7201 results for "canc*"

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• Massive genomic rearrangement acquired in a single catastrophic event during cancer development

  Massive genomic rearrangement acquired in a single catastrophic event during cancer development

  Dataset EGAD00001000002

• CLL Cancer Whole Genome Sequencing

  CLL Cancer Whole Genome Sequencing

  Dataset EGAD00001000013

• Whole Genome Sequencing of Multiple Myeloma patients treated with T-cell redirecting immunotherapies

  Samples was collected at the Arnie Charbonneau Cancer Institute (University of Calgary). Whole Genome Sequencing was performed at the New York Genome Center, and libraries were prepared using the Truseq DNA Nano Library Preparation Kit. Libraries were sequenced on an Illumina Novaseq 6000 sequencer using 2 x 150-bp cycles. The dataset consists in 85 BAM files from patients with Multiple Myeloma treated with bi-specific and CAR-T therapies. Reference Genome: GRCh38.

  Dataset EGAD50000000776

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 16)

  The dataset contains whole genome sequencing data of 58 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 144 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000000777

• ICARUS-BREAST01-RNAseq

  Efficacy, safety and biomarker analysis of ICARUS-BREAST01: a phase 2 Study of Patritumab Deruxtecan in patients with HR+/HER2- advanced breast cancer. RNA-squencing is available for 44 samples comprising 22 samples collected at entry into the trial and 22 samples collected during treatment (cycle 1 day 3, cycle 1 day 19, or cycle 2 day 3) from 22 patients.

  Study EGAS50000000543

• Genomic profiling of Rare Tumors Release 2

  Utilizing the rare and unique patient samples provided by Pattern Medicine, LLC, MD Anderson will molecularly characterize rare cancer samples, and potentially generate a collection of preclinical models to enable identification of novel therapeutic targets and concepts, as well as evaluation of innovative treatment strategies.

  Study EGAS50000000615

• 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

• Systematic dissection of tumor-normal single-cell ecosystems across a thousand tumors of 30 cancer types

  The complexity of the tumor microenvironment poses significant challenges in cancer therapy. Here, to comprehensively investigate the tumor-normal ecosystems, we perform an integrative analysis of 4.9 million single-cell transcriptomes from 1,070 tumor and 493 normal samples in combination with pan-cancer 137 spatial transcriptomics, 8,887 TCGA, and 1,261 checkpoint inhibitor-treated bulk tumors. We define a myriad of cell states constituting the tumor-normal ecosystems and also identify hallmark gene signatures across different cell types and organs. Our atlas characterizes distinctions between inflammatory fibroblasts marked by AKR1C1 or WNT5A in terms of cellular interactions and spatial co-localization patterns. Co-occurrence analysis reveals interferon-enriched community states including tertiary lymphoid structure (TLS) components, which exhibit differential rewiring between tumor, adjacent normal, and healthy normal tissues. The favorable response of interferon-enriched community states to immunotherapy is validated using immunotherapy-treated cancers (n=1,261) including our lung cancer cohort (n=497). Deconvolution of spatial transcriptomes discriminates TLS-enriched from non-enriched cell types among immunotherapy-favorable components. Our systematic dissection of tumor-normal ecosystems provides a deeper understanding of inter- and intra-tumoral heterogeneity.

  Study EGAS50000000324

• Systematic dissection of tumor-normal single-cell ecosystems across a thousand tumors of 30 cancer types

  Raw bam file for bulk RNA-seq of checkpoint-blockade treated lung cancer cohorts

  Dataset EGAD50000000469

• DAC for a single-cell multi-omic atlas of nodal B-cell non-Hodgkin lymphomas

  Nodal B-cell non-Hodgkin lymphomas (B-NHL) are a clinically diverse set of cancers thought to originate from distinct stages of B-cell maturation. To characterize intratumor heterogeneity across B-NHL entities, we performed CITE-Seq (cellular indexing of transcriptomes and epitopes) on 51 lymph node samples including mantle cell lymphoma (MCL, n = 8), follicular lymphoma (FL, n = 12), germinal center (GCB, n = 5) or activated B-cell (non-GCB/ABC, n = 7) diffuse large B-cell lymphoma (DLBCL) and marginal zone lymphoma (MZL, n = 11) tumors, in addition to non-malignant reactive lymph nodes (rLN, n = 8). We also performed 5 prime scRNA-seq with immune receptor profiling for 11 of these samples (2 rLN, 2 MCL, 3 FL, 2 DLBCL, and 2 MZL).

  Dac EGAC50000000226