14982 results for "cancer studies using rna-seq"

in 23.89 milliseconds.

• scMultiomics of ARID1B+/+ (control) and ARID1B+/- human telencephalic organoids at D120

  This dataset contains scMultiomics (scRNAseq + scATACseq) data of human telencephalic organoids, at day 120, from 3 different sequencing runs (libraries), as follows (please see cell line clone nomenclature in original publication): 1. Library 233269(RNA)/235293(ATAC): Pat.1 ARID1B+/- clone 1a (9 pooled organoids). 2. Library 233270(RNA)/235294(ATAC): HD.1 ARID1B+/+ clone 3a (9 pooled organoids). 3. Library 233271(RNA)/235295(ATAC): HD.1 ARID1B+/- clone 3b (8 pooled organoids).

  Dataset EGAD50000000499

• Single cell RNA sequencing of co-culture of human organoids with polarized pro-inflammatory (M1) or anti-inflammatory (M2) macrophages

  Human intestinal organoids co-cultured with pro-inflammatory (M1) or anti-inflammatory (M2) human macrophages for 48 hours. 3 days after the co-culture alive cells were sorted and processed for single cell RNA sequencing

  Study EGAS50000000467

• Bulk RNA sequencing of 36 multi-region IPMN–PDAC tumours comprising 160 sequencing runs

  This dataset contains bulk RNA sequencing data generated from 36 multi-region tumour samples obtained from patients with intraductal papillary mucinous neoplasms (IPMN) and associated pancreatic ductal adenocarcinoma (PDAC). A total of 160 sequencing runs are included. Libraries were prepared from poly(A)-selected RNA and sequenced on an Illumina platform. The data are provided as raw sequencing files for downstream transcriptomic analyses.

  Dataset EGAD50000002215

• Whole genome and RNA sequencing of cutaneous melanoma metastases

  Whole genome sequencing of cutaneous melanoma skin and brain metastases and matched normal DNA, as well as RNA sequencing of material from the skin and brain metastases. In addition, RNA sequencing was performed for Dabrafenib and Trametinib treated patient-derived xenografts, together with untreated and vehicle treated controls.

  Dataset EGAD00001004130

• RNA sequencing of SCLC tumor/normal sample pairs and cell lines

  RNA sequencing of SCLC tumor/normal sample pairs and cell lines

  Dataset EGAD00001000223

• RNA sequencing of AD, MCI and control OM cells

  Total RNA sequencing of cultured OM cells derived from patients with Alzheimer's disease (AD), individuals with mild cognitive impairment (MCI) and cognitively healthy controls.

  Dataset EGAD00001008707

• RNA Sequencing of paediatric patients with B lymphoblastic leukemia

  RNA sequencing was performed on 54 bone marrow samples at diagnosis of paediatric patients with B lymphoblastic leukemia.

  Dataset EGAD00001005103

• Total RNA sequencing in M1911

  The dataset comprises total RNA sequencing data obtained from two samples of testicular tissue from the individual M1911, who was diagnosed with meiotic arrest.

  Dataset EGAD00001008639

• Plasma RNA sequencing

  Plasma RNA sequencing (consists of 70 cases)

  Dataset EGAD00001008836

• RNA sequencing of human ILC3 from lymphoid organs and blood

  Rna sequencing of purified human group 3 innate lymphoid cells from non-reactive lymph nodes and spleen, inflamed tonsils and peripheral blood.

  Dataset EGAD00001003704

• Single-cell RNA and TCR sequencing of 40 advanced HCC biopsies.

  Single-cell RNA and TCR sequencing of 40 advanced HCC pre-treatment biopsies from 38 patients.

  Dataset EGAD00001011347

• RNAseq cutaneous and uveal melanoma liver metastases

  RNA sequencing analyses of tumor liver metastases from untreated cutaneous melanoma (CM) and uveal melanoma (UM) patients.

  Study EGAS00001004794

• Impact of BRCA mutation type in non-tumorous breast tissue transcriptome

  To investigate the transcriptomic difference between BRCA1 vs. BRCA2 carriers, RNA sequencing was carried out.

