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Updated: Sep 17, 2025
Through the Looking Glass: Time-lapse Microscopy and Longitudinal Tracking of Single Cells to Study Anti-cancer Therapeutics
Published on: May 14, 2016
Application of single-cell and spatial omics in deciphering cellular hallmarks of cancer drug response and resistance
Xiaoxia Cheng1,2, Ting Peng2,3, Tian Chu1,2
1Department of Gynecologic Oncology, Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1277, Jiefang Road, Wuhan, 430030, Hubei, China.
Abstract:
Drug resistance poses a significant challenge in cancer therapy, contributing to rapid recurrence, disease progression, and high patient mortality. Despite its critical impact, few reliable predictors for cancer drug response or failure have been established for clinical application. Tumor heterogeneity and the tumor microenvironment (TME) are pivotal factors influencing cancer drug efficacy and resistance. Tumor heterogeneity leads to variable therapeutic responses among patients, while dynamic interactions between cancer cells and the TME enhance tumor survival and proliferation, underscoring the urgent need to identify cellular hallmarks for predicting drug response and resistance. Single-cell and spatial omics technologies provide high-resolution insights into gene expression at the individual cell level, capturing intercellular heterogeneity and revealing the underlying pathologies, mechanisms, and cellular interactions. This review delves into the principles, methodologies, and workflows of single-cell and spatial omics in cancer drug research, highlighting key hallmarks involving tumor heterogeneity, TME reprogramming, cell-cell interactions, metabolic modulation, and signaling pathway regulation in drug treatment at single-cell and spatial levels. Furthermore, we synthesize predictive cellular biomarkers for cancer drug response and resistance across 25 cancer types, paving the way for advancements in cancer precision medicine.
Insights
Single-cell and spatial omics reveal cellular hallmarks predicting cancer drug response and resistance. This research identifies key biomarkers across 25 cancer types to advance precision medicine and improve patient outcomes.
Area of Science:
- Oncology
- Genomics
- Biotechnology
Background:
- Drug resistance is a major obstacle in cancer therapy, leading to poor outcomes.
- Predicting patient response to cancer drugs remains a significant clinical challenge.
- Tumor heterogeneity and the tumor microenvironment (TME) critically influence drug efficacy and resistance.
Purpose of the Study:
- To review the application of single-cell and spatial omics in understanding cancer drug response and resistance.
- To identify key cellular hallmarks associated with drug treatment outcomes.
- To synthesize predictive biomarkers for cancer drug response and resistance.
Main Methods:
- Review of single-cell and spatial omics technologies and their workflows.
- Analysis of cellular heterogeneity, TME interactions, and signaling pathways.
- Synthesis of predictive cellular biomarkers from existing literature.
Main Results:
- Single-cell and spatial omics provide high-resolution insights into gene expression and cellular interactions.
- Key hallmarks influencing drug response include tumor heterogeneity, TME reprogramming, cell-cell interactions, metabolic modulation, and signaling pathways.
- Predictive cellular biomarkers for drug response and resistance were identified across 25 cancer types.
Conclusions:
- Single-cell and spatial omics are powerful tools for dissecting cancer drug resistance mechanisms.
- Identification of predictive biomarkers is crucial for advancing cancer precision medicine.
- This work provides a foundation for developing novel therapeutic strategies and improving patient stratification.
