15154 results for "cancer studies using rna-seq"

in 23.81 milliseconds.

• Genomic and Transcriptomic Profile of Paired Primary-Metastasis Colorectal Tumors

  The goal of this study is to identify mechanisms of metastization in a portuguese cohort of colorectal cancer. Namely, we want to identify patterns of genomic and transcriptomic diversification associated with metastasis.

  Study EGAS00001005276

• Pre-post neoadjuvant chemotherapy breast cancer dataset- RNAseq data

  This dataset contains RNAseq data of 20 paired pre-post neoadjuvant chemotherapy breast cancer samples. In total the set contains n=20 biopsies, n=20 surgery specimens. Each sample has 2 fastq files, so n=80 fastq files are uploaded in total.

  Dataset EGAD00001008421

• Targeted amplicon sequencing on 218 samples from Stage 1 epithelial ovarian cancer biopises

  BAM files (aligned against the hg38 genome) from a targeted amplicon sequencing (139 genes) experiment (median depth 1000X) on 218 samples from Stage 1 epithelial ovarian cancer biopises. Samples labeled "bis" or "tris" with the same ID are relapses; "left" or "right" samples indicate, in the case of bilateral tumor, from which ovary the sample was taken.

  Dataset EGAD00001006873

• Whole Genome sequencing of colorectal cancer patients (SG-BULK-3)

  Whole Genome sequencing of colorectal cancer patients (SG-BULK-3)

  Dataset EGAD00001008592

• DNA Whole Exome Sequence for manuscript titled: Evaluation of Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration (EBUS-TBNA) Samples from Advanced Non-Small Cell Lung Cancer for Whole Genome, Whole Exome and Comprehensive Panel Sequencing

  DNA Whole Exome Sequence for manuscript titled: Evaluation of Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration (EBUS-TBNA) Samples from Advanced Non-Small Cell Lung Cancer for Whole Genome, Whole Exome and Comprehensive Panel Sequencing

  Dataset EGAD00001015395

• WXS dataset of Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience

  WXS dataset of Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience

  Dataset EGAD00001015638

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002019

• GILD-ExomeSeq-PTNHL

  This study is meant to gain further knowledge in haematological cancers. Patients samples (mainly DNAs or PCR products) from haematolocical cancer patients will be sequenced, and the outputs will be correlated to their diagnosis and/or prognosis; the findings may also add more insight into the understanding of biology in this type of tumour. We will be sequencing Primary Testicular Lymphomas (PTL) to identify genetic drivers of this rare cancer

  Dataset EGAD00001001986

• PLCRC study

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from Colorectal cancer patients and subjected to short paired end sequencing on the llumina platform. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Dataset EGAD00001000947

• Colorectal cancer WES/WGS analysis in Dr. Liu’s group in Sun Yat-sen University Cancer Center

  The samples include paired tumor and normal tissues from 205 patients (201 for normal and primary tumor tissues; 4 for normal, primary tumor and liver metastatic tissues). High-coverage WES sequencing or whole genome sequencing of DNA samples were performed on the Illumina HiSeq 2000 system

  Dataset EGAD00001003452

• Whole Exome sequencing of Gingivo-buccal Cancer - ICGC India Project Batch04

  This dataset pertains to whole exome sequencing of paired DNA samples of Gingivo-buccal oral cancer patient.DNA was isolated from the tumor and blood tissues of 47 patients (94 samples).We have performed Nextera exome capture and sequenced exome libraries in Illumina HiSeq platform.We have uploaded BWA-ALN aligned BAM files.

  Dataset EGAD00001003987

• CPTAC: Microscaled Proteogenomic Methods for Precision Oncology

  Cancer proteogenomics combines genomics, transcriptomics and mass spectrometry-based proteomics to gain insights into cancer biology and treatment outcomes. To promote clinical investigation, we developed a "microscaled" proteogenomics approach for tumor-rich frozen core needle biopsies. Tissue-sparing specimen processing ("Biopsy Trifecta EXTraction", BioTExt) and microscaled proteomics (MiProt) generated deep-scale proteogenomics datasets. As a proofof- concept, biopsies were accrued from ERBB2 positive (ERBB2+) breast cancers before and 48 to 72 hours after the first dose of neoadjuvant trastuzumab-based chemotherapy. Multi-omics comparisons were conducted between samples associated with residual disease versus complete pathological response (pCR). Integrated analyses diagnosed diverse molecular causes of treatmentresistance including: 1) absence of ERBB2 amplification (false-ERBB2&#43); 2) insufficient ERBB2 activity for therapeutic sensitivity despite ERBB2 amplification (pseudo-ERBB2&#43); 3) resistance features in true-ERBB2+ cases including androgen receptor signaling, mucin expression and an inactive immune microenvironment; 4) lack of acute phospho-ERBB2 down-regulation in nonpCR cases. We conclude microscaled cancer proteogenomics could improve diagnostic precision.