  Study EGAS00001004890

• PAK4 inhibition improves PD-1 blockade immunotherapy

  Introduction with rationale and aims for study Immune checkpoint blockade therapies have significantly altered the current landscape of cancer treatment. However, this immunotherapy still fails more often than it succeeds. There are now evidences that the lack of tumour infiltration by immune cells is the main mechanism of primary resistance to PD‐1 blockade therapies for cancer. It has been postulated that cancer cell‐intrinsic mechanisms may actively exclude T cells from tumours, suggesting that the finding of actionable molecules that could be inhibited to increase T cell infiltration may synergize with checkpoint inhibitor immunotherapy. With the idea of finding potential drivers of immune exclusion, we performed RNA sequencing analysis of biopsies from melanoma patients and compared the transcriptomic differences of samples that where infiltrated with those that did not have immune infiltration. Methods RNAseq analysis of gene expressions on biopsies from melanoma patients treated with checkpoint blockade were analysed. We focused on the variable of "infiltration: yes or no,", e.g. tumors that were well infiltrated by immune cells with those that kept immune cells out. Sequencing revealed a list of genes whose expression differed between the infiltrated and noninfiltrated tumors. The kinase PAK4 stood out as a good candidate for inhibition treatment in the future as it was consistently enriched in the samples without immune infiltration. To test whether immunotherapy would work better if we deleted PAK4, we first knocked out PAK4, using CRISPR‐Cas9, in the ‐resistant melanoma cell line, B16. Then they injected the melanoma cells into mice and observed that PAK4 KO tumours now responded to PD‐1 blockade. In order to elucidate whether pharmacological inhibition of PAK4 could recapitulate the results observed in the B16 PAK4 KO tumours, we obtained the PAK4 inhibitor, KPT-9274, from Karyopharm Therapeutics. Indeed, inhibiting PAK4 in combination with anti‐PD‐1 immunotherapy significantly slowed the growth of the B16 melanomas more than either drug alone. Results and Conclusions Transcriptomic analysis of melanoma tumors that were well infiltrated by immune cells with those that kept immune cells out revealed a list of genes whose expression differed between the infiltrated and non-infiltrated tumours. The result suggests that p21 activated kinase 4 (PAK4) is enriched in non-responding tumour biopsies with low T cell and dendritic cell infiltration. In addition, PAK4 decreased WNT activity, a signalling pathway that has previously been involved in immune exclusion. In mouse models, genetic deletion of PAK4 increased T cell infiltration and reversed resistance to PD‐1 blockade in a CD8 T cell-dependent manner. Furthermore, combination of with the PAK4 inhibitor, KPT-9274, improved anti‐tumour responses compared to anti‐PD‐1 alone. Therefore, high PAK4 expression is correlated with low T cell and dendritic cell infiltration and lack of response to PD‐1 blockade, which could be reversed with PAK4 inhibition. The data establish a rationale for targeting this kinase with inhibitors in combination with immune checkpoint inhibitors for patients. Future work and data that we can anticipate for this study Oncogenic signalling pathways and specially the WNT signalling pathway, have been associated with lack of immune infiltration and resistance to PD‐1 blockade therapies. Here, we show that PAK4 overcome resistance to PD‐1 blockade while significantly decreases WNT signalling activity. Therefore, it constitutes the first potential druggable target that is able to reverse oncogenic driven immune cell exclusion. However, the fully mechanism whereby PAK4 sensitizes tumours to immunotherapy remains to be fully elucidated. It is necessary to address whether PAK4 inhibition overcomes resistance through WNT signalling inhibition or if other signalling pathways are involved in the observed phenotype.

  Study phs001919

• Combined – whole blood and skin fibroblasts - transcriptomic analysis in Psoriatic arthritis.

  Whole blood RNA sequencing was performed longitudinally in 27 subjects with PsA at the beginning, one month and six months after treatment and response to therapy was defined at 6 months. As control groups 7 healthy individuals and 9 subjects with rheumatoid arthritis were recruited combined with public RNA-sequencing datasets from patients with psoriasis and systemic lupus erythematous. Differential expression analysis and weighted gene co-expression network analysis were performed to identify gene expression signatures, while deconvolution and flow cytometry to characterize the peripheral blood immune cell profile. RNA sequencing of skin fibroblasts was performed in a subset of affected (n=3) and healthy individuals (n=3) combined with CellChat to identify the blood-skin fibroblasts interaction network.

