Use of patient-derived xenograft mouse models in cancer research and treatment

Mimicking women's endocrine milieu in mice for women's health-related studies

To improve preclinical studies and their translation, patient-derived xenografts (PDXs) are increasingly used. They have human-specific tumor characteristics and reflect intra and inter-tumor heterogeneity. However, the endocrine milieu differs between humans and host mice. In light of sex-specific cancer biology and a rise in endocrine-related cancers there is an urgent need to correctly reflect the hormonal milieu in PDX models. We show that female mice of NOD.Cg-Prkdc scid Il2rg tm1Wjl /SzJ (NSG) strain widely used for PDXs has 17-β-estradiol (E2) and testosterone (T) levels comparable to C57Bl6 females but higher progesterone (P4) levels. E2 levels are comparable, T levels are lower and P4 levels higher than those observed in postmenopausal women. Ovariectomy increases T to levels observed in postmenopausal women. Subcutaneous E2 and combined E2/P4 silicon pellets provide NSG females with premenopausal ovarian hormone levels. These procedures humanize the endocrine environment of experimental animals, improving PDX relevance in women's health-related research.

Optimizing Xenograft Models for Breast Cancer: A Comparative Analysis of Cell-Derived and Patient-Derived Implantation Techniques in Pre-Clinical Research

Purpose

The high mortality rate of breast cancer motivates researchers to search for effective treatments. Due to their ability to simulate human conditions, xenograft models such as CDX (Cell line-Derived Xenografts) and PDX (Patient-Derived Xenografts) have gained popularity in pre-clinical research. The choice of xenograft technique is influenced by the type of tumor employed, particularly in more aggressive tumor models like TNBC with metastases. Subcutaneous or orthotopic implantation may influence tumor engraftment rates and the applicability of the models for drug testing. To optimize xenograft models and support the development of breast cancer drugs, selecting a suitable transplantation technique is essential to attaining the best results.

Methods

This scoping review used PRISMA-Scr methodology to summarize findings from eleven articles published between 2012 and 2024 on pre-clinical trials related to xenograft models for breast cancer considering PDX began traction after 2010. Using specific criteria, the review included studies from electronic platforms. The inclusion criteria ensured relevant English sources were available in full text, while the exclusion criteria eliminated certain types of articles and inadequately comprehensive studies.

Results

Subcutaneous and orthotopic implantation are critical methods for xenograft models in cancer research. Subcutaneous implantation is less invasive and more manageable but does not fully mimic the tumor's natural environment. Orthotopic implantation accurately mimic the migration, invasion, and molecular characteristics of the original tumor, although the procedure is more complex and requires specialized techniques. The specific research objectives determine their choice, the need for accurate tumor replication, and the testing convenience.

Conclusion

Orthotopic implantation is the preferable method for developing PDX and CDX models of breast cancer because it closely mimics the tumor microenvironment and metastatic behavior, yielding clinically relevant results for drug testing. Subcutaneous implantation may result in higher engraftment rates, but it cannot accurately represent the complexity of tumors.

Mimicking and analyzing the tumor microenvironment

The tumor microenvironment (TME) is increasingly appreciated to play a decisive role in cancer development and response to therapy in all solid tumors. Hypoxia, acidosis, high interstitial pressure, nutrient-poor conditions, and high cellular heterogeneity of the TME arise from interactions between cancer cells and their environment. These properties, in turn, play key roles in the aggressiveness and therapy resistance of the disease, through complex reciprocal interactions between the cancer cell genotype and phenotype, and the physicochemical and cellular environment. Understanding this complexity requires the combination of sophisticated cancer models and high-resolution analysis tools. Models must allow both control and analysis of cellular and acellular TME properties, and analyses must be able to capture the complexity at high depth and spatial resolution. Here, we review the advantages and limitations of key models and methods in order to guide further TME research and outline future challenges.