  Study phs001907

• Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer

  Circulating tumor DNA (ctDNA)-based minimal residual disease (MRD) monitoring shows promise for risk stratification and decision-making in cancer patients. However, factors like background noise from non-tumor DNA, clonal haematopoiesis, and non-shedding tumors may complicate manual interpretation and limit its clinical application. In this proof-of-concept study in advanced non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), we developed an algorithm that automatically classifies serial cell-free DNA (cfDNA) samples, thereby enabling reliable and reproducible interpretation, and preventing time-consuming manual interpretation in approximately 75% of patients. Importantly, application of the algorithm allowed early risk stratification and decision-making, specifically identifying approximately 35% of patients with short-term clinical benefit and approximately 25% of patients who may potentially benefit from treatment escalation. Simultaneous serum tumor marker (STM) monitoring further improved risk stratification and decision-making in our study, enabling accurate identification of all patients with a clinical benefit of at least one year.

  Study EGAS50000001554

• Sequencing of an organoid biobank for childhood kidney cancers that captures disease and tissue heterogeneity.

  Kidney tumors are among the most common solid tumors in children, comprising several distinct subtypes differing in many aspects, including cell-of-origin, genetics, and pathology. Pre-clinical cell models capturing the disease heterogeneity are currently lacking. Here, we describe the first pediatric cancer organoid biobank. It contains tumor and matching normal organoids from over 50 children with different subtypes of kidney cancer, including Wilms tumors, malignant rhabdoid tumors, renal cell carcinomas, and congenital mesoblastic nephromas. The malignant rhabdoid tumor organoids represent the first organoid model for tumors of non-epithelial origin. The tumor organoids retain key properties of native tumors, useful for revealing patient specific drug vulnerabilities. We further demonstrate that organoid cultures derived from Wilms tumors consist of multiple different cell types, including epithelial, stromal and blastemal-like. Our organoid biobank captures the cellular heterogeneity of pediatric kidney tumors, providing a representative collection of well-characterized models for basic cancer research, drug-screening, and personalized medicine.

  Study EGAS00001003853

• Long-read sequencing of diagnosis and post-therapy medulloblastoma reveals complex rearrangement patterns and epigenetic signatures

  Cancer genomes harbor a broad spectrum of structural variants (SV) driving tumorigenesis, a relevant subset of which are likely to escape discovery in short reads. We employed Oxford Nanopore Technologies (ONT) sequencing in a paired diagnostic and post-therapy medulloblastoma to unravel the haplotype-resolved somatic genetic and epigenetic landscape. We assemble complex rearrangements and such associated with telomeric sequences, including a 1.55 Megabasepair chromothripsis event. We uncover a complex SV pattern termed "templated insertion thread", characterized by short (mostly less than 1kb) insertions showing prevalent self-concatenation into highly amplified structures of up to 50kbp in size. Templated insertion threads occur in 3% of cancers, with a prevalence ranging to 74% in liposarcoma, and frequent colocalization with chromothripsis. We also perform long-read based methylome profiling and discover allele-specific methylation (ASM) effects, complex rearrangements exhibiting differential methylation, and differential promoter methylation in seven cancer-driver genes. Our study shows the potential of long-read sequencing in cancer.

  Study EGAS00001006576

• MED12L Gene Alterations Define Aggressive BRCA2-Mutant Prostate Cancers

  Germline mutation of BRCA2 increases the lifetime risk of developing prostate cancer (PCa) by over 700%. BRCA2-mutant PCa have poorer prognosis than sporadic PCa, with rapid development of metastatic, castrate-resistant prostate cancer (mCRPC) and 5-year cancer-specific survival rates of ~50-60%1-4. Despite this, unique genomic driver events that explain the aggressiveness of localized BRCA2-mutant PCa are lacking. We used whole-genome sequencing to fully characterize 14 BRCA2-mutant PCa and demonstrate that BRCA2-mutant PCa is associated with increased genetic instability and a mutually exclusive mutational burden when compared to sporadic PCa. Importantly, BRCA2-mutated cancers are defined by unique copy number gains and hypomethylation events, including alterations in the MED12L/MED12 axis, which are found solely in mCRPC and are enriched in PCa tumours harbouring aggressive intraductal carcinoma (IDC-P) pathologic sub-types. Our findings begin to explain the clinical entity of BRCA2-mutated PCa as these tumours have a unique and aggressive genotype de novo, associated with IDC-P and mCRPC, even in the hormone-naive setting.

