Significant increase of high-risk chromosome 1q gain and 6q loss at recurrence in posterior fossa group A ependymoma: A multicenter study.

BACKGROUND: Ependymoma (EPN) posterior fossa group A (PFA) has the highest rate of recurrence and the worst prognosis of all EPN molecular groups. At relapse, it is typically incurable even with re-resection and re-irradiation. The biology of recurrent PFA remains largely unknown; however, the increasing use of surgery at first recurrence has now provided access to clinical samples to facilitate a better understanding of this. METHODS: In this large longitudinal international multicenter study, we examined matched samples of primary and recurrent disease from PFA patients to investigate the biology of recurrence. RESULTS: DNA methylome derived copy number variants (CNVs) revealed large-scale chromosome gains and losses at recurrence in PFA. CNV changes were dominated by chromosome 1q gain and/or 6q loss, both previously identified as high-risk factors in PFA, which were present in 23% at presentation but increased to 61% at first recurrence. Multivariate survival analyses of this cohort showed that cases with 1q gain or 6q loss at first recurrence were significantly more likely to recur again. Predisposition to 1q+/6q- CNV changes at recurrence correlated with hypomethylation of heterochromatin-associated DNA at presentation. Cellular and molecular analyses revealed that 1q+/6q- PFA had significantly higher proportions of proliferative neuroepithelial undifferentiated progenitors and decreased differentiated neoplastic subpopulations. CONCLUSIONS: This study provides clinically and preclinically actionable insights into the biology of PFA recurrence. The hypomethylation predisposition signature in PFA is a potential risk-classifier for trial stratification. We show that the cellular heterogeneity of PFAs evolves largely because of genetic evolution of neoplastic cells.

Spatial transcriptomic analysis delineates epithelial and mesenchymal subpopulations and transition stages in childhood ependymoma.

BACKGROUND: The diverse cellular constituents of childhood brain tumor ependymoma, recently revealed by single cell RNA-sequencing, may underly therapeutic resistance. Here we use spatial transcriptomics to further advance our understanding of the tumor microenvironment, mapping cellular subpopulations to the tumor architecture of ependymoma posterior fossa subgroup A (PFA), the commonest and most deadly childhood ependymoma variant. METHODS: Spatial transcriptomics data from intact PFA sections was deconvoluted to resolve the histological arrangement of neoplastic and non-neoplastic cell types. Key findings were validated using immunohistochemistry, in vitro functional assays and outcome analysis in clinically-annotated PFA bulk transcriptomic data. RESULTS: PFA are comprised of epithelial and mesenchymal histological zones containing a diversity of cellular states, each zone including co-existing and spatially distinct undifferentiated progenitor-like cells; a quiescent mesenchymal zone population, and a second highly mitotic progenitor population that is restricted to hypercellular epithelial zones and that is more abundant in progressive tumors. We show that myeloid cell interaction is the leading cause of mesenchymal transition in PFA, occurring in zones spatially distinct from hypoxia-induced mesenchymal transition, and these distinct EMT-initiating processes were replicated using in vitro models of PFA. CONCLUSIONS: These insights demonstrate the utility of spatial transcriptomics to advance our understanding of ependymoma biology, revealing a clearer picture of the cellular constituents of PFA, their interactions and influence on tumor progression.

A novel, germline, deactivating CBL variant p.L493F alters domain orientation and is associated with multiple childhood cancers.

CBL is a mammalian gene encoding the protein CBL, which is an E3 ubiquitin-protein ligase involved in cell signaling and protein ubiquitination. Pathogenic variants in this gene have been implicated in a number of human cancers, particularly acute myeloid leukemia (AML). Here, we present a 5-year-old male patient with a history of AML, diffuse midline glioma, and left brain lesion with histiocytic features. A variant of uncertain significance (VUS): p.L493F was detected in his CBL gene via clinical evaluation. Protein modeling predicts this variant to be pathogenic. Details of the clinical evaluation and modeling assay are discussed.

Diagnostic accuracy of neuroimaging in pediatric optic chiasm/sellar/suprasellar tumors.

Preoperative diagnosis for tumors arising in the optic chiasm/sellar/suprasellar region in children is helpful to determine surgical necessity and approach, given the high operative risk in this area. We evaluated the ability to differentiate tumor type by preoperative neuroimaging. Thirty-eight of 53 tumors were correctly diagnosed by neuroimaging based on final pathologic diagnosis (prediction accuracy 72%). Prediction accuracies were 87% (20/23) for craniopharyngioma, 79% (11/14) for optic pathway glioma, 64% (7/11) for germ cell tumor, and 0% (0/5) for Langerhans cell histiocytosis. Diagnosis of optic chiasm/sellar/suprasellar tumors in children by imaging alone should be considered when biopsy is considered high risk.

