Search Results - EGA European Genome-Phenome Archive

Clinical validity of post-surgery circulating tumor DNA (ctDNA) in stage III colon cancer patients treated with adjuvant chemotherapy: the PROVENC3 study

The PROVENC3 study aimed to determine the clinical validity of post-surgery ctDNA testing in patients with stage III colon cancer treated with adjuvant chemotherapy (ACT). Blood was collected pre-surgery, post-surgery and post-adjuvant chemotherapy. Tumor-informed plasma ctDNA detection was performed through integrated whole genome sequencing (WGS) analyses of formalin-fixed paraffin-embedded tumor tissue DNA (80x), white blood cell germline DNA (40x) and plasma cell-free DNA (30x). These raw WGS data for 209 patients are shared in .cram format in this EGA submission. For 196/209 of these patients there is overlapping FFPE tumor RNA sequencing data available, shared in .fastq format in this EGA submission.

Study EGAS50000000804

Centers for Common Disease Genomics (CCDG) - Whole Genome Sequencing in Type 1 Diabetes (T1DGC)

The Type 1 Diabetes Genetics Consortium (T1DGC) was established to collect resources (biological samples and data) and conduct research to better understand the genetic basis of type 1 diabetes (T1D). Collection was initiated by ascertaining affected sib-pair families (both parents, two affected siblings and, when available, an unaffected sibling), collected from five geographic regions through four recruitment networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, the T1DGC collected trio families (both parents and affected child) and cases and controls from low-prevalence populations (African-American, with four grandparents self-reporting as African ancestry; Mexican-American, with four grandparents self-reporting as ancestry from Mexico). The T1DGC also served as a repository for contributed collections from other studies, all meeting the broad data-sharing policy of the T1DGC, for inclusion in the genetic studies. These collections include T1D case samples ascertained from the UK Genetic Resource Investigating Diabetes (UK GRID) cohort, SEARCH for Diabetes in Youth (SEARCH), The Genetics of Kidneys in Diabetes (GoKinD), and control samples obtained from the British 1958 Birth Cohort, the UK National Blood Services collection, CLEAR (Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis), the New York Cancer Project (NYCP), and other cohorts. For the NHGRI-funded Centers for Common Disease Genomics (CCDG) project, participants with T1D and ancestry-matched controls were identified through the T1DGC, either through direct ascertainment or by contribution from other sources to the T1DGC. As the CCDG has focused initially on non-Caucasian populations for whole genome sequencing, T1DGC participants of African, Mexican and Asian ancestry (targeting ~1200 cases and ~1200 controls in each ancestral group) and a small group of participants of Northern European ancestry (~100 cases, ~100 controls) were to be contributed to the study. Whole genome sequencing of T1DGC samples would be conducted at Washington University McDonnell Genome Institute and based upon matching case-control status within an ancestry group and prioritization by the CCDG.

Study phs001222

Single cell RNAseq of stenotic, inflamed and non-inflamed transmural lesions from patients with Crohn's disease

