Genomic characterization of a large panel of patient-derived hepatocellular carcinoma xenograft tumor models for preclinical development

Preclinical Human and Murine Models of Hepatocellular Carcinoma (HCC)

Hepatocellular carcinoma (HCC) is the most frequent liver cancer, which account for more than 90 % of all liver cancer cases. It is the fifth leading cause of cancer globally and the second leading cause of cancer-related mortality in men. The availability of competent HCC preclinical models is fundamental to the success of mechanistic studies, molecular target identification, and drug testing. However, there are challenges associated with the use of these models. In this review, we provided updates on various cell lines, animals, and human HCC models, their specific preclinic use and associated potential challenges. Overall, the understanding of the merits and demerits of a particular HCC model will improve model selection for various preclinical studies.

Patient-Derived-Xenografts in Mice: A Preclinical Platform for Cancer Research

The use of patient-derived xenografts (PDXs) has dramatically improved drug development programs. PDXs (1) reproduce the pathological features and the genomic profile of the parental tumors more precisely than other preclinical models, and (2) more faithfully predict therapy response. However, PDXs have limitations. These include the inability to completely capture tumor heterogeneity and the role of the immune system, the low engraftment efficiency of certain tumor types, and the consequences of the human-host interactions. Recently, the use of novel mouse strains and specialized engraftment techniques has enabled the generation of "humanized" PDXs, partially overcoming such limitations. Importantly, establishing, characterizing, and maintaining PDXs is costly and requires a significant regulatory, administrative, clinical, and laboratory infrastructure. In this review, we will retrace the historical milestones that led to the implementation of PDXs for cancer research, review the most recent innovations in the field, and discuss future avenues to tackle deficiencies that still exist.

The Power and Promise of Patient-Derived Xenografts of Human Breast Cancer

In 2016, a group of researchers engaged in the development of patient-derived xenografts (PDXs) of human breast cancer provided a comprehensive review of the state of the field. In that review, they summarized the clinical problem that PDXs might address, the technical approaches to their generation (including a discussion of host animals and transplant conditions tested), and presented transplantation success (take) rates across groups and across transplantation conditions. At the time, there were just over 500 unique PDX models created by these investigators representing all three clinically defined subtypes (ER+, HER2+, and TNBC). Today, many of these PDX resources have at least doubled in size, and several more PDX development groups now exist, such that there may be well upward of 1000 PDX models of human breast cancer in existence worldwide. They also presented a series of open questions for the field. Many of these questions have been addressed. However, several remain open, or only partially addressed. Herein, we revisit these questions, and recount the progress that has been made in a number of areas with respect to generation, characterization, and use of PDXs in translational research, and re-present questions that remain open. These open questions, and others, are now being addressed not only by individual investigators, but also large, well-funded consortia including the PDXNet program of the National Cancer Institute in the United States, and the EuroPDX Consortium, an organization of PDX developers across Europe. Finally, we discuss the new opportunities in PDX-based research.

The importance of preclinical models in cholangiocarcinoma

Cholangiocarcinoma (CCA) is an adenocarcinoma of the hepatobiliary system with a grim prognosis. Incidence is rising globally and surgery is currently the only curative treatment, but is only available for patients who are fit and diagnosed in an early-stage of disease progression. Great importance has been placed on developing preclinical models to help further our understanding of CCA and potential treatments to improve therapeutic outcomes. Preclinical models of varying complexity and cost have been established, ranging from more simplistic in vitro 2D CCA cell lines in culture, to more complex in vivo genetically engineered mouse models. Currently there is no single model that faithfully recaptures the complexities of human CCA and the in vivo tumour microenvironment. Instead a multi-model approach should be used when designing preclinical trials to study CCA and potential therapies.

Hepatocellular Carcinoma: Old and Emerging Therapeutic Targets

Liver cancer, predominantly hepatocellular carcinoma (HCC), globally ranks sixth in incidence and third in cancer-related deaths. HCC risk factors include non-viral hepatitis, alcohol abuse, environmental exposures, and genetic factors. No specific genetic alterations are unequivocally linked to HCC tumorigenesis. Current standard therapies include surgical options, systemic chemotherapy, and kinase inhibitors, like sorafenib and regorafenib. Immunotherapy, targeting immune checkpoints, represents a promising avenue. FDA-approved checkpoint inhibitors, such as atezolizumab and pembrolizumab, show efficacy, and combination therapies enhance clinical responses. Despite this, the treatment of hepatocellular carcinoma (HCC) remains a challenge, as the complex tumor ecosystem and the immunosuppressive microenvironment associated with it hamper the efficacy of the available therapeutic approaches. This review explores current and advanced approaches to treat HCC, considering both known and new potential targets, especially derived from proteomic analysis, which is today considered as the most promising approach. Exploring novel strategies, this review discusses antibody drug conjugates (ADCs), chimeric antigen receptor T-cell therapy (CAR-T), and engineered antibodies. It then reports a systematic analysis of the main ligand/receptor pairs and molecular pathways reported to be overexpressed in tumor cells, highlighting their potential and limitations. Finally, it discusses TGFβ, one of the most promising targets of the HCC microenvironment.

Advancements and application prospects of three-dimensional models for primary liver cancer: a comprehensive review

Primary liver cancer (PLC) is one of the most commonly diagnosed cancers worldwide and a leading cause of cancer-related deaths. However, traditional liver cancer models fail to replicate tumor heterogeneity and the tumor microenvironment, limiting the study and personalized treatment of liver cancer. To overcome these limitations, scientists have introduced three-dimensional (3D) culture models as an emerging research tool. These 3D models, utilizing biofabrication technologies such as 3D bioprinting and microfluidics, enable more accurate simulation of the in vivo tumor microenvironment, replicating cell morphology, tissue stiffness, and cell-cell interactions. Compared to traditional two-dimensional (2D) models, 3D culture models better mimic tumor heterogeneity, revealing differential sensitivity of tumor cell subpopulations to targeted therapies or immunotherapies. Additionally, these models can be used to assess the efficacy of potential treatments, providing guidance for personalized therapy. 3D liver cancer models hold significant value in tumor biology, understanding the mechanisms of disease progression, and drug screening. Researchers can gain deeper insights into the impact of the tumor microenvironment on tumor cells and their interactions with the surrounding milieu. Furthermore, these models allow for the evaluation of treatment responses, offering more accurate guidance for clinical interventions. In summary, 3D models provide a realistic and reliable tool for advancing PLC research. By simulating tumor heterogeneity and the microenvironment, these models contribute to a better understanding of the disease mechanisms and offer new strategies for personalized treatment. Therefore, 3D models hold promising prospects for future PLC research.

Identification of biomarkers, pathways, and therapeutic targets for EGFR-TKI resistance in NSCLC

This study aimed to map the hub genes and potential pathways that might be involved in the molecular pathogenesis of EGFR-TKI resistance in NSCLC. We performed bioinformatics analysis to identify differentially expressed genes, their function, gene interactions, and pathway analysis between EGFR-TKI-sensitive and EGFR-TKI-resistant patient-derived xenotransplantation samples based on Gene Expression Omnibus database. Survival analysis was performed via the GEPIA database (GEO). The relationship between the key gene ITGAM and the therapeutic candidates was retrieved from DGIdb. A total of 1,302 differentially expressed genes were identified based on GEO. The PPI network highlighted 10 potential hub genes. Only ITGAM was linked to poor DSF in NSCLC patients. A total of 10 drugs were predicted to be potential therapeutics for NSCLC with EGFR-TKI resistance. This study indicates the hub genes related to EGFR-TKI resistance in NSCLC through bioinformatics technologies which can improve the understanding of the mechanisms of EGFR-TKI resistance and provide novel insights into therapeutics.

