Antitumor effect of FP3 in a patient-derived tumor tissue xenograft model of gastric carcinoma through an antiangiogenic mechanism

Patient-derived xenograft models for gastrointestinal tumors: A single-center retrospective study

BACKGROUND

Patient-derived xenograft (PDX) models have shown a great efficiency in preclinical and translational applications. Gastrointestinal (GI) tumors have a strong heterogeneity, and the engraftment rate of PDX models remarkably vary. However, the clinicopathological and molecular characteristics affecting the engraftment rate still remain elusive.

METHODS

A total of 312 fresh tumor tissue samples from patients with GI cancer were implanted into immunodeficient mice. The median follow-up time of patients was 37 months. Patients' characteristics were compared in terms of PDX growth and overall survival. PDX models of 3-6 generations were used for drug evaluation.

RESULTS

In total, 171 (54.8%, 171/312) PDX models were established, including 85 PDX models of colorectal cancer, 21 PDX models of esophageal cancer, and 65 PDX models of gastric cancer. Other than tumor site, histology, differentiation degree, and serum alpha-fetoprotein (AFP) level, no significant differences were found between transplantation of xenografts and patients' characteristics. For patients who had undergone neoadjuvant therapy, the incidence of tumor formation was higher in those with progressive disease (PD) or stable disease (SD). In gastric cancer, the results showed a higher transplantation rate in deficient mismatch repair (dMMR) tumors, and Ki-67 could be an important factor affecting the engraftment rate. The gene mutation status of RAS and BRAF, two important molecular markers in colorectal cancer, showed a high degree of consistency between patients' tumors and PDXs. However, no significant effects of these two mutations on PDX engraftment rate were observed. More importantly, in this study although KRAS mutations were detected in two clinical cases, evident tumor inhibition was still observed after cetuximab treatment in both PDX models and patients.

CONCLUSION

A large-scale PDX model including 171 cases was successfully established for GI tumors in our center. The relationship between clinicopathological and molecular features and engraftment rates were clarified. Furthermore, this resource provides us with profound insights into tumor heterogeneity, making these models valuable for PDX-guided treatment decisions, and offering the PDX model as a great tool for personalized treatment and translation research.

Patient-Derived Xenograft: A More Standard "Avatar" Model in Preclinical Studies of Gastric Cancer

Despite advances in diagnosis and treatment, gastric cancer remains the third most common cause of cancer-related death in humans. The establishment of relevant animal models of gastric cancer is critical for further research. Due to the complexity of the tumor microenvironment and the genetic heterogeneity of gastric cancer, the commonly used preclinical animal models fail to adequately represent clinically relevant models of gastric cancer. However, patient-derived models are able to replicate as much of the original inter-tumoral and intra-tumoral heterogeneity of gastric cancer as possible, reflecting the cellular interactions of the tumor microenvironment. In addition to implanting patient tissues or primary cells into immunodeficient mouse hosts for culture, the advent of alternative hosts such as humanized mouse hosts, zebrafish hosts, and in vitro culture modalities has also facilitated the advancement of gastric cancer research. This review highlights the current status, characteristics, interfering factors, and applications of patient-derived models that have emerged as more valuable preclinical tools for studying the progression and metastasis of gastric cancer.

Current status and perspectives of patient-derived xenograft models in cancer research

Cancers remain a major public health problem worldwide, which still require profound research in both the basic and preclinical fields. Patient-derived xenograft (PDX) models are created when cancerous cells or tissues from patients' primary tumors are implanted into immunodeficient mice to simulate human tumor biology in vivo, which have been extensively used in cancer research. The routes of implantation appeared to affect the outcome of PDX research, and there has been increasing applications of patient-derived orthotopic xenograft (PDOX) models. In this review, we firstly summarize the methodology to establish PDX models and then go over recent application and function of PDX models in basic cancer research on the areas of cancer characterization, initiation, proliferation, metastasis, and tumor microenvironment and in preclinical explorations of anti-cancer targets, drugs, and therapeutic strategies and finally give our perspectives on the future prospects of PDX models.

Drug sensitivity testing platforms for gastric cancer diagnostics

Gastric cancer diagnostics has traditionally been histomorphological and primarily the domain of surgical pathologists. Although there is an increasing usage of molecular and genomic techniques for clinical diagnostics, there is an emerging field of personalised drug sensitivity testing. In this review, we describe the various personalised drug sensitivity testing platforms and discuss the challenges facing clinical adoption of these assays for gastric cancer.

