Summary
Recent scientific discoveries fuelled by the application of next‐generation DNA and RNA sequencing technologies highlight the striking impact of these platforms in characterizing multiple ...aspects in genomics research. This technology has been used in the study of the B‐cell and T‐cell receptor repertoire. The novelty of immunosequencing comes from the recent rapid development of techniques and the exponential reduction in cost of sequencing. Here, we describe some of the technologies, which we collectively refer to as Rep‐Seq (repertoire sequencing), to portray achievements in the field and to present the essential and inseparable role of next‐generation sequencing to the understanding of entities in immune response. The large Rep‐Seq data sets that should be available in the near future call for new computational algorithms to segue the transition from ‘classic’ molecular‐based analysis to system‐wide analysis. The combination of new algorithms with high‐throughput data will form the basis for possible new clinical implications in personalized medicine and deeper understanding of immune behaviour and immune response.
Abstract Identifying robust, patient-specific, and predictive biomarkers presents a major obstacle in precision oncology. To optimize patient-specific therapeutic strategies, here we couple pathway ...knowledge with large-scale drug sensitivity, RNAi, and CRISPR-Cas9 screening data from 460 cell lines. Pathway activity levels are found to be strong predictive biomarkers for the essentiality of 15 proteins, including the essentiality of MAD2L1 in breast cancer patients with high BRCA-pathway activity. We also find strong predictive biomarkers for the sensitivity to 31 compounds, including BCL2 and microtubule inhibitors (MTIs). Lastly, we show that Bcl-xL inhibition can modulate the activity of a predictive biomarker pathway and re-sensitize lung cancer cells and tumors to MTI therapy. Overall, our results support the use of pathways in helping to achieve the goal of precision medicine by uncovering dozens of predictive biomarkers.
Dendritic cells (DCs) control the balance between effector T cells and regulatory T cells in vivo. Hence, the study of DCs might identify mechanisms of disease pathogenesis and guide new therapeutic ...approaches for disorders mediated by the immune system. We found that interleukin 27 (IL-27) signaling in mouse DCs limited the generation of effector cells of the TH1 and TH17 subsets of helper T cells and the development of experimental autoimmune encephalomyelitis (EAE). The effects of IL-27 were mediated at least in part through induction of the immunoregulatory molecule CD39 in DCs. IL-27-induced CD39 decreased the extracellular concentration of ATP and downregulated nucleotide-dependent activation of the NLRP3 inflammasome. Finally, therapeutic vaccination with IL-27-conditioned DCs suppressed established relapsing-remitting EAE. Thus, IL-27 signaling in DCs limited pathogenic T cell responses and the development of autoimmunity.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
While multiplexing samples using DNA barcoding revolutionized the pace of biomedical discovery, multiplexing of live imaging-based applications has been limited by the number of fluorescent proteins ...that can be deconvoluted using common microscopy equipment. To address this limitation, we develop visual barcodes that discriminate the clonal identity of single cells by different fluorescent proteins that are targeted to specific subcellular locations. We demonstrate that deconvolution of these barcodes is highly accurate and robust to many cellular perturbations. We then use visual barcodes to generate 'Signalome' cell-lines by mixing 12 clones of different live reporters into a single population, allowing simultaneous monitoring of the activity in 12 branches of signaling, at clonal resolution, over time. Using the 'Signalome' we identify two distinct clusters of signaling pathways that balance growth and proliferation, emphasizing the importance of growth homeostasis as a central organizing principle in cancer signaling. The ability to multiplex samples in live imaging applications, both in vitro and in vivo may allow better high-content characterization of complex biological systems.
