15120 results for "cancer studies using rna-seq"

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• Automated machine-learning approach for next generation profiling of sequence alterations, mutation burden, microsatellite instability, and structural variants in human cancers

  Sequence and structural alterations together with tumor mutation burden (TMB) and microsatellite instability (MSI) have been identified as biomarkers for the determination of response to targeted and immune checkpoint inhibitor therapies. However, widespread clinical adoption of these biomarkers has historically been limited due to barriers such as evidence of clinical utility and reimbursement. We have developed 2.2 Mb targeted NGS system and an automated machine-learning analysis approach (PGDx elio™ tissue complete, ETC) that has been FDA cleared for examination of 500+ cancer-related genes and 68 mononucleotide repeats for identification of sequence and structural alterations, TMB, and MSI in solid cancers in a clinical setting. We designed and trained this approach using sequence data from 4,174 cancers and >124,000 in silico alterations and evaluated the methodology in >2,550 tumor or non-cancerous normal samples. Independent analyses of ETC sequence changes in 440 formalin fixed paraffin embedded (FFPE) tumor or cell line samples using MSK-IMPACT™, FoundationOne®, and ddPCR revealed a positive percent agreement (PPA) >97% with high sensitivity as low as 3% mutant allele fraction. We observed high concordance between panel-wide and whole-exome TMB for 307 pan-cancer FFPE tumors (Pearson r=0.95, p < 0.0001) using samples with ≥20% tumor cellularity. Comparison of the mutation context and repeat-based MSI approach in ETC with a multiplex MSI PCR assay in 223 samples revealed a PPA of 99% and negative predictive agreement (NPA) >99%. We confirmed the accuracy and precision of TMB and MSI measurements across three independent laboratories (CV of <5% and average PPA >99%, respectively). Finally, evaluation of amplifications and translocations against DNA and RNA-based approaches exhibited >98% NPA and PPA of 86% and 82% respectively. These results demonstrate high analytical performance for determination of sequence and structural changes, TMB, and MSI using a targeted NGS panel and provide a scalable and facile approach for evaluating these biomarkers in a clinical laboratory.

  Study EGAS00001005556

• cell-free Nucleosome ChIP-seq

  Dataset includes cell-free ChIP-seq data of 268 samples (from 61 self-declared healthy donors, four patients with acute myocardial infarction, 29 patients suffering from autoimmune, metabolic, or viral liver diseases and 56 metastatic colorectal carcinoma (CRC) patients). DNA libraries preparation is documented in the methods section. Libraries were paired end sequenced by Illumina NextSeq 500 and aligned to the human genome (hg19) using bowtie2 (2.3.4.3) with ‘no-mixed’ and ‘no-discordant’ flags. This dataset includes fastq and BAM files of all samples.

  Dataset EGAD00001006811

• scRNA-seq dataset of patient with immune dysregulation

  scRNA-seq dataset on a patient (P_IKZF2-het) presenting with immune dysregulation. This dataset contains raw and processed files from scRNA-seq performed on samples using the 10x Genomics Chromium Controller with the Chromium Single Cell 3′ Reagent Kit (v3 chemistry). There are three paired-end (75 bp) fastq files (I1, R1, R2) and three processed files generated with 10x Genomics Cell Ranger v3.0.2 software against GRCh38 human reference transcriptome (scrnaseq_P_IKZF2-het_barcodes.tsv.gz, scrnaseq_P_IKZF2-het_features.tsv.gz, scrnaseq_P_IKZF2-het_matrix.mtx.gz).

  Dataset EGAD00001008443

• Evaluation of somatic mutations in urine samples as a non-invasive method for the detection and molecular classification of endometrial cancer

  Purpose: Current diagnostic methods for endometrial cancer lack specificity, leading to many women undergoing invasive procedures. The aim of this study was to evaluate somatic mutations in urine to accurately discriminate endometrial cancer patients from controls. Experimental Design: Overall, 72 samples were analyzed using next-generation sequencing with molecular identifiers targeting 47 genes. We evaluated urine supernatant samples from women with endometrial cancer (n=19) and age-matched controls (n=20). Cell pellets from urine and plasma samples from seven cases were sequenced; further, we also evaluated paired tumor samples from all cases. Finally, immunohistochemical markers for molecular profiling were evaluated in all tumor samples. Results: Overall, we were able to identify mutations in DNA from urine supernatant samples in 100% of endometrial cancers. In contrast, only one control (5%) showed variants at a variant allele frequency (VAF)≥2% in the urine supernatant samples. The molecular classification obtained by using tumor samples and urine samples showed good agreement. Analyses in paired samples revealed a higher number of mutations and VAFs in urine supernatants than in urine cell pellets and blood samples. Conclusions: Evaluation of somatic mutations using urine samples may offer a user-friendly and reliable tool for endometrial cancer detection and molecular classification. The diagnostic performance for endometrial cancer detection was very high, and cases could be molecularly classified using these noninvasive and self-collected samples. Additional multi-center evaluations using larger sample sizes are needed to validate the results and understand the potential of urine samples for the early detection and prognosis of endometrial cancer.

