CNA differences between RNA-based subtypes of PDAC

Pancreatic ductal adenocarcinomas (PDAC) have a dismal prognosis with a 5-year survival of <5%. Chemoresistance and recurrences, seen in approximately 70% of PDAC patients, may partly be explained by intratumor heterogeneity (ITH) through which tumors may develop ‘escape routes’. In the Pancreas Multibiopsy (PM)-project we have obtained multiple fragments from pancreatic and other peri-ampullary carcinomas in order to reveal potential ITH and identify genetic aberrations that predict outcome after surgery and response to chemotherapy. CNA-profiles were used to complement the characterization of liabilities in PDAC that we identified previously using RNAseq in the form of epithelial, secretory, compound pancreatic, and mesenchymal subgroups that showed survival outcomes. Comparison of CNA-profiles between these transcriptomics-based subgroups (with 8, 3, 6, and 6 tumors respectively per group) showed differences, ranging from ‘quiet’(i.e. hardly any CNA) to ‘wild’(i.e. lots of CNA), but these were not statistically significant (Chi2 0.09). When differentiating between the classical and basal-like molecular subtypes of PDAC differences in CNA (high or low) were even less statistically significant (Chi2 0.292).

Type: Cancer Genomics
Archiver: European Genome-Phenome Archive (EGA)

1 Dataset 1 Publication

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD50000001732	Associated with CNA differences between RNA-based subtypes of PDAC. Shallow Whole Genome Sequencing (sWGS) generated 47 .bam files from 37 patients. sWGS was used for Copy number aberrations (CNA) determination.	Illumina HiSeq 2500	47

Publications	Citations
Unsupervised class discovery in pancreatic ductal adenocarcinoma reveals cell-intrinsic mesenchymal features and high concordance between existing classification systems. Dijk F, Veenstra VL, Soer EC, Dings MPG, Zhao L, Halfwerk JB, Hooijer GK, Damhofer H, Marzano M, Steins A, Waasdorp C, Busch OR, Besselink MG, Tol JA, Welling L, van Rijssen LB, Klompmaker S, Wilmink HW, van Laarhoven HW, Medema JP, Vermeulen L, van Hooff SR, Koster J, Verheij J, van de Vijver MJ, Wang X, Bijlsma MF. Sci Rep 10: 2020 337	52

Publications

Citations

Unsupervised class discovery in pancreatic ductal adenocarcinoma reveals cell-intrinsic mesenchymal features and high concordance between existing classification systems.
Dijk F, Veenstra VL, Soer EC, Dings MPG, Zhao L, Halfwerk JB, Hooijer GK, Damhofer H, Marzano M, Steins A, Waasdorp C, Busch OR, Besselink MG, Tol JA, Welling L, van Rijssen LB, Klompmaker S, Wilmink HW, van Laarhoven HW, Medema JP, Vermeulen L, van Hooff SR, Koster J, Verheij J, van de Vijver MJ, Wang X, Bijlsma MF. Sci Rep 10: 2020 337