This dataset contains a gene-cell matrix derived from single-cell RNA sequencing (scRNA-seq) data of ileal tissue from Crohn's disease (CD) patients and colorectal cancer (CRC) patients. It includes: Crohn's Disease Patients: A trio of transmural lesions (stenotic, inflamed, and non-inflamed) from each patient. Colorectal Cancer Patients: Unaffected ileal tissue used as external non-inflamed control. Cell Level Metadata: The dataset includes relevant cell-level metadata such as cell type annotations used in the study. Experimental Details: Platform: 10x Genomics Chromium Single Cell 3' GEX Sequencing: Illumina NovaSeq Processing: Data processed with Cell Ranger software. Resulting count matrices were merged for downstream analysis, including integration and dimensionality reduction. Dataset Composition: Crohn's Disease Patients: 10 patients with 3 samples each (non-inflamed, inflamed, stenotic), totaling 30 samples. Colorectal Cancer Patients: 5 patients with 1 sample each of unaffected tissue, totaling 5 samples. Data Provided: Merged Raw Count Matrix: The final merged raw count matrix used for downstream analysis. Cell Metadata File: Contains details of sample, tissue, and patient for each cell in the count matrix. Barcodes File: Indicate each cell barcode which also encodes the sample, tissue, and patient details for each cell. CD.S_Inf: Stenotic Corhn's disease inflamed samples CD.S_Sten: Stenotic CD patient stenosis sample CD.S_Prox: Stenotic CD Patient - proximal non-inflamed sample CC.C_Prox: CRC Patient proximal unaffected sample eg: A barcode 'CC.C_1_Prox_AAGTCGTAGACCCTTA' indicates CRC Patient unaffected proximal sampe from CRC Patient no.1 and the nucleic acid sequence indicate a unique cell from this sample. Total Samples: Crohn's Disease (CD) Patients: 30 samples Colorectal Cancer (CRC) Patients: 5 samples Patient_no Sample Sample_type 1 CC.C_1 CC.C_1_Prox CC.C_Prox 2 CD.S_1 CD.S_1_Prox CD.S_Prox 3 CD.S_1 CD.S_1_Infl CD.S_Infl 4 CD.S_1 CD.S_1_Sten CD.S_Sten 5 CC.C_2 CC.C_2_Prox CC.C_Prox 6 CD.S_2 CD.S_2_Prox CD.S_Prox 7 CD.S_2 CD.S_2_Infl CD.S_Infl 8 CD.S_2 CD.S_2_Sten CD.S_Sten 9 CC.C_3 CC.C_3_Prox CC.C_Prox 10 CC.C_4 CC.C_4_Prox CC.C_Prox 11 CD.S_3 CD.S_3_Prox CD.S_Prox 12 CD.S_3 CD.S_3_Infl CD.S_Infl 13 CD.S_3 CD.S_3_Sten CD.S_Sten 14 CD.S_4 CD.S_4_Prox CD.S_Prox 15 CD.S_4 CD.S_4_Infl CD.S_Infl 16 CD.S_4 CD.S_4_Sten CD.S_Sten 17 CC.C_5 CC.C_5_Prox CC.C_Prox 18 CD.S_5 CD.S_5_Prox CD.S_Prox 19 CD.S_5 CD.S_5_Infl CD.S_Infl 20 CD.S_5 CD.S_5_Sten CD.S_Sten 21 CD.S_6 CD.S_6_Prox CD.S_Prox 22 CD.S_6 CD.S_6_Infl CD.S_Infl 23 CD.S_6 CD.S_6_Sten CD.S_Sten 24 CD.S_7 CD.S_7_Prox CD.S_Prox 25 CD.S_7 CD.S_7_Infl CD.S_Infl 26 CD.S_7 CD.S_7_Sten CD.S_Sten 27 CD.S_8 CD.S_8_Prox CD.S_Prox 28 CD.S_8 CD.S_8_Infl CD.S_Infl 29 CD.S_8 CD.S_8_Sten CD.S_Sten 30 CD.S_9 CD.S_9_Prox CD.S_Prox 31 CD.S_9 CD.S_9_Infl CD.S_Infl 32 CD.S_9 CD.S_9_Sten CD.S_Sten 33 CD.S_10 CD.S_10_Prox CD.S_Prox 34 CD.S_10 CD.S_10_Infl CD.S_Infl 35 CD.S_10 CD.S_10_Sten CD.S_Sten

Dataset EGAD50000000559

WXS and RNA-seq for 22 patients treated with radiation + immunotherapy

Over 500 active clinical trials are investigating combination radiation (RT) and immune checkpoint blockade (ICB) as a cancer treatment; however, the majority of trials have found no positive interaction. We performed a comprehensive molecular analysis of a randomized phase I clinical trial of patients with non-small cell lung cancer (NSCLC) treated with concurrent or sequential ablative RT and ICB. Concurrent treatment was superior to sequential treatment in augmenting local and distant tumor responses and improving overall survival in a subset of patients with highly aneuploid tumors, but not in those with less aneuploid tumors. Our analysis suggested that concurrent treatment eliminated immunologically cold aneuploid tumors better than sequential treatment and improved patient outcomes. In addition, we report that RT alone decreased intratumoral cytotoxic effector T cell and adaptive immune gene expression signatures, in contrast to upregulation of key immune pathways after concurrent administration of RT and ICB. Our findings distinguish the differential genomic and transcriptomic effects of RT versus RT and ICB and challenge the prevailing paradigm that local ablative RT beneficially stimulates the immune response. We propose the use of tumor aneuploidy as a novel biomarker and therapeutic target in personalizing treatment approaches for patients with NSCLC treated with RT and ICB.

Study EGAS00001006212

Target sequencing of 27 cancer-predisposing genes in Japanese colorectal cancer patients

Background: National Comprehensive Cancer Network (NCCN) recently recommended germline genetic testing for all pancreatic cancer patients. However, the genes targeted by genetic testing and the feasibility of selecting patients likely to carry pathogenic variants have not been sufficiently verified. The purpose of this study was to genetically characterize Japanese patients and examine whether the current guideline is applicable in this population. Methods: Using targeted sequencing, we analyzed the coding regions of 27 cancer-predisposing genes in 1,005 pancreatic cancer patients and 23,705 controls in Japan. We compared the pathogenic variant frequency between cases and controls and documented the demographic and clinical characteristics of carrier patients. We then examined if it was possible to use machine learning to predict carrier status based on those characteristics. Findings: We identified 205 pathogenic variants across the 27 genes. Pathogenic variants in BRCA2, ATM, and BRCA1 were significantly associated with pancreatic cancer. Characteristics associated with carrier status were inconsistent with previous investigations. Machine learning classifiers had a low performance in determining the carrier status of pancreatic cancer patients, while the same classifiers, when applied to breast cancer data as a positive control, had a higher performance that was comparable to that of the NCCN guideline. Interpretation: Our findings support the clinical significance of multigene panel testing for pancreatic cancer and indicate that at least 3.4% of Japanese patients may respond to poly (ADP ribose) polymerase inhibitor treatments. The difficulty in predicting carrier status suggests that offering germline genetic testing for all pancreatic cancer patients is reasonable.