Understanding the Interplay of CAR-NK Cells and Triple-Negative Breast Cancer: Insights from Computational Modeling

Chimeric antigen receptor (CAR)-engineered natural killer (NK) cells have recently emerged as a promising and safe alternative to CAR-T cells for targeting solid tumors. In the case of triple-negative breast cancer (TNBC), traditional cancer treatments and common immunotherapies have shown limited effectiveness. However, CAR-NK cells have been successfully employed to target epidermal growth factor receptor (EGFR) on TNBC cells, thereby enhancing the efficacy of immunotherapy. The effectiveness of CAR-NK-based immunotherapy is influenced by various factors, including the vaccination dose, vaccination pattern, and tumor immunosuppressive factors in the microenvironment. To gain insights into the dynamics and effects of CAR-NK-based immunotherapy, we propose a computational model based on experimental data and immunological theories. This model integrates an individual-based model that describes the interplay between the tumor and the immune system, along with an ordinary differential equation model that captures the variation of inflammatory cytokines. Computational results obtained from the proposed model shed light on the conditions necessary for initiating an effective anti-tumor response. Furthermore, global sensitivity analysis highlights the issue of low persistence of CAR-NK cells in vivo, which poses a significant challenge for the successful clinical application of these cells. Leveraging the model, we identify the optimal vaccination time, vaccination dose, and time interval between injections for maximizing therapeutic outcomes.

3D cancer models: One step closer to in vitro human studies

Cancer immunotherapy is the great breakthrough in cancer treatment as it displayed prolonged progression-free survival over conventional therapies, yet, to date, in only a minority of patients. In order to broad cancer immunotherapy clinical applicability some roadblocks need to be overcome, first among all the lack of preclinical models that faithfully depict the local tumor microenvironment (TME), which is known to dramatically affect disease onset, progression and response to therapy. In this review, we provide the reader with a detailed overview of current 3D models developed to mimick the complexity and the dynamics of the TME, with a focus on understanding why the TME is a major target in anticancer therapy. We highlight the advantages and translational potentials of tumor spheroids, organoids and immune Tumor-on-a-Chip models in disease modeling and therapeutic response, while outlining pending challenges and limitations. Thinking forward, we focus on the possibility to integrate the know-hows of micro-engineers, cancer immunologists, pharmaceutical researchers and bioinformaticians to meet the needs of cancer researchers and clinicians interested in using these platforms with high fidelity for patient-tailored disease modeling and drug discovery.

Comparison of classical tumour growth models for patient derived and cell-line derived xenografts using the nonlinear mixed-effects framework

In this study we compare seven mathematical models of tumour growth using nonlinear mixed-effects which allows for a simultaneous fitting of multiple data and an estimation of both mean behaviour and variability. This is performed for two large datasets, a patient-derived xenograft (PDX) dataset consisting of 220 PDXs spanning six different tumour types and a cell-line derived xenograft (CDX) dataset consisting of 25 cell lines spanning eight tumour types. Comparison of the models is performed by means of visual predictive checks (VPCs) as well as the Akaike Information Criterion (AIC). Additionally, we fit the models to 500 bootstrap samples drawn from the datasets to expand the comparison of the models under dataset perturbations and understand the growth kinetics that are best fitted by each model. Through qualitative and quantitative metrics the best models are identified the effectiveness and practicality of simpler models is highlighted.

Possible Role of Cytochrome P450 1B1 in the Mechanism of Gemcitabine Resistance in Pancreatic Cancer

Patient-derived xenograft models reportedly represent original tumor morphology and gene mutation profiles. In addition, patient-derived xenografts are expected to recapitulate the parental tumor drug responses. In this study, we analyzed the pathways involved in gemcitabine resistance using patient-derived xenograft models of pancreatic cancer. The patient-derived xenograft models were established using samples from patients with pancreatic cancer. The models were treated with gemcitabine to better understand the mechanism of resistance to this anti-cancer drug. We performed comparative gene analysis through the next-generation sequencing of tumor tissues from gemcitabine-treated or non-treated patient-derived xenograft mice and gene set enrichment analysis to analyze mRNA profiling data. Pathway analysis of gemcitabine-treated patient-derived xenografts disclosed the upregulation of multiple gene sets and identified several specific gene pathways that could potentially be related to gemcitabine resistance in pancreatic cancer. Further, we conducted an in vitro analysis to validate these results. The mRNA expression of cytochrome P450 1B1 and cytochrome P450 2A6 was upregulated in a concentration-dependent manner following gemcitabine treatment. Moreover, the sensitivity to gemcitabine increased, and viable cells were decreased by the cytochrome P450 1B1 inhibitor, indicating that the cytochrome P450 1B1 pathway may be related to gemcitabine resistance in pancreatic cancer.