Recent Advancement in Breast Cancer Research: Insights from Model Organisms-Mouse Models to Zebrafish

Animal models have been utilized for decades to investigate the causes of human diseases and provide platforms for testing novel therapies. Indeed, breakthrough advances in genetically engineered mouse (GEM) models and xenograft transplantation technologies have dramatically benefited in elucidating the mechanisms underlying the pathogenesis of multiple diseases, including cancer. The currently available GEM models have been employed to assess specific genetic changes that underlay many features of carcinogenesis, including variations in tumor cell proliferation, apoptosis, invasion, metastasis, angiogenesis, and drug resistance. In addition, mice models render it easier to locate tumor biomarkers for the recognition, prognosis, and surveillance of cancer progression and recurrence. Furthermore, the patient-derived xenograft (PDX) model, which involves the direct surgical transfer of fresh human tumor samples to immunodeficient mice, has contributed significantly to advancing the field of drug discovery and therapeutics. Here, we provide a synopsis of mouse and zebrafish models used in cancer research as well as an interdisciplinary 'Team Medicine' approach that has not only accelerated our understanding of varied aspects of carcinogenesis but has also been instrumental in developing novel therapeutic strategies.

Patient-derived models facilitate precision medicine in liver cancer by remodeling cell-matrix interaction

Liver cancer is an aggressive tumor originating in the liver with a dismal prognosis. Current evidence suggests that liver cancer is the fifth most prevalent cancer worldwide and the second most deadly type of malignancy. Tumor heterogeneity accounts for the differences in drug responses among patients, emphasizing the importance of precision medicine. Patient-derived models of cancer are widely used preclinical models to study precision medicine since they preserve tumor heterogeneity ex vivo in the study of many cancers. Patient-derived models preserving cell-cell and cell-matrix interactions better recapitulate in vivo conditions, including patient-derived xenografts (PDXs), induced pluripotent stem cells (iPSCs), precision-cut liver slices (PCLSs), patient-derived organoids (PDOs), and patient-derived tumor spheroids (PDTSs). In this review, we provide a comprehensive overview of the different modalities used to establish preclinical models for precision medicine in liver cancer.

A PDX model combined with CD-DST assay to evaluate the antitumor properties of KRpep-2d and oxaliplatin in KRAS (G12D) mutant colorectal cancer

Patient-derived xenograft (PDX) models are more faithful in maintaining the characteristics of human tumors than cell lines and are widely used in drug development, although they have some disadvantages, including their relative low success rate, long turn-around time, and high costs. The collagen gel droplet embedded culture drug sensitivity test (CD-DST) has been used as an in-vitro drug sensitivity test for patients with cancer because of its high success rate of primary cell culture, high sensitivity, and good clinical relevance, but it is based on an in-vitro cell culture and may not simulate the tumor microenvironment accurately. This study aims to combine a PDX model with CD-DST to evaluate the efficiency of antitumor agents. KRpep-2d, a small peptide targeting KRAS (G12D), and oxaliplatin were used to verify the feasibility of this approach. Whole-exome sequencing and Sanger sequencing were first applied to test and validate the KRAS mutation status of a panel of colorectal cancer PDX tissues. One PDX model was verified to carry KRAS (G12D) mutation and was used for in-vivo and the CD-DST drug tests. We then established the PDX mouse model from the patient with the KRAS (G12D) mutation and obtained viable cancer cells derived from the same PDX model. Next, the antitumor abilities of KRpep-2d and oxaliplatin were estimated in the PDX model and the CD-DST. We found that KRpep-2d showed no significant antitumor effect on the xenograft model or on cancer cells derived from the same PDX model. In contrast, oxaliplatin showed significant inhibitory effects in both tests. In conclusion, the PDX model in combination with the CD-DST assay is a comprehensive and feasible method of evaluating the antitumor properties of compounds and could be applied for new drug discovery.

Translation Potential and Challenges of In Vitro and Murine Models in Cancer Clinic

As one of the leading causes of death from disease, cancer continues to pose a serious threat to human health globally. Despite the development of novel therapeutic regimens and drugs, the long-term survival of cancer patients is still very low, especially for those whose diagnosis is not caught early enough. Meanwhile, our understanding of tumorigenesis is still limited. Suitable research models are essential tools for exploring cancer mechanisms and treatments. Herein we review and compare several widely used in vitro and in vivo murine cancer models, including syngeneic tumor models, genetically engineered mouse models (GEMM), cell line-derived xenografts (CDX), patient-derived xenografts (PDX), conditionally reprogrammed (CR) cells, organoids, and MiniPDX. We will summarize the methodology and feasibility of various models in terms of their advantages and limitations in the application prospects for drug discovery and development and precision medicine.

Patient-derived xenograft models in hepatopancreatobiliary cancer

Animal models are crucial tools for evaluating the biological progress of human cancers and for the preclinical investigation of anticancer drugs and cancer prevention. Various animals are widely used in hepatopancreatobiliary cancer research, and mouse models are the most popular. Generally, genetic tools, graft transplantation, and chemical and physical measures are adopted to generate sundry mouse models of hepatopancreatobiliary cancer. Graft transplantation is commonly used to study tumour progression. Over the past few decades, subcutaneous or orthotopic cell-derived tumour xenograft models (CDX models) have been developed to simulate distinct tumours in patients. However, two major limitations exist in CDX models. One model poorly simulates the microenvironment of tumours in humans, such as the vascular, lymphatic and immune environments. The other model loses genetic heterogeneity compared with the corresponding primary tumour. Increased efforts have focused on developing better models for hepatopancreatobiliary cancer research. Hepatopancreatobiliary cancer is considered a tumour with high molecular heterogeneity, making precision medicine challenging in cancer treatment. Developing a new animal model that can better mimic tumour tissue and more accurately predict the efficacy of anticancer treatments is urgent. For the past several years, the patient-derived xenograft model (PDX model) has emerged as a promising tool for translational research. It can retain the genetic and histological stability of their originating tumour at limited passages and shed light on precision cancer medicine. In this review, we summarize the methodology, advantages/disadvantages and applications of PDX models in hepatopancreatobiliary cancer research.

In Vivo and In Vitro Models of Hepatocellular Carcinoma: Current Strategies for Translational Modeling

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide and the third leading cause of cancer-related death globally. HCC is a complex multistep disease and usually emerges in the setting of chronic liver diseases. The molecular pathogenesis of HCC varies according to the etiology, mainly caused by chronic hepatitis B and C virus infections, chronic alcohol consumption, aflatoxin-contaminated food, and non-alcoholic fatty liver disease associated with metabolic syndrome or diabetes mellitus. The establishment of HCC models has become essential for both basic and translational research to improve our understanding of the pathophysiology and unravel new molecular drivers of this disease. The ideal model should recapitulate key events observed during hepatocarcinogenesis and HCC progression in view of establishing effective diagnostic and therapeutic strategies to be translated into clinical practice. Despite considerable efforts currently devoted to liver cancer research, only a few anti-HCC drugs are available, and patient prognosis and survival are still poor. The present paper provides a state-of-the-art overview of in vivo and in vitro models used for translational modeling of HCC with a specific focus on their key molecular hallmarks.

In vitro 3D liver tumor microenvironment models for immune cell therapy optimization

Despite diagnostic and therapeutic advances, liver cancer kills more than 18 million people every year worldwide, urging new strategies to model the disease and to improve the current therapeutic options. In vitro tumor models of human cancer continue to evolve, and they represent an important screening tool. However, there is a tremendous need to improve the physiological relevance and reliability of these in vitro models to fulfill today's research requirements for better understanding of cancer progression and treatment options at different stages of the disease. This review describes the hepatocellular carcinoma microenvironmental characteristics and illustrates the current immunotherapy strategy to fight the disease. Moreover, we present a recent collection of 2D and 3D in vitro liver cancer models and address the next generation of in vitro systems recapitulating the tumor microenvironment complexity in more detail.

Drug discovery oncology in a mouse: concepts, models and limitations

The utilization of suitable mouse models is a critical step in the drug discovery oncology workflow as their generation and use are important for target identification and validation as well as toxicity and efficacy assessments. Current murine models have been instrumental in furthering insights into the mode of action of drugs before transitioning into the clinic. Recent advancements in genome editing with the development of the CRISPR/Cas9 system and the possibility of applying such technology directly in vivo have expanded the toolkit of preclinical models available. In this review, a brief presentation of the current models used in drug discovery will be provided with a particular emphasis on the novel CRISPR/Cas9 models.

