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Accepted (AM)Open Access (License Unspecified), Open
Journal article
Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case Study
IEEE/ACM transactions on computational biology and bioinformatics, v 13(4), pp 643-655
Jul 2016
PMID: 26353381
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
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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Details
- Title
- Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case Study
- Creators
- Daniele Catanzaro - Université Catholique de LouvainStanley E Shackney - Drexel UniversityAlejandro A Schaffer - Computational Biology Branch of NCBI, NIH, Bethesda, MD 20894Russell Schwartz - Carnegie Mellon UniversityRoy E Schwartz - Pediatrics
- Publication Details
- IEEE/ACM transactions on computational biology and bioinformatics, v 13(4), pp 643-655
- Publisher
- IEEE
- Grant note
- NIH (10.13039/100000002) Intramural Research Program Belgian National Fund for Scientific Research (FRS-FNRS) (D.C) NLM (A.A.S.) (10.13039/100000092) 1R01CA140214; 1R01AI076318 / US National Institutes of Health
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Pediatrics
- Web of Science ID
- WOS:000381506500005
- Scopus ID
- 2-s2.0-84982204058
- Other Identifier
- 991019173908304721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Biochemical Research Methods
- Computer Science, Interdisciplinary Applications
- Mathematics, Interdisciplinary Applications
- Statistics & Probability