Patient-derived xenografts: a relevant preclinical model for drug development

Current methods in translational cancer research

Recent developments in pre-clinical screening tools, that more reliably predict the clinical effects and adverse events of candidate therapeutic agents, has ushered in a new era of drug development and screening. However, given the rapid pace with which these models have emerged, the individual merits of these translational research tools warrant careful evaluation in order to furnish clinical researchers with appropriate information to conduct pre-clinical screening in an accelerated and rational manner. This review assesses the predictive utility of both well-established and emerging pre-clinical methods in terms of their suitability as a screening platform for treatment response, ability to represent pharmacodynamic and pharmacokinetic drug properties, and lastly debates the translational limitations and benefits of these models. To this end, we will describe the current literature on cell culture, organoids, in vivo mouse models, and in silico computational approaches. Particular focus will be devoted to discussing gaps and unmet needs in the literature as well as current advancements and innovations achieved in the field, such as co-clinical trials and future avenues for refinement.

Regorafenib inhibits migration, invasion, and vasculogenic mimicry of hepatocellular carcinoma via targeting ID1-mediated EMT

Regorafenib is approved for patients with unresectable hepatocellular carcinoma (HCC) following sorafenib. However, the effect of regorafenib on HCC metastasis and its mechanism are poorly understood. Here, our data showed that regorafenib significantly restrained the migration, invasion and vasculogenic mimicry (VM) of HCC cells, and downregulated the expression of epithelial-to-mesenchymal transition (EMT)/VM-related molecules. Using RNA-seq and cellular thermal shift assays, we found that inhibitor of differentiation 1 (ID1) was a key target of regorafenib. In HCC tissues, the protein expression of ID1 was positively correlated with EMT and VM formation (CD34- /PAS+ ). Functionally, ID1 knockdown inhibited HCC cell migration, invasion, metastasis, and VM formation in vitro and in vivo, with upregulation of E-cadherin and downregulation of Snail and VE-cadherin. Moreover, Snail overexpression promoted the migration, invasion, and VM formation of ID1 knockdown cells. Snail knockdown reduced the migration, invasion, and VM formation of ID1 overexpression cells. Finally, regorafenib suppressed VM formation and decreased the expression of ID1, VE-cadherin and Snail in HCC PDX model. In conclusion, we manifested that regorafenib distinctly inhibited EMT in HCC cells via targeting ID1, leading to the suppression of cell migration, invasion and VM formation. These findings suggest that regorafenib may be developed as a suitable therapeutic agent for HCC metastasis.

Co-Clinical Trials: An Innovative Drug Development Platform for Cholangiocarcinoma

Cholangiocarcinoma (CCA), a group of malignancies that originate from the biliary tract, is associated with a high mortality rate and a concerning increase in worldwide incidence. In Thailand, where the incidence of CCA is the highest, the socioeconomic burden is severe. Yet, treatment options are limited, with surgical resection being the only form of treatment with curative intent. The current standard-of-care remains adjuvant and palliative chemotherapy which is ineffective in most patients. The overall survival rate is dismal, even after surgical resection and the tumor heterogeneity further complicates treatment. Together, this makes CCA a significant burden in Southeast Asia. For effective management of CCA, treatment must be tailored to each patient, individually, for which an assortment of targeted therapies must be available. Despite the increasing numbers of clinical studies in CCA, targeted therapy drugs rarely get approved for clinical use. In this review, we discuss the shortcomings of the conventional clinical trial process and propose the implementation of a novel concept, co-clinical trials to expedite drug development for CCA patients. In co-clinical trials, the preclinical studies and clinical trials are conducted simultaneously, thus enabling real-time data integration to accurately stratify and customize treatment for patients, individually. Hence, co-clinical trials are expected to improve the outcomes of clinical trials and consequently, encourage the approval of targeted therapy drugs. The increased availability of targeted therapy drugs for treatment is expected to facilitate the application of precision medicine in CCA.

Deep learning of pharmacogenomics resources: moving towards precision oncology

The recent accumulation of cancer genomic data provides an opportunity to understand how a tumor's genomic characteristics can affect its responses to drugs. This field, called pharmacogenomics, is a key area in the development of precision oncology. Deep learning (DL) methodology has emerged as a powerful technique to characterize and learn from rapidly accumulating pharmacogenomics data. We introduce the fundamentals and typical model architectures of DL. We review the use of DL in classification of cancers and cancer subtypes (diagnosis and treatment stratification of patients), prediction of drug response and drug synergy for individual tumors (treatment prioritization for a patient), drug repositioning and discovery and the study of mechanism/mode of action of treatments. For each topic, we summarize current genomics and pharmacogenomics data resources such as pan-cancer genomics data for cancer cell lines (CCLs) and tumors, and systematic pharmacologic screens of CCLs. By revisiting the published literature, including our in-house analyses, we demonstrate the unprecedented capability of DL enabled by rapid accumulation of data resources to decipher complex drug response patterns, thus potentially improving cancer medicine. Overall, this review provides an in-depth summary of state-of-the-art DL methods and up-to-date pharmacogenomics resources and future opportunities and challenges to realize the goal of precision oncology.

Ex Vivo Culture Models to Indicate Therapy Response in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is characterized by a poor 5 year survival and varying response rates to both standard-of-care and new treatments. Despite advances in medicine and treatment methods, mortality rates have hardly decreased in recent decades. Reliable patient-derived tumor models offer the chance to predict therapy response in a personalized setting, thereby improving treatment efficacy by identifying the most appropriate treatment regimen for each patient. Furthermore, ex vivo tumor models enable testing of novel therapies before introduction in clinical practice. A literature search was performed to identify relevant literature describing three-dimensional ex vivo culture models of HNSCC to examine sensitivity to chemotherapy, radiotherapy, immunotherapy and targeted therapy. We provide a comprehensive overview of the currently used three-dimensional ex vivo culture models for HNSCC with their advantages and limitations, including culture success percentage and comparison to the original tumor. Furthermore, we evaluate the potential of these models to predict patient therapy response.

Establishment and characterisation of testicular cancer patient-derived xenograft models for preclinical evaluation of novel therapeutic strategies

Testicular cancer (TC) is the most common solid tumour in young men. While cisplatin-based chemotherapy is highly effective in TC patients, chemoresistance still accounts for 10% of disease-related deaths. Pre-clinical models that faithfully reflect patient tumours are needed to assist in target discovery and drug development. Tumour pieces from eight TC patients were subcutaneously implanted in NOD scid gamma (NSG) mice. Three patient-derived xenograft (PDX) models of TC, including one chemoresistant model, were established containing yolk sac tumour and teratoma components. PDX models and corresponding patient tumours were characterised by H&E, Ki-67 and cyclophilin A immunohistochemistry, showing retention of histological subtypes over several passages. Whole-exome sequencing, copy number variation analysis and RNA-sequencing was performed on these TP53 wild type PDX tumours to assess the effects of passaging, showing high concordance of molecular features between passages. Cisplatin sensitivity of PDX models corresponded with patients' response to cisplatin-based chemotherapy. MDM2 and mTORC1/2 targeted drugs showed efficacy in the cisplatin sensitive PDX models. In conclusion, we describe three PDX models faithfully reflecting chemosensitivity of TC patients. These models can be used for mechanistic studies and pre-clinical validation of novel therapeutic strategies in testicular cancer.

