12214 results for "cancer rna-seq"

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• Proteogenomic Characterization Unveils Biomarkers Associated With Chemoresistance in Muscle Invasive Bladder Cancer

  Cisplatin-based neoadjuvant chemotherapy (NAC) combined with radical cystectomy has been used as a standard of care for patients with clinically non-metastatic muscle invasive urothelial bladder cancer, but 40-50% patients will benefit from the treatment. Molecular subtypes of muscle invasive bladder cancer (MIBC) provide a possible biomarker roadmap that may help identify patients who may or may not respond to NAC. Recently, by integrating Mass Spectrometry-based proteomics, proteogenomic studies from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) have demonstrated the potential of this approach in prioritizing candidate driver genes and facilitating understanding of the chemotherapy resistance mechanisms. To demonstrate the proteogenomic workflow for investigating the mechanisms underlying chemotherapy resistance in MIBC, we conducted proteogenomic characterization of 46 pre- and 14 post- treatment tumors, including whole exome sequencing (WES), mRNA sequencing, Tandem Mass Tag (TMT)-proteomics, or TMT-phosphoproteomic. These samples were selected from an initial cohort of 143 MIBC tissues and filtered by tumor purity, clinical history, pathological response, and proteomic quality control metrics. The final cohort comprised samples from 53 patients, including 45 with both genomic and proteomic data and 8 with genomic data only.Our multi-omics-based clustering reveals subtypes associated with chemotherapy sensitivity. Protein abundance of a short isoform of ATAD1 and RAF family proteins were identified as biomarkers of chemosensitivity which highlights the importance of proteomics data. Integration of proteomic and phosphoproteomic data reveals Wnt signaling via GSK3B-S9 phosphorylation and the JAK/STAT pathway as potential targets to overcome chemoresistance. Correlations between PD-L1 and TROP-2/NECTIN-4 indicate an additive benefit of combination therapy targeting these proteins. Our data analysis clearly demonstrates that proteogenomic plays an important role in uncovering potential resistance mechanisms that operate only at protein and Post-Translational Modification (PTM) levels. Proteomics data can be accessed through PRIDE with ID PXD060290. RNA-seq and whole-exome sequencing (WES) FASTQ files are archived in the dbGaP database.

  Study phs004049

• Pancreatic islets PISA RNA-seq samples

  GWAS have identified more than 700 genetic signals associated with type 2 diabetes (T2D). To gain insight into the underlying molecular mechanisms, we created the Translational human pancreatic Islet Genotype tissue-Expression Resource (TIGER), aggregating >500 human islet RNA-seq and genotyping datasets. We imputed genotypes using 4 reference panels and meta-analyzed cohorts to improve coverage of expression quantitative trait loci (eQTL) and developed a method to combine allele-specific expression across samples (cASE). We identified >1 million islet eQTLs (56% novel), of which 53 colocalize with T2D signals (60% novel). Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identified 8 novel cASE colocalizations, among which an SLC30A8 T2D associated variant. We make all the data available through the open-access TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translate this into therapeutic insight and precision medicine for T2D.

  Study EGAS00001005535

• Effects of Metformin on Transcriptomic and Metabolomic Profiles in Breast Cancer Survivors Enrolled in the Randomized Placebo-Controlled MetBreCS Trial

  RNA from snap-frozen breast tissue biopsies were purified after lysing by tissuelyser (Qiagen) and using RNA Purification Plus Kit (Norgen biotek CORP, 47700) with additional on-column DNase-I treatment (Qiagen, 79254) at 27 °C. RNA purity and integrity (RIN) were quantified using RNA 6000 Nano kit (Agilent Technologies, 5067-1511) on the 4200 TapeStation (Agilent, Santa Clara, USA). Library preparation and 2x75bp paired-end of 160 ng total RNA input was performed using Illumina Stranded Total RNA Prep Ligation kit and Illumina HiSeq4000 system (Illumina, Sand Diego, CA, USA). RNA sequencing data from HiSeq4000 were quality checked and aligned to GRCh38 (GCA_000001405.15) reference genome using HISAT2 2.0.5 and submitted to subread v.1.5.2 for feature counts calculation. Finally, 36 paired biopsies samples (metformin n=26 and placebo n=12) were sequenced and included in the final analyses.

