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Neuroblastoma, a rare embryonic tumor arising from neural crest development, is responsible for 15% of pediatric cancer-related deaths. Recently, several single-cell transcriptome studies were performed on neuroblastoma patient samples to investigate the cell of origin and tumor heterogeneity. However, these individual studies involved a small number of tumors and cells, limiting the conclusions that could be drawn. To overcome this limitation, we integrated seven single-cell or single-nucleus datasets into a harmonized cell atlas covering 362,991 cells across 61 patients. We use this atlas to decipher the transcriptional landscape of neuroblastoma at single-cell resolution, revealing associations between transcriptomic profiles and clinical outcomes within the tumor compartment. In addition, we characterize the complex immune-cell landscape and uncover considerable heterogeneity among tumor-associated macrophages. Finally, we showcase the utility of our atlas as a resource by expanding it with additional data and using it as a reference for data-driven cell-type annotation., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Diabetic kidney disease (DKD) is a prevalent microvascular complication of diabetes mellitus and is associated with a significantly worse prognosis compared to diabetic patients without kidney involvement, other microvascular complications, or non-diabetic chronic kidney disease, due to its higher risk of cardiovascular events, faster progression to end-stage kidney disease, and increased mortality. In clinical practice, diagnosis is based on estimated glomerular filtration rate (eGFR) and albuminuria. However, given the limitations of these diagnostic markers, novel biomarkers must be identified. Omics is a new field of study involving the comprehensive analysis of various types of biological data at the molecular level. In different fields, they have shown promising results in (early) detection of diseases, personalized medicine, therapeutic monitoring, and understanding pathogenesis. DKD is primarily utilized in scientific research and has not yet been implemented in routine clinical practice. The aim of this review is to provide an overview of currently available data on targeted omics. After an extensive literature search, 25 different (panels of) omics were withheld and analyzed. Both serum/plasma and urine proteomics and metabolomics have been described with varying degrees of evidence. For all omics, there is still a relative paucity of data from large, prospective, longitudinal cohorts, presumably because of the heterogeneity of DKD and the lack of patient selection in studies, the complexity of omics technologies, and various practical and ethical considerations (e.g., limited accessibility, cost, and privacy concerns).

Pediatric central nervous system tumors remain challenging to diagnose. Imaging approaches do not provide sufficient detail to discriminate between different tumor types, while the histopathological examination of tumor tissue shows high inter-observer variability. Recent studies have demonstrated the accurate classification of central nervous system tumors based on the DNA methylation profile of a tumor biopsy. However, a brain biopsy holds significant risk of bleeding and damaging the surrounding tissues. Liquid biopsy approaches analyzing circulating tumor DNA show high potential as an alternative and less invasive tool to study the DNA methylation pattern of tumors. Here, we explore the potential of classifying pediatric brain tumors based on methylation profiling of the circulating cell-free DNA (cfDNA) in cerebrospinal fluid (CSF). For this proof-of-concept study, we collected cerebrospinal fluid samples from 19 pediatric brain cancer patients via a ventricular drain placed for reasons of increased intracranial pressure. Analyses on the cfDNA showed high variability of cfDNA quantities across patients ranging from levels below the limit of quantification to 40 ng cfDNA per milliliter of CSF. Classification based on methylation profiling of cfDNA from CSF was correct for 7 out of 20 samples in our cohort. Accurate results were mostly observed in samples of high quality, more specifically those with limited high molecular weight DNA contamination. Interestingly, we show that centrifugation of the CSF prior to processing increases the fraction of fragmented cfDNA to high molecular weight DNA. In addition, classification was mostly correct for samples with high tumoral cfDNA fraction as estimated by computational deconvolution (> 40%). In summary, analysis of cfDNA in the CSF shows potential as a tool for diagnosing pediatric nervous system tumors especially in patients with high levels of tumoral cfDNA in the CSF. Further optimization of the collection procedure, experimental workflow and bioinformatic approach is required to also allow classification for patients with low tumoral fractions in the CSF., (© 2024. The Author(s).)

T-cell acute lymphoblastic leukemia (T-ALL) and T-cell lymphoblastic lymphoma (T-LBL) are rare aggressive hematologic malignancies. Current treatment consists of intensive chemotherapy leading to 80% overall survival but is associated with severe toxic side effects. Furthermore, 10-20% of patients still die from relapsed or refractory disease providing a strong rationale for more specific, targeted therapeutic strategies with less toxicities. Here, we report a novel MYH9::PDGFRB fusion in a T-LBL patient, and demonstrate that this fusion product is constitutively active and sufficient to drive oncogenic transformation in vitro and in vivo. Expanding our analysis more broadly across T-ALL, we found a T-ALL cell line and multiple patient-derived xenograft models with PDGFRB hyperactivation in the absence of a fusion, with high PDGFRB expression in TLX3 and HOXA T-ALL molecular subtypes. To target this PDGFRB hyperactivation, we evaluated the therapeutic effects of a selective PDGFRB inhibitor, CP-673451, both in vitro and in vivo and demonstrated sensitivity if the receptor is hyperactivated. Altogether, our work reveals that hyperactivation of PDGFRB is an oncogenic driver in T-ALL/T-LBL, and that screening T-ALL/T-LBL patients for phosphorylated PDGFRB levels can serve as a biomarker for PDGFRB inhibition as a novel targeted therapeutic strategy in their treatment regimen.