The Effects of the Alkaloid Tambjamine J on Mice Implanted with Sarcoma 180 Tumor Cells

The tambjamines are a small group of bipyrrolic alkaloids that, collectively, display a significant range of biological activities including antitumor, antimicrobial and immunosuppressive properties. The key objective of the present study was to undertake preclinical assessments of tambjamine J (T-J) so as to determine its in vivo antitumor effects. To that end, sarcoma 180 cells were transplanted in mice and the impacts of the title compound then evaluated using a range of protocols including hematological, biochemical, histopathological, genotoxic and clastogenic assays. As a result it was established that this alkaloid has a significant therapeutic window and effectively reduces tumor growth (by 40 % and 79 % at doses of 10 and 20 mg/kg/day, respectively). In this regard it displays similar antitumor activity to the anticancer agent cyclophosphamide and alters animal weight in an analogous manner.

Disruption of redox homeostasis for combinatorial drug efficacy in K-Ras tumors as revealed by metabolic connectivity profiling

Abstract

Background

Rewiring of metabolism induced by oncogenic K-Ras in cancer cells involves both glucose and glutamine utilization sustaining enhanced, unrestricted growth. The development of effective anti-cancer treatments targeting metabolism may be facilitated by the identification and rational combinatorial targeting of metabolic pathways.

Methods

We performed mass spectrometric metabolomics analysis in vitro and in vivo experiments to evaluate the efficacy of drugs and identify metabolic connectivity.

Results

We show that K-Ras-mutant lung and colon cancer cells exhibit a distinct metabolic rewiring, the latter being more dependent on respiration. Combined treatment with the glutaminase inhibitor CB-839 and the PI3K/aldolase inhibitor NVP-BKM120 more consistently reduces cell growth of tumor xenografts. Maximal growth inhibition correlates with the disruption of redox homeostasis, involving loss of reduced glutathione regeneration, redox cofactors, and a decreased connectivity among metabolites primarily involved in nucleic acid metabolism.

Conclusions

Our findings open the way to develop metabolic connectivity profiling as a tool for a selective strategy of combined drug repositioning in precision oncology.

Personalized cancer therapy prioritization based on driver alteration co-occurrence patterns

Identification of actionable genomic vulnerabilities is key to precision oncology. Utilizing a large-scale drug screening in patient-derived xenografts, we uncover driver gene alteration connections, derive driver co-occurrence (DCO) networks, and relate these to drug sensitivity. Our collection of 53 drug-response predictors attains an average balanced accuracy of 58% in a cross-validation setting, rising to 66% for a subset of high-confidence predictions. We experimentally validated 12 out of 14 predictions in mice and adapted our strategy to obtain drug-response models from patients’ progression-free survival data. Our strategy reveals links between oncogenic alterations, increasing the clinical impact of genomic profiling.

Head and neck cancer patient-derived xenograft models - A systematic review

BACKGROUND

Patient-derived xenograft (PDX) involve the direct surgical transfer of fresh human tumor samples to immunodeficient mice. This systematic review aimed to identify publications of head and neck cancer PDX (HNC-PDX) models, describing the main methodological characteristics and outcomes.

METHODS

An electronic search was undertaken in four databases, including publications having used HNC-PDX. Data were analyzed descriptively.

RESULTS

63 articles were yielded. The nude mouse was one most commonly animal model used (38.8 %), and squamous cell carcinoma accounted for the majority of HNC-PDX (80.6 %). Tumors were mostly implanted in the flank (86.3 %), and the latency period ranged from 30 to 401 days. The successful rate ranged from 17 % to 100 %. Different drugs and pathways were identified.

CONCLUSION

HNC-PDX appears to significantly recapitulate the morphology of the original HNC and represents a valuable method in translational research for the assessment of the in vivo effect of novel therapies for HNC.

Phosphoproteomic analysis identifies CLK1 as a novel therapeutic target in gastric cancer

BACKGROUND

Phosphorylation is an important regulatory mechanism of protein activity in cells. Studies in various cancers have reported perturbations in kinases resulting in aberrant phosphorylation of oncoproteins and tumor suppressor proteins.

METHODS

In this study, we carried out quantitative phosphoproteomic analysis of gastric cancer tissues and corresponding xenograft samples. Using these data, we employed bioinformatics analysis to identify aberrant signaling pathways. We further performed molecular inhibition and silencing of the upstream regulatory kinase in gastric cancer cell lines and validated its effect on cellular phenotype. Through an ex vivo technology utilizing patient tumor and blood sample, we sought to understand the therapeutic potential of the kinase by recreating the tumor microenvironment.

RESULTS

Using mass spectrometry-based high-throughput analysis, we identified 1,344 phosphosites and 848 phosphoproteins, including differential phosphorylation of 177 proteins (fold change cut-off ≥ 1.5). Our data showed that a subset of differentially phosphorylated proteins belonged to splicing machinery. Pathway analysis highlighted Cdc2-like kinase (CLK1) as upstream kinase. Inhibition of CLK1 using TG003 and CLK1 siRNA resulted in a decreased cell viability, proliferation, invasion and migration as well as modulation in the phosphorylation of SRSF2. Ex vivo experiments which utilizes patient's own tumor and blood to recreate the tumor microenvironment validated the use of CLK1 as a potential target for gastric cancer treatment.

CONCLUSIONS

Our data indicates that CLK1 plays a crucial role in the regulation of splicing process in gastric cancer and that CLK1 can act as a novel therapeutic target in gastric cancer.

Harnessing Omics Approaches on Advanced Preclinical Models to Discovery Novel Therapeutic Targets for the Treatment of Metastatic Colorectal Cancer

Metastatic colorectal cancer (mCRC) remains challenging because of the emergence of resistance mechanisms to anti-epidermal growth factor receptor (EGFR) therapeutics, so more effective strategies to improve the patients’ outcome are needed. During the last decade, the application of a multi-omics approach has contributed to a deeper understanding of the complex molecular landscape of human CRC, identifying a plethora of drug targets for precision medicine. Target validation relies on the use of experimental models that would retain the molecular and clinical features of human colorectal cancer, thus mirroring the clinical characteristics of patients. In particular, organoids and patient-derived-xenografts (PDXs), as well as genetically engineered mouse models (GEMMs) and patient-derived orthotopic xenografts (PDOXs), should be considered for translational purposes. Overall, omics and advanced mouse models of cancer represent a portfolio of sophisticated biological tools that, if optimized for use in concert with accurate data analysis, could accelerate the anticancer discovery process and provide new weapons against cancer. In this review, we highlight success reached following the integration of omics and experimental models; moreover, results produced by our group in the field of mCRC are also presented.

Testicular cancer: Determinants of cisplatin sensitivity and novel therapeutic opportunities

Testicular cancer (TC) is the most common solid tumor among men aged between 15 and 40 years. TCs are highly aneuploid and the 12p isochromosome is the most frequent chromosomal abnormality. The mutation rate is of TC is low, with recurrent mutations in KIT and KRAS observed only at low frequency in seminomas. Overall cure rates are high, even in a metastatic setting, resulting from excellent cisplatin sensitivity of TCs. Factors contributing to the observed cisplatin sensitivity include defective DNA damage repair and a hypersensitive apoptotic response to DNA damage. Nonetheless, around 10-20% of TC patients with metastatic disease cannot be cured by cisplatin-based chemotherapy. Resistance mechanisms include downregulation of OCT4 and failure to induce PUMA and NOXA, elevated levels of MDM2, and hyperactivity of the PI3K/AKT/mTOR pathway. Several pre-clinical approaches have proven successful in overcoming cisplatin resistance, including specific targeting of PARP, MDM2 or AKT/mTOR combined with cisplatin. Finally, patient-derived xenograft models hold potential for mechanistic studies and pre-clinical validation of novel therapeutic strategies in TC. While clinical trials investigating targeted drugs have been disappointing, pre-clinical successes with chemotherapy and targeted drug combinations fuel the need for further investigation in clinical setting.