  Dataset EGAD50000001274

• Single cell RNA-seq of two rare cases of human glioblastoma at multiple sampling points

  Glioblastoma is characterized by large cellular diversity whose complexity and organizing principles are only starting to be uncovered. Both neurodevelopment-like and mesenchymal-like cell states have been described in glioblastoma but the nature of the mesenchymal-like cell states remains unresolved. Here, we performed deep single-cell RNA sequencing of two rare glioblastoma cases where tissue could be sampled from tumor core to macroscopically normal cortex with the aim of understanding these tumor cell states.

  Study EGAS50000001030

• RNA-seq profiling of NKX6.1 reporter iPSC lines for isolation and analysis of functionally relevant neuronal and pancreas populations

  We generated human induced pluripotent stem cell (iPSC) lines with a GFP reporter inserted in the endogenous NKX6.1 locus. Characterisation of the reporter lines demonstrated faithful GFP labelling of NKX6.1 expression during pancreas and motor neuron differentiation. We performed three independent in vitro differentiations towards the pancreatic endocrine lineage. We FACS-purified GFP positive and negative cells from stage 7 cultures, and generated Smart-Seq2 RNA-sequencing libraries for the pre-sorted cells, as well as the two GFP-sorted cell populations. Gene expression profiling by RNA-sequencing reveals that the NKX6.1-positive population closely resembles mature human beta cells and the functional evaluation of purified populations shows that the glucose-responsive beta-like cells are enriched within the NKX6.1-positive population. These reporter lines provide a valuable resource to the scientific community for the derivation of functional relevant pancreas and neuronal cell subtypes.

  Dataset EGAD00001003911

• IMCISION RNAseq

  RNA sequencing of 32 primary head and neck squamous cell carcinoma (HNSCC) samples prior to treatment with neoadjuvant anti-PD-1 (n=6) or anti-PD-1 + anti-CTLA-4 (n=26) immunotherapy, and 30 paired on-treatment HNSCC samples (i.e. after neoadjuvant immunotherapy). RNA quantity used: 10ng. Library Preparation Kit: SMART Stranded Total RNA Seq Kit (Takara). Sequencing parameters: NovaSeq 6000, 2x 100 bp. File type: fastQ

  Dataset EGAD00001008127

• RNA sequencing of end-stage kidney disease patients with COVID-19

  This dataset contains paired RNA sequencing data for end-stage kidney disease (ESKD) patients on dialysis. There are two cohorts. The first includes 179 samples from 51 COVID-19 patients recruited during the initial phase of the COVID-19 pandemic (April-May 2020) and 55 non-infected ESKD patients as controls. 17 patients initially recruited as controls as part of the Wave 1 cohort were later infected with COVID-19 in January-March 2021. We acquired a total of 90 samples during the acute infection and convalescent samples for 12 of the 17 patients following the acute COVID-19 episode. RNA-seq counts and full clinical metadata for these cohorts are available without restriction from Zenodo (https://doi.org/10.5281/zenodo.6497251).

  Dataset EGAD00001009752

• single cell data from HPV-positive head and neck cancer patients receiving induction CTLA-4 and PD-1 immune checkpoint blockade

  Baseline and on-treatment tumor samples from human papillomavirus-positive oropharynx cancer patients receiving anti-CTLA-4 and anti-PD-1 immune checkpoint blockade were analyzed by single-cell RNA and TCR sequencing.

  Dataset EGAD50000000487

• Genome_wide_CRISPR_Cas9_screening_of_Human_Organoids

  In this study we will exploit the bacterial clustered regularly interspaced short palindromic repeats (CRISPR) system to perform a genome-wide single-guide RNA (sgRNA) library to screen for genes required for proliferation and survival in human organoids.

  Study EGAS00001001932

• Recurrent loss of heterozygosity correlates with clinical outcome in pancreatic neuroendocrine cancer

  Pancreatic neuroendocrine tumors (pNETs) are uncommon cancers arising from pancreatic islet cells. Here we report analysis of gene mutation, copy number and RNA expression of 57 sporadic well-differentiated pNETs.

