516 results for "cancer rna-seq"

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• ICGC Breast Cancer Project, RNA seq

  A comprehensive characterisation and analysis of human breast cancers through genome-wide approaches through transcriptomics.

  Dataset EGAD00001001323

• Single cell RNA sequencing of PBMC samples from CRC patients

  This data contains scRNA-seq on 14 PBMC samples from colorectal cancer patients.

  Dataset EGAD50000000841

• Plasma cell-free small RNA sequencing of pancreatic cancer and control samples

  This dataset contains plasma-derived cell-free small RNA sequencing data from 78 human samples, comprising 39 pancreatic ductal adenocarcinoma patients and 39 control subjects. Each sample was sequenced as a single-end FASTQ library on both Illumina NovaSeq 6000 and Ultima Genomics UG 100 platforms, yielding 156 submitted sequencing runs. The data were generated from SMARTer smRNA-Seq libraries to support comparative analysis of sequencing performance, mature microRNA detection, and pancreatic cancer-associated cell-free small RNA expression across the two platforms.

  Dataset EGAD50000002771

• Genomic profiling of BRCA- mutant breast cancer tumors

  This data set contains whole exome sequencing (WXS) and RNA-Seq on germline BRCA- mutant tumors from 18 patients. BAM files are provided for WXS on tumor and germline samples. FASTQ files are provided for the RNA-Seq samples. Sequencing was done on an Illumina Hi-Seq 2500.

  Dataset EGAD00001008276

• The function of circular RMST in neuroendocrine tumours

  Circular RNA (circRNA) is a class of noncoding RNA with regulatory potentials. Its role in the transdifferentiation of prostate and lung adenocarcinoma into neuroendocrine prostate cancer (NEPC) and small cell lung cancer (SCLC) remains unexplored. Here we identified circRMST as an exceptionally abundant circRNA predominantly expressed in NEPC using total RNA-seq profiling of patient samples. In addition, circRMST is also abundantly expressed in SCLC. Functional studies using shRNA, siRNA, CRISPR-Cas13 and Cas9 consistently demonstrate that circRMST is essential for tumour growth and the expression of ASCL1, a master regulator of neuroendocrine fate. Mechanistically, circRMST physically interacts with lineage transcription factors NKX2-1 and SOX2. Loss of circRMST induces NKX2-1 protein degradation through autophagy-lysosomal pathway and alters the genomic binding of SOX2, collectively leading to the loss of ASCL1 transcription.

  Study EGAS50000000897

• Deregulation of FOXF1/FENDRR from t(14;16)(q32;q24) defines a subtype of high risk lineage ambiguous leukemia

  Despite great progress in understanding the genomic basis of immature T-cell acute lymphoblastic leukemia/lymphoblastic lymphoma (T-ALL) and acute leukemias of ambiguous lineage (ALAL), there are still cases that lack defining genetic markers, complicating risk stratification and limiting targeted therapeutic options. Here, we describe a subtype of leukemia defined by the t(14;16)(q32;q24) translocation, which places the FOXF1 gene and its antisense long noncoding RNA gene FENDRR under the regulatory control of the BCL11B enhancer, leading to their ectopic transcriptional activation. Analysis of different high-throughput sequencing data, including WGS, RNA-seq, scDNA-seq, scRNA-seq, ChIP-seq, ATAC-seq, and HiChIP-seq, identified BCL11B-enhancer mediated deregulation of FOXF1/FENDRR as a hallmark of a subtype of high-risk lineage ambiguous leukemia that is potentially amenable to targeted therapeutic intervention.

  Study EGAS50000001255

• DNTR sequencing data of paediatric acute lymphoblastic leukemia

  This study used the DNTR-seq method in leukaemia samples to profile the whole-genome and mRNA jointly in single cells. Direct tagmentation is used in a collection of single-cell whole genome sequencing (scWGS) methods, including DNTR-seq, which provide high quality data at ultra-low to low coverage. The overall goal was to characterize the genetic and transcriptional heterogeneity of cancer samples. To infer clonal structure and evolutionary history, copy number analysis based workflows were implemented. Bone marrow mononuclear cells from pediatric acute lymphoblastic leukemia samples were FACS sorted into 384 plates to generate the DNA and RNA profiles.

  Study EGAS50000001247

• RNA-seq study of a Princess Margaret Cancer Centre human acute myeloid leukemia patient cohort

  The PMCC AML RNAseq dataset consists of 81 AML patient samples (clinical data in Supplemental Table 11 of manuscript), processed in two batches. These patient samples are able to engraft in the NSG (NOD.Cg PrkdcscidIl2rgtm1Wjl /SzJ) mouse model. Five patients (90543, 598, 90240, 110484, 100500) were included in both batches. Viaably frozen material from the Leukemia Tissue Bank at Princess Margaret Cancer Centre/ University Health Network were thawed by dropwise addition of X-VIVO + 50% fetal calf serum supplemented with DNase (100μg/mL final concentration, Roche). RNA was extracted from bulk peripheral blood mononuclear cells (PBMC) using the RNeasy Micro Kit (Qiagen Inc.). A paired-end 76 base-pair flow-cell lane Illumina High seq 2000 yielded an average of 240 million sequence reads aligning to genome per sample at the Genome Sciences Centre, BC Cancer Agency for cohort 1. Cohort 2 was subjected to 125 bp, paired-end RNA-sequencing on the Illumina HiSeq 2500 with an average of 50 million reads/sample at the Centre for Applied Genomics, Sick Kids Hospital.

  Study EGAS00001004792

• Comparison of good PDX responders and bad PDX responders

  RNA-Seq raw data of untreated breast cancer xenografts known as good or bad acetalax responders.

  Dataset EGAD50000000876

• RNA-Seq of kidney cancer organoid biobank

  Dataset EGAD00001005318