Molecular phenotypes reveal heterogeneous engraftments of patient-derived hepatocellular carcinoma xenografts

Objective

Patient-derived xenograft (PDX) models provide a promising preclinical platform for hepatocellular carcinoma (HCC). However, the molecular features associated with successful engraftment of PDX models have not been revealed.

Methods

HCC tumor samples from 76 patients were implanted in immunodeficient mice. The molecular expression was evaluated by immunohistochemistry. Patient and tumor characteristics as well as tumor molecular expressions were compared for PDX engraftment using the Chi-square test. The independent prediction parameters were identified by logistic regression analyses.

Results

The engraftment rate for PDX models from patients with HCC was 39.47% (30/76). Tumors from younger patients and patients with elevated preoperative alpha-fetoprotein level had higher engraftment rates. Tumors with poor differentiation and vascular invasion were related to engraftment success. The positive expression of CK19, CD133, glypican-3 (GPC3), and Ki67 in tumor samples was associated with engraftment success. Logistic regression analyses indicated that GPC3 and Ki67 were two of the strongest predictors of PDX engraftment. Tumors with GPC3/Ki67 phenotypes showed heterogeneous engraftment rates, with 71.9% in GPC3⁺/Ki67⁺ tumors, 30.8% in GPC3⁻/Ki67⁺ tumors, 15.0% in GPC3⁺/Ki67⁻ tumors, and 0 in GPC3⁻/Ki67⁻ tumors.

Conclusions

Successful engraftment of HCC PDXs was significantly related to molecular features. Tumors with the GPC3⁺/Ki67⁺ phenotype were the most likely to successfully establish HCC PDXs.

Patient-Derived Organoids of Cholangiocarcinoma

Cholangiocarcinoma (CC) is an aggressive malignancy with an inferior prognosis due to limited systemic treatment options. As preclinical models such as CC cell lines are extremely rare, this manuscript reports a protocol of cholangiocarcinoma patient-derived organoid culture as well as a protocol for the transition of 3D organoid lines to 2D cell lines. Tissue samples of non-cancer bile duct and cholangiocarcinoma were obtained during surgical resection. Organoid lines were generated following a standardized protocol. 2D cell lines were generated from established organoid lines following a novel protocol. Subcutaneous and orthotopic patient-derived xenografts were generated from CC organoid lines, histologically examined, and treated using standard CC protocols. Therapeutic responses of organoids and 2D cell lines were examined using standard CC agents. Next-generation exome and RNA sequencing was performed on primary tumors and CC organoid lines. Patient-derived organoids closely recapitulated the original features of the primary tumors on multiple levels. Treatment experiments demonstrated that patient-derived organoids of cholangiocarcinoma and organoid-derived xenografts can be used for the evaluation of novel treatments and may therefore be used in personalized oncology approaches. In summary, this study establishes cholangiocarcinoma organoids and organoid-derived cell lines, thus expanding translational research resources of cholangiocarcinoma.

Upregulation of lncRNA NIFK-AS1 in hepatocellular carcinoma by m6A methylation promotes disease progression and sorafenib resistance

Long non-coding RNAs (LncRNAs) have recently emerged as vital regulators in the development and progression of hepatocellular carcinoma (HCC), providing new opportunities as novel therapeutic targets. Here we identified the lncRNA NIFK-AS1 as being highly expressed in HCC tissues and cells and showed this up-regulation resulted from METTL3-dependent m⁶A methylation. Functionally, knockdown of NIFK-AS1 inhibited the proliferation, colony formation, migration, and invasion of HCC cells. Moreover, these effects were elicited though AKT1 and we uncovered a ceRNA network involving an NIFK-AS1/miR-637/AKT1 axis with downstream effects on HCC progression involving regulation of MMP-7 and MMP-9 expression. From the clinical perspective, we showed that knockdown of NIFK-AS1 sensitized HCC cells to sorafenib through the up-regulation of the drug transporters OATP1B1 and OATP1B3. Clinical investigations showed HCC patients with low NIFK-AS1 expression benefited from sorafenib therapy and this phenomenon was reproduced in patient-derived tumor xenograft models (PDX) comparing HCC with low and high expression of NIFK-AS1. Taken together, these results suggest an essential role for NIFK-AS1 in HCC progression and promote NIFK-AS1 as a new therapeutic target and predictor of sorafenib benefit in HCC patients.

Patient-Derived Xenograft Models for Intrahepatic Cholangiocarcinoma and Their Application in Guiding Personalized Medicine

Background

Intrahepatic cholangiocarcinoma (ICC) remains one of the most intractable malignancies. The development of effective drug treatments for ICC is seriously hampered by the lack of reliable tumor models. At present, patient derived xenograft (PDX) models prove to accurately reflect the genetic and biological diversity required to decipher tumor biology and therapeutic vulnerabilities. This study was designed to investigate the establishment and potential application of PDX models for guiding personalized medicine and identifying potential biomarker for lenvatinib resistance.

Methods

We generated PDX models from 89 patients with ICC and compared the morphological and molecular similarities of parental tumors and passaged PDXs. The clinicopathologic features affecting PDX engraftment and the prognostic significance of PDX engraftment were analyzed. Drug treatment responses were analyzed in IMF-138, IMF-114 PDX models and corresponding patients. Finally, lenvatinib treatment response was examined in PDX models and potential drug resistance mechanism was revealed.

Results

Forty-nine PDX models were established (take rate: 55.1%). Successful PDX engraftment was associated with negative HbsAg (P = 0.031), presence of mVI (P = 0.001), poorer tumor differentiation (P = 0.023), multiple tumor number (P = 0.003), presence of lymph node metastasis (P = 0.001), and later TNM stage (P = 0.039). Moreover, patients with tumor engraftment had significantly shorter time to recurrence (TTR) (P < 0.001) and worse overall survival (OS) (P < 0.001). Multivariate analysis indicated that PDX engraftment was an independent risk factor for shortened TTR (HR = 1.84; 95% CI, 1.05–3.23; P = 0.034) and OS (HR = 2.13; 95% CI, 1.11–4.11; P = 0.024). PDXs were histologically and genetically similar to their parental tumors. We also applied IMF-138 and IMF-114 PDX drug testing results to guide clinical treatment for patients with ICC and found similar treatment responses. PDX models also facilitated personalized medicine for patients with ICC based on drug screening results using whole exome sequencing data. Additionally, PDX models reflected the heterogeneous sensitivity to lenvatinib treatment and CDH1 might be vital to lenvatinib-resistance.

Conclusion

PDX models provide a powerful platform for preclinical drug discovery, and potentially facilitate the implementation of personalized medicine and improvement of survival of ICC cancer patient.

Advances of Fibroblast Growth Factor/Receptor Signaling Pathway in Hepatocellular Carcinoma and its Pharmacotherapeutic Targets

Hepatocellular carcinoma (HCC) is a type of primary liver cancer with poor prognosis, and its incidence and mortality rate are increasing worldwide. It is refractory to conventional chemotherapy and radiotherapy owing to its high tumor heterogeneity. Accumulated genetic alterations and aberrant cell signaling pathway have been characterized in HCC. The fibroblast growth factor (FGF) family and their receptors (FGFRs) are involved in diverse biological activities, including embryonic development, proliferation, differentiation, survival, angiogenesis, and migration, etc. Data mining results of The Cancer Genome Atlas demonstrate high levels of FGF and/or FGFR expression in HCC tumors compared with normal tissues. Moreover, substantial evidence indicates that the FGF/FGFR signaling axis plays an important role in various mechanisms that contribute to HCC development. At present, several inhibitors targeting FGF/FGFR, such as multikinase inhibitors, specific FGFR4 inhibitors, and FGF ligand traps, exhibit antitumor activity in preclinical or early development phases in HCC. In this review, we summarize the research progress regarding the molecular implications of FGF/FGFR-mediated signaling and the development of FGFR-targeted therapeutics in hepatocarcinogenesis.

Patient-derived non-small cell lung cancer xenograft mirrors complex tumor heterogeneity

Objective

Patient-derived xenograft (PDX) models have shown great promise in preclinical and translational applications, but their consistency with primary tumors in phenotypic, genetic, and pharmacodynamic heterogeneity has not been well-studied. This study aimed to establish a PDX repository for non-small cell lung cancer (NSCLC) and to further elucidate whether it could preserve the heterogeneity within and between tumors in patients.