  Study EGAS00001001615

• Combined hereditary and somatic mutations of replication error repair genes result in rapid onset of ultra-hypermutated cancers

  DNA replication-associated mutations are repaired by two components: polymerase proofreading and mismatch repair. The mutational consequences of disruption to both repair components in humans are not well studied. We sequenced cancer genomes from children with inherited biallelic mismatch repair deficiency (bMMRD). High-grade bMMRD brain tumors exhibited massive numbers of substitution mutations (>250/Mb) – higher than all childhood and most cancers (>7000 analyzed). All ultra-hypermutated bMMRD cancers acquired early somatic driver mutations in DNA polymerases epsilon or delta. The ensuing mutation signatures and numbers are unique and diagnostic of childhood germline bMMRD (p<10e-13). Sequential tumor biopsy analysis revealed that bMMRD/polymerase mutant cancers rapidly amass an excess of simultaneous mutations (~600 mutations/cell division), reaching but not exceeding ~20,000 exonic mutations in <6 months. Thus implying a threshold compatible with cancer cell survival. We suggest a new mechanism of cancer progression in which mutations develop in a rapid burst after ablation of replication repair.

  Study EGAS00001001112

• The PEACE (Posthumous Evaluation of Advanced Cancer Environment) Study DAC

  Dac EGAC00001003055

• Cancer Genomics Project RCC Data Access Committee

  Dac EGAC00001000109

• DAC for integrated genomics of metastatic prostate cancer

  Dac EGAC00001000230

• The NOWAC blood-breast cancer commitee data access agreement

  Dac EGAC00001000684

• Ludwig Data Access Committee for the Study of Oesophageal Cancer

  Dac EGAC00001000978

• Children's Cancer Therapy Development Institute Data Access Commitee

  Dac EGAC00001001160

• Latency and interval therapy affect the evolution in metastatic colorectal cancer.

  Dac EGAC00001001198

• Zero Childhood Cancer

  Dac EGAC00001001683

• Whole Exome Sequencing of Mixed Histology Lung Cancer at MDACC

  Dac EGAC00001002034

• Peter MacCallum Cancer Centre Research Data Access Committee

  Dac EGAC00001002510

• Garvan/St Vincent’s Prostate Cancer Tissue and Data Access Committee

  Dac EGAC00001002769

• Hoag Family Cancer Institute Carcinoid Multiomic Study Data Access Committee

  Dac EGAC00001003084

• TCR sequencing of TIL in breast cancer data access committee

  Dac EGAC00001003173

• EGAD00010000554

  SNP 6.0 arrays of small cell lung cancer

  Dataset EGAD00010000554

• EGAD00010000556

  SNP 6.0 arrays of small cell lung cancer

  Dataset EGAD00010000556

• OvCan2

  Digital images of ovarian cancer metastases

  Dataset EGAD00010001099

• Human Throid Cancer and CDK4/6 inhibition Data Access Commitee

  Dac EGAC00001003446

• Netherlands Cancer Institute (NKI) - Wilbert Zwart Group

  Dac EGAC00001003257

• Unraveling the genetics of transformed splenic marginal zone lymphoma

  Study EGAS00001006389

• Mechanisms of duodenal adenoma development in familial polyposis syndromes

  Study EGAS00001006561

• Resident memory CD8 T cell in human lung cancer

  Study EGAS00001004707

• Single cell RNAseq of PBMC from bladder cancer patients

  Study EGAS00001004458

• Genomic Analysis of a Metastatic Fusion-negative Embryonal Rhabdomyosarcoma

  Study EGAS00001006946

• University of Melbourne Centre for Cancer Research (UMCCR) Data Access Committee

