485 results for "cancer rna-seq"

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• Somatic Mutation Profile by Next Generation Sequencing in HER2+ Breast Cancer

  The HER pathway is the driving force behind 30% of human breast cancers. It is important to understand how targeted therapies block different cellular pathways, and mechanisms of escape from this blockage. Therapies directed at HER2 establish a successful treatment paradigm, but de novo and acquired resistance exist. The HER signaling system is a complex network with four receptors and eleven ligands, a phosphorylation signaling cascade, and many transcription factors, all complicated by both positive and negative feedback circuits. Analysis of genomes, exomes and transcriptomes by next generation sequencing is aimed at uncovering the genetic factors responsible for patient responses to HER2-directed therapies. We are sequencing HER2-overexpressing cancers, in order to identify potential somatic changes that may better select patients who will benefit from therapy, to determine new targets that may overcome resistance, and to improve outcomes with known current HER2-targeted therapies. Whole exome capture sequencing will determine somatic mutation profiles in HER2-overexpressing tumors, to comprehensively characterize the somatic alterations, with the goal of identifying those patients most likely to respond, as well as discovering new targets that may overcome resistance to HER2-directed therapy. We augment the whole exome data with RNA-seq data to determine expression levels of somatic mutations we discover.

  Study phs000770

• An oncogenic enhancer-rearrangement causes concomitant deregulation of EVI1 and GATA2 in leukemia. Targeted resequencing of chromosomal regions centered on 3q21 and 3q26 in conjunction with RNA-Seq from Acute Myeloid Leukemia patients.

  Chromosomal rearrangements without gene-fusions have been implicated in leukemogenesis by causing deregulation of proto-oncogenes via relocation of cryptic regulatory DNA elements. AML with inv(3)/t(3;3) is associated with aberrant expression of the stem-cell regulator EVI1. Applying functional genomics and genome-engineering, we demonstrate that both 3q-rearrangements reposition a distal GATA2 enhancer to ectopically activate EVI1 and simultaneously confer GATA2 functional haploinsufficiency, previously identified as the cause of sporadic familial AML/MDS and MonoMac/Emberger syndromes. Genomic excision of the ectopic enhancer restored EVI1 silencing and led to growth inhibition and differentiation of AML cells, which could be replicated by pharmacologic BET-inhibition. Our data show that structural rearrangements involving chromosomal repositioning of enhancers can cause deregulation of two unrelated distal genes, with cancer as the outcome.

  Study EGAS00001000669

• Integrated single-cell profiling dissects cell-state-specific enhancer landscapes of human tumor infiltrating T cells.

  Despite extensive studies on the chromatin landscape of exhausted T cells, the transcriptional wiring underlying functional and dysfunctional states of human tumor infiltrating lymphocytes (TILs) is incompletely understood. Here, we identify tissue-specific and general gene-regulatory landscapes in the wide breadth of CD8+ TIL functional states covering four cancer entities using single-cell chromatin profiling. We map enhancer-promoter interactions in human TILs by integrating single-cell chromatin accessibility with single-cell RNA-seq data from tumor entity-matching samples and prioritize key elements by super enhancer analysis. Our analysis reveals a human core chromatin trajectory to TIL dysfunction and identifies key enhancers, transcriptional regulators, and deregulated target genes involved in this process. Finally, we validate enhancer regulation at loci encoding PD1, TCF1, and TIM3 by targeting non-coding regulatory elements with potent CRISPR activators and repressors. In summary, our study advances the understanding of molecular regulation of TIL (dys-)function and provides a framework for modulating immunotherapeutic relevant TIL genes via their enhancers.

