Computational selection of antibody-drug conjugate targets for breast cancer.

ABSTRACT: The selection of therapeutic targets is a critical aspect of antibody-drug conjugate research and development. In this study, we applied computational methods to select candidate targets overexpressed in three major breast cancer subtypes as compared with a range of vital organs and tissues. Microarray data corresponding to over 8,000 tissue samples were collected from the public domain. Breast cancer samples were classified into molecular subtypes using an iterative ensemble approach combining six classification algorithms and three feature selection techniques, including a novel kernel density-based method. This feature selection method was used in conjunction with differential expression and subcellular localization information to assemble a primary list of targets. A total of 50 cell m

SUBMITTER: Fauteux F 

PROVIDER: S-EPMC4823055 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature