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Tumor evolutionary directed graphs and the history of chronic lymphocytic leukemia.

Wang J, Khiabanian H, Rossi D, Fabbri G, Gattei V, Forconi F, Laurenti L, Marasca R, Del Poeta G, Foà R, Pasqualucci L, Gaidano G, Rabadan R - Elife (2014)

Bottom Line: Cancer is a clonal evolutionary process, caused by successive accumulation of genetic alterations providing milestones of tumor initiation, progression, dissemination, and/or resistance to certain therapeutic regimes.To unravel these milestones we propose a framework, tumor evolutionary directed graphs (TEDG), which is able to characterize the history of genetic alterations by integrating longitudinal and cross-sectional genomic data.Our results suggest that TEDG may constitute an effective framework to recapitulate the evolutionary history of tumors.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Informatics, Columbia University, New York, United States.

ABSTRACT
Cancer is a clonal evolutionary process, caused by successive accumulation of genetic alterations providing milestones of tumor initiation, progression, dissemination, and/or resistance to certain therapeutic regimes. To unravel these milestones we propose a framework, tumor evolutionary directed graphs (TEDG), which is able to characterize the history of genetic alterations by integrating longitudinal and cross-sectional genomic data. We applied TEDG to a chronic lymphocytic leukemia (CLL) cohort of 70 patients spanning 12 years and show that: (a) the evolution of CLL follows a time-ordered process represented as a global flow in TEDG that proceeds from initiating events to late events; (b) there are two distinct and mutually exclusive evolutionary paths of CLL evolution; (c) higher fitness clones are present in later stages of the disease, indicating a progressive clonal replacement with more aggressive clones. Our results suggest that TEDG may constitute an effective framework to recapitulate the evolutionary history of tumors.

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Fitting the evolution models.(A) Distribution of the clonal evolution pattern in the 60 non-Richter cases. Three of the 60 cases show replacement during tumor progression. (B) Scatter plot showing p-values of observing increased and decreased subclones in the 80 samples of the 60 multi-time point patients. Samples with evidence of clonal replacement are located in the right-up corner (highlighted by yellow circle). (C) Number of patients following linear vs branched evolution pattern according to SF3B1 mutational emergence and previous treatment (p-value 0.0016 by Fisher's exact test).DOI:http://dx.doi.org/10.7554/eLife.02869.012
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fig5: Fitting the evolution models.(A) Distribution of the clonal evolution pattern in the 60 non-Richter cases. Three of the 60 cases show replacement during tumor progression. (B) Scatter plot showing p-values of observing increased and decreased subclones in the 80 samples of the 60 multi-time point patients. Samples with evidence of clonal replacement are located in the right-up corner (highlighted by yellow circle). (C) Number of patients following linear vs branched evolution pattern according to SF3B1 mutational emergence and previous treatment (p-value 0.0016 by Fisher's exact test).DOI:http://dx.doi.org/10.7554/eLife.02869.012

Mentions: Based on pivotal NGS studies, two different evolutionary models have been proposed in CLL, namely gradual linear and branching evolution (Knight et al., 2012; Schuh et al., 2012). The analysis of our cohort (excluding patients with Richter's transformation, refer to ‘Materials and methods’ for details) shows that a minority of patients (n = 3/60, 5%; FDR = 0.1) are characterized by a significantly decreased or undetectable representation of the founding clone, coupled with a significant increase of a second subclone that represented a small subpopulation at an earlier time point, consistent with a branching evolution model (highlighted by yellow circle in Figure 5A–B, and Table 1). Interestingly, in all three cases clonal replacement events involve SF3B1 mutations and occur after treatment (Figure 5C), suggesting that the branching evolution model is closely connected to the combination of treatments and the emergence of SF3B1 mutations (p-value = 0.0016 by Fisher's exact test). This observation implies that, at the time of treatment requirement, limiting the knowledge of disease genetics to the dominant clone will likely be uninformative for accurate therapeutic decisions. Of particular interest in this scenario is the development of therapeutic strategies to prevent the branching evolution of the tumor, with the goal of eradicating dominant as well as minor clones (Anderson et al., 2011; Notta et al., 2011; Ding et al., 2012; Egan et al., 2012; Keats et al., 2012; Walker et al., 2012; Rossi et al., 2014).10.7554/eLife.02869.012Figure 5.Fitting the evolution models.


