Application of single-cell and spatial omics in deciphering cellular hallmarks of cancer drug response and resistance
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...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-07-01
|
| Series: | Journal of Hematology & Oncology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13045-025-01722-1 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|---|
| ISSN: | 1756-8722 |