Modeling the Tumor Microenvironment and Pathogenic Signaling in Bone Sarcoma

Investigations of cancer biology and screening of potential therapeutics for efficacy and safety begin in the preclinical laboratory setting. A staple of most basic research in cancer involves the use of tissue culture plates, on which immortalized cell lines are grown in monolayers. However, this practice has been in use for over six decades and does not account for vital elements of the tumor microenvironment that are thought to aid in initiation, propagation, and ultimately, metastasis of cancer. Furthermore, information gleaned from these techniques does not always translate to animal models or, more crucially, clinical trials in cancer patients. Osteosarcoma (OS) and Ewing sarcoma (ES) are the most common primary tumors of bone, but outcomes for patients with metastatic or recurrent disease have stagnated in recent decades. The unique elements of the bone tumor microenvironment have been shown to play critical roles in the pathogenesis of these tumors and thus should be incorporated in the preclinical models of these diseases. In recent years, the field of tissue engineering has leveraged techniques used in designing scaffolds for regenerative medicine to engineer preclinical tumor models that incorporate spatiotemporal control of physical and biological elements. We herein review the clinical aspects of OS and ES, critical elements present in the sarcoma microenvironment, and engineering approaches to model the bone tumor microenvironment. Impact statement The current paradigm of cancer biology investigation and therapeutic testing relies heavily on monolayer, monoculture methods developed over half a century ago. However, these methods often lack essential hallmarks of the cancer microenvironment that contribute to tumor pathogenesis. Tissue engineers incorporate scaffolds, mechanical forces, cells, and bioactive signals into biological environments to drive cell phenotype. Investigators of bone sarcomas, aggressive tumors that often rob patients of decades of life, have begun to use tissue engineering techniques to devise in vitro models for these diseases. Their efforts highlight how critical elements of the cancer microenvironment directly affect tumor signaling and pathogenesis.

Comparative Molecular Analysis of Cancer Behavior Cultured In Vitro, In Vivo, and Ex Vivo

Current pre-clinical models of cancer fail to recapitulate the cancer cell behavior in primary tumors primarily because of the lack of a deeper understanding of the effects that the microenvironment has on cancer cell phenotype. Transcriptomic profiling of 4T1 murine mammary carcinoma cells from 2D and 3D cultures, subcutaneous or orthotopic allografts (from immunocompetent or immunodeficient mice), as well as ex vivo tumoroids, revealed differences in molecular signatures including altered expression of genes involved in cell cycle progression, cell signaling and extracellular matrix remodeling. The 3D culture platforms had more in vivo-like transcriptional profiles than 2D cultures. In vivo tumors had more cells undergoing epithelial-to-mesenchymal transition (EMT) while in vitro cultures had cells residing primarily in an epithelial or mesenchymal state. Ex vivo tumoroids incorporated aspects of in vivo and in vitro culturing, retaining higher abundance of cells undergoing EMT while shifting cancer cell fate towards a more mesenchymal state. Cellular heterogeneity surveyed by scRNA-seq revealed that ex vivo tumoroids, while rapidly expanding cancer and fibroblast populations, lose a significant proportion of immune components. This study emphasizes the need to improve in vitro culture systems and preserve syngeneic-like tumor composition by maintaining similar EMT heterogeneity as well as inclusion of stromal subpopulations.

3D cultures for modeling nanomaterial-based photothermal therapy

Photothermal therapy (PTT) is one of the most promising techniques for cancer tumor ablation. Nanoparticles are increasingly being investigated for use with PTT and can serve as theranostic agents. Based on the ability of near-infrared nano-photo-absorbers to generate heat under laser irradiation, PTT could prove advantageous in certain situations over more classical cancer therapies. To analyze the efficacy of nanoparticle-based PTT, preclinical in vitro studies typically use 2D cultures, but this method cannot completely mimic the complex tumor organization, bioactivity, and physiology that all control the complex penetration depth, biodistribution, and tissue diffusion parameters of nanomaterials in vivo. To fill this knowledge gap, 3D culture systems have been explored for PTT analysis. These models provide more realistic microenvironments that allow spatiotemporal oxygen gradients and cancer cell adaptations to be considered. This review highlights the work that has been done to advance 3D models for cancer microenvironment modeling, specifically in the context of advanced, functionalized nanoparticle-directed PTT.

Cytoplasmic ERα and NFκB Promote Cell Survival in Mouse Mammary Cancer Cell Lines

There is a desperate need in the field for mouse mammary tumors and cell lines that faithfully mimic estrogen receptor (ER) expression and activity found in human breast cancers. We found that several mouse mammary cancer cell lines express ER but fail to demonstrate classical estrogen-driven proliferation or transcriptional activity. We investigated whether these cell lines may be used to model tamoxifen resistance by using small molecule inhibitors to signaling pathways known to contribute to resistance. We found that the combination of NFκB inhibition and ER antagonists significantly reduced cell proliferation in vitro, as well as growth of syngeneic tumors. Surprisingly, we found that ER was localized to the cytoplasm, regardless of any type of treatment. Based on this, we probed extra-nuclear functions of ER and found that co-inhibition of ER and NFκB led to an increase in oxidative stress and apoptosis. Together, these findings suggest that cytoplasmic ER and NFκB may play redundant roles in protecting mammary cancer cells from oxidative stress and cell death. Although this study has not identified a mouse model with classical ER activity, cytoplasmic ER has been described in a small subset of human breast tumors, suggesting that these findings may be relevant for some breast cancer patients.

Genetic heterogeneity and clonal evolution during metastasis in breast cancer patient-derived tumor xenograft models

Genetic heterogeneity within a tumor arises by clonal evolution, and patients with highly heterogeneous tumors are more likely to be resistant to therapy and have reduced survival. Clonal evolution also occurs when a subset of cells leave the primary tumor to form metastases, which leads to reduced genetic heterogeneity at the metastatic site. Although this process has been observed in human cancer, experimental models which recapitulate this process are lacking. Patient-derived tumor xenografts (PDX) have been shown to recapitulate the patient's original tumor's intra-tumor genetic heterogeneity, as well as its genomics and response to treatment, but whether they can be used to model clonal evolution in the metastatic process is currently unknown. Here, we address this question by following genetic changes in two breast cancer PDX models during metastasis. First, we discovered that mouse stroma can be a confounding factor in assessing intra-tumor heterogeneity by whole exome sequencing, thus we developed a new bioinformatic approach to correct for this. Finally, in a spontaneous, but not experimental (tail-vein) metastasis model we observed a loss of heterogeneity in PDX metastases compared to their orthotopic "primary" tumors, confirming that PDX models can faithfully mimic the clonal evolution process undergone in human patients during metastatic spreading.