Patient-Derived Gastric Carcinoma Xenograft Mouse Models Faithfully Represent Human Tumor Molecular Diversity

Patient-derived cancer xenografts (PDCX) generally represent more reliable models of human disease in which to evaluate a potential drugs preclinical efficacy. However to date, only a few patient-derived gastric cancer xenograft (PDGCX) models have been reported. In this study, we aimed to establish additional PDGCX models and to evaluate whether these models accurately reflected the histological and genetic diversities of the corresponding patient tumors. By engrafting fresh patient gastric cancer (GC) tissues into immune-compromised mice (SCID and/or nude mice), thirty two PDGCX models were established. Histological features were assessed by a qualified pathologist based on H&E staining. Genomic comparison was performed for several biomarkers including ERBB1, ERBB2, ERBB3, FGFR2, MET and PTEN. These biomarkers were profiled to assess gene copy number by fluorescent in situ hybridization (FISH) and/or protein expression by immunohistochemistry (IHC). All 32 PDGCX models retained the histological features of the corresponding human tumors. Furthermore, among the 32 models, 78% (25/32) highly expressed ERBB1 (EGFR), 22% (7/32) were ERBB2 (HER2) positive, 78% (25/32) showed ERBB3 (HER3) high expression, 66% (21/32) lost PTEN expression, 3% (1/32) harbored FGFR2 amplification, 41% (13/32) were positive for MET expression and 16% (5/32) were MET gene amplified. Between the PDGCX models and their parental tumors, a high degree of similarity was observed for FGFR2 and MET gene amplification, and also for ERBB2 status (agreement rate = 94~100%; kappa value = 0.81~1). Protein expression of PTEN and MET also showed moderate agreement (agreement rate = 78%; kappa value = 0.46~0.56), while ERBB1 and ERBB3 expression showed slight agreement (agreement rate = 59~75%; kappa value = 0.18~0.19). ERBB2 positivity, FGFR2 or MET gene amplification was all maintained until passage 12 in mice. The stability of the molecular profiles observed across subsequent passages within the individual models provides confidence in the utility and translational significance of these models for in vivo testing of personalized therapies.

Profile of conbercept in the treatment of neovascular age-related macular degeneration

In developed countries, age-related macular degeneration (AMD) is the leading cause of irreversible blindness in individuals over the age of 65 years. Vascular endothelial growth factor (VEGF) plays a vital role in the formation of neovascular AMD. VEGF regulates angiogenesis, enhances vascular permeability, and drives the formation of choroidal neovascularization. As a result of the introduction of anti-VEGF drugs, the incidence of blindness from neovascular AMD has greatly reduced. Anti-VEGF drugs are used as a first-line treatment for neovascular AMD. The most recent anti-VEGF drug is conbercept, also named KH902, which was approved for the treatment of neovascular AMD by the China Food and Drug Administration in December 2013. In this review, recent clinical information regarding the use of conbercept to treat neovascular AMD is summarized. Conbercept is a soluble receptor decoy that blocks all isoforms of VEGF-A, VEGF-B, VEGF-C, and PlGF, which has a high binding affinity to VEGF and a long half-life in vitreous. Preclinical studies have demonstrated its anti-angiogenesis activity in both ocular neovascular disease models and tumor models. Clinical trials of conbercept have shown its superior efficacy and safety. Patients respond well even with 3-month treatment intervals following loading doses once a month for 3 months. The potential therapeutic effect of conbercept on the treatment of polypoidal choroidal vasculopathy, a special type of neovascular AMD, is also promising. In summary, conbercept is a new treatment option for ophthalmologists and their patients and may help address the limitations of current anti-VEGF drugs.

One mouse, one patient paradigm: New avatars of personalized cancer therapy

Over the last few decades, study of cancer in mouse models has gained popularity. Sophisticated genetic manipulation technologies and commercialization of these murine systems have made it possible to generate mice to study human disease. Given the large socio-economic burden of cancer, both on academic research and the health care industry, there is a need for in vivo animal cancer models that can provide a rationale that is translatable to the clinic. Such a bench-to-bedside transition will facilitate a long term robust strategy that is economically feasible and clinically effective to manage cancer. The major hurdles in considering mouse models as a translational platform are the lack of tumor heterogeneity and genetic diversity, which are a hallmark of human cancers. The present review, while critical of these pitfalls, discusses two newly emerging concepts of personalized mouse models called "Mouse Avatars" and Co-clinical Trials. Development of "Mouse Avatars" entails implantation of patient tumor samples in mice for subsequent use in drug efficacy studies. These avatars allow for each patient to have their own tumor growing in an in vivo system, thereby allowing the identification of a personalized therapeutic regimen, eliminating the cost and toxicity associated with non-targeted chemotherapeutic measures. In Co-clinical Trials, genetically engineered mouse models (GEMMs) are used to guide therapy in an ongoing human patient trial. Murine and patient trials are conducted concurrently, and information obtained from the murine system is applied towards future clinical management of the patient's tumor. The concurrent trials allow for a real-time integration of the murine and human tumor data. In combination with several molecular profiling techniques, the "Mouse Avatar" and Co-clinical Trial concepts have the potential to revolutionize the drug development and health care process. The present review outlines the current status, challenges and the future potential of these two new in vivo approaches in the field of personalized oncology.