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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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ABSOLUTE report of case #37.Several models fit the data with different purity estimates.
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fig20: ABSOLUTE report of case #37.Several models fit the data with different purity estimates.

Mentions: To compare our method to genome-wide methods, we have analyzed previously published whole-exome sequencing (WES) and SNP array data of four of our patients: #57, #4, #37, and #59 (Fabbri et al., 2013, JEM, and Messina et al., 2014, Blood. SNP array data for the other six patients are not available). We ran ABSOLUTE 1.0.6 with the parameters min.ploidy=1, and max.ploidy=3 (given that all samples in the research of Landau et al. (Landau et al., 2013, Cell) were estimated to have near-diploid DNA content). CCFs (cancer cell fraction as defined by ABSOLUTE) are calculated. By comparing MCF with the confidence interval of CCF, for mutations of 3 out of 4 cases, the results are consistent (Author response image 13). In patient #37, however, according to ABSOLUTE, MCF of a TP53 mutation (MAF=0.34) is close to 100% because the tumor content is estimated to be ∼40%, which is not consistent with our FACS analysis (CD19+CD5+ cell fraction is 95%). This indicates that in this discrepant case, ABSOLUTE underestimates the tumor purity (40%) compared to FACS (95%). We were extremely curious about this underestimation and upon further investigation we find that ABSOLUTE reports different models that fit the data, and in fact there are several solutions that coincide with our estimate of MCF and the FACS analysis (Author response image 14).


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)

ABSOLUTE report of case #37.Several models fit the data with different purity estimates.
© Copyright Policy
Related In: Results  -  Collection

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

fig20: ABSOLUTE report of case #37.Several models fit the data with different purity estimates.
Mentions: To compare our method to genome-wide methods, we have analyzed previously published whole-exome sequencing (WES) and SNP array data of four of our patients: #57, #4, #37, and #59 (Fabbri et al., 2013, JEM, and Messina et al., 2014, Blood. SNP array data for the other six patients are not available). We ran ABSOLUTE 1.0.6 with the parameters min.ploidy=1, and max.ploidy=3 (given that all samples in the research of Landau et al. (Landau et al., 2013, Cell) were estimated to have near-diploid DNA content). CCFs (cancer cell fraction as defined by ABSOLUTE) are calculated. By comparing MCF with the confidence interval of CCF, for mutations of 3 out of 4 cases, the results are consistent (Author response image 13). In patient #37, however, according to ABSOLUTE, MCF of a TP53 mutation (MAF=0.34) is close to 100% because the tumor content is estimated to be ∼40%, which is not consistent with our FACS analysis (CD19+CD5+ cell fraction is 95%). This indicates that in this discrepant case, ABSOLUTE underestimates the tumor purity (40%) compared to FACS (95%). We were extremely curious about this underestimation and upon further investigation we find that ABSOLUTE reports different models that fit the data, and in fact there are several solutions that coincide with our estimate of MCF and the FACS analysis (Author response image 14).

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