Methods

A total of 75 surgically resected NSCLC specimens were implanted into immunodeficient NOD/SCID mice. Based on the successful establishment of the NSCLC PDX model, we compared the expressions of vimentin, Ki67, EGFR, and PD-L1 proteins between cancer tissues and PDX models using hematoxylin and eosin staining and immunohistochemical staining. In addition, we detected whole gene expression profiling between primary tumors and PDX generations. We also performed whole exome sequencing (WES) analysis in 17 first generation xenografts to further assess whether PDXs retained the patient heterogeneities. Finally, paclitaxel, cisplatin, doxorubicin, atezolizumab, afatininb, and AZD4547 were used to evaluate the responses of PDX models to the standard-of-care agents.

Results

A large collection of serially transplantable PDX models for NSCLC were successfully developed. The histology and pathological immunohistochemistry of PDX xenografts were consistent with the patients' tumor samples. WES and RNA-seq further confirmed that PDX accurately replicated the molecular heterogeneities of primary tumors. Similar to clinical patients, PDX models responded differentially to the standard-of-care treatment, including chemo-, targeted- and immuno-therapeutics.

Conclusions

Our established PDX models of NSCLC faithfully reproduced the molecular, histopathological, and therapeutic characteristics, as well as the corresponding tumor heterogeneities, which provides a clinically relevant platform for drug screening, biomarker discovery, and translational research.

m6A RNA methylation-mediated HNF3γ reduction renders hepatocellular carcinoma dedifferentiation and sorafenib resistance

Hepatocyte nuclear factor 3γ (HNF3γ) is a hepatocyte nuclear factor, but its role and clinical significance in hepatocellular carcinoma (HCC) remain unclear. Herein, we report that HNF3γ expression is downregulated in patient HCC and inversely correlated with HCC malignancy and patient survival. Moreover, our data suggested that the HNF3γ reduction in HCC could be mediated by METTL14-dependent m6A methylation of HNF3γ mRNA. HNF3γ expression was increased during hepatic differentiation and decreased in dedifferentiated HCC cells. Interestingly, HNF3γ delivery promoted differentiation of not only HCC cells but also liver CSCs, which led to suppression of HCC growth. Mechanistic analysis suggested an HNF3γ-centered regulatory network that includes essential liver differentiation-associated transcription factors and functional molecules, which could synergistically facilitate HCC cell differentiation. More importantly, enforced HNF3γ expression sensitized HCC cells to sorafenib-induced growth inhibition and cell apoptosis through transactivation of OATP1B1 and OATP1B3 expression, which are major membrane transporters for sorafenib uptake. Clinical investigation showed that patient-derived HCC xenografts with high HNF3γ expression exhibited a sorafenib response and patients with high HCC HNF3γ levels benefited from sorafenib therapy. Together, these results suggest that HNF3γ plays an essential role in HCC differentiation and may serve as a therapeutic target and predictor of sorafenib benefit in patients.

Predicting HCC Response to Multikinase Inhibitors With In Vivo Cirrhotic Mouse Model for Personalized Therapy

BACKGROUND & AIMS

Hepatocellular carcinoma (HCC) arises in a cirrhotic, pro-angiogenic microenvironment. Inhibiting angiogenesis is a key mode of action of multikinase inhibitors and current non-cirrhotic models are unable to predict treatment response. We present a novel mouse cirrhotic model of xenotransplant that predicts the natural biology of HCC and allows personalized therapy.

METHODS

Cirrhosis was induced in NOD Scid gamma mice with 4 months of thioacetamide administration. Patient derived xenografts (PDXs) were created by transplant of human HCC subcutaneously into non-cirrhotic mice and intra-hepatically into both cirrhotic and non-cirrhotic mice. The applicability of cirrhotic PDXs for drug testing was tested with 16 days of either sorafenib or lenvatinib. Treatment response was evaluated by MRI.

RESULTS

8 out of 19 (42%) human HCC engrafted in the cirrhotic model compared with only 3 out of 19 (16%) that engrafted in the subcutaneous non-cirrhotic model. Tumor vasculature was preserved in the cirrhotic model but was diminished in the non-cirrhotic models. Metastasis developed in 3 cirrhotic PDX lines and was associated with early HCC recurrence in all 3 corresponding patients (100%), compared with only 5 out of 16 (31%) of the other PDX lines, P = .027. The cirrhotic model was able to predict response and non-response to lenvatinib and sorafenib respectively in the corresponding patients. Response to lenvatinib in the cirrhotic PDX was associated with reduction in CD34, VEGFR2 and CLEC4G immunofluorescence area and intensity (all P ≤ .03).

CONCLUSIONS

A clinically relevant cirrhotic PDX model preserves tumor angiogenesis and allows prediction of response to multikinase inhibitors for personalized therapy.

Bevacizumab Augments the Antitumor Efficacy of Infigratinib in Hepatocellular Carcinoma

The fibroblast growth factor (FGF) signaling cascade is one of the key signaling pathways in hepatocellular carcinoma (HCC). FGF has been shown to augment vascular endothelial growth factor (VEGF)-mediated HCC development and angiogenesis, as well as to potentially lead to resistance to VEGF/VEGF receptor (VEGFR)-targeted agents. Thus, novel agents targeting FGF/FGF receptor (FGFR) signaling may enhance and/or overcome de novo or acquired resistance to VEGF-targeted agents in HCC. Mice bearing high- and low-FGFR tumors were treated with Infigratinib (i.e., a pan-FGFR kinase inhibitor) and/or Bevacizumab (i.e., an angiogenesis inhibitor). The antitumor activity of both agents was assessed individually or in combination. Tumor vasculature, intratumoral hypoxia, and downstream targets of FGFR signaling pathways were also investigated. Infigratinib, when combined with Bevacizumab, exerted a synergistic inhibitory effect on tumor growth, invasion, and lung metastasis, and it significantly improved the overall survival of mice bearing FGFR-dependent HCC. Infigratinib/Bevacizumab promoted apoptosis, inhibited cell proliferation concomitant with upregulation of p27, and reduction in the expression of FGFR2-4, p-FRS-2, p-ERK1/2, p-p70S6K/4EBP1, Cdc25C, survivin, p-Cdc2, and p-Rb. Combining Infigratinib/Bevacizumab may provide therapeutic benefits for a subpopulation of HCC patients with FGFR-dependent tumors. A high level of FGFR-2/3 may serve as a potential biomarker for patient selection to Infigratinib/Bevacizumab.

Uncovering Biological Factors That Regulate Hepatocellular Carcinoma Growth Using Patient-Derived Xenograft Assays

BACKGROUND AND AIMS

Several major factors limit our understanding of hepatocellular carcinoma (HCC). First, human HCCs are infrequently biopsied for diagnosis and thus are not often biologically interrogated. Second, HCC initiation and progression are strongly influenced by the cirrhotic microenvironment, and the exact contributions of intrinsic and extrinsic tumor factors are unclear. A powerful approach to examine the personalized biology of liver cancers and the influence of host tissues is with patient-derived xenograft (PDX) models. In Asia, HCCs from patients with hepatitis B virus have been efficiently converted into PDXs, but few parallel efforts from the west have been reported.

APPROACH AND RESULTS

In a large-scale analysis, we implanted 93 HCCs and 8 cholangiocarcinomas (CCAs) to systematically analyze host factors and to define an optimized platform for PDX development from both surgical and biopsy samples. NOD Scid IL-2Rγ^-/- (NSG) mice that had undergone partial hepatectomy (PHx) represented the best combination of engraftability, growth, and passageability, but overall rates were low and indicative of a unique intrinsic biology for HCCs in the United States. PDX models preserved the histology and genetic features of parental tumors, and ultimately, eight models were usable for preclinical studies. Intriguingly, HCC PDXs were differentially sensitive to regorafenib and sorafenib, and CCA PDXs were also highly sensitive to regorafenib.

