15130 results for "cancer studies using rna-seq"

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• Single-cell profiling of neoantigen-specific T cells in lung cancers treated with neoadjuvant PD-1 blockade

  We study the expression profile of MANA-specific T cells, we used the MANA functional expansion of specific T cells (MANAFEST) assay in neoadjuvant anti-PD-1-treated lung cancers and applied their T cell receptor’s (TCR) complementarity-determining region 3 (CDR3) as a “barcode” to track and analyze their transcriptional programs in the tumor microenvironment using single cell TCR sequencing coupled with single cell RNA sequencing. We revealed distinct phenotype for MANA- and virus-specific clones in TIL and adjacent normal lung, regardless of response. MANA-specific T cells show features that drive the differences between responders and non-responders.

  Study EGAS00001005343

• Single-cell analysis reveals transcriptomic and epigenomic impacts on the maternal-fetal interface upon SARS-CoV-2 infection

  We assessed the transcriptome and chromatin states of patient and control samples at both bulk and single-cell resolutions with RNA-seq and ATAC-seq. Maternal-fetal interface samples were collected from 7 patients infected with SARS-CoV-2 during late pregnancy, and from 7 gestational age-matched control donors. Raw and processed files are provided in this dataset.

  Dataset EGAD00001008770

• Spatial multi-omic map of human myocardial infarction

  We applied an integrative single-cell genomics strategy with single nucleus RNA sequencing (snRNA-seq) and single nucleus Assay for Transposase-Accessible Chromatin sequencing (snATAC-seq) together with spatial transcriptomics from the same tissue mapping human cardiac cells in homeostasis and after myocardial infarction (MI) at unprecedented spatial and molecular resolution. We profiled in total 31 samples from 23 patients including four non-transplanted donor hearts as controls and samples from tissues with necrotic tissue areas (ischemic zone, IZ), border zone (BZ), and the non-affected left ventricular myocardium (remote zone, RZ) of patients with acute MI.

  Dataset EGAD00001008952

• Epigenetic Profiling of Human Colorectal Cancer

  DNA methylation, together with chromatin modifications, constitute the epigenome that functions to regulate gene expression and genome integrity. DNA methylation alterations are ubiquitous in human cancers, as many genes acquire DNA methylation in a cancer-specific manner. DNA methylation at these sites in the genome of cancer cells not only serves as a marker for tumor identification, but together with gene mutation and gene expression data, can also be used to describe subsets of tumors of the same organ source. We have previously shown distinct human colorectal cancer subtypes based on DNA methylation differences. Correlating these DNA methylation differences with clinical co-variates will serve to further understand how these distinct subtypes are generated. We have collected 100 colorectal tumor tissues (for which clinical information is known) and have obtained (unprotected) genome-wide DNA methylation and chromatin modification information for each sample for the purposes of identifying and classifying unique tumor subtypes of colorectal cancers. In addition, we have determined mutations of key genes relevant to colorectal cancer as well as gene expression profiles. We will use the clinical data for each de-identified sample to correlate with the DNA methylation, mutation and gene expression information so as to understand the driving forces behind these distinct colorectal subtypes. We have selected the most promising tumors for whole-genome bisulfite sequencing using next-generation sequencing technology to obtain complete maps of colon cancer methylomes. Researchers will be unable to identify the subjects because the samples and associated information have been de-identified and anonymized by the tissue source site. In addition, upon receipt by the USC Epigenome Center, we have assigned new random identifiers for each sample. The data generated using these new codes are not traceable to the patient identity.