  Study EGAS00001007396

• Childhood Cancer Model Atlas

  we establish a single-site collection of 243 cell lines, including 207 paediatric cancer cell lines representing 14 distinct extracranial and brain childhood tumour types. We subjected 164 paediatric cancer cell lines to multi-omic analyses across three dimensions (DNA-sequencing, RNA-sequencing, DNA methylation) to classify them based on clinically relevant molecular subtypes.

  Study EGAS00001006320

• Transcriptomic Analysis of HIV-Infected Cells

  Defining the attributes of rare CD4 T cells that harbor latent HIV under therapy with anti-retroviral agents has been challenging due to difficulties in identifying and isolating these cells. These cells represent an important barrier to cure, and characterizing them would aid the design and development of novel HIV cure strategies. In this study, we addressed this challenge using a custom microfluidic technology named Focused Interrogation of cells by Nucleic acid Detection and Sequencing (FIND-seq) that isolates HIV-infected cell transcriptomes, based on HIV DNA detection. We applied this method to HIV DNA+ memory CD4 T cells isolated from blood from five persons with HIV who were receiving anti-retroviral agents. After curating samples based on data quality, we proceeded with bioinformatics analysis from three persons. This analysis identified six transcriptomic pathways that were inhibited in HIV DNA+ cells compared to HIV DNA- cells. These included death receptor signaling, necroptosis signaling, and anti-proliferative G-alpha12/13 signaling. Furthermore, we identified two gene clusters, including 60 and 85 genes, that were significantly associated with HIV DNA+ cells identified by co-expression network analysis. These genes included negative regulators of HIV transcription that were higher in HIV DNA+ cells, positive regulators of HIV transcription that were lower in HIV DNA+ cells, and other genes involved in the negative regulation of mRNA translation, additional RNA processing functions, and the regulation of cellular state and fate. We further examined these signatures in transcriptomic data from CD4 T cell subsets sorted by flow cytometry from nine persons with HIV. We found a partial similarity between the smaller cluster of genes and the signature of CCR6- peripheral TFH cells. Raw sequencing data from all eleven human participant samples included in the study are available. These include samples from two participants who were studied only by FIND-seq, three participants who were studied by both FIND-seq and flow cytometry and six participants who were studied only by flow cytometry.

  Study phs003095

• Genomic Characterization of Head and Neck Squamous Cell Carcinoma Cell Lines

  Head and neck squamous cell carcinoma (HNSCC) is the sixth leading cancer by incidence worldwide(1). Various chemical carcinogens (tobacco, alcohol and betel nut), human papillomavirus (HPV) infection, and genetic predisposition contribute to the etiology of HNSCC, and to the complex genetic alterations in tumor subsets that differ in prognosis and response to therapies (2). Recently, a comprehensive landscape of genomic and transcriptomic alterations in HNSCC tumors has emerged from The Cancer Genome Atlas (TCGA) Network (3). TCGA revealed novel and previously recognized gene and chromosomal region copy number alterations (CNAs), mutations, and expression clusters, and defined their frequency, co-occurrence, and relationship to common and rare subtypes of HPV(-) and (+) tumors that vary in prognosis. To identify cell line models for determining the functional role and therapeutic importance of these alterations, we are performing whole exome and RNA sequencing and bioinformatic analysis of an expanded panel of 15 HPV(-) and 11 HPV(+) HNSCC cell lines and primary oral keratinocytes. We find that the recurrent genomic alterations in cell lines are remarkably consistent with those found in more aggressive tumors, from which cell lines have traditionally been most readily adapted to culture (4). Genome-wide correlation of CN (copy number) with expression identified a suite of potential drivers or modifier genes that differ by HPV status, and are of potential biologic and therapeutic relevance. Further, our findings elucidate and validate genomic alterations underpinning numerous discoveries made with these widely-used and recently derived HNSCC lines, and provide a roadmap for their potential use as models for future studies of tumor subtypes with worse prognosis. References Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015;65(2):87-108. Van Waes C, Musbahi O. Genomics and advances towards precision medicine for head and neck squamous cell carcinoma. Laryngoscope Investig Otolaryngol. 2017;2(5):310-9. Cancer Genome Atlas N. Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature. 2015;517(7536):576-82. White JS, Weissfeld JL, Ragin CC, Rossie KM, Martin CL, Shuster M, et al. The influence of clinical and demographic risk factors on the establishment of head and neck squamous cell carcinoma cell lines. Oral Oncol. 2007;43(7):701-12.

