Researchers from Moffitt Cancer Center have developed a real-time ex vivo chemosensitivity assay to predict patients’ clinical response to chemotherapy in pancreatic cancer. The study, published in Oncotarget, addresses the limitations of using patient-derived organoids (PDOs) and xenografts (PDXs) for drug screening.
PDOs and PDXs have been widely studied for drug screening, but their establishment time is lengthy, and they have high engraftment failure rates. Additionally, the tumor microenvironment of these models differs from that of the original tumors. To overcome these limitations, the researchers developed a real-time ex vivo chemosensitivity assay called real-time live tissue sensitivity assay (RT-LTSA) using fresh tumor samples.
The assay involves placing tissue slices from resected pancreatic cancer samples in 96-well plates and treating them with chemotherapeutic agents. The researchers analyzed the correlation between tissue slice chemo-sensitivity and each patient’s clinical outcome. The viability and tumor microenvironment of the tissue slices were well-preserved for up to 5 days, and the drug sensitivity assay results were available within 5 days after tissue collection.
The study found that patients who received RT-LTSA sensitive adjuvant regimens had better disease-free survival compared to those who received resistant regimens. All four patients who received RT-LTSA sensitive adjuvant regimens did not develop recurrence, while seven out of eight patients who received resistant regimens had recurrences. There was a significant negative correlation between the RT-LTSA value and relapse-free survival.
The researchers concluded that RT-LTSA, which maintains the tumor microenvironment and architecture found in patients, could be used as a personalized strategy for pancreatic adenocarcinoma. However, further studies are needed to verify these findings.
This new method has the potential to improve the prediction of chemotherapy response in pancreatic cancer patients and may contribute to more personalized treatment strategies. Additional research could lead to a better understanding of how to optimize therapy choices based on a patient’s individual tumor characteristics and response to treatment.
Source: Oncotarget Journal