Transcriptomics

Dataset Information

20

Expression profiling of pancreatic ductal adenocarcinoma


ABSTRACT: Pancreatic ductal adenocarcinoma (PDAC) has the worst prognosis of all common cancers, but divergent outcomes are apparent between patients. To delineate the intertumor heterogeneity that contributes to this, we aimed to identify clinically distinct gene expression-based subgroups. From a cohort of 345 resected pancreatic cancer cases, 90 samples with confirmed diagnosis of PDAC and sufficient tumor content were available for gene expression analysis by RNA sequencing. Unsupervised classification was applied, and a classifier was constructed. Species-specific transcript analysis on matching patient-derived xenografts (PDX, N=14) allowed construction of tumor- and stroma-specific classifiers for use on PDX models and cell lines.

INSTRUMENT(S): Illumina HiSeq 2500

ORGANISM(S): Homo sapiens  

DISEASE(S): Pancreatic Ductal Adenocarcinoma

SUBMITTER: Maarten F. Bijlsma   Hao Huang  

PROVIDER: E-MTAB-6830 | ArrayExpress | 2020-01-25

SECONDARY ACCESSION(S): ERP109062

REPOSITORIES: ArrayExpress, ENA

Dataset's files

Source:
Action DRS
E-MTAB-6830.idf.txt Idf
E-MTAB-6830.idf.txt_original Idf
E-MTAB-6830.sdrf.txt Txt
Items per page:
1 - 3 of 3
altmetric image

Publications


Pancreatic ductal adenocarcinoma (PDAC) has the worst prognosis of all common cancers. However, divergent outcomes exist between patients, suggesting distinct underlying tumor biology. Here, we delineated this heterogeneity, compared interconnectivity between classification systems, and experimentally addressed the tumor biology that drives poor outcome. RNA-sequencing of 90 resected specimens and unsupervised classification revealed four subgroups associated with distinct outcomes. The worst-pr  ...[more]

Similar Datasets

2020-01-25 | E-MTAB-6830 | BioStudies
2020-01-01 | S-EPMC6962149 | BioStudies
1000-01-01 | S-EPMC6198443 | BioStudies
2019-01-01 | S-EPMC6411448 | BioStudies
2016-01-01 | S-EPMC4941373 | BioStudies
2020-01-01 | S-EPMC7315507 | BioStudies
2019-01-01 | S-EPMC6328084 | BioStudies
2019-01-01 | S-EPMC6937817 | BioStudies
2019-01-01 | S-EPMC6329841 | BioStudies
1000-01-01 | S-EPMC4464647 | BioStudies