7406 results for "canc*"

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• Extensive and differential platinum chemotherapy mutagenesis in livers of children - Whole genome NanoSeq

  Whole genome NanoSeq of a cohort predominantly consisting of paired blood, normal liver and liver tumour from children with liver cancer. The cohort includes platinum-exposed and platinum naïve samples.

  Dataset EGAD00001016142

• DNA WGS BAM files for PMID: 41845530 titled: Multi-omics reveals key molecular and cellular features of advanced small cell lung cancers associated with distinct therapeutic opportunities

  DNA WGS BAM files for PMID: 41845530 titled: Multi-omics reveals key molecular and cellular features of advanced small cell lung cancers associated with distinct therapeutic opportunities

  Dataset EGAD00001016147

• HCA Organoid | Colon - a cohort-scale multi-omic atlas of human colon organoids and matched primary tissue biopsies.

  Single-nucleus multiome sequencing data (snRNA-seq + snATAC-seq) from healthy tissue of 81 donors with colorectal cancer (71 matched organoid and primary tissue; 10 with one sample type only), generated as part of the Human Cell Atlas Organoid Project.

  Dataset EGAD00001016153

• snRNA sequencing of high-grade pancreatic neuroendocrine carcinoma (panNEC)

  High-grade pancreatic neuroendocrine carcinoma (panNEC) is a rare, aggressive cancer with limited tissue availability. Single-nucleus transcriptomics of five large-cell panNECs revealed two interesting neuroendocrine cell states: one highly proliferative with an aberrant brain-specific neuronal differentiation program and another stress-responsive state enriched for heat stress, hypoxia, and glycolysis. Our findings suggest potential therapeutic vulnerabilities, highlighting the need to evaluate the efficacy of combination therapies.

  Dataset EGAD00001016154

• scRNAseq of tumor infiltrating CD8+ T cells

  single cell mRNA sequencing of tumor infiltrating CD8+ T cells. CD8+ T cells were FACS sorted from tumor tissue obtained from 8 non-small cell lung cancer patients. Gene expression and TCR library preparation was performed using the Chromium Next GEM Single Cell 5' Kit v2, Chromium 5' Feature Barcode Kit, and Chromium Single Cell Human TCR Amplification Kit from 10x genomics. After paired-end sequencing this resulted in fastq files containing TCR sequences, gene expression, and feature barcode levels.

  Dataset EGAD50000002739

• Bulk RNAseq of cancer-associated CD8 T cell populations

  Bulk mRNA sequencing of cancer-associated CD8 T cell populations isolated from tumor and tumor-adjacent tissue from non-small cell lung cancer patients. CD8 T cell populations isolated were CD103+CD39- and CD103+CD39+ from tumor tissue, and CD103+CD39- from adjacent tissue. These populations were isolated from 5 patients, totaling 15 samples. bulk poly-A RNA was isolated and libraries were prepped using the Smart-Seq2 protocol, followed by paired-end sequencing (Illumina). Raw data are in fastq format.

  Dataset EGAD50000002740

• GBM-Space: Whole Genome Sequencing of Laser Capture Microdissected Glioblastoma (LCM-WGS)

  Cancer cells display heterogeneous and dynamic states in glioblastoma, but how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generate a deep single cell and spatial multi-region atlas of 12 isocitrate dehydrogenase wild-type (IDH-wt) primary glioblastomas that integrates transcriptomic, epigenomic and genomic analysis to comprehensively characterise their tumour heterogeneity. This dataset contains whole genome sequencing (WGS) data generated from regions of interest (ROIs) collected via laser capture microdissection (LCM), towards identifying copy number alterations and subclones directly at the DNA level.

  Dataset EGAD00001016155

• Dataset for 18 PTK7 RNASeq samples

  This dataset contains 18 RNASeq tumor and control samples of patient with colorectal cancer. Sequencing was performed on Illumina NovaSeq X Plus. The sequencing was always paired.

  Dataset EGAD00001016160

• Single cell characterization of T-cell lymphoma: RNA (2025-07-31)

  Lymphomas are types of blood cancer derived from lymphocytes, and can be classified into two main categories, Hodgkin's lymphomas (HL) and non-Hodgkin lymphomas (NHL). T-cell lymphoma is a type of NHL that develops from T lymphocytes and accounts for 10-15% of total NHL cases. As a rare disease, T-cell lymphoma is functionally, pathologically, and clinically complex and heterogeneous. The 2016 revision of the WHO classification has listed 29 subtypes of mature T/NK-cell neoplasms, among which over 25 are T lymphocyte in origin. These subtypes of T-cell lymphomas have different biological behaviours and clinical prognosis. Clinically, T-cell lymphoma ranges from indolent (slow-growing) to aggressive (fast-growing and spreading) disease. According to the guideline booklet provided by the Lymphoma Research Foundation (https://lymphoma.org/aboutlymphoma/nhl/), indolent T-cell lymphoma subtypes include adult T-cell leukaemia/lymphoma (ATLL), cutaneous T-cell lymphoma (CTCL), and mycosis fungoides (MF), while the aggressive subtypes include anaplastic large cell lymphoma (ALCL), angioimmunoblastic T-cell lymphoma (AITL), peripheral T-cell lymphoma (PTCL), and T lymphoblastic lymphoma (TLBL). PTCL and ALCL represent the most common subtypes of aggressive T-cell lymphoma whereas TLBL is a rare and aggressive subtype mostly diagnosed in children. In this study, we will use single cell RNA sequencing and single cell multiomic methods three aggressive T-cell lymphoma subtypes (ALCL, PTCL and TLBL) and try to gain a deeper insight into the genotypic and phenotypic features of these T-cell lymphomas. . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015669

• A non-canonical lymphoblast in refractory childhood T-cell leukaemia

  Refractory cancers may arise either through the acquisition of resistance mechanisms or represent distinct disease states. The origin of childhood T-cell acute lymphoblastic leukaemia (T-ALL) that does not respond to initial treatment, i.e. refractory disease, is unknown. Refractory T-ALL carries a poor prognosis and cannot be predicted at diagnosis. Here, we perform single cell mRNA sequencing of T-ALL from 58 children (84 samples) who did, or did not respond to initial treatment. We identify a transcriptionally distinctive blast population, exhibiting features of innate-like lymphocytes, as the major source of refractory disease. Evidence of such blasts at diagnosis heralds refractory disease across independent datasets and is associated with survival in a large, contemporary trial cohort. Our findings portray refractory T-ALL as a distinct disease with the potential for immediate clinical utility. This dataset contains 56 single-cell RNA sequencing data files with corresponding single-cell T cell receptor sequencing data files. The data here form the validation cohort in our paper.

  Dataset EGAD00001015673