4058 results for "*oma"

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• Integrated Genomic, Epigenetic, and Expression Analyses of Ovarian Cancer Cell Lines

  Epithelial ovarian carcinoma of all subtypes has one of the worst outcomes of any human cancer. To improve our understanding of underlying biology and therapeutic possibilities in this disease, we performed whole genome sequencing, methylation, and expression analyses of a comprehensive set of 47 ovarian cancer cell lines representing different histologic tumor subtypes. Given the challenges of genomic analyses in tumors without matched normal samples, we developed novel approaches for detection of somatic alterations and used these to identify sequence, copy number, and rearrangement changes and integrated these with genome-wide epigenetic and expression alterations. Ovarian cancer cell lines had molecular changes in genes involved in cell cycle, PI3K, RAS, BRCA, chromatin regulating, and p53 pathways, and displayed global mutation and methylation changes similar to primary ovarian carcinoma. We identified alterations not previously implicated in ovarian cancer including amplification or overexpression of ASXL1 and H3F3B, deletion or underexpression of CDC73 and members of the TGF beta receptor pathway, including TGFBR2, SMAD3 and SMAD4, in-frame rearrangements of YAP1-MAML2 and IKZF2-ERBB4, and fusions involving MET, NF1, FBXW7 and CCND1. Integrating cell line alterations with dose-response data using three targeted therapies revealed novel molecular dependencies, including increased sensitivity of tumors with PIK3CA and PPP2R1A alterations to PI3K inhibitor GNE-493, those with MYC amplifications to PARP inhibitor BMN673, and SMAD4 alterations to MEK inhibitor MEK162. Genome-wide analyses revealed intrachromosomal rearrangements as an improved measure of sensitivity to PARP inhibition compared to the homologous recombination defect (HRD) score. This study provides a comprehensive resource of molecular information for ovarian cancer cell line models and a pharmacogenomic platform for developing rational cancer therapeutic strategies.

  Study EGAS00001002998

• Summary statistics from genome-wide association study in glioma of 12,488 cases and 18,169 controls.

  Genome-wide association studies (GWAS) have transformed our understanding of glioma susceptibility, but individual studies have had limited power to identify risk loci. We performed a meta-analysis of existing GWAS and two new GWAS, which totaled 12,488 cases and 18,169 controls. We identified five new loci for glioblastoma (GBM) at 1p31.3 (rs12752552; P = 2.04 × 10-9, odds ratio (OR) = 1.22), 11q14.1 (rs11233250; P = 9.95 × 10-10, OR = 1.24), 16p13.3 (rs2562152; P = 1.93 × 10-8, OR = 1.21), 16q12.1 (rs10852606; P = 1.29 × 10-11, OR = 1.18) and 22q13.1 (rs2235573; P = 1.76 × 10-10, OR = 1.15), as well as eight loci for non-GBM tumors at 1q32.1 (rs4252707; P = 3.34 × 10-9, OR = 1.19), 1q44 (rs12076373; P = 2.63 × 10-10, OR = 1.23), 2q33.3 (rs7572263; P = 2.18 × 10-10, OR = 1.20), 3p14.1 (rs11706832; P = 7.66 × 10-9, OR = 1.15), 10q24.33 (rs11598018; P = 3.39 × 10-8, OR = 1.14), 11q21 (rs7107785; P = 3.87 × 10-10, OR = 1.16), 14q12 (rs10131032; P = 5.07 × 10-11, OR = 1.33) and 16p13.3 (rs3751667; P = 2.61 × 10-9, OR = 1.18). These data substantiate that genetic susceptibility to GBM and non-GBM tumors are highly distinct, which likely reflects different etiology.

  Study EGAS00001003372

• Intratumoural Heterogeneity Underlies Distinct Therapy Responses and Treatment Resistance in Glioblastoma

  Glioblastomas are the most common and lethal neoplasms of the central nervous system. Neighbouring glioma cells maintain extreme degrees of genetic and phenotypic variation that forms intratumoural heterogeneity. This genetic diversity allows the most adaptive tumour clones to show treatment resistance and conserve the tumour bulk. We aimed to model this phenomenon and test the effectiveness of several targeted therapeutic interventions to overcome therapy resistance. Heterogenic tumour masses were first deconstructed into single tumour cells, which were expanded independently as single-cell clones. SNP arrays, whole-genome and RNA sequencing, and CpG methylation analysis validated the unique molecular profile of each tumour clone, which displayed distinct pathologic features, including cell morphology, growth rate, and resistance to temozolomide and ionizing radiation. We also identified variable sensitivities to AURK, CDK, and EGFR inhibitors, consistent with the heterogenic molecular alterations that each clone harboured. These targeted therapies effectively eliminated the temozolomide- and/or irradiation-resistant clones and also parental polyclonal cells. Our findings indicate that polyclonal tumours create a dynamic environment that consists of diverse tumour elements and treatment responses. Designing targeted therapies based on a range of molecular profiles can be a more effective strategy to eradicate treatment resistance, recurrence, and metastasis.

