期刊
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
卷 13, 期 4, 页码 643-655出版社
IEEE COMPUTER SOC
DOI: 10.1109/TCBB.2015.2476808
关键词
Tumor profiling; single-cell sequencing; ductal carcinoma of the breast; phylogeny estimation; parsimony criterion; computational biology; distance methods; network design; combinatorial optimization; mixed integer linear programming
类别
资金
- Belgian National Fund for Scientific Research (FRS-FNRS)
- US National Institutes of Health [1R01CA140214, 1R01AI076318]
- Intramural Research Program of the NIH, NLM
Ductal Carcinoma In Situ (DCIS) is a precursor lesion of Invasive Ductal Carcinoma (IDC) of the breast. Investigating its temporal progression could provide fundamental new insights for the development of better diagnostic tools to predict which cases of DCIS will progress to IDC. We investigate the problem of reconstructing a plausible progression from single-cell sampled data of an individual with synchronous DCIS and IDC. Specifically, by using a number of assumptions derived from the observation of cellular atypia occurring in IDC, we design a possible predictive model using integer linear programming (ILP). Computational experiments carried out on a preexisting data set of 13 patients with simultaneous DCIS and IDC show that the corresponding predicted progression models are classifiable into categories having specific evolutionary characteristics. The approach provides new insights into mechanisms of clonal progression in breast cancers and helps illustrate the power of the ILP approach for similar problems in reconstructing tumor evolution scenarios under complex sets of constraints.
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