Tumor evolutionary directed graphs and the history of chronic lymphocytic leukemia.

Wang J, Khiabanian H, Rossi D, Fabbri G, Gattei V, Forconi F, Laurenti L, Marasca R, Del Poeta G, Foà R, Pasqualucci L, Gaidano G, Rabadan R - Elife (2014)

Fitting the evolution models.(A) Distribution of the clonal evolution pattern in the 60 non-Richter cases. Three of the 60 cases show replacement during tumor progression. (B) Scatter plot showing p-values of observing increased and decreased subclones in the 80 samples of the 60 multi-time point patients. Samples with evidence of clonal replacement are located in the right-up corner (highlighted by yellow circle). (C) Number of patients following linear vs branched evolution pattern according to SF3B1 mutational emergence and previous treatment (p-value 0.0016 by Fisher's exact test).DOI:http://dx.doi.org/10.7554/eLife.02869.012
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4308685&req=5

fig5: Fitting the evolution models.(A) Distribution of the clonal evolution pattern in the 60 non-Richter cases. Three of the 60 cases show replacement during tumor progression. (B) Scatter plot showing p-values of observing increased and decreased subclones in the 80 samples of the 60 multi-time point patients. Samples with evidence of clonal replacement are located in the right-up corner (highlighted by yellow circle). (C) Number of patients following linear vs branched evolution pattern according to SF3B1 mutational emergence and previous treatment (p-value 0.0016 by Fisher's exact test).DOI:http://dx.doi.org/10.7554/eLife.02869.012
Mentions: Based on pivotal NGS studies, two different evolutionary models have been proposed in CLL, namely gradual linear and branching evolution (Knight et al., 2012; Schuh et al., 2012). The analysis of our cohort (excluding patients with Richter's transformation, refer to ‘Materials and methods’ for details) shows that a minority of patients (n = 3/60, 5%; FDR = 0.1) are characterized by a significantly decreased or undetectable representation of the founding clone, coupled with a significant increase of a second subclone that represented a small subpopulation at an earlier time point, consistent with a branching evolution model (highlighted by yellow circle in Figure 5A–B, and Table 1). Interestingly, in all three cases clonal replacement events involve SF3B1 mutations and occur after treatment (Figure 5C), suggesting that the branching evolution model is closely connected to the combination of treatments and the emergence of SF3B1 mutations (p-value = 0.0016 by Fisher's exact test). This observation implies that, at the time of treatment requirement, limiting the knowledge of disease genetics to the dominant clone will likely be uninformative for accurate therapeutic decisions. Of particular interest in this scenario is the development of therapeutic strategies to prevent the branching evolution of the tumor, with the goal of eradicating dominant as well as minor clones (Anderson et al., 2011; Notta et al., 2011; Ding et al., 2012; Egan et al., 2012; Keats et al., 2012; Walker et al., 2012; Rossi et al., 2014).10.7554/eLife.02869.012Figure 5.Fitting the evolution models.

Bottom Line: Cancer is a clonal evolutionary process, caused by successive accumulation of genetic alterations providing milestones of tumor initiation, progression, dissemination, and/or resistance to certain therapeutic regimes.To unravel these milestones we propose a framework, tumor evolutionary directed graphs (TEDG), which is able to characterize the history of genetic alterations by integrating longitudinal and cross-sectional genomic data.Our results suggest that TEDG may constitute an effective framework to recapitulate the evolutionary history of tumors.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Informatics, Columbia University, New York, United States.

ABSTRACT
Cancer is a clonal evolutionary process, caused by successive accumulation of genetic alterations providing milestones of tumor initiation, progression, dissemination, and/or resistance to certain therapeutic regimes. To unravel these milestones we propose a framework, tumor evolutionary directed graphs (TEDG), which is able to characterize the history of genetic alterations by integrating longitudinal and cross-sectional genomic data. We applied TEDG to a chronic lymphocytic leukemia (CLL) cohort of 70 patients spanning 12 years and show that: (a) the evolution of CLL follows a time-ordered process represented as a global flow in TEDG that proceeds from initiating events to late events; (b) there are two distinct and mutually exclusive evolutionary paths of CLL evolution; (c) higher fitness clones are present in later stages of the disease, indicating a progressive clonal replacement with more aggressive clones. Our results suggest that TEDG may constitute an effective framework to recapitulate the evolutionary history of tumors.

Show MeSH
Related in: MedlinePlus