Unbiased Label-Free Quantitative Proteomics of Cells Expressing Amyotrophic Lateral Sclerosis (ALS) Mutations in CCNF Reveals Activation of the Apoptosis Pathway: A Workflow to Screen Pathogenic Gene Mutations

The past decade has seen a rapid acceleration in the discovery of new genetic causes of ALS, with more than 20 putative ALS-causing genes now cited. These genes encode proteins that cover a diverse range of molecular functions, including free radical scavenging (e.g., SOD1), regulation of RNA homeostasis (e.g., TDP-43 and FUS), and protein degradation through the ubiquitin-proteasome system (e.g., ubiquilin-2 and cyclin F) and autophagy (TBK1 and sequestosome-1/p62). It is likely that the various initial triggers of disease (either genetic, environmental and/or gene-environment interaction) must converge upon a common set of molecular pathways that underlie ALS pathogenesis. Given the complexity, it is not surprising that a catalog of molecular pathways and proteostasis dysfunctions have been linked to ALS. One of the challenges in ALS research is determining, at the early stage of discovery, whether a new gene mutation is indeed disease-specific, and if it is linked to signaling pathways that trigger neuronal cell death. We have established a proof-of-concept proteogenomic workflow to assess new gene mutations, using CCNF (cyclin F) as an example, in cell culture models to screen whether potential gene candidates fit the criteria of activating apoptosis. This can provide an informative and time-efficient output that can be extended further for validation in a variety of in vitro and in vivo models and/or for mechanistic studies. As a proof-of-concept, we expressed cyclin F mutations (K97R, S195R, S509P, R574Q, S621G) in HEK293 cells for label-free quantitative proteomics that bioinformatically predicted activation of the neuronal cell death pathways, which was validated by immunoblot analysis. Proteomic analysis of induced pluripotent stem cells (iPSCs) derived from patient fibroblasts bearing the S621G mutation showed the same activation of these pathways providing compelling evidence for these candidate gene mutations to be strong candidates for further validation and mechanistic studies (such as E3 enzymatic activity assays, protein-protein and protein-substrate studies, and neuronal apoptosis and aberrant branching measurements in zebrafish). Our proteogenomics approach has great utility and provides a relatively high-throughput screening platform to explore candidate gene mutations for their propensity to cause neuronal cell death, which will guide a researcher for further experimental studies.

3D Cancer Models: The Need for a Complex Stroma, Compartmentalization and Stiffness

The use of tissue-engineered 3D models of cancer has grown in popularity with recent advances in the field of cancer research. 3D models are inherently more biomimetic compared to 2D cell monolayers cultured on tissue-culture plastic. Nevertheless 3D models still lack the cellular and matrix complexity of native tissues. This review explores different 3D models currently used, outlining their benefits and limitations. Specifically, this review focuses on stiffness and collagen density, compartmentalization, tumor-stroma cell population and extracellular matrix composition. Furthermore, this review explores the methods utilized in different models to directly measure cancer invasion and growth. Of the models evaluated, with PDX and in vivo as a relative "gold standard", tumoroids were deemed as comparable 3D cancer models with a high degree of biomimicry, in terms of stiffness, collagen density and the ability to compartmentalize the tumor and stroma. Future 3D models for different cancer types are proposed in order to improve the biomimicry of cancer models used for studying disease progression.

