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Analysis of the copy number profiles of several tumor samples from the same patient reveals the successive steps in tumorigenesis.

Letouzé E, Allory Y, Bollet MA, Radvanyi F, Guyon F - Genome Biol. (2010)

Bottom Line: We present a computational method, TuMult, for reconstructing the sequence of copy number changes driving carcinogenesis, based on the analysis of several tumor samples from the same patient.We demonstrate the reliability of the method with simulated data, and describe applications to three different cancers, showing that TuMult is a valuable tool for the establishment of clonal relationships between tumor samples and the identification of chromosome aberrations occurring at crucial steps in cancer progression.

View Article: PubMed Central - HTML - PubMed

Affiliation: INSERM, UMR-S 973, MTi, Université Paris Diderot - Paris 7, 35 rue Hélène Brion, 75205 Paris Cedex 13, France. eric.letouze@gmail.com

ABSTRACT
We present a computational method, TuMult, for reconstructing the sequence of copy number changes driving carcinogenesis, based on the analysis of several tumor samples from the same patient. We demonstrate the reliability of the method with simulated data, and describe applications to three different cancers, showing that TuMult is a valuable tool for the establishment of clonal relationships between tumor samples and the identification of chromosome aberrations occurring at crucial steps in cancer progression.

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Overview of the TuMult algorithm. (a) Discretized copy number profiles of three tumors from the same patient (yellow, 'normal copy number'; green, 'loss'; red, 'gain'). The eight breakpoints identified in the samples (dashed lines) divide the chromosome into seven 'homogeneous segments', A to G, in which copy number is constant in any sample. The profiles can be represented as amplitude vectors (see Materials and methods), in which 'up' and 'down' breakpoints are distinguished by their position in the vector. A common breakpoint (gray shading) appears as a non-zero value at the same position in the amplitude matrix. The frequency Fk of each breakpoint is calculated from a reference data set of independent samples. (b) An identical breakpoint score (IBS), characterizing the similarity of two profiles in terms of chromosome breakpoints, is calculated for each pair of samples, and the pair displaying the highest level of similarity is selected. (c) The copy number profile of the common precursor of the two samples is reconstructed based on their common breakpoints, represented by dashed lines and black arrows. Edges are added between the common precursor (CP) and the two nodes, labeled with the aberrations defined by their specific breakpoints, represented by gray arrows. Note that a breakpoint may be both common and specific, if its amplitude is larger in one of the samples, like the 'down' breakpoint between segments A and B in this example. (d) Steps (b) and (c) are iterated until there is only one node left in the front. (e) A 'normal cell' node has been added above the common ancestor of all tumors.
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Figure 2: Overview of the TuMult algorithm. (a) Discretized copy number profiles of three tumors from the same patient (yellow, 'normal copy number'; green, 'loss'; red, 'gain'). The eight breakpoints identified in the samples (dashed lines) divide the chromosome into seven 'homogeneous segments', A to G, in which copy number is constant in any sample. The profiles can be represented as amplitude vectors (see Materials and methods), in which 'up' and 'down' breakpoints are distinguished by their position in the vector. A common breakpoint (gray shading) appears as a non-zero value at the same position in the amplitude matrix. The frequency Fk of each breakpoint is calculated from a reference data set of independent samples. (b) An identical breakpoint score (IBS), characterizing the similarity of two profiles in terms of chromosome breakpoints, is calculated for each pair of samples, and the pair displaying the highest level of similarity is selected. (c) The copy number profile of the common precursor of the two samples is reconstructed based on their common breakpoints, represented by dashed lines and black arrows. Edges are added between the common precursor (CP) and the two nodes, labeled with the aberrations defined by their specific breakpoints, represented by gray arrows. Note that a breakpoint may be both common and specific, if its amplitude is larger in one of the samples, like the 'down' breakpoint between segments A and B in this example. (d) Steps (b) and (c) are iterated until there is only one node left in the front. (e) A 'normal cell' node has been added above the common ancestor of all tumors.

Mentions: As chromosomal aberrations accumulate during tumor progression, several aberrations may affect the same region of the chromosome in succession. An aberration common to two samples will therefore be missed if it is partly affected by a subsequent aberration overlapping the same region. However, common breakpoints remain recognizable in most cases (as illustrated in Figure 2d), making it possible to infer the initial genetic alteration occurring in the common precursor of the samples. Indeed, a breakpoint is only erased if a breakpoint of the opposite sign occurs at the same location, and such events are likely to be rare. We therefore decided to use chromosome breakpoints, rather than chromosome aberrations, for reconstruction of the tumor progression trees.


