High-resolution characterization of the pancreatic adenocarcinoma genome - PubMed (original) (raw)

. 2004 Jun 15;101(24):9067-72.

doi: 10.1073/pnas.0402932101.

Cameron Brennan, Gerald Bailey, Raktim Sinha, Bin Feng, Christopher Leo, Yunyu Zhang, Jean Zhang, Joseph D Gans, Nabeel Bardeesy, Craig Cauwels, Carlos Cordon-Cardo, Mark S Redston, Ronald A DePinho, Lynda Chin

Affiliations

High-resolution characterization of the pancreatic adenocarcinoma genome

Andrew J Aguirre et al. Proc Natl Acad Sci U S A. 2004.

Abstract

The pancreatic adenocarcinoma genome harbors multiple amplifications and deletions, pointing to the existence of numerous oncogenes and tumor suppressor genes driving the genesis and progression of this lethal cancer. Here, array comparative genomic hybridization on a cDNA microarray platform and informatics tools have been used to define the copy number alterations in a panel of 24 pancreatic adenocarcinoma cell lines and 13 primary tumor specimens. This high-resolution genomic analysis has identified all known regional gains and losses as well as many previously uncharacterized highly recurrent copy number alterations. A systematic prioritization scheme has selected 64 focal minimal common regions (MCRs) of recurrent copy number change. These MCRs possess a median size of 2.7 megabases (Mb), with 21 (33%) MCRs spanning 1 Mb or less (median of 0.33 Mb) and possessing an average of 15 annotated genes. Furthermore, complementary expression profile analysis of a significant fraction of the genes residing within these 64 prioritized MCRs has enabled the identification of a subset of candidates with statistically significant association between gene dosage and mRNA expression. Thus, the integration of DNA and RNA profiles provides a highly productive entry point for the discovery of genes involved in the pathogenesis of pancreatic adenocarcinoma.

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Figures

Fig. 1.

Fig. 1.

Genomic profiles from pancreatic adenocarcinoma samples. Array-CGH profiles with x axis coordinates representing cDNA probes ordered by genomic map positions. Segmented data are displayed in red, median filtered (three nearest neighbors) in blue, and raw data in black. (A) Whole-genome profiles of primary tumor specimen PA.T.7692 (Upper) and cell line Panc 10.05 (Lower). Note presence of focal high-level amplifications and deletions as well as large regional gains and losses in both samples. (B) Recurrence of chromosomal alterations. (Upper) Integer-value recurrence of CNAs in segmented data (y axis) plotted for each cDNA probe evenly aligned along the x axis in genome order. Dark red or green bars denote gain or loss of chromosome material. Bright red or green bars represent probes within regions of amplification or deletion. (Lower)

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(Eisen laboratory, University of California, Berkeley) showing discrete CNAs within all samples. Red represents chromosomal gain, and green denotes chromosomal loss. (C) CGH profiles of 12p12.3-q13.3 locus (locus no. 15, Table 1) in three samples illustrating the definition of the physical extent, peak profile, and MCRs for that locus. Note that the left MCR is defined by the overlap between samples on top and bottom, whereas the right MCR is defined by the overlap between the two samples on top. Because data points are plotted on the x axis by genomic map positions, gaps in the profiles encompass regions of copy number transition for which there is no data point.

Fig. 2.

Fig. 2.

QPCR verifies complexity within CNAs. (A) Chromosome 7 CGH profiles (Left) showing amplification of a discrete region of 7q22 in both the AsPC-1 cell line and PA.T.14172 (locus no. 9, Table 1), with MCR defined by both samples (outlined by dashed lines). A-D indicate the relative positions of QPCR assays (Right), which confirm the gene copy alterations in AsPC-1 (dark gray bars) and PA.T.14172 (light gray bars). (B) Chromosome 9 array-CGH profile (Left) for a complex CNA in the HUP-T3 cell line. Homozygous deletion of the known target p16Ink4a is confirmed by QPCR (Right), which also verifies existence of two discrete focal amplicons and a narrow region of one-copy loss revealed by array-CGH. Note that CNAs covered by only one or two probes are not identified by the segmentation algorithm.

Fig. 3.

Fig. 3.

Combined array-CGH and expression analysis facilitates identification of candidate genes. (A) Analysis of 17q23.2-25.3 locus (locus no. 21, Table 1) in cell line Hup T3. (Upper) Array-CGH profile of HUP-T3. (Lower) Expression profile of genes on Affymetrix U133A array within the specified locus for the HUP-T3 cell line. Note that the subset of genes exhibiting prominent gene dosage correlated expression fall within the peak of the locus (arrows). (B) Analysis of 9p24.3-21.2 locus (locus no. 41, Table 1) in the cell line BxPC-3. (Upper) Array-CGH profile of the 9p region. (Lower) Affymetrix expression profile of genes mapping to the same region. Note the dramatically reduced expression of the p16INK4A gene (arrows) within the MCR. (C) Correlation of p16INK4A expression and copy number in 24 cell lines analyzed. Note the bimodal distribution of both expression values and copy number values for this gene across all samples (green lines). The red box defines those samples (BxPC-3, MiaPaCa, Capan 1, Hup-T3, and Dan-G) in which p16INK4A is homozygously deleted and not expressed. The blue box encloses samples (Panc-1, Panc 03.27, SW1990, Panc 08.13, Hup-T4, and Panc 02.13) in which p16INK4A is present but with absent or reduced expression.

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