Fluorescence Lifetime Imaging for Quantification of Targeted Drug Delivery in Varying Tumor Microenvironments
Amit Verma1, Vikas Pandey2, Catherine Sherry1
1Department of Molecular and Cellular Physiology, Albany Medical College, Albany, NY 12208, USA.
Rationale:
Trastuzumab (TZM) is a monoclonal antibody that targets the human epidermal growth factor receptor (HER2) and is clinically used for the treatment of HER2-positive breast tumors. However, the tumor microenvironment can limit the access of TZM to the HER2 targets across the whole tumor and thereby compromise TZM's therapeutic efficacy. An imaging methodology that can non-invasively quantify the binding of TZM-HER2, which is required for therapeutic action, and distribution within tumors with varying tumor microenvironments is much needed.
Methods:
We performed near-infrared (NIR) fluorescence lifetime (FLI) Forster Resonance Energy Transfer (FRET) to measure TZM-HER2 binding, using in vitro microscopy and in vivo widefield macroscopy, in HER2 overexpressing breast and ovarian cancer cells and tumor xenografts, respectively. Immunohistochemistry was used to validate in vivo imaging results.
Results:
NIR FLI FRET in vitro microscopy data show variations in intracellular distribution of bound TZM in HER2-positive breast AU565 and AU565 tumor-passaged XTM cell lines in comparison to SKOV-3 ovarian cancer cells. Macroscopy FLI (MFLI) FRET in vivo imaging data show that SKOV-3 tumors display reduced TZM binding compared to AU565 and XTM tumors, as validated by ex vivo immunohistochemistry. Moreover, AU565/XTM and SKOV-3 tumor xenografts display different amounts and distributions of TME components, such as collagen and vascularity. Therefore, these results suggest that SKOV-3 tumors are refractory to TZM delivery due to their disrupted vasculature and increased collagen content.
Conclusion:
Our study demonstrates that FLI is a powerful analytical tool to monitor the delivery of antibody drug tumor both in cell cultures and in vivo live systems. Especially, MFLI FRET is a unique imaging modality that can directly quantify target engagement with potential to elucidate the role of the TME in drug delivery efficacy in intact live tumor xenografts.
Insights
Near-infrared fluorescence lifetime imaging (FLI) with Förster Resonance Energy Transfer (FRET) effectively monitors Trastuzumab (TZM) delivery to HER2-positive tumors. This method reveals how tumor microenvironment factors like collagen and vascularity impact TZM binding and efficacy.
Area of Science:
- Oncology
- Biomedical Imaging
- Pharmacology
Background:
- Trastuzumab (TZM) is a key therapy for HER2-positive breast cancer, but its effectiveness can be limited by the tumor microenvironment (TME).
- Non-invasive imaging is needed to quantify TZM binding and distribution within tumors to understand treatment efficacy.
- Understanding TZM-HER2 interactions is crucial for optimizing cancer therapy.
Approach:
- Near-infrared (NIR) fluorescence lifetime imaging (FLI) combined with Förster Resonance Energy Transfer (FRET) was employed to measure TZM-HER2 binding.
- Experiments were conducted using in vitro microscopy on cancer cell lines and in vivo widefield macroscopy on tumor xenografts.
- Immunohistochemistry was used for ex vivo validation of in vivo imaging findings.
Key Points:
- NIR FLI FRET microscopy revealed variations in TZM intracellular distribution in different HER2-positive cancer cell lines.
- In vivo macroscopy FLI (MFLI) FRET showed reduced TZM binding in SKOV-3 ovarian cancer xenografts compared to breast cancer xenografts.
- Tumor microenvironment components, including collagen and vascularity, differed between xenograft models, correlating with TZM delivery and binding efficacy.
Conclusions:
- FLI is a powerful tool for monitoring antibody drug delivery in both in vitro and in vivo systems.
- MFLI FRET can directly quantify target engagement and elucidate the role of the TME in drug delivery.
- This imaging approach has the potential to guide personalized cancer treatment strategies by assessing drug efficacy in real-time.