Recent progress in translational engineered in vitro models of the central nervous system

The complexity of the human brain poses a substantial challenge for the development of models of the CNS. Current animal models lack many essential human characteristics (in addition to raising operational challenges and ethical concerns), and conventional in vitro models, in turn, are limited in their capacity to provide information regarding many functional and systemic responses. Indeed, these challenges may underlie the notoriously low success rates of CNS drug development efforts. During the past 5 years, there has been a leap in the complexity and functionality of in vitro systems of the CNS, which have the potential to overcome many of the limitations of traditional model systems. The availability of human-derived induced pluripotent stem cell technology has further increased the translational potential of these systems. Yet, the adoption of state-of-the-art in vitro platforms within the CNS research community is limited. This may be attributable to the high costs or the immaturity of the systems. Nevertheless, the costs of fabrication have decreased, and there are tremendous ongoing efforts to improve the quality of cell differentiation. Herein, we aim to raise awareness of the capabilities and accessibility of advanced in vitro CNS technologies. We provide an overview of some of the main recent developments (since 2015) in in vitro CNS models. In particular, we focus on engineered in vitro models based on cell culture systems combined with microfluidic platforms (e.g. 'organ-on-a-chip' systems). We delve into the fundamental principles underlying these systems and review several applications of these platforms for the study of the CNS in health and disease. Our discussion further addresses the challenges that hinder the implementation of advanced in vitro platforms in personalized medicine or in large-scale industrial settings, and outlines the existing differentiation protocols and industrial cell sources. We conclude by providing practical guidelines for laboratories that are considering adopting organ-on-a-chip technologies.

Cellular and Molecular Progression of Prostate Cancer: Models for Basic and Preclinical Research

Simple Summary

The molecular progression of prostate cancer is complex and elusive. Biological research relies heavily on in vitro and in vivo models that can be used to examine gene functions and responses to the external agents in laboratory and preclinical settings. Over the years, several models have been developed and found to be very helpful in understanding the biology of prostate cancer. Here we describe these models in the context of available information on the cellular and molecular progression of prostate cancer to suggest their potential utility in basic and preclinical prostate cancer research. The information discussed herein should serve as a hands-on resource for scholars engaged in prostate cancer research or to those who are making a transition to explore the complex biology of prostate cancer.

Abstract

We have witnessed noteworthy progress in our understanding of prostate cancer over the past decades. This basic knowledge has been translated into efficient diagnostic and treatment approaches leading to the improvement in patient survival. However, the molecular pathogenesis of prostate cancer appears to be complex, and histological findings often do not provide an accurate assessment of disease aggressiveness and future course. Moreover, we also witness tremendous racial disparity in prostate cancer incidence and clinical outcomes necessitating a deeper understanding of molecular and mechanistic bases of prostate cancer. Biological research heavily relies on model systems that can be easily manipulated and tested under a controlled experimental environment. Over the years, several cancer cell lines have been developed representing diverse molecular subtypes of prostate cancer. In addition, several animal models have been developed to demonstrate the etiological molecular basis of the prostate cancer. In recent years, patient-derived xenograft and 3-D culture models have also been created and utilized in preclinical research. This review is an attempt to succinctly discuss existing information on the cellular and molecular progression of prostate cancer. We also discuss available model systems and their tested and potential utility in basic and preclinical prostate cancer research.

High expression levels of polymeric immunoglobulin receptor are correlated with chemoresistance and poor prognosis in pancreatic cancer

Pancreatic cancer has extremely poor prognosis, warranting the discovery of novel therapeutic and prognostic markers. The expression of polymeric immunoglobulin receptor (pIgR), a key component of the mucosal immune system, is increased in several cancers. However, its clinical relevance in pancreatic cancer remains unclear. In the present study, the prognostic value of pIgR in pancreatic cancer patients after surgical resection was assessed and it was determined that the expression of pIgR was correlated with poor prognosis. Ten pancreatic cancer patient‑derived xenograft (PDX) lines were established, followed by next‑generation sequencing of tumor tissues from these lines after standard chemotherapy. Immunohistochemical analysis of chemoresistance‑related molecules using 77 pancreatic cancer tissues was also performed. The expression of pIgR mRNA in the PDX group treated with anticancer drugs was higher than in the untreated group. High pIgR expression in tissue specimens from 77 pancreatic cancer patients was significantly associated with poor prognosis and was revealed to be an independent prognostic factor, predicting poor outcomes. High pIgR mRNA and protein levels were independent prognostic factors, indicating that pIgR could be a novel predictor for poor prognosis of pancreatic cancer patients.