Applications of patient-derived tumor xenograft models and tumor organoids

Patient-derived tumor xenografts (PDXs), in which tumor fragments surgically dissected from cancer patients are directly transplanted into immunodeficient mice, have emerged as a useful model for translational research aimed at facilitating precision medicine. PDX susceptibility to anti-cancer drugs is closely correlated with clinical data in patients, from whom PDX models have been derived. Accumulating evidence suggests that PDX models are highly effective in predicting the efficacy of both conventional and novel anti-cancer therapeutics. This also allows “co-clinical trials,” in which pre-clinical investigations in vivo and clinical trials could be performed in parallel or sequentially to assess drug efficacy in patients and PDXs. However, tumor heterogeneity present in PDX models and in the original tumor samples constitutes an obstacle for application of PDX models. Moreover, human stromal cells originally present in tumors dissected from patients are gradually replaced by host stromal cells as the xenograft grows. This replacement by murine stroma could preclude analysis of human tumor-stroma interactions, as some mouse stromal cytokines might not affect human carcinoma cells in PDX models. The present review highlights the biological and clinical significance of PDX models and three-dimensional patient-derived tumor organoid cultures of several kinds of solid tumors, such as those of the colon, pancreas, brain, breast, lung, skin, and ovary.

Developments in zebrafish avatars as radiotherapy sensitivity reporters - towards personalized medicine

Background

Whereas the role of neoadjuvant radiotherapy in rectal cancer is well-established, the ability to discriminate between radioresistant and radiosensitive tumors before starting treatment is still a crucial unmet need. Here we aimed to develop an in vivo test to directly challenge living cancer cells to radiotherapy, using zebrafish xenografts.

Methods

We generated zebrafish xenografts using colorectal cancer cell lines and patient biopsies without in vitro passaging, and developed a fast radiotherapy protocol consisting of a single dose of 25 Gy. As readouts of the impact of radiotherapy we analyzed proliferation, apoptosis, tumor size and DNA damage.

Findings

By directly comparing isogenic cells that only differ in the KRAS^G13D allele, we show that it is possible to distinguish radiosensitive from radioresistant tumors in zebrafish xenografts, even in polyclonal tumors, in just 4 days. Most importantly, we performed proof-of-concept experiments using primary rectum biopsies, where clinical response to neoadjuvant chemoradiotherapy correlates with induction of apoptosis in their matching zebrafish Patient-Derived Xenografts-Avatars.

Interpretation

Our work opens the possibility to predict tumor responses to radiotherapy using the zebrafish Avatar model, sparing valuable therapeutic time and unnecessary toxicity.

Scaffold-Assisted Ectopic Transplantation of Internal Organs and Patient-Derived Tumors

Xenotransplantation of human tissues into immunodeficient mice has emerged as an invaluable preclinical model to study human biology and disease progression and predict clinical response. The most common anatomical site for tissue transplantation is the subcutaneous pocket due to simple surgical procedures and accessibility for gross monitoring and advanced imaging modalities. However, subcutaneously implanted tissues initially experience a sharp change in oxygen and nutrient supply and increased mechanical deformation. During this acute phase of tissue integration to the host vasculature, substantial cell death and tissue fibrosis occur limiting engraftment efficiency. Previously, we demonstrated that the implantation of inverted colloidal crystal hydrogel scaffolds triggers proangiogenic and immunomodulatory functions without characteristic foreign body encapsulation. In this study, we examine the use of this unique host response to improve the ectopic transplantation of tissues to the subcutaneous site. Scaffold-assisted tissues preserved morphological features and blood vessel density compared to native tissues, whereas scaffold-free tissues collapsed and were less vascularized. Notably, the supporting biomaterial scaffold modulated the foreign body response to reduce the localization of Ly6G⁺ cells within the transplanted tissues. Cotransplantation of patient-derived gastric cancer with a scaffold resulted in a comparable level of engraftment to conventional methods; however, detailed immunohistological characterization revealed significantly better retention of proliferative cells (Ki67⁺) and human immune cells (CD45⁺) by the end of the study. We envision that leveraging the immunomodulatory properties of biomaterial interfaces can be an attractive strategy to improve the functional engraftment of xenotransplants and accelerate individualized diagnostics and the development of novel therapeutic strategies.

A selective BCL-XL PROTAC degrader achieves safe and potent antitumor activity

BCL-X_L is a well-validated cancer target. However, the on-target and dose-limiting thrombocytopenia limits the use of BCL-X_L inhibitors such as ABT263 as safe and effective anticancer agents. To reduce the toxicity of ABT263, we converted it into DT2216, a BCL-X_L proteolysis targeting chimera (PROTAC), that targets BCL-X_L to the Von Hippel-Lindau (VHL) E3 ligase for degradation. We found that DT2216 was more potent against various BCL-X_L-dependent leukemia and cancer cells but significantly less toxic to platelets than ABT263 in vitro because VHL is poorly expressed in platelets. In vivo, DT2216 effectively inhibits the growth of several xenograft tumors as a single agent or in combination with other chemotherapeutic agents, without causing significant thrombocytopenia. These findings demonstrate the potential to use PROTAC technology to reduce on-target drug toxicities and rescue the therapeutic potential of previously undruggable targets. Furthermore, DT2216 may be developed as a safe first-in-class anticancer agent targeting BCL-X_L.

Generation and application of patient-derived xenograft models in pancreatic cancer research

OBJECTIVE

Pancreatic ductal adenocarcinoma cancer (PDAC) is one of the leading causes of cancer-related death worldwide. Hence, the development of effective anti-PDAC therapies is urgently required. Patient-derived xenograft (PDX) models are useful models for developing anti-cancer therapies and screening drugs for precision medicine. This review aimed to provide an updated summary of using PDX models in PDAC.

DATA SOURCES

The author retrieved information from the PubMed database up to June 2019 using various combinations of search terms, including PDAC, pancreatic carcinoma, pancreatic cancer, patient-derived xenografts or PDX, and patient-derived tumor xenografts or PDTX.

STUDY SELECTION

Original articles and review articles relevant to the review's theme were selected.

RESULTS

PDX models are better than cell line-derived xenograft and other models. PDX models consistently demonstrate retained tumor morphology and genetic stability, are beneficial in cancer research, could enhance drug discovery and oncologic mechanism development of PDAC, allow an improved understanding of human cancer cell biology, and help guide personalized treatment.

CONCLUSIONS

In this review, we outline the status and application of PDX models in both basic and pre-clinical pancreatic cancer researches. PDX model is one of the most appropriate pre-clinical tools that can improve the prognosis of patients with pancreatic cancer in the future.

Impact of mouse contamination in genomic profiling of patient-derived models and best practice for robust analysis

BACKGROUND

Patient-derived xenograft and cell line models are popular models for clinical cancer research. However, the inevitable inclusion of a mouse genome in a patient-derived model is a remaining concern in the analysis. Although multiple tools and filtering strategies have been developed to account for this, research has yet to demonstrate the exact impact of the mouse genome and the optimal use of these tools and filtering strategies in an analysis pipeline.

RESULTS

We construct a benchmark dataset of 5 liver tissues from 3 mouse strains using human whole-exome sequencing kit. Next-generation sequencing reads from mouse tissues are mappable to 49% of the human genome and 409 cancer genes. In total, 1,207,556 mouse-specific alleles are aligned to the human genome reference, including 467,232 (38.7%) alleles with high sensitivity to contamination, which are pervasive causes of false cancer mutations in public databases and are signatures for predicting global contamination. Next, we assess the performance of 8 filtering methods in terms of mouse read filtration and reduction of mouse-specific alleles. All filtering tools generally perform well, although differences in algorithm strictness and efficiency of mouse allele removal are observed. Therefore, we develop a best practice pipeline that contains the estimation of contamination level, mouse read filtration, and variant filtration.

