95 research outputs found

    Learning smoothing models of copy number profiles using breakpoint annotations

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    Many models have been proposed to detect breakpoints in chromosomal copy number profiles, but it is usually not obvious to decide which is most effective for a given data set. Furthermore, most methods have a smoothing parameter that determines the number of breakpoints and must be chosen using various heuristics. We present three contributions toward automatic training of smoothing models. First, we propose to select the model and degree of smoothness that maximizes agreement with visual breakpoint region annotations. Second, we develop cross-validation procedures to estimate the error of the trained models. Third, we apply these methods to a new database of annotated neuroblastoma copy number profiles, which we make available as a public benchmark for testing new algorithms. Whereas previous studies have been qualitative or limited to simulated data, our approach is quantitative and suggests which algorithms are fastest and most accurate in practice on real data

    SVDetect: a tool to identify genomic structural variations from paired-end and mate-pair sequencing data

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    Summary: We present SVDetect, a program designed to identify genomic structural variations from paired-end and mate-pair next-generation sequencing data produced by the Illumina GA and ABI SOLiD platforms. Applying both sliding-window and clustering strategies, we use anomalously mapped read pairs provided by current short read aligners to localize genomic rearrangements and classify them according to their type, e.g. large insertions–deletions, inversions, duplications and balanced or unbalanced inter-chromosomal translocations. SVDetect outputs predicted structural variants in various file formats for appropriate graphical visualization

    Control-free calling of copy number alterations in deep-sequencing data using GC-content normalization

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    Summary: We present a tool for control-free copy number alteration (CNA) detection using deep-sequencing data, particularly useful for cancer studies. The tool deals with two frequent problems in the analysis of cancer deep-sequencing data: absence of control sample and possible polyploidy of cancer cells. FREEC (control-FREE Copy number caller) automatically normalizes and segments copy number profiles (CNPs) and calls CNAs. If ploidy is known, FREEC assigns absolute copy number to each predicted CNA. To normalize raw CNPs, the user can provide a control dataset if available; otherwise GC content is used. We demonstrate that for Illumina single-end, mate-pair or paired-end sequencing, GC-contentr normalization provides smooth profiles that can be further segmented and analyzed in order to predict CNAs

    Control-FREEC: a tool for assessing copy number and allelic content using next-generation sequencing data

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    Summary: More and more cancer studies use next-generation sequencing (NGS) data to detect various types of genomic variation. However, even when researchers have such data at hand, single-nucleotide polymorphism arrays have been considered necessary to assess copy number alterations and especially loss of heterozygosity (LOH). Here, we present the tool Control-FREEC that enables automatic calculation of copy number and allelic content profiles from NGS data, and consequently predicts regions of genomic alteration such as gains, losses and LOH. Taking as input aligned reads, Control-FREEC constructs copy number and B-allele frequency profiles. The profiles are then normalized, segmented and analyzed in order to assign genotype status (copy number and allelic content) to each genomic region. When a matched normal sample is provided, Control-FREEC discriminates somatic from germline events. Control-FREEC is able to analyze overdiploid tumor samples and samples contaminated by normal cells. Low mappability regions can be excluded from the analysis using provided mappability tracks

    Single-cell transcriptomics reveals shared immunosuppressive landscapes of mouse and human neuroblastoma

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    BACKGROUND High-risk neuroblastoma is a pediatric cancer with still a dismal prognosis, despite multimodal and intensive therapies. Tumor microenvironment represents a key component of the tumor ecosystem the complexity of which has to be accurately understood to define selective targeting opportunities, including immune-based therapies. METHODS We combined various approaches including single-cell transcriptomics to dissect the tumor microenvironment of both a transgenic mouse neuroblastoma model and a cohort of 10 biopsies from neuroblastoma patients, either at diagnosis or at relapse. Features of related cells were validated by multicolor flow cytometry and functional assays. RESULTS We show that the immune microenvironment of MYCN-driven mouse neuroblastoma is characterized by a low content of T cells, several phenotypes of macrophages and a population of cells expressing signatures of myeloid-derived suppressor cells (MDSCs) that are molecularly distinct from the various macrophage subsets. We document two cancer-associated fibroblasts (CAFs) subsets, one of which corresponding to CAF-S1, known to have immunosuppressive functions. Our data unravel a complex content in myeloid cells in patient tumors and further document a striking correspondence of the microenvironment populations between both mouse and human tumors. We show that mouse intratumor T cells exhibit increased expression of inhibitory receptors at the protein level. Consistently, T cells from patients are characterized by features of exhaustion, expressing inhibitory receptors and showing low expression of effector cytokines. We further functionally demonstrate that MDSCs isolated from mouse neuroblastoma have immunosuppressive properties, impairing the proliferation of T lymphocytes. CONCLUSIONS Our study demonstrates that neuroblastoma tumors have an immunocompromised microenvironment characterized by dysfunctional T cells and accumulation of immunosuppressive cells. Our work provides a new and precious data resource to better understand the neuroblastoma ecosystem and suggest novel therapeutic strategies, targeting both tumor cells and components of the microenvironment

