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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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Application of FSM ULS method to FFPE samples creates equivalent results to those from fresh-frozen samples.(A) Plot showing dLRsd for 122 FFPE tumor specimens processed according to either standard ULS or FSM ULS protocols and analyzed on Agilent 1 M arrays. (B) Data quality (dLRsd) from (A) plotted by FFPE block age and method. Dashed lines indicate linear regression. Statistics indicate magnitude and significance of correlation between block age and aCGH data quality. (C) Quality (dLRsd) of Agilent 1 M aCGH data of 78 fresh-frozen tissue specimens or frozen tumorsphere cell cultures processed according to either standard ULS or FSM ULS protocols. (D) FFPE and Frozen FSM ULS subsets from (A) and (C) compared to 206 fresh-frozen GBM specimens analyzed on Agilent 244 k arrays from the glioblastoma TCGA study. Statistical significance was assessed by t test and ANOVA, (****;p<.0001, ns;p>0.05), and error bars indicate mean and standard deviation. Additional QC metrics data for all samples are provided in Table S2.
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pone-0038881-g005: Application of FSM ULS method to FFPE samples creates equivalent results to those from fresh-frozen samples.(A) Plot showing dLRsd for 122 FFPE tumor specimens processed according to either standard ULS or FSM ULS protocols and analyzed on Agilent 1 M arrays. (B) Data quality (dLRsd) from (A) plotted by FFPE block age and method. Dashed lines indicate linear regression. Statistics indicate magnitude and significance of correlation between block age and aCGH data quality. (C) Quality (dLRsd) of Agilent 1 M aCGH data of 78 fresh-frozen tissue specimens or frozen tumorsphere cell cultures processed according to either standard ULS or FSM ULS protocols. (D) FFPE and Frozen FSM ULS subsets from (A) and (C) compared to 206 fresh-frozen GBM specimens analyzed on Agilent 244 k arrays from the glioblastoma TCGA study. Statistical significance was assessed by t test and ANOVA, (****;p<.0001, ns;p>0.05), and error bars indicate mean and standard deviation. Additional QC metrics data for all samples are provided in Table S2.

Mentions: To determine whether the FSM method might improve the results obtained from both FFPE and non-FFPE tissue samples, we rigorously compared array data obtained using the FSM protocol with data obtained using the standard manufacturer’s ULS protocol. Hybridizations were performed using Agilent SurePrint stock arrays with a 1 million feature resolution. A diverse set of FFPE tumor specimens (n = 122), frozen tumor tissues (n = 7), primary tumorspheres and other tumor cell cultures (n = 71) were analyzed (Table S1). First, we assessed differences in the data quality generated by FFPE central nervous system (CNS) malignancies obtained from multiple institutions from blocks of various ages (one to 15 years). The quality of the array data processed according to the standard ULS protocol (n = 42, µdLRsd = 0.36, σdLRsd = 0.12) was inferior to that of samples processed according to the FSM ULS protocol (n = 80, µdLRsd = 0.20, σdLRsd = 0.03) with the difference reaching statistical significance (p<0.0001) as assessed by t and F tests (Figure 5A).


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)

Application of FSM ULS method to FFPE samples creates equivalent results to those from fresh-frozen samples.(A) Plot showing dLRsd for 122 FFPE tumor specimens processed according to either standard ULS or FSM ULS protocols and analyzed on Agilent 1 M arrays. (B) Data quality (dLRsd) from (A) plotted by FFPE block age and method. Dashed lines indicate linear regression. Statistics indicate magnitude and significance of correlation between block age and aCGH data quality. (C) Quality (dLRsd) of Agilent 1 M aCGH data of 78 fresh-frozen tissue specimens or frozen tumorsphere cell cultures processed according to either standard ULS or FSM ULS protocols. (D) FFPE and Frozen FSM ULS subsets from (A) and (C) compared to 206 fresh-frozen GBM specimens analyzed on Agilent 244 k arrays from the glioblastoma TCGA study. Statistical significance was assessed by t test and ANOVA, (****;p<.0001, ns;p>0.05), and error bars indicate mean and standard deviation. Additional QC metrics data for all samples are provided in Table S2.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3376148&req=5

pone-0038881-g005: Application of FSM ULS method to FFPE samples creates equivalent results to those from fresh-frozen samples.(A) Plot showing dLRsd for 122 FFPE tumor specimens processed according to either standard ULS or FSM ULS protocols and analyzed on Agilent 1 M arrays. (B) Data quality (dLRsd) from (A) plotted by FFPE block age and method. Dashed lines indicate linear regression. Statistics indicate magnitude and significance of correlation between block age and aCGH data quality. (C) Quality (dLRsd) of Agilent 1 M aCGH data of 78 fresh-frozen tissue specimens or frozen tumorsphere cell cultures processed according to either standard ULS or FSM ULS protocols. (D) FFPE and Frozen FSM ULS subsets from (A) and (C) compared to 206 fresh-frozen GBM specimens analyzed on Agilent 244 k arrays from the glioblastoma TCGA study. Statistical significance was assessed by t test and ANOVA, (****;p<.0001, ns;p>0.05), and error bars indicate mean and standard deviation. Additional QC metrics data for all samples are provided in Table S2.
Mentions: To determine whether the FSM method might improve the results obtained from both FFPE and non-FFPE tissue samples, we rigorously compared array data obtained using the FSM protocol with data obtained using the standard manufacturer’s ULS protocol. Hybridizations were performed using Agilent SurePrint stock arrays with a 1 million feature resolution. A diverse set of FFPE tumor specimens (n = 122), frozen tumor tissues (n = 7), primary tumorspheres and other tumor cell cultures (n = 71) were analyzed (Table S1). First, we assessed differences in the data quality generated by FFPE central nervous system (CNS) malignancies obtained from multiple institutions from blocks of various ages (one to 15 years). The quality of the array data processed according to the standard ULS protocol (n = 42, µdLRsd = 0.36, σdLRsd = 0.12) was inferior to that of samples processed according to the FSM ULS protocol (n = 80, µdLRsd = 0.20, σdLRsd = 0.03) with the difference reaching statistical significance (p<0.0001) as assessed by t and F tests (Figure 5A).

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