5032 results for "*oma"

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• Rare SNPs in receptor tyrosine kinases are negative outcome predictors in multiple myeloma

  Multiple myeloma (MM) is a plasma cell disorder that is characterized by a great genetic heterogeneity. Recent next generation sequencing studies revealed an accumulation of tumor-associated mutations in receptor tyrosine kinases (RTKs) which may also contribute to the activation of survival pathways in MM. To investigate the clinical role of RTK-mutations in MM, we deep-sequenced the coding DNA-sequence of EGFR, EPHA2, ERBB3, IGF1R, NTRK1 and NTRK2 which were previously found to be mutated in MM, in 75 uniformly treated MM patients of the "Deutsche Studiengruppe Multiples Myelom". Subsequently, we correlated the detected mutations with common cytogenetic alterations and clinical parameters. We identified 11 novel non-synonymous SNVs or rare patient-specific SNPs, not listed in the SNP databases 1000 genomes and dbSNP, in 10 primary MM cases. The mutations predominantly affected the tyrosine-kinase and ligand-binding domains and no correlation with cytogenetic parameters was found. Interestingly, however, patients with RTK-mutations, specifically those with rare patient-specific SNPs, showed a significant lower overall, event-free and progression-free survival. This indicates that RTK SNVs and rare patient-specific RTK SNPs are of prognostic relevance and suggests that MM patients with RTK-mutations could potentially profit from treatment with RTK-inhibitors.

  Study EGAS00001001665

• Clonal_expansion_of_mutated_cell_population_in_bladder_urothelium_

  1cm biospies of from patients undergoing bladder cystectomy will be collected. The underlying muscle and stroma will be removed and the remaining epithelia dissected into small sequential areas which will be sent for ultra-deep exome sequencing using a panel of known cancer and viral genes. Sequence analysis using similar methods to Martincorena I et al (Science 2015, 348:880) will provide an idea of the somatic mutational landscape in these patient samples. Individual patient muscle samples will also be sequenced as a reference.

  Study EGAS00001001687

• Automated system for scoring hematoxylin and eosin-stained ovarian cancer sections by identifying single cells uncovered that stromal cell ratio is a significant predictor for overall survival and progression-free survival.

  Concerted efforts in genomic studies have revealed profound insights in prognostic ovarian cancer subtypes. On the other hand, abundant histology slides have been generated to date, yet their uses remain very limited and largely qualitative. Our goal is to develop automated histology analysis as an alternative subtyping technology for ovarian cancer that is cost-efficient and do not rely on DNA quality. We develop an automated system for scoring hematoxylin and eosin-stained (H&E) primary tumour sections of 91 late-stage ovarian cancer to identify single cells including cancer and stromal cells. We demonstrated high accuracy of our system based on expert pathologists’ scores (cancer=97.1%, stromal=89.1%) as well as compared to immunohistochemistry scoring (correlation=0.87). Quantitative stromal cell ratio is significantly associated with poor overall survival after controlling for clinical parameters including debulking status and age (multivariate analysis p=0.0021, HR=2.54, CI=1.40-4.60) and progression-free survival (multivariate analysis p=0.022, HR=1.75, CI=1.09–2.82). We demonstrate how automated image analysis enables objective quantification of microenvironmental composition of ovarian tumours. Our analysis reveals a strong effect of the tumour microenvironment on ovarian cancer progression and highlights the potential of therapeutic interventions that target the stromal compartment or cancer-stroma signalling in the stroma-high, late-stage ovarian cancer subset.

  Study EGAS00001001694

• The ITCC-P4 PDX platform of pediatric cancers for preclinical testing

  Cancer is the leading cause of disease-related deaths among children in high-income countries. Tumor heterogeneity and lack of mechanism-of-action-based therapeutic options are key challenges to overcome in order to improve pediatric cancer patients’ survival. Here, we report the EU-IMI-2 funded public-private partnership “ITCC-Pediatric Preclinical Proof-of-Concept Platform” (ITCC-P4), which has built a large repertoire of patient-derived xenograft (PDX) models, representing all major solid pediatric cancer types, for in vivo drug testing. Three-hundred-fifty-three PDX models from diagnostic and relapsed pediatric cancers have been established and molecularly characterized, together with matched germline/tumor samples. As proof-of-concept, we present in vivo drug screening data in neuroblastoma and rhabdomyosarcoma models. PDX data, accessible at http://r2platform.com/itcc-p4, allow the selection of models based on oncogenic drivers and/or potential biomarkers for preclinical testing. Operated by a non-profit entity (www.itccp4.com), this sustainable platform aids academic and industrial researchers in developing and prioritizing innovative therapies for pediatric cancer.

