510 results for "cancer rna-seq"

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• Single-cell RNA-seq data from metastatic ovarian cancer for quality control study

  Quality control is a crucial preliminary step in any single-cell RNAseq experiment, where hard thresholds are commonly used. In order to develop a methodology for a more precise cell filtering in the early steps of a scRNAseq data analysis, we collected tissue samples before chemotherapy from 4 patients.

  Study EGAS00001005066

• Cancer and germline exomes, and cancer RNA-seq consisiting of FASTQ paired-end reads from melanoma, lung and colon cancer samples

  Discovery of patient-specific tumor antigens usually requires in vitro-expanded autologous tumor infiltrating lymphocytes (TILs), among which tumor antigen-specific T cells are however often rare, thus limiting sensitivity. We designed in vitro culture conditions to improve the identification of rare tumor antigen-specific CD8 TILs. This innovative yet accessible pipeline allows highly-sensitive identification of tumor antigens and cognate T cell receptors (TCRs), greatly improving the selection of candidates for personalized cancer vaccines and TCR-based cellular immunotherapies.

  Study EGAS00001005513

• RNA-seq analysis of metastatic prostate cancer solid tumor biopsies

  The prevalence and features of treatment-emergent small-cell neuroendocrine prostate cancer (t-SCNC) are not well characterized in the era of modern androgen receptor (AR)–targeting therapy. We sought to characterize the clinical and genomic features of t-SCNC in a multi-institutional prospective study. Patients with progressive, metastatic castration-resistant prostate cancer (mCRPC) underwent metastatic tumor biopsy and were followed for survival. t-SCNC is present in nearly one fifth of patients with mCRPC and is associated with shortened survival.

  Study EGAS00001006369

• Luminal progenitor cell line iHBEC(CD117)

  Basal-like breast cancer originates in luminal progenitors, frequently with an altered PI3K pathway, and focally in close association with genetically altered myoepithelial cells at the site of tumor initiation. The exact trajectory behind this bi-lineage phenomenon remains poorly understood. Here we used a breast cancer relevant transduction protocol including hTERT, shp16, shp53, and PIK3CA(H1047R) to immortalize FACS isolated luminal cells, and we identified a candidate multipotent progenitor. We found that the apparent luminal phenotype of these oncogene transduced progenitors was metastable giving rise to basal-like cells dependent on culture conditions. After culturing the cells for more than 60 passages, cells were subjected to scRNA-seq as well as bulk RNA sequencing of two subpopulations (CD271+ and CD271-).

  Dataset EGAD50000000723

• The Role of E2F4 in Controlling Resistance to Irinotecan (CPT-11) in Human Colon Cancer

  This study reports the results of RNA sequencing (RNA-seq) experiments performed on three isogenic clones of the human HT29 colon cancer cell line, genetically engineered to achieve the selective inactivation of the adenovirus early 2 (E2) gene transcription factor 4 (E2F4) protein, a key functional component of the multimeric transcriptional repression complex known as the dimerization partner (DP), retinoblastoma-like (RB-like), E2F and multi-vulva class B (MuvB) complex (DREAM). In previous studies, we identified E2F4 as a key regulator of colorectal cancer (CRC) resistance to irinotecan (CPT-11), a cytotoxic agent that stands at the backbone of multiple chemotherapy regimens for the treatment of metastatic CRCs. The molecular mechanisms linking E2F4 to irinotecan resistance, however, remain poorly understood. The present study was designed to identify which genes are under the transcriptional control of E2F4, either at baseline or following exposure to SN38 (i.e., the active metabolite of irinotecan, generated in vivo by biotransformation in the liver) in order to clarify the role played by E2F4 in shaping colon cancer resistance to chemotherapy. The cell line used for this study (HT29) is aneuploid and contains three copies of the E2F4 gene, because of a trisomy of chromosome 16, where the E2F4 gene is located (Kawai et al., Genes, Chromosomes & Cancer, 34:1-8, 2002; PMID: 11921276). HT29 cells were infected with lentivirus vectors encoding for CRISPR/Cas9 constructs designed to selectively inactivate the E2F4 gene, using three distinct guide-RNAs (gRNAs), each targeting a different sequence within the proximal exons of the E2F4 gene (exon 1, exon 2). Lentivirus-infected cells were sub-cloned by single-cell fluorescence-activated cell sorting (FACS), based on the differential expression of a fluorescent reporter (EGFP) expressed in tandem with the gRNAs. Isogenic clones (EGFP+) were then screened to identify those with a tri-allelic knock-out, as revealed by both genetic sequencing of the E2F4 gene (revealing the presence of three distinct frameshift mutations) and Western blot (revealing complete loss of E2F4 protein expression). The study includes twelve (n=12) RNA-seq experiments, representative of 3 experimental replicates (i.e., three distinct isogenic clones of the HT29 cell line, each displaying complete loss of E2F4 expression) and 3 negative controls (i.e., three independent preparations of the parent HT29 cell line, infected with a lentivirus vector encoding for a non-targeting gRNA) exposed to 2 distinct in vitro cell culture conditions: a) treatment with SN38 resuspended in dimethyl sulfoxide (DMSO); or b) treatment with DMSO alone (negative control). The in vitro treatment regimen used for SN38 (32 nM, 24 hours) was designed so that the exposure to SN38 experienced in vitro by HT29 cells would mirror the exposure to SN38 experienced in vivo by malignant tissues, as measured, for example, in metastatic CRC patients receiving a standard dose of irinotecan (180 mg/m2) administered by intravenous infusion over 90 minutes (Deyme et al., Cancer Chemotherapy and Pharmacology, 88:247-258, 2021; PMID: 33912999).

