11805 results for "cancer rna-seq"

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• Targeted sequencing of paired tumour/blood of 34 T1 stage bladder cancer patients

  Stage T1 bladder cancer presents a high risk of progression and requires improved understanding. In continuation of our whole-exome sequencing study on this subtype of the disease, we carried out this targeted paired tumour/blood sequencing study including 34 T1 stage bladder cancer patients. Agilent’s SureDesign tool was used to design a 1.133 Mb SureSelect custom capture for all coding exons of the 140 selected candidate genes.

  Study EGAS00001005767

• 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

• RRBS data from TRACERx non-small cell lung cancer (NSCLC) tumours and matched normal adjacent tissue.

  TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC). This study looks at multi-region RRBS data from the TRACERx cohort selected for quantity of material available and high tumour purity

  Study EGAS00001006523

• The Landscape of N-6 Methyladenosine in Primary Localized Prostate Cancer

  Using meRIP-sequencing, we profiled N-6 methyladenosine (m6A) in a cohort of 148 primary prostate cancer samples as part of the Canadian Prostate Cancer Genome Network project (CPC-GENE). Paired-end sequencing of 150 bp reads were mapped to GRCh38.p13 using annotations from gencode.v34.chr_patch_hapl_scaff.annotation.gtf. Peaks were called using MeTPeak, joint peaks were identified and IP reads were quantitated, normalized and adjusted using Input reads to obtain estimates of m6A abundance.

  Study EGAS00001006925

• PE-CGS: Optimizing Engagement of Hispanic Colorectal Cancer Patients in Cancer Genomic Characterization Studies

  Colorectal Cancer (CRC) is the second leading cause of cancer death in the US. Hispanic/Latinos (H/L) are the largest and fasting growing ethnic group in the US, and cancer is the leading cause of death among H/L in the US. Therefore, we need to fully understand the full complexity of the molecular etiology of cancer in this ethnic group. For instance, although incidence rates of CRC are lower among Latinos as compared to Whites or African Americans, Hispanics with metastatic disease have shorter overall survival when adjusted for health care setting, demographics, disease characteristics and treatment factors. H/L also tend to be diagnosed at a younger age and with higher stage, and we have previously reported that Mexican H/L in California have the greatest proportion of young (The Cancer Genome Atlas has provided a deep overview of the molecular taxonomy of CRC in 594 cases, however, less than 1% of the cases (n=5) were H/L. Therefore, it is imperative for us to take more detailed assessment of the molecular genomic landscape of CRC in H/L. One of the major issues likely limiting our ability to perform these large genomic initiatives in minority patients is that Patient or Participant Engagement practices may not be investigated to identify best practices for accruing and consenting patients into clinical translational biomedical research studies. This concept of Participant Engagement is critically important for both the patients and the translational cancer research community. Optimizing and improving our approaches for directly engaging patients at initial contact, throughout the course of a translational genomic study, and during the time of return of results is likely to lead to stronger relationships between the medical community and patients, but could also lead to significant improvement in outcomes for patients and for the cancer care community as a whole. As such, we propose the creation of the USC Center for Optimization of Participant Engagement in Cancer Characterization (COPECC) with a focus on optimizing the engagement of Latinos in CRC Genomic Characterization research studies. USC COPECC would serve as a member of the NCI U2C Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network. Our investigative team includes experts in all relevant areas of research for genomic characterization, participant engagement, and engagement optimization. We have an established platform for consenting patients into cancer genomics studies that will serve as a standard process. The overall goal of USC COPECC is to generate results on participant engagement optimization and CRC genomic research that will be shared with the broader community to distribute best practices for engaging Latinos in hopes of improving overall outcomes for CRC in this underserved population.

  Study phs003985

• Transcriptome atlas of brain organoid developent

  Single-cell Cut&Tag of three histone modifications and chromatin accessibility over a timecourse of brain organoid development from pluripotency. We profiled 5 time points of brain organoid development and 2 time points of retinal organoid development. We used scRNA-seq to profile transcriptome. Library preparation was carried out with the 10x genomics platform.

  Dataset EGAD50000000223

• BIOMIROX

  This dataset regroups RNAseq of paired primary colorectal cancers and liver metastases extracted from 113 patients In Paris and Besançon University Hospitals. 216 FASTQ files from single-end 3' PolyA (QuantSeq 3′mRNA-Seq Kit FWD for Illumina (Lexogen)) RNAseq samples were generated On NOVASEQ 6000 (ILLUMINA).

  Dataset EGAD50000000443

• Saliva_Fulani_Database

  In total, 90 DNA samples were genotyped on the Illumina Infinium H3Africa Consortium array (designed for 2,271,503 SNPs; using BeadChip type: H3Africa_2019_20037295_B1). Genotyping was performed at the SNP&SEQ Technology Platform (NGI/SciLifeLab Genomics, Sweden). Saliva Fulani dataset includes individuals from the following populations: 30 individuals from Senegal_FulaniLinguere, 30 individuals from Mauritania_FulaniAssaba, and 30 individuals from Mali_FulaniInnerDelta.

  Dataset EGAD50000000653

• Single-Cell Profiling of the Human Endometrium in Polycystic Ovary Syndrome: Uncovering Disease Signatures and Treatment Responses

  Single-nuclei map of human endometrial biopsies from women with and without PCOS to identify cell-type-specific disease signatures, compositional variations, and transcriptomic reversibility after a 16-week intervention with metformin or lifestyle. Single nuclei were extracted from 27 frozen endometrial biopsies for snRNA-seq using the 10X Genomics protocol.

  Dac EGAC50000000468

• Mixture of 4

  Mixture of 4 unrelated individuals sequenced by 10x as a scRNA-seq. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile. The clustering of SNPs is submitted as the processed file. The Sequencing fastqs are submitted as unprocessed files.

  Dataset EGAD00001008724