Fibroepithelial stromal polyps (FSPs) are benign mesenchymal lesions occurring in the vulvovaginal region. Following the identification of loss of Retinoblastoma 1 (RB1) on immunohistochemical staining in routine practice, we stained a series of FSPs and performed additional fluorescence in situ hybridization (FISH) and copy number variation (CNV) sequencing to detect losses/deletions in the Retinoblastoma transcriptional corepressor 1 (RB1) gene. Fifteen FSP cases were stained for RB1, and subsequently, 9 cases were examined by FISH to detect a loss of RB1 (13q). Next, CNV sequencing was performed to assess genomic alterations. The mean age of the patients was 50 years. Loss of RB1 expression on immunohistochemistry was seen in 13 cases, and heterogeneous RB1 staining in the remaining 2 cases. FISH showed deletion of RB1 in all of the cases. CNV sequencing failed in almost all cases due to a low tumor content. Based on our findings, we hypothesize that FSPs are part of a spectrum of genetically related lesions, namely the 13q/RB1 family of tumors (which includes pleomorphic fibromas and spindle cell/pleomorphic lipomas). Due to the clinical, morphologic, and molecular overlap, we suggest that FSPs are pleomorphic fibromas occurring in the specialized stroma of the genital region., Competing Interests: The authors declare no conflict of interest., (Copyright © 2023 by the International Society of Gynecological Pathologists.)

Objectives: Cytogenetic abnormalities are predictors of poor prognosis in multiple myeloma (MM). This paper aims to build and validate a multiparametric conventional and functional whole-body MRI-based prediction model for cytogenetic risk classification in newly diagnosed MM., Methods: Patients with newly diagnosed MM who underwent multiparametric conventional whole-body MRI, spinal dynamic contrast-enhanced (DCE-)MRI, spinal diffusion-weighted MRI (DWI) and had genetic analysis were retrospectively included (2011-2020/Ghent University Hospital/Belgium). Patients were stratified into standard versus intermediate/high cytogenetic risk groups. After segmentation, 303 MRI features were extracted. Univariate and model-based methods were evaluated for feature and model selection. Testing was performed using receiver operating characteristic (ROC) and precision-recall curves. Models comparing the performance for genetic risk classification of the entire MRI protocol and of all MRI sequences separately were evaluated, including all features. Four final models, including only the top three most predictive features, were evaluated., Results: Thirty-one patients were enrolled (mean age 66 ± 7 years, 15 men, 13 intermediate-/high-risk genetics). None of the univariate models and none of the models with all features included achieved good performance. The best performing model with only the three most predictive features and including all MRI sequences reached a ROC-area-under-the-curve of 0.80 and precision-recall-area-under-the-curve of 0.79. The highest statistical performance was reached when all three MRI sequences were combined (conventional whole-body MRI + DCE-MRI + DWI). Conventional MRI always outperformed the other sequences. DCE-MRI always outperformed DWI, except for specificity., Conclusions: A multiparametric MRI-based model has a better performance in the noninvasive prediction of high-risk cytogenetics in newly diagnosed MM than conventional MRI alone., Critical Relevance Statement: An elaborate multiparametric MRI-based model performs better than conventional MRI alone for the noninvasive prediction of high-risk cytogenetics in newly diagnosed multiple myeloma; this opens opportunities to assess genetic heterogeneity thus overcoming sampling bias., Key Points: • Standard genetic techniques in multiple myeloma patients suffer from sampling bias due to tumoral heterogeneity. • Multiparametric MRI noninvasively predicts genetic risk in multiple myeloma. • Combined conventional anatomical MRI, DCE-MRI, and DWI had the highest statistical performance to predict genetic risk. • Conventional MRI alone always outperformed DCE-MRI and DWI separately to predict genetic risk. DCE-MRI alone always outperformed DWI separately, except for the parameter specificity to predict genetic risk. • This multiparametric MRI-based genetic risk prediction model opens opportunities to noninvasively assess genetic heterogeneity thereby overcoming sampling bias in predicting genetic risk in multiple myeloma., (© 2024. The Author(s).)

T-lineage acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy that accounts for 10%-15% of pediatric and 25% of adult ALL cases. Although the prognosis of T-ALL has improved over time, the outcome of T-ALL patients with primary resistant or relapsed leukemia remains poor. Therefore, further progress in the treatment of T-ALL requires a better understanding of its biology and the development of more effective precision oncologic therapies. The proto-oncogene MYB is highly expressed in diverse hematologic malignancies, including T-ALLs with genomic aberrations that further potentiate its expression and activity. Previous studies have associated MYB with a malignant role in the pathogenesis of several cancers. However, its role in the induction and maintenance of T-ALL remains relatively poorly understood. In this study, we found that an increased copy number of MYB is associated with higher MYB expression levels, and might be associated with inferior event-free survival of pediatric T-ALL patients. Using our previously described conditional Myb overexpression mice, we generated two distinct MYB-driven T-ALL mouse models. We demonstrated that the overexpression of Myb synergizes with Pten deletion but not with the overexpression of Lmo2  to accelerate the development of T-cell lymphoblastic leukemias. We also showed that MYB is a dependency factor in T-ALL since RNA interference of Myb blocked cell cycle progression and induced apoptosis in both human and murine T-ALL cell lines. Finally, we provide preclinical evidence that targeting the transcriptional activity of MYB can be a useful therapeutic strategy for the treatment of T-ALL., Competing Interests: The authors declare no conflict of interest., (© 2024 The Authors. HemaSphere published by John Wiley & Sons Ltd on behalf of European Hematology Association.)