aCGH and oCGH were performed with DNA isolated from FFPE preserved samples from four different radical prostatectomy cases (designated 13P, 33P, 34P, 41P) using both BAC arrays containing 2,460 BAC clones printed at UCSF as well as Agilent’s Human Genome 44 or 244 K 60 mer oligonucleotide arrays containing approximately 40,000 and 244,000 probes, respectively. Samples were selected to represent both good (≥12 kb) and poor quality (≥500 bp) DNA that is obtained from FFPE tissue. All samples were archived for 8 years prior to processing, except sample 41P which was 6 years old.
Detailed comparison of aberration calls made from the 44 K oligonucleotide and BAC array data was performed for FFPE samples 13P and 33P, with the focus being regions where both platforms had overlapping probes. Dye flip experiments for the oligonucleotide data were combined, and aberrations were called using CGH Analytics aberration detection algorithm ADM-1 with a threshold of 6. Aberrations in BAC data were identified using the standard sample specific threshold method [6
] and also using ADM-1. Aberrant intervals identified in the BAC data showed good agreement with corresponding intervals from the oligonucleotide data ( and ). We also computed the fraction of BAC probes above or below the sample specific threshold showing gain or loss that were inside oligonucleotide amplified or deleted intervals. For samples 13P and 33P, 82 and 90%, respectively, of BAC probes showing gain or loss were identified within oligonucleotide aberrant intervals.
Fig. 1 Genome view of a CGH aberration calls for samples 13P (A) and 33P (B). The upper panel of each set shows the oligonucleotide array dye flip pair results and the lower panel displays the BAC array results, both display log2 ratio splotted as a function (more ...)
Comparison of Aberration Calls Made by ADM-1 Algorithm for BAC and Oligonucleotide Data
There was good concordance observed between the overall copy number profiles across the genome obtained from the BAC and oligonucleotide array platforms for both samples 13P and 33P both in terms of the genomic position of the gains and losses and in the magnitude of the copy number differences (). The Pearson correlation of the average log2
ratios in matching aberrant regions was 0.87 and 0.96 for samples 13P and 33P, respectively. For example, deletion of the entire p arm on chromosome 8 for sample 13P was identified by an average log2
ratio in both the BAC and oligonucleotide data as 0.56. This deletion call was based on 59 BAC probes and 556 oligonucleotide probes, extending from 0 to 38 Mb in the BAC data and 0 to 43 Mb in the oligonucleotide data. A detailed visualization of the aberrations observed on chromosome 8 is highlighted in . Chromosome 8 was chosen because 8p is known to be commonly deleted in prostate cancer [9
Fig. 2 Detailed view of oligonucleotide and BAC aCGH data on chromosomes 8 and 12. Log2 ratios are plotted for each probe as a function of chromosomal position. Probes with log2 ratio >0.25 are shown in red, probes with log2 ratio <−0.25 (more ...)
In some cases, the oligonucleotide array platform provided more precise mapping of aberration boundaries due to the higher density of oligonucleotide probes. The higher density of oligonucleotide probes can also add statistical confidence to copy number calls, especially where only one BAC probe maps to an aberration. An example highlighting this was found in sample 13P on chromosome 12 (p 12.1) where the same copy number change was observed in both the BAC and oligonucleotide array data. However, the aberration breakpoints were more precisely mapped in the oligonucleotide data due to the higher density of probes (), thereby narrowing the number of candidate genes.
Oligonucleotide arrays developed specifically for CGH [2
] and whole genome BAC tiling arrays [12
] have the potential to provide very high-resolution copy number measurements. The goal of these experiments was to assess the quality of CGH data obtained with whole genome oligonucleotide arrays using clinically relevant, but challenging DNA from archived prostate tissue, that has been shown previously to work well using BAC arrays. The results from the oligonucleotide array platform correlated very well with the BAC array results although there were some instances of aberrations detected more robustly and with more precise mapping with the oligonucleotide arrays due to the higher probe density on these arrays. The only considerable differences were attributable to regions where clones were absent in the BAC data. It is note worthy that Agilent has selected probes biased toward genes, in particular cancer related genes (represented by a minimum of two probes), ensuring adequate coverage in the most commonly studied genomic regions.
In our hands, DNA extracted from frozen or FFPE tissue using our published protocols are equivalent for BAC-based aCGH and this is true regardless of the laboratory of source’s fixation protocol [1
]. This is consistent with a study published by Little et al. comparing frozen and FFPE DNA for CGH on BAC arrays. In the present study matched fresh frozen and fixed specimens could not be directly compared. To overcome this limitation, we embedded DUI45 prostate cancer cells to mimic routine frozen and FFPE archiving and compared extracted DNA on 244 K oCGH arrays to DNA extracted from unfixed DU145 cells on BAC arrays. The frozen and FFPE DNA produced concordant copy number profiles on the Agilent arrays and produced copy number profiles essentially identical to each other (). In addition, these profiles match our unpublished and others published BAC aCGH data for DU145 [14
]. We chose to focus on FFPE material in this manuscript because it is commonly believed to be more difficult to work with than frozen material and because of its importance for translational research.
DU145 fresh and fixed tissue penetrance plot for the frozen and FFPE 244KoCGH data. The frequency of a copy number call at a particular locus is shown for each chromosome, with gains in red and losses in green.
DNA yields from FFPE specimens may be small because many of the most informative experiments and clinical applications will need to begin with needle biopsies where yields may be in the range of 500 ng. Thus, it is significant that we obtained comparable oCGH results using only 500 ng of FFPE (). shows an overlay of BAC-based aCGH and oCGH using 1 μg DNA and oCGH using 500 ng DNA from sample 13P (). Qualitative assessment of two additional oCGH 500 ng samples in shows great similarity with the corresponding aCGH data using 1 μg of DNA. The average log2 ratio standard deviation of the replicate probes randomly dispersed on the array, which serve as a measure of the quality of the array result, was 0.028 (34P) and 0.071 (41P). Next we extracted DNA from an FFPE prostate tumor biopsy and for analysis on the 244K oCGH platform. The average standard deviation of the log2 ratios for the replicate probes on the biopsy array was 0.039. A penetrance plot is shown for the copy number changes detected by oCGH for the biopsy and its matched primary tumor (). It may of interest to note the similarity between the two copy number plots despite the fact that distinct foci of the same tumor were analyzed.
Fig. 4 Genome view of aCGH and oCGH aberration calls using Agilent’s CGH Analytics software. A: Sample 13P 44KoCGH with 1 μg sample input (purple) and oCGH with 500 ng input (blue), and BAC aCGH with 1 μg input (green). Aberration calls (more ...)
Fig. 5 FFPE prostate biopsy and matched primary oCGH penetrance plot. Both samples were run with 500 ng unamplified DNA on Agilent’s 244K oCGH platform. The frequency of gains and deletions are shown in red and green, respectively, for each chromosome. (more ...)