  Study EGAS00001003038

• Transcriptome Sequencing PPGL

  RNA library preparation of samples with RNA Integrity Number (RIN) > 5.5 (median 7.1; range 5.6-8.9) was performed as described in the TruSeq Stranded mRNA Library Prep Kit (Illumina, RS-122-2101). Briefly, 0.7-1 µg total RNA PolyA+ fraction was purified and randomly fragmented, converted to double stranded cDNA and processed through subsequent enzymatic treatments of end-repair, dA-tailing, and ligation to adapters. Adapter-ligated library was completed by PCR with Illumina PE primers. The resulting purified cDNA library was applied to an Illumina flow cell for cluster generation and sequenced on an Illumina HiSeq2500 on a 51bp single-read format following manufacturer's protocols. cDNA libraries from FFPE tumors and low integrity RNA’s (RIN<5.5) from FF tumors (median 2.4; range 1-5.5) but % of fragments > 200 nucleotides higher than 20% (median 57.5; range 20-96) were prepared using QuantSeq 3’ mRNA-Seq Library Prep Kit FWD for Illumina (Lexogen, 015) with a UMI Second Strand Synthesis Module for QuantSeq FWD (Lexogen, 081), vendor’s protocol for low input/ low quality/ FFPE RNA using 200-500 ng of total RNA, according to availability, was used as starting material. PCR Add-on Kit for Illumina (Lexogen, 020) was used to adjust the library amplification number of cycles. Libraries were applied to an Illumina flow cell for cluster generation and sequenced on NovaSeq6000. Image analysis, per-cycle basecalling and quality score assignment was performed with Illumina Real Time Analysis software. Demultiplexing of BCL files to FASTQ format was performed with the bcl2fastq Software (Illumina).

  Study EGAS00001006044

• Bulk RNASeq on CD8+CD69+CD103+ and CD8+CD69+CD103- T cells form breast cancer.

  CD8+CD69+CD103+ and CD8+CD69+CD103- T cells were flow sorted from 1 primary triple negative breast cancer, 1 primary HER2 amplified breast cancer, and 1 triple negative liver metastasis. Prior to flow sorting, fresh tumor samples were digested to produce single cell homogenates on the day of surgery. Following RNA extraction, RNASeq was performed using polyA selection.

  Dataset EGAD00001003964

• Omics data of advanced bladder cancer

  To identify the therapeutic targets in a treatment-refractory cancer patient, we performed single-cell RNA sequencing for 3,115 cells from primary bladder cancer (BC159-T#3) and patient-derived xenografts (BC159-T#3-PDX-vehicle and BC159-T#3-PDX-tipifarnib). Matched time-series bulk tumor tissues were also sequenced using whole exome target probe (WES) and whole transcriptome target probe (WTS).

  Dataset EGAD00001005978

• Data for the study "Plasma ctDNA is a tumor tissue surrogate and enables clinical-genomic stratification of metastatic bladder cancer"

  Sequencing data from patients with bladder cancer. BAM files from targeted DNA sequencing of bladder cancer driver genes in 344 circulating tumor DNA and tumor tissue samples. BAM files from whole exome sequencing of 49 circulating tumor DNA and tumor tissue samples. Paired FASTQ files from RNA sequencing of 86 tumor tissue samples.

  Dataset EGAD00001006362

• Circulating tumor DNA, pathological and immunologic responses to neoadjuvant nivolumab or nivolumab plus relatlimab and chemoradiotherapy in resectable esophageal/gastroesophageal junction cancer

  The dataset for the study “Circulating tumor DNA, pathological and immunologic responses to neoadjuvant nivolumab or nivolumab plus relatlimab and chemoradiotherapy in resectable esophageal/gastroesophageal junction cancer” includes 173 bam files from hybrid capture targeted error-correction next-generation sequencing (TEC-Seq) from plasma cell-free DNA and matched white blood cell DNA from 32 individuals with esophageal/gastroesophageal junction cancer, who received immunotherapy-containing regimens.