Functional Interplay Between Collagen Network and Cell Behavior Within Tumor Microenvironment in Colorectal Cancer

Colorectal cancer is the second most common cancer diagnosed in men and the third most commonly occurring in women worldwide. Interactions between cells and the surrounding extracellular matrix (ECM) are involved in tumor development and progression of many types of cancer. The organization of the ECM molecules provides not only physical scaffoldings and dynamic network into which cells are embedded but also allows the control of many cellular behaviors including proliferation, migration, differentiation, and survival leading to homeostasis and morphogenesis regulation. Modifications of ECM composition and mechanical properties during carcinogenesis are critical for tumor initiation and progression. The core matrisome consists of five classes of macromolecules, which are collagens, laminins, fibronectin, proteoglycans, and hyaluronans. In most tissues, fibrillar collagen is the major component of ECM. Cells embedded into fibrillar collagen interact with it through their surface receptors, such as integrins and discoidin domain receptors (DDRs). On the one hand, cells incorporate signals from ECM that modify their functionalities and behaviors. On the other hand, all cells within tumor environment (cancer cells, cancer-associated fibroblasts, endothelial cells, and immune cells) synthesize and secrete matrix macromolecules under the control of multiple extracellular signals. This cell-ECM dialog participates in a dynamic way in ECM formation and its biophysical and biochemical properties. Here, we will review the functional interplay between cells and collagen network within the tumor microenvironment during colorectal cancer progression.

Differential effects of thymoquinone on lysophosphatidic acid-induced oncogenic pathways in ovarian cancer cells

Thymoquinone, a therapeutic phytochemical derived from Nigella sativa, has been shown to have a potent anticancer activity. However, it has been identified that the tumor microenvironment (TME) can attenuate the anticancer effects of thymoquinone (TQ) in ovarian cancer. Lysophosphatidic acid (LPA), a lipid growth factor present in high concentration in the TME of ovarian cancer, has been shown to regulate multiple oncogenic pathways in ovarian cancer. Taking account of the crucial role of LPA in the genesis and progression of ovarian cancer, the present study is focused on assessing the efficacy of TQ in inhibiting LPA-stimulated oncogenic pathways in ovarian cancer cells. Our results indicate that TQ is unable to attenuate LPA-stimulated proliferation or metabolic reprogramming in ovarian cancer cells. However, TQ potently inhibits the basal as well as LPA-stimulated migratory responses of the ovarian cancer cells. Furthermore, TQ abrogates the invasive migration of ovarian cancer cells induced by Gαi2, through which LPA stimulates cell migration. TQ also attenuates the activation of JNK, Src, and FAK, the downstream signaling nodes of LPA-LPAR-Gαi2 signaling pathway. In addition to establishing the differential effects of TQ in ovarian cancer cells, our results unravel the antitherapeutic role of LPA in the ovarian cancer TME could override the inhibitory effects of TQ on cell proliferation and metabolic reprogramming of ovarian cancer cells. More importantly, the concomitant finding that TQ could still sustain its inhibitory effect on LPA-stimulated invasive cell migration, points to its potential use as a response-specific therapeutic agent in ovarian cancer.

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LPA, present in the TME of ovarian cancer, plays a determinant role in limiting the anti-oncogenic efficacy of TQ.

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TQ has no inhibitory effect on LPA-stimulated oncogenic cell proliferation and metabolic reprogramming.

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However, TQ potently inhibits both the basal and LPA- or the downstream Gαi2-induced invasive migration ovarian cancer cells.

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Corollary to these findings, TQ also inhibits JNK, Src, and FAK that are involved in LPA-induced invasive cell migration.

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These findings identify the potential of TQ as a response-specific therapeutic phytochemical in vivo.

Genetically Engineered Pigs to Study Cancer

Recent decades have seen groundbreaking advances in cancer research. Genetically engineered animal models, mainly in mice, have contributed to a better understanding of the underlying mechanisms involved in cancer. However, mice are not ideal for translating basic research into studies closer to the clinic. There is a need for complementary information provided by non-rodent species. Pigs are well suited for translational biomedical research as they share many similarities with humans such as body and organ size, aspects of anatomy, physiology and pathophysiology and can provide valuable means of developing and testing novel diagnostic and therapeutic procedures. Porcine oncology is a new field, but it is clear that replication of key oncogenic mutation in pigs can usefully mimic several human cancers. This review briefly outlines the technology used to generate genetically modified pigs, provides an overview of existing cancer models, their applications and how the field may develop in the near future.

