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Published on: August 16, 2020
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
|May 8, 2026
Summary
Tumor microenvironment cellular diversity 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 chemotherapy and targeted treatments.
Area of Science:
- Oncology
- Cancer Biology
- Drug Discovery
Background:
- High-grade serous tubo-ovarian cancer (HGSC) exhibits significant inter- and intra-tumor heterogeneity.
- Tumor microenvironment (TME) cellular composition varies across metastatic sites, correlating with poorer patient outcomes.
- The impact of TME cellular makeup on chemotherapy and targeted therapy sensitivity remains underexplored.
Purpose of the Study:
- To investigate if variations in TME cellular composition can predict drug efficacy in HGSC.
- To assess the drug responses of diverse tumoroid cellular configurations to multiple therapeutic agents.
- To correlate TME cellular composition with treatment responses using machine learning.
Main Methods:
- Utilized a high-throughput 3D in vitro tumoroid model with 23 distinct cellular compositions.
- Tested tumoroids (OVCAR3 HGSC cells, mesenchymal stem cells, HUVEC, U937 monocytes) against five therapeutic agents, including carboplatin and paclitaxel.
- Employed random forest machine learning to analyze the influence of TME cellular composition on treatment reactions.
Main Results:
- Tumoroid compositions with abundant myeloid cells exhibited the highest pooled viability against the tested drugs.
- Tumoroids composed solely of cancer cells demonstrated the greatest sensitivity to the therapeutic agents.
- Mesenchymal-rich tumoroids (≥400 mesenchymal stem cells) showed increased sensitivity to carboplatin compared to paclitaxel.
Conclusions:
- TME cellular diversity significantly influences HGSC treatment responses, acting as a predictor of therapeutic outcomes.
- Human tumoroids with variable cellular composition offer a valuable platform for studying TME components' role in cancer cell drug susceptibility.
- Findings highlight the need to consider TME heterogeneity for personalized ovarian cancer treatment strategies.
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