  Dataset EGAD00001008662

• Genetic Aberrations and Subclonal Structure Impact Chronic Lymphocytic Leukemia

  Large-scale whole-exome sequencing (WES) of primary tumor samples enables the unbiased discovery of recurrent putative driver events and patterns of clonal evolution. We report the identification of 44 recurrently mutated genes and 11 recurrent CNVs through the WES of 538 chronic lymphocytic leukemia (CLL) and matched germline DNAs. These include previously unrecognized cancer drivers (e.g., RPS15, IKZF3), and collectively identify nuclear export, MYC activity and MAPK signaling as central pathways affected by somatic mutation in CLL. A clonality analysis of this large dataset further enabled the reconstruction of temporal relationships between these driver events. Several drivers were associated with shorter progression-free survival (PFS) in 280 samples that were collected prior to uniform treatment with front line chemo-immunotherapy, with mature follow up of greater than 10 years. Direct comparison between matched pretreatment and relapse CLL from 59 samples demonstrated marked clonal evolution occurring in more than 95% of these patients. Distinct patterns of clonal evolution in relationship to specific gene alteration were observed, suggesting a hierarchy of fitness amongst mutations. Thus, large WES datasets of clinically informative samples enable the discovery of novel driver genes as well as the network of relationships between the drivers and their impact on disease relapse and clinical outcome.Additionally, we performed RNA-seq for 268 CLL samples (including 26 follow-up samples) and used them to identify expression subtypes of CLL. RRBS for 30 of these samples was also generated. In an integrative analysis of genetic, transcriptomic, and epigenetic data, incorporating known and newly identified subtypes of CLL, we built new models to improve patient prognostication.

  Study phs000922

• Super enhancers define regulatory subtypes and cell identity in neuroblastoma - RNA-seq

  Half of the children diagnosed with neuroblastoma have high-risk disease, disproportionately contributing to overall childhood cancer-related deaths. In addition to recurrent gene mutations, there is increasing evidence supporting the role of epigenetic deregulation in disease pathogenesis. Yet, comprehensive cis-regulatory network descriptions from neuroblastoma tissues are lacking. Here, using genome-wide H3K27ac profiles across 60 neuroblastomas, covering the different clinical and molecular subtypes, we identified four major super enhancer-driven epigenetic subtypes and their underlying master regulatory networks. Three of these subtypes recapitulated known clinical groups, namely MYCN amplified, MYCN non-amplified high-risk and MYCN non-amplified low-risk neuroblastomas. The fourth subtype, exhibiting mesenchymal characteristics, shared features with multipotent Schwann cell precursors, was induced by RAS activation and enriched in relapsed disease. Notably, CCND1, a disease essential gene, was regulated by both mesenchymal and adrenergic regulatory networks converging on distinct super-enhancer modules. Together, this reveals subtype-specific super-enhancer regulation in neuroblastoma.

  Study EGAS00001004552

• Molecular risk stratification in patients with T1 colorectal cancer_WES

  The introduction of bowel cancer screening has led to a significant increase in the proportion of patients being diagnosed with asymptomatic, early-stage colorectal cancer (CRC). Although the majority of these patients are successfully treated with surgery alone, a small proportion of patients have 'born-to-be-bad' aggressive lesions with early dissemination leading to distant metastases. Current standard of care histological assessment is unable to distinguish between these aggressive versus non-aggressive early lesions which is essential to provide appropriate clinical management decisions. This study aims to carry out molecular and histological profiling of approximately 300 T1 CRCs in order to develop a molecular stratifier based on the risk of relapse in early-invasive CRC. This novel T1 cohort will represent the world's largest molecularly characterised T1 cohort of samples, with digital pathology assessment alongside whole exome sequencing, copy number variation analysis and 3' RNA-seq. This data will be used to generate a robust panel of molecular and/or histological markers applicable to formalin-fixed paraffin embedded (FFPE) archival tissue which discriminates between T1 lesions based on risk of relapse, which will ultimately be used to inform clinical management of CRC at the earliest stages of the disease.

  Dataset EGAD00001010890

• Single cell RNAseq of stenotic, inflamed and non-inflamed transmural lesions from patients with Crohn's disease

