3773 results for "*oma"

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• Intellance-2: omics data on recurrent glioblastoma patients participating in the Intellance-2 clinical trial, prior to treatment.

  This study contains omics data from patients from the Intellance-2 clinical trial, in which effectiveness of ABT414 in EGFR amplified recurrent glioblastoma patients was tested. Patients were randomly assigned to one of three arms: (1) standard of care treatement (TMZ or CCNU), (2) Only ABT414 and (3) ABT414 + (TMZ|CCNU)

  Study EGAS00001005437

• Xenograft_Sequencing

  Sequencing of mouse/human carcinoma xenograft samples.

  Study EGAS00001000140

• Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Study EGAS00001006935

• Exome sequencing of familial high-grade serous ovarian carcinoma reveals heterogeneity for rare candidate susceptibility genes

  High-grade serous ovarian carcinoma (HGSOC) has a significant hereditary component, approximately half of which cannot be explained by known genes. To discover genes, we analyse germline exome sequencing data from 516 BRCA1/2-negative women with HGSOC, focusing on genes enriched with rare, protein-coding loss-of-function (LoF) variants. Overall, there is a significant enrichment of rare protein-coding LoF variants in the cases (p < 0.0001, chi-squared test). Only thirty-four (6.6%) have a pathogenic variant in a known or proposed predisposition gene. Few genes have LoF mutations in more than four individuals and the majority are detected in one individual only. Forty-three highly-ranked genes are identified with three or more LoF variants that are enriched by three-fold or more compared to GnomAD. These genes represent diverse functional pathways with relatively few involved in DNA repair, suggesting that much of the remaining heritability is explained by previously under-explored genes and pathways.

  Study EGAS00001004235

• Copy-number signatures and mutational processes in ovarian carcinoma

  This study contains the data underlying our approach for copy-number signature identification in high-grade serous ovarian cancer. The samples studied are part of the BriTROC-1 consortium, a national study into relapsed high-grade serous ovarian cancer. The dataset consists of shallow-whole genome sequencing of 300 samples from 143 patients with match tagged-amplicon sequencing of TP53. The study also contains deeper whole-genome sequencing of 48 cases.

  Study EGAS00001002557

• Exploring high-throughput drug sensitivity testing in neuroblastoma cell lines and patient-derived tumor organoids in the era of precision medicine

  Despite druggable events in 80% of neuroblastoma patients within the Princess Máxima Center precision medicine program 'iTHER', clinical uptake of treatment recommendations has been low, and the clinical impact for individual patients remains hard to predict. This stresses the need for a method integrating genomics and transcriptomics with functional approaches into therapeutic decision making. We aimed to launch an online repository integrating genomics and transcriptomics with high-throughput drug screening (HTS) of nineteen commonly used neuroblastoma cell lines and fourteen generated neuroblastoma patient-derived organoids (NBL-PDOs) to improve identification of molecularly matched therapies and support clinical uptake. Cell lines, NBL-PDOs and their parental tumors were characterized utilizing (lc)WGS, WES and RNAseq. Cells were exposed to a ~200 compound library, and viability was assessed using CellTiterGlo or MTT. Molecular and HTS results were transferred to the R2 platform (http://r2platform.com/pmc_nb_drugs/), in which a comprehensive suite of visualizations and analysis options were implemented. As a result, a powerful reference set of cell lines is available, reflecting distinct known pharmacologic vulnerabilities, including resistance of TP53-inactivated lines to MDM2 inhibitor idasanutlin; ALK-inhibitor sensitivity in ALK-activated lines, and sensitivity of an ATM-deleted cell line to PARP- and CHEK1-inhibitors. Novel established NBL-PDOs retained molecular features of their parental tumor and again reflected established drug sensitivities. However, HTS also identified additional therapeutic vulnerabilities in vitro, such as a striking correlation between a positive mesenchymal signature and sensitivity to BCL2-inhibitor venetoclax. Finally, we explored personalized drug sensitivities within iTHER, demonstrating HTS can support genomic and transcriptomic results, thereby strengthening the rationale for clinical uptake. Furthermore, in vitro insensitivity may avoid ineffective treatments. Lastly, novel treatment options may be identified, as indicated by sensitivity to ponatinib correlating with overexpression of RET or KIT. In conclusion, we established a dynamic publicly available dataset with detailed genomic, transcriptomic, and pharmacological annotation of classical neuroblastoma cell lines as well as NBL-PDOs, representing the heterogeneous landscape of neuroblastoma. We anticipate that in vitro drug screening will be complementary to genomic-guided precision medicine by supporting clinical decision making, thereby improving prognosis for all neuroblastoma patients in the future.

  Study EGAS00001007160

• OAC WGS

  Please see our related publication, 'Molecular profiling to predict immunochemotherapy outcomes in esophageal adenocarcinoma'

  Study EGAS00001006470

• Monocyte Spike-in RNASeq

  Please see our related publication, 'Tumor monocyte content predicts immunochemotherapy outcomes in esophageal adenocarcinoma'.

  Study EGAS00001007197

• Spatiotemporal genomic architecture informs precision oncology in glioblsatoma

  We characterized genomic and expression profiles across 127 multi-sector or longitudinal specimens from 52 glioma patients. We showed that, while samples from nearby geographical location shared similar genomic alterations (clonal or subclonal) and expression signatures, multifocal tumors were seeded from individual clones.

  Study EGAS00001001880

• Spatial and temporal genomic evolution in glioblastoma

  Tumor heterogeneity is a challenging barrier to successful targeted therapy in glioblastoma. Identifying the mechanisms that drive cancer cells as they genetically evolve and adapt in response to treatment is a vital goal of modern cancer research. Analysis of sequencing data provides a method for uncovering the mechanisms sustaining tumor heterogeneity and driving evolution. Here, we analyzed genomic profiles of GBM biopsies taken from pre- and post-treatment GBMs (with matched germline controls), to understand 1) the intratumoral clonal compositions of primary GBM and 2) how GBM responds to therapeutic intervention. Our results provide a molecular portrait of GBM recurrence.

  Study EGAS00001001033