High expression of olfactomedin-4 is correlated with chemoresistance and poor prognosis in pancreatic cancer

Pancreatic cancer has an extremely poor prognosis, and identification of novel predictors of therapeutic efficacy and prognosis is urgently needed. Chemoresistance-related molecules are correlated with poor prognosis and may be effective targets for cancer treatment. Here, we aimed to identify novel molecules correlated with chemoresistance and poor prognosis in pancreatic cancer. We established 10 patient-derived xenograft (PDX) lines from patients with pancreatic cancer and performed next-generation sequencing (NGS) of tumor tissues from PDXs after treatment with standard drugs. We established a gene-transferred tumor cell line to express chemoresistance-related molecules and analyzed the chemoresistance of the established cell line against standard drugs. Finally, we performed immunohistochemical (IHC) analysis of chemoresistance-related molecules using 80 pancreatic cancer tissues. From NGS analysis, we identified olfactomedin-4 (OLFM4) as having high expression in the PDX group treated with anticancer drugs. In IHC analysis, OLFM4 expression was also high in PDXs administered anticancer drugs compared with that in untreated PDXs. Chemoresistance was observed by in vitro analysis of tumor cell lines with forced expression of OLFM4. In an assessment of tissue specimens from 80 patients with pancreatic cancer, Kaplan-Meier analysis showed that patients in the low OLFM4 expression group had a better survival rate than patients in the high OLFM4 expression group. Additionally, multivariate analysis showed that high expression of OLFM4 was an independent prognostic factor predicting poor outcomes. Overall, our study revealed that high expression of OLFM4 was involved in chemoresistance and was an independent prognostic factor in pancreatic cancer. OLFM4 may be a candidate therapeutic target in pancreatic cancer.

Patient-derived xenograft models-the future of personalised cancer treatment

For many tumours there is a lack of randomised data from which we can guide systemic treatments. Although gene expression profiling along with proteomics has led to advances in diagnosis, classification and prognosis, our ability to target many cancers has been further limited due to a lack of therapeutic options. The use of patient-derived xenograft (PDX) models in the setting of a rare malignancy is discussed here by Kamili et al, with the successful establishment of new model systems.

Animal Models to Study Cancer and Its Microenvironment

Cancers are complex tissues composed by genetically altered cancer cells and stromal elements such as inflammatory/immune cells, fibroblasts, endothelial cells and pericytes, neuronal cells, and a non-cellular component, the extracellular matrix. The complex network of interactions and crosstalk established between cancer cells and the supportig cellular and non-cellular components of the microenvironment are of extreme importance for tumor initiation and progression, strongly impacting the course and the outcome of the disease. Therefore, a better understanding of the tumorigenic processes implies the combined study of the cancer cell and the biologic, chemical and mechanic constituents of the tumor microenvironment, as their concerted action plays a major role in the carcinogenic pathway and is a key determinant of the efficacy of anti-cancer treatments. The use of animal models (e.g. Mouse, Zebrafish and Drosophila) to study cancer has greatly impacted our understanding of the processes governing initiation, progression and metastasis and allowed the discovery and pre-clinical validation of novel cancer treatments as it allows to recreate tumor development in a more pathophysiologic environment.

