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__Introduction__ Currently used tools for breast cancer prognostication and prediction may not adequately reflect a young patient’s prognosis or likely treatment benefit because they were not adequately validated in young patients. Since breast cancers diagnosed at a young age are considered prognostically unfavourable, many treatment guidelines recommend adjuvant systemic treatment for all young patients. Patients cured by locoregional treatment alone are, therefore, overtreated. Lack of prognosticators for young breast cancer patients represents an unmet medical need and has led to the initiation of the PAtients with bReAst cancer DIaGnosed preMenopausally (PARADIGM) initiative. Our aim is to reduce overtreatment of women diagnosed with breast cancer aged ≤40 years. __Methods and analysis__ All young, adjuvant systemic treatment naive breast cancer patients, who had no prior malignancy and were diagnosed between 1989 and 2000, were identified using the population based Netherlands Cancer Registry (n=3525). Archival tumour tissues were retrieved through linkage with the Dutch nationwide pathology registry. Tissue slides will be digitalised and placed on an online im

Contains fulltext : 153904.pdf (publisher's version ) (Open Access), Breast cancers with BRCA1 germline mutation have a characteristic DNA copy number (CN) pattern. We developed a test that assigns CN profiles to be 'BRCA1-like' or 'non-BRCA1-like', which refers to resembling a BRCA1-mutated tumor or resembling a tumor without a BRCA1 mutation, respectively. Approximately one third of the BRCA1-like breast cancers have a BRCA1 mutation, one third has hypermethylation of the BRCA1 promoter and one third has an unknown reason for being BRCA1-like. This classification is indicative of patients' response to high dose alkylating and platinum containing chemotherapy regimens, which targets the inability of BRCA1 deficient cells to repair DNA double strand breaks. We investigated whether this classification can be reliably obtained with next generation sequencing and copy number platforms other than the bacterial artificial chromosome (BAC) array Comparative Genomic Hybridization (aCGH) on which it was originally developed. We investigated samples from 230 breast cancer patients for which a CN profile had been generated on two to five platforms, comprising low coverage CN sequencing, CN extraction from targeted sequencing panels (CopywriteR), Affymetrix SNP6.0, 135K/720K oligonucleotide aCGH, Affymetrix Oncoscan FFPE (MIP) technology, 3K BAC and 32K BAC aCGH. Pairwise comparison of genomic position-mapped profiles from the original aCGH platform and other platforms revealed concordance. For most cases, biological differences between samples exceeded the differences between platforms within one sample. We observed the same classification across different platforms in over 80% of the patients and kappa values of at least 0.36. Differential classification could be attributed to CN profiles that were not strongly associated to one class. In conclusion, we have shown that the genomic regions that define our BRCA1-like classifier are robustly measured by different CN profiling technologies, providing the possibility to retro- and prospectively in

Breast cancers with BRCA1 germline mutation have a characteristic DNA copy number (CN) pattern. We developed a test that assigns CN profiles to be ‘BRCA1-like’ or ‘non-BRCA1-like’, which refers to resembling a BRCA1-mutated tumor or resembling a tumor without a BRCA1 mutation, respectively. Approximately one third of the BRCA1-like breast cancers have a BRCA1 mutation, one third has hypermethylation of the BRCA1 promoter and one third has an unknown reason for being BRCA1-like. This classification is indicative of patients' response to high dose alkylating and platinum containing chemotherapy regimens, which targets the inability of BRCA1 deficient cells to repair DNA double strand breaks. We investigated whether this classification can be reliably obtained with next generation sequencing and copy number platforms other than the bacterial artificial chromosome (BAC) array Comparative Genomic Hybridization (aCGH) on which it was originally developed. We investigated samples from 230 breast cancer patients for which a CN profile had been generated on two to five platforms, comprising low coverage CN sequencing, CN extraction from targeted sequencing panels (CopywriteR), Affymetrix SNP6.0, 135K/720K oligonucleotide aCGH, Affymetrix Oncoscan FFPE (MIP) technology, 3K BAC and 32K BAC aCGH. Pairwise comparison of genomic position-mapped profiles from the original aCGH platform and other platforms revealed concordance. For most cases, biological differences between samples exceeded the differences between platforms within one sample. We observed the same classification across different platforms in over 80% of the patients and kappa values of at least 0.36. Differential classification could be attributed to CN profiles that were not strongly associated to one class. In conclusion, we have shown that the genomic regions that define our BRCA1-like classifier are robustly measured by different CN profiling technologies, providing the possibility to retro- and prospectively in, Intelligent Systems, Electrical Engineering, Mathematics and Computer Science

Item does not contain fulltext, Glycosylated alpha-dystroglycan (alpha-DG) serves as cellular entry receptor for multiple pathogens, and defects in its glycosylation cause hereditary Walker-Warburg syndrome (WWS). At least eight proteins are critical to glycosylate alpha-DG, but many genes mutated in WWS remain unknown. To identify modifiers of alpha-DG, we performed a haploid screen for Lassa virus entry, a hemorrhagic fever virus causing thousands of deaths annually that hijacks glycosylated alpha-DG to enter cells. In complementary screens, we profiled cells for absence of alpha-DG carbohydrate chains or biochemically related glycans. This revealed virus host factors and a suite of glycosylation units, including all known Walker-Warburg genes and five additional factors critical for the modification of alpha-DG. Our findings accentuate the complexity of this posttranslational feature and point out genes defective in dystroglycanopathies.

