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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 order of CLL alterations with and without treatments.All events are sorted by fold change between in-degree and out-degree, and all significant early or late events are labeled by *(p-value < 0.05) or **(p-value < 0.01). The upper panel represents the results of patients with only watch and wait, while the lower panel represents the results of patients with treatment.DOI:http://dx.doi.org/10.7554/eLife.02869.009
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fig3s2: The order of CLL alterations with and without treatments.All events are sorted by fold change between in-degree and out-degree, and all significant early or late events are labeled by *(p-value < 0.05) or **(p-value < 0.01). The upper panel represents the results of patients with only watch and wait, while the lower panel represents the results of patients with treatment.DOI:http://dx.doi.org/10.7554/eLife.02869.009

Mentions: To understand the evolutionary pattern of genetic alterations in CLL, we infer TEDG by removing indirect orders in ISN. The TEDG of CLL (Figure 3B) shows a clear pattern of the flow of alterations, revealing that genetic alterations of CLL are sequentially ordered in a branching mode. To statistically assess the temporal pattern of the genetic lesions, we use the binomial test to assess significance by assuming that the number of in-degree and out-degree of each alteration are randomly distributed. Consistent with TEDG, this analysis suggests the following temporal order of the lesion: mutations of MYD88, deletion 13q14, +12, mutations of NOTCH1, RB1 deletion, 17p13 deletion, mutations of SF3B1, 11q22-q23 deletion, BIRC3 deletion, mutations of TP53, and mutations of BIRC3 (Figure 3C). Deletion of 13q14, +12 and mutations of NOTCH1 are significant early events in CLL development, while mutations of TP53 and BIRC3 are significant late events. Though the sample size prevents statistical considerations, MYD88 mutations might occur even before 13q14 deletion (one of six patients), indicating that activation of the Toll-like receptor pathway could be important in the initiation of a fraction of CLL tumors (Arvaniti et al., 2011). The sequential order of the genetic lesions remains consistent (Pearson's correlation = 0.9, p-value < 1e-3) when evolutionary networks are constructed with patients who received chemotherapy (Figure 3—figure supplement 2), suggesting that the order of development of the genetic lesions may be affected by therapy (the Pearson's correlation of the order in patients without chemotherapy is 0.4 with p-value > 0.1).


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 order of CLL alterations with and without treatments.All events are sorted by fold change between in-degree and out-degree, and all significant early or late events are labeled by *(p-value < 0.05) or **(p-value < 0.01). The upper panel represents the results of patients with only watch and wait, while the lower panel represents the results of patients with treatment.DOI:http://dx.doi.org/10.7554/eLife.02869.009
© Copyright Policy
Related In: Results  -  Collection

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

fig3s2: The order of CLL alterations with and without treatments.All events are sorted by fold change between in-degree and out-degree, and all significant early or late events are labeled by *(p-value < 0.05) or **(p-value < 0.01). The upper panel represents the results of patients with only watch and wait, while the lower panel represents the results of patients with treatment.DOI:http://dx.doi.org/10.7554/eLife.02869.009
Mentions: To understand the evolutionary pattern of genetic alterations in CLL, we infer TEDG by removing indirect orders in ISN. The TEDG of CLL (Figure 3B) shows a clear pattern of the flow of alterations, revealing that genetic alterations of CLL are sequentially ordered in a branching mode. To statistically assess the temporal pattern of the genetic lesions, we use the binomial test to assess significance by assuming that the number of in-degree and out-degree of each alteration are randomly distributed. Consistent with TEDG, this analysis suggests the following temporal order of the lesion: mutations of MYD88, deletion 13q14, +12, mutations of NOTCH1, RB1 deletion, 17p13 deletion, mutations of SF3B1, 11q22-q23 deletion, BIRC3 deletion, mutations of TP53, and mutations of BIRC3 (Figure 3C). Deletion of 13q14, +12 and mutations of NOTCH1 are significant early events in CLL development, while mutations of TP53 and BIRC3 are significant late events. Though the sample size prevents statistical considerations, MYD88 mutations might occur even before 13q14 deletion (one of six patients), indicating that activation of the Toll-like receptor pathway could be important in the initiation of a fraction of CLL tumors (Arvaniti et al., 2011). The sequential order of the genetic lesions remains consistent (Pearson's correlation = 0.9, p-value < 1e-3) when evolutionary networks are constructed with patients who received chemotherapy (Figure 3—figure supplement 2), suggesting that the order of development of the genetic lesions may be affected by therapy (the Pearson's correlation of the order in patients without chemotherapy is 0.4 with p-value > 0.1).

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