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Cracking the code: predicting tumor microenvironment enabled chemoresistance with machine learning in the human
Michael E Bregenzer1, Pooja Mehta2, Kathleen M Burkhard1
1Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI USA.
Npj Biomedical Innovations
|August 22, 2025
Summary
Tumor microenvironment cellular composition impacts high-grade serous tubo-ovarian cancer (HGSC) treatment response. Cancer cell-only tumoroids were most sensitive, while myeloid-rich tumoroids showed higher viability to therapies.
Area of Science:
- Oncology
- Biotechnology
- Cancer Research
Background:
- High-grade serous tubo-ovarian cancer (HGSC) exhibits significant tumor heterogeneity.
- Tumor microenvironment (TME) cellular composition varies across metastatic sites, impacting patient outcomes.
- The relationship between TME cellularity and therapy sensitivity remains underexplored.
Purpose of the Study:
- To investigate if TME cellular composition can predict drug efficacy in HGSC.
- To assess the impact of varying cellular configurations on therapeutic responses.
- To establish a foundation for using diverse tumoroid models in cancer research.
Main Methods:
- Utilized a high-throughput 3D in vitro tumoroid model with 23 distinct cellular configurations.
- Tested drug responses of tumoroids (OVCAR3 HGSC cells, mesenchymal stem cells, HUVEC, U937 monocytes) to five therapeutic agents, including carboplatin and paclitaxel.
- Employed random forest machine learning algorithms to analyze TME composition's influence on treatment reactions.
Main Results:
- Tumoroid compositions with abundant myeloid cells exhibited the highest pooled viability against tested drugs.
- Tumoroids composed solely of cancer cells demonstrated the greatest sensitivity to the therapeutic agents.
- "Mesenchymal tumoroids" with ≥400 mesenchymal stem cells showed greater sensitivity to carboplatin than paclitaxel.
Conclusions:
- TME cellular diversity significantly influences therapeutic outcomes in HGSC.
- Tumoroid composition serves as a predictor of drug response, highlighting the role of stromal and immune cells.
- This study supports the use of varied human tumoroid models to explore TME cell functions in enhancing cancer treatment susceptibility.
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