15056 results for "cancer studies using rna-seq"

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• Extracellular transcriptome in seminal plasma for non-invasive prostate cancer diagnosis

  A diagnostic non-invasive biomarker test for prostate cancer at an early stage, with high sensitivity and specificity, would improve diagnostic decision making. Extracellular RNAs present in seminal plasma might contain biomarker potential for the accurate detection of clinically significant prostate cancer. So far, the extracellular messenger RNA (mRNA) profile of seminal plasma has not been interrogated for its biomarker potential in the context of prostate cancer. Here, we investigate the mRNA transcriptome in seminal plasma samples obtained from prostate cancer patients (n=25), patients with benign prostate hyperplasia (n=26) and individuals without prostatic disease (n=6). Seminal plasma harbors a complex mRNA repertoire that reflects prostate as its tissue of origin. The endogenous RNA content is higher in the prostate cancer samples compared to the control samples. Prostate cancer antigen 3 (PCA3), a long non-coding RNA with prostate cancer-specific overexpression, and ATP-binding cassette transporter 1 (ABCA1), known to be involved in the prostate cancer pathogenesis, were more abundant in the prostate cancer group. In addition, twelve high confidence fusion transcripts could be detected in prostate cancer samples, including the bona-fide prostate cancer fusion transcript TMPRSS2-ERG. Our findings provide proof-of-principle that the extracellular transcriptome of seminal plasma can reveal information of an underlying prostate cancer.

  Study EGAS00001005277

• Constructing database of magnetic resonance imaging of the brain and the ancillary clinical information for multisite collaboration studies: a dataset from Schizophrenia individuals

  Previously there was no neuroimaging database available for research community that incorporated a large Japanese sample of healthy people and patients with neuropsychiatric disorders. Establishing such a database will enable large-scale, neuroimaging-based investigations on pathophysiology of neuropsychiatric disorders by simply using the large data pool or by combining it with investigators' own data sets.

  Study JGAS000043

• Constructing database of magnetic resonance imaging of the brain and the ancillary clinical information for multisite collaboration studies: a dataset from normal individuals

  Previously there was no neuroimaging database available for research community that incorporated a large Japanese sample of healthy people and patients with neuropsychiatric disorders. Establishing such a database will enable large-scale, neuroimaging-based investigations on pathophysiology of neuropsychiatric disorders by simply using the large data pool or by combining it with investigators' own data sets.

  Study JGAS000042

• Constructing database of magnetic resonance imaging of the brain and the ancillary clinical information for multisite collaboration studies: a dataset from Bipolar disorder individuals

  Previously there was no neuroimaging database available for research community that incorporated a large Japanese sample of healthy people and patients with neuropsychiatric disorders. Establishing such a database will enable large-scale, neuroimaging-based investigations on pathophysiology of neuropsychiatric disorders by simply using the large data pool or by combining it with investigators' own data sets.

  Study JGAS000045

• Constructing database of magnetic resonance imaging of the brain and the ancillary clinical information for multisite collaboration studies: a dataset from Depression individuals

  Previously there was no neuroimaging database available for research community that incorporated a large Japanese sample of healthy people and patients with neuropsychiatric disorders. Establishing such a database will enable large-scale, neuroimaging-based investigations on pathophysiology of neuropsychiatric disorders by simply using the large data pool or by combining it with investigators' own data sets.

  Study JGAS000044

• Medulloblastoma dataset

  This dataset contains a tumor + normal DNA sequence data and tumor RNA seq data for a medulloblastoma patient.

  Dataset EGAD50000000384

• DAC Ghent University - Department of Movement and Sports Sciences

  DAC of Ghent University for RNA-seq data of human skeletal muscle biopsies collected at the Department of Movement and Sports Sciences

  Dac EGAC50000000263

• RNAseq counts

  RNA-seq data from ILC samples. This dataset includes raw, unnormalized counts per gene, per sample.