  Study phs001581

• Integrative genomic analysis reveals cancer-associated mutations at diagnosis of CML in patients with high risk disease

  Genomic events associated with poor outcome in chronic myeloid leukemia (CML) are poorly understood. We performed whole exome sequencing, copy number variation and/or RNA-Seq for 65 patients to discover mutations at diagnosis and blast crisis (BC). Forty-six chronic phase patients with the extremes of outcome were studied at diagnosis. Cancer gene variants were detected in 15/27 patients (56%) with subsequent BC or poor outcome and in 3/19 optimal responders (16%), P=.007. Frequently mutated genes at diagnosis were ASXL1, IKZF1 and RUNX1. The methyltransferase SETD1B was a novel recurrently mutated gene. A novel class of variant associated with the Philadelphia translocation was detected at diagnosis in 11/46 patients (24%) comprising fusions and/or rearrangement of genes on the translocated chromosomes, with evidence of fragmentation, inversion and imperfect sequence reassembly. These were more frequent at diagnosis in patients with poor outcome: 9/27 (33%) versus 2/19 optimal responders (11%), P=.07. Thirty-nine patients were tested at BC and all had cancer gene variants, including ABL1 kinase domain mutations in 58%. However, ABL1 mutations co-occurred with other mutated cancer genes in 89% of cases, and these predated ABL1 mutations in 62% of evaluable patients. Gene fusions not associated with the Philadelphia translocation occurred in 42% of patients at BC and commonly involved fusion partners that were known cancer genes (78%). Genomic analysis revealed numerous relevant variants at diagnosis in patients with poor outcome and all patients at BC. Future refined biomarker testing of specific variants will likely provide prognostic information to facilitate a risk-adapted therapeutic approach.

  Study EGAS00001003071

• (h)MeDIP-Seq of high-risk prostate cancer

  high-throughput sequencing of methylated and hydroxymethylated DNA from tumor and non-tumor tissue of patients with high-risk prostate cancer

  Dataset EGAD00001002010

• Automated system for scoring hematoxylin and eosin-stained ovarian cancer sections by identifying single cells uncovered that stromal cell ratio is a significant predictor for overall survival and progression-free survival.

  Concerted efforts in genomic studies have revealed profound insights in prognostic ovarian cancer subtypes. On the other hand, abundant histology slides have been generated to date, yet their uses remain very limited and largely qualitative. Our goal is to develop automated histology analysis as an alternative subtyping technology for ovarian cancer that is cost-efficient and do not rely on DNA quality. We develop an automated system for scoring hematoxylin and eosin-stained (H&E) primary tumour sections of 91 late-stage ovarian cancer to identify single cells including cancer and stromal cells. We demonstrated high accuracy of our system based on expert pathologists’ scores (cancer=97.1%, stromal=89.1%) as well as compared to immunohistochemistry scoring (correlation=0.87). Quantitative stromal cell ratio is significantly associated with poor overall survival after controlling for clinical parameters including debulking status and age (multivariate analysis p=0.0021, HR=2.54, CI=1.40-4.60) and progression-free survival (multivariate analysis p=0.022, HR=1.75, CI=1.09–2.82). We demonstrate how automated image analysis enables objective quantification of microenvironmental composition of ovarian tumours. Our analysis reveals a strong effect of the tumour microenvironment on ovarian cancer progression and highlights the potential of therapeutic interventions that target the stromal compartment or cancer-stroma signalling in the stroma-high, late-stage ovarian cancer subset.