Why and how should we assess occupational health impacts in integrated product policy?

Integrated product policy (IPP) and life cycle assessment (LCA), one of the analytic tools used in IPP, focus traditionally on environmental impacts. However, in an attempt to consider other sustainability criteria and to avoid a shift from environmental health impacts to occupational health impacts one may want to include occupational health in IPP. Should and can occupational health impacts be included in LCA and IPP? Using published and unpublished occupational health data for injuries and illnesses and an economic input-output model of the United States, we provide attributional occupational health impacts measured in disability adjusted life years per dollars output for 491 industry sectors including supply chain impacts. Estimates for the "true" number of United States occupational health impacts suggest that this initial analysis underestimates the total impact 3-7-fold. A comparison suggests that United States occupational health impacts are about 10 times smaller than environmental health impacts and are, relatively speaking, important only for sectors with hazardous working environments but low environmental impacts. A consequential rather than attributional view suggests that a method to assess true consequences on long-term health impacts by product policies needs to be able to predict effects from present-day work place exposure and to account for likely changes in the labor market, including changes in unemployment rates and other substitution mechanisms.

Life cycle emission distributions within the economy: implications for life cycle impact assessment.

Refinements of methods for life cycle impact assessment (LCIA) are directed at removing unjustified simplifications and quantifying and reducing uncertainties in results. The amount of uncertainty reduction that is actually achieved through LCIA method refinement depends on the structure of the life cycle inventory model. We investigate the general structure of inventory models using an economic input/output (I/O) life cycle assessment model of the U.S. economy. In particular, we study the results of applying a streamlining algorithm to the I/O LCA model. The streamlining algorithm retains only those "branches" of the process tree that are jointly required to account for a specified fraction of the total impacts upstream of each point in the tree. We examine the implications of these "tree pruning" results for site-informed LCIA. Percentiles are presented for U.S. commodities and several important pollutants, for the share of total upstream emissions contributed by the set of processes in each supply tier, that is, each set of processes that directly supply inputs to another set of processes Capturing at least 90% of the total direct plus upstream emissions for criteria air pollutants and toxic releases for at least 75% of the commodities in the U.S. economy requires full modeling of direct emissions plus the first five supply tiers. The requirements for capturing a high percentage (e.g., >80%) of total emissions vary widely across products or commodities. To capture more than 60% of total emissions for more than half of all commodities requires models with more than 4,000 process instances. To well characterize the total impacts of products, life cycle impact assessment methods must characterize foreground process impacts in a site-informed way and mean impacts of far-removed processes in an unbiased way.

Integrating risk assessment and life cycle assessment: a case study of insulation.

Increasing residential insulation can decrease energy consumption and provide public health benefits, given changes in emissions from fuel combustion, but also has cost implications and ancillary risks and benefits. Risk assessment or life cycle assessment can be used to calculate the net impacts and determine whether more stringent energy codes or other conservation policies would be warranted, but few analyses have combined the critical elements of both methodologies In this article, we present the first portion of a combined analysis, with the goal of estimating the net public health impacts of increasing residential insulation for new housing from current practice to the latest International Energy Conservation Code (IECC 2000). We model state-by-state residential energy savings and evaluate particulate matter less than 2.5 microm in diameter (PM2.5), NOx, and SO2 emission reductions. We use past dispersion modeling results to estimate reductions in exposure, and we apply concentration-response functions for premature mortality and selected morbidity outcomes using current epidemiological knowledge of effects of PM2.5 (primary and secondary). We find that an insulation policy shift would save 3 x 10(14) British thermal units or BTU (3 x 10(17) J) over a 10-year period, resulting in reduced emissions of 1,000 tons of PM2.5, 30,000 tons of NOx, and 40,000 tons of SO2. These emission reductions yield an estimated 60 fewer fatalities during this period, with the geographic distribution of health benefits differing from the distribution of energy savings because of differences in energy sources, population patterns, and meteorology. We discuss the methodology to be used to integrate life cycle calculations, which can ultimately yield estimates that can be compared with costs to determine the influence of external costs on benefit-cost calculations.