Chimeric Antigen Receptor-T Cells for Targeting Solid Tumors: Current Challenges and Existing Strategies

Chimeric antigen receptor-T cells (CAR-Ts) are an exciting new cancer treatment modality exemplified by the recent regulatory approval of two CD19-targeted CAR-T therapies for certain B cell malignancies. However, this success in the hematological setting has yet to translate to a significant level of objective clinical responses in the solid tumor setting. The reason for this lack of translation undoubtedly lies in the substantial challenges raised by solid tumors to all therapies, including CAR-T, that differ from B cell malignancies. For instance, intravenously infused CAR-Ts are likely to make rapid contact with cancerous B cells since both tend to reside in the same vascular compartments within the body. By contrast, solid cancers tend to form discrete tumor masses with an immune-suppressive tumor microenvironment composed of tumor cells and non-tumor stromal cells served by abnormal vasculature that restricts lymphocyte infiltration and suppresses immune function, expansion, and persistence. Moreover, the paucity of uniquely and homogeneously expressed tumor antigens and inherent plasticity of cancer cells provide major challenges to the specificity, potency, and overall effectiveness of CAR-T therapies. This review focuses on the major preclinical and clinical strategies currently being pursued to tackle these challenges in order to drive the success of CAR-T therapy against solid tumors.

Cancer invasion regulates vascular complexity in a three-dimensional biomimetic model

INTRODUCTION

There is a growing appreciation for including a complex, vascularised stroma in three-dimensional (3D) tumour models to recapitulate the native tumour microenvironment in situ.

METHODS

Using a compartmentalised, biomimetic, 3D cancer model, comprising a central cancer mass surrounded by a vascularised stroma, we have tested the invasive capability of colorectal cancer cells.

RESULTS

We show histological analysis of dense collagen I/laminin scaffolds, forming necrotic cores with cellular debris. Furthermore, cancer cells within this 3D matrix form spheroids, which is corroborated with high EpCAM expression. We validate the invasive growth of cancer cells into the stroma through quantitative image analysis and upregulation of known invasive gene markers, including metastasis associated in colon cancer 1, matrix metalloproteinase 7 and heparinase. Tumouroids containing highly invasive HCT116 cancer masses form less complex and less branched vascular networks, recapitulating 'leaky' vasculature associated with highly metastatic cancers. Angiogenic factors regulating this were vascular endothelial growth factor A and hepatocyte growth factor active protein. Where vascular networks were formed with less invasive cancer masses (HT29), higher expression of vascular endothelial cadherin active protein resulted in more complex and branched networks. To eliminate the cell-cell interaction between the cancer mass and stroma, we developed a three-compartment model containing an acellular ring to test the chemoattractant pull from the cancer mass. This resulted in migration of endothelial networks through the acellular ring accompanied by alignment of vascular networks at the cancer/stroma boundary.

DISCUSSION

This work interrogates to the gene and protein level how cancer cells influence the development of a complex stroma, which shows to be directly influenced by the invasive capability of the cancer.

Advances in personalized treatment of metastatic spine disease

The spine is one of the most common sites of bony metastases, and its involvement leads to significant patient morbidity. Surgical management in these patients is aimed at improving quality of life and functional status throughout the course of the disease. Resection of metastases often leads to critical size bone defects, presenting a challenge to achieving adequate bone regeneration to fill the void. Current treatment options for repairing these defects are bone grafting and commercial bone cements; however, each has associated limitations. Additionally, tumor recurrence and tumor-induced bone loss make bone regeneration particularly difficult. Systemic therapeutic delivery, such as bisphosphonates, have become standard of care to combat bone loss despite unfavorable systemic side-effects and lack of local efficacy. Developments from tissue engineering have introduced novel materials with osteoinductive and osteoconductive properties which also act as structural support scaffolds for bone regeneration. These new materials can also act as a therapeutic reservoir to sustainably release drugs locally as an alternative to systemic therapy. In this review, we outline recent advancements in tissue engineering and the role of translational research in developing implants that can fully repair bone defects while also delivering local therapeutics to curb tumor recurrence and improve patient quality of life.

Towards precision medicine: advances in 5-hydroxymethylcytosine cancer biomarker discovery in liquid biopsy

Robust and clinically convenient biomarkers for cancer diagnosis, early detection, and prognosis have great potential to improve patient survival and are the key to precision medicine. The advent of next-generation sequencing technologies enables a more sensitive and comprehensive profiling of genetic and epigenetic information in tumor-derived materials. Researchers are now able to monitor the dynamics of tumorigenesis in new dimensions, such as using circulating cell-free DNA (cfDNA) and tumor DNA (ctDNA). Mutation-based assays in liquid biopsy cannot always provