Abstract 6356: Multiscale high-content imaging to identify molecular and morphological signatures in drug-resistant cancer cells

Abstract Drug resistance in cancer therapy remains a significant challenge, driven by the ability of cancer cells to evade treatment through complex epigenetic adaptations. Identifying distinct molecular and structural signatures in drug-resistant cells is crucial for uncovering predictive biomarkers and understanding the mechanisms underlying resistance. In this study, we combine highly multiplexed fluorescence imaging and label-free quantitative phase imaging technologies with genomic analyses to investigate the morphological and molecular alterations associated with drug resistance. Using the colon cancer cell line SW480, we developed a drug-resistant phenotype by gradually increasing concentration of 5-fluorouracil (5-FU). Our approach includes morphological analysis, profiling 26 proteins and chromatin modifications, and transcriptomic evaluation. Genomic analyses—including CUT&RUN, RNA-seq, and ATAC-seq—further characterize histone modifications, gene expression, and chromatin accessibility in drug-resistant and parental cells. Our analysis reveals distinct morphological features in drug-resistant (DR) cells compared to their parental counterparts, such as increased morphological plasticity, an elongated shape and pronounced protrusions characteristic of cells undergoing epithelial-to-mesenchymal transition (EMT). A deep neural network analysis of these morphological features effectively distinguishes drug-resistant cells from parental cells, achieving a high area under the receiver operating characteristic curve (AUC) of 0.95. Biomarker expression analysis identifies significant changes in protein expression in drug-resistant cells, notably H3K27me3, H3K27ac, CD44, and EZH2, indicating substantial epigenetic reprogramming and increased stemness. Gene ontology analysis highlights the upregulation of Wnt and EMT pathways, alongside the downregulation of cell adhesion and tight junction pathways, reflecting enhanced invasiveness in drug-resistant cells. Additionally, ATAC-seq analysis reveals a more compact chromatin landscape in drug-resistant cells, consistent with epigenetic modifications that drive transcriptional repression of specific pathways. In conclusion, our multiscale high-content imaging platform proves to be a powerful tool for uncovering the morphological and molecular characteristics of drug-resistant cancer cells. We demonstrate that drug-resistant cells adopt mesenchymal-like morphology, coupled with significant epigenetic reprogramming, chromatin compaction, and enhanced stemness. These results underscore the interplay between morphological adaptations and epigenetic alterations in the development of drug resistance. Our study provides critical insights into the mechanisms driving resistance and lays the groundwork for identifying novel biomarkers and therapeutic targets. Citation Format: Yaxin Yang, Jianquan Xu, Chaojie Zhang, Hongqiang Ma, Sarah J. Hainer, Yang Liu. Multiscale high-content imaging to identify molecular and morphological signatures in drug-resistant cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6356.