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Updated: Jun 18, 2026
Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres
Published on: July 22, 2020
Detection of treatment-induced changes in signaling pathways in gastrointestinal stromal tumors using transcriptomic
Michael F Ochs1, Lori Rink, Chi Tarn
1Division of Oncology Biostatistics and Bioinformatics, Johns Hopkins University, Baltimore, Maryland 21205, USA. mfo@jhu.edu
Abstract:
Cell signaling plays a central role in the etiology of cancer. Numerous therapeutics in use or under development target signaling proteins; however, off-target effects often limit assignment of positive clinical response to the intended target. As direct measurements of signaling protein activity are not generally feasible during treatment, there is a need for more powerful methods to determine if therapeutics inhibit their targets and when off-target effects occur. We have used the Bayesian Decomposition algorithm and data on transcriptional regulation to create a novel methodology, Differential Expression for Signaling Determination (DESIDE), for inferring signaling activity from microarray measurements. We applied DESIDE to deduce signaling activity in gastrointestinal stromal tumor cell lines treated with the targeted therapeutic imatinib mesylate (Gleevec). We detected the expected reduced activity in the KIT pathway, as well as unexpected changes in the p53 pathway. Pursuing these findings, we have determined that imatinib-induced DNA damage is responsible for the increased activity of p53, identifying a novel off-target activity for this drug. We then used DESIDE on data from resected, post-imatinib treatment tumor samples and identified a pattern in these tumors similar to that at late time points in the cell lines, and this pattern correlated with initial clinical response. The pattern showed increased activity of ETS domain-containing protein Elk-1 and signal transducers and activators of transcription 3 transcription factors, which are associated with the growth of side population cells. DESIDE infers the global reprogramming of signaling networks during treatment, permitting treatment modification that leverages ongoing drug development efforts, which is crucial for personalized medicine.
Insights
A new method, DESIDE, infers cell signaling activity from gene expression data to identify drug targets and off-target effects. This approach revealed imatinib’s unexpected impact on the p53 pathway and predicted clinical response in cancer patients.
Area of Science:
- Oncology
- Bioinformatics
- Molecular Biology
Background:
- Cell signaling is crucial in cancer development, and targeted therapies aim to inhibit specific signaling proteins.
- Off-target effects of cancer therapeutics can limit clinical efficacy, necessitating methods to monitor drug activity and unintended consequences.
- Direct measurement of signaling protein activity during treatment is challenging, highlighting the need for advanced analytical approaches.
Purpose of the Study:
- To develop and validate a novel computational methodology, Differential Expression for Signaling Determination (DESIDE), for inferring cell signaling activity from gene expression data.
- To apply DESIDE to analyze the effects of imatinib (Gleevec) on signaling pathways in gastrointestinal stromal tumor (GIST) cell lines and patient samples.
- To identify both intended and unintended (off-target) signaling alterations induced by imatinib and correlate these with clinical response.
Main Methods:
- Utilized the Bayesian Decomposition algorithm combined with transcriptional regulation data to create the DESIDE methodology.
- Applied DESIDE to analyze microarray data from GIST cell lines treated with imatinib.
- Analyzed DESIDE-derived signaling patterns in GIST patient tumor samples post-imatinib treatment.
Main Results:
- DESIDE successfully inferred signaling activity, detecting expected KIT pathway inhibition and unexpected p53 pathway activation by imatinib in cell lines.
- Identified imatinib-induced DNA damage as the cause of increased p53 activity, revealing a novel off-target effect.
- Observed a signaling pattern in patient tumors, characterized by increased Elk-1 and STAT3 activity, that correlated with clinical response and resembled late-stage cell line responses.
Conclusions:
- DESIDE provides a powerful tool for inferring global signaling network reprogramming during cancer therapy.
- The study identified a novel off-target effect of imatinib on the p53 pathway, mediated by DNA damage.
- DESIDE analysis of patient tumors revealed signaling patterns predictive of clinical response, supporting its utility in personalized medicine and treatment modification.