    Combination Therapies Targeting ALK-aberrant Neuroblastoma in Preclinical Models

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    PURPOSE ALK-activating mutations are identified in approximately 10% of newly diagnosed neuroblastomas and ALK amplifications in a further 1%-2% of cases. Lorlatinib, a third-generation anaplastic lymphoma kinase (ALK) inhibitor, will soon be given alongside induction chemotherapy for children with ALK-aberrant neuroblastoma. However, resistance to single-agent treatment has been reported and therapies that improve the response duration are urgently required. We studied the preclinical combination of lorlatinib with chemotherapy, or with the MDM2 inhibitor, idasanutlin, as recent data have suggested that ALK inhibitor resistance can be overcome through activation of the p53-MDM2 pathway. EXPERIMENTAL DESIGN We compared different ALK inhibitors in preclinical models prior to evaluating lorlatinib in combination with chemotherapy or idasanutlin. We developed a triple chemotherapy (CAV: cyclophosphamide, doxorubicin, and vincristine) in vivo dosing schedule and applied this to both neuroblastoma genetically engineered mouse models (GEMM) and patient-derived xenografts (PDX). RESULTS Lorlatinib in combination with chemotherapy was synergistic in immunocompetent neuroblastoma GEMM. Significant growth inhibition in response to lorlatinib was only observed in the ALK-amplified PDX model with high ALK expression. In this PDX, lorlatinib combined with idasanutlin resulted in complete tumor regression and significantly delayed tumor regrowth. CONCLUSIONS In our preclinical neuroblastoma models, high ALK expression was associated with lorlatinib response alone or in combination with either chemotherapy or idasanutlin. The synergy between MDM2 and ALK inhibition warrants further evaluation of this combination as a potential clinical approach for children with neuroblastoma

    ALK germline mutations in patients with neuroblastoma: a rare and weakly penetrant syndrome

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    Neuroblastic tumours may occur in a predisposition context. Two main genes are involved: PHOX2B, observed in familial cases and frequently associated with other neurocristopathies (Ondine's and Hirschsprung's disease); and ALK, mostly in familial tumours. We have assessed the frequency of mutations of these two genes in patients with a presumable higher risk of predisposition. We sequenced both genes in 26 perinatal cases (prebirth and o1 month of age, among which 10 were multifocal), 16 multifocal postnatal (41 month) cases, 3 pairs of affected relatives and 8 patients with multiple malignancies. The whole coding sequences of the two genes were analysed in tumour and/or constitutional DNAs. We found three ALK germline mutations, all in a context of multifocal tumours. Two mutations (T1151R and R1192P) were inherited and shared by several unaffected patients, thus illustrating an incomplete penetrance. Younger age at tumour onset did not seem to offer a relevant selection criterion for ALK analyses. Conversely, multifocal tumours might be the most to benefit from the genetic screening. Finally, no PHOX2B germline mutation was found in this series. In conclusion, ALK deleterious mutations are rare events in patients with a high probability of predisposition. Other predisposing genes remain to be discovered

    Methylation-associated PHOX2B gene silencing is a rare event in human neuroblastoma.

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    International audienceNeuroblastoma (NB), an embryonic tumour originating from neural crest cells, is one of the most common solid tumours in childhood. Although NB is characterised by numerous recurrent, large-scale chromosome rearrangements, the genes targeted by these imbalances have remained elusive. We recently identified the paired-like homeobox 2B (PHOX2B, MIM 603851) gene as disease-causing in dysautonomic disorders including Congenital Central Hypoventilation Syndrome (CCHS), Hirschsprung disease (HSCR) and NB in various combinations. Most patients with NB due to a germline heterozygous PHOX2B gene mutation are familial and/or syndromic. PHOX2B, at chromosome 4p12, does not lie in a commonly rearranged locus in NB. To evaluate the role of PHOX2B in sporadic, isolated NB, we analysed 13 NB cell lines and 45 tumours for expression, mutations of coding and promoter sequences, loss of heterozygosity (LOH), or aberrant hypermethylation of PHOX2B (13 cell lines and 18 tumours). We didn't identify any mutation but LOH in about 10% of the cases and aberrant CpG dinucleotide methylation of the 500 bp PHOX2B promoter region in 4/31 tumours and cell lines (12.9%). Altogether, both germinal and somatic anomalies at the PHOX2B locus are found in NB

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