  Dataset EGAD00001011822

• scRNA-seq of patient-derived PDAC organoids and matched CAFs

  We established direct three-dimensional (3D) co-cultures of primary PDAC organoids and patient-matched CAFs. Single-cell RNA sequencing was performed for three organoid/CAF pairs in mono- and co-culture to uncover transcriptional changes induced by tumor-stroma interaction. Single-cell RNA sequencing data evidenced induction of a pro-inflammatory phenotype in CAFs in co-cultures. Organoids showed increased expression of genes associated with epithelial-to-mesenchymal transition (EMT) in co-cultures and several potential receptor-ligand interactions related to EMT were identified, supporting a key role of CAF-driven induction of EMT in PDAC chemoresistance.

  Study EGAS00001006661

• snRNA-seq analysis in multinucleated myogenic FSHD cells identifies heterogeneous FSHD transcriptome signatures associated with embryonic-like program activation and oxidative stress-induced apoptosis

  The sporadic nature of DUX4 expression in FSHD muscle challenges comparative transcriptome analyses between FSHD and control samples. A variety of DUX4 and FSHD-associated transcriptional changes have been identified, but bulk RNA-seq strategies prohibit comprehensive analysis of their spatiotemporal relation, interdependence and role in the disease process. In this study, we used single-nucleus RNA-sequencing of nuclei isolated from patient- and control-derived multinucleated primary myotubes to investigate the cellular heterogeneity in FSHD. Taking advantage of the increased resolution in snRNA-sequencing of fully differentiated myotubes, two distinct populations of DUX4-affected nuclei could be defined by their transcriptional profiles. Our data provides insights into the differences between these two populations and suggests heterogeneity in two well-known FSHD-associated transcriptional aberrations: increased oxidative stress and inhibition of myogenic differentiation. Additionally, we provide evidence that DUX4-affected nuclei share transcriptome features with early embryonic cells beyond the well-described cleavage stage, progressing into the 8-cell and blastocyst stages. Altogether, our data suggests that the FSHD transcriptional profile is defined by a mixture of individual and sometimes mutually exclusive DUX4-induced responses and cellular state-dependent downstream effects.

  Study EGAS00001007635

• Fastq data for smRNA-Seq assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for smRNA-Seq assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001401

• How to use the EGA search box

  Tips on how to search Tip 1: Use simple and clear keywords No matter what you are searching: a study, a dataset or a committee; the search will look recursively in all the fields of all the entities in the database. Thus, there is no need to specify which type of data you are looking for. Try to use single and specific words and avoid long and complex expressions. Try it out: cancer rna-seq instead of cancer studies using RNA-seq. Tip 2: Narrow your results using search operators Search operators give you more control over the results. They manage the way keywords are used to restrict the search. By default, the search engine applies an OR operator when a space is inserted between two words. Include AND (capitalised) between the keywords in your search in order to show only pages containing both terms. Try it out: Search all the studies based on transcriptomic data, including those ones that use RNA sequencing to obtain this data. Tip 3: Do not worry about details The search engine automatically checks for the most common spelling mistakes of given words and suggests the use of the correct version. It also ignores capital letters and most punctuation so none of these mistakes will hamper the accuracy of your search. Besides, when using a combination of words, the search engine will suggest similar combinations with a higher number of results. Tip 4: Use words that are likely to appear within the text Unfortunately, our search engine is not able to interpret words yet. Therefore, words which do not appear in the body text will not return any result despite them denoting a group of present terms. For instance, if we are looking for studies focused on neurological diseases, using neurological as a keyword would not be the best option. Instead, you should use the name of each neurological disease such as bipolar disorder, schizophrenia or depression. In the same fashion, incomplete words do not return any result. Please include an asterisk (*) before and/or after the incomplete word in order to allow for partial matching. Try it out: canc* instead of canc(without wildcard). Also you can try out *oma, or even *geneti* Tip 5: Narrow down your search by filtering the results You can filter the results by the following options: general, study, and dataset. Under these categories, you will find more sub-filters to refine your search. Make sure that you click on Apply in order to filter the results. You can clear the filtering anytime. Advanced Searches Additional example queries: Search for DUO:0000005 and word lung example query Or write: DUO:0000005 AND lung Search for an exome sequencing study in dbGaP example query Or write: study_type: "exome sequencing" AND repository:dbGaP Search for an exome sequencing study in EGA example query Or write: study_type: "exome sequencing" AND repository:ega Search for a dataset that is at the EGA beacon and with type "Whole genome sequencing" and with number of samples between 100 and 2000 and with technology "Illumina HiSeq 2000" example query Or write: is_in_beacon:true AND dataset_types:"Whole genome sequencing" AND samples:[100 TO 2000] AND dataset_technologies:"Illumina HiSeq 2000" Search for PMIDS example query Or write: pmids:32025007