  Study phs000385

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

  Metformin reduces the incidence of breast cancer in patients with obesity and type 2 diabetes. However, our knowledge of the effects of metformin on breast cancer recurrence is limited. Within the randomized double-blind placebo-controlled phase II trial MetBreCS, we examined changes in breast tissue from breast cancer survivors with BMI >25 kg/m2 after treatment with metformin. To identify metformin-regulated signaling pathways, we integrated the transcriptomic, metabolomic and steroid hormone profiles using bivariate and functional analyses. We identified MS4A1, HBA2, MT-RNR1 and MT-RNR2 expression to be differentially expressed in breast tissues from metformin-treated women. We also found metformin-associated down-regulation of EGFL6 and FDCSP in postmenopausal women. The integration of transcriptomic and metabolomic profiles revealed down-regulation of immune response genes associated with reduced levels of arginine and citrulline in the metformin-treated group. The integration of transcriptomic and steroid hormone profiles showed an enrichment of steroid hormone biosynthesis and metabolism pathways with highly negatively correlated CYP11A1 and CYP1B1 expression in breast tissue from postmenopausal metformin-treated women. Our results indicate that breast cancer survivors treated with metformin have specific changes in breast tissue gene expression that may prevent the development of new tumors. Within the randomized double-blind placebo-controlled phase II trial MetBreCS, we examined changes in breast tissue from breast cancer survivors with BMI >25 kg/m2 after treatment with metformin using bulk RNAseq (total mRNA sequencing), that is deposited in Federated EGA. The steroid hormones, and metabolomics and the insulin sensitivity serum biomarker data underlying this article may be shared upon reasonable request to the PI of the MetBreCS study (Dr. Bernardo Bonanni), following approval by the Data and Safety Monitoring Board at IEO, Milan.

  Study EGAS50000000874

• Somatic Mutation Profile by Next Generation Sequencing in HER2+ Breast Cancer

  The HER pathway is the driving force behind 30% of human breast cancers. It is important to understand how targeted therapies block different cellular pathways, and mechanisms of escape from this blockage. Therapies directed at HER2 establish a successful treatment paradigm, but de novo and acquired resistance exist. The HER signaling system is a complex network with four receptors and eleven ligands, a phosphorylation signaling cascade, and many transcription factors, all complicated by both positive and negative feedback circuits. Analysis of genomes, exomes and transcriptomes by next generation sequencing is aimed at uncovering the genetic factors responsible for patient responses to HER2-directed therapies. We are sequencing HER2-overexpressing cancers, in order to identify potential somatic changes that may better select patients who will benefit from therapy, to determine new targets that may overcome resistance, and to improve outcomes with known current HER2-targeted therapies. Whole exome capture sequencing will determine somatic mutation profiles in HER2-overexpressing tumors, to comprehensively characterize the somatic alterations, with the goal of identifying those patients most likely to respond, as well as discovering new targets that may overcome resistance to HER2-directed therapy. We augment the whole exome data with RNA-seq data to determine expression levels of somatic mutations we discover.

  Study phs000770

• Cancer genome scanning in plasma: detection of tumor-associated copy number aberrations, single nucleotide variants and tumoral heterogeneity by massively parallel sequencing

  Tumor-derived DNA can be found in the plasma of cancer patients. We explored the use of shotgun massively parallel sequencing of plasma DNA obtained from cancer patients to scan a cancer genome noninvasively. We achieved the profiling of copy number aberrations and point mutations, in a genomewide manner using this approach. By measuring the genomewide aggregated allelic loss and point mutations, we determined the fractional tumor-derived DNA concentrations in plasma and correlated these values with tumor size and surgical treatment. We have also demonstrated the application of this approach to monitoring a complex oncologic scenario, in a patient with two synchronous cancers. In particular, through the use of multi-regional sequencing of tumoral tissues and shotgun sequencing of plasma DNA, we have shown that plasma DNA sequencing is a valuable approach for studying tumoral heterogeneity. Shotgun plasma DNA sequencing is thus a powerful tool for cancer monitoring and research.

  Study EGAS00001000370

• A capture methyl-seq protocol with improved efficiency and cost-effectiveness using pre-pooling and enzymatic conversion

  The opportunities for sequencing-based methylome analysis of clinical samples are increasing. To reduce its cost and the amount of genomic DNA required for library preparation, we aimed to establish a capture methyl-seq protocol, which adopts pre-pooling of multiple libraries before hybridization capture and TET2/APOBEC-mediated conversion of unmethylated cytosine to thymine. We compared a publicly available dataset generated by the standard Agilent protocol of SureSelect XT Human Methyl-Seq Kit and our dataset obtained by our modified protocol, EMCap, that adopted sample pre-pooling and enzymatic conversion. We confirmed that the quality of DNA methylation data was comparable between the two datasets. As our protocol, EMCap, is more cost-effective and reduces the amount of input genomic DNA, it would serve as a better choice for clinical methylome sequencing.

