4774 results for "*oma"

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• 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

• High Grade Serous Ovarian Carcinomas Originate in the Fallopian Tube

  High-grade serous ovarian carcinoma (HGSOC) is the most frequent type of ovarian cancer and has a poor outcome. It has been proposed that fallopian tube cancers may be precursors of HGSOC but evolutionary evidence for this hypothesis has been limited. To provide insights into the origins of HGSOC, we We performed whole-exome sequence and copy number analyses of laser-capture microdissected fallopian tube lesions (p53 signatures, serous tubal intraepithelial carcinomas (STICs), and fallopian tube carcinomas), ovarian cancers, and metastases from nine patients with HGSOC. The majority of tumor-specific sequence and structural alterations in ovarian cancers were present in STICs, including those affecting TP53, BRCA1, BRCA2 or PTEN genes. An eEvolutionary analyseis revealed that p53 signatures and STICs were are the precursors of ovarian carcinoma which in turn gave rise to metastatic lesionsand identify a. In one patient we identified a second STIC as a metastasis in the fallopian tube opposite from the affected ovary. These analyses revealed a window of seven years between the development of a STIC and the initiation of ovarian carcinomas, with development of metastases following rapidly thereafter. Our results provide insights into the etiology of ovarian cancer and have implications for the prevention, early detection and therapeutic intervention of this disease.

  Study EGAS00001002589

• Oral mucosa organoids as a potential model for personalized therapies

  Organoids were established from both tumor and matched wildtype tissue from patients diagnosed with head and neck squamous cell carcinoma (HNSCC). In order to confirm tumor status and identify oncogenic driver mutations, DNA derived of these organoids was sequenced. After validation of tumor identity, organoids were exposed to a range of (targeted) chemotherapeutics and radiotherapy. Differential responses to therapeutics were subsequently correlated to underlying genetic alterations to see if DNA mutation status could be predictive for responses to therapy.

  Study EGAS00001003628

• Skin Adenocarcinoma Genome Sequencing

  Skin Adenocarcinoma Genome Sequencing

  Study EGAS00001001052

• Genomic analysis of seminomas

  This study looks at the genomic landscape of seminomas, based on exome sequencing data and SNP array data. Eight seminoma tumors and their matched normal DNAs were exome sequenced on Illumina platforms. The same samples were also processed on Affymetrix SNP 6.0 arrays.

  Study EGAS00001000943

• Spatial genomic heterogeneity in multiple myeloma revealed by multi- region sequencing

  The bone-marrow (BM) containing skeletal system is the reservoir of Multiple Myeloma (MM), the malignant counterpart of antibody-secreting plasma cells. To gain insight into its spatial clonal architecture, we performed multi-region whole-exome sequencing of radiology-guided fine-needle aspirates from 51 MM patients. We found spatial genomic heterogeneity in a substantial proportion of cases including bi-allelic inactivation of tumor suppressors and mutations affecting cancer genes. The amount of heterogeneous mutations associated with the size of focal tumor lesions in whole body imaging consistent with focal outgrowth of highly advanced clones. In conclusion, our results support the regional initiation of transformation processes leading to high-risk disease as well as the pre-existence of key driver events in restricted areas. As such, our study does not only provide new insights in the underlying biology of MM progression but also has considerable implications for standard diagnostic approaches in the clinic.

  Study EGAS00001002111

• Targeted sequencing data and shallow whole genome sequencing data of Follicular lymphoma.

  Contain data of 2 studies 1: 82 nodal stage 1 FL cases and 139 stage III/IV cases 2: 44 watch and wait stage III/IV and 46 Immediate treatment stage III/IV targeted sequencing data of 369 genes and 12 translocation regions whole genome shallow sequencing data

  Study EGAS00001005755

• The Precision Medicine in Liver Cancer across an Asia-pacific NETwork (PLANET)

  Hepatocellular carcinoma (HCC) is the 2nd most important cause of cancer deaths in the world. The outcomes of treatment in HCC are poor compared to other common cancers because there are no good systemic therapy drugs. We designed a prospective study that will involve 5 different sites within the established Asia-Pacific Hepatocellular Carcinoma Trials Group to study both the genetics as well as immune profiles of HCC in different ethnicities. In this study, patients will be followed-up and at recurrence the tissues to understand the evolution of disease progression. Here, we presented both the genomic (DNA) and phenotypic (RNA) evolution for the first batch of 56 patients. The detailed findings will be listed in the corresponding publication soon.

  Study EGAS00001003813

• Genomic Analysis of Primary Plasma Cell Leukemia reveals Complex Structural Alterations and High Risk Mutational Patterns

  Primary plasma cell leukemia (pPCL) is a rare and aggressive form of multiple myeloma (MM) that is characterized by circulating plasma cells. Overall survival remains poor despite advances of anti-MM therapy. In an attempt to identify key biological mechanisms that result in the aggressive pPCL phenotype we performed whole exome sequencing of 23 patients with pPCL. For matched non-tumor control for each patient to exclude germline variants we used CD34+ cells from stem cell harvest (n=20) or cells obtained from buccal swabs (n=3). Tumor samples were from bone marrow derived CD138+ cells. Tumor samples were compared to the germline control to identify somatic abnormalities.

  Study EGAS00001003834

• Deciphering Intratumoral Molecular Heterogeneity in Clear Cell Renal Cell Carcinoma with a Radiogenomics Platform

  Intratumoral heterogeneity (ITH) challenges the molecular characterization of clear cell renal cell Carcinoma (ccRCC) with percutaneous biopsies and is a confounding factor in selection of molecular-targeted versus immune-based therapy. Magnetic Resonance (MR) Imaging can noninvasively assess the spatial landscape of the entire tumor. To validate MRI for ITH assessment, we implemented a radiogenomic platform through a systematic imaging based co-localization approach for multi region tissue acquisition from single tumors. We investigated if the spatial changes in imaging can predict the molecular changes using transcriptome and histopathological correlatives. Our study confirmed imaging heterogeneity as a predictor of molecular heterogeneity in ccRCC.

  Study EGAS00001003846