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. 2012 Apr 17;109(16):5934-41.
doi: 10.1073/pnas.1202490109. Epub 2012 Mar 15.

Sleeping Beauty Mutagenesis Reveals Cooperating Mutations and Pathways in Pancreatic Adenocarcinoma

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Free PMC article

Sleeping Beauty Mutagenesis Reveals Cooperating Mutations and Pathways in Pancreatic Adenocarcinoma

Karen M Mann et al. Proc Natl Acad Sci U S A. .
Free PMC article

Abstract

Pancreatic cancer is one of the most deadly cancers affecting the Western world. Because the disease is highly metastatic and difficult to diagnosis until late stages, the 5-y survival rate is around 5%. The identification of molecular cancer drivers is critical for furthering our understanding of the disease and development of improved diagnostic tools and therapeutics. We have conducted a mutagenic screen using Sleeping Beauty (SB) in mice to identify new candidate cancer genes in pancreatic cancer. By combining SB with an oncogenic Kras allele, we observed highly metastatic pancreatic adenocarcinomas. Using two independent statistical methods to identify loci commonly mutated by SB in these tumors, we identified 681 loci that comprise 543 candidate cancer genes (CCGs); 75 of these CCGs, including Mll3 and Ptk2, have known mutations in human pancreatic cancer. We identified point mutations in human pancreatic patient samples for another 11 CCGs, including Acvr2a and Map2k4. Importantly, 10% of the CCGs are involved in chromatin remodeling, including Arid4b, Kdm6a, and Nsd3, and all SB tumors have at least one mutated gene involved in this process; 20 CCGs, including Ctnnd1, Fbxo11, and Vgll4, are also significantly associated with poor patient survival. SB mutagenesis provides a rich resource of mutations in potential cancer drivers for cross-comparative analyses with ongoing sequencing efforts in human pancreatic adenocarcinoma.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
SB mutagenesis drives pancreatic tumorigenesis in the mouse. Five cohorts of mice were aged and monitored for pancreatic tumor development. All five cohorts carried the Pdx1-Cre driver to activate oncogenic KrasG12D and SB transposase in the pancreas. KrasG12D was required for the high frequency induction of pancreatic tumors. Animals with oncogenic KrasG12D and T2Onc3 died significantly earlier than animals in the other four cohorts (P < 0.001). n is the number of animals aged for tumors.
Fig. 2.
Fig. 2.
Histopathological classification of pancreatic lesions. SB mutagenesis generated pancreatic lesions at all stages of tumor progression. (A) Mice exhibited pancreatic masses that often involved neighboring organs such as the kidney and cecum. Metastatic nodules on the liver (B) and lymph nodes (C) were also often visible on gross inspection. A spectrum of mPanIN lesions was also observed with oncogenic KrasG12D, including early mPanIN1B lesions (D) showing enlarged cell volume and high mucin content in addition to mPanIN2 and mPanIN3 lesions (E). Nineteen animals from the T2Onc2 and T2Onc3 cohorts developed ductal pancreatic tumors. Fourteen animals developed multiple invasive ductal adenocarcinomas (F). Several animals also developed multiple metastatic lesions to the lung (G) and lymph nodes (H and I).
Fig. 3.
Fig. 3.
Circos map of pancreatic cancer candidate cancer genes identified by the GKC method. Transposon insertions in the plus (orange lines) and minus (purple lines) strands show genome-wide coverage of mutagenesis. GKC CCGs are illustrated on the outer perimeter of the plot with their exact location denoted by a black line. Genes listed in red are mutated in human pancreatic cancer. The blue lines in the center connect bolded GKC CCGs that significantly co-occur in tumors (Fisher exact test, P < 0.0003).
Fig. 4.
Fig. 4.
CTNND1 and GNAQ show absent or weak staining in human pancreatic tumors. Immunohistochemistry was performed on a human pancreatic tissue microarray for (A) CTNND1 and (B) GNAQ. Arrows indicate tumors with weak or absent staining, whereas adjacent benign ducts or acini (indicated by white arrowheads) verify the presence of intact staining in tissue sections. Weak or absent staining of (C) CTNND1 (log rank P = 0.022) and (D) GNAQ (log rank P = 0.051) is predictive of poor survival. Kaplan–Meier plots (C and D) of patient survival represent two patient groups dichotomized into the top two tertiles (green) vs. bottom tertile (blue) using the histoscore for high and low staining.

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