  Documentation discovery/metadata/search-box

• Breast Cancer in Blacks: Impact of Genomics, Healthcare Use and Lifestyle on Outcomes (BRIGHT)

  Young Black females bear a disproportionate burden of breast cancer (BC) mortality compared to White females and are underrepresented in clinical studies. It remains critical to understand factors that contribute to the high mortality from BC among young Black females in order to improve outcomes. The higher BC mortality rate among young Black females with breast cancer is partially attributed to the disproportionately higher proportions who develop the aggressive triple-negative breast cancer (TNBC). In addition to biologic factors, timely access to care, and lifestyle factors contribute to this disparity. Consequently, we sought to evaluate the interplay between biologic and non-biologic contributors to BC outcomes (i.e., BC disease-free survival (DFS)), and to better characterize the highly aggressive TNBC among young Black females based on distinct molecular subtypes. Ultimately, it is critical to assess both biologic and non-biologic factors to fully understand and address existing health disparities in this population. Through prior and subsequent recruitment of a population-based study of young Black females diagnosed with invasive breast cancer spanning 2009-2016, we: 1) assessed the contribution of biologic and non-biologic factors on BC-DFS observed among young Black females with BC, and 2) investigated molecular features of the subgroup with TNBC. Through this study, consented participants were asked to provide a saliva sample from which DNA was extracted for germline analyses, including germline inherited cancer genetic testing and Infinium Expanded Multi-Ethnic Genotyping Array. Breast cancer tumor specimens were also collected, and tumor RNA was extracted from viable FFPE tumor samples. Tumor RNA analyses included gene expression profiling through NanoString PAM50.Data that will be available through dbGaP for this study include SNP array data and PAM50 data.

  Study phs003466

• Raw sequencing of single-cell RNA-seq data of a phase II clinical trial (NCT03419481)

  This is a single-arm Phase II trial of pembrolizumab in patients with hepatitis B virus-related hepatocellular carcinoma with parallel study on baseline and serial change in the immune environment.

  Study EGAS50000001315

• Expressed fusion transcripts in rare bone tumours

  mRNA-Seq on total RNA from primary osteoblastomas and phosphaturic mesenchymal tumours, focussing on fusion transcript expression

  Dataset EGAD00001000990

• Single-cell atlas of the human healthy airways

  Single cell atlas of human airways from 10 healthy volunteers by 10X Genomics 3’ RNA-seq profiling. 77,969 cells were collected by bronchoscopy at 35 distinct locations, from the nose to the 12th division of the airway tree, either by forceps (46,791 cells), or brush biopsies (31,178 cells).

  Dataset EGAD00001005714

• Human T-bet governs innate and innate-like adaptive IFN-g immunity against mycobacteria.

  We report a patient with mycobacterial disease due to inherited deficiency of the transcription factor T-bet. PBMCs from the patient and his heterozygous father were analyzed with scRNA-seq. these represent 2 single cell RNA samples generated using the 0xGenomics technology and being processed through cell ranger.

  Dataset EGAD00001006623

• (sn)RNA-seq dataset of Multi-modal analysis of pediatric pilocytic astrocytomas reveals tumor location-associated cellular and transcriptional heterogeneity

  Aim: to comprehensively characterize the cellular and transcriptional landscape of pediatric pilocytic astrocytomas across anatomical tumor locations

  Dataset EGAD00001015705