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Updated: Aug 14, 2026
Patient-Derived Tumor Explants As a "Live" Preclinical Platform for Predicting Drug Resistance in Patients
Published on: February 7, 2021
Sensing-Integrated Patient-Derived Tumorspheres Predict Chemotherapeutic Efficacy via Local Extracellular pH Dynamics
Stefania Forciniti1,2, Valentina Onesto1,2, Anna Chiara Siciliano1,2
1Institute of Nanotechnology, National Research Council (CNR-NANOTEC), c/o Campus Ecotekne, Lecce, Italy.
Abstract:
Pancreatic ductal adenocarcinoma (PDAC) is among the deadliest malignancies, due to late diagnosis, poor therapeutic response, and high inter- and intra-patient heterogeneity. Metabolic alterations, particularly extracellular acidification, critically impair drug response yet remain underexplored in clinical stratification. We present a sensing-integrated 3D platform that enables non-invasive time-resolved mapping of pH dynamics in patient-derived tumorspheres. Primary PDAC cells from five patients were embedded in an alginate-based matrix incorporating ratiometric optical pH sensors, allowing real-time monitoring of local extracellular acidification associated with individual cells during treatment. In contrast to existing bulk or invasive methods, our platform captures extracellular acidification dynamics with high spatial and temporal resolution in a 3D model with potential clinical relevance. Distinct extracellular acidification profiles emerged in response to FOLFIRINOX, gemcitabine, and paclitaxel. These metabolic signatures correlated with treatment efficacy and highlighted patient-specific drug sensitivities. This platform offers a rapid, scalable tool for personalized drug screening and highlights a potential role of pH metabolic heterogeneity in PDAC chemoresistance. It may complement existing clinical workflows by providing early predictive insights into patient-specific therapeutic outcomes.
Insights
This study introduces a 3D platform to monitor pH changes in pancreatic cancer cells, revealing metabolic signatures linked to drug response and patient-specific sensitivities for personalized treatment.
Area of Science:
- Oncology
- Biomedical Engineering
- Metabolic Research
Background:
- Pancreatic ductal adenocarcinoma (PDAC) presents significant challenges due to late diagnosis and treatment resistance.
- Metabolic alterations, including extracellular acidification, are critical in PDAC but poorly understood for clinical use.
- Current methods for assessing tumor microenvironment lack the resolution needed to capture dynamic metabolic changes.
Purpose of the Study:
- To develop and validate a novel 3D platform for real-time, non-invasive monitoring of extracellular pH dynamics in patient-derived PDAC models.
- To investigate the correlation between metabolic acidification profiles and therapeutic response to standard chemotherapy regimens.
- To explore the potential of pH heterogeneity as a biomarker for predicting patient-specific drug sensitivity and chemoresistance in PDAC.
Main Methods:
- A sensing-integrated 3D platform was created using alginate matrices with embedded ratiometric optical pH sensors.
- Patient-derived PDAC cells (tumorspheres) from five individuals were cultured within the sensor-laden matrix.
- Extracellular acidification dynamics were monitored in real-time during treatment with FOLFIRINOX, gemcitabine, and paclitaxel.
Main Results:
- The platform successfully captured high-resolution, time-resolved extracellular pH dynamics in 3D PDAC tumorspheres.
- Distinct extracellular acidification profiles were observed in response to different chemotherapeutic agents.
- Metabolic signatures correlated with treatment efficacy, demonstrating patient-specific drug sensitivities and highlighting heterogeneity in chemoresistance.
Conclusions:
- The developed 3D sensing platform provides a clinically relevant tool for personalized drug screening in PDAC.
- Extracellular pH dynamics and metabolic heterogeneity are significant factors in PDAC chemoresistance.
- This approach offers potential for early prediction of therapeutic outcomes, complementing existing clinical strategies.