  Study EGAS00001003438

• Detecting and tracking circulating tumour DNA copy number profiles during first line chemotherapy in oesophagogastric adenocarcinoma

  DNA somatic copy number aberrations (SCNAs) are key drivers in oesophago-gastric adenocarcinoma (OGA). Whether minimally invasive SCNA analysis of circulating tumour (ct)DNA can predict treatment outcomes and reveal how SCNAs evolve during chemotherapy is unknown. We investigated this by low-coverage whole genome sequencing (lcWGS) of ctDNA from 30 patients with advanced OGA prior to first-line chemotherapy and on progression.

  Study EGAS00001003695

• Clonal architectures predict clinical outcome in clear cell renal cell carcinoma

  We analyze the clonal architectures of ccRCC patients from three different populations, including TCGA, Japanese and Chinese patients. We characterize the mutational signatures across different populations and evolution stages. The TCGA and Japanese data sets were downloaded from published studies and we also generated the whole genome sequencing data for more than 40 Chinese patients.

  Study EGAS00001003447

• Whole genome sequencing of Ewings Sarcoma

  Sarcomas are cancers of the bone and soft tissue often defined by their gene fusions. However, the timing, context, and processes by which these pathogenic fusions arise are unknown. We explored this in Ewing sarcoma, a cancer driven by EWSR1-ETS fusions, with very few cooperating mutations. Combining whole-genome sequencing with enhanced informatics, we found that the EWSR1-ETS fusion arose from striking rearrangement clusters in 42% of cases (52/124). Notably, these were organized in loops that universally contained the fusion at their center, while also weaving up to 18 genes together with it. We found the same pattern of rearrangements in three additional types of sarcoma. From these data, we define a new signature for sarcoma fusions that precedes other somatic changes, in the earliest replicating DNA of the genome. This dramatic, sudden process impinges on many genes – generating multiple coding changes that profoundly affect the transcriptome, with the disease-defining gene fusion at its core. These rearrangement loops emerge in an early ES clone from which both the primary tumor and the lethal relapse emerged, and then evolved in parallel until clinically detected.

  Study EGAS00001003385

• Adenoma to Carcinoma transition in Colorectal Cancer

  Although colorectal carcinoma development is well accepted as a step-wise and sequential process, it is commonly investigated using non-sequential adenoma and carcinoma samples. Here we compared molecular pathologies of the earliest carcinoma stages with those in their adenomatous precursors to unravel common and divergent genetic traits between matched neoplasms with a shared evolutionary history but different contemporary biology.

  Study EGAS00001003468

• Analysis of Multiparametric MR imaging and tumor tissue sampling to identify response and acquired resistance to HIF-2 inhibition in patients with advanced clear cell renal cell carcinoma enrolled in a phase 1, multiple-dose, dose-escalation trial of PT2385, a HIF-2alpha inhibitor

  Study EGAS00001003506

• Growth Hormone (GH) -secreting Pituitary Adenoma

  We profiled the somatic landscape of 21 growth hormone (GH) -secreting pituitary adenomas using somatic copy-number alteration (SCNA), whole-genome sequencing (WGS), bisulfate sequencing, and transcriptome approaches. See details in Valimaki et al. Genetic and epigenetic characterization of growth hormone (GH) - secreting pituitary tumors. Manuscript in preparation, 2019.

  Study EGAS00001003488

• Predicting brain tumor recurrence: development and validation of a DNA-methylation based nomogram in meningioma

  Our work is the first to demonstrate the transformative utility of integrating clinical and molecular factors for use beyond simple classification into the realm of individualized prognostication for any brain tumor. Using our developed and validated tools that are publicly available, clinicians will be able combine clinical and molecular factors to determine an individualized probability of recurrence for patients with meningiomas. This represents a major advance in the field of personalized medicine for neuro-oncology, and the use of this tool can help clinicians overcome one of the most challenging limitations we face when treating patients with meningiomas.

