16802 results for "sec+and+unspecified+malignant+neoplasm"

in 36.78 milliseconds.

• Bulk RNAseq of Neuroblastoma patient's tumors

  This dataset contains 9 bulk RNAseq of neuroblastoma patient's tumors used to compare with derived PDXs and/or single-cell data in the Thirant C et al, Nature Communications, 2023. They were intially produced for the Berlanga P., Cancer Discovery, 2022.

  Dataset EGAD00001010287

• Sequencing data for oesophageal and related samples - Ganguli et al (sWGS)

  Data supporting: "TBC" Ganguli et al (sWGS for 75 samples)

  Dataset EGAD00001011189

• Whole exome sequencing (WES) of CIMP leukemias

  Whole exome sequencing of tumor material derived from 14 mixed myeloid/lymphoid leukemias with a CpG Island Methylator Phenotype (CIMP). For 4 of these patients, normal material was also sequenced and used as control (files with the same identifiers prepended by an “h”).

  Dataset EGAD00001011053

• Total RNA sequencing data from the Triple Negative Trial (TNT)

  BAM files from total RNA sequencing of samples from breast cancer patients in the TNT trial. Data includes 186 primary tumour samples and 13 matched recurrence samples.

  Dataset EGAD00001011141

• Sequencing data for oesophageal and related samples - Abbas et al (RNA)

  Data supporting: "Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma" Abbas et al (RNA for 197 samples)

  Dataset EGAD00001011269

• Single cell TotalSeqC protein data of 20 PMBC pools of HCC patients

  Single cell TotalSeqC protein data serial peripheral blood mononuclear cell (PBMC) samples taken from advanced HCC patients. TotalSeqC is available for 41 out of 72 PBMC samples included in the study, and were combined into 20 pools.

  Dataset EGAD00001011346

• The dataset for "Validation of cfDNA fragmentome analyses for early detection of liver cancer"

  The dataset for “Validation of cfDNA fragmentome analyses for early detection of liver cancer” includes 380 cram files from whole genome next-generation sequencing on the Illumina NovaSeq 6000 with 10x coverage. The samples analyzed include plasma samples from patients with cancer and liver disease.

  Dataset EGAD00001015538

• Oncogenic Ectodomain deletion of FGFR1 caused by Breakage-Fusion-Bridges in Squamous Cell lung Cancer

  The identification of recurrent 8p11.23 amplifications including FGFR1 raised the hope of a treatable target in squamous cell lung cancer (SQLC). However, only a minority of patients with FGFR1-amplified tumors respond to single agent inhibitor therapy targeting FGFR. To understand the underlying mechanism of FGFR1 dependency, we performed whole genome and transcriptome sequencing of 25 FGFR1-amplified primary tumors with unknown response upon FGFR inhibition. In addition, we performed deep sequencing of 26 FGFR1-amplified samples whereof the response upon FGFR inhibition was known for 25 samples. In both cohorts we identified intra-chromosomal tail-to-tail breaks close to the FGFR1 transcription start site, being responsible for focal amplification of FGFR1. These specific breaks are caused by a Breakage-Fusion-Bridge-like (BFB-like) mechanism. Here, we associate these breaks with FGFR inhibitor sensitivity. Moreover, in some cases these breaks are located within the open reading frame of FGFR1, which leads to the expression of an ΔEC-FGFR1 transcript that lacks the ecto-domain. Overexpression of ΔEC-FGFR1 transforms Baf3 cells and lead to an FGFR1-dependent phenotype. Our results demonstrate that the truncation of the FGFR1 ectodomain is a frequent event in 8p11.23-amplified squamous cell lung cancer caused by tail-to-tail breaks. These breaks might be used as a predictive therapeutic marker to stratify patients for FGFR-inhibitor therapy.

  Study EGAS00001005059

• Human CD4 Memory T Cell Activation Time Course

  We performed a high-resolution time course RNA-seq experiment on CD4+ memory T cells during activation with anti-CD3/CD28 beads. We performed this in 24 adult individuals of European ancestry with no autoimmune diseases. We used 1 million cells as starting material, per time point (up to 8 time points per individual from 0 to 72 hours). We identified widespread dynamic allele-specific expression (dynASE) across the genome, i.e. ASE that changes with time after activation, which reflects cell state-dependent genetic regulatory effects. DynASE events were enriched in risk loci for multiple autoimmune diseases. This highlights the importance of studying multiple cellular states in order to elucidate the mechanisms of autoimmune disease. It also provides a successful framework to do it in other cellular systems relevant for other traits. We also showed an unprecedented amount of regulatory variation for HLA genes. HLA-DQB1 has 3 distinct regulatory haplotypes with expression profiles that could come from 3 different genes. We performed ATAC-seq in replicate for CD4+ memory T cells stimulated for 72 hours from another healthy individual. These data, together with genetic fine-mapping, CRISPR editing, EMSA and luciferase assays, helped us find a SNP in the promoter of HLA-DQB1 that causes at least part of the large cell state-dependent change in expression, at the RNA and protein levels.

  Study phs002259

• Genomic Landscape of Human Skin at a Single-Cell Resolution

  Every cell in the human body has a unique set of somatic mutations, yet it remains difficult to comprehensively genotype an individual cell. Here, we developed solutions to overcome this obstacle in the context of normal human skin, thus offering the first glimpse into the genomic landscapes of melanocytes at single-cell resolution. We comprehensively genotyped 133 melanocytes from 19 sites across 6 donors. As expected, sun-shielded melanocytes had fewer mutations than sun-exposed melanocytes. However, within sun-exposed sites, melanocytes on chronically sun-exposed skin (e.g. the face) displayed a lower mutation burden than melanocytes on intermittently sun-exposed skin (e.g. the back). Melanocytes from donors with a history of skin cancer had higher mutation burdens than melanocytes from donors without skin cancer, implying that the mutation burden of normal skin can be harnessed to measure cumulative sun damage and skin cancer risk. Moreover, melanocytes from healthy skin commonly harbor pathogenic mutations, likely explaining the origins of the melanomas that arise in the absence of a pre-existing nevus. Phylogenetic analyses identified groups of related melanocytes, suggesting that melanocytes spread throughout skin as fields of clonally related cells, invisible to the naked eye. Overall, our study offers an unprecedented view into the genomic landscapes of individual melanocytes, revealing key insights into the causes and origins of melanoma.

  Study phs001979