  Dataset EGAD50000000826

• DAC - Department of Periodontology, University of Gothenburg, Sweden

  Data Access Committee to manage external requests. Project: RNA-seq data from soft tissue biopsies harvested from dental implant sites with peri-implantitis

  Dac EGAC50000000241

• Single cell RNA-Seq of Clear Cell Sarcoma of the Kidney

  Dataset EGAD00001007498

• Long-term organoid culture of a small intestinal neuroendocrine tumor

  organoid and tissue bam files from rna-seq experiment

  Dataset EGAD00001010175

• Transcriptome sequencing of cancer cell lines

  This dataset contains RNA sequencing data for 675 cancer cell lines. RNA libraries were made with the TruSeq RNA Sample Preparation kit (Illumina) according to the manufacturer protocol. The libraries were sequenced on an Illumnia HiSeq 2000

  Dataset EGAD00001000725

• COLONOMICS small RNA sequencing

  This dataset consists of SOLiD small RNA-seq of 250 colorectal samples: 100 tumor tissue samples, 100 normal tissue samples (adjacent to tumor sites) and 50 matched control samples of healthy individuals. CSfasta and qual files converted to single fastq files prior to uploading.

  Dataset EGAD00001004827

• Genomic (WGS) data for the validation of the glioblastoma progression study (GBMatch).

  43 low-coverage genomes derived from fresh-frozen glioblastoma tumor samples. These genomes have been produced for validation purposes and match the corresponding RRBS and RNA-seq profiles in that DNA and RNA was extracted from the same tumor samples.

  Dataset EGAD00001004077

• Transcriptome (RNA-seq) data for the validation of the glioblastoma progression study (GBMatch).

  37 transcriptomes derived from fresh-frozen glioblastoma tumor samples. These transcriptomes have been produced for validation purposes and match the corresponding RRBS and WGS profiles in that DNA and RNA was extracted from the same tumor samples.

  Dataset EGAD00001004076

• Identifying aberrant splicing isoforms and potential neoantigens in non-small cell lung cancer

  To identify aberrant splicing isoforms and potential neoantigens, we performed full-length cDNA sequencing of seven non-small cell lung cancer specimens using a long-read sequencer MinION. We detected aberrant splicing isoforms using our bioinformatics pipeline and constructed a comprehensive catalogue.

  Study JGAS000245

• A Phase II Neoadjuvant Study of Palbociclib in Combination with Letrozole and Trastuzumab as Neoadjuvant Treatment of Stage II-III ER+ HER2+ Breast Cancer (PALTAN)

  Women with early stage ER+/HER2+ breast cancer (BC) are less likely to achieve pathological complete response (pCR) after chemotherapy with standard of care dual HER2 blockade than patients with ER-/HER2+ BC. Additionally, the toxicity burden of standard systemic therapy is high. Thus, this single arm phase 2 clinical trial investigated a novel de-escalation regimen with trastuzumab, letrozole, and palbociclib in those with early stage ER+/HER2+ BC. The aim was to determine if this treatment regimen will achieve similar pCR rates as conventional treatment and spare women the toxicity burden of regular treatments. The primary endpoint was pCR after 16 weeks of treatment with trastuzumab, letrozole, and palbociclib. Patients with newly diagnosed ER+ HER2+ invasive BC with clinical stages II and III were eligible for this protocol. Research biopsies were performed during the treatment course for whole exome and RNA sequencing, PAM50 molecular subtyping, and Ki67 assessment using immunohistochemistry for complete cell cycle arrest (CCCA: Ki67 ≤2.7%). Results showed a pCR of 7.7% and a rate of residual cancer burden at 0 or I of 38.5%. CCCA was observed in 85% at Cycle 1 day 15 post palbociclib, trastuzumab, and letrozole treatment (C1D15), compared to 27% at surgery after palbociclib was discontinued. PAM50 subtyping identified 31.2% HER2-E, 43.8% Luminal B, 25% Luminal A. 161 genes were differentially expressed comparing C1D15 to baseline. Whole exome and RNA sequencing data will be available through dbGaP.

