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Genome Landscape of Primary Pancreatic Ductal Adenocarcinoma

The purpose of the Australian ICGC Pancreatic Cancer Genome Sequencing Initiativestudy is to identify the common driving mutations underlying the initiation anddevelopment of Pancreatic Adenocarcinoma in a large cohort of pancreatic cancerpatients (n=350). Matched genome sequences will be generated from normal tissue(duodenum) and resected primary tumour tissue in each patient using exome andwhole genome sequencing. The complete repertoire of somatic mutations will bedetermined (substitutions, indels, copy number changes and structural changes).Where possible, matched transcriptome sequencing will also be carried out todetermine locus activity, which mutations are actively expressed and whichrearrangements give rise to gene-fusion transcripts.

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
EGAD00001000049 AB SOLiD 4 System AB SOLiD System 3.0 26
EGAD00001000096 AB SOLiD 4 System 166
EGAD00001000323 AB SOLiD 4 System Illumina HiSeq 2000 200
EGAD00001000371 Illumina HiSeq 2000 Illumina HiSeq 2500 54
EGAD00001000660 353
EGAD00001002192 346
EGAD00001003298 96
Publications Citations
Pancreatic cancer genomes reveal aberrations in axon guidance pathway genes.
Nature 491: 2012 399-405
Whole genomes redefine the mutational landscape of pancreatic cancer.
Nature 518: 2015 495-501
Genomic analyses identify molecular subtypes of pancreatic cancer.
Nature 531: 2016 47-52
ROBO2 is a stroma suppressor gene in the pancreas and acts via TGF-β signalling.
Nat Commun 9: 2018 5083
HNF4A and GATA6 Loss Reveals Therapeutically Actionable Subtypes in Pancreatic Cancer.
Cell Rep 31: 2020 107625
Single-PanIN-seq unveils that ARID1A deficiency promotes pancreatic tumorigenesis by attenuating KRAS-induced senescence.
Elife 10: 2021 e64204
Open-source curation of a pancreatic ductal adenocarcinoma gene expression analysis platform (pdacR) supports a two-subtype model.
Commun Biol 6: 2023 163
Generalising uncertainty improves accuracy and safety of deep learning analytics applied to oncology.
Sci Rep 13: 2023 7395