  Study JGAS000605

• ovarian cancer sample exome seq

  Tissue samples were collected from 18 ovarian cancer patients. After mechanical and enzymatic dissociation, a part of these tissues underwent growth factoromics analysis. For four cases, single-cell sequencing analysis was conducted under conditions with or without estradiol. Additionally, the remains of the tissues were frozen and subsequently subjected to exome sequencing on 16 of these samples. Sixteen cases were diagnosed as HGSOC, while two samples were clear cell or mucinous type (Extended Data Table 1). All cases were grade 3, and none had received neoadjuvant chemotherapy.

  Dataset EGAD50000002057

• Whole exome sequencing of endometriod ovarian cancer tumours

  Whole Exome sequencing data of tumour samples for 112 patients with endometrioid ovarian carcinoma in FASTQ format. Data was derived as summarized below: Library Preparation: Libraries were prepared from each DNA sample using the Illumina TruSeq Exome Library Prep kit (#FC-150-1002) according to the provided protocol using modifications for working with FFPE sourced material. Libraries were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Library QC: Exome-captured sequencing library pools were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Fragment size and quantity measurements were used to calculate molarity for each library pool. Sequencing: Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC-404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002).

  Dataset EGAD00001006389

• RNAseq of Sjögren's Syndrome and Healthy Volunteers' Salivary Glands

  Mechanistic genetic and inflammatory endpoints were studied to gain insight into the molecular mechanisms of Sjögren's syndrome. Transcriptomic studies allowed the exploration of molecular alterations that might cause or influence the studied salivary gland pathology and potentially elucidate druggable pathways for intervention.

  Study phs001842

• Whole exome sequence analysis in sporadic amyotrophic lateral sclerosis

  To identify a susceptible gene for amyotrophic lateral sclerosis, exome sequence analysis was conducted in patients with amyotrophic lateral sclerosis and control subjects to perform whole genome association studies. In this data set, exome sequencing data of 11 patients with amyotrophic lateral sclerosis was included.

  Study JGAS000013

• HipSci_RNASEQ_PID

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Platelet and bleeding disorders patients

  Study EGAS00001001990

• ESGI___Molecular_diagnosis_for_mitochondrial_disorders_

  The MITOEXME project aims to improve protocols for molecular diagnosis of patients with OXPHOS disorders with a focus on a next generation sequencing methods and to increase the knowledge of pahtophysiological mechanisms by identification of new targets and cellular studies. In this project we will sequence the exomes fo 120 patients.

  Study EGAS00001000164

• HipSci_RNASEQ_Usher syndrome and congenital eye defects

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Usher syndrome and congenital eye defects.

  Study EGAS00001001997

• Functionally Active Copy Number Variants Associated with Prostate Cancer Risk

  Prostate cancer is a leading cause of cancer death in males throughout the world and has the largest estimated effect of heritability among the most common tumor types. Copy Number Variants (CNVs) are a recently recognized class of human germline polymorphisms (Iafrate AJ, et al. (2004) Nat Genet 36, 949-951; Sebat J, et al. (2004) Science 305, 525-528.) and are associated with a variety of human diseases, including cancer. This study characterized 1,903 individuals from the Tyrol Early Prostate Cancer Detection Program (Bartsch G, et al. (2008) BJU Int 101, 809-816) using a computational framework (Banerjee S, et al. (2011) PLoS One 29;6(3)). The study results establish non-coding and coding germline CNVs as significant risk factors for prostate cancer susceptibility and implicate their role in disease development and progression. The study "Identification of functionally active, low frequency copy number variants at 15q21.3 and 12q21.31 associated with prostate cancer risk," Demichelis F, Setlur SR, Proc Natl Acad Sci U S A. 2012 Apr 24;109(17):6686-91.

