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Heterogeneity of Ex Vivo Tumor Responses in Ovarian Cancer Tissues
Chiara Maestri1, Ivan Trus1,2, Rajeshwar Nitiyanandan1
1SageMedic Corp, Redwood City, California, USA.
Background:
Advanced-stage ovarian cancers exhibit significant variability in responses to standard chemotherapy ranging from platinum-refractory to platinum-sensitive cancers. While genomic testing reveals tissue heterogeneity, it rarely provides actionable data for guiding therapy.
Aims:
To evaluate the heterogeneity of ex vivo drug responses in primary ovarian cancer tissues using a functional profiling platform, and to assess the platform's potential for guiding personalized therapy selection within current clinical practice.
Methods And Results:
A functional profiling platform that creates 3D microtumors from fresh biopsies was used to enable ex vivo assessment of drug efficacy in a physiologically relevant model. Interpatient heterogeneity was quantified as the statistical variability of the EC50 values, calculated using the ratio of upper and lower interdecile values. Seventeen ovarian cancer tissues were processed and exposed to NCCN-recommended drugs and drug combinations. Drug efficacy demonstrated significant interpatient heterogeneity (p < 0.001). Carboplatin and paclitaxel alone exhibited moderate heterogeneity (54-fold and 42-fold difference), while their combination showed higher heterogeneity (3880-fold difference), suggesting synergy in certain samples but not in others. Gemcitabine exhibited the highest single-agent heterogeneity across the cohort (1504-fold difference), whereas doxorubicin and olaparib demonstrated more consistent responses but limited efficacy in many samples (20-fold and 16-fold difference).
Conclusion:
These findings align with the clinically observed variability in patient responses, highlighting the platform's potential to optimize therapy selection and support patient-centric care within the standard of care for ovarian cancer patients.
Insights
This study reveals significant patient-to-patient differences in how ovarian cancer tissues respond to chemotherapy drugs. A new functional profiling platform shows potential for guiding personalized treatment selection in ovarian cancer.
Area of Science:
- Oncology
- Pharmacology
- Biotechnology
Background:
- Advanced ovarian cancer shows variable responses to chemotherapy, with genomic testing offering limited actionable insights.
- Tissue heterogeneity in ovarian cancer contributes to diverse treatment outcomes.
- Current therapeutic strategies lack personalized guidance due to limitations in predicting drug response.
Purpose of the Study:
- To assess ex vivo drug response heterogeneity in primary ovarian cancer tissues using a novel functional profiling platform.
- To evaluate the platform's capability in guiding personalized therapy selection for ovarian cancer patients.
- To quantify interpatient variability in drug efficacy for standard chemotherapeutic agents.
Main Methods:
- A functional profiling platform was utilized to create 3D microtumors from fresh ovarian cancer biopsies for ex vivo drug efficacy assessment.
- Drug efficacy was evaluated by measuring the half-maximal effective concentration (EC50) and quantifying interpatient heterogeneity.
- Seventeen ovarian cancer tissue samples were exposed to NCCN-recommended drugs and drug combinations, including carboplatin, paclitaxel, gemcitabine, doxorubicin, and olaparib.
Main Results:
- Significant interpatient heterogeneity in drug response was observed across all tested agents (p < 0.001).
- The combination of carboplatin and paclitaxel demonstrated substantial heterogeneity (3880-fold difference), indicating variable synergy.
- Gemcitabine showed the highest single-agent heterogeneity (1504-fold difference), while doxorubicin and olaparib had more consistent but often limited efficacy.
Conclusions:
- The observed drug response heterogeneity aligns with clinical variability in ovarian cancer patient outcomes.
- The functional profiling platform demonstrates potential for optimizing therapy selection in ovarian cancer.
- This approach supports patient-centric care by providing actionable data within the standard of care.
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