  Study EGAS00001006288

• MILK-Omics: Systems Biology of Human Milk and Its Links to Maternal and Infant Health

  The primary objective of the project is to generate a systems-level view of human milk in the context of healthy mothers and their term infants. The study uses biospecimens and clinical data from the Mothers and Infants LinKed for Healthy Growth Study (MILk Study), a prospective observational cohort of approximately 500 exclusively breastfeeding women and their infants who are followed to 6 months of age. The project focuses on mature milk samples collected at 1 month postpartum and infant gut microbiome samples collected at 1 and 6 months of age. Specific Aim 1 is to identify maternal genetic and clinical factors that shape human milk gene expression. Using bulk and single-cell RNA sequencing of the milk cell pellet and genotypes from maternal DNA, we will identify novel genetic determinants of the milk transcriptome and assess potential modification of these genetic associations by gestational weight gain, diet, and other clinical factors. Specific Aim 2 is to describe key features of the normative human milk biosystem and their interactions with one another. Specifically, machine learning techniques will be used to characterize interaction networks and correlational structures among the following features of human milk: transcriptomics, microbiomes, oligosaccharides, metabolomics, lipidomics, and milk macronutrient composition. Specific Aim 3 is to establish how the milk biosystem is related to variation in infant gut microbiomes and health. dbGaP will house the maternal genotype and milk transcriptomics data.The infant microbiome sequence data are associated with BioProject PRJNA1019702.

  Study phs003408

• Massively parallel nanowell-based single-cell gene expression profiling

  Technological advances have enabled transcriptome characterization of cell types at the single-cell level providing new biological insights. New methods that enable simple yet high-throughput single-cell expression profiling are highly desirable. Here we report a novel nanowell-based single-cell RNA sequencing system, ICELL8, which enables processing of thousands of cells per sample. The system employs a 5184-nanowell-containing microchip to capture ~1300 single cells and process them. Each nanowell contains preprinted oligonucleotides encoding poly-d(T), a unique well barcode, and a unique molecular identifier. The ICELL8 system uses imaging software to identify nanowells containing viable single cells and only wells with single cells are processed into sequencing libraries. Here, we report the performance and utility of ICELL8 using samples of increasing complexity from cultured cells to mouse solid tissue samples. Our assessment of the system to discriminate between mixed human and mouse cells showed that ICELL8 has a low cell multiplet rate (< 3%) and low cross-cell contamination. We characterized single-cell transcriptomes of more than a thousand cultured human and mouse cells as well as 468 mouse pancreatic islets cells. We were able to identify distinct cell types in pancreatic islets, including alpha, beta, delta and gamma cells. Overall, ICELL8 provides efficient and cost-effective single-cell expression profiling of thousands of cells, allowing researchers to decipher single-cell transcriptomes within complex biological samples.

  Study EGAS00001002320

• Characterization of HCV-specific CD4 T cells during DAA-Therapy

  Background: Chronic HCV-infection is characterized by a severe impairment of HCV-specific CD4 T cell help that is driven by chronic antigen stimulation. We aimed to study the fate of HCV-specific CD4 T cells after viral elimination. Methods: HCV-specific CD4 T cell responses were longitudinally analyzed using MHC class II tetramer-technology, multicolor flow cytometry and RNA sequencing in a cohort of chronically HCV-infected patients undergoing therapy with direct-acting antivirals. In addition, HCV-specific neutralizing antibodies and CXCL13 levels were analyzed. Results: We observed that the frequency of HCV-specific CD4 T cells increased within two weeks after initiation of DAA therapy. Multicolor flow cytometry revealed a downregulation of exhaustion and activation markers and an upregulation of memory-associated markers. While cells with a Th1 phenotype were the predominant subset at baseline, cells with phenotypic and transcriptional characteristics of follicular T helper cells increasingly shaped the circulating HCV-specific CD4 T cell repertoire, suggesting antigen-independent survival of this subset. These changes were accompanied by a decline of HCV-specific neutralizing antibodies and the germinal center activity. Conclusion: We identified a population of HCV-specific CD4 T cells with a follicular T helper cell signature that is maintained after therapy-induced elimination of persistent infection and may constitute an important target population for vaccination efforts to prevent re-infection and immunotherapeutic approaches for persistent viral infections.

