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The findings of the latest study, published in the journal EMBO Molecular Medicine, Peschke et al. (2022), show that patient-derived organoids can identify new cancer treatments for patients with pancreatic ductal adenocarcinoma (PDAC).
Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant form of pancreatic cancer with a 5-year survival rate of about 10%. Early metastatic progression, as well as high resistance to all current standard treatments, including radiotherapy and chemotherapy, make it a devastating disease. Surgical resection combined with chemotherapy has therapeutic potential, but only in about 20% of cases, most patients are diagnosed with advanced disease and are not suitable for surgical resection.
Common treatment options for pancreatic ductal adenocarcinoma (PDAC) include gemcitabine (Gem) plus albumin-binding paclitaxel or FOLFIRINOX (5-fluorouracil, folinic acid, irinotecan, and oxaliplatin). Although these regimens were not statistically significant in comparison between trials, the efficacy of FOLFIRINOX makes it the preferred first-line treatment option for patients. In addition, due to its superior tolerability, Gem-based treatment regimens are only suitable for poorly constructed or elderly patients. However, these chemotherapy regimens inevitably develop toxicity and resistance and can only increase median survival by about a year. Therefore, if the sensitivity of individualized chemotherapy can be predicted in relevant models, it is possible to minimize toxicity while improving the expected efficacy.
Standard treatment options for pancreatic ductal adenocarcinoma (PDAC) include combination chemotherapy, which is associated with toxicity and eventual tumor resistance. In PDAC, a pattern needs to be looked for due to the lack of relevant tools to identify and evaluate new therapies, especially in cases where there is resistance to standard treatments.
In the study by Peschke et al. (2022), they describe a longitudinal platform that utilizes patient-derived organoids (PDOs) to identify drug-induced vulnerabilities after standard care chemotherapy treatment, providing the opportunity to predict treatment response and define new treatment vulnerabilities induced by standard care.
Previously, tumor resistance to chemotherapy was often described as the selection of drug-resistant tumor cell populations. However, Peschke et al. (2022) demonstrated that PDAC cells appear to acquire resistance not only through genetic alterations, but also through alterations in cell plasticity leading to changes in gene expression and metabolism. Therefore, the study supports this type of platform for identifying new therapeutic targets after standard treatment with PDAC.
Treatment-induced plasticity is the main cause of failure of PDAC treatment. PDOs derived before and after treatment can be used to predict drug responses, identify chemotherapy-induced vulnerabilities, and provide opportunities for patients to choose an effective treatment regimen.
Further analysis found that FOLFIRINOX treatments create a resistant phenotype by inducing changes in cell plasticity, leading to new drug sensitivities. Peschke et al. (2022) conducted drug screening for 415 compounds and narrowed the difference in response between sensitive and drug-resistant PDOs to 3%. Post-treatment PDOs are resistant to Aurora kinase inhibitors, eIF4E/eIF4G interaction inhibitors, and SMAC mimetics, but are sensitive to ATPase p97/valosin-containing protein inhibitors (CB-5083 and NMS-873), epidermal growth factor receptor inhibitors (lapatinib and bozetinib), and MEK inhibitors (trimetinib, corbitinib, and BI-847325).
Since the KRAS-MEK-ERK axis is the primary driver of PDAC tumorigenesis, Peschke et al. (2022) validated the sensitivity of MEK inhibitors (MEKi) in a larger patient cohort and confirmed chemotherapy-induced cellular fragility after neoadjuvant therapy. Using PDOs, this study identified different responses to the cellular plasticity exerted by multi-chemotherapy regimens and associated targeted therapies.
The authors demonstrated that the vulnerability of cancer cells after chemotherapy is not related to genetic mechanisms. This suggests that additional tests using PDOs are necessary to determine the sensitivity of new treatment options, rather than just assessing the genetic profile of the tumor. Additional research into these new pathways that change after chemotherapy will help select PDAC treatment options.
The PDO model used in this study makes it a highly reliable and specific model for studying these mechanisms. This suggests another potential use for PDOs is to identify new cancer treatments for PDAC patients.