CONCLUSIONS

PDX models functionalize early and advanced stage HCCs and revealed unique biological features of liver cancers from the United States.

iPSC-Derived Liver Organoids: A Journey from Drug Screening, to Disease Modeling, Arriving to Regenerative Medicine

Liver transplantation is the most common treatment for patients suffering from liver failure that is caused by congenital diseases, infectious agents, and environmental factors. Despite a high rate of patient survival following transplantation, organ availability remains the key limiting factor. As such, research has focused on the transplantation of different cell types that are capable of repopulating and restoring liver function. The best cellular mix capable of engrafting and proliferating over the long-term, as well as the optimal immunosuppression regimens, remain to be clearly well-defined. Hence, alternative strategies in the field of regenerative medicine have been explored. Since the discovery of induced pluripotent stem cells (iPSC) that have the potential of differentiating into a broad spectrum of cell types, many studies have reported the achievement of iPSCs differentiation into liver cells, such as hepatocytes, cholangiocytes, endothelial cells, and Kupffer cells. In parallel, an increasing interest in the study of self-assemble or matrix-guided three-dimensional (3D) organoids have paved the way for functional bioartificial livers. In this review, we will focus on the recent breakthroughs in the development of iPSCs-based liver organoids and the major drawbacks and challenges that need to be overcome for the development of future applications.

High FLT3 Levels May Predict Sorafenib Benefit in Hepatocellular Carcinoma

PURPOSE

To identify a predictive biomarker of sorafenib for hepatocellular carcinoma personalized therapy.

EXPERIMENTAL DESIGN

The patients treated with or without sorafenib after hepatocellular carcinoma recurrence from multicenters were matched with propensity score matching analysis. The expression levels of Fms-like tyrosine kinase 3 (FLT3) in hepatocellular carcinoma specimens of the matched patients (n = 276) were analyzed by IHC. The optimal cut-off point of FLT3 levels for overall survival (OS) was defined via Cutoff Finder. Subgroup analysis of OS was employed to investigate the association between FLT3 levels and sorafenib benefit. The predictive value was assessed via Cox regression models with an interaction term. Hepatocellular carcinoma and paratumoral normal tissues were used to investigate the expression and copy-number variation of FLT3. Patient-derived xenograft (PDX) models were used to confirm the association between FLT3 levels and sorafenib response.

RESULTS

Patients with FLT3-high hepatocellular carcinoma exhibited a superior OS upon sorafenib treatment. High FLT3 levels were predictive of sorafenib benefit in terms of OS (P _interaction = 0.00006). Copy-number losses and decreased expression of FLT3 in hepatocellular carcinoma were detected in about 64% of patients. Moreover, the PDXs derived from tumors with high FLT3 levels also displayed a better response to sorafenib.

CONCLUSIONS

Sorafenib may be able to delay tumor progression in patients with FLT3-high hepatocellular carcinoma. This potential biomarker needs to be further validated in independent cohorts prior to helping stratify patients for precision therapy in advanced hepatocellular carcinoma.

A poor prognosis in human hepatocellular carcinoma is associated with low expression of DPP4

This study aimed to explore the prognostic role of dipeptidyl peptidase 4 (DPP4) expression in hepatocellular carcinoma (HCC). DPP4 expression was measured in formalin-fixed paraffin-embedded specimens that were gathered from 327 HCC patients. Immunohistochemistry analyses were utilized to examine DPP4 expression characteristics and prognostic values (overall survival (OS) and time to recurrence) of DDP4 in HCC tissues. In addition, a patient-derived xenograft (PDX) model was used to assess the correlation between DPP4 expression and tumor growth in vivo. DPP4 was expressed in low levels in HCC tissues in contrast to paired peritumoral tissues (38 cases were down-regulated in a total of 59 cases, 64.4%. P=0.0202). DPP4 expression was significantly correlated with TNM stage (P=0.038), tumor number (P=0.035), and vascular invasion (P=0.024), and significantly reduced in patients who were in TNM stages II and III-V, with multiple tumors, and with microvascular invasion compared to patients with TNM stage I, single tumor, and no microvascular invasion. Notably, HCC tissues with low expression of DPP4 had poor OS (P=0.016) compared with HCC tissues with high expression of DPP4, and results from PDX model showed that tumor growth was significantly faster in HCC patients that lowly expressed DPP4 compared to those with highly expressed DPP4. Our findings suggested that low levels of DPP4 could impact the aggressiveness of HCC and contribute to a poor prognosis.

A Preliminary Study on the Establishment of the PDTX Model

Objective

The current study aims to explore the establishment of the patient-derived tumor xenograft (PDTX) model.

Materials and Methods

Twenty patients with gastric cancer, 10 males and 10 females, were enrolled in the current study. Firstly, the volume, invasion and metastasis of the xenografts were observed. Subsequently, the correlation between tumor tissues of the PDTX mouse model and the patients' primary tumor tissues was evaluated by pathological H&E staining and immunohistochemistry.

Results

The results showed that the PDTX models corresponding to 15 of the 20 patients were successfully established, and the success rate of PDTX model establishment was 75%. Furthermore, the PDTX models maintained the differentiation degree, morphological characteristics and structural characteristics of tumor cells.

Conclusion

A PDTX model can be used as a substitute for cancer patients in clinical practice and may be suitable for clinical pharmacodynamic screening and new drug development.

Advances in molecular classification and precision oncology in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) arises from hepatocytes through the sequential accumulation of multiple genomic and epigenomic alterations resulting from Darwinian selection. Genes from various signalling pathways such as telomere maintenance, Wnt/β-catenin, P53/cell cycle regulation, oxidative stress, epigenetic modifiers, AKT/mTOR and MAP kinase are frequently mutated in HCC. Several subclasses of HCC have been identified based on transcriptomic dysregulation and genetic alterations that are closely related to risk factors, pathological features and prognosis. Undoubtedly, integration of data obtained from both preclinical models and human studies can help to accelerate the identification of robust predictive biomarkers of response to targeted biotherapy and immunotherapy. The aim of this review is to describe the main advances in HCC in terms of molecular biology and to discuss how this knowledge could be used in clinical practice in the future.

Novel patient-derived preclinical models of liver cancer

Preclinical models of cancer based on the use of human cancer cell lines and mouse models have enabled discoveries that have been successfully translated into patients. And yet the majority of clinical trials fail, emphasising the urgent need to improve preclinical research to better interrogate the potential efficacy of each therapy and the patient population most likely to benefit. This is particularly important for liver malignancies, which lack highly efficient treatments and account for hundreds of thousands of deaths around the globe. Given the intricate network of genetic and environmental factors that contribute to liver cancer development and progression, the identification of new druggable targets will mainly depend on establishing preclinical models that mirror the complexity of features observed in patients. The development of new 3D cell culture systems, originating from cells/tissues isolated from patients, might create new opportunities for the generation of more specific and personalised therapies. However, these systems are unable to recapitulate the tumour microenvironment and interactions with the immune system, both proven to be critical influences on therapeutic outcomes. Patient-derived xenografts, in particular with humanised mouse models, more faithfully mimic the physiology of human liver cancer but are costly and time-consuming, which can be prohibitive for personalising therapies in the setting of an aggressive malignancy. In this review, we discuss the latest advances in the development of more accurate preclinical models to better understand liver cancer biology and identify paradigm-changing therapies, stressing the importance of a bi-directional communicative flow between clinicians and researchers to establish reliable model systems and determine how best to apply them to expanding our current knowledge.

Comparison of the molecular and cellular phenotypes of common mouse syngeneic models with human tumors

BACKGROUND

The clinical success of immune checkpoint inhibitors demonstrates that reactivation of the human immune system delivers durable responses for some patients and represents an exciting approach for cancer treatment. An important class of preclinical in vivo models for immuno-oncology is immunocompetent mice bearing mouse syngeneic tumors. To facilitate translation of preclinical studies into human, we characterized the genomic, transcriptomic, and protein expression of a panel of ten commonly used mouse tumor cell lines grown in vitro culture as well as in vivo tumors.