  Study EGAS00001001694

• Single-cell RNA-seq of immune cells sorted from human melanoma tumors

  Tumor immune cell compositions play a major role in response to immunotherapy but the heterogeneity and dynamics of immune infiltrates in human cancer lesions remain poorly characterized. Here we identify conserved intratumoral CD4 and CD8 T cell behaviors in scRNA-seq data from 25 melanoma patients. We discover a large population of CD8 T cells showing continuous progression from an early effector "transitional" into a dysfunctional T cell state. CD8 T cells that express a complete cytotoxic gene set are rare, and TCR sharing data suggest their independence from the transitional and dysfunctional cell states. Notably, we demonstrate that dysfunctional T cells are the major intratumoral proliferating immune cell compartment and that the intensity of the dysfunctional signature is associated with tumor-reactivity. Our data demonstrate that CD8 T cells previously defined as exhausted, are in fact a highly proliferating, clonal and dynamically differentiating cell population within the human tumor microenvironment.

  Study EGAS00001003363

• Longitudinal 3'RNA-Seq data from MEMORI trial

  80 bam files generated from 3'RNAseq of tumour biopsies from oesophageal adenocarcinoma. Samples were collected within the clinical MEMORI trial.

  Dataset EGAD50000000357

• cHCC-ICC RNAseq

  The RNA-seq data of 97 tumor samples from 77 cHCC-ICC cases, data of two other HCC tumor samples were also included.

  Dataset EGAD00001005182

• RCC transcriptomic data

  RNA-seq data. 287 Japanese RCC cases.

  Dataset EGAD00001010003

• Transcriptome Profiling of human AT2 cells in COPD

  RNA-seq of FACS sorted AT2 cells from ex-smokers with (n=6) and without (n=3) COPD at different disease stages. Fastq files are provided.

  Dataset EGAD00001011115

• Genomic Analysis of Paired Endometrial Cancer Primaries and Metastases

  Formation of metastases is the major cause of cancer related deaths. Recent studies have sequenced primary endometrial carcinomas yielding data for a single entity in the progression from the birth of a progenitor tumor cell to metastatic disease. However, the progression of these tumors to metastases has not been characterized. We performed whole-exome sequencing of 98 tumor biopsies including complex atypical hyperplasias, primary tumors and paired abdominopelvic metastases to survey the evolutionary landscape of endometrial cancer. We expanded and reanalyzed TCGA-data, identifying novel recurrent alterations in primary tumors, including mutations in the estrogen receptor cofactor NRIP1 in 12% of patients. We found that likely driver events tended to be shared by primary and metastatic tissue-samples, with notable exceptions such as ARID1A mutations. Phylogenetic analyses in cases with multiple metastases indicated these metastases typically arose from one lineage of the primary tumor. These data indicate extensive genetic heterogeneity within endometrial cancers and relative homogeneity across metastatic sites.

  Study phs001127

• RNA sequencing of BCP-LBL patients samples

  In order to perform comprehensive transcriptomics and gene fusion analyses of a cohort of BCP-LBL patients, we performed RNA sequencing of 49 tissue samples from BCP-LBL patients. Because the material was available as FFPE, and had a relative low quality, we used a capture-based approach, where NGS libraries obtained from total RNA were captured in 4-plex, using a whole exome capture panel.

  Dataset EGAD50000000419

• RNAseq profiles from the CheckMate-142 clinical trial

  The dataset contains RNAseq profiles of 57 patients from the CheckMate-142 clinical trial. The Allprep DNA/RNA FFPE kit was used to simultaneously purify genomic DNA and RNA from formalin-fixed, paraffin embedded (FFPE) tissue sections. Baseline tumor tissue samples were processed using the Illumina TruSeq RNA Access in-solution hybrid capture panel and underwent subsequent NGS on the Illumina NovaSeq platform. Fastq files are included.

  Dataset EGAD50000000609

• CXCL8 secreted by immature granulocytes inhibits wildtype hematopoiesis in chronic myelomonocytic leukemia

  CXCL8 secreted by immature granulocytes inhibits wildtype hematopoiesis in chronic myelomonocytic leukemia [Abstract] In chronic myelomonocytic leukemia, blocking CXCL8 produced by clonal dysplastic granulocytes is a potential therapeutic strategy to slow disease progression. [Data provided] Exome-sequencing, bulk mRNA-seq and single-cell RNA-seq of iGRAN, monocytes and PBMC of CMML patients and controls.

  Dataset EGAD50000000789

• Sequence data for "An allele-resolved nanopore-guided tour of the human placental methylome" (Kindlova et al 2025)

  Sequence data generated for the study "An allele-resolved nanopore-guided tour of the human placental methylome" includes Illumina WGS, Illumina RNA-seq, Illumina EM-seq, and Oxford Nanopore Technologies PromethION sequence data.

  Dataset EGAD50000001850