Tumorgenesis is a dynamic process caused by many intertwined factors. During cancer progression, genetic and epigenetic aberrations lead to dramatically different genomic landscapes in patients, and different treatments further contribute to genome evolution and remodeling. In addition, intratumoral spatial and temporal heterogeneity adds to the complexity of cancer, which refers to the diversity of cancer cell phenotypes and different states of cancer cells in a single patient due to cancer evolution and anticancer treatment choices. Furthermore, the spatial structure of cancer is formed by interactions between different cellular components and tissue structures such as blood vessel distribution. Capturing these fundamental features and recapitulating these evolutionary features of human cancers are key prerequisites for cancer models to accurately reflect cancer responses and address the challenges of cancer therapy. Medicilon’s research on PDX model includes molecular level genotyping and pharmacological efficacy evaluation service of orthotopic model, promising great prediction for clinical efficacy research.
The Emergence of PDX Model - What
is PDX Model
Therefore, animal models such as genome-edited mouse models, patient-derived organoids, and patient-derived xenografts (PDX) have been used to study cancer biology and cancer pathogenesis studies. [1] Animal models play an important role in the development of new drugs and the study of biological mechanisms. Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer.Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds.
PDX for a New Era in Cancer Therapy. This figure shows the challenges of current cancer treatment, including beneficiary limitation, tumor heterogeneity, drug resistance, and tumor metastasis and recurrence, and shows the multiple functions of PDX in the development of anticancer therapies
History of PDX Model Development
PDX
models have had a history of "rediscovery". The first reported
patient-derived xenografts meeting the definition of the PDX model date back to
1969, when Rygaard and Povlsen excised colon adenocarcinoma from a patient and
implanted tumor fragments into nude mice. Later, the researchers demonstrated
that the PDX models showed comparable responses to corresponding patients when
they received chemotherapy. In the 2010s, the optimization of PDX establishment
technology and the popularization of sequencing technology boosted the revival
of PDX models. The use of the colorectal cancer PDX platform to identify HER-2
inhibitors for cetuximab-resistant patients is an example demonstrating the
utility of PDX models in targeted therapy. In 2016, Gao built about 1,000 PDX models
and tested drug response on them according to the clinical trial design, which
is a paradigm of patient-derived clinical trials (PCT). Widespread use of sequencing
further validates the genomic concordance between patients and PDX models and
facilitates preclinical studies of targeted therapies in PDX models. Since
then, a growing number of platforms have validated that PDX models faithfully
reproduce cancer mechanisms. [1]
Brief Timeline of PDX Research Milestones
PDX model-In-vivo Studies of Drugs
PDX models are widely used in in-vivo tests of drugs, including pharmacodynamic evaluation of anti-tumor drugs, screening of new tumor drugs, drug combination tests and tumor drug resistance studies, etc. For example, the heterogeneity of the PDX model makes the tumor samples from different patients have different genetic information, and the drug test on the PDX model of different patients can better reflect the individual situation of the patient, and has a greater impact on individualized clinical medicine. Good instructive. Drug resistance of tumor cells is an important reason why many cancer patients are difficult to treat, especially multidrug resistance (MDR) is one of the problems that need to be solved urgently in cancer treatment. The mechanism of tumor drug resistance has always been a research hotspot. Since PDX models can provide a large number of materials and microenvironments similar to original human tumors, they have been widely used in the evaluation of tumor radiotherapy, tumor stem cells, tumor biomarkers and targeted therapy, and tumor hormone resistance. Experiments have confirmed that both blood tumors and solid tumors contain TICs (tumor-initiating cells) or CSCs (cancer stem cells) subpopulations. Although TICs/CSCs are only a very small subset of cells in tumor tissue, preclinical studies have shown that TICs are more resistant to radiation, chemotherapy, and targeted therapy, and such characteristics are very important for the study of drug resistance and tumor recurrence. Compared with traditional cell line in vitro experiments and cell line xenograft models, tumors in PDX models are derived from patient specimens, and TICs isolated from them better maintain the biological characteristics of the primary tumor. Due to the good repeatability and parallel control of the PDX model, it can reveal the evolution of tumor cell clones, and can also be used to design new treatment methods and predict drug resistance mechanisms.
Problems with PDX models
When applying PDX models and analyzing experimental results, it must be clearly recognized that the advantages of PDX models are relative. Mice and humans are always two different species, and the differences between species cannot be completely eliminated. In addition, the cost of PDX model modeling is high and the cycle is long, and only the primary transplantation takes more than 2 to 3 months. The technical requirements for the operation are high, and the specimens need the close cooperation of surgeons, histologists and researchers after they are obtained from the operating room. At the same time, due to the limited number of patient-derived tumor tissues and the restrictions on use by medical ethics, the number of existing primary models is small, and the passaged samples need to be tested by histopathology to determine their consistency with the original samples. After undergoing this series of precise and complex operations, the average tumor formation rate of PDX models is only about 25%.
Outlook:
WHO reported that there were about
14 million new cancer cases and 8.2 million deaths from cancer in 2012. With
the number of new cases expected to increase by about 70% in the next two
decades, cancer remains the leading cause of morbidity and mortality worldwide.
In the research of cancer treatment, the biggest challenge is that the model of
preclinical test cannot fully simulate the clinical situation, so the test
results cannot be successfully applied to the clinic. In fact, although many
therapeutic methods are very effective in mouse models, when applied to humans,
the efficacy is greatly reduced, even less than 10%. For example, in the study
of non-small cell lung cancer, 5% of the therapeutic drugs had good preclinical
efficacy, but were abandoned due to the lack of due effect in clinical phase
III trials. The main reason for the analysis was the lack of response to
personalized medicine sensitive groups. The PDX model replicates the
heterogeneity of the patient's tumor, establishes a drug evaluation system that
reflects the patient's own characteristics, and better solves the
above-mentioned clinical predictability problem.[2]
Reference:
[1]. Liu, Y., Wu, W., Cai, C. et al. Patient-derived xenograft models in cancer therapy: technologies and applications. Sig Transduct Target Ther 8, 160 (2023). https://doi .org/10.1038/s41392-023-01419-2
[2]. Hu Binquan, Chen Chengming, Zhang Tongdi, Li Tian, Shi Changhong. The advantages and disadvantages of human tumor PDX transplantation models[J]. Experimental Animal Science, 2015,32(05):59-62.
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