RESULTS

Our studies identified a number of genetic and cellular phenotypic differences that distinguish commonly used mouse syngeneic models in our study from human cancers. Only a fraction of the somatic single nucleotide variants (SNVs) in these common mouse cell lines directly match SNVs in human actionable cancer genes. Some models derived from epithelial tumors have a more mesenchymal phenotype with relatively low T-lymphocyte infiltration compared to the corresponding human cancers. CT26, a colon tumor model, had the highest immunogenicity and was the model most responsive to CTLA4 inhibitor treatment, by contrast to the relatively low immunogenicity and response rate to checkpoint inhibitor therapies in human colon cancers.

CONCLUSIONS

The relative immunogenicity of these ten syngeneic tumors does not resemble typical human tumors derived from the same tissue of origin. By characterizing the mouse syngeneic models and comparing with their human tumor counterparts, this study contributes to a framework that may help investigators select the model most relevant to study a particular immune-oncology mechanism, and may rationalize some of the challenges associated with translating preclinical findings to clinical studies.

Next-Generation Liver Medicine Using Organoid Models

"Liver medicine" refers to all diagnostic and treatment strategies of diseases and conditions that cause liver failure directly or indirectly. Despite significant advances in the field of liver medicine in recent years, improved tools are needed to efficiently define the pathophysiology of liver diseases and provide effective therapeutic options to patients. Recently, organoid technology has been established as the state-of-the-art cell culture tool for studying human biology in health and disease. In general, organoids are simplified three-dimensional (3D) mini-organ structures that can be grown in a 3D matrix where the structural and functional aspects of real organs are efficiently recapitulated. The generation of organoids is facilitated by exogenous factors that regulate multiple signaling pathways and promote the self-renewal, proliferation, and differentiation of the cells to promote spontaneous self-organization and tissue-specific organogenesis. Newly established protocols suggest that liver-specific organoids can be derived from either pluripotent stem cells or liver-specific stem/progenitor cells. Today, robust and long-term cultures of organoids with the closest physiology to in vivo liver, in terms of cellular composition and function, open a new era in studying and understanding the disease pathology as well as high-throughput drug screening. Of note, these next-generation cell culture systems have immense potential to be further improved by genome editing and bioengineering technologies to foster the development of patient-specific therapeutic options for clinical applications. Here, we will discuss recent advances and challenges in the generation of human liver organoids and highlight emerging concepts for their potential applications in liver medicine.

A reliable method to determine which candidate chemotherapeutic drugs effectively inhibit tumor growth in patient-derived xenografts (PDX) in single mouse trials

PURPOSE

We report on a statistical method for grouping anti-cancer drugs (GRAD) in single mouse trials (SMT). The method assigns candidate drugs into groups that inhibit or do not inhibit tumor growth in patient-derived xenografts (PDX). It determines the statistical significance of the group assignments without replicate trials of each drug.

METHODS

The GRAD method applies a longitudinal finite mixture model, implemented in the statistical package PROC TRAJ, to analyze a mixture of tumor growth curves for portions of the same tumor in different mice, each single mouse exposed to a different drug. Each drug is classified into an inhibitory or non-inhibitory group. There are several advantages to the GRAD method for SMT. It determines that probability that the grouping is correct, uses the entire longitudinal tumor growth curve data for each drug treatment, can fit different shape growth curves, accounts for missing growth curve data, and accommodates growth curves of different time periods.

RESULTS

We analyzed data for 22 drugs for 18 human colorectal tumors provided by researchers in a previous publication. The GRAD method identified 18 drugs that were inhibitory against at least one tumor, and 10 tumors for which there was at least one inhibitory drug. Analysis of simulated data indicated that the GRAD method has a sensitivity of 84% and a specificity of 98%.

CONCLUSION

A statistical method, GRAD, can group anti-cancer drugs into those that are inhibitory and those that are non-inhibitory in single mouse trials and provide probabilities that the grouping is correct.

Current and Future Horizons of Patient-Derived Xenograft Models in Colorectal Cancer Translational Research

Our poor understanding of the intricate biology of cancer and the limited availability of preclinical models that faithfully recapitulate the complexity of tumors are primary contributors to the high failure rate of novel therapeutics in oncology clinical studies. To address this need, patient-derived xenograft (PDX) platforms have been widely deployed and have reached a point of development where we can critically review their utility to model and interrogate relevant clinical scenarios, including tumor heterogeneity and clonal evolution, contributions of the tumor microenvironment, identification of novel drugs and biomarkers, and mechanisms of drug resistance. Colorectal cancer (CRC) constitutes a unique case to illustrate clinical perspectives revealed by PDX studies, as they overcome limitations intrinsic to conventional ex vivo models. Furthermore, the success of molecularly annotated "Avatar" models for co-clinical trials in other diseases suggests that this approach may provide an additional opportunity to improve clinical decisions, including opportunities for precision targeted therapeutics, for patients with CRC in real time. Although critical weaknesses have been identified with regard to the ability of PDX models to predict clinical outcomes, for now, they are certainly the model of choice for preclinical studies in CRC. Ongoing multi-institutional efforts to develop and share large-scale, well-annotated PDX resources aim to maximize their translational potential. This review comprehensively surveys the current status of PDX models in translational CRC research and discusses the opportunities and considerations for future PDX development.

Establishment of the PDTX model of gynecological tumors

OBJECTIVE

Fresh tumor tissues from patients with gynecological tumors were obtained by surgery or biopsy, and transplanted into NOD-Prkdcem26ll2rgem26Nju (NCG) mice to establish a patient-derived tumor xenograft (PDTX).

MATERIALS AND METHODS

A total of 15 patients with gynecologic tumors were enrolled into the present study. Among these patients, 12 patients had epithelial fallopian tube/ovarian/peritoneal cancer, one patient had metastatic ovarian cancer, and two patients had cervical cancer. Furthermore, among these patients, three patients were treated with puncture or microscopy biopsy, six patients underwent laparoscopic surgery, and six patients underwent robotic surgery. The tumor formation latency, tumor formation rate, tumor volume, tumor invasion and metastasis of the transplanted tumor were observed, the consistency of the PDTX model tumor tissue and patient's primary tumor tissue was compared by pathological H&E staining, and pharmacodynamics testing was performed.

RESULTS

Seven of 15 PDTX models were successfully established, with a success rate of 46.7%. The tumor formation time ranged within 21-130 days, with a median tumor formation time of 73 days. The PDTX model maintained the differentiation, morphological and structural characteristics of tumor cells, and the pharmacodynamic test was completed in five patients.

CONCLUSION

The PDTX model is highly consistent with the pathology of the patient's tumor, and can be used as a substitute for clinical patients to guide the accurate treatment and scientific research of gynecological tumors.

Molecularly annotation of mouse avatar models derived from patients with colorectal cancer liver metastasis

Background: Liver is the most common metastatic site in advanced colorectal cancer. Most patients with colorectal cancer liver metastasis (CRLM) do not benefit from current treatment. Patient-derived xenografts (PDXs) with defined molecular signatures are attractive models for preclinical studies. Methods: Successfully established PDXs were evaluated to elucidate their fidelity of patients' biologic characteristics (pathologic, genetic and protein properties, together with chemosensitivity). The genomic variations of PDXs were analyzed by next-generation sequencing to explore the underlying molecular mechanism of metastasis and potential therapeutic targets. Results: CRLM (N=73) showed a significantly higher successful PDX establishment rate than primary specimens (N=26; 76.7% vs. 57.7%). CRLM PDXs recapitulated the pathologic, genetic and protein properties of parental tumors, as well as chemosensitivity. Frequent altered genes in PDXs showed high consistency compared to patients' genomic alterations and were enriched in MAPK, ErbB, cell cycle, focal adhesion pathways for CRLM PDXs, whereas primary tumor-derived PDXs only exhibited genomic variations involving ErbB and cell cycle. The genetic alterations showed high concordance between paired PDXs from primary and metastatic tissues, except for recurrent gene mutations (ARID1A, CDK8, ETV1, STAT5B and WNK3) and common copy number gains in chromosomes 20q (e.g., SRC/AURKA). Several potential drug targets such as KRAS, HER2, and FGFR2 were validated using corresponding inhibitors. Additionally, PDX models could also be used in screening efficient regimens for patients with no druggable alterations. Conclusion: This study has successfully established and validated a large panel of molecularly annotated platforms from patients with CRLM for preclinical studies.

