7253 results for "canc*"

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• Exome sequencing files for "Minimal functional driver gene heterogeneity among untreated metastases"

  Files from whole exome sequencing of 14 tumors from two cancer patients (endometrial and lung cancer) along with a matched normal tissue per patient.

  Dataset EGAD00001004212

• Illumina_WGS_MET-CELL

  Whole-genome sequencing on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer metastasis sample

  Dataset EGAD00001002085

• Illumina_WXS_T-XEN

  Whole-exome sequencing on Illumina HiSeq2000/2500 of Patient-derived xenograft derived from colorectal cancer primary tumor sample

  Dataset EGAD00001002102

• Single Cell Genome Sequence for DLP+ library A96141A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 8 on DLP+ library A96141A

  Dataset EGAD00001009777

• Comprehensive RNA repository of tissue and plasma from patients with esophageal cancer or precursor lesions

  A comprehensive RNA repository (both coding and non-coding) from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were collected. This dataset includes both mRNA and small RNA sequencing data (fastq.gz files) of all tissue and plasma samples. In total,102 RNA-seq libraries from 51 samples (17 plasma and 34 tissue samples) were sequenced (plasma mRNA libraries were sequenced twice).

  Dataset EGAD00001006857

• Illumina_WXS_T-CELL

  Whole-exome sequencing on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer primary tumor sample

  Dataset EGAD00001002100

• BCSA_Exome+SmartSeq3

  Multiple regions were cut out of each tumor extracted form breast cancer patients and two experiments were run: - Whole exome sequencing on each of the regions plus an adjacent normal tissue sample - Smart-Seq3 Single cell RNA sequencing on EPCAM+ CD45- sorted cells from different tumor regions

  Dataset EGAD00001009781

• RNA-seq analysis of transcriptome variation with human ESC subclones

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ .

  Dataset EGAD00001004266

• Novel method for efficient establishment, expansion and drug response profiling of high-grade serous ovarian cancer organoids

  HGSOC patient-derived organoids and their tissue of origin

  Dataset EGAD00001008753

• Tumor Educated Platelets (TEPs) for breast cancer detection

  The TEP dataset consists of 549 Fastq samples which are divided into two experiments: a training data cohort, used to train the classifier, and a validation data cohort, used to assess classifier performance

  Dataset EGAD00001009790