  This dataset contains a gene-cell matrix derived from single-cell RNA sequencing (scRNA-seq) data of ileal tissue from Crohn's disease (CD) patients and colorectal cancer (CRC) patients. It includes: Crohn's Disease Patients: A trio of transmural lesions (stenotic, inflamed, and non-inflamed) from each patient. Colorectal Cancer Patients: Unaffected ileal tissue used as external non-inflamed control. Cell Level Metadata: The dataset includes relevant cell-level metadata such as cell type annotations used in the study. Experimental Details: Platform: 10x Genomics Chromium Single Cell 3' GEX Sequencing: Illumina NovaSeq Processing: Data processed with Cell Ranger software. Resulting count matrices were merged for downstream analysis, including integration and dimensionality reduction. Dataset Composition: Crohn's Disease Patients: 10 patients with 3 samples each (non-inflamed, inflamed, stenotic), totaling 30 samples. Colorectal Cancer Patients: 5 patients with 1 sample each of unaffected tissue, totaling 5 samples. Data Provided: Merged Raw Count Matrix: The final merged raw count matrix used for downstream analysis. Cell Metadata File: Contains details of sample, tissue, and patient for each cell in the count matrix. Barcodes File: Indicate each cell barcode which also encodes the sample, tissue, and patient details for each cell. CD.S_Inf: Stenotic Corhn's disease inflamed samples CD.S_Sten: Stenotic CD patient stenosis sample CD.S_Prox: Stenotic CD Patient - proximal non-inflamed sample CC.C_Prox: CRC Patient proximal unaffected sample eg: A barcode 'CC.C_1_Prox_AAGTCGTAGACCCTTA' indicates CRC Patient unaffected proximal sampe from CRC Patient no.1 and the nucleic acid sequence indicate a unique cell from this sample. Total Samples: Crohn's Disease (CD) Patients: 30 samples Colorectal Cancer (CRC) Patients: 5 samples Patient_no Sample Sample_type 1 CC.C_1 CC.C_1_Prox CC.C_Prox 2 CD.S_1 CD.S_1_Prox CD.S_Prox 3 CD.S_1 CD.S_1_Infl CD.S_Infl 4 CD.S_1 CD.S_1_Sten CD.S_Sten 5 CC.C_2 CC.C_2_Prox CC.C_Prox 6 CD.S_2 CD.S_2_Prox CD.S_Prox 7 CD.S_2 CD.S_2_Infl CD.S_Infl 8 CD.S_2 CD.S_2_Sten CD.S_Sten 9 CC.C_3 CC.C_3_Prox CC.C_Prox 10 CC.C_4 CC.C_4_Prox CC.C_Prox 11 CD.S_3 CD.S_3_Prox CD.S_Prox 12 CD.S_3 CD.S_3_Infl CD.S_Infl 13 CD.S_3 CD.S_3_Sten CD.S_Sten 14 CD.S_4 CD.S_4_Prox CD.S_Prox 15 CD.S_4 CD.S_4_Infl CD.S_Infl 16 CD.S_4 CD.S_4_Sten CD.S_Sten 17 CC.C_5 CC.C_5_Prox CC.C_Prox 18 CD.S_5 CD.S_5_Prox CD.S_Prox 19 CD.S_5 CD.S_5_Infl CD.S_Infl 20 CD.S_5 CD.S_5_Sten CD.S_Sten 21 CD.S_6 CD.S_6_Prox CD.S_Prox 22 CD.S_6 CD.S_6_Infl CD.S_Infl 23 CD.S_6 CD.S_6_Sten CD.S_Sten 24 CD.S_7 CD.S_7_Prox CD.S_Prox 25 CD.S_7 CD.S_7_Infl CD.S_Infl 26 CD.S_7 CD.S_7_Sten CD.S_Sten 27 CD.S_8 CD.S_8_Prox CD.S_Prox 28 CD.S_8 CD.S_8_Infl CD.S_Infl 29 CD.S_8 CD.S_8_Sten CD.S_Sten 30 CD.S_9 CD.S_9_Prox CD.S_Prox 31 CD.S_9 CD.S_9_Infl CD.S_Infl 32 CD.S_9 CD.S_9_Sten CD.S_Sten 33 CD.S_10 CD.S_10_Prox CD.S_Prox 34 CD.S_10 CD.S_10_Infl CD.S_Infl 35 CD.S_10 CD.S_10_Sten CD.S_Sten