  Study EGAS00001003490

• Genomic stratification and liquid biopsy in a rare adrenocortical carcinoma (ACC) case, with dual lung metastases

  Adrenocortical carcinoma is a rare malignancy with a poor prognosis and few treatment options. Molecular characterization of this cancer remains limited. We present a case of an adrenocortical carcinoma (ACC) in a 37-yr-old female, with dual lung metastases identified 1 yr following commencement of adjuvant mitotane therapy. As standard therapeutic regimens are often unsuccessful in ACC, we undertook a comprehensive genomic study into this case to identify treatment options and monitor disease progress. We performed targeted and whole-genome sequencing of germline, primary tumor, and both metastatic tumors from this patient and monitored recurrence over 2 yr using liquid biopsy for ctDNA and steroid hormone measurements. Sequencing revealed the primary and metastatic tumors were hyperhaploid, with extensive loss of heterozygosity but few structural rearrangements. Loss-of-function mutations were identified in MSH2, TP53, RB1, and PTEN, resulting in tumors with mismatch repair signatures and microsatellite instability. At the cellular level, tumors were populated by mitochondria-rich oncocytes. Longitudinal ctDNA mutation and hormone profiles were unable to detect micrometastatic disease, consistent with clinical indicators of disease remission. The molecular signatures in our ACC case suggested immunotherapy in the event of disease progression; however, the patient remains free of cancer. The extensive molecular analysis presented here could be applied to other rare and/or poorly stratified cancers, to identify novel or repurpose existing therapeutic options, thereby broadly improving diagnoses, treatments, and prognoses.

  Study EGAS00001003497

• Paired whole exome sequence of subcutaneous panniculitis-like T-cell lymphoma.

  Subcutaneous panniculitis-like T-cell lymphoma (SPTCL) is a rare subtype of peripheral T-cell lymphoma affecting younger cases and associated with hemophagocytic lymphohistiocytosis. To clarify molecular pathogenesis of SPTCL, we analyzed paired tumor and germline DNAs from 13 patients by whole exome sequencing.

  Study EGAS00001003282

• Myeloma WGS

  Most patients with multiple myeloma (MM) die from progressive disease after relapse. To advance our understanding of MM evolution mechanisms, we performed whole-genome sequencing of 80 tumour-normal newly diagnosed pairs and 24 matched relapse tumours from the Myeloma XI trial.

  Study EGAS00001004000

• Evolution of GBM through therapy

  Primary glioblastoma (GBM) tumours recur following treatment. This is likely due to intratumour heterogeneity (ITH), which reduces the effectiveness of cancer therapies by enabling therapy-driven tumour evolution: Darwinian selection of genotypically and/or phenotypically distinct cells (subclones) that resist treatment to seed regrowth of an even less treatable recurrence. To investigate this we sequenced a pilot cohort of nine paired primary and locally recurrent GBM tumours, alongside matched blood samples, in order to begin characterising therapy resistant cells and thereby infer the mechanisms by which they evaded treatment. These data were included in the first data release from the Glioma Longitudinal AnalySiS (GLASS) consortium.

  Study EGAS00001003546

• Transcriptional changes in GBM through therapy

  Primary glioblastoma (GBM) tumours recur following therapy, owing to treatment resistance mechanisms in unresectable cells. We have sequenced RNA from paired primary and locally recurrent GBM tumours to begin characterising therapy resistant cells and thereby infer the mechanisms by which they evaded treatment. Exome sequencing data from these samples were included in the first data release from the Glioma Longitudinal AnalySiS (GLASS) consortium

  Study EGAS00001003790

• Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma

  Background: Cancer patients with advanced disease exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates sequencing data with functional assay data to develop patient-specific combination cancer treatments. Methods: Tissue taken from a murine model of alveolar rhabdomyosarcoma was used to perform single agent drug screening and DNA/RNA sequencing experiments; results integrated via our computational modeling approach identified a synergistic personalized two-drug combination. Cells derived from the tumor were allografted into mouse models and used to validate the personalized two-drug combination. Computational modeling of single agent drug screening and RNA sequencing of multiple heterogenous sites from a single patient’s epithelioid sarcoma identified a personalized two-drug combination effective across all tumor regions. The heterogeneity-consensus combination was validated in a xenograft model derived from the patient’s primary tumor. Cell cultures derived from human and canine undifferentiated pleomorphic sarcoma were assayed by drug screen; computational modeling identified a resistance-abrogating two-drug combination common to both cell cultures. This combination was validated in vitro via a cell regrowth assay. Results Our computational modeling approach addresses three major challenges in personalized cancer therapy: synergistic drug combination predictions (validated in vitro and in vivo in a genetically engineered murine cancer model), identification of unifying therapeutic targets to overcome intra-tumor heterogeneity (validated in vivo in a human cancer xenograft), and mitigation of cancer cell resistance and rewiring mechanisms (validated in vitro in a human and canine cancer model). Conclusions These proof-of-concept studies support the use of an integrative functional approach to personalized combination therapy prediction for the population of high-risk cancer patients lacking viable clinical options and without actionable DNA sequencing-based therapy.