CONCLUSIONS

The inclusion of mouse cells in patient-derived models hinders genomic analysis and should be addressed carefully. Our suggested guidelines improve the robustness and maximize the utility of genomic analysis of these models.

Elevated proportion of collapsed microvessels indicate poor survival outcome in patients with non-small cell lung cancer

BACKGROUND

An integral and well-functioning vascular system is essential for tumor progression and chemotherapy infusion. However, the lumen integrity of the microvessels and its significance in prognosis has not been studied. In this study, we found that the proportion of collapsed microvessels is suggested to be a novel biomarker for predicting prognosis in patients with non-small cell lung cancer (NSCLC).

METHODS

In this study, immunohistochemical CD31 staining was performed to identify the microvessels in tumor specimens. Proportions of collapsed vessels were estimated in CD31-stained tumor specimens from 100 patients with NSCLC. The correlation between collapsed microvessel proportion and survival time were evaluated by univariate and multivariate analysis.

RESULTS

Data from 99 patients were analyzed and a wide range of collapse-microvessel fraction was observed in 96 patients (1.4%-70%). Elevated collapse proportion (⩾6.5%) indicated poor overall survival in both univariate analysis (p = 0.042) and multivariate analysis (p = 0.014).

CONCLUSIONS

Elevated proportion of collapsed microvessels indicted poor survival outcome in patients with NSCLC.

Bone sarcoma patient-derived xenografts are faithful and stable preclinical models for molecular and therapeutic investigations

Standard therapy of osteosarcoma (OS) and Ewing sarcoma (EW) rests on cytotoxic regimes, which are largely unsuccessful in advanced patients. Preclinical models are needed to break this impasse. A panel of patient-derived xenografts (PDX) was established by implantation of fresh, surgically resected osteosarcoma (OS) and Ewing sarcoma (EW) in NSG mice. Engraftment was obtained in 22 of 61 OS (36%) and 7 of 29 EW (24%). The success rate in establishing primary cell cultures from OS was lower than the percentage of PDX engraftment in mice, whereas the reverse was observed for EW; the implementation of both in vivo and in vitro seeding increased the proportion of patients yielding at least one workable model. The establishment of in vitro cultures from PDX was highly efficient in both tumor types, reaching 100% for EW. Morphological and immunohistochemical (SATB2, P-glycoprotein 1, CD99, caveolin 1) studies and gene expression profiling showed a remarkable similarity between patient’s tumor and PDX, which was maintained over several passages in mice, whereas cell cultures displayed a lower correlation with human samples. Genes differentially expressed between OS original tumor and PDX mostly belonged to leuykocyte-specific pathways, as human infiltrate is gradually replaced by murine leukocytes during growth in mice. In EW, which contained scant infiltrates, no gene was differentially expressed between the original tumor and the PDX. A novel therapeutic combination of anti-CD99 diabody C7 and irinotecan was tested against two EW PDX; both drugs inhibited PDX growth, the addition of anti-CD99 was beneficial when chemotherapy alone was less effective. The panel of OS and EW PDX faithfully mirrored morphologic and genetic features of bone sarcomas, representing reliable models to test therapeutic approaches.

Application of Highly Immunocompromised Mice for the Establishment of Patient-Derived Xenograft (PDX) Models

Patient-derived xenograft (PDX) models are created by engraftment of patient tumor tissues into immunocompetent mice. Since a PDX model retains the characteristics of the primary patient tumor including gene expression profiles and drug responses, it has become the most reliable in vivo human cancer model. The engraftment rate increases with the introduction of Non-obese diabetic Severe combined immunodeficiency (NOD/SCID)-based immunocompromised mice, especially the NK-deficient NOD strains NOD/SCID/interleukin-2 receptor gamma chain(IL2Rγ)null (NOG/NSG) and NOD/SCID/Jak3(Janus kinase 3)null (NOJ). Success rates differ with tumor origin: gastrointestinal tumors acquire a higher engraftment rate, while the rate is lower for breast cancers. Subcutaneous transplantation is the most popular method to establish PDX, but some tumors require specific environments, e.g., orthotropic or renal capsule transplantation. Human hormone treatment is necessary to establish hormone-dependent cancers such as prostate and breast cancers. PDX mice with human hematopoietic and immune systems (humanized PDX) are powerful tools for the analysis of tumor-immune system interaction and evaluation of immunotherapy response. A PDX biobank equipped with patients' clinical data, gene-expression patterns, mutational statuses, tumor tissue architects, and drug responsiveness will be an authoritative resource for developing specific tumor biomarkers for chemotherapeutic predictions, creating individualized therapy, and establishing precise cancer medicine.

Targeting cyclin-dependent kinase 9 by a novel inhibitor enhances radiosensitization and identifies Axl as a novel downstream target in esophageal adenocarcinoma

Cyclin-dependent kinase 9 (CDK9) transcriptionally regulates several proteins and cellular pathways central to radiation induced tissue injury. We investigated a role of BAY1143572, a new highly specific CDK9 inhibitor, as a sensitizer to radiation in esophageal adenocarcinoma. In vitro synergy between the CDK9 inhibitor and radiation was evaluated by clonogenic assay. In vivo synergy between the CDK9 inhibitor and radiation was assessed in multiple xenograft models including a patient’s tumor derived xenograft (PDX). Reverse phase protein array (RPPA), western blotting, immunohistochemistry, and qPCR were utilized to identify and validate targets of the CDK9 inhibitor. The CDK9 inhibitor plus radiation significantly reduced growth of FLO-1, SKGT4, OE33, and radiation resistant OE33R xenografts and PDXs as compared to the cohorts treated with either single agent CDK9 inhibitor or radiation alone. RPPA identified Axl as a candidate target of CDK9 inhibition. Western blot and qPCR demonstrated reduced Axl mRNA (p = 0.02) and protein levels after treatment with CDK9 inhibitor with or without radiation in FLO-1 and SKGT4 cells. Axl protein expression in FLO-1 xenografts treated with combination of CDK9 inhibitor and radiation was significantly lower than the xenografts treated with radiation alone (p = 0.003). Clonogenic assay performed after overexpression of Axl in FLO-1 and SKGT4 cells enhanced radiosensitization by the CDK9 inhibitor, suggesting dependency of radiosensitization effects of the CDK9 inhibitor on Axl. In conclusion, these findings indicate that targeting CDK9 by BAY1143572 significantly enhances the effects of radiation and Axl is a novel downstream target of CDK9 in esophageal adenocarcinoma.

Fidelity of a PDX-CR model for bladder cancer

Patient-derived xenografts (PDXs) are widely recognised as a more physiologically relevant preclinical model than standard cell lines, but are expensive and low throughput, have low engraftment rate and take a long time to develop. Our newly developed conditional reprogramming (CR) technology addresses many PDX drawbacks, but lacks many in vivo factors. Here we determined whether PDXs and CRCs of the same cancer origin maintain the biological fidelity and complement each for translational research and drug development. Four CRC lines were generated from bladder cancer PDXs. Short tandem repeat (STR) analyses revealed that CRCs and their corresponding parental PDXs shared the same STRs, suggesting common cancer origins. CRCs and their corresponding parental PDXs contained the same genetic alterations. Importantly, CRCs retained the same drug sensitivity with the corresponding downstream signalling activity as their corresponding parental PDXs. This suggests that CRCs and PDXs can complement each other, and that CRCs can be used for in vitro fast, high throughput and low cost screening while PDXs can be used for in vivo validation and study of the in vivo factors during translational research and drug development.

