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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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The impact of sampling error on MCF.Confidence interval of MCF is inferred based on the variation of MAF estimated by dilution experiments.
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fig17: The impact of sampling error on MCF.Confidence interval of MCF is inferred based on the variation of MAF estimated by dilution experiments.

Mentions: To show how the sampling error affects MCF, we calculate the 95% confidence interval of MCF based on variation of MAF described by Rossi et al., 2014. Particularly, the 95% confidence interval of MAF at 0.5%, 2.5%, 5%, and 25% are used to estimate upper and lower bound of MCF with the formula described in Materials and methods, “Adjustment of Mutation Allele Frequency”, and Figure 1–figure supplement 1. The length of 95% confidence interval of MCF are respectively 0.1%, 0.6%, 1.2%, and 2%, indicating that the sampling error slightly fluctuates the value of MCF; however, only 0.2% (1 out of 415) of the detected mutations, which is on the boundary of our cutoff, will be affected by this fluctuation, not changing the overall results (Author response image 11).


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)

The impact of sampling error on MCF.Confidence interval of MCF is inferred based on the variation of MAF estimated by dilution experiments.
© Copyright Policy
Related In: Results  -  Collection

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

fig17: The impact of sampling error on MCF.Confidence interval of MCF is inferred based on the variation of MAF estimated by dilution experiments.
Mentions: To show how the sampling error affects MCF, we calculate the 95% confidence interval of MCF based on variation of MAF described by Rossi et al., 2014. Particularly, the 95% confidence interval of MAF at 0.5%, 2.5%, 5%, and 25% are used to estimate upper and lower bound of MCF with the formula described in Materials and methods, “Adjustment of Mutation Allele Frequency”, and Figure 1–figure supplement 1. The length of 95% confidence interval of MCF are respectively 0.1%, 0.6%, 1.2%, and 2%, indicating that the sampling error slightly fluctuates the value of MCF; however, only 0.2% (1 out of 415) of the detected mutations, which is on the boundary of our cutoff, will be affected by this fluctuation, not changing the overall results (Author response image 11).

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