61 research outputs found

    Enhanced detection of neoantigen-reactive T cells targeting unique and shared oncogenes for personalized cancer immunotherapy.

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    Adoptive cell transfer (ACT) of tumor-infiltrating lymphocytes (TILs) targeting neoantigens can mediate tumor regression in selected patients with metastatic epithelial cancer. However, effectively identifying and harnessing neoantigen-reactive T cells for patient treatment remains a challenge and it is unknown whether current methods to detect neoantigen-reactive T cells are missing potentially clinically relevant neoantigen reactivities. We thus investigated whether the detection of neoantigen-reactive TILs could be enhanced by enriching T cells that express PD-1 and/or T cell activation markers followed by microwell culturing to avoid overgrowth of nonreactive T cells. In 6 patients with metastatic epithelial cancer, this method led to the detection of CD4+ and CD8+ T cells targeting 18 and 1 neoantigens, respectively, compared with 6 and 2 neoantigens recognized by CD4+ and CD8+ T cells, respectively, when using our standard TIL fragment screening approach. In 2 patients, no recognition of mutated peptides was observed using our conventional screen, while our high-throughput approach led to the identification of 5 neoantigen-reactive T cell receptors (TCRs) against 5 different mutations from one patient and a highly potent MHC class II-restricted KRASG12V-reactive TCR from a second patient. In addition, in a metastatic tumor sample from a patient with serous ovarian cancer, we isolated 3 MHC class II-restricted TCRs targeting the TP53G245S hot-spot mutation. In conclusion, this approach provides a highly sensitive platform to isolate clinically relevant neoantigen-reactive T cells or their TCRs for cancer treatment

    Cell-specific deletion of C1qa identifies microglia as the dominant source of C1q in mouse brain

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    BACKGROUND: The complement cascade not only provides protection from infection but can also mediate destructive inflammation. Complement is also involved in elimination of neuronal synapses which is essential for proper development, but can be detrimental during aging and disease. C1q, required for several of these complement-mediated activities, is present in the neuropil, microglia, and a subset of interneurons in the brain. METHODS: To identify the source(s) of C1q in the brain, the C1qa gene was selectively inactivated in the microglia or Thy-1(+) neurons in both wild type mice and a mouse model of Alzheimer’s disease (AD), and C1q synthesis assessed by immunohistochemistry, QPCR, and western blot analysis. RESULTS: While C1q expression in the brain was unaffected after inactivation of C1qa in Thy-1(+) neurons, the brains of C1qa (FL/FL) :Cx3cr1 (CreERT2) mice in which C1qa was ablated in microglia were devoid of C1q with the exception of limited C1q in subsets of interneurons. Surprisingly, this loss of C1q occurred even in the absence of tamoxifen by 1 month of age, demonstrating that Cre activity is tamoxifen-independent in microglia in Cx3cr1 (CreERT2/WganJ) mice. C1q expression in C1qa (FL/FL) : Cx3cr1 (CreERT2/WganJ) mice continued to decline and remained almost completely absent through aging and in AD model mice. No difference in C1q was detected in the liver or kidney from C1qa (FL/FL) : Cx3cr1 (CreERT2/WganJ) mice relative to controls, and C1qa (FL/FL) : Cx3cr1 (CreERT2/WganJ) mice had minimal, if any, reduction in plasma C1q. CONCLUSIONS: Thus, microglia, but not neurons or peripheral sources, are the dominant source of C1q in the brain. While demonstrating that the Cx3cr1 (CreERT2/WganJ) deleter cannot be used for adult-induced deletion of genes in microglia, the model described here enables further investigation of physiological roles of C1q in the brain and identification of therapeutic targets for the selective control of complement-mediated activities contributing to neurodegenerative disorders. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12974-017-0814-9) contains supplementary material, which is available to authorized users

    The CCP4 suite : integrative software for macromolecular crystallography

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    The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world

    Reading tea leaves worldwide: decoupled drivers of initial litter decomposition mass‐loss rate and stabilization

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    The breakdown of plant material fuels soil functioning and biodiversity. Currently, process understanding of global decomposition patterns and the drivers of such patterns are hampered by the lack of coherent large‐scale datasets. We buried 36,000 individual litterbags (tea bags) worldwide and found an overall negative correlation between initial mass‐loss rates and stabilization factors of plant‐derived carbon, using the Tea Bag Index (TBI). The stabilization factor quantifies the degree to which easy‐to‐degrade components accumulate during early‐stage decomposition (e.g. by environmental limitations). However, agriculture and an interaction between moisture and temperature led to a decoupling between initial mass‐loss rates and stabilization, notably in colder locations. Using TBI improved mass‐loss estimates of natural litter compared to models that ignored stabilization. Ignoring the transformation of dead plant material to more recalcitrant substances during early‐stage decomposition, and the environmental control of this transformation, could overestimate carbon losses during early decomposition in carbon cycle models
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