Integrating patient-derived organoids and multi-omics to decode spatiotemporal therapeutic resistance

Abstract

Intratumoral heterogeneity, alongside the dynamic evolution of cancer cells, continues to pose principal obstacles to efficacious cancer therapies. Although patient-derived organoids (PDOs) represent the gold standard for recapitulating patient-specific histopathology, their full utility emerges only through integration with high-resolution molecular profiling. This review synthesizes recent progress in combining PDOs with multi-omics approaches—including genomics, single-cell transcriptomics, and spatial omics—to elucidate the underpinnings of therapeutic resistance. We initially explore how organoid genomic profiling can monitor clonal dynamics and subclonal selection under therapeutic pressure. Next, we underscore the contributions of single-cell RNA sequencing in delineating transcriptional plasticity, detecting infrequent drug-tolerant persister populations, and charting nongenetic adaptive pathways. Of particular importance, we address the nascent domain of spatial transcriptomics, which preserves the structural integrity of organoids to uncover how proximate cell-cell interactions and niche elements shield tumor cells from therapeutic insult. Through the fusion of these multifaceted datasets, we advance a novel paradigm that frames resistance not as a fixed binary state, but as a spatiotemporally evolving adaptive phenomenon. The review culminates in delineating the translational promise of this synergistic paradigm for devising combination regimens that concurrently address genetic aberrations and adaptive microenvironments.

Keywords

Patient-derived organoids / Multi-omics profiling / Therapeutic resistance / Spatiotemporal heterogeneity / Clonal evolution / Single-cell RNA sequencing

Acknowledgments

None.

Funding

This work was supported by the Key Special Projects of the “14th Five-Year Plan” of the National Key R&D Program of China (2023YFC2508601, 2023YFC2508604, and 2023YFC2508605), the National Natural Science Foundation of China (grant numbers: 82072568, 82373320), the Shanghai Shenkang Hospital Development Center (grant number: SHDC12020110), the Shanghai Shenkang Development Research Physician Project (grant number: SHDC2022CRD048), and the Tongji University Medicine-X Interdisciplinary Research Initiative (2025-0554-ZD-08).

Conflict of interest

The authors declare that they have no competing interests.

Author contributions

Conceptualization: Chunxia Su, Cize Gao, Jianing Chen

Funding acquisition: Chunxia Su

Resources: Leilei Wu

Supervision: Leilei Wu, Chunxia Su

Visualization: Cize Gao

Writing-original draft: Cize Gao

Writing-review & editing: Chunxia Su, Jianing Chen, Cize Gao, Boyue Pang

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data

Not applicable.

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