The ongoing trends of patient‐derived xenograft models in oncology

Abstract

The ongoing trends of patient-derived xenograft models in oncology 1 MAIN TEXT Patient-derived xenograft (PDX) models have garnered increasing attention since the last decade. These models are typically characterized by the implantation of fresh patient-derived tumor tissues into immunodeficient mice. PDX models are well recognized in academic laboratories, pharmaceutical institutions, and specialized commercial organizations as having the ability to recapitulate genomics, transcriptomics, proteomics, and metabolomics of the parental tumor tissue [1,2]. Recently, these models have been successfully used in preclinical studies to identify potential biomarkers for drug response and resistance, and to measure tumor evolution in response to treatment [3,4]. Favorable outcomes demonstrated using PDX models could be used as ideal models for preclinical research and clinical translation studies. At present, the concept of co-clinical trial, the simultaneous use of the so-called Avatar models, has attracted growing attention and has been expanded to include PDX models. These Avatar models are generated from patients enrolled in clinical trials and are simultaneously treated with the same anticancer therapies as the patients [5]. Several retrospective studies have shown that responses of PDX models toward certain agents were strongly correlated to the clinical response seen in the patients [6]. Moreover, Avatar models have been involved in 15 clinical trials covering different tumor settings, including prostate cancer, breast cancer, lung cancer, colorectal cancer, sarcoma, head and neck carcinoma, ovarian cancer, and pancreatic cancer (https://ClinicalTrials.gov). Some prospective studies were also performed using PDX models to guide clinical treatment decisions in a small number of patients and demonstrated prolonged survival [7,8]. Stebbing's et al. [8] showed that 20.1% (6/29) of their investigated patients with advanced sarcoma obtained direct clinical benefits from PDX-guided therapy. Bousquet et al. [9] suggested that Abbreviations: CNAs, copy number alterations; PDX, patient-derived xenograft; PDX-MI, PDX model minimal information standard This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Assessing the performance of different outcomes for tumor growth studies with animal models

“…This is similarly reflected in the results of Oberg et al, who explored the use of linear mixed‐effects models with complex correlation structures in the context of ovarian cancer PDX studies 20 . Additional work has examined the need for unified frameworks of PDX studies and their evaluation to better ensure replicability and optimal use of study data 5,21,22 …”

Artificial tumor matrices and bioengineered tools for tumoroid generation

“…The PDX models have highly similar histopathological and genetic characteristics to the maternal tumors. Studies have shown that, the drug sensitivity of the PDX model to anticancer drugs is highly correlated with the clinical treatment outcomes of cancer patients [11]. PDX models are still the most used models in the pharmaceutical industry and personalized medicine in the past few decades although they are time-consuming and cost-ineffective [12][13][14].…”