Pediatric leukemia: Moving toward more accurate models

Leukemia is a complex genetic disease caused by errors in differentiation, growth, and apoptosis of hematopoietic cells in either lymphoid or myeloid lineages. Large-scale genomic characterization of thousands of leukemia patients has produced a tremendous amount of data that have enabled a better understanding of the differences between adult and pediatric patients. For instance, although phenotypically similar, pediatric and adult myeloid leukemia patients differ in their mutational profiles, typically involving either chromosomal translocations or recurrent single-base-pair mutations, respectively. To elucidate the molecular mechanisms underlying the biology of this cancer, continual efforts have been made to develop more contextually and biologically relevant experimental models. Leukemic cell lines, for example, provide an inexpensive and tractable model but often fail to recapitulate critical aspects of tumor biology. Likewise, murine leukemia models of leukemia have been highly informative but also do not entirely reproduce the human disease. More recent advances in the development of patient-derived xenografts (PDXs) or human models of leukemias are poised to provide a more comprehensive, and biologically relevant, approach to directly assess the impact of the in vivo environment on human samples. In this review, the advantages and limitations of the various current models used to functionally define the genetic requirements of leukemogenesis are discussed.

Drug repurposing in oncology: Compounds, pathways, phenotypes and computational approaches for colorectal cancer

The strategy of using existing drugs originally developed for one disease to treat other indications has found success across medical fields. Such drug repurposing promises faster access of drugs to patients while reducing costs in the long and difficult process of drug development. However, the number of existing drugs and diseases, together with the heterogeneity of patients and diseases, notably including cancers, can make repurposing time consuming and inefficient. The key question we address is how to efficiently repurpose an existing drug to treat a given indication. As drug efficacy remains the main bottleneck for overall success, we discuss the need for machine-learning computational methods in combination with specific phenotypic studies along with mechanistic studies, chemical genetics and omics assays to successfully predict disease-drug pairs. Such a pipeline could be particularly important to cancer patients who face heterogeneous, recurrent and metastatic disease and need fast and personalized treatments. Here we focus on drug repurposing for colorectal cancer and describe selected therapeutics already repositioned for its prevention and/or treatment as well as potential candidates. We consider this review as a selective compilation of approaches and methodologies, and argue how, taken together, they could bring drug repurposing to the next level.

Post-neoadjuvant treatment and the management of residual disease in breast cancer: state of the art and perspectives

Achieving a pathologic complete response after neoadjuvant treatment is associated with improved prognosis in breast cancer. The CREATE-X trial demonstrated a significant survival improvement with capecitabine in patients with residual invasive disease after neoadjuvant chemotherapy, and the KATHERINE trial showed a significant benefit of trastuzumab-emtansine (TDM1) in human epidermal growth factor receptor 2 (HER2)-positive patients who did not achieve a pathologic complete response after neoadjuvant treatment, creating interesting alternatives of post-neoadjuvant treatments for high-risk patients. New agents are arising as therapeutic options for metastatic breast cancer such as the cyclin-dependent kinase inhibitors and the immune-checkpoint inhibitors, but none has been incorporated into the post-neoadjuvant setting so far. Evolving techniques such as next-generation sequencing and gene expression profiles have improved our knowledge regarding the biology of residual disease, and also on the mechanisms involved in treatment resistance. The present manuscript reviews the current available strategies, the ongoing trials, the potential biomarker-guided approaches and the perspectives for the post-neoadjuvant treatment and the management of residual disease after neoadjuvant treatment in breast cancer.

Serial patient-derived orthotopic xenografting of adenoid cystic carcinomas recapitulates stable expression of phenotypic alterations and innervation

BACKGROUND

Patient-derived xenograft (PDX) models have significantly enhanced cancer research, and often serve as a robust model. However, enhanced growth rate and altered pathological phenotype with serial passages have repeatedly been shown in adenoid cystic carcinoma (ACC) PDX tumors, which is a major concern.

METHODS

We evaluated the fidelity of ACCs in their natural habitat by performing ACC orthotopic xenotransplantation (PDOX) in salivary glands.

FINDINGS

Our PDOX model enabled solid tumors to integrate within the local epithelial, stromal and neuronal environment. Over serial passages, PDOX tumors maintained their stereotypic MYB-NFIB translocation, and FGFR2 and ATM point mutations. Tumor growth rate and histopathology were retained, including ACCs hallmark presentations of cribriform, tubular, solid areas and innervation. We also demonstrate that the PDOX model retains its capacity as a tool for drug testing.

INTERPRETATION

Unlike the precedent PDX model, our data shows that the PDOX is a superior model for future cancer biology and therapy research. FUND: This work was supported by the National Institutes of Health (NIH)/National Institute of Dental and Craniofacial Research (NIDCR) grants DE022557, DE027034, and DE027551.

Tumor Tissue Explant Culture of Patient-Derived Xenograft as Potential Prioritization Tool for Targeted Therapy

Despite of remarkable progress made in the head and neck cancer (HNC) therapy, the survival rate of this metastatic disease remain low. Tailoring the appropriate therapy to patients is a major challenge and highlights the unmet need to have a good preclinical model that will predict clinical response. Hence, we developed an accurate and time efficient drug screening method of tumor ex vivo analysis (TEVA) system, which can predict patient-specific drug responses. In this study, we generated six patient derived xenografts (PDXs) which were utilized for TEVA. Briefly, PDXs were cut into 2 × 2 × 2 mm3 explants and treated with clinically relevant drugs for 24 h. Tumor cell proliferation and death were evaluated by immunohistochemistry and TEVA score was calculated. Ex vivo and in vivo drug efficacy studies were performed on four PDXs and three drugs side-by-side to explore correlation between TEVA and PDX treatment in vivo. Efficacy of drug combinations was also ventured. Optimization of the culture timings dictated 24 h to be the time frame to detect drug responses and drug penetrates 2 × 2 × 2 mm3 explants as signaling pathways were significantly altered. Tumor responses to drugs in TEVA, significantly corresponds with the drug efficacy in mice. Overall, this low cost, robust, relatively simple and efficient 3D tissue-based method, employing material from one PDX, can bypass the necessity of drug validation in immune-incompetent PDX-bearing mice. Our data provides a potential rationale for utilizing TEVA to predict tumor response to targeted and chemo therapies when multiple targets are proposed.

Challenges in Stratifying the Molecular Variability of Patient-Derived Colon Tumor Xenografts

Colorectal cancer (CRC) is the second most common cancer in Europe and a leading cause of death worldwide. Patient-derived xenograft (PDX) models maintain complex intratumoral biology and heterogeneity and therefore remain the platform of choice for translational drug discovery. In this study, we implanted 37 primary CRC tumors and five CRC cell lines into NU/J mice to develop xenograft models. Primary tumors and established xenografts were histologically assessed and surveyed for genetic variants and gene expression using a panel of 409 cancer-related genes and RNA-seq, respectively. More than half of CRC tumors (20 out of 37, 54%) developed into a PDX. Histological assessment confirmed that PDX grading, stromal components, inflammation, and budding were consistent with those of the primary tumors. DNA sequencing identified an average of 0.14 variants per gene per sample. The percentage of mutated variants in PDXs increased with successive passages, indicating a decrease in clonal heterogeneity. Gene Ontology analyses of 4180 differentially expressed transcripts (adj. p value < 0.05) revealed overrepresentation of genes involved in cell division and catabolic processes among the transcripts upregulated in PDXs; downregulated transcripts were associated with GO terms related to extracellular matrix organization, immune responses, and angiogenesis. Neither a transcriptome-based consensus molecular subtype (CMS) classifier nor three other predictors reliably matched PDX molecular subtypes with those of the primary tumors. In sum, both genetic and transcriptomic profiles differed between donor tumors and PDXs, likely as a consequence of subclonal evolution at the early phase of xenograft development, making molecular stratification of PDXs challenging.