  Study EGAS00001008330

• Targeted-capture sequencing (bam files) of 81 samples of myxofibrosarcoma and 44 matched pairs

  Myxofibrosarcoma (MFS) is a rare subtype of sarcomas in the elderly, whose genetic basis is poorly understood. To elucidate it, the Targeted-capture sequencing was performed.

  Study EGAS00001005443

• Linking genes, genomic instability and molecular subgroups in medulloblastoma

  Brain tumors are the second most common pediatric cancer and carry the highest mortality rates in this age group. Medulloblastoma is the most frequent malignant brain tumor of childhood. Recent studies indicate that medulloblastoma comprises at least four sub-entities (SHH-signaling, WNT-signaling, Group-C, Group-D) that differ in molecular alterations, cell of origin, clinicopathological features and outcome. Further characterization of the entire spectrum of genomic alterations underlying the formation of these distinct groups is urgently needed to identify diagnostic and prognostic biomarkers for clinical management and uncover novel therapeutic targets.

  Study EGAS00001000085

• Pharmacogenomic landscape of patient-derived cells informs precision oncology therapy

  Outcomes of anticancer therapy vary dramatically among patients, which may be caused by the specific molecular alterations in each patient’s tumor. Precision oncology aims to apply optimal therapies for each tumor based on its molecular characteristics. We have established a resource reporting the genomic and transcriptomic profiles of 462 patient tumor-derived cells (PDCs) across 14 cancer types, together with responses to 60 targeted agents. Compared with long-term cultured cancer cell lines, PDCs better recapitulate the molecular profiles of the original tumors. Among other unreported associations, we identify molecular factors inducing resistance to EGFR inhibitors in glioblastoma, and we suggest repurposing ibrutinib (currently used in hematological malignancies) for EGFR-specific therapy in gliomas. Lastly, using a retrospective clinical study, we find that PDC-derived sensitivities can be used to predict patient responses.

  Study EGAS00001002515

• Somatic_Variation_Angiosarcoma

  Through whole genome sequencing, this study will explore the mutational profiles and signatures within an angiosarcoma tumour from a patient with xeroderma pimentosum. Very little information is known about this tumour type and it has not previously been studied within the context of xerogerma pigmentosum.

  Study EGAS00001002610

• Myeloma_Follow_up_Pilot

  Targeted capture of exonic and intronic regions of interest for the study of genomic alterations in multiple myeloma.

  Study EGAS00001000743

• Mutant KIT as imatinib-sensitive target in metastatic sinonasal carcinoma (H021)

  Sinonasal carcinomas (SNCs) comprise various rare tumor types that are characterized by marked histologic diversity and largely unknown molecular profiles, yet share an overall poor prognosis owing to an aggressive clinical course and frequent late-stage diagnosis. The lack of effective systemic therapies for locally advanced or metastatic SNC poses a major challenge to therapeutic decision making for individual patients. Here, we used whole-exome and transcriptome sequencing to identify a KIT exon 11 mutation (c.1733_1735del, p.578_579del) as actionable target in a patient with metastatic SNC whose tumor, despite all diagnostic efforts, could not be assigned to any known SNC category and was refractory to multimodal therapy. Molecularly guided treatment with imatinib resulted in a dramatic and durable response with remission of nearly all tumor manifestations, indicating a dominant driver function of mutant KIT in this tumor. This observation highlights the potential of unbiased genomic profiling for uncovering the vulnerabilities of individual malignancies, particularly in rare and unclassifiable tumors, and underscores that KIT exon 11 mutations represent tractable therapeutic targets across different histologies.H021

  Study EGAS00001001845