  Study EGAS00001003950

• Cisplatin increases sensitivity to FGFR inhibition in patient-derived xenograft models of lung squamous cell carcinoma

  Lung squamous cell carcinoma (SqCC) is a molecularly complex and genomically unstable disease. No targeted therapy is currently approved for lung SqCC, although potential oncogenic drivers of SqCC have been identified, including amplification of the fibroblast growth factor receptor 1 (FGFR1). Reports from a recently completed clinical trial indicate low response rates in patients treated with FGFR tyrosine kinase inhibitors, suggesting inadequacy of FGFR1 amplification as a biomarker of response, or the need for combination treatment. We aimed to develop accurate models of lung SqCC and determine improved targeted therapies for these tumors. We show that detection of FGFR1 mRNA by RNA in situ hybridisation is a better predictor of response to FGFR inhibition than FGFR1 gene amplification using clinically relevant patient-derived xenograft (PDX) models of lung SqCC. FGFR1-overexpressing tumors were observed in all histological subtypes of non-small cell lung cancers (NSCLC) as assessed on a tissue microarray, indicating a broader range of tumors that may respond to FGFR inhibitors. In FGFR1-overexpressing PDX tumors, we observed increased differentiation and reduced proliferation following FGFR inhibition. Combination therapy with cisplatin was able to increase tumor cell death, and dramatically prolonged animal survival compared to single agent treatment. Our data suggest that FGFR tyrosine kinase inhibitors can benefit NSCLC patients with FGFR1-overexpressing tumors and provides a rationale for clinical trials combining cisplatin with FGFR inhibitors.

  Study EGAS00001002423

• snRNA-seq in white matter post-mortem tissue from MS and controls - DAC

  Dac EGAC00001001105

• DAC for scRNA-seq and scp-MS data on human bone marrow

  Dac EGAC00001003505

• Comprehensive molecular profiling of ETMR

  ETMR RIPSeq

  Dataset EGAD00001004802

• whole exome seq

  whole exome sequencing data

  Dataset EGAD00001004464

• Exome

  Exome Seq for EGAS00001001845

  Dataset EGAD00001002160

• HDBR exome sequencing data (May 2022)

  Exome sequencing data from seven phenotypically abnormal human fetal samples. Anaysis perfomed using Illumina NovaSeq 6000, Twist Bioscience - Human Comprehensive Exome. Paired end fastq files were aligned to hg38 reference genome using BWA-MEM v0.7.15, followed by sorting using SAMtools sort v1.3.1, and duplicate reads marked using Picard Tools MarkDuplicates v2.18.2

  Dataset EGAD00001008825

• HDBR exome sequencing data (November 2022)

  Exome sequencing data from seven phenotypically abnormal human fetal samples. Anaysis perfomed using Illumina NovaSeq 6000, Twist Bioscience - Human Comprehensive Exome. Paired end fastq files were aligned to hg38 reference genome using BWA-MEM v0.7.15, followed by sorting using SAMtools sort v1.3.1, and duplicate reads marked using Picard Tools MarkDuplicates v2.18.2

  Dataset EGAD00001009715

• Gene expression signatures associated with chronic endometritis revealed by RNA sequencing

  Chronic endometritis (CE) is a persistent inflammatory condition of the endometrium characterized by the infiltration of plasma cells. CD138 immunohistochemistry is considered to improve the CE diagnosis rate. Using the number of CD138-positive cells equal or greater than five as a diagnostic criterion for CE, we identified 24 CE and 33 non-CE cases among women with infertility. We conducted RNA-sequencing analysis for these 57 cases in total as an attempt to elucidate the molecular pathogenesis of CE and to search for new biomarkers for CE. By comparing CE and non-CE groups, we identified 20 genes upregulated in the endometria of CE patients, including 12 immunoglobulin-related genes and eight non-immunoglobulin genes as differentially expressed genes. The eight genes were MUC5AC, LTF, CAPN9, MESP1, ACSM1, TVP23A, ALOX15, and MZB1. By analyzing samples in the proliferative and secretory phases of the menstrual cycle separately, we also identified four additional non-immunoglobulin genes upregulated in CE endometria: CCDC13 by comparing the samples in the proliferative phase, and OVGP1, MTUS2, and CLIC6 by comparing the samples in the secretory phase. Although the genes upregulated in CE may serve as novel diagnostic markers of CE, many of them were upregulated only in a limited number of CE cases showing an extremely high number of CD138-positive cells near or over one hundred. Exceptionally, TVP23A was upregulated in the majority of CE cases regardless of the number of CD138-positive cells. The upregulation of TVP23A in the endometria of CE cases may reflect the pathophysiology of a cell-type or cell-types intrinsic to the endometrium rather than the accumulation of plasma cells. Our data, consisting of clinical and transcriptomic information for CE and non-CE cases, helped us identify gene expression signatures associated with CE.