Analysis of the copy number profiles of several tumor samples from the same patient reveals the successive steps in tumorigenesis.

Letouzé E, Allory Y, Bollet MA, Radvanyi F, Guyon F - Genome Biol. (2010)

Overview of the TuMult algorithm. (a) Discretized copy number profiles of three tumors from the same patient (yellow, 'normal copy number'; green, 'loss'; red, 'gain'). The eight breakpoints identified in the samples (dashed lines) divide the chromosome into seven 'homogeneous segments', A to G, in which copy number is constant in any sample. The profiles can be represented as amplitude vectors (see Materials and methods), in which 'up' and 'down' breakpoints are distinguished by their position in the vector. A common breakpoint (gray shading) appears as a non-zero value at the same position in the amplitude matrix. The frequency Fk of each breakpoint is calculated from a reference data set of independent samples. (b) An identical breakpoint score (IBS), characterizing the similarity of two profiles in terms of chromosome breakpoints, is calculated for each pair of samples, and the pair displaying the highest level of similarity is selected. (c) The copy number profile of the common precursor of the two samples is reconstructed based on their common breakpoints, represented by dashed lines and black arrows. Edges are added between the common precursor (CP) and the two nodes, labeled with the aberrations defined by their specific breakpoints, represented by gray arrows. Note that a breakpoint may be both common and specific, if its amplitude is larger in one of the samples, like the 'down' breakpoint between segments A and B in this example. (d) Steps (b) and (c) are iterated until there is only one node left in the front. (e) A 'normal cell' node has been added above the common ancestor of all tumors.
© Copyright Policy - open-access
Related In: Results  -  Collection

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Figure 2: Overview of the TuMult algorithm. (a) Discretized copy number profiles of three tumors from the same patient (yellow, 'normal copy number'; green, 'loss'; red, 'gain'). The eight breakpoints identified in the samples (dashed lines) divide the chromosome into seven 'homogeneous segments', A to G, in which copy number is constant in any sample. The profiles can be represented as amplitude vectors (see Materials and methods), in which 'up' and 'down' breakpoints are distinguished by their position in the vector. A common breakpoint (gray shading) appears as a non-zero value at the same position in the amplitude matrix. The frequency Fk of each breakpoint is calculated from a reference data set of independent samples. (b) An identical breakpoint score (IBS), characterizing the similarity of two profiles in terms of chromosome breakpoints, is calculated for each pair of samples, and the pair displaying the highest level of similarity is selected. (c) The copy number profile of the common precursor of the two samples is reconstructed based on their common breakpoints, represented by dashed lines and black arrows. Edges are added between the common precursor (CP) and the two nodes, labeled with the aberrations defined by their specific breakpoints, represented by gray arrows. Note that a breakpoint may be both common and specific, if its amplitude is larger in one of the samples, like the 'down' breakpoint between segments A and B in this example. (d) Steps (b) and (c) are iterated until there is only one node left in the front. (e) A 'normal cell' node has been added above the common ancestor of all tumors.
Mentions: As chromosomal aberrations accumulate during tumor progression, several aberrations may affect the same region of the chromosome in succession. An aberration common to two samples will therefore be missed if it is partly affected by a subsequent aberration overlapping the same region. However, common breakpoints remain recognizable in most cases (as illustrated in Figure 2d), making it possible to infer the initial genetic alteration occurring in the common precursor of the samples. Indeed, a breakpoint is only erased if a breakpoint of the opposite sign occurs at the same location, and such events are likely to be rare. We therefore decided to use chromosome breakpoints, rather than chromosome aberrations, for reconstruction of the tumor progression trees.

Bottom Line: We present a computational method, TuMult, for reconstructing the sequence of copy number changes driving carcinogenesis, based on the analysis of several tumor samples from the same patient.We demonstrate the reliability of the method with simulated data, and describe applications to three different cancers, showing that TuMult is a valuable tool for the establishment of clonal relationships between tumor samples and the identification of chromosome aberrations occurring at crucial steps in cancer progression.

View Article: PubMed Central - HTML - PubMed

Affiliation: INSERM, UMR-S 973, MTi, Université Paris Diderot - Paris 7, 35 rue Hélène Brion, 75205 Paris Cedex 13, France. eric.letouze@gmail.com

ABSTRACT
We present a computational method, TuMult, for reconstructing the sequence of copy number changes driving carcinogenesis, based on the analysis of several tumor samples from the same patient. We demonstrate the reliability of the method with simulated data, and describe applications to three different cancers, showing that TuMult is a valuable tool for the establishment of clonal relationships between tumor samples and the identification of chromosome aberrations occurring at crucial steps in cancer progression.

Show MeSH
Related in: MedlinePlus