Interview: Screening Platform Informs Personalized Treatments for Cancer Patients
Contributors: Dr. Nan Qin, Medical Faculty at the Department of Pediatric Oncology, Hematology, and Clinical Immunology Department in University Hospital Düsseldorf
Last updated: July 2023
Live-cell analysis is a powerful tool for studying the phenotype and function of cells in real time. In clinical research, monitoring live cells facilitates drug testing on disease models, such as cancer cells, providing rich insights on mechanism of action, toxic effects, dosing, and personalized treatments for patients. Additionally, live monitoring provides valuable information about cell growth and behavior during the development of 2D and 3D models systems, such as organoids.
In this interview, Simon Bennett, Regional Business Manager at Sartorius spoke with Dr. Nan Qin, Medical Faculty at the Department of Pediatric Oncology, Hematology, and Clinical Immunology Department in University Hospital Düsseldorf, about using advanced cell-based screening to help match cancer patients with the optimal late-stage anticancer drugs. She also explains how live-cell analysis enables them to get a more complete drug response profiles in their clinical studies using 2D and 3D models.
Question: Could you describe your role and research focus?
Nan Qin
I am currently conducting research on group 3 medulloblastoma, which is the most prevalent malignant brain tumor found in children. This particular type of tumor has a significantly poorer prognosis than other pediatric tumors, with approximately 50% of patients succumbing to it within five years. As a result, our team has taken the initiative to construct a high-throughput drug screening process to guide personalized treatment strategies for patients.
Initially, we followed the standard procedure by incubating patient cells with drugs in a white-bottom plate for 72 hours and conducting various endpoint readouts. However, we were not able to monitor the cells throughout the process, leaving us uncertain about their condition right after dispensing into the wells, and their behavior during incubation. As a result, we encountered several outcomes that we couldn't understand. Hence, we became intrigued by live-cell imaging and discovered that the Incucyte system was a better fit for exploring drug screening for personalized therapy.
Question: What were the major limitations with your previous workflows for 3D culture preparation? Such as missing data points and the right time to do endpoint analysis.
Nan Qin
In standard experiments, repeating a test is a viable option when there are doubts about the result. However, this is not possible with patient samples since there may only be a limited amount available, and only one opportunity to conduct the experiment. This means that when the data collected is of poor quality, it cannot be used to determine the appropriate treatment strategy for the patient.
By incorporating Incucyte into our workflow, we can gather more in-depth information about cells. Unlike before, we can now run experiments for up to 120 hours. We can monitor exactly what happens in each well from the moment we dispense the cells until we calculate the numbers. The imaging data is more accurate and reliable, giving us greater confidence in our findings. Additionally, unlike endpoint experiments, with the live-cell imaging system we no longer need to add a readout reagent that can kill cells. This allows us to conduct further experiments once we complete detection using Incucyte.
Furthermore, we can use a combination of dyes, such as Cytotox dyes and Annexin V, to get more information from each well. In some cases, the staining data can validate one another. For instance, if we notice a reduction in cell number and an increase in annexin staining, which is an indication of apoptosis, we can have more confidence in the results we obtain.
Question: How does the Incucyte enable your high-throughput drug screening workflow?
Nan Qin
We use the Incucyte system to conduct two types of experiments. In our high-throughput studies, we test single concentrations of compounds and observe their response over time. For instance, we expose cells to 2.5 microliters of a drug and analyze how it affects them as time passes. Once we identify potential drugs, we subject them to dose-response testing over time.
Question: What sort of mechanistic insights have you gained from these sets of experiments about the action of the drugs?
Nan Qin
Initially, we expected certain compounds to have a significant anti-cancer effect after 72 hours, but we were surprised to see no effect at all. However, after using the Incucyte system, we noticed that these compounds took 120 hours to start working. This observation is consistent with what we have seen in patients, where chemotherapy treatments often take several months to show results. The Incucyte experiment helped us realize that we had underestimated the therapeutic effect of some compounds due to inadequate incubation time. By using live-cell imaging, we were able to better understand the dynamic drug response and optimize appropriate drug doses.
Question: How is the ability to study 3D organoids with live-cell analysis driving your personalized medicine goals? What sort of questions are you trying to answer?
Nan Qin
Timing is crucial for ensuring the success of organoids and by using the Incucyte live-cell imaging system we can improve the conditions for culturing 3D model systems. We label the primary cancer cells with live-cell staining and monitor the intensity of the fluorescence signal to semi-quantify the growth of cancer cells. This enables us to monitor the drug response over a prolonged period and effectively determine the optimal treatment duration for certain compounds in the 3D model system.
Question: How do you currently grow the organoid models? Are you using patient cells?
Nan Qin
We have been facing difficulties in growing a 3D organoid system with patient cells as most of them die before reaching the 3D model stage. Our success rate has been only around 20%. Therefore, we have decided to switch to different models. Our current focus is on creating a brain organoid using healthy iPS cells, which provide a suitable microenvironment for tumor cells. We then introduce labeled tumor cells to this organoid. This fresh approach has led to a significant increase in cell viability and a higher percentage of viable cells, which we can use for our drug validation studies downstream.
Question: Where do you see your field going in the future?
Nan Qin
Before reaching the market, clinical drugs must undergo a strict validation process that includes testing in animal models. Unfortunately, some patients, such as patients with brain metastases, who typically have a survival rate of less than 6 months, cannot afford to wait for these tests to be completed. Therefore, personalized drug screening using patient-specific 3D models and combining the results with advanced surgical and radiological techniques may help improve their prognosis.
