15017 results for "cancer studies using rna-seq"

in 16.35 milliseconds.

• EORTC RP1335 SPECTA Lung cancer data - Oncomine

  EORTC RP1335 SPECTA Lung cancer data - Oncomine dataset

  Dataset EGAD00001006594

• KiCS cancer panel academic only data

  This data set contains KiCS cancer panel data for academic and for-profit use.

  Dataset EGAD00001009733

• Pan Prostate Cancer Group data

  The Pan Prostate Cancer Group intends to provide breakthrough advances from the analysis of a very large series of Whole Genome DNA data, contributed by many of the leading scientists and clinicians working in prostate cancer genomics generating Whole Genome DNA Sequence (WGS) data from prostate cancer patients. The accumulated data, collected and compared in a common format including common storage, re-analysis through a single pipeline, and investigation to achieve a variety of scientific goals, are presented in this series. This project will provide a global framework for the future analysis of even larger series of genomes as costs of DNA sequencing, storage, and sequence analysis decrease. In addition to these WGS data from different clinical categories, ethnicities, levels of aggressiveness, and disease managed by different treatments with information linked to long-term clinical follow up, we intend to add additional layers of data, including transcriptome and methylation data. The current data series focuses primarily on the analysis of WGS data. For further information, please refer to https://panprostate.org/, and The Pan Prostate Cancer Group Data Sharing Policy, EGAP50000000784.

  Study EGAS00001002876

• Neoantigen-Targeted CD8+ T-Cell Responses 1 With PD-1 Blockade Therapy

  Background: The primary target of T-cell responses induced against cancer cells are peptides derived from non-synonymous mutations presented by HLA (neoantigens). However, the large diversity of HLA alleles and restricted availability of clinical samples have limited the study of the specificity and the evolution over time of the neoantigen-specific T cell responses induced after treatment with immune checkpoint blockade (ICB) immunotherapy. Methods: We applied a newly developed neoepitope-specific T cell isolation technology to perform a longitudinal landscape analysis of the neoepitope-specific T cells in peripheral blood and tumor from 11 patients with metastatic melanoma; 7 with response and 4 with no response to ICB. Briefly, first using computational prediction, the putative neoantigens in each patient were ranked based on affinity for the patient's HLA and expression levels. Then hundreds of barcoded capture reagents consisting of the patient HLA class I subtypes loaded with the corresponding predicted neoantigen were made and used to isolate neoepitope-specific T cells. Once isolated, the TCRs and the barcodes were sequenced. Finally, the tumor reactivity of the isolated neoepitope-specific TCRs (neoTCRs) was assessed upon co-culture of autologous melanoma cell lines from each patient with primary human T cells expressing the neoTCRs generated using a CRISPR-based non-viral gene editing to replace the endogenous TCRs. Results: The tumor mutation burden ranged between 3507 and 177 for patients with response to therapy and 977 to 31 for patients without response to therapy. We screened a median of 172 predicted neoantigen-HLA per patient across their 6 HLA molecules and isolated neoTCRs in all 11 patients. The number of mutations targeted ranged between 13 and 1. We assessed the neoTCR-tumor reactivity in samples from 3 patients with response and 3 patients without response. 39 of the 62 neoTCRs demonstrated specific recognition and cytotoxicity to patient-matched melanoma cell lines. Multiple T cell clonotypes recognized a limited number of mutations in 7 patients with response (median of 41 different neoTCR clonotypes per patient), and the T cell specificities were recurrently detected in the blood and the tumor over time. Samples from 4 patients without response to therapy also demonstrated neoepitope-specific T cell responses in blood and tumor to a similarly restricted number of mutations, but lacked TCR polyclonality (median 6.5 neoTCR clonotypes per patient) and were not recurrently detected in sequential samples. Conclusion: Effective ICB therapy is associated with polyclonal neoepitope-specific T-cell responses in the tumor and blood that recognize a limited number of immunodominant mutations and are recurrently detected over time.

  Study phs003153

• RNA stability controlled by m6A methylation contributes to X-to-autosome dosage compensation in mammals

  In mammals, X-chromosomal genes are expressed from a single copy since males (XY) possess a single X chromosome, while females (XX) undergo X inactivation. To compensate for this reduction in dosage compared to two active copies of autosomes, it has been proposed that genes from the active X chromosome exhibit dosage compensation. However, the existence and mechanism of X-to-autosome dosage compensation are still under debate. Here, we show that X-chromosomal transcripts are reduced in m6A modifications and more stable compared to their autosomal counterparts. Acute depletion of m6A selectively stabilises autosomal transcripts, resulting in perturbed dosage compensation in mouse embryonic stem cells. We propose that higher stability of X-chromosomal transcripts is directed by lower levels of m6A, indicating that mammalian dosage compensation is partly regulated by epitranscriptomic RNA modifications.

  Study EGAS00001007112

• ICGC prostate cancer whole genome mate-pair sequencing

  ICGC prostate cancer whole genome mate-pair sequencing

  Dataset EGAD00001000303

• SNParray copy number dataset

  4 oesophageal cancer derived organoid lines and 2 ovarian cancer derived organoid lines

  Dataset EGAD00010002002

• Amsterdam UMC Head and Neck Cancer Biology and Immunology

  This data access committee oversees data and assesses requests for the Head and Neck Cancer Biology and Immunology lab of Amsterdam UMC, location VUmc.

  Dac EGAC50000000350

• SPECTA Lung cancer DNA FASTQ files

  SPECTA Lung cancer DNA FASTQ files (Illumina TST170 targeted analysis)

  Dataset EGAD00001006223

• Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring

  Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring

  Dataset EGAD00001006237