Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Ena-DATASET-JHU-SOM-01-09-2017-17:11:13:045-143 - samples

ABSTRACT: The dataset for Direct Detection of Early-Stage Cancers using Circulating Tumor DNA includes 602 bam files from next-generation sequencing on the Illumina HiSeq2500 or MiSeq. The samples analyzed include cancer cell lines as well as plasma and tissue specimens from healthy individuals and patients with cancer.

PROVIDER: EGAD00001003601 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Json Xml

Publications

Direct detection of early-stage cancers using circulating tumor DNA.

Phallen Jillian J Sausen Mark M Adleff Vilmos V Leal Alessandro A Hruban Carolyn C White James J Anagnostou Valsamo V Fiksel Jacob J Cristiano Stephen S Papp Eniko E Speir Savannah S Reinert Thomas T Orntoft Mai-Britt Worm MW Woodward Brian D BD Murphy Derek D Parpart-Li Sonya S Riley David D Nesselbush Monica M Sengamalay Naomi N Georgiadis Andrew A Li Qing Kay QK Madsen Mogens Rørbæk MR Mortensen Frank Viborg FV Huiskens Joost J Punt Cornelis C van Grieken Nicole N Fijneman Remond R Meijer Gerrit G Husain Hatim H Scharpf Robert B RB Diaz Luis A LA Jones Siân S Angiuoli Sam S Ørntoft Torben T Nielsen Hans Jørgen HJ Andersen Claus Lindbjerg CL Velculescu Victor E VE

Science translational medicine 20170801 403

Early detection and intervention are likely to be the most effective means for reducing morbidity and mortality of human cancer. However, development of methods for noninvasive detection of early-stage tumors has remained a challenge. We have developed an approach called targeted error correction sequencing (TEC-Seq) that allows ultrasensitive direct evaluation of sequence changes in circulating cell-free DNA using massively parallel sequencing. We have used this approach to examine 58 cancer-re ...[more]

PMID: 28814544

Similar Datasets

Palaniappan2021_Cell free modelling of second generation Toehold switches

Project description:Cervical cancer is a global public health subject as it affects women in the reproductive ages, and accounts for the second largest burden among cancer patients worldwide with an unforgiving 50% mortality rate. Poor awareness and access to effective diagnosis have led to this enormous disease burden, calling for point-of-care, minimally invasive diagnosis methods. Here, an end-to-end quantitative approach for a new kind of diagnosis has been developed, comprising identification of optimal biomarkers, design of the sensor, and simulation of the diagnostic circuit. Using miRNA expression data in the public domain, we identified circulating miRNA biomarkers specific to cervical cancer using multi-tier screening. Synthetic riboregulators called toehold switches specific for the biomarker panel were then designed. To predict the dynamic range of toehold switches for use in genetic circuits as biosensors, we developed a generic grammar of these switches, and built a multivariate linear regression model using thermodynamic features derived from RNA secondary structure and interaction. The model yielded predictions of toehold efficacy with an adjusted R2 = 0.59. Reaction kinetics modelling was performed to predict the sensitivity of the second-generation toehold switches to the miRNA biomarkers. Simulations showed a linear response between 10nM and 100nM before saturation. Our study demonstrates an end-to-end workflow for the efficient design of genetic circuits geared towards the effective detection of unique genomic signatures that would be increasingly important in today’s world. The approach has the potential to direct experimental efforts and minimise costs. All resources are provided open-source (https://github.com/igem2019) under GNU GPLv3 licence.

2022-05-05 | MODEL2107150001 | BioModels

ena-DATASET-GTI-14-02-2017-17:04:07:050-336 - samples

Project description:For each subject, genomic DNA from whole blood, circulating cell free DNA and tumor tissues (whenever possible) were performed targeting next generation sequencing on Illumina Miseq or Hiseq 4000 platforms. The sequencing results of whole blood were used to distinguish germline and somatic mutations. Specimens were collected from patients with different kinds of solid tumors, but most are lung cancer patients.

| EGAD00001003176 | EGA

Evaluating the gut microbiota shifts caused by two diets based on ancient grains

Project description:Total DNA was extracted from stool specimens, amplified to collect amplicons of variable V3–V4 regions of the bacterial 16s rRNA gene and sequenced with MiSeq (2x300bp) Illumina platform.

2022-08-24 | GSE206807 | GEO

Analysis of microbiota composition within breast tumor and healthy breast tissues in males and females

Project description:Total DNA was extracted from FFPE specimens of breast tumor and surrounding healthy tissue, amplified to collect amplicons of variable V3–V4 regions of the bacterial 16s rRNA gene and sequenced with MiSeq (2x300bp) Illumina platform.