Polycomb group (PcG) proteins bind and regulate hundreds of genes. Previous evidence has suggested that long-range chromatin interactions may contribute to the regulation of PcG target genes. Here, we adapted the Chromosome Conformation Capture on Chip (4C) assay to systematically map chromosomal interactions in Drosophila melanogaster larval brain tissue. Our results demonstrate that PcG target genes interact extensively with each other in nuclear space. These interactions are highly specific for PcG target genes, because non-target genes with either low or high expression show distinct interactions. Notably, interactions are mostly limited to genes on the same chromosome arm, and we demonstrate that a topological rather than a sequence-based mechanism is responsible for this constraint. Our results demonstrate that many interactions among PcG target genes exist and that these interactions are guided by overall chromosome architecture., Polycomb group (PcG) proteins bind and regulate hundreds of genes. Previous evidence has suggested that long-range chromatin interactions may contribute to the regulation of PcG target genes. Here, we adapted the Chromosome Conformation Capture on Chip (4C) assay to systematically map chromosomal interactions in Drosophila melanogaster larval brain tissue. Our results demonstrate that PcG target genes interact extensively with each other in nuclear space. These interactions are highly specific for PcG target genes, because non-target genes with either low or high expression show distinct interactions. Notably, interactions are mostly limited to genes on the same chromosome arm, and we demonstrate that a topological rather than a sequence-based mechanism is responsible for this constraint. Our results demonstrate that many interactions among PcG target genes exist and that these interactions are guided by overall chromosome architecture.

The mechanism by which the immune system produces effector and memory T cells is largely unclear. To allow a large-scale assessment of the development of single naive T cells into different subsets, we have developed a technology that introduces unique genetic tags (barcodes) into naive T cells. By comparing the barcodes present in antigen-specific effector and memory T cell populations in systemic and local infection models, at different anatomical sites, and for TCR–pMHC interactions of different avidities, we demonstrate that under all conditions tested, individual naive T cells yield both effector and memory CD8+ T cell progeny. This indicates that effector and memory fate decisions are not determined by the nature of the priming antigen-presenting cell or the time of T cell priming. Instead, for both low and high avidity T cells, individual naive T cells have multiple fates and can differentiate into effector and memory T cell subsets.

Specific interactions of the genome with the nuclear lamina (NL) are thought to assist chromosome folding inside the nucleus and to contribute to the regulation of gene expression. High-resolution mapping has recently identified hundreds of large, sharply defined lamina-associated domains (LADs) in the human genome, and suggested that the insulator protein CTCF may help to demarcate these domains. Here, we report the detailed structure of LADs in Drosophila cells, and investigate the putative roles of five insulator proteins in LAD organization. We found that the Drosophila genome is also organized in discrete LADs, which are about five times smaller than human LADs but contain on average a similar number of genes. Systematic comparison to new and published insulator binding maps shows that only SU(HW) binds preferentially at LAD borders and at specific positions inside LADs, while GAF, CTCF, BEAF-32 and DWG are mostly absent from these regions. By knockdown and overexpression studies we demonstrate that SU(HW) weakens genome – NL interactions through a local antagonistic effect, but we did not obtain evidence that it is essential for border formation. Our results provide insights into the evolution of LAD organization and identify SU(HW) as a fine-tuner of genome – NL interactions., Biotechnology, Applied Sciences

Contains fulltext : 47779.pdf (publisher's version ) (Closed access), Follicular lymphoma (FL) is a disease characterized by a long clinical course marked by frequent relapses that vary in clinical aggressiveness over time. Therefore, the main dilemma at each relapse is the choice for the most effective treatment for optimal disease control and failure-free survival while at the same time avoiding overtreatment and harmful side effects. The selection for more aggressive treatment is currently based on histologic grading and clinical criteria; however, in up to 30% of all cases these methods prove to be insufficient. Using supervised classification on a training set of paired samples from patients who experienced either an indolent or aggressive disease course, a gene expression profile of 81 genes was established that could, with an accuracy of 100%, distinguish low-grade from high-grade disease. This profile accurately classified 93% of the FL samples in an independent validation set. Most important, in a third series of FL cases where histologic grading was ambiguous, precluding meaningful morphologic guidance, the 81-gene profile shows a classification accuracy of 94%. The FL stratification profile is a more reliable marker of clinical behavior than the currently used histologic grading and clinical criteria and may provide an important alternative to guide the choice of therapy in patients with FL both at presentation and at relapse.