Establishment and characterization of melanoma patient-derived xenograft models for preclinical evaluation of novel therapeutics

Patient-derived xenograft (PDX) models mostly retain the histological and genetic features of their donor tumors, which have been used for investigating various types of cancer. However, PDX models for melanoma, especially acral melanoma, are reported occasionally. We aimed to establish a large panel of melanoma PDX models representing the predominant Asian melanomas. Ninety-three fresh melanoma samples were implanted subcutaneously into nonobese diabetic/severe combined immunodeficiency mice. The histological and genetic characteristics were analyzed in both patient tumors and PDX models using immunohistochemistry, PCR amplification, and Sanger sequencing. Furthermore, the sensitivities of PDX models harboring distinct mutation profiles to binimetinib (a MEK inhibitor), vemubrafenib (a BRAF inhibitor), and imatinib (a KIT inhibitor) were also evaluated. Twenty-five PDX models were established successfully [25/93 (26.9%)] and passaged to maintain tumors in vivo. Clinical stage and origin of tumor sample were correlated with successful establishment rates (P=0.008 and <0.001, respectively). The histological (expression of NRAS, P16, and RB) and genetic (mutation status of NRAS, BRAF, and KIT) characteristics were stably maintained from patient tumors to PDX models. Targeted drugs could inhibit the tumor growth of PDX models harboring the corresponding target gene mutations. These PDX models constitute a pharmacological platform, enabling personalized development of therapeutic strategies for Asian melanomas.

Hepatocellular Carcinoma Xenografts Established From Needle Biopsies Preserve the Characteristics of the Originating Tumors

Hepatocellular carcinoma (HCC) is the second leading cause of cancer‐related deaths worldwide. Treatment options for patients with advanced‐stage disease are limited. A major obstacle in drug development is the lack of an in vivo model that accurately reflects the broad spectrum of human HCC. Patient‐derived xenograft (PDX) tumor mouse models could overcome the limitations of cancer cell lines. PDX tumors maintain the genetic and histologic heterogeneity of the originating tumors and are used for preclinical drug development in various cancers. Controversy exists about their genetic and molecular stability through serial passaging in mice. We aimed to establish PDX models from human HCC biopsies and to characterize their histologic and molecular stability during serial passaging. A total of 54 human HCC needle biopsies that were derived from patients with various underlying liver diseases and tumor stages were transplanted subcutaneously into immunodeficient, nonobese, diabetic/severe combined immunodeficiency gamma‐c mice; 11 successfully engrafted. All successfully transplanted HCCs were Edmondson grade III or IV. HCC PDX tumors retained the histopathologic, transcriptomic, and genomic characteristics of the original HCC biopsies over 6 generations of retransplantation. These characteristics included Edmondson grade, expression of tumor markers, tumor gene signature, tumor‐associated mutations, and copy number alterations. Conclusion: PDX mouse models can be established from undifferentiated HCCs, with an overall success rate of approximately 20%. The transplanted tumors represent the entire spectrum of the molecular landscape of HCCs and preserve the characteristics of the originating tumors through serial passaging. HCC PDX models are a promising tool for preclinical personalized drug development.

Chronic Treatment with Multi-Kinase Inhibitors Causes Differential Toxicities on Skeletal and Cardiac Muscles

Despite recent progress, chemotherapy remains the preferred treatment for cancer. We have shown a link between anticancer drugs and the development of cachexia, i.e., body wasting accompanied by muscle loss. The multi-kinase inhibitors (MKIs) regorafenib and sorafenib, used as second-line treatment for solid tumors, are frequently accompanied by several side effects, including loss of muscle mass and strength. In the present study we aimed to investigate the molecular mechanisms associated with the occurrence of muscle toxicities in in vivo conditions. Hence, we treated 8-week old healthy CD2F1 male mice with MKIs for up to six weeks and observed decreased skeletal and cardiac muscle mass, consistent with muscle weakness. Modulation of ERK1/2 and GSK3β, as well as increased expression of markers of autophagy, previously associated with muscle atrophy conditions, were shown in skeletal muscle upon treatment with either drug. MKIs also promoted cardiac abnormalities consistent with reduced left ventricular mass, internal diameter, posterior wall thickness and stroke volume, despite unchanged overall function. Notably, different signaling pathways were affected in the heart, including reduced expression of mitochondrial proteins, and elevated AKT, GSK3β, mTOR, MEK1/2 and ERK1/2 phosphorylation. Combined, our data demonstrate detrimental effects on skeletal and cardiac muscle in association with chronic administration of MKIs, although different mechanisms would seem to contribute to the cachectic phenotype in the two tissues.

Phosphoglucomutase 1 inhibits hepatocellular carcinoma progression by regulating glucose trafficking

Glycogen metabolism commonly altered in cancer is just beginning to be understood. Phosphoglucomutase 1 (PGM1), the first enzyme in glycogenesis that catalyzes the reversible conversion between glucose 1-phosphate (G-1-P) and glucose 6-phosphate (G-6-P), participates in both the breakdown and synthesis of glycogen. Here, we show that PGM1 is down-regulated in hepatocellular carcinoma (HCC), which is associated with the malignancy and poor prognosis of HCC. Decreased PGM1 expression obstructed glycogenesis pathway, which leads to the increased flow of glucose into glycolysis, thereby promoting tumor cell proliferation and HCC development. The loss of forkhead box protein J2 (FOXJ2), at least partly due to low genomic copy number in HCC, releases cellular nucleic acid-binding protein (CNBP), a nucleic acid chaperon, to bind to and promote G-quadruplex formation in PGM1 promoter and therefore decreases PGM1 expression. In addition, integrated analyses of PGM1 and FOXJ2 expression provide a better prediction for the malignance and prognosis of HCC. This study establishes a tumor-suppressive role of PGM1 by regulating glucose trafficking and uncovers a novel regulatory mechanism of PGM1 expression.

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer in adults. Sorafenib is the only clinically approved systemic drug for patients with advanced HCC. Identification of novel targets and biomarkers will provide new therapeutic strategies for advanced HCC and better prognostic prediction. Phosphoglucomutase (PGM) is an evolutionarily conserved enzyme that regulates one of the most important pathways in glucose metabolis—catalyzing the bidirectional interconversion of glucose 1-phosphate (G-1-P) and glucose 6-phosphate (G-6-P). In this study, we identify PGM1 as a metabolic tumor suppressor. Its expression allocates more glucose to glycogenesis, which reduces the glycolytic intermediates for biosynthesis, thereby impairing HCC progression. We delineate the mechanism of PGM1 down-regulation in HCC, finding that forkhead box protein J2 (FOXJ2) loss releases cellular nucleic acid-binding protein (CNBP) to bind to and modify the DNA structure of PGM1 promoter, thereby inhibiting PGM1 expression. Immunohistochemical analyses of human HCC tumors indicate that low FOXJ2 and PGM1 expression correlates with the malignancy and poor progression of human HCC. These results also suggest that the activation of residual PGM1 may impair HCC development through switching glycolysis to glycogenesis.

Antitumor effect of sorafenib and mammalian target of rapamycin inhibitor in liver transplantation recipients with hepatocellular carcinoma recurrence

Both sorafenib and mammalian target of rapamycin inhibitor (mTORi) have antitumor effects. This study aimed to evaluate their antitumor effects in liver transplantation (LT) recipients with hepatocellular carcinoma (HCC) recurrence. We performed a laboratory study using sorafenib and mTORi and subsequently validated their survival benefit in a clinical LT setting. In the laboratory study, the HepG2.2.15 liver tumor cell line and 5 patient-derived graft HCC cell lines were used for in vitro cytotoxic studies. After treatment with everolimus and sorafenib, cell viability and apoptosis assays revealed noticeable cytotoxic effects with individual agents and augmented effects by combination therapy. An in vivo mouse study also demonstrated similar cytotoxic outcomes. In the clinical study including 232 LT recipients with HCC recurrence, the 3-month medication drop-out rate was 35.6% for sorafenib administration and 23.5% for mTORi administration. Postrecurrence survival rates were not different according to sorafenib administration (P = 0.17) but were significantly improved following mTORi administration (P < 0.001). In mTORi subgroups with and without sorafenib, there was no difference in the overall postrecurrence patient survival period (P = 0.26), indicating an absence of synergistic or additional antitumor effect from sorafenib. The median progression-free and overall survival period was 6.4 and 11.8 months, respectively, after sorafenib administration. Time of tumor recurrence and use of mTORi were independent risk factors. In conclusion, our laboratory study demonstrated synergistic antitumor effects of sorafenib and mTORi, but this was not reproduced in our clinical LT study. Our clinical result of mTORi administration showed improved postrecurrence survival, thus administering mTORi in LT recipients with HCC recurrence appears worthwhile. However, the antitumor effect of sorafenib on posttransplant recurrence was not determined in this retrospective study, thus requiring further studies with early start of sorafenib administration. Liver Transplantation 24 932-945 2018. © 2018 AASLD.

