Radial Data Visualization-Based Step-by-Step Eliminative Algorithm to Predict Colorectal Cancer Patients’ Response to FOLFOX Therapy

Abstract

Application of the FOLFOX scheme to colorectal cancer (CRC) patients often results in the development of chemo-resistance, leading to therapy failure. This study aimed to develop a functional and easy-to-use algorithm to predict patients’ response to FOLFOX treatment. Transcriptomic data of CRC patient’s samples treated with FOLFOX were downloaded from the Gene Expression Omnibus database (GSE83129, GSE28702, GSE69657, GSE19860 and GSE41568). Comparing the expression of top up- and downregulated genes in FOLFOX responder and non-responder patients’ groups, we selected 30 potential markers that were used to create a step-by-step eliminative procedure based on modified radial data visualization, which depicts the interplay between the expression level of chosen attributes (genes) to locate data points in low-dimensional space. Our analysis proved that FOLFOX-resistant CRC samples are predominantly characterized by upregulated expression levels of TMEM182 and MCM9 and downregulated LRRFIP1. Additionally, the procedure developed based on expression levels of TMEM182, MCM9, LRRFIP1, LAMP1, FAM161A, KLHL36, ETV5, RNF168, SRSF11, NCKAP5, CRTAP, VAMP2, ZBTB49 and RIMBP2 proved to be capable in predicting FOLFOX therapy response. In conclusion, our approach can give a unique insight into clinical decision-making regarding therapy scheme administration, potentially increasing patients’ survival and, consequently, medical futility due to incorrect therapy application.