  Study phs003147

• CATNON: IDH-mutant astroctyoma RNA FASTQ

  Raw fastq files obtained by RNA sequencing 138 IDH-mutant astrocytomas included in the CATNON trial. RNA was extracted from formalin-fixed paraffin-embedded (FFPE) tissue blocks using the RNeasy FFPE kit. RNA sequencing was performed on an Illumina NovaSeq 6000 (GenomeScan BV, Leiden, The Netherlands) with 150bp paired-end reads including UMI tags.

  Dataset EGAD50000000558

• Modulation of the peripheral blood immune cell transcriptome by vitamin D3 supplementation in people with a first demyelinating event: a randomized placebo-controlled trial

  Vitamin D deficiency is a risk factor for developing multiple sclerosis (MS). Both in vitro and animal studies suggest an immunomodulatory effect of vitamin D. The PrevANZ trial, a phase IIb randomized placebo-controlled trial of oral vitamin D3 supplementation in people with a first demyelinating event (FDE), was conducted to determine if supplementation can prevent recurrent disease activity in this cohort at high risk of developing definite MS. As a sub-study of this trial, we used whole blood transcriptomic analyses to investigate the effect of vitamin D3 supplementation on peripheral immune cells in people with an FDE, and to gain insight into potential mechanisms by which vitamin D3 may regulate MS risk and disease activity. The PrevANZ trial randomized participants to 1000 IU, 5000 IU or 10,000 IU daily of oral vitamin D3 or placebo. Peripheral blood was collected at baseline and 12 weeks in PAXgene Blood RNA tubes. Transcriptomic datasets were generated by RNA sequencing.

  Study EGAS00001007346

• PsychENCODE Consortium: Epigenetic and Transcriptional Dysregulation in Autism Spectrum

  Our current understanding of autism spectrum disorders (ASD) delineates a highly heritable, yet etiologically heterogeneous disease. Forward genetic approaches to find disease associated mutations or common variation have been successful and continue to offer considerable power. Yet, given the accumulating evidence for very significant heterogeneity and environmental influences, complementary approaches to classic forward genetics become necessary. Genetic polymorphism and mutation data to date have identified dozens of causal or contributory variants, yet our preliminary data from autism brain suggest that common molecular pathways are involved in a significant subset of cases. This convergence at the tissue level suggests that other mechanisms, specifically epigenetic changes, combined with genetic background, are contributing to such final common pathways. We further tested this hypothesis by taking a comprehensive and integrative genome-wide approach to assessing brain gene-expression, miRNA levels and the related, causal epigenetic mechanisms in ASD etiology. We performed RNA-seq analyses of four cerebral cortical regions and cerebellum from ASD cases and controls, to assess mRNA, miRNA, and splicing isoform regulation. In parallel, we identified key differences in chromatin state and DNA methylation across multiple brain regions in the same ASD and control individuals used in the expression analyses using ChIP-Seq and MeDIP. We assessed the mechanisms by which changes in DNA methylation, histone modification, and DNA sequence contribute to the observed differences in gene expression. This work, which represents an unprecedented effort to unify these often disparate data (usually produced without integration in mind), delineates potential shared molecular pathways in ASD and the underlying mechanism of these differences at the level of miRNA, the chromatin regulatory apparatus, and DNA methylation. The following substudies are part of the PsychENCODE release at dbGaP and offer additional molecular data: PsychENCODE: RNA-Sequencing - SRRM4 Splicing Study phs000872 PsychENCODE: Global Changes in Patterning, Splicing and lncRNAs phs001061 PsychENCODE: Chromatin Contact Map in Fetal Cortical Laminae phs001190 PsychENCODE: Epigenetic Dysregulation in Autism Spectrum Disorder phs001220

