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Hernandez, T.; Baños, N.; Del Puerto Nevado, L.; Mahíllo-Fernández, I.; Doger De-Speville, B.; Calvo, E.; Wick, M.; Garcia-Foncillas, J.; Moreno, V. Patient-Derived Xenografts. Encyclopedia. Available online: https://encyclopedia.pub/entry/52282 (accessed on 18 June 2024).
Hernandez T, Baños N, Del Puerto Nevado L, Mahíllo-Fernández I, Doger De-Speville B, Calvo E, et al. Patient-Derived Xenografts. Encyclopedia. Available at: https://encyclopedia.pub/entry/52282. Accessed June 18, 2024.
Hernandez, Tatiana, Natalia Baños, Laura Del Puerto Nevado, Ignacio Mahíllo-Fernández, Bernard Doger De-Speville, Emiliano Calvo, Michael Wick, Jesus Garcia-Foncillas, Victor Moreno. "Patient-Derived Xenografts" Encyclopedia, https://encyclopedia.pub/entry/52282 (accessed June 18, 2024).
Hernandez, T., Baños, N., Del Puerto Nevado, L., Mahíllo-Fernández, I., Doger De-Speville, B., Calvo, E., Wick, M., Garcia-Foncillas, J., & Moreno, V. (2023, December 03). Patient-Derived Xenografts. In Encyclopedia. https://encyclopedia.pub/entry/52282
Hernandez, Tatiana, et al. "Patient-Derived Xenografts." Encyclopedia. Web. 03 December, 2023.
Patient-Derived Xenografts
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Patient-derived xenografts (PDXs) have defined the field of translational cancer research, becoming one of the most-used tools in early drug development. The process of establishing cancer models in mice has turned out to be challenging, since little research focuses on evaluating which factors impact engraftment success. 

patient-derived xenografts PDX mice models engraftment

1. Introduction

The use of preclinical models is a core component of translational research in oncology. As one of the first steps in cancer research, it provides the background biological knowledge required for successful drug development and clinical trial designs. Despite the revolution that cancer cell line development has brought for cancer discoveries, it is still challenging to translate the preclinical data into clinical results, and the rate of failure in drug development remains very high [1]. There are several limitations to using conventional cell lines in research, negatively influencing their predictive value regarding activity in cancer types in clinical trials: the diversity of solid tumors with respect to molecular profile and sensitivity to specific drugs; the interpatient variability in drug exposure, difficult to predict from preclinical studies; and the highly variable tumor cell doubling time across different tumor types and within a single tumor. Intratumor heterogeneity is a key factor hampering the utility of in vitro preclinical models. In this setting, there is supportive evidence showing the significant genetic variations existing between a primary tumor and the cell lines deriving from that tumor [2][3], a problem that could be surpassed with the development of patient-derived tumor xenograft models (PDTX or PDX). The models have proven to better predict final clinical responses of cytotoxic drugs [4], leading to an increase in the establishment of disease-specific panels of patient-derived xenografts worldwide [5].
In 1983, Bosma et al. reported the severe combined immunodeficiency (SCID) mutant CB17 mice [6] lacking immune T cells, which made them attractive for human tumor engraftments [7][8]. Further crossing of SCID mice with the non-obese diabetic (NOD) strain led to the development of NOD-SCID mice [9], which lack both T- and B-lymphocytes. Many groups have used NOD-SCID mice for PDX model establishment, with it becoming one of the most used tools for this purpose [10][11][12]. This idea was further developed by the National Cancer Institute in the United States [13], and has since been translated into laboratories worldwide.
In the development of PDXs, many protocols have been proposed from different research groups [13][14]. Researchers have studied and found their own ways to improve PDX engraftment success rate [2][15][16]. The usual protocol implies that pieces of solid tumors are collected from tumor tissues obtained from patients either by surgery or biopsy. These pieces are implanted subcutaneously in mice (subcutaneous transplantation), in the same organ as the original tumors in the patients (orthotopic transplantation), or in the renal capsule in the recipient mouse. Subcutaneous transplantation is not only easier to implant, but also easier to follow for engraftment success [3][4][17].
Several studies have tried to determine predictive factors for engraftment success. Reported success has ranged between 23% and 75%, depending mostly on the tumor type and proliferation rate [18][19][20][21][22][23]. Overall, colorectal (64–89%) and pancreatic (62%) tumors have had high engraftment rates, but low-proliferation tumors such as receptor-positive breast cancers [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] and neuroendocrine low-grade tumors have shown low success rates, even in the laboratories considered most successful in PDX engraftment in general [24]. Likewise, aggressive and advanced (metastatic) cancers have shown high PDX model success rates compared to less-aggressive and nonmetastatic cancers [18][25][26][27].

