5495 results for "*oma"

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• Targeting vulnerabilities in IDH mutant tumours: The model matters WES study

  Introduction: Synthetic lethal interactions with IDH1 and IDH2 (IDH) mutations were identified in non-endogenous IDH mutant (IDHmut) AML and glioma models, but are absent in endogenous IDHmut chondrosarcoma cell lines. The translation into successful clinical applications has remained challenging, implying artificially created models do not fully recapitulate endogenous IDHmut tumour biology. The aim of this study was to elucidate if the model system is indeed an important factor to consider when studying therapeutic vulnerabilities in IDHmut tumours. Methods: Vector-based and CRISPR-Cas9 approaches were used to introduce or revert the IDH1 mutation in chondrosarcoma cell lines. These isogenic cell line pairs were used to examine the presence of known therapeutic vulnerabilities and their underlying biological mechanisms. Results: Vector-based IDHmut chondrosarcoma models showed the previously reported synthetic lethal interactions, but these treatment sensitivities were absent in the CRISPR-edited models. Interestingly, not all vector-based IDHmut cell lines displayed the same therapeutic vulnerabilities. Differences in treatment response were associated with multiple factors, including IDHmut protein expression and D-2-HG levels, in line with the fact that therapeutic vulnerabilities could be induced in the CRISPR-edited models by enhancing D-2-HG levels. Conclusion: Our findings demonstrate that synthetic lethal interactions observed in vector-based models are often a consequence of IDHmut protein overexpression and supra-physiological D-2-HG levels. These results highlight that relying on artificially created IDHmut models may lead to the identification of therapeutic vulnerabilities that are not present in IDHmut tumours, potentially explaining the poor translation of preclinical findings to clinical trials.

  Study EGAS50000001870

• RNAseq of medulloblastoma data (MB_COMICS cohort)

  Medulloblastoma (MB) is the most common malignant brain tumor in children. It is a neuroectodermal tumor located in the cerebellum. International consensus recognizes four distinct subgroups of MBs including Wingless (WNT), Sonic Hedgehog (SHH), Group 3 (G3), and Group 4 (G4) with distinct molecular characteristics, prognoses, and mortality rates in patients. Here, we have compiled and evaluated a large international MB cohort for which we generated transcriptomic data (RNAseq) for 208 primary MB patient samples.

  Study EGAS50000000410

• Methylome of medulloblastoma data (MB_COMICS cohort)

  Study EGAS00001007815

• Spatial Transcriptomics Uncovers Tumor Microenvironment-Based Subtypes in Invasive Lobular Carcinoma

  Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer (BC); however, little is known about its tumor microenvironment (TME). Here, we investigated the spatial architecture of 43 hormone-receptor-positive, HER2-negative (HR+/HER2-) primary ILC samples, using spatial transcriptomics and detailed morphological annotation. By integrating morphology, spatial, and single-cell data, we mapped TME-related cell types, exploring their proximity to tumor cells and their enrichment in specific compartments. Clustering of spatial transcriptomics spots revealed significant inter- and intra-tumor heterogeneity, identifying pathways and cell types linked with disease outcomes. Morphological and gene expression data were finally integrated with a multimodal approach, leading to the identification of 4 new ILC subtypes based on TME heterogeneity. By using derived, specific gene expression signatures, these subtypes were identified and validated in external bulk RNA-seq/microarray datasets (SCAN-B and METABRIC), where differences in prognosis emerged.

  Study EGAS50000001001

• Gene expression adaptation of metastases to their host tissue

  The adaptation of metastatic cells to their host tissue critically determines the pathogenicity of a cancer and therefore patient survival. Yet, it remains elusive to what extent the host environment drives gene expression programs in metastatic cells. Here we identify adaptive mechanisms that enable metastases to establish themselves in a novel tissue context. We performed single-cell RNA-sequencing on malignant and benign tissue samples from untreated donors with colorectal adenocarcinoma and liver metastasis to deduce tissue adaptive expression patterns. A novel computational approach identified genes and pathways that consistently adapted to the host tissue at the transition from the primary tumor to the paired metastasis across donors. This analysis revealed that the majority of expression changes in the metastasis reflect an expression signature reminiscent of benign liver epithelial cells. Cellular processes adapting to the liver environment include basic cellular functions such as energy metabolism, as well as tissue-specific pathways such as the regulation of lipid metabolism by PPAR-α. These adaptations potentially increase the pathogenicity of the metastatic cells and may provide new therapeutic strategies.

  Study EGAS50000000817

• Recurrent/Metastatic Adenoid Cystic Carcinoma Treated with Axitinib and Avelumab

  Data from patients with adenoid cystic carcinoma treated with combination of VEGFR inhibitor axitinib and anti-PD-L1 avelumab. Eligible patients had R/M ACC with progression within 6 months before enrollment. The primary end point was objective response rate (ORR) per RECIST 1.1; secondary end points included progression-free survival (PFS), overall survival (OS), and toxicity. The study reached its primary end point with ≥4 PRs in 28 evaluable patients (confirmed ORR of 18%).

  Study EGAS50000001714

• Genome-wide genotype data of 125 Agotes individuals presented in Portela-Estevez et al. 2026

  Genome-wide genotype data of 125 Agotes individuals presented in Portela-Estevez et al. (2026). The dataset from the Agotes Project was presented in the following article:Genome-wide evidence for the local ancestry of the Agotes from Navarra, Spain. Alicia Portela-Estevez, Alin P. Acuna-Alonzo, Cesar A. Fortes-Lima, Elsa de Cabo, Amaya Gorostiza, Maitane Tirapu de Goni, Araxi O. Urrutia, Georgios Athanasiadis, and Antonio Gonzalez-Martin. iScience, 2026, volume 29, issue 9, article 117229.https://doi.org/10.1016/j.isci.2026.1172

  Dataset EGAD00010002839

• RNA-seq and NGS target panel dataset related to "Ex vivo therapy-driven selection of glioblastoma stem-like cells models resistance evolution"

  Dac EGAC50000001111

• Plasma cell‐free transcriptome profiling in chronic liver disease

  RNAseq data from plasma samples corresponding to a Grand Challenge Programme project to find biomarkers for liver disease, including NAFLD, NASH, Cirrhosis and Hepatocelullarcarcinoma. A template of the DTA and DAA files is available in the following zenodo repository https://doi.org/10.5281/zenodo.19047046.

  Dac EGAC50000000360

• Genome-wide association study of never-smoking non-drinking young adults developing oral squamous cell carcinoma

  This study aims to evaluate if rare germline variants are associated with never-smoking non-drinking young adults oral squamous cell carcinoma.

  Study EGAS50000001809