Background: patient-derived xenografts (PDXs) have defined the field of translational cancer research in recent years, 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. We sought to determine the clinical, pathological, or molecular factors which may predict better engraftment rates in PDXs.Methods: between March 2017 and January 2021, tumor samples obtained from patients with primary or metastatic cancer were implanted into athymic nude mice. A full comprehensive evaluation of baseline factors associated with the patients and patients’ tumors was performed, with the goal of potentially identifying predictive markers of engraftment. We focused on clinical (patient factors) pathological (patients’ tumor samples) and molecular (patients’ tumor samples) characteristics, analyzed either by immunohistochemistry (IHC) or next-generation sequencing (NGS), which were associated with the likelihood of final engraftment, as well as with tumor growth rates in xenografts.Results: a total of 585 tumor samples were collected and implanted. Twenty-one failed to engraft, due to lack of malignant cells. Of 564 tumor-positive samples, 187 (33.2%) grew at time of analysis. The study was able to find correlation and predictive value for engraftment for the following: the use of systemic antibiotics by the patient within 2 weeks of sampling (38.1% (72/189) antibiotics- group vs. 30.7% (115/375) no-antibiotics) (p= 0.048), and the administration of systemic steroids to the patients within 2 weeks of sampling (41.5% (34/48) steroids vs. 31.7% (153/329), no-steroids) (p= 0.049). Regarding patient’s baseline tests, we found certain markers could help predict final engraftment success: for lactate dehydrogenase (LDH) levels, 34.1% (140/411) of tumors derived from patients with baseline blood LDH levels above the upper limit of normality (ULN) achieved growth, against 30.7% (47/153) with normal LDH (p= 0.047). Histological tumor characteristics, such as grade of differentiation, were also correlated. Grade 1: 25.4% (47/187), grade 2: 34.8% (65/187) and grade 3: 40.1% (75/187) tumors achieved successful growth (p= 0.043), suggesting the higher the grade, the higher the likelihood of success. Similarly, higher ki67 levels were also correlated with better engraftment rates: low (Ki67 < 15%): 8.9% (9/45) achieved growth vs. high (Ki67 ≥ 15%): 31% (35/113) (p: 0.002). Other markers of aggressiveness such as the presence of lymphovascular invasion in tumor sample of origin was also predictive: 42.2% (97/230) with lymphovascular vs. 26.9% (90/334) of samples with no invasion (p= 0.0001). From the molecular standpoint, mismatch-repair-deficient (MMRd) tumors showed better engraftment rates: 62.1% (18/29) achieved growth vs. 40.8% (75/184) of proficient tumors (p= 0.026). A total of 84 PDX were breast models, among which 57.9% (11/19) ER-negative models grew, vs. 15.4% (10/65) of ER-positive models (p= 0.0001), also consonant with ER-negative tumors being more aggressive. BRAFmut cancers are more likely to achieve engraftment during the development of PDX models. Lastly, tumor growth rates during first passages can help establish a cutoff point for the decision-making process during PDX development, since the higher the tumor grades, the higher the likelihood of success.Conclusions: tumors with higher grade and Ki67 protein expression, lymphovascular and/or perineural invasion, with dMMR and are negative for ER expression have a higher probability of achieving growth in the process of PDX development. The use of steroids and/or antibiotics in the patient prior to sampling can also impact the likelihood of success in PDX development. Lastly, establishing a cutoff point for tumor growth rates could guide the decision-making process during PDX development.
背景：近年来，患者来源异种移植模型（PDX）已成为转化癌症研究领域的重要工具，在早期药物开发中应用广泛。然而，由于鲜有研究关注影响移植成功率的因素，在小鼠体内建立癌症模型的过程仍具挑战性。本研究旨在确定可能预测PDX模型更高移植成功率的临床、病理或分子因素。 方法：2017年3月至2021年1月期间，将从原发或转移性癌症患者获取的肿瘤样本植入胸腺缺陷裸鼠体内。我们对患者及其肿瘤样本的基线因素进行全面评估，以期识别潜在的移植预测标志物。研究聚焦于临床（患者因素）、病理（患者肿瘤样本）及分子（患者肿瘤样本）特征，通过免疫组化（IHC）或二代测序（NGS）进行分析，探究这些特征与最终移植成功率及异种移植瘤生长速率的关系。 结果：共收集并植入585个肿瘤样本。其中21个因缺乏恶性细胞未能成功移植。在564个肿瘤阳性样本中，187个（33.2%）在分析时成功生长。研究发现以下因素与移植成功率具有相关性及预测价值：患者在采样前2周内使用全身性抗生素（用药组38.1%（72/189） vs 未用药组30.7%（115/375），p=0.048）；患者在采样前2周内使用全身性类固醇（用药组41.5%（34/48） vs 未用药组31.7%（153/329），p=0.049）。在患者基线检测指标中，某些标志物可预测最终移植成功率：对于乳酸脱氢酶（LDH）水平，基线血LDH高于正常值上限（ULN）的患者肿瘤生长成功率为34.1%（140/411），而LDH正常者为30.7%（47/153）（p=0.047）。肿瘤组织学特征如分化程度亦存在相关性：1级肿瘤生长成功率25.4%（47/187），2级34.8%（65/187），3级40.1%（75/187）（p=0.043），提示分级越高成功率越高。类似地，较高Ki67水平与更好移植率相关：低表达（Ki67<15%）生长成功率8.9%（9/45） vs 高表达（Ki67≥15%）31%（35/113）（p=0.002）。其他侵袭性标志物如原发肿瘤样本存在淋巴血管浸润也具有预测性：有浸润样本成功率42.2%（97/230） vs 无浸润样本26.9%（90/334）（p=0.0001）。从分子角度，错配修复缺陷（MMRd）肿瘤显示更高移植率：62.1%（18/29）成功生长 vs 修复正常肿瘤40.8%（75/184）（p=0.026）。在84个乳腺癌PDX模型中，57.9%（11/19）ER阴性模型成功生长，而ER阳性模型仅15.4%（10/65）（p=0.0001），这与ER阴性肿瘤更具侵袭性的特性相符。BRAF突变癌症在PDX模型建立过程中更易成功移植。最后，早期传代阶段的肿瘤生长速率有助于建立PDX开发过程中的决策截断值，因为肿瘤分级越高，成功可能性越大。 结论：在PDX模型建立过程中，具有较高分级和Ki67蛋白表达、存在淋巴血管和/或神经周围浸润、错配修复缺陷且ER表达阴性的肿瘤更可能成功生长。患者采样前使用类固醇和/或抗生素也会影响PDX建立的成功率。此外，建立肿瘤生长速率的截断值可指导PDX开发过程中的决策制定。
肿瘤(癌症)患者之家