6048 results for "canc*"

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• Concurrent germline and somatic pathogenic BAP1 variants in a patient with metastatic bladder cancer

  Study EGAS00001004055

• DNA Methylation loss coupled with mitotic cell division promotes immune evasion of tumours with high mutation load

  Mitotic cell division increases tumour mutation burden and copy number load with a positive and inverse correlation, respectively, with the clinical benefit of immunotherapy. Markers of cell division correlate also with genomic demethylation involving methylation loss in late-replicating partial methylation domains. Here we find that immunomodulatory pathway genes are concentrated in these domains and transcriptionally repressed in demethylated tumours with CpG island promoter hypermethylation. Global methylation loss correlated with immune evasion signatures independently of mutation burden and aneuploidy. Methylome data of our cohort (n = 60) and a published cohort (n = 81) in lung cancer and a melanoma cohort (n = 40) consistently demonstrated that genomic methylation alterations counteract the contribution of high mutation burden and increase immunotherapeutic resistance. Higher predictive power was observed for methylation loss than mutation burden. We also found that genomic hypomethylation correlates with the immune escape signatures of aneuploid tumours. Hence, DNA methylation alterations implicate epigenetic modulation as a combination regimens for precision immunotherapy.

  Study EGAS00001003731

• Measuring minimal residual disease in acute myeloid leukemia with MASQ

  Study EGAS00001003732

• Dual-mTOR inhibitor Rapalink-1 reduces prostate cancer patient-derived xenograft growth and alters tumor heterogeneity

  Bone metastasis is the leading cause of prostate cancer (PCa) mortality, frequently marking the progression to castration-resistant PCa. In this study, we compared the molecular pathways enriched in a set of bone metastasis from breast and prostate cancer from snap-frozen tissue. To further model PCa drug resistance mechanisms, we used two patient-derived xenografts (PDX) models of bone-metastatic PCa, BM18 and LAPC9.

  Study EGAS00001004431

• Landscape and significance of multiple mutations in oncogenes.

  This study is a comprehensive pan-cancer study of oncogenic multiple mutations (MMs) which includes long-read whole-genome sequencing data (n = 3).

  Study EGAS00001003763

• IBD-dysplasia

  Study EGAS00001003767

• Copy number and mutation profiling of Stage 1 epithelial ovarian cancer biopsies

  This project aims at characterizing the genome-wide copy number profile and the variant profile of 139 genes om the five major histotytpes of early-stage (stage I) epithelial ovarian cancer (EOC), to provide insight in the the aethiology and development of the disease.

  Study EGAS00001004961

• WXS of 147 lung cancer patients treated with immunotherapy

  We first attempted to predict MHC-binding neoantigens at high accuracy with convolutional neural networks. This prediction model outperformed previous methods in > 70% of test cases. Importantly, our method remarkably increased the predictive value of neoantigen load especially in combination with known resistance parameters. We then developed a classifier that can predict resistance from point mutations that are deleterious to protein function. Notably, genes involved in the adaptive immune response, cytokine signaling,and EGFR signaling held high explanatory power. Furthermore, when integrated with our neoantigen profiling, these anti-immunogenic mutations revealed significantly higher predictive power than known resistance factors.

  Study EGAS00001003781

• Polyomavirus-positive Merkel cell carcinoma derived from a trichoblastoma suggests an epithelial origin of Merkel cell carcinoma

  Study EGAS00001003784

• Patient-Derived Lung Cancer Organoid

  Lung cancer shows substantial genetic and phenotypic heterogeneity across individuals, driving a need for personalized medicine. Here we report lung cancer organoids and normal bronchial organoids established from patients tissues comprising five histological subtypes of lung cancer and non-neoplastic bronchial mucosa as in vitro models representing individual patient. The lung cancer organoids recapitulate the tissue architecture of the primary lung tumours and maintain the genomic alterations of the original tumours during long-term expansion in vitro. The normal bronchial organoids maintain cellular components of normal bronchial mucosa. Lung cancer organoids respond to drugs based on their genomic alterations: a BRCA2 mutant organoid to olaparib, an EGFR mutant organoid to erlotinib, and an EGFR mutant/MET amplified organoid to crizotinib. Considering the short length of time from organoid establishment to drug testing, our newly developed model may prove useful for predicting patient-specific drug responses through in vitro patient-specific drug trials.

  Study EGAS00001003786