COMBSecretomics: A pragmatic methodological framework for higher-order drug combination analysis using secretomics

PloS One
Efthymia ChantziMats G Gustafsson

Abstract

Multi drug treatments are increasingly used in the clinic to combat complex and co-occurring diseases. However, most drug combination discovery efforts today are mainly focused on anticancer therapy and rarely examine the potential of using more than two drugs simultaneously. Moreover, there is currently no reported methodology for performing second- and higher-order drug combination analysis of secretomic patterns, meaning protein concentration profiles released by the cells. Here, we introduce COMBSecretomics (https://github.com/EffieChantzi/COMBSecretomics.git), the first pragmatic methodological framework designed to search exhaustively for second- and higher-order mixtures of candidate treatments that can modify, or even reverse malfunctioning secretomic patterns of human cells. This framework comes with two novel model-free combination analysis methods; a tailor-made generalization of the highest single agent principle and a data mining approach based on top-down hierarchical clustering. Quality control procedures to eliminate outliers and non-parametric statistics to quantify uncertainty in the results obtained are also included. COMBSecretomics is based on a standardized reproducible format and could be employed with an...Continue Reading

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Methods Mentioned

BETA
biopsy
suspension array technology
protein release assay
in silico methods

Software Mentioned

COMBImage2
COMBSecretomics
Windows
MATLAB
Linux
BioMAP
FlexMap

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