7188 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

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• Exploration of CNV’s and SNV’s in cancers with well-known genetic rearrangements: Identification of additional genetic changes in rearrangements-driven cancer

  Specific cancers are well known to have specific gene rearrangements. Representative cancer is chronic myeloid leukemia (CML) which is famous for BCR/ABL gene rearrangements. By the way, also genetic rearrangements are not infrequently found in acute leukemia, and those include CBFB/MYH11 rearrangements, PML/RARA rearrangements, AML/ETO rearrangements, and BCR/ABL rearrangements. The situation is same is for lung adenocarcinoma of non-smokers and prostate cancers, and ALK and RET gene rearrangements are recently found. However, not all these rearrangements are sufficient to develop cancer, and it is suggested that some genetic aberrations are required for the development and progression of cancer in addition to these genetic rearrangements. In this study, we have a plan to explore the existence of additional genetic changes including single nucleotide variants (SNV’s) and copy number variations (CNV’s) in cancers with specific genetic rearrangements so as to define additional genetic changes that confer full oncogenic potential to cancer cells. So as to look at SNV’s and small indels, we are going to use whole exome sequencing (WES) data. And as for CNV’s, we are going to use array-CGH data. Also, to check the functionality of these genetic changes, we are going to use whole transcriptome data (WTS). In addition, in samples with whole genome sequencing (WGS ) data, we are going to explore genetic changes in intronic regions also. In fact, we sequenced 10 AML samples which are known to have specific genetic rearrangements. Analysis of these WGS, WES and WTS data are under the way. If we have a chance to access WES, array-CGH and WTS data of other cancer samples with specific genetic rearrangements, we would be able to compare additional genetic changes required for oncogenesis in cancer cells with various genetic rearrangements. We hope this result will enlighten our understanding of cancer genetics further.

  Study EGAS00001000673

• SCANDARE MACARON

  Among gynecological cancers, high-grade serous ovarian cancer has the highest prevalence and more than 75% of patients have advanced stage at diagnosis with a 5-year survival of 40%. When the initial complete surgical removal is not possible (60% of patients), an interval surgery can be considered after three to four cycles of neoadjuvant chemotherapy to reduce the tumor mass. However, in approximately 50% of cases the tumor has little or no response to neoadjuvant chemotherapy. Therefore, identification of potential drug targets, biomarkers and/or pathways whose modulation can help in the prevention, interception, or curing of the disease is essential to address the unmet need. Therefore, MACARON project aims to address these issues through the identification of shared neoantigens arising out of somatic alterations and aberrant transcriptional programs in ovarian cancer DNA/RNA datasets.

  Study EGAS50000000145

• "Distinct immunometabolic signatures in circulating immune cells define disease outcome in acute-on-chronic liver failure"

  We performed single-cell transcriptomics of PBMC’s from healthy (n= 3), acute decompensated (AD) (n= 3) and Acute-on-chronic liver failure (ACLF) patients. Lay Summary: Acute-on-chronic liver failure (ACLF) develops in cirrhotic patients and is characterized by an hyper-inflammatory immune state driving multiple organ failure(s). As a paradox, circulating immune cells also show transcription and metabolic evidence of exhaustion, explaining why these patients are often susceptible to secondary infections. We characterized at a transcriptional level all circulating immune cells of ACLF patiens, and specifically unraveled a distinct recovery and non-recovery ACLF signature within the monocyte population. Moreover, these changes were closely linked to metabolic differences within these cells. The described alterations allowed for a robust prediction of recovery and non-recovery of patients at admission to the hospital.

  Study EGAS50000000391

• MYC Inhibition By Omomyc Causes DNA Damage And Overcomes PARPi Resistance In Breast Cancer.

  This study investigates the role of MYC dysregulation in DNA damage response (DDR) and PARP inhibitor (PARPi) resistance in breast cancer. Using Omomyc, a direct MYC inhibitor, we demonstrate that MYC inhibition shuts down DDR genes in triple-negative breast cancer (TNBC), causing DNA repair defects and inducing DNA damage that synergizes with PARPi treatment. Through patient-derived models and clinical samples from metastatic HR-altered breast cancer patients treated with PARPi, we identify MYC transcriptional activity as a predictive biomarker of PARPi resistance. Digital spatial profiling (DSP) analysis of pre-treatment tumor biopsies reveals that patients with progressive disease have significantly elevated MYC signatures compared to responders. These findings support the therapeutic strategy of combining MYC inhibition with PARPi in PARPi-resistant breast cancers where high MYC activity predicts poor response to therapy.

  Study EGAS50000001347

• Translational analyses from a phase II study of pembrolizumab and epigenetic modification with azacitidine in platinum-resistant epithelial ovarian cancer

  Epigenetic modulators may sensitize platinum-resistant ovarian cancer (PROC) to immune checkpoint inhibition by reprogramming the tumor microenvironment. We report clinical and translational findings from a phase II non-randomized study of pembrolizumab and oral azacytidine in 34 women with PROC (NCT02900560). The effect of combined epigenetic and immunotherapy was evaluated by transcriptomic analyses of serially biopsied tumors. Differential gene expression analyses revealed an upregulation of inflammatory and cytolytic genes and co-inhibitory checkpoints 6 weeks on-therapy. Upregulation of interferon signaling, antigen presentation and immune cell adhesion and migration gene sets was prominent on-therapy, together with an increased density of CD8+ T -cells. Patients with a CA-125 and/or clinical response showed an enrichment of adaptive and conserved immune response gene sets on-therapy.