  Study phs000487

• Whole-genome sequencing of tumour, germline and plasma samples from a BRCA1-mutant breast cancer patient

  This data set contains the fastq files from whole-genome sequencing of temporally matched tumour (fresh frozen biopsies), blood germline and plasma samples collected from a BRCA1-mutant breast cancer patient to directly compare mutation signature analysis using gold-standard tumour-germline paired variant calling with a novel ctDNA-based method (MisMatchFinder).

  Dataset EGAD50000000811

• Whole genome sequencing of circulating cell-free DNA on Illumina and Ultima platforms

  The dataset includes Illumina (n=1) and Ultima (n=92) sequencing of circulating cell-free DNA. The dataset was generated through standard whole genome sequencing (Illumina n=1 & Ultima n = 15) and using a duplex unique molecular identifier whole genome sequencing workflow (Ultima, n=77). This dataset includes cancer samples and cancer-free control samples.

  Dataset EGAD50000001234

• The dataset of Detection and characterization of lung cancer using cell-free DNA fragmentomes on NovaSeq 6000 at 1-2x coverage

  The dataset contains 364 CRAM files from whole-genome next-generation sequencing on the Illumina NovaSeq 6000 at 1- 2x coverage. These are plasma samples from healthy individuals and patients with cancer.

  Dataset EGAD50000001961

• Biomodal duet +modC sequencing of endometrial cancer plasma cfDNA samples

  This dataset contains biomodal sequencing data generated using the duet + modC assay from plasma-derived cell-free DNA of endometrial cancer patients and healthy donors. Sequencing was performed on an Illumina NovaSeq 6000. Dataset includes raw sequencing FASTQ files. Duet +modC output enables whole-genome profiling of both genetic variation and DNA methylation.

  Dataset EGAD50000002261

• CNV detection in targeted NGS panel data

  We present targeted NGS panel data from 170 samples that were processed using the TruSightTM Cancer (TSC) panel (Illumina, San Diego, CA, USA), which targets 94 genes and 284 SNPs associated with a predisposition towards cancer. The samples are enriched for CNVs in the genes of interest. All CNVs have previously been assessed with MLPA and can therefore be considered as confirmed.

  Dataset EGAD00001003400

• Targeted Pulldown Validation of mutations found in whole genome sequencing

  This experiment is to inform us of the validity of using pre-made library material to perform a bespoke pulldown experiment to validate the mutations found between the whole genome sequencing of the DNA from the same individuals cancer and normal material. This is to identify the valid and informative mutations in cancer genomes.

  Dataset EGAD00001001061

• Whole-exome sequencing of liver cancer organoids

  Whole-exome sequencing was performed from organoids derived from 10 liver cancer biopsies (7 hepatocellular carcinoma and 3 cholangiocarcinoma), corresponding liver and non-tumoral biopsies. For 3 of the organoids, both early and late passage organoids were sequenced. Whole-exome sequencing was performed using the Agilent Clinical Research Exome capture kit followed by Illumina sequencing. BAM files are provided in this dataset.

  Dataset EGAD00001004205

• Dataset Gene-Breakpoint Panel

  In this study we analysed patients with metastatic prostate cancer to scan their tumor genomes noninvasively in plasma DNA. We enriched 1.3 Mbp of seven plasma DNAs (4 CRPC cases: CRPC1-3 and CRPC5; 3 CSPC cases: CSPC1-2 and CSPC4) including exonic sequences of 55 cancer genes and 38 introns of 18 genes, where fusion breakpoints have been described using Sure Select Custom DNA Kit.

  Dataset EGAD00001000365

• Determining off-target effects of splice-switching antisense oligonucleotides using short read RNAseq in neuronally differentiated human induced pluripotent stem cells

  Neuronal cells derived from female healthy control hiPSC lines LUMCi003-A, LUMCi003-B and LUMCi023-A were transfected with in total four different splice-switching AONs targeting three different human transcripts. Untransfected samples as well as samples transfected with a scrambled AON were included as controls. Three days after transfection, RNA was isolated for sequencing using Illumina Novaseq6000 in order to perform differential gene expression analysis and differential splicing analysis to determine off-target effects. Sequencing was performed in two batches: one containing the samples from cell line LUMCi003-A and the other containing cell lines LUMCi003-B and LUMCi023-A.

  Dataset EGAD50000001742