2023-06-14 | GSE212891 | GEO

Circulating microRNAs as non-invasive biomarkers for early detection of non-small-cell lung cancer

Project description:Plasma samples from 100 early stage (I to IIIA) non–small-cell lung cancer (NSCLC) patients and 100 non-cancer controls were screened for 754 circulating microRNAs via qRT-PCR, using TaqMan MicroRNA Arrays. Our objective was to identify a panel of circulating microRNAs in plasma that will contribute to early detection of lung cancer.

2015-12-31 | GSE64591 | GEO

Optimization of ultracentrifugation-based method to enhance the purity and proteomic profiling depth of plasma-derived extracellular vesicles and particles

Project description:Circulating extracellular vesicles and particles (EVPs) are being investigated as potential biomarkers for early cancer detection, prognosis, and disease monitoring. However, the suboptimal purity of EVPs isolated from peripheral blood plasma has posed a challenge of in-depth analysis of the EVP proteome. Here, we compared the effectiveness of different methods for isolating EVPs from healthy donor plasma, including ultracentrifugation (UC)-based protocols, phosphatidylserine-Tim4 interaction-based affinity capture (referred to as "PS"), and several commercial kits. Modified UC methods with an additional UC washing or size exclusion chromatography step substantially improved EVP purity and enabled the detection of additional proteins via proteomic mass spectrometry, including many plasma membrane and cytoplasmic proteins involved in vesicular regulation pathways. This improved performance was reproduced in cancer patient plasma specimens, resulting in the identification of a greater number of differentially expressed EVP proteins, thus expanding the range of potential biomarker candidates. However, PS and other commercial kits did not outperform UC-based methods in improving plasma EVP purity. PS yielded abundant contaminating proteins and a biased enrichment for specific EVP subsets, thus unsuitable for proteomic profiling of plasma EVPs. Therefore, we have optimized UC-based protocols for circulating EVP isolation, which enable further in-depth proteomic analysis for biomarker discovery.

2024-08-10 | PXD052726 | Pride

High concordance between Illumina HiSeq2500 and NextSeq500 for Reduced Representation Bisulfite Sequencing (RRBS)

Project description:Reduced representation bisulfite sequencing (RRBS) provides an efficient method for measuring DNA methylation at single base resolution in regions of high CpG density. This technique has been extensively tested on the HiSeq2500, which uses a 4-colour detection method, however it is unclear if the method will also work on the NextSeq500 platform, which employs a 2-colour detection system. We created an RRBS library and sequenced it on both the HiSeq2500 and NextSeq500, and found no significant difference in the base composition of reads derived from either machine. Moreover, the methylation calls made from the data of each instrument were highly concordant, with methylation patterns across the genome appearing as expected. Therefore, RRBS can be sequenced on the Nextseq500 with comparable quality to that of the HiSeq2500.

2017-02-09 | GSE87097 | GEO

Reanalysis of transcriptomic profiling of isolated CTC from 31 patients

Project description:The CTC-iChip microfluidic device [PMID: 23552373 ] enables isolation of rare viable circulating tumor cells (CTCs) directly from whole blood specimens of patients with cancer. Reanalysis of freshly isolated CTC from 31 women with hormone receptor positive metastatic breast cancer.

2023-06-20 | GSE215886 | GEO

ena-DATASET-JHU-UAD-14-09-2018-18:13:52:593-711 - samples

Project description:The dataset for Evolution of neoantigen landscape during immune checkpoint blockade in non-small cell lung cancer includes 17 bam files from next-generation sequencing on the Illumina HiSeq2500. The biospecimens analyzed include matched tumor pre-treatment, post-progression and normal samples.

| EGAD00001004336 | EGA

A gene expression profile that predicts circulating tumor cell presence in breast cancer patients

Project description:Development of a primary tumor gene expression profile that can predict the presence of circulating tumor cells in the blood of breast cancer patients. The detection of circulating tumor cells (CTCs) in the peripheral blood and microarray gene expression profiling of the primary tumor are two promising new technologies able to provide valuable prognostic data for patients with breast cancer. In the current study, we aimed to develop a novel profile which provided independent prognostic data by building a signature predictive of CTC status rather than outcome. Seventy-two primary breast cancer tumor have been analyzed against a breast cancer reference pool.

2012-04-11 | E-GEOD-31364 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data