2. Patient-Derived Xenografts

Amongst the factors so far correlated to a higher engraftment PDX rate, the following are included:

2.1. Tumor Stage

Chen Y et al. [28][29][30] found different tumor stages play a vital role in engraftment rate, which can roughly reflect tumor burden In non-small-cell lung cancer (NSCLC), tumor samples from patients with stage II (43/96, 45%) and stage III (25/49, 51%) disease seem to have higher engraftment rates than those from stage I disease (32/145, 22%) [15]. Oh et al. evaluated similar parameters, and concluded tumors arising from advanced diseases would grow better in xenografts, specifically in colorectal cancer. Their results showed xenograft uptake in 4 of 15 (26.7%) stage I tumors, in 41 of 72 (56.9%) stage II tumors, in 50 of 84 (59.5%) stage III tumors, and in 55 of 70 (78.6%) stage IV tumors, with a clear higher uptake rate in more advanced disease [31][32]. Similarly, Jung et al. found that patients’ primary tumor size is a significant factor of the success of PDX models in pancreatic cancer [32][33]. Weroha et al.’s results were also consistent, confirming that tumor stage, tumor grade and presence of ascites correlated with better engraftment rates in ovarian cancer models [34][35]. When it comes to scientific research, choosing samples with high tumor stage may be helpful to establish PDX models.

2.2. Sample Origin: Metastases

Researchers have shown metastatic cancers exhibit higher PDX model engraftment rates compared to non-metastatic cancers [36][37][38]. Masanori and colleagues generated a PDX model of human brain metastases of breast cancer in the mouse brain [39]. This method had no perioperative mortality and a 100% (10/10) engraftment rate. In colon cancer PDX research, 100% (8/8) engraftment rate was achieved with samples coming from metastases compared with the 84% (27/32) engraftment rate with primary cancer [39][40]. These data suggest that the capability of tumors to grow serially in mice could be associated with their capability to metastasize and seed distant sites, but no real comparative studies have been performed, and samples are still very small for drawing conclusions [30]

2.3. Tumor Type and Subtype

Among various tumors in different studies, breast cancer seems to have the relatively lowest success rate of PDX engraftment, ranging from 21% to 37% [29][30][32][35][39][40][41][42][43]. Since breast cancer is a hormone-dependent disease, hormonal receptor status determines the treatment regimen. Moreover, immunodeficient mice cannot provide the hormones needed for tumor growth after transplantation tissue is engrafted from the human body to mice, which leads to the difficulty in establishing breast cancer PDX models [35]. Thus, transplantation rate for triple-negative breast cancer is relatively higher than other breast cancer types. For example, in triple-negative breast cancer, engraftment has resulted to be significantly higher than HER2 positive and luminal cancers, in line with tumor grade and hormonal environment influencing final engraftment rates [18][26][39][41]. Moreover, the stable take rate of ER-negative (52%) and PR-negative (37%) tumors was noticeably higher than that of ER-positive (2%) and PR-positive (3%) tumors [18][26][40]. On the other hand, colorectal cancer, pancreatic cancer, head and neck cancer and ovarian cancer show acceptable engraftment rates in immunodeficient mice, regardless of subtypes [18][29][32][35][42][44][45]. A large study by Echeverria et al. [18], in which 269 tumor samples were obtained from patients diagnosed with triple-negative breast cancer (TNBC) participating in the ARTEMIS trial, achieved success in establishing 62 models, for an overall intake of 23%. They did not find association between prior therapies and engraftment success [18]. The multivariate analysis for several clinical characteristics demonstrated that lymph node status at diagnosis (all samples were from local or locally advanced disease) did correlate with a higher engraftment rate. Ki67 protein-expression positivity was also correlated with higher success rate, with both results considered statistically significant (p = 0.020 and p = 0.032, respectively). Other markers such histology, subtype, androgen receptors, ethnicity, race or age were not correlated. Interestingly, and in line with previous findings, tumor tissue samples collected from 308 patients who were diagnosed with non-small-cell lung cancer (NSCLC) which were implanted into immunodeficient mice revealed that squamous cell carcinomas had a higher engraftment rate compared with adenocarcinomas [44]. In GBM, in a study by Sloan et al. [45][46], 69 samples from patients with glioblastoma multiforme were collected for PDX generation, achieving successful engraftment in 37 implanted samples in mice. Interestingly, tumor growth rate was measured between passages, and confirmed to be progressively higher, with 11 samples (15.9%) reaching 40% or more increase in tumor growth rate between the first and third passages [47].

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