Tumor heterogeneity and nanoparticle-mediated tumor targeting: the importance of delivery system personalization

After the discovery of the enhanced permeability and retention effect in 1986, it was envisioned that nanoparticle-mediated tumor-targeted delivery of chemotherapeutics would make a radical change in cancer therapy. However, after three decades of extensive research, only a few nanotherapeutics have been approved for clinical use. Although significant advantages of nanomedicines have been demonstrated in pre-clinical studies, clinical outcome was found to be variable. Advanced research has revealed that significant biochemical and structural variations exist between (and among) different tumors. These variations can considerably affect the tumor delivery and efficacy of nanomedicines. Tumor penetration is an important determining factor for positive therapeutic outcome and same nanomedicine can show diverse efficacy against different tumors depending on the extent of tumor accumulation and penetration. Recent research has started shading light on how the tumor variations can influence nanoparticle tumor delivery. These findings indicate that there is no "ideal" design of nanoparticles for exhibiting equally high efficacy against a broad spectrum of tumors. For achieving maximum benefit of the nanotherapeutics, it is necessary to analyze the tumor microenvironment for understanding the biological and structural characteristics of the tumor. Designing of the nanomedicine should be done according to the tumor characteristics. In this comprehensive review, we have first given a brief overview of the design characteristics of nanomedicine which impact their tumor delivery. Then we discussed about the variability in the tumor architecture and how it influences nanomedicine delivery. Finally, we have discussed the possibility of delivery system personalization based on the tumor characteristics.

Methodology, Criteria, and Characterization of Patient-Matched Thyroid Cell Lines and Patient-Derived Tumor Xenografts

OBJECTIVE

To investigate the molecular underpinnings of thyroid cancer, preclinical cell line models are crucial; however, ∼40% of these have been proven to be either duplicates of existing thyroid lines or even nonthyroid-derived lines or are not derived from humans at all. Therefore, we set out to establish procedures and guidelines that should proactively avoid these problems, which facilitated the creation of criteria to make valid preclinical models for thyroid cancer research.

DESIGN

Based on our recommendations, we systematically characterized all new cell lines that we generated by a standardized approach that included (1) determination of human origin, (2) exclusion of lymphoma, (3) DNA fingerprinting and histological comparisons to establish linkage to presumed tissue of origin, (4) examining thyroid differentiation by screening two to three thyroid markers, (5) examination of biological behavior (growth rate, tumorigenicity), and (6) presence of common thyroid cancer genetic changes (TP53, BRAF, PTEN, PIK3CA, RAS, TERT promoter, RET/PTC, PAX8/PPARγ, NF1, and EIF1AX).

RESULTS

We established seven new thyroid cell lines (LAM136, EAM306, SDAR1, SDAR2, JEM493, THJ529, and THJ560) out of 294 primary culture attempts, and 10 patient-derived tumor xenografts (PDTXs; MC-Th-95, MC-Th-374, MC-Th-467, MC-Th-491, MC-Th-493, MC-Th-504, MC-Th-524, MC-Th-529, MC-Th-560, and MC-Th-562) out of 67 attempts. All were successfully validated by our protocols.

CONCLUSIONS

This standardized approach for cell line and PDTX characterization should prevent (or detect) future cross-contamination and ensure that only valid preclinical models are used for thyroid cancer research.

Immuno-Oncology: Emerging Targets and Combination Therapies

Host immunity recognizes and eliminates most early tumor cells, yet immunological checkpoints, exemplified by CTLA-4, PD-1, and PD-L1, pose a significant obstacle to effective antitumor immune responses. T-lymphocyte co-inhibitory pathways influence intensity, inflammation and duration of antitumor immunity. However, tumors and their immunosuppressive microenvironments exploit them to evade immune destruction. Recent PD-1 checkpoint inhibitors yielded unprecedented efficacies and durable responses across advanced-stage melanoma, showcasing potential to replace conventional radiotherapy regimens. Neverthless, many clinical problems remain in terms of efficacy, patient-to-patient variability, and undesirable outcomes and side effects. In this review, we evaluate recent advances in the immuno-oncology field and discuss ways forward. First, we give an overview of current immunotherapy modalities, involving mainy single agents, including inhibitor monoclonal antibodies (mAbs) targeting T-cell checkpoints of PD-1 and CTLA-4. However, neoantigen recognition alone cannot eliminate tumors effectively in vivo given their inherent complex micro-environment, heterogeneous nature and stemness. Then, based mainly upon CTLA-4 and PD-1 checkpoint inhibitors as a "backbone," we cover a range of emerging ("second-generation") therapies incorporating other immunotherapies or non-immune based strategies in synergistic combination. These include targeted therapies such as tyrosine kinase inhibitors, co-stimulatory mAbs, bifunctional agents, epigenetic modulators (such as inhibitors of histone deacetylases or DNA methyltransferase), vaccines, adoptive-T-cell therapy, nanoparticles, oncolytic viruses, and even synthetic "gene circuits." A number of novel immunotherapy co-targets in pre-clinical development are also introduced. The latter include metabolic components, exosomes and ion channels. We discuss in some detail of the personalization of immunotherapy essential for ultimate maximization of clinical outcomes. Finally, we outline possible future technical and conceptual developments including realistic in vitro and in vivo models and inputs from physics, engineering, and artificial intelligence. We conclude that the breadth and quality of immunotherapeutic approaches and the types of cancers that can be treated will increase significantly in the foreseeable future.

Trabectedin arrests a doxorubicin-resistant PDGFRA-activated liposarcoma patient-derived orthotopic xenograft (PDOX) nude mouse model

BACKGROUND

Pleomorphic liposarcoma (PLPS) is a rare, heterogeneous and an aggressive variant of liposarcoma. Therefore, individualized therapy is urgently needed. Our recent reports suggest that trabectedin (TRAB) is effective against several patient-derived orthotopic xenograft (PDOX) mouse models. Here, we compared the efficacy of first-line therapy, doxorubicin (DOX), and TRAB in a platelet-derived growth factor receptor-α (PDGFRA)-amplified PLPS.

METHODS

We used a fresh sample of PLPS tumor derived from a 68-year-old male patient diagnosed with a recurrent PLPS. Subcutaneous implantation of tumor tissue was performed in a nude mouse. After three weeks of implantation, tumor tissues were isolated and cut into small pieces. To match the patient a PDGFRA-amplified PLPS PDOX was created in the biceps femoris of nude mice. Mice were randomized into three groups: Group 1 (G1), control (untreated); Group 2 (G2), DOX-treated; Group 3 (G3), TRAB-treated. Measurement was done twice a week for tumor width, length, and mouse body weight.

RESULTS

The PLPS PDOX showed resistance towards DOX. However, TRAB could arrest the PLPS (p < 0.05 compared to control; p < 0.05 compared to DOX) without any significant changes in body-weight.

CONCLUSIONS

The data presented here suggest that for the individual patient the PLPS PDOX model could specifically distinguish both effective and ineffective drugs. This is especially crucial for PLPS because effective first-line therapy is harder to establish if it is not individualized.