  Study phs003560

• 10x genomics single cell RNA-seq and ATAC-seq from 10 pre-menopausal patients fimbriae and ampullary part of the fallopian tube

  The fallopian tube, connecting the uterus with the ovary, is a dynamic organ that undergoes cyclical changes and is the site of several diseases, including serous cancer. Here, we use single-cell technologies to construct a comprehensive cell map of healthy pre-menopausal fallopian tubes, capturing the impact of the menstrual cycle and menopause on different fallopian tube cells at the molecular level. The comparative analysis between pre- and post-menopausal fallopian tubes reveals substantial shifts in cellular abundance and gene expression patterns, highlighting the physiological changes associated with menopause. Further investigations into menstrual cycle phases illuminate distinct molecular states in secretory epithelial cells caused by hormonal fluctuations. The markers we identified characterizing secretory epithelial cells provide a valuable tool for classifying ovarian cancer subtypes.

  Study EGAS50000000628

• UROMOL 2020 - RNA-seq data

  The molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we performed a large integrative multi-omics analysis of patients diagnosed with NMIBC (n=834). Transcriptomic analysis identifies four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provide independent prognostic value beyond established prognostic clinicopathological parameters.

  Study EGAS00001004693

• Single MII oocyte mRNA expression from women

  This dataset contains 14 paired-end FASTQ sequences from mRNA-Seq on single human M-II stage oocytes that were collected from ovarian tissue from unstimulated patients undergoing fertility preservation treatments due to cancer diagnoses, which did not influence ovarian function. Cumulus-oocyte-complexes were matured in vitro according Gruhn et al (Science 365: 1466-1469) and short term flash frozen prior to lysis, RNA extraction, full length cDNA preparation and amplification using the Ultra-low-input SMART-Seq2 v4 kit from Takara Clonetech. Further, these cDNA were used to prepare libraries for sequencing according the Nextera XT DNA library preparation kit from Illumina

  Dataset EGAD00001005971

• RNA-seq data from 224 advanced prostate tumors generated by the West Coast Dream Team

  224 pairs of FASTQ files from metastatic Castration-Resistant Prostate Cancer (mCRPC) sequenced on HiSeq 4000 instruments. Patients were enrolled in the West Coast Dream Team study. Biopsies include various tissue sites including bone, soft tissue, and lymph node.

  Dataset EGAD00001008487

• Combined Tumor and Immune Signals From Genomes or Transcriptomes Predict Outcomes of Checkpoint Inhibition in Melanoma

  Cancer immunotherapy with checkpoint blockade (CPB) leads to improved outcomes in melanoma and other tumor types, but a majority of patients do not respond. High tumor mutation burden (TMB) and high levels of tumor-infiltrating T cells have been associated with response to immunotherapy, and integrative models using DNA and RNA have improved predictions of clinical benefit. However, identification of immune and tumor-intrinsic features in models using DNA or RNA alone have not been comprehensively explored in melanoma. In this study, we sequenced DNA and RNA of tumors from 67 melanoma patients receiving CPB, and aggregated this cohort with previously published data, yielding whole exome sequencing (WES) data for 189 patients and bulk RNA sequencing data for 178 patients. Using these datasets, we derived genomic and transcriptomic factors that predict overall survival (OS) and response to immunotherapy. Using whole exome DNA data alone, we calculated T cell burden (TCB) and B cell burden (BCB) based on rearranged TCR/Ig DNA sequences, and found that melanoma patients with high TMB and either high TCB or high BCB survived longer and had higher response rates, as compared to patients with low TMB and either low TCB or low BCB. Next, using bulk RNA-Seq data, differential expression analysis identified 83 genes which are associated with high or low OS. By combining pairs of immune-expressed genes with tumor-expressed genes, we identified three gene pairs which are associated with response and survival (Bonferroni P<0.05). All three gene pair models were validated in an independent cohort (n=180) (Bonferroni P<0.05). The best performing gene pair model included the lymphocyte-expressed MAP4K1 (Gene ID: 11184) and the transcription factor TBX3 (Gene ID: 6926) which is overexpressed in poorly differentiated melanomas. We concluded that RNA-based (MAP4K1 and TBX3) or DNA-based (TCB and TMB) models combining with immune and tumor measures improve predictions of outcome after checkpoint blockade in melanoma.

  Study phs002683