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DNA fragmentation simulation method (FSM) and fragment size matching improve aCGH performance of FFPE tissues.

Craig JM, Vena N, Ramkissoon S, Idbaih A, Fouse SD, Ozek M, Sav A, Hill DA, Margraf LR, Eberhart CG, Kieran MW, Norden AD, Wen PY, Loda M, Santagata S, Ligon KL, Ligon AH - PLoS ONE (2012)

Bottom Line: While robust for basic research studies, reliable whole-genome copy number analysis has been unsuccessful in routine clinical practice due to a number of technical limitations.Most important, aCGH results have been suboptimal because of the poor integrity of DNA derived from formalin-fixed paraffin-embedded (FFPE) tissues.Results from FFPE samples were equivalent to results from fresh samples and those available through the glioblastoma Cancer Genome Atlas (TCGA).

View Article: PubMed Central - PubMed

Affiliation: Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America.

ABSTRACT
Whole-genome copy number analysis platforms, such as array comparative genomic hybridization (aCGH) and single nucleotide polymorphism (SNP) arrays, are transformative research discovery tools. In cancer, the identification of genomic aberrations with these approaches has generated important diagnostic and prognostic markers, and critical therapeutic targets. While robust for basic research studies, reliable whole-genome copy number analysis has been unsuccessful in routine clinical practice due to a number of technical limitations. Most important, aCGH results have been suboptimal because of the poor integrity of DNA derived from formalin-fixed paraffin-embedded (FFPE) tissues. Using self-hybridizations of a single DNA sample we observed that aCGH performance is significantly improved by accurate DNA size determination and the matching of test and reference DNA samples so that both possess similar fragment sizes. Based on this observation, we developed a novel DNA fragmentation simulation method (FSM) that allows customized tailoring of the fragment sizes of test and reference samples, thereby lowering array failure rates. To validate our methods, we combined FSM with Universal Linkage System (ULS) labeling to study a cohort of 200 tumor samples using Agilent 1 M feature arrays. Results from FFPE samples were equivalent to results from fresh samples and those available through the glioblastoma Cancer Genome Atlas (TCGA). This study demonstrates that rigorous control of DNA fragment size improves aCGH performance. This methodological advance will permit the routine analysis of FFPE tumor samples for clinical trials and in daily clinical practice.

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“Matching” DNA fragment size distributions are necessary for optimal aCGH data.(A,C,E,G) Agarose gel electrophoresis images and ImageJ gel intensity analysis plots of reference gDNA (Promega) after heat fragmentation. Mode fragment size is indicated in blue (bp) relative to DNA ladder. Heat times were adjusted to produce four mode fragment size combinations (225/225, 525/225, 525/140, 225/140). (B,D,F,H) Plot of results from chromosome 1 following self-hybridization of specific combinations of mode size. Differentially labeled aliquots (cy5/cy3) were coded as follows: green;log2ratio<-0.3, black;-0.3≤log2ratio≤0.3, red;log2ratio>0.3. Data quality was assessed by dLRsd on Agilent 180 K arrays.
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pone-0038881-g001: “Matching” DNA fragment size distributions are necessary for optimal aCGH data.(A,C,E,G) Agarose gel electrophoresis images and ImageJ gel intensity analysis plots of reference gDNA (Promega) after heat fragmentation. Mode fragment size is indicated in blue (bp) relative to DNA ladder. Heat times were adjusted to produce four mode fragment size combinations (225/225, 525/225, 525/140, 225/140). (B,D,F,H) Plot of results from chromosome 1 following self-hybridization of specific combinations of mode size. Differentially labeled aliquots (cy5/cy3) were coded as follows: green;log2ratio<-0.3, black;-0.3≤log2ratio≤0.3, red;log2ratio>0.3. Data quality was assessed by dLRsd on Agilent 180 K arrays.

Mentions: Despite the initially intact and identical condition of the gDNA in each pair, three out of four self-hybridizations failed to achieve derivative log ratio spread (dLRsd) values less than 0.3, a primary QC metric and threshold for array data quality [19], [28] (Figure 1). The self-hybridization pair with matched DNA size distributions that had been exposed to identical fragmentation conditions resulted in a dLRsd of less than 0.3 (Figure 1A, B), indicating a hybridization likely to yield robust copy number data. The introduction of even moderate size mismatches (300 bp differential) was sufficient to introduce profound changes in final data quality, even when the mismatch resulted from an increase in fragment size (Figure 1C, D). Additional loss of data quality was noted when the difference in fragment sizes between the competitively hybridized DNA samples was further increased to 385 bp (Figure 1E, F). The magnitude of the size mismatch effect on data quality is not completely dependent on the magnitude of the size differential, however; as seen in the high dLRsd of the array data in Figure 1G, H, it is likely that decreased fragment size also adds complexity to the mechanism. These findings demonstrate that fragment size matching is critical for reducing the variability of array data quality even when using highly intact, optimal DNA samples.