How to find the right drug for each patient? Advances and challenges in pharmacogenomics

Cancer is a highly heterogeneous disease with complex underlying biology. For these reasons, effective cancer treatment is still a challenge. Nowadays, it is clear that a cancer therapy that fits all the cases cannot be found, and as a result the design of therapies tailored to the patient's molecular characteristics is needed. Pharmacogenomics aims to study the relationship between an individual's genotype and drug response. Scientists use different biological models, ranging from cell lines to mouse models, as proxies for patients for preclinical and translational studies. The rapid development of "-omics" technologies is increasing the amount of features that can be measured in these models, expanding the possibilities of finding predictive biomarkers of drug response. Finding these relationships requires diverse computational approaches ranging from machine learning to dynamic modeling. Despite major advances, we are still far from being able to precisely predict drug efficacy in cancer models, let alone directly on patients. We believe that the new experimental techniques and computational approaches covered in this review will bring us closer to this goal.

PATRI, a Genomics Data Integration Tool for Biomarker Discovery

The availability of genomic datasets in association with clinical, phenotypic, and drug sensitivity information represents an invaluable source for potential therapeutic applications, supporting the identification of new drug sensitivity biomarkers and pharmacological targets. Drug discovery and precision oncology can largely benefit from the integration of treatment molecular discriminants obtained from cell line models and clinical tumor samples; however this task demands comprehensive analysis approaches for the discovery of underlying data connections. Here we introduce PATRI (Platform for the Analysis of TRanslational Integrated data), a standalone tool accessible through a user-friendly graphical interface, conceived for the identification of treatment sensitivity biomarkers from user-provided genomics data, associated with information on sample characteristics. PATRI streamlines a translational analysis workflow: first, baseline genomics signatures are statistically identified, differentiating treatment sensitive from resistant preclinical models; then, these signatures are used for the prediction of treatment sensitivity in clinical samples, via random forest categorization of clinical genomics datasets and statistical evaluation of the relative phenotypic features. The same workflow can also be applied across distinct clinical datasets. The ease of use of the PATRI tool is illustrated with validation analysis examples, performed with sensitivity data for drug treatments with known molecular discriminants.

Engineering Breast Cancer Microenvironments and 3D Bioprinting

The extracellular matrix (ECM) is a critical cue to direct tumorigenesis and metastasis. Although two-dimensional (2D) culture models have been widely employed to understand breast cancer microenvironments over the past several decades, the 2D models still exhibit limited success. Overwhelming evidence supports that three dimensional (3D), physiologically relevant culture models are required to better understand cancer progression and develop more effective treatment. Such platforms should include cancer-specific architectures, relevant physicochemical signals, stromal-cancer cell interactions, immune components, vascular components, and cell-ECM interactions found in patient tumors. This review briefly summarizes how cancer microenvironments (stromal component, cell-ECM interactions, and molecular modulators) are defined and what emerging technologies (perfusable scaffold, tumor stiffness, supporting cells within tumors and complex patterning) can be utilized to better mimic native-like breast cancer microenvironments. Furthermore, this review emphasizes biophysical properties that differ between primary tumor ECM and tissue sites of metastatic lesions with a focus on matrix modulation of cancer stem cells, providing a rationale for investigation of underexplored ECM proteins that could alter patient prognosis. To engineer breast cancer microenvironments, we categorized technologies into two groups: (1) biochemical factors modulating breast cancer cell-ECM interactions and (2) 3D bioprinting methods and its applications to model breast cancer microenvironments. Biochemical factors include matrix-associated proteins, soluble factors, ECMs, and synthetic biomaterials. For the application of 3D bioprinting, we discuss the transition of 2D patterning to 3D scaffolding with various bioprinting technologies to implement biophysical cues to model breast cancer microenvironments.

Human tissue models in cancer research: looking beyond the mouse

Mouse models, including patient-derived xenograft mice, are widely used to address questions in cancer research. However, there are documented flaws in these models that can result in the misrepresentation of human tumour biology and limit the suitability of the model for translational research. A coordinated effort to promote the more widespread development and use of ‘non-animal human tissue’ models could provide a clinically relevant platform for many cancer studies, maximising the opportunities presented by human tissue resources such as biobanks. A number of key factors limit the wide adoption of non-animal human tissue models in cancer research, including deficiencies in the infrastructure and the technical tools required to collect, transport, store and maintain human tissue for lab use. Another obstacle is the long-standing cultural reliance on animal models, which can make researchers resistant to change, often because of concerns about historical data compatibility and losing ground in a competitive environment while new approaches are embedded in lab practice. There are a wide range of initiatives that aim to address these issues by facilitating data sharing and promoting collaborations between organisations and researchers who work with human tissue. The importance of coordinating biobanks and introducing quality standards is gaining momentum. There is an exciting opportunity to transform cancer drug discovery by optimising the use of human tissue and reducing the reliance on potentially less predictive animal models.

Summary: Samuel Jackson and Gareth Thomas discuss the limitations of patient-derived xenograft mouse models and highlight initiatives to maximise the use of human tissue in cancer research, with the goal of improving translation and reducing animal experimentation.

Targeting KRAS in metastatic colorectal cancer: current strategies and emerging opportunities

Developing drugs that target KRAS, the most frequently mutated oncogene in cancer, has not been successful despite much concerted efforts dedicated towards it in the last thirty years. Considering the key role this driver oncogene plays, the pharmacological drugging of KRAS remains a key challenge for cancer research. In this review, we highlight the emerging experimental strategies for blocking KRAS function and signaling and its direct targeting. We also report on the results in this field of research produced by our group.

Using PDX for Preclinical Cancer Drug Discovery: The Evolving Field

The ability to create patient derived xenografts (PDXs) has evolved considerably from the breakthrough of the development of immune compromised mice. How researchers in drug discovery have utilized PDX of certain cancer types has also changed from traditionally selecting a few models to profile a drug, to opting to assess inter-tumor response heterogeneity by screening across a broad range of tumor models, and subsequently to enable clinical stratification strategies. As with all models and methodologies, imperfections with this approach are apparent, and our understanding of the fidelity of these models continues to expand. To date though, they are still viewed as one of the most faithful modeling systems in oncology. Currently, there are many efforts ongoing to increase the utility and translatability of PDXs, including introducing a human immune component to enable immunotherapy studies.

Antitumor activity of kinetochore-associated protein 2 siRNA against lung cancer patient-derived tumor xenografts

It has been widely reported that patient-derived tumor xenografts (PDXs) are more similar to tumor tissues than conventional cancer cell lines. Kinetochore-associated protein 2 (KNTC2) is known to be upregulated specifically in tumor tissues of cancer patients and is recognized as a potential target for cancer therapy. Previously, in vivo antitumor activities of KNTC2 short interfering RNA encapsulated into a lipid nanoparticle (KNTC2-LNP) were reported in orthotopic hepatocellular carcinoma mouse models. However, it remains unclear whether KNTC2-LNP exhibits antitumor activities against lung cancer PDXs. In the present study, the antitumor activities of KNTC2-LNP were clarified in a three-dimensional culture system and a subcutaneous tumor model of lung cancer PDX, LC-60, which was resistant to erlotinib. Growth inhibitory activities of KNTC2-LNP were associated with knockdown activities. Furthermore, KNTC2-LNP also exhibited in vivo antitumor activity against another lung cancer PDX, LC-45, which was sensitive to erlotinib. These results suggest that KNTC2 is a promising target for patients with lung cancer.