  Dataset EGAD50000000559

• Long-term organoid culture of a small intestinal neuroendocrine tumor rna-seq

  Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are rare and highly heterogeneous neoplasms whose incidence has markedly increased over the last decades. A grading system based on the tumor cells' proliferation index predicts high-risk for G3 NETs. However, low-to-intermediate grade (G1/G2) NETs have an unpredictable clinical course that varies from indolent to highly malignant. Cultures of human cancer cells enable to perform functional perturbation analyses that are instrumental to enhance our understanding of cancer biology. To date, no tractable and reliable long-term culture of G1/G2 NET has been reported to permit disease modeling and pharmacological screens. Here, we report of the first long-term culture of a G2 metastatic small intestinal NET that preserves the main genetic drivers of the tumor and retains expression patterns of the endocrine cell lineage. Replicating the tissue, this long-term culture showed a low proliferation index, and yet it could be propagated continuously without dramatic changes in the karyotype. The model was readily available for pharmacological screens using targeted agents and as expected, showed low tumorigenic capacity in vivo. Overall, this is the first long-term culture of NETs to faithfully recapitulate many aspects of the original neuroendocrine tumor.

  Study EGAS00001007108

• WXS and RNA-seq for 22 patients treated with radiation + immunotherapy

  Over 500 active clinical trials are investigating combination radiation (RT) and immune checkpoint blockade (ICB) as a cancer treatment; however, the majority of trials have found no positive interaction. We performed a comprehensive molecular analysis of a randomized phase I clinical trial of patients with non-small cell lung cancer (NSCLC) treated with concurrent or sequential ablative RT and ICB. Concurrent treatment was superior to sequential treatment in augmenting local and distant tumor responses and improving overall survival in a subset of patients with highly aneuploid tumors, but not in those with less aneuploid tumors. Our analysis suggested that concurrent treatment eliminated immunologically cold aneuploid tumors better than sequential treatment and improved patient outcomes. In addition, we report that RT alone decreased intratumoral cytotoxic effector T cell and adaptive immune gene expression signatures, in contrast to upregulation of key immune pathways after concurrent administration of RT and ICB. Our findings distinguish the differential genomic and transcriptomic effects of RT versus RT and ICB and challenge the prevailing paradigm that local ablative RT beneficially stimulates the immune response. We propose the use of tumor aneuploidy as a novel biomarker and therapeutic target in personalizing treatment approaches for patients with NSCLC treated with RT and ICB.

  Study EGAS00001006212

• Integrative analysis of exome-seq, RNA-seq, ATAC-seq (bulk and single-cell), and Hi-C data generated from 3-D spatially mapped samples acquired during surgical resection from 10 patients diagnosed with IDH-WT glioblastoma

  Glioblastoma (GBM), the most common primary brain cancer in adults, remains incurable with no targeted therapies approved despite decades of investigation into its molecular landscape. Treatment failure is attributed to intratumoral heterogeneity in the GBM genome and epigenome, which foster tumor evolution and selection of resistant clones. However, tumor evolution and intratumoral heterogeneity remain poorly understood on the level of the whole tumor as most studies are based on single samples per patient and lack spatial context. Here, we have used 3-D neuronavigation during surgical resection for 10 primary IDH-WT GBM patients to collect 102 samples representing maximal tumor diversity, each mapped by 3-D spatial coordinates. We have applied a strategic set of genomic and epigenomic assays spanning multiple levels of resolution to discover, orthogonally validate, and functionally assess drivers of tumor evolution and intratumoral heterogeneity. These include extrachromosomal DNA amplifications, chromothripsis events, inversions, and translocations that disrupt both the GBM genome and epigenome while generating fusion transcripts and opportunities for therapeutic intervention. We define epigenomic programs that contribute to GBM evolution and intratumoral heterogeneity, revealing their 3-D spatial patterning within whole tumors and their cell type(s) of origin in single-cell data from the same tumor samples. Notably, we distinguish neuronal, glial, and immune programs aberrantly active in tumor cells from their counterparts in normal cells and discover NEUROD1, JUN/FOS, and NF1 transcription factors as key drivers of GBM evolution and growth. Collectively, these data provide unprecedented insight into GBM evolution and intratumoral heterogeneity from single-cell to whole-tumor resolution, redefining current understanding and providing a rich resource of targets for therapeutic investigation.

  Study EGAS00001006785