  Dac EGAC00001003567

• Resolving the Full Spectrum of Human Genome Variation using Linked-Reads

  Large-scale population based analyses coupled with advances in technology have demonstrated that the human genome is more diverse than originally thought. Standard short-read approaches, used primarily due to accuracy, throughput and costs, fail to give a complete picture of a genome. They struggle to identify large, balanced structural events, cannot access repetitive regions of the genome and fail to resolve the human genome into its two haplotypes. Here we describe an approach that retains long range information while harnessing the power of short reads. Starting from only 1ng of DNA, we produce barcoded short read libraries. The use of novel informatic approaches allows for the barcoded short reads to be associated with the long molecules of origin producing a novel datatype known as 'Linked-Reads'. This approach allows for simultaneous detection of small and large variants from a single Linked-Read library. We have previously demonstrated the utility of whole genome Linked-Reads (lrWGS) for performing diploid, de novo assembly of individual genomes. In this manuscript, we show the utility of reference based analysis using a single Linked-Read library for full spectrum genome analysis. We demonstrate the ability of Linked-Reads to reconstruct megabase scale haplotypes and to recover parts of the genome that are typically inaccessible to short reads, including phenotypically important genes such as STRC, SMN1 and SMN2. We demonstrate the ability of both lrWGS and Linked-Read Whole Exome Sequencing (lrWES) to identify complex structural variations, including balanced events, single exon deletions, and single exon duplications. The data presented here show that Linked-Reads provide a scalable approach for comprehensive genome analysis that is not possible using short reads alone.

  Study EGAS00001003121

• We evaluate the potential for routine WGS using ONT by sequencing the well-characterised reference sample NA12878 and the genome of an individual with ataxia-pancytopenia syndrome accompanied by severe immune dysregulation.

  Whole-genome sequencing (WGS) is becoming widely used in clinical medicine in diagnostic contexts and to inform treatment choice. While current sequencing technologies have been extremely successful, their reliance on short read lengths necessarily involves some limitations: accurately assaying certain genomic regions and classes of variation can be problematic. Recent advances in throughput and cost have made WGS using the Oxford Nanopore Technologies (ONT) MinION long-read single-molecule sequencer a potential solution to these challenges. Here we evaluate the potential for routine WGS using ONT by sequencing the well-characterised reference sample NA12878 and the genome of an individual with ataxia-pancytopenia syndrome accompanied by severe immune dysregulation, to 82× and 30× respectively. For NA12878, we evaluated single-nucleotide variant (SNV) calls based on data from multiple base-calling algorithms. We demonstrate that phasing metrics from a novel, reference panel-free, long-read-based method can improve variant-calling performance from otherwise modest levels, resulting in a false discovery rate of 7.1% and false negative rate of 8.5%; remaining errors are concentrated near homopolymers and in regions of reduced sequencing coverage. In the clinical sample, we are able to identify and directly phase two non-synonymous de novo variants in SAMD9L, (OMIM #159550) inferring that they both lie on a common paternal haplotype by overlap with parental genotypes at nearby common variants. This work demonstrates that methodological innovation can substantially reduce variant-calling error rates in ONT data, and that with on-going improvements in throughput, base-calling and dedicated long-read-based SNV-calling methodology, ONT offers promise as an option for clinical WGS.

  Study EGAS00001003469

• Performance Characteristics of Selective Targeted Enrichment in Genetic Diagnostic Testing

  The Nex-StoCT and ACMG recommend that validation of an NGS-based diagnostic test include performance test characteristics for assay accuracy, analytical sensitivity and specificity, reproducibility and repeatability. To measure these parameters for the GEDi capture and sequencing test, 4 samples (three randomly selected patient samples and the NA12878 HapMap sample) were prepared and sequenced in triplicate on each of three separate days. We also performed WES and SNP array genotyping analyses of these 4 samples using Agilent V4+UTR whole exome enrichment kit and Illumina Omni 2.5 SNP arrays, respectively.

  Study phs000798

• Fetal Chorioamniotic Membranes Show Molecular Changes in Placenta Previa and Placenta Accreta Spectrum

  Placenta previa and the placenta accreta spectrum (PAS) are understudied pregnancy disorders with serious consequences for both mother and infant. To better understand the molecular and cellular etiologies of these diseases, we performed 3SEQ of formalin-fixed paraffin-embedded (FFPE) fetal chorioamniotic membrane samples from PAS, previa, and gestationally age-matched spontaneous pre-term birth samples to identify molecule signatures of these diseases. These samples were subsequently validated using a second validation cohort of previa, PAS, and control patients. FFPE archival samples provide opportunities for retrospective molecular investigation of many diseases.

