Paper Info
Title
Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case Study.
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.
Year
DOI
Venue
2016
10.1109/TCBB.2015.2476808
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Keywords
Field
DocType
Tumors,Bioinformatics,Data models,Computational biology,Phylogeny,Marine animals
Ductal carcinoma,Cellular atypia,Computer science,Single cell sequencing,Integer programming,Artificial intelligence,Bioinformatics,Machine learning,Diagnostic tools
Journal
Volume
Issue
ISSN
13
4
1545-5963
Citations 
PageRank 
References 
0
0.34
9
Authors
4
Name
Order
Citations
PageRank
Daniele Catanzaro19410.23
Stanley Shackney2766.95
Alejandro A. Schäffer3827136.66
Russell Schwartz454868.68