  Study EGAS00001003564

• Sequencing data of multiple sarcoma samples for personalized medicine and endotype identification

  Sequencing data derived from multiple patient samples was used to guide multiple patient-specific experiments and identify potential therapeutic options. These diseases are rare and high-risk (undifferentiated pleomorphic sarcoma, rhabdomyosarcoma) and thus have few available validated clinical options. This leaves the population of patients with few options if, and when, standard therapy fails to cure or control disease. An aspect of the personalize therapy design included the identification of broader disease endotypes (a combination of genetic and clinical data describing patient status) to identify subgroups of the individual disease that could better define treatments and could segment patient populations for deeper preclinical research.

  Study EGAS00001003981

• Multi-region exome sequencing of lung adenocarcinoma precursors -1

  To characterize the genomic landscape of invasive lung adenocarcinoma and its precursors; to depict the genomic evolution from preneoplasia of lung to invasive lung adenocarcinoma; to decipher mechanism to drive the tumor progression.

  Study EGAS00001003439

• RNA-sequencing of adult T-cell leukemia/lymphoma samples

  Adult T-cell leukemia/lymphoma (ATL) is a highly aggressive hematological malignancy derived from mature CD4+ T-lymphocytes. In this study, we performed RNA-sequencing (RNA-seq) analysis for ATL samples including 9 primary tumors and 1 ATL cell line to clarify gene expression profiles in this disease.

  Study EGAS00001003575

• A Phase II Trial of High Dose Interleukin-2 and Multi-site Stereotactic Ablative Radiotherapy for Patients with Metastatic Renal Cell Carcinoma

  Immune-based therapies have improved outcomes for metastatic renal cell carcinoma (mRCC) but there is still a significant margin for improvement. Here, we report the results of a phase II trial combining high dose Interleukin-2 (HD-IL-2) with stereotactic ablative body radiotherapy (SAbR) for patients with metastatic renal cell carcinoma.

  Study EGAS00001003605

• Recapitulation of genetic predisposition to medulloblastoma in human neuroepithelial stem cells

  Human neural stem cell cultures provide progenitor cells that are potential cells of origin for brain cancers. However, the extent to which genetic predisposition to tumor formation can be faithfully captured in stem cell lines is uncertain. Here we evaluated neuroepithelial stem (NES) cells, representative of cerebellar progenitors. We transduced NES cells with MYCN, observing medulloblastoma upon orthotopic implantation in mice. Significantly, transcriptomes and patterns of DNA methylation from xenograft tumors were globally more representative of human medulloblastoma compared to a MYCN-driven genetically engineered mouse model. Orthotopic transplantation of NES cells generated from Gorlin syndrome, patients predisposed to medulloblastoma due to germline mutated PTCH1, also generated medulloblastoma. We engineered candidate cooperating mutations in Gorlin NES cells, with mutation of DDX3X or loss of GSE1 both accelerating tumorigenesis. These findings demonstrate that human NES cells provide a potent experimental resource for dissecting genetic causation in medulloblastoma.

  Study EGAS00001003620

• Berlin Neuroblastoma Dataset DAC

  Dac EGAC00001003082

• Berlin Neuroblastoma Dataset DAC

  Dac EGAC00001003112

• Analysis of copy number variation landscape of glioma by shallow coverage whole genome sequencing

  We reported shallow coverage whole genome sequencing (WGS) is an economic method for identification of whole genome somatic copy number variation (SCNV). Combining with a Taqman low density array (TLDA) designed for molecular subtyping of glioma, it enabled classification of glioma into biological entities with different cellular origin and genomic alterations. Further, we also showed shallow-coverage WGS enabled systematic identification of clonal and subclonal SCNV in glioma genomes and the burden and pattern of SCNV can serve as an objective marker of tumor progression and predict risk and relapse.

  Study EGAS00001003690

• ID1 in glioblastoma

  Study EGAS00001003711