  Study EGAS50000001165

• Understanding_the_development_of_resident_memory_T_cells__Trm__in_the_human_small_intestine_using_integrative_multiomic_approaches__Adult_RNA

  Animal studies have demonstrated that resident memory T (Trm) cells provide enhanced protective responses to a broad array of tissue-tropic pathogens, thus making Trm cells promising targets for novel vaccination strategies. However, the biological pathways that enable the long-term survival of Trm cells are poorly understood in humans. Here, we will employ a unique human intestinal transplantation setting that allows us to study the retention of persistent T cells in the grafts and the temporal development of resident T-cell populations from recruited recipient T cells. We will integrate high resolution transcriptomics, epigenetics, proteomics and immune repertoire single-cell data from purified intestinal T cells. These single-cell multiomics approaches will uncover the diversity and differentiation of the T cell populations in the human intestine, allowing us to temporally resolve the generation and maintenance of gut resident T cells.

  Study EGAS00001008257

• Functional_genomics_approaches_to_understand_osteoarthritis

  The aim of this work is to apply an integrated systems approach to understand the biological underpinnings of large joint (hip and knee) osteoarthritis which culminates in the need for total joint replacement (TJR). We will obtain diseased and non-diseased cartilage as well as other disease-relevant tissue following TJR, coupled with a blood sample. We will generate genotype data and will characterise the pairs of diseased and non-diseased tissue samples in terms of methylation, transcription (RNASeq) and expression (quantitative proteomics). We will apply integrative approaches to combine information across the –omics levels to characterise genes, pathways, and networks that underlie osteoarthritis progression. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002255

• Transcriptional_Consequences_of_Copy_Number_Changes_MY_HDBR_200531

  Every normal human cell has two copies of each non-sex chromosome. The gain or loss of an extra copy underlies many health conditions, including developmental syndromes and cancer. Ultimately, it is the patterns of genes that are turned on and off that determines which proteins a cell produces and its biological function. Despite the importance of changes in chromosome number (known as aneuploidy or copy number changes), little is known about how these changes impact patterns of gene expression. This project will aim to fill this gap by creating an atlas of patterns of gene expression in cells from developmental tissues with aberrant numbers of chromosomes. These gene expression profiles will then be compared to the patterns of expression in the same cells with two copies of each chromosome, directly measuring the precise, cell specific, consequences of copy number change on gene expression.

  Study EGAS00001005100

• Profiling_molecular_heterogeneity_in_human_primary_microglia

  In the brain the cells that control inflammation are called a type of white blood cell called microglia. Microglia are located throughout the brain and spinal cord and account for 10–15% of all cells found within the brain. As the resident white blood cells, they are the main active immune defence in the central nervous system (CNS). Microglia are part of an important class of cells known as macrophages that have two main states: M1 and M2. M1 cells are pro- inflammatory, leading to more inflammation, while M2 are anti-inflammatory, and drive wound healing. In this study, we will collect primary microglia from surgical biospies of 100 individuals. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002494

• Epithelial, fibroblast, myeloid, T cell, primary prostate cancer

  The collection and use of tissue for this study had Melbourne Health institutional review board approval and patients provided written informed consent (Melbourne Health Local Project Number: 2016.087). Following the prostatectomy of 13 patients, ranging from 52 to 78 years of age and from CAPRA-S risk score of 0 (attributed to benign tissue samples, harvested from a site far from a low grade, low volume cancer) to 7 (Supplementary file 2), a four millimeter tissue core was collected from the prostate tumour site, conditional to histopathological verification66,67. If not otherwise specified, all procedures were carried out at 4 °C. Tissue blocks were washed in Phosphate-buffered saline (PBS) solution for 2 minutes and minced for 2 minutes with a scalpel. Homogenised tissue was added to a solution (total volume of 7 ml) composed by of 1 mg/ml collagenase IV (Worthington Biochemical Corp, USA), 0.02 mg/ml DNase 1 (New England Biolabs, USA), 0.2 mg/ml dispase (Merck, USA). The tissue homogenised was serially digested at 37 °C at 180 rpm, through three steps of 5, 10 and 10 minutes of duration, with the final 3 minutes dedicated to sedimentation at 0 rpm. After each digestion step, the supernatant was aspirated and filtered through a 70 μm strainer into a pre-chilled tube, diluting the solution with 15 ml of 2% bovine serum PBS to quench the enzymatic reaction. The resulting cumulative solution was then centrifuged at 1500 rpm for five minutes, with the supernatant collected and the cell pellet resuspended into 1 ml 2% PBS-serum prior to labelling (Fig. S1).

  Dataset EGAD00001004948