Study JGAS000346

Target sequencing of 27 cancer-predisposing genes in Japanese pancreatic cancer patients

Background: National Comprehensive Cancer Network (NCCN) recently recommended germline genetic testing for all pancreatic cancer patients. However, the genes targeted by genetic testing and the feasibility of selecting patients likely to carry pathogenic variants have not been sufficiently verified. The purpose of this study was to genetically characterize Japanese patients and examine whether the current guideline is applicable in this population. Methods: Using targeted sequencing, we analyzed the coding regions of 27 cancer-predisposing genes in 1,005 pancreatic cancer patients and 23,705 controls in Japan. We compared the pathogenic variant frequency between cases and controls and documented the demographic and clinical characteristics of carrier patients. We then examined if it was possible to use machine learning to predict carrier status based on those characteristics. Findings: We identified 205 pathogenic variants across the 27 genes. Pathogenic variants in BRCA2, ATM, and BRCA1 were significantly associated with pancreatic cancer. Characteristics associated with carrier status were inconsistent with previous investigations. Machine learning classifiers had a low performance in determining the carrier status of pancreatic cancer patients, while the same classifiers, when applied to breast cancer data as a positive control, had a higher performance that was comparable to that of the NCCN guideline. Interpretation: Our findings support the clinical significance of multigene panel testing for pancreatic cancer and indicate that at least 3.4% of Japanese patients may respond to poly (ADP ribose) polymerase inhibitor treatments. The difficulty in predicting carrier status suggests that offering germline genetic testing for all pancreatic cancer patients is reasonable.

Study JGAS000327

Platinum Pedigree Consortium Long-Read Sequencing

Platinum Pedigree Consortium includes whole genome sequencing of blood-derived DNA using five technologies on a 4-generation family. This is the CEPH-Utah (CEU) family 1463 and includes 4 grandparents from 1st generation, 2 parents from 2nd generation, 5 children from 3rd generation, 9 individuals from the 4th generation representing 2 branches of the 3rd generation, and their 2 additional parents. Family was not selected for disease, rather large size to study genetic transmission and human variation.Data available through dbGaP include raw sequence data: PacBio HiFi reads in unaligned BAM formats, Ultra-Long Oxford Nanopore (ONT) reads in FASTQ formats, Illumina sequencing, strand-seq and Element sequencing data in FASTQ format. Additionally, alignment files for HiFi reads mapped to the GRCh38 and CHM13v2.0 reference genomes, as well as de novo genome assemblies generated for this project are included.

Study phs003793

Single Cell DNA Methylation Analysis for Forensic Epigenetics

As part of the Epigenetic CHaracterization and Observation (ECHO) program, the Genomic Analysis Laboratory at the Salk Institute generated the DNA methylation profiles of certain PBMC cell types to determine the change in methylation levels before, during or after exposure to certain biological or chemical agents. Samples from individuals who either handled anthrax in controlled environments or who tested positive to MRSA, MSSA, HIV, COVID-19 or exposed to Flu virus or organophosphates, or control samples were used in single-nucleus methylation (snmC-seq) assays to quantify DNA methylation levels of cytosine residues of the DNA. Around 5-10% cytosine sites were sampled in the assay. Using computational analyses, regions in the genome differentially methylated in response to the exposure were identified. This information can be used to develop diagnostic tools to predict the type of infection or time since exposure.

Study phs003204

Multimodal epigenetic sequencing analysis of cell-free DNA identifies biomarkers for ALS diagnosis and progression

The role of the circulating epigenome in ALS remains understudied. We aim to develop diagnostic and prognostic blood-based biomarkers for Amyotrophic Lateral Sclerosis (ALS) by profiling methylome signatures in circulating cell-free DNA (cfDNA) in 20 sporadic ALS cases, 10 C9orf72-associated ALS cases, 10 asymptomatic C9orf72 expansion carriers, and 21 healthy controls using targeted enzymatic methyl-sequencing (EM-seq) of ~4 million CpG loci. We detected numerous differentially methylated genes, including several implicated in ALS risk and pathobiology, and integrated multiple epigenetic features with our Multimodal Epigenetic Sequencing Analysis (MESA) algorithm, achieving an ROC AUC of 0.91 and detecting ~70% of ALS cases at ~100% specificity. Methylation at a subset of loci also correlated with clinical progression and cerebrospinal-fluid neurofilament levels, supporting the potential of cfDNA-based biomarkers for ALS diagnosis and monitoring.

Study EGAS50000001267

pe_meta_20170131

Inverse variance weighted fixed effect meta-analysis of three European GWAS studies of the offspring of Pre-eclampsia affected births (2658 Cases and 308267 Controls).

Dataset EGAD00010001211

15174 results for "cancer studies using rna-seq"

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