  Study JGAS000621

• UCSF WCDT WGS/WGBS mCRPC

  This dataset contains 29 paired FASTQ files from whole-genome bisulfite sequencing (WGBS) assay performed on mCRPC tumors. Sequencing was performed using 150nt paired reads generated by a Novaseq 6000 instrument. It also contains whole-genome sequencing bam files aligned to hg38 using BWA from 36 patients, with tumor and matched tumor-adjacent normal samples. Sequencing was generated using HiSeq X Ten.

  Study EGAS00001006649

• Drug Perturbation of Primary Lymphoma Patient Samples and RNA Sequencing

  This submission contains 3'-end-based shallow-depth RNA sequencing data from 108 patients with chronic lymphocytic leukemia and 8 patients with lymphoma. Each primary patient sample was treated in vitro with DMSO as a control and with up to ten small-molecule drugs (ibrutinib, duvelisib, everolimus, trametinib, nutlin-3a, I-BET762, MK2206, selinexor, compound 26, and a combination of ibrutinib and compound 26). The samples were sequenced after 48 hours. The total data set consists of 1476 RNA sequencing samples from 6 batches (pilot, batch 1, batch 1 replicate, batch 2, batch 3, batch 4).

  Study EGAS50000001500

• bulk RNA sequencing, single cell RNA sequencing and nanopore sequencing of T-ALL patients with TCF7-SI1 fusion

  This dataset contains all sequencing data of the publication "Oncogenic cooperation between the TCF7-SPI1 fusion and NRAS(G12D) requires β-catenin activity to drive T-cell acute lymphoblastic leukemia." This is bulk RNA sequencing of 4 T-ALL patients (X09, XB37, XB41 and XB47) of which X09 has a TCF7-SPI1 fusion, single cell RNA sequencing of these 4 patients toghether with a PDX model of the X09 patient and two patients from another cohort (SJTALL030263 and SJTALL031201) which also have a TCF7-SPI1 fusion, and nanopore sequencing of all patients with the TCF7-SPI1 fusion. Moreover these patient samples with the fusion where treated with PKF 118-310, and bulk RNA sequencing was performed in triplicate to determine the differentially expressed genes.

  Dataset EGAD00001007010

• Single-cell DNA sequencing on Pediatric MDS

  Single-cell DNA sequencing with antibody-oligonucleotide staining was performed using the Mission Bio Tapestri single-cell DNA sequencing platform, per the manufacturer’s instructions. All libraries were sized and quantified using an Agilent Bioanalyzer and pooled for sequencing on an Illumina NovaSeq6000 with 150 base-paired ending multiplexed runs. Fastq files generated by the sequencers were processed using the Tapestri Pipeline V2 and included adapter trimming, sequence alignment (BWA), barcode correction, cell finding, and variant calling (GATK v4/Haplotypecaller). FastQ files are provided for the 5 samples that were processed using the aforementioned pipeline.

  Study EGAS00001005433

• Somatic L1 retrotransposition in normal colorectal epthelium

  Throughout an individual’s lifetime, genomic alterations accumulate in somatic cells. However, the mutational landscape induced by retrotransposition of long interspersed nuclear element-1 (L1), a widespread mobile element in the human genome, is poorly understood in normal cells. Here, we explored the whole-genome sequences of 406 normal colorectal clones, 12 MUTYH-associated adenomatous clones, and 19 matched colorectal cancer tissues. In addition, we analyzed promoter DNA methylation status of retrotransposition-competent L1 (in 139 clones) and read-through RNA expression profiles (in 116 clones) to investigate the epigenetic regulation of L1 activity.

