by Christos Evangelou, MSc, PhD – Medical Writer and Editor
In a recent study, researchers at the University of Leicester and University Hospitals of Leicester NHS Trust developed a novel patient-derived explant (PDE) platform that could accelerate the development and preclinical testing of personalized breast cancer treatments. This novel PDE platform maintains the tumor’s complex architecture and immune microenvironment, replicating the in vivo environment of the tumor.1
By combining the PDE platform with digital pathology and multi-immunofluorescent imaging, the researchers were able to predict patient responses to both chemotherapy and targeted antibody therapies.1 According to the authors, the findings offer new hope for more effective, individualized treatment strategies for breast cancer.
“We showed that the sensitivity of PDEs to standard-of-care therapies, as measured by drug-induced tumor killing, were significantly correlated to patient outcomes, suggesting that the PDE platform reflects clinical responses,”
said Gareth Miles, PhD, lecturer at the University of Leicester and the corresponding author of the study.
“We also found significantly more tumor cell killing in breast cancer PDEs with high expression of HER2 when treated with trastuzumab, a therapeutic HER2 antibody, compared to PDEs with lower HER2 expression. This demonstrated that the PDE platform is amenable to testing antibody-directed therapies,”
Dr. Miles added.
The report was published in Scientific Reports.
The Unmet Need: Predicting Treatment Response in Breast Cancer
Despite significant advances in breast cancer treatment, many tumors are resistant to therapy, highlighting the need for more accurate and cost-effective methods to predict therapeutic benefit. Traditional preclinical models, such as cell line-derived xenografts and patient-derived xenografts, have limitations in terms of predictive power, cost, and time efficiency.1 Although patient-derived cancer organoids have shown promise, they cannot accurately recapitulate the patient-specific tumor characteristics and microenvironment.
“Our work primarily focuses on supporting anticancer drug development to improve patient outcomes. Around 95% of anticancer drugs fail to make it into the clinic due to a variety of factors. One major challenge is a lack of preclinical models that faithfully recapitulate the complexity of human tumors,”
noted Dr. Miles.
To address these challenges, researchers developed and optimized a PDE platform to predict treatment response in breast cancer.1 Dr. Miles explained that this approach aims to retain the intact tumor architecture and immune microenvironment while allowing for rapid assessment of drug responses in the preclinical setting.
“Developing models that have the potential to improve success rates in anticancer drug development inspired us to optimize our breast cancer PDE model,”
he said.
Approach: Combining Patient‑Derived Explants With Digital Pathology
The researchers collected fresh tumor samples from 55 patients who underwent surgery for breast cancer. These samples were processed into small fragments and cultured as PDEs on specialized inserts at the air-liquid interface. The team optimized culture conditions, including the use of autologous serum, to maintain tissue integrity.1
To assess drug responses, researchers treated the PDEs with a combination of chemotherapy drugs (5-fluorouracil, epirubicin, and docetaxel; FET) commonly used in breast cancer treatment. Some PDEs were also treated with the HER2-targeted antibody trastuzumab.1
The researchers employed advanced multiplexed immunofluorescence and whole-slide digital scanning to analyze biomarker changes in both tumor and stromal areas. Key parameters evaluated included cell proliferation (using Ki67 and Geminin markers), apoptosis (using cleaved PARP), and necrosis. The team also assessed the preservation of the immune microenvironment by analyzing various T cell populations within PDEs.
“Due to the complex intra-tumor heterogeneity, genetically and micro-environmentally, it is becoming increasingly realized that evaluating the spatial complexity of tumors is vitally important in understanding how cancers develop and how they respond to anticancer drugs. With this in mind, we optimized multiplexed fluorescent immunohistochemistry approaches and coupled it to digital whole-slide scanning and digital pathology image analysis software to determine if drug responses in PDEs could be spatially resolved,”
explained Dr. Miles.
PDEs Mirror Clinical Responses
PDE responses to FET chemotherapy showed a statistically significant relationship with patient progression-free survival (PFS). PDEs classified as responsive to FET treatment were associated with a mean PFS of 30 months, compared to 23 months for resistant PDEs (P = 0.012).1
When researchers assessed histological and molecular subtype-specific responses, they found that drug-induced cell death in PDEs reflected clinical expectations based on the tumor subtypes. For example, compared to invasive ductal carcinomas, mucinous carcinomas showed significantly higher apoptosis in response to FET.1
Moreover, the study showed that the PDEs reflect clinical responses to HER2-targeted therapy. The addition of trastuzumab to FET treatment resulted in significantly higher cell death in HER2-positive tumors, correlating with HER2 status and enrichment scores.1
PDEs Mirror Stromal Responses and the Immune Microenvironment
The platform allowed for the assessment of drug effects on both the tumor and stromal areas, revealing a positive correlation between drug-induced apoptosis in these regions. Furthermore, digital pathology analysis showed that the PDEs preserved the complex immune microenvironment of the tumor, maintaining immune cell populations, such as various T-cell subsets.1 PDEs retained intact tumor architecture and immune microenvironment for up to 72 hours in culture, which, according to Dr. Miles, is a key advantage over other ex vivo models.
“Whilst we did not dive into significant single cell detail, this study shows that the PDE platform can be assessed at the single cell level, maintaining spatial resolution, which has important implications for evaluating different types of biomarkers when assessing novel anticancer drug performance,”
he said.
Limitations and Future Work
The researchers acknowledge that larger multicenter studies are needed to further validate the predictive power of the PDE platform. The study included 55 patients, with only a small number experiencing disease progression or death.1
“In our study, we did have comparatively low numbers of triple-negative and HER2-enriched breast cancer subtypes, so more samples would be required to ensure the robustness of the data regarding these subtypes,”
noted Dr. Miles.
Moreover, PDEs were treated with anticancer drugs for 24 hours, and the short-term nature of the PDE culture (up to 72 hours) limits the ability to assess long-term drug effects or acquired resistance mechanisms.1
“There was some degree of tissue disintegration at later time points, so the model is best suited for assessing drug performance with anticancer drugs where we can see changes in a short period of time,”
Dr. Miles acknowledged.
Commenting on their next steps, Dr. Miles revealed their plans to assess the functionality of the immune microenvironment of breast cancer PDEs and test the utility of the PDE platform in evaluating immunomodulatory therapies, such as immune checkpoint inhibitors.
“We are also developing multiple additional models of PDEs from a large variety of different cancer types, which could be used for the same purposes,”
he added.
Dr. Miles concluded with his hope that the PDE platform could be utilized as a companion preclinical model in anticancer drug development, as a near-to-patient model.
“This would allow for the identification of more specific and bespoke predictive biomarkers of drug response, which could allow for the rationale design of stratified clinical trials to enhance personalized medicine and improve patient outcomes,”
he said.
References
- Demetriou C, Abid N, Butterworth M, et al. An optimised patient-derived explant platform for breast cancer reflects clinical responses to chemotherapy and antibody-directed therapy. Sci Rep. 2024;14(1):12833. Published 2024 Jun 4. doi:10.1038/s41598-024-63170-0
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