS ± SD, 46% ± 22% and 92% ± 6%, P = .038). CONCLUSION: Genomic aberrations of resectable non-MYCN-amplified stage 2 neuroblastomas have a distinct age-dependent prognostic impact. Chromosome 1p loss is a risk factor for relapse but not for diminished OS in patients < 18 months, SCAs (especially 11q loss) are risk factors for reduced EFS and OS in those > 18months. In older patients with SCA, a randomized trial of postoperative chemotherapy compared with observation alone may be indicated.

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.