  Study phs001022

• Sperm sequencing reveals extensive positive selection in the human germline -WGS

  Mutations that occur during human ageing in the cell lineages of sperm or eggs have the potential to be transmitted to offspring. In males, positive selection of driver mutations during spermatogenesis is known to increase the birth prevalence of certain developmental disorders and cancer predisposition syndromes. However, direct observation of the scope of this selection in sperm has been limited by the error rates of sequencing technologies. Using the duplex sequencing method known as NanoSeq, we sequenced bulk sperm samples from individuals aged 24 to 75 years. Our findings revealed a linear accumulation mutations per year and mutational signatures consistent with pedigree studies. Deep targeted and deep exome NanoSeq of sperm samples identified genes subject to significant positive selection in the male germline, which are linked to diverse cellular pathways including RAS/MAPK and BMP signaling. Strikingly, nearly all positively selected genes are associated with developmental or cancer predisposition disorders in children. We find that this effect drives an elevated risk of known likely disease-causing mutations in sperm across a wide age range. This implies that the disorders attributed to these genes likely exhibit elevated birth prevalence in human populations, particularly among older fathers. These findings shed light on the dynamics of germline mutations and highlight an increased disease risk for children born to fathers of advanced age.

  Dataset EGAD00001015592

• Sperm sequencing reveals extensive positive selection in the human germline -NanoSeq

  Mutations that occur during human ageing in the cell lineages of sperm or eggs have the potential to be transmitted to offspring. In males, positive selection of driver mutations during spermatogenesis is known to increase the birth prevalence of certain developmental disorders and cancer predisposition syndromes. However, direct observation of the scope of this selection in sperm has been limited by the error rates of sequencing technologies. Using the duplex sequencing method known as NanoSeq, we sequenced bulk sperm samples from individuals aged 24 to 75 years. Our findings revealed a linear accumulation mutations per year and mutational signatures consistent with pedigree studies. Deep targeted and deep exome NanoSeq of sperm samples identified genes subject to significant positive selection in the male germline, which are linked to diverse cellular pathways including RAS/MAPK and BMP signaling. Strikingly, nearly all positively selected genes are associated with developmental or cancer predisposition disorders in children. We find that this effect drives an elevated risk of known likely disease-causing mutations in sperm across a wide age range. This implies that the disorders attributed to these genes likely exhibit elevated birth prevalence in human populations, particularly among older fathers. These findings shed light on the dynamics of germline mutations and highlight an increased disease risk for children born to fathers of advanced age.

  Dataset EGAD00001015590

• Sperm sequencing reveals extensive positive selection in the human germline -TargetedNanoSeq

  Mutations that occur during human ageing in the cell lineages of sperm or eggs have the potential to be transmitted to offspring. In males, positive selection of driver mutations during spermatogenesis is known to increase the birth prevalence of certain developmental disorders and cancer predisposition syndromes. However, direct observation of the scope of this selection in sperm has been limited by the error rates of sequencing technologies. Using the duplex sequencing method known as NanoSeq, we sequenced bulk sperm samples from individuals aged 24 to 75 years. Our findings revealed a linear accumulation mutations per year and mutational signatures consistent with pedigree studies. Deep targeted and deep exome NanoSeq of sperm samples identified genes subject to significant positive selection in the male germline, which are linked to diverse cellular pathways including RAS/MAPK and BMP signaling. Strikingly, nearly all positively selected genes are associated with developmental or cancer predisposition disorders in children. We find that this effect drives an elevated risk of known likely disease-causing mutations in sperm across a wide age range. This implies that the disorders attributed to these genes likely exhibit elevated birth prevalence in human populations, particularly among older fathers. These findings shed light on the dynamics of germline mutations and highlight an increased disease risk for children born to fathers of advanced age.