Neurotoxicology is hampered by the inability to predict regional and cellular targets of toxicant‐induced damage. Evaluating astrogliosis overcomes this problem because reactive astrocytes highlight ...the location of toxicant‐induced damage. While enhanced expression of glial fibrillary acidic protein is a hallmark of astrogliosis, few other biomarkers have been identified. However, bacterial artificial chromosome ‐ translating ribosome affinity purification (bacTRAP) technology allows for characterization of the actively translating transcriptome of a particular cell type; use of this technology in aldehyde dehydrogenase 1 family member L1 (ALDH1L1) bacTRAP mice can identify genes selectively expressed in astrocytes. The aim of this study was to characterize additional biomarkers of neurotoxicity‐induced astrogliosis using ALDH1L1 bacTRAP mice. The known dopaminergic neurotoxicant 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP; 12.5 mg/kg s.c.) was used to induce astrogliosis. Striatal tissue was obtained 12, 24, and 48 h following exposure for the isolation of actively translating RNA. Subsequently, MPTP‐induced changes in this RNA pool were analyzed by microarray and 184 statistically significant, differentially expressed genes were identified. The dataset was interrogated by gene ontology, pathway, and co‐expression network analyses, which identified novel genes, as well as those with known immune and inflammatory functions. Using these analyses, we were directed to several genes associated with reactive astrocytes. Of these, TIMP1 and miR‐147 were identified as candidate biomarkers because of their robust increased expression following both MPTP and trimethyl tin exposures. Thus, we have demonstrated that bacTRAP can be used to identify new biomarkers of astrogliosis and aid in the characterization of astrocyte phenotypes induced by toxicant exposures.
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This article has received a badge for *Open Materials* because it provided all relevant information to reproduce the study in the manuscript. The complete Open Science Disclosure form for this article can be found at the end of the article. More information about the Open Practices badges can be found at https://cos.io/our-services/open-science-badges/.
Cover Image for this issue: doi: 10.1111/jnc.14518.
The unpredictable targets of neurotoxicant‐induced neural injury can be revealed by astrogliosis at the sites of damage. Astrogliosis often is defined by enhanced expression of GFAP but a broader repertoire of astrogliosis biomarkers would enhance characterization of astroglial responses to brain injuries. Aldehyde dehydrogenase 1 family member L1 bacterial artificial chromosome ‐ translating ribosome affinity purification (ALDH1L1 bacTRAP) transgenic mice provide a means to evaluate exposure‐driven, transcriptomics following exposure. Here, ALDH1L1 bacTRAP mice were exposed to MPTP identifying two potential biomarkers of toxicant‐induced astrogliosis that were conserved across neurotoxicant exposures, demonstrating the utility of in vivo, cell‐specific analysis in neurotoxicology.
Open Science: This manuscript was awarded with the Open Materials Badge
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Cover Image for this issue: doi: 10.1111/jnc.14518.
Glioblastoma Multiforme (GBM) is the most common and lethal primary tumor of the brain. GBM is associated with one of the worst 5-year survival rates among all human cancers, despite much effort in ...different modes of treatment.
Here, we demonstrate specific GBM cancer phenotypes that are governed by modifications to the MAPAKAP network. We then demonstrate a novel regulation mode by which a set of five key factors of the MAPKAP pathway are regulated by the same microRNA, hsa-miR-9.We demonstrate that hsa-miR-9 overexpression leads to MAPKAP signaling inhibition, partially by interfering with the MAPK14/MAPKAP3 complex. Further, hsa-miR-9 overexpression initiates re-arrangement of actin filaments, which leads us to hypothesize a mechanism for the observed phenotypic shift.
The work presented here exposes novel microRNA features and situates hsa-miR-9 as a therapeutic target, which governs metastasis and thus determines prognosis in GBM through MAPKAP signaling.
Tumors comprise functionally diverse subpopulations of cells with distinct proliferative potential. Here, we show that dynamic epigenetic states defined by the linker histone H1.0 determine which ...cells within a tumor can sustain the long-term cancer growth. Numerous cancer types exhibit high inter- and intratumor heterogeneity of H1.0, with H1.0 levels correlating with tumor differentiation status, patient survival, and, at the single-cell level, cancer stem cell markers. Silencing of H1.0 promotes maintenance of self-renewing cells by inducing derepression of megabase-sized gene domains harboring downstream effectors of oncogenic pathways. Self-renewing epigenetic states are not stable, and reexpression of H1.0 in subsets of tumor cells establishes transcriptional programs that restrict cancer cells' long-term proliferative potential and drive their differentiation. Our results uncover epigenetic determinants of tumor-maintaining cells.