  Dataset EGAD00001010183

• Heterogeneity of IKZF1 genomic alterations and risk of relapse in childhood B-cell precursor acute lymphoblastic leukemia

  Purpose Genomic alterations of IKZF1 are common and associated with adverse clinical features in B-ALL, but the relationship between the type of IKZF1 alteration, disease subtype and outcome are incompletely understood. Patients and Methods We used transcriptome and genomic sequencing, and SNP microarray data to determine leukemia subtype and genomic alterations for 688 pediatric patients with B-ALL enrolled into St. Jude Total Therapy 15 and 16 studies. Results IKZF1 alterations were identified in 115 (16.7%) patients, commonly in BCR::ABL1 (78%) and CRLF2-rearranged, BCR::ABL1-like B-ALL (70%), and were associated with five-year cumulative incidence of relapse (CIR) of 14.8 ± 3.3% compared to 5.0 ± 0.9% for patients without any IKZF1 alteration (P < 0.0001). IKZF1 deletions of exon 4-7 (P = 0.0002), genomic IKZF1plus with any IKZF1 deletion (P = 0.006) or with focal IKZF1 deletion (P = 0.0007), and unfavorable genomic subtypes (P < 0.005) were independently adversely prognostic. Patients with both IKZF1 exon 4-7 deletion and unfavorable genomic subtype had a significantly increased risk of relapse (HR = 58.3; 95% CI, 11.9 – 285.4, P < 0.0001) whereas IKZF1 sequence mutations were not independently predictive of outcome. Conclusions Genomic IKZF1plus with any IKZF1 deletion, IKZF1 deletion of exon 4-7, and unfavorable subtype confer increased risk of relapse. The combination of unfavorable genomic subtype and IKZF1 deletion of exon 4-7 identified patients at greatest risk of relapse despite MRD-directed therapy. The type of IKZF1 alteration together with subtype are informative for risk stratification and predict response in patients with B-ALL.

  Study EGAS50000000106

• Extreme phenotypes define epigenetic and metabolic signatures in cardiovascular diseases

  Improving the understanding of cardiometabolic syndrome pathophysiology and its relationship with thrombosis are ongoing healthcare challenges. Using plasma biomarkers analysis coupled with the transcriptional and epigenetic characterisation of cell types involved in thrombosis, obtained from two extreme phenotype groups (obese and lipodystrophy) and comparing these to lean individuals and blood donors, the present study identifies the molecular mechanisms at play, highlighting patterns of abnormal activation in innate immune phagocytic cells and shows that extreme phenotype groups could be distinguished from lean individuals, and from each other, across all data layers. The characterisation of the same obese group, six months after bariatric surgery shows the loss of the patterns of abnormal activation of innate immune cells previously observed. However, rather than reverting to the gene expression landscape of lean individuals, this occurs via the establishment of novel gene expression landscapes. Netosis and its control mechanisms emerge amongst the pathways that show an improvement after surgical intervention. Taken together, by integrating across data layers, the observed molecular and metabolic differences form a disease signature that is able to discriminate, amongst the blood donors, those individuals with a higher likelihood of having cardiometabolic syndrome, even when not presenting with the classic features.

  Dataset EGAD00001005197

• small RNA sequencing for 6 patients

  small RNA sequencing data for 3 patients with type 2D diabetes, and 3 patients with non diabetes. Single end sequencing was performed with read length of 100.

  Dataset EGAD50000001259

• Dataset of single cell RNA sequencing of peripheral blood HSPC

  Here, we conducted peripheral blood CD34+ cells single-cell RNA sequencing of patients with sickle cell anemia (n=4) and healthy donors (n=3)

  Dataset EGAD50000001522

• Star-based RNA count files

  To ellucidate gene activity in mRCC, RNA Sequencing data was generated as part of the EuroTarget study. Star aligner 2.7 was used to generate count files

  Dataset EGAD50000002296

• Single-cell RNA sequencing

  Single-cell RNA sequencing on 10 antrum and 4 body gastric biopsies

  Dataset EGAD00001010166

• Single-cell RNA and TCR sequencing of PBMC from patients with uveal melanoma

  Single-cell RNA and TCR sequencing of PBMC from patients with uveal melanoma.

  Dataset EGAD00001007913

• Patient TSO500 RNA

  Original patient tumours from which PDX models were derived. TruSight Oncology RNA panel for 2 samples, sequenced over 4 lanes each, gave 8 pairs of fastq files

  Dataset EGAD00001009659

• The Extracellular RNA Quality Control (exRNAQC) study (phase 1)

  mRNA capture sequencing and small RNA sequencing data (FASTQ files) of the exRNAQC study phase 1.