  Dataset EGAD00001015591

• ATAC-seq data in normal colon mucosa

  This dataset includes ATAC-seq data generated in normal colon mucosa obtained in four healthy volunteers during colonoscopy indicated for colorectal cancer screening. Subjects had no lesions in the colon. Also includes one frozen sw480 colon adenocarcinoma cell line sample for piloting the protocol

  Study EGAS00001005281

• Genomic and epigenomic study of Japanese renal cell carcinoma including WGS, RNA-seq, ATAC-seq, and methyl-seq

  We performed whole-genomic and transcriptomic sequencing of more than 100 Japanese renal cell carcinoma (RCC) cases, including clear cell RCC, papillary RCC, chromophobe RCC, and TFE3-translocated RCC. In addition, we conducted epigenome sequencing analyses: the assay for transposase-accessible chromatin sequencing (ATAC-seq) and enzymatic methyl sequencing.

  Study EGAS00001006919

• Shallow whole genome sequencing of ctDNA samples from DETECT study

  A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival from the paper "A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival", by Beddowes et al. Mol.Onc.

  Study EGAS50000000911

• Establishment and characterization of a new Pseudomonas aeruginosa infection model using 2D airway organoids and dual RNA sequencing

  Study EGAS00001007463

• Highlights from 2025: Our top 10 requested studies

  In 2025, as in previous years, EGA has facilitated the reuse of numerous datasets spanning a broad range of research and healthcare topics. To reflect on this activity, we would like to highlight the top 10 studies behind the most requested datasets of last year. Notably, the vast majority of these highly requested datasets are cancer-focused, particularly involving the study of immune checkpoint inhibitor therapies. Immune checkpoint inhibitors (ICIs) have become one of the most transformative advances in modern cancer therapy. These monoclonal antibodies enhance antitumor immune responses by targeting inhibitory immune checkpoint molecules. While ICIs have led to remarkably favorable and durable responses in some patients, treatment outcomes vary widely. This variability has fueled intense research efforts aimed at understanding resistance mechanisms, exploring combination therapies, and discovering predictive biomarkers to better stratify patients and guide treatment decisions. Study Title Disease 1 EGAS00001005503 Integrated genomic analyses reveal molecular correlates of clinical response and resistance to atezolizumab in combination with bevacizumab in advanced hepatocellular carcinoma Liver Cancer 2 EGAS00001005013 Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer Lung Cancer 3 EGAS00001004809 BIOKEY: A single-cell catalogue of the dynamic changes underlying Checkpoint Immunotherapy response in Early Breast Cancer Breast Cancer 4 EGAS50000000138 BIOKEY: Immune heterogeneity in small cell lung cancer and vulnerability to immune checkpoint blockade Lung Cancer 5 EGAS50000000497 Bladder cancer subtyping study across 4 atezo clinical trials Bladder Cancer 6 EGAS50000000689 MOSAIC - Multi-Omics Spatial Atlas In Cancer Cancer Atlas 7 EGAS00000000083 METABRIC (Breast cancer - genome and transcriptome) Breast Cancer 8 EGAS00001005702 Human genomic and phenotypic synthetic data for the study of rare diseases Synthetic data 9 EGAS00001002556 TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells Bladder Cancer 10 EGAS00001004353 Molecular subsets in renal cancer determine outcome to checkpoint and angiogenesis blockade Renal Cancer The most requested dataset of the year was EGAD00001008128. It belongs to a study that analyzed 358 liver cancer patients enrolled in clinical trials and treated with the combination of atezolizumab (anti–PD-L1) and bevacizumab (anti-VEGF), atezolizumab alone, or sorafenib. The study highlights how bevacizumab enhances anti-PD-L1 effect and identifies candidate biomarkers to predict treatment response. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and the third leading cause of cancer-related death worldwide [1]. Because symptoms often appear late, many patients are diagnosed at advanced stages, when curative options are no longer viable. For many years, sorafenib—a multikinase inhibitor approved in 2007—was the only systemic treatment available. Although numerous clinical trials followed, it was not until a decade later that additional therapies showed meaningful clinical benefit. Among these advances, immunotherapy emerged as a promising first-line option [2]. In particular, the combination of atezolizumab and bevacizumab demonstrated improved survival in patients with advanced HCC, reshaping the treatment landscape. However, treatment efficacy remains limited by the complex and diverse hepatic microenvironments that influence immune responses, as well as by high intratumoral heterogeneity. Identifying robust predictors of treatment response is critical to enable effective patient stratification and maximize the benefits of these therapies [2]. The continued demand for these datasets highlights the interest and critical role of data reuse in deepening our understanding of cancer, accelerating the development of more effective therapies, and improving patient outcomes. By providing secure access to high-quality genomic and clinical data, EGA acts as a catalyst for biomedical progress. References Sung, Hyuna, et al. "Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries."CA: a cancer journal for clinicians 71.3 (2021): 209-249. Ladd, Alexandra D, et al.“Mechanisms of drug resistance in HCC.” Hepatology 79(4) (2024): 926-940