DNA fragmentation simulation method (FSM) and fragment size matching improve aCGH performance of FFPE tissues.

Craig JM, Vena N, Ramkissoon S, Idbaih A, Fouse SD, Ozek M, Sav A, Hill DA, Margraf LR, Eberhart CG, Kieran MW, Norden AD, Wen PY, Loda M, Santagata S, Ligon KL, Ligon AH - PLoS ONE (2012)

“Matching” DNA fragment size distributions are necessary for optimal aCGH data.(A,C,E,G) Agarose gel electrophoresis images and ImageJ gel intensity analysis plots of reference gDNA (Promega) after heat fragmentation. Mode fragment size is indicated in blue (bp) relative to DNA ladder. Heat times were adjusted to produce four mode fragment size combinations (225/225, 525/225, 525/140, 225/140). (B,D,F,H) Plot of results from chromosome 1 following self-hybridization of specific combinations of mode size. Differentially labeled aliquots (cy5/cy3) were coded as follows: green;log2ratio<-0.3, black;-0.3≤log2ratio≤0.3, red;log2ratio>0.3. Data quality was assessed by dLRsd on Agilent 180 K arrays.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3376148&req=5

pone-0038881-g001: “Matching” DNA fragment size distributions are necessary for optimal aCGH data.(A,C,E,G) Agarose gel electrophoresis images and ImageJ gel intensity analysis plots of reference gDNA (Promega) after heat fragmentation. Mode fragment size is indicated in blue (bp) relative to DNA ladder. Heat times were adjusted to produce four mode fragment size combinations (225/225, 525/225, 525/140, 225/140). (B,D,F,H) Plot of results from chromosome 1 following self-hybridization of specific combinations of mode size. Differentially labeled aliquots (cy5/cy3) were coded as follows: green;log2ratio<-0.3, black;-0.3≤log2ratio≤0.3, red;log2ratio>0.3. Data quality was assessed by dLRsd on Agilent 180 K arrays.
Mentions: Despite the initially intact and identical condition of the gDNA in each pair, three out of four self-hybridizations failed to achieve derivative log ratio spread (dLRsd) values less than 0.3, a primary QC metric and threshold for array data quality [19], [28] (Figure 1). The self-hybridization pair with matched DNA size distributions that had been exposed to identical fragmentation conditions resulted in a dLRsd of less than 0.3 (Figure 1A, B), indicating a hybridization likely to yield robust copy number data. The introduction of even moderate size mismatches (300 bp differential) was sufficient to introduce profound changes in final data quality, even when the mismatch resulted from an increase in fragment size (Figure 1C, D). Additional loss of data quality was noted when the difference in fragment sizes between the competitively hybridized DNA samples was further increased to 385 bp (Figure 1E, F). The magnitude of the size mismatch effect on data quality is not completely dependent on the magnitude of the size differential, however; as seen in the high dLRsd of the array data in Figure 1G, H, it is likely that decreased fragment size also adds complexity to the mechanism. These findings demonstrate that fragment size matching is critical for reducing the variability of array data quality even when using highly intact, optimal DNA samples.

Bottom Line: While robust for basic research studies, reliable whole-genome copy number analysis has been unsuccessful in routine clinical practice due to a number of technical limitations.Most important, aCGH results have been suboptimal because of the poor integrity of DNA derived from formalin-fixed paraffin-embedded (FFPE) tissues.Results from FFPE samples were equivalent to results from fresh samples and those available through the glioblastoma Cancer Genome Atlas (TCGA).

View Article: PubMed Central - PubMed

Affiliation: Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America.

ABSTRACT
Whole-genome copy number analysis platforms, such as array comparative genomic hybridization (aCGH) and single nucleotide polymorphism (SNP) arrays, are transformative research discovery tools. In cancer, the identification of genomic aberrations with these approaches has generated important diagnostic and prognostic markers, and critical therapeutic targets. While robust for basic research studies, reliable whole-genome copy number analysis has been unsuccessful in routine clinical practice due to a number of technical limitations. Most important, aCGH results have been suboptimal because of the poor integrity of DNA derived from formalin-fixed paraffin-embedded (FFPE) tissues. Using self-hybridizations of a single DNA sample we observed that aCGH performance is significantly improved by accurate DNA size determination and the matching of test and reference DNA samples so that both possess similar fragment sizes. Based on this observation, we developed a novel DNA fragmentation simulation method (FSM) that allows customized tailoring of the fragment sizes of test and reference samples, thereby lowering array failure rates. To validate our methods, we combined FSM with Universal Linkage System (ULS) labeling to study a cohort of 200 tumor samples using Agilent 1 M feature arrays. Results from FFPE samples were equivalent to results from fresh samples and those available through the glioblastoma Cancer Genome Atlas (TCGA). This study demonstrates that rigorous control of DNA fragment size improves aCGH performance. This methodological advance will permit the routine analysis of FFPE tumor samples for clinical trials and in daily clinical practice.

Show MeSH
Related in: MedlinePlus