The role of molecular enrichment on future therapies in hepatocellular carcinoma

Hepatocellular carcinomas (HCCs) are characterised by considerable phenotypic and molecular heterogeneity. Treating HCC and designing clinical trials are particularly challenging because co-existing liver disease, present in most patients, limits aggressive therapeutic options. Positive results in recent phase III clinical trials have confirmed the high value of anti-angiogenic therapies for HCC in both first (sorafenib and lenvatinib) and second line (regorafenib and cabozantinib) treatment modalities. However, failure of several large randomised controlled clinical trials over the last 10 years underlines the necessity for innovative treatment strategies and implementation of translational findings to overcome the unmet clinical need. Furthermore, the promising results from novel immunotherapies are likely to complement the landscape of active compounds for HCC and will require a completely different approach to patients, as well as the development of prognostic/predictive biomarkers. Given our increasing understanding of the most abundant molecular alterations in HCC, effective enrichment of patients based on clinical and molecular biomarkers, as well as adaptive clinical trials, are now feasible and should be implemented. Herein, we aim to review important aspects of precision medicine approaches in HCC that might contribute to improving the molecular subclassification of patients in a clinical trial setting and pave the way for novel therapeutic strategies.

Precision oncology in liver cancer

With the widespread adoption of molecular profiling in clinical oncology practice, many physicians are faced with making therapeutic decisions based upon isolated genomic alterations. For example, epidermal growth factor receptor tyrosine kinase inhibitors (TKIs) are effective in EGFR-mutant non-small cell lung cancers (NSCLC) while anti-EGFR monoclonal antibodies are ineffective in Ras-mutant colorectal cancers. The matching of mutations with drugs aimed at their respective gene products represents the current state of "precision" oncology. Despite the great expectations of this approach, only a fraction of cancers responds to 'targeted' interventions, and many early responders will ultimately develop resistance to these agents. The underwhelming success of mutation-driven therapies across all cancer types is not due to an inability to detect genetic changes in tumors; rather a deficit in functional insight into the genomic alterations that give rise to each cancer. The Achilles heel of precision oncology thus remains the lack of a robust functional understanding of an individual cancer genome that then allows prediction of the best therapy and resultant outcome for that patient. Current practice focuses on one 'actionable' mutation at a time, while solid cancers typically possess many mutations that involve different cellular sub-populations within a tumor. No method or platform currently exists to guide the interpretation of these complex data, nor to accurately predict response to treatment. This problem is particularly germane to primary liver cancers (PLC), for which only a handful of targeted therapies have been introduced. Here, we will review strategies aimed at overcoming some of these challenges in precision oncology, using liver cancer as an example.

Lenvatinib inhibits angiogenesis and tumor fibroblast growth factor signaling pathways in human hepatocellular carcinoma models

Unresectable hepatocellular carcinoma (uHCC) is one of the most lethal and prevalent cancers worldwide, and current systemic therapeutic options for uHCC are limited. Lenvatinib, a multiple receptor tyrosine kinase inhibitor targeting vascular endothelial growth factor receptors (VEGFRs) and fibroblast growth factor receptors (FGFRs), recently demonstrated a treatment effect on overall survival by statistical confirmation of noninferiority to sorafenib in a phase 3 study of uHCC. Here, we investigated mechanisms underlying the antitumor activity of lenvatinib in preclinical HCC models. In vitro proliferation assay of nine human HCC cell lines showed that lenvatinib selectively inhibited proliferation of FGF signal-activated HCC cells including FGF19-expressing Hep3B2.1-7. Lenvatinib suppressed phosphorylation of FRS2, a substrate of FGFR1-4, in these cells in a concentration-dependent manner. Lenvatinib inhibited in vivo tumor growth in Hep3B2.1-7 and SNU-398 xenografts and decreased phosphorylation of FRS2 and Erk1/2 within the tumor tissues. Lenvatinib also exerted antitumor activity and potently reduced tumor microvessel density in PLC/PRF/5 xenograft model and two HCC patient-derived xenograft models. These results suggest that lenvatinib has antitumor activity consistently across diverse HCC models, and that targeting of tumor FGF signaling pathways and anti-angiogenic activity underlies its antitumor activity against HCC tumors.

PDXliver: a database of liver cancer patient derived xenograft mouse models

Background

Liver cancer is the second leading cause of cancer-related deaths and characterized by heterogeneity and drug resistance. Patient-derived xenograft (PDX) models have been widely used in cancer research because they reproduce the characteristics of original tumors. However, the current studies of liver cancer PDX mice are scattered and the number of available PDX models are too small to represent the heterogeneity of liver cancer patients. To improve this situation and to complement available PDX models related resources, here we constructed a comprehensive database, PDXliver, to integrate and analyze liver cancer PDX models.

Description

Currently, PDXliver contains 116 PDX models from Chinese liver cancer patients, 51 of them were established by the in-house PDX platform and others were curated from the public literatures. These models are annotated with complete information, including clinical characteristics of patients, genome-wide expression profiles, germline variations, somatic mutations and copy number alterations. Analysis of expression subtypes and mutated genes show that PDXliver represents the diversity of human patients. Another feature of PDXliver is storing drug response data of PDX mice, which makes it possible to explore the association between molecular profiles and drug sensitivity. All data can be accessed via the Browse and Search pages. Additionally, two tools are provided to interactively visualize the omics data of selected PDXs or to compare two groups of PDXs.

Conclusion

As far as we known, PDXliver is the first public database of liver cancer PDX models. We hope that this comprehensive resource will accelerate the utility of PDX models and facilitate liver cancer research. The PDXliver database is freely available online at: http://www.picb.ac.cn/PDXliver/

Characterization and validation of potential therapeutic targets based on the molecular signature of patient-derived xenografts in gastric cancer

Background

Patient-derived xenograft (PDX) models with definite molecular signature are attractive preclinical models for development of novel targeted drugs. Here, we profiled and explored potential therapeutic targets based on characterized PDX models for advanced gastric cancer (AGC).

Methods

The genomic variation and molecular profile of 50 PDX models from AGC patients were analyzed by targeted next-generation sequencing, in situ hybridization, and immunohistochemistry. The antitumor activities of several targeted drugs were investigated in the PDX models. Furthermore, response biomarkers were explored.

Results

Each PDX model had individual histopathological and molecular features, and recurrent alterations in the MAPK, ErbB, VEGF, mTOR, and cell cycle signaling pathways were major events in these PDX models. Several potential drug targets, such as EGFR, MET, and CCNE1, were selected and validated in this study. Volitinib demonstrated strong antitumor activity in PDX models with MET and phosphorylated MET (pMET) overexpression. The EGFR monoclonal antibodies BK011 and cetuximab inhibited tumor growth in a PDX model with EGFR amplification. Afatinib inhibited tumor growth in the PDX models with EGFR amplification, EGFR overexpression, or HER2 amplification. Apatinib was more sensitive in the PDX models with high microvessel density. The CDK1/2/9 inhibitor AZD5438 had superior anti-tumor activity in two models with higher copy number of CCNE1.

Conclusions

PDX models with defined molecular signature are useful for preclinical studies with targeted drugs, and the results should be validated in larger studies with PDX models or in clinical trials.

Electronic supplementary material

The online version of this article (10.1186/s13045-018-0563-y) contains supplementary material, which is available to authorized users.