7362 results for "canc*"

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• Sequencing of serial plasma and multiregional tumor samples in a patient with metastatic breast cancer

  Circulating tumor DNA analysis can be used to track tumor burden and analyze cancer genomes non-invasively but the extent to which it represents metastatic heterogeneity is unknown. Here, we follow a patient with metastatic ER and HER2 positive breast cancer receiving two lines of targeted therapy over 3 years. We characterize genomic architecture and infer clonal evolution in 8 tumor biopsies and 9 plasma samples collected over 1,193 days of clinical follow-up using exome and targeted amplicon sequencing.

  Study EGAS00001001466

• AML_WES

  This 2014_AML_WES study includes 40 paired samples derived from Korean AML paitients. AML Bone Marrow samples were collected and paired with each normal(Saliva or BM derived) sequencing data. The results of this CN study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001001559

• Data from the paper Context-specific Effects of TGFβ/SMAD3 in Cancer Are Modulated by the Epigenome. Tufegdzic et al, Cell Reports 2015

  The transforming growth factor beta (TGFβ) signalling pathway exerts opposing effects on cancer cells, acting either as a tumor-promoter or as a tumor-suppressor. Here we show these opposing effects are a result of the synergy between SMAD3, a downstream effector of TGFβ signalling, and the distinct epigenomes of breast tumor initiating cells (BTICs). These effects of TGFβ are associated with distinct gene expression programs, but genomic SMAD3 binding patterns are highly similar in the BTIC-promoting and BTIC- suppressing contexts. Our data show cell type-specific epigenetic configurations provide a modulatory layer by determining accessibility of genes to regulation by TGFβ/SMAD3. LBH, one such context-specific target gene, is regulated according to its DNA methylation status, and is crucial for TGFβ-dependent promotion of BTICs. Overall, these results reveal that the epigenome plays a central and previously overlooked role in shaping the context-specific effects of TGFβ in cancer.

  Study EGAS00001001570

• Melanoma_C32_ENU_Resistance_to_Single_Agent_Therapy

  This study involves mutagenizing C32, a melanoma cell line, with ENU to identify those mutations which engender resistance to a targeted treatment.

  Study EGAS00001001697

• Tissue-specific mutation accumulation in human adult stem cells during life

  Gradual accumulation of mutations in human adult stem cells during life is associated with various age-related diseases, including cancer. The number of stem cell divisions throughout life is believed to be a major determinant for mutation accumulation and could explain the extreme variation of cancer incidence across different organs. Yet, mutation patterns and rates of healthy adult stem cells remain unknown. Here, we determined genome-wide mutation patterns in primary adult stem cells of the small intestine, colon and liver of human donors with ages ranging from 3 to 87 years. We find that the number of mutations increases linearly with age up to several thousand mutations per cell at 87 years of age, while mutation spectra remain constant throughout life. Small intestine and colon stem cells have a 2-fold higher mutation rate per year compared with liver stem cells. These differences could be exclusively attributed to the mutagenic action of spontaneous deamination of cytosine residues and may reflect the high stem cell division rate in these tissues. The genomic distribution of somatic mutations is non-random and predominantly associated with DNA replication dynamics in the small intestine and colon, and with transcription in the liver. These results indicate that a stable balance between various mutagenic and DNA repair processes is maintained throughout life and that the activity of these processes in adult stem cells varies between tissues.

  Study EGAS00001001682

• Genome-wide DNA methylation profiles of NSCLC xenograft and primary lung tissues for the identification of epigenetic predictive biomarkers.

  Non-small cell lung cancers (NSCLC) are the most common cause of cancer-related deaths worldwide and primarily treated with platinum-based drugs like cisplatin and carboplatin, radiation and surgery. The major challenge in the management of NSCLC are intrinsic or acquired resistance mechanisms with only few published molecular markers which can predict the outcome of the patients. On the other side, changes in DNA methylation are observed in nearly all cancer types making them suitable as biomarker. Here genome-wide methylation profiles from MeDIP-Seq and gene expression profiling data of 22 primary NSCLC, adjacent normal tissue and PDX samples are provided. For each PDX tumor growth rates were measured in absence or presence of chemotherapy.

  Study EGAS00001002479

• Gastric_and_Esophageal_tumour_rearrangement_screen

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from gastric and esophageal tumours and subjected to total of two lanes of 50 bp, paired end sequencing on the llumina HiSeq. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Study EGAS00001000037

• 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