The transcriptional networks that regulate gene expression and modifications to this network are at the core of the cancer phenotype. MicroRNAs, a well-studied species of small non-coding RNA ...molecules, have been shown to have a central role in regulating gene expression as part of this transcriptional network. Further, microRNA deregulation is associated with cancer development and with tumor progression. Glioblastoma Multiform (GBM) is the most common, aggressive and malignant primary tumor of the brain and is associated with one of the worst 5-year survival rates among all human cancers. To study the transcriptional network and its modifications in GBM, we utilized gene expression, microRNA sequencing, whole genome sequencing and clinical data from hundreds of patients from different datasets. Using these data and a novel microRNA-gene association approach we introduce, we have identified unique microRNAs and their associated genes. This unique behavior is composed of the ability of the quantifiable association of the microRNA and the gene expression levels, which we show stratify patients into clinical subgroups of high statistical significance. Importantly, this stratification goes unobserved by other methods and is not affiliated by other subsets or phenotypes within the data. To investigate the robustness of the introduced approach, we demonstrate, in unrelated datasets, robustness of findings. Among the set of identified microRNA-gene associations, we closely study the example of MAF and hsa-miR-330-3p, and show how their co-behavior stratifies patients into prognosis clinical groups and how whole genome sequences tells us more about a specific genomic variation as a possible basis for patient variances. We argue that these identified associations may indicate previously unexplored specific disease control mechanisms and may be used as basis for further study and for possible therapeutic intervention.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Mice overexpressing the longevity protein SIRT6 or deficient for the liver’s most prevalent microRNA miR-122 display a similar set of phenotypes, including improved lipid profile and protection ...against damage linked to obesity. Here, we show that miR-122 and SIRT6 negatively regulate each other’s expression. SIRT6 downregulates miR-122 by deacetylating H3K56 in the promoter region. MiR-122 binds to three sites on the SIRT6 3′ UTR and reduces its levels. The interplay between SIRT6 and miR-122 is manifested in two physiologically relevant ways in the liver. First, they oppositely regulate a similar set of metabolic genes and fatty acid β-oxidation. Second, in hepatocellular carcinoma patients, loss of a negative correlation between SIRT6 and miR-122 expression is significantly associated with better prognosis. These findings show that SIRT6 and miR-122 negatively regulate each other to control various aspects of liver physiology and SIRT6-miR-122 correlation may serve as a biomarker for hepatocarcinoma prognosis.
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•SIRT6 and miR-122 negatively regulate each other•MiR-122 differentially represses SIRT6 depending on its 3′ UTR binding site number•SIRT6 and miR-122 co-regulate fatty acid beta oxidation•Loss of this SIRT6-miR-122 relationship correlates with HCC prognosis
Elhanati et al. find that SIRT6 and miR-122 negatively regulate each other. The interplay between them is linked to regulation of a shared set of metabolic genes and fatty acid β-oxidation and may present a biomarker for hepatocarcinoma prognosis.
Paclitaxel, the most commonly used form of chemotherapy, is utilized in curative protocols in different types of cancer. The response to treatment differs among patients. Biological interpretation of ...a mechanism to explain this personalized response is still unavailable. Since paclitaxel is known to target BCL2 and TUBB1, we used pan-cancer genomic data from hundreds of patients to show that a single-nucleotide variant in the BCL2 sequence can predict a patient's response to paclitaxel. Here, we show a connection between this BCL2 genomic variant, its transcript structure, and protein abundance. We demonstrate these findings in silico, in vitro, in formalin-fixed paraffin-embedded (FFPE) tissue, and in patient lymphocytes. We show that tumors with the specific variant are more resistant to paclitaxel. We also show that tumor and normal cells with the variant express higher levels of BCL2 protein, a phenomenon that we validated in an independent cohort of patients. Our results indicate BCL2 sequence variations as determinants of chemotherapy resistance. The knowledge of individual BCL2 genomic sequences prior to the choice of chemotherapy may improve patient survival. The current work also demonstrates the benefit of community-wide, integrative omics data sources combined with in-lab experimentation and validation sets.
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