  Blog top-10-studies-2025

• Prader-Willi Syndrome and Early-onset Morbid Obesity Natural History Protocol

  This observational study will involve the comprehensive assessment of the medical, behavioral and nutritional history and the clinical features of individuals with Prader-Willi syndrome and individuals with features of PWS-like/EMO. A blood sample will be obtained from the participants in order to create a DNA and RNA repository. In those PWS participants with a known deletion a blood sample will be collected for DNA in order to perform array comparative genome hybridization (aCGH) microarray or Methylation-Specific Multiplex Ligation-dependent Probe Amplification (MS-MLPA) studies to characterize the extent of the deletion. DNA samples will be sent to the Consortium Center at Baylor College of Medicine for the performance of the aCGH studies and to either Dr. Driscoll or Dr. Butler lab for MS-MLPA analysis. No drugs or treatments will be administered through this protocol. Our goal is to enroll as many participants as possible over a 8 year period. Currently we have enrolled 297 total subjects of which 265 have PWS and 32 EMO. Our original goal was to have enrolled over the first 5 years a clinical database of 200 individuals with PWS and 100 with EMO. We have exceeded expectations in PWS enrollment, but have fallen short in the enrollment of individuals with EMO. Therefore, we would like to reset our goals. We now propose to have an enrollment goal of 400 total subjects of which 350 will have PWS and 50 will have EMO. Eligible participants will be initially enrolled in the natural history study from the 4 clinic sites currently involved with PWS (University of Florida, Kansas University Medical Center, Vanderbilt University and University of California at Irvine). Participants assessed will serve to provide a background of information and a willing cohort for future interventional studies. All participants will have had standard genetic testing at a commercial laboratory prior to entry into the study. The PWS participants will be classified into one of the 3 main molecular classes (deletion, UPD and ID). The EMO participants will have had laboratory testing ruling out PWS and chromosomal aneuploidy (e.g., trisomy 21, Klinefelter syndrome, etc.). Going forward we feel it is important that all newly recruited EMO subjects have an aCGH as part of their evaluation so we can identify those with discrete deletions, duplications or copy number variants (CNV) and compare them to those without aCGH abnormalities. The participants will be assessed annually (0-3 years of age) or biennially (> 3 years) in the Clinical Research Center (or equivalent facility) using standardized protocol including photographs for documentation purposes to compare the evolution of the clinical phenotype.

  Study phs000575

• 28 RNA-Seq from CAF-S1, CAF-S4 and EPCAM cells coming from Primary tumors and Lymph nodes of 5 patients)

  Dataset EGAD00001005744

• RNAseq RPKM

  RNA-seq data from ILC samples. This dataset includes counts normalized for sequencing depth and gene length.

  Dataset EGAD50000000828

• scRNA primaries

  Single cell RNA-seq for primary samples

  Dataset EGAD00001006135