  Dataset EGAD00001007697

• PrevANZ RNAseq dataset

  Whole blood samples collected at baseline and week 12 in PAXgene Blood RNA tubes. RNA sequencing on the Illumina NovaSeq 6000 System generated 150 base pair length paired end reads.

  Dataset EGAD00001011069

• RNA sequencing data of child-mother pairs, maternal smoking.

  RNA sequencing data of whole blood samples from smoking and non-smoking mothers and their children at gestation/birth and follow-up years.

  Dataset EGAD00001002011

• RNA sequencing study for 8 pairs of primary NSCLCs and distant metastases

  RNA sequencing study for 8 pairs of primary NSCLCs and distant metastases. This dataset includes a total of 29 samples.

  Dataset EGAD00001005765

• GermCellTumour

  DNA and RNA sequencing across a number of different germ cell tumours, included mixed components within the same tumour.

  Study EGAS00001003457

• Multi-omics profiling of PSCCE

  We performed whole-exome sequencing, RNA sequencing and immunohistochemistry profiling of primary small cell carcinomas of the esophagus.

  Study EGAS00001004889

• Single-cell RNA sequencing of CML patients

  This dataset contains 15 single-cell RNA sequencing samples from 6 CML patients before and after TKI-cessation. The raw data is available as fastq files.

  Dataset EGAD00001012842

• Single cell characterization of T-cell lymphoma: RNA (2025-07-31)

  Lymphomas are types of blood cancer derived from lymphocytes, and can be classified into two main categories, Hodgkin's lymphomas (HL) and non-Hodgkin lymphomas (NHL). T-cell lymphoma is a type of NHL that develops from T lymphocytes and accounts for 10-15% of total NHL cases. As a rare disease, T-cell lymphoma is functionally, pathologically, and clinically complex and heterogeneous. The 2016 revision of the WHO classification has listed 29 subtypes of mature T/NK-cell neoplasms, among which over 25 are T lymphocyte in origin. These subtypes of T-cell lymphomas have different biological behaviours and clinical prognosis. Clinically, T-cell lymphoma ranges from indolent (slow-growing) to aggressive (fast-growing and spreading) disease. According to the guideline booklet provided by the Lymphoma Research Foundation (https://lymphoma.org/aboutlymphoma/nhl/), indolent T-cell lymphoma subtypes include adult T-cell leukaemia/lymphoma (ATLL), cutaneous T-cell lymphoma (CTCL), and mycosis fungoides (MF), while the aggressive subtypes include anaplastic large cell lymphoma (ALCL), angioimmunoblastic T-cell lymphoma (AITL), peripheral T-cell lymphoma (PTCL), and T lymphoblastic lymphoma (TLBL). PTCL and ALCL represent the most common subtypes of aggressive T-cell lymphoma whereas TLBL is a rare and aggressive subtype mostly diagnosed in children. In this study, we will use single cell RNA sequencing and single cell multiomic methods three aggressive T-cell lymphoma subtypes (ALCL, PTCL and TLBL) and try to gain a deeper insight into the genotypic and phenotypic features of these T-cell lymphomas. . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015669

• METABRIC

  The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (CNVs, SNPs) and acquired somatic copy number aberrations (CNAs) were associated with expression in 40% of genes, although the landscape was dominated by cis and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP, and MAP2K4. Unsupervised analysis of paired DNA/RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, ER-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration 0152hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the 0152CNA-devoid sub-group and a Basal-specific chromosome 5 deletion-driven mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic copy number aberrations on the transcriptome.

  Study EGAS00000000083

• Evolutionary analysis of pancreatic cancer and coexistent precursor lesions using whole exome sequencing data

  Most adult carcinomas develop from noninvasive precursor lesions, a progression that is supported by genetic analysis. Further, the evolution of these lesions contextualizes the dynamics of advanced stage disease. We analyzed the somatic variants of co-existing pancreatic cancers and precursor lesions sampled from distinct regions of the same pancreas. After inferring evolutionary relationships, we found that the ancestral cell had initiated and clonally expanded to form one or more lesions, and that subsequent driver gene mutations eventually led to a pancreatic cancer. We also found that this multi-step progression generally spans many years. Our data suggest that independent, high-grade pancreatic lesions observed in a histologic cross section often represent a single neoplasm that can spread and colonize the ductal system, accumulating spatial and genetic divergence over time.

  Study EGAS00001002778