Limits...
Estimation of copy number alterations from exome sequencing data.

Valdés-Mas R, Bea S, Puente DA, López-Otín C, Puente XS - PLoS ONE (2012)

Bottom Line: Here we show that somatic copy number alterations can be reliably estimated using exome sequencing data through a strategy that we have termed exome2cnv.We explore the main factors affecting sensitivity and false positives with real data, and provide a side by side comparison with CGH arrays.Together, these results underscore the utility of exome sequencing to study cancer samples by allowing not only the identification of substitutions and indels, but also the accurate estimation of copy number alterations.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Bioquímica y Biología Molecular, Instituto Universitario de Oncología, Universidad de Oviedo, Oviedo, Spain.

ABSTRACT
Exome sequencing constitutes an important technology for the study of human hereditary diseases and cancer. However, the ability of this approach to identify copy number alterations in primary tumor samples has not been fully addressed. Here we show that somatic copy number alterations can be reliably estimated using exome sequencing data through a strategy that we have termed exome2cnv. Using data from 86 paired normal and primary tumor samples, we identified losses and gains of complete chromosomes or large genomic regions, as well as smaller regions affecting a minimum of one gene. Comparison with high-resolution comparative genomic hybridization (CGH) arrays revealed a high sensitivity and a low number of false positives in the copy number estimation between both approaches. We explore the main factors affecting sensitivity and false positives with real data, and provide a side by side comparison with CGH arrays. Together, these results underscore the utility of exome sequencing to study cancer samples by allowing not only the identification of substitutions and indels, but also the accurate estimation of copy number alterations.

Show MeSH

Related in: MedlinePlus

Scheme depicting the strategy used by exome2cnv for detecting CNAs using exome coverage data for a tumor sample and a normal sample from the same patient.Normalized coverage (RPKMs) is determined for each individual capturing exon, and the ratio tumor/normal is calculated for each probe. Genome-wide analysis of ratios allows the identification of regions having somatic copy number alterations in the tumor (red lines).
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC3526607&req=5

pone-0051422-g002: Scheme depicting the strategy used by exome2cnv for detecting CNAs using exome coverage data for a tumor sample and a normal sample from the same patient.Normalized coverage (RPKMs) is determined for each individual capturing exon, and the ratio tumor/normal is calculated for each probe. Genome-wide analysis of ratios allows the identification of regions having somatic copy number alterations in the tumor (red lines).

Mentions: An important field for the application of technologies allowing the identification of CNAs is cancer genomics, as a large number of somatic mutations affecting oncogenes or tumor suppressor genes involve either amplification or deletion of the corresponding loci. To determine whether chromosomal gains or losses as well as smaller CNAs could be detected in tumor samples using exome sequencing data, we studied 86 CLL samples known to have changes in copy number by aCGH [8], [37]. CLL represents an interesting model because this tumor type usually has very few CNAs [8], what allows an accurate estimation of the number of false positive calls by novel approaches as the one described in this study. For this aim, we developed a strategy to identify CNAs using exome data that we called exome2cnv (Figure 2). Thus, for each single capturing exon we compared the log2 ratio of the RPKMs obtained from the tumor sample to the RPKMs obtained from the normal sample, and applied a circular binary segmentation algorithm (DNAcopy) to identify regions potentially lost or gained in the tumor sample [35]. To reduce the noise introduced due to exons with poor capturing efficiency, we selected only those exons having at least two RPKMs in the normal sample from the same patient (>89% of the exons). For all those cases, in addition to exome data we also had available aCGH data for tumor and normal samples (see Material and Methods), what allowed us to compare the results of the exome2cnv approach in terms of sensitivity and false positives.


Estimation of copy number alterations from exome sequencing data.

Valdés-Mas R, Bea S, Puente DA, López-Otín C, Puente XS - PLoS ONE (2012)

Scheme depicting the strategy used by exome2cnv for detecting CNAs using exome coverage data for a tumor sample and a normal sample from the same patient.Normalized coverage (RPKMs) is determined for each individual capturing exon, and the ratio tumor/normal is calculated for each probe. Genome-wide analysis of ratios allows the identification of regions having somatic copy number alterations in the tumor (red lines).
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3526607&req=5

pone-0051422-g002: Scheme depicting the strategy used by exome2cnv for detecting CNAs using exome coverage data for a tumor sample and a normal sample from the same patient.Normalized coverage (RPKMs) is determined for each individual capturing exon, and the ratio tumor/normal is calculated for each probe. Genome-wide analysis of ratios allows the identification of regions having somatic copy number alterations in the tumor (red lines).
Mentions: An important field for the application of technologies allowing the identification of CNAs is cancer genomics, as a large number of somatic mutations affecting oncogenes or tumor suppressor genes involve either amplification or deletion of the corresponding loci. To determine whether chromosomal gains or losses as well as smaller CNAs could be detected in tumor samples using exome sequencing data, we studied 86 CLL samples known to have changes in copy number by aCGH [8], [37]. CLL represents an interesting model because this tumor type usually has very few CNAs [8], what allows an accurate estimation of the number of false positive calls by novel approaches as the one described in this study. For this aim, we developed a strategy to identify CNAs using exome data that we called exome2cnv (Figure 2). Thus, for each single capturing exon we compared the log2 ratio of the RPKMs obtained from the tumor sample to the RPKMs obtained from the normal sample, and applied a circular binary segmentation algorithm (DNAcopy) to identify regions potentially lost or gained in the tumor sample [35]. To reduce the noise introduced due to exons with poor capturing efficiency, we selected only those exons having at least two RPKMs in the normal sample from the same patient (>89% of the exons). For all those cases, in addition to exome data we also had available aCGH data for tumor and normal samples (see Material and Methods), what allowed us to compare the results of the exome2cnv approach in terms of sensitivity and false positives.

Bottom Line: Here we show that somatic copy number alterations can be reliably estimated using exome sequencing data through a strategy that we have termed exome2cnv.We explore the main factors affecting sensitivity and false positives with real data, and provide a side by side comparison with CGH arrays.Together, these results underscore the utility of exome sequencing to study cancer samples by allowing not only the identification of substitutions and indels, but also the accurate estimation of copy number alterations.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Bioquímica y Biología Molecular, Instituto Universitario de Oncología, Universidad de Oviedo, Oviedo, Spain.

ABSTRACT
Exome sequencing constitutes an important technology for the study of human hereditary diseases and cancer. However, the ability of this approach to identify copy number alterations in primary tumor samples has not been fully addressed. Here we show that somatic copy number alterations can be reliably estimated using exome sequencing data through a strategy that we have termed exome2cnv. Using data from 86 paired normal and primary tumor samples, we identified losses and gains of complete chromosomes or large genomic regions, as well as smaller regions affecting a minimum of one gene. Comparison with high-resolution comparative genomic hybridization (CGH) arrays revealed a high sensitivity and a low number of false positives in the copy number estimation between both approaches. We explore the main factors affecting sensitivity and false positives with real data, and provide a side by side comparison with CGH arrays. Together, these results underscore the utility of exome sequencing to study cancer samples by allowing not only the identification of substitutions and indels, but also the accurate estimation of copy number alterations.

Show MeSH
Related in: MedlinePlus