  Study phs002075

• Transcriptional Profiling of PD-1+ and PD-1- Teff and Treg Cells in Glioblastoma and Health

  PD-1 is an important immune checkpoint inhibitor that shows great promise in the clinic, particularly for melanoma and lung cancers. Since PD-1 is also expressed on infiltrating CD4+ Treg and Teffector cells in glioblastoma, we sought to better understand the role of PD-1 on these infiltrating CD4+ Treg and Teffector cells. To this end, we performed functional and transcriptional profiling using CD4+ Treg and Teffector cells isolated from healthy donors and glioblastoma patients (from both tumors and blood).

  Study phs001079

• Spermidine/spermine N1-acetyltransferase controls tissue-specific regulatory T cell function in chronic inflammation

  In this project we wanted to understand the role of tissue resident regulatory T cells with the aim of finding commonalities between multiple inflammatory diseases namely psoriasis, sarcoidosis and inflammatory bowel disease. Using single cell sequencing data we found that specifically in the skin, Spermidine/spermin N1-acetyltransferase seems to mediate a „fragile“ Treg phenotype. To test the influence of the tissue on this phenotype we also sought to charactierize a similar population in patient PBMCs for which we generated this data.

  Study EGAS50000000745

• Targeted panel DNA sequencing of melanomas, nevi and melanocytic tumors

  This dataset was derived from 360 formalin-fixed paraffin-embedded (FFPE) samples distributed across (i) 118 primary melanomas, (ii) 132 nevi and (iii) 110 melanocytic tumors. Next generation sequencing (NGS) libraries were prepared following the FFPE DNA Archer VariantPlex Somatic Protocol for Illumina. Input DNA was determined by the PreSeq DNA QC assay, with 100 ng of DNA used for samples with high quality scores, 200 ng for low quality scores and 300 ng for samples with bad quality scores as defined by the PreSeq DNA QC assay. NGS libraries were quantified using the KAPA Library Quantification Kit for Illumina (KK4824) and sequencing performed on the Nextseq 500/2000 without custom primers using paired-end sequencing (151bp for Read 1 and Read 2) with index reads (8bp for Index Read 1 and Index Read 2). For each sample, resulting paired-end fastq files are available as part of this dataset. Prefix for each sample name is associated with the the type of sample: NAE: nevi samples. MEL: Melanoma samples. BL: melanocytic tumor.

  Dataset EGAD50000001297

• SweGen genetic variation from the Swedish Twin Registry

  The dataset contains files with single nucleotide variants in VCF format for a total of 942 DNA samples, selected to represent a cross-section of the Swedish population. The samples originate from the Swedish Twin Registry (STR) and have been obtained from different geographical regions. For each of the 942 individuals, DNA was extracted from a blood sample and subject to whole genome sequencing (WGS). The WGS was performed using 2x150 bp paired-end chemistry on Illumina HiSeq X Ten instrumentation at the SciLifeLab National Genomics Infrastructure (NGI) in Stockholm and Uppsala. FASTQ files generated by WGS were analyzed using the nf-core pipeline Sarek, which includes pre-processing, alignment to the human GRCh38 reference genome, and germline variant calling. All participants gave their written informed consent and the TwinGene study was approved by the regional ethics committee (Regionala Etikprövningsnämnden, Stockholm, dnr 2007-644-31, dnr 2014/521-32). Access to phenotypic information can be requested from the Swedish Twin Registry (http://ki.se/en/research/the-swedish-twin-registry).

  Dataset EGAD50000001323

• SweGen whole-genome sequencing from the Swedish Twin Registry

  The dataset contains whole-genome sequencing data (aligned read files) in CRAM-format (lossless compression) for a total of 942 DNA samples, selected to represent a cross-section of the Swedish population. The samples originate from the Swedish Twin Registry (STR) and have been obtained from different geographical regions. For each of the 942 individuals, DNA was extracted from a blood sample and subject to whole genome sequencing (WGS). The WGS was performed using 2x150 bp paired-end chemistry on Illumina HiSeq X Ten instrumentation at the SciLifeLab National Genomics Infrastructure (NGI) in Stockholm and Uppsala. FASTQ files generated by WGS were analyzed using the nf-core pipeline Sarek, which includes pre-processing, alignment to the human GRCh38 reference genome, and germline variant calling. All participants gave their written informed consent and the TwinGene study was approved by the regional ethics committee (Regionala Etikprövningsnämnden, Stockholm, dnr 2007-644-31, dnr 2014/521-32). Access to phenotypic information can be requested from the Swedish Twin Registry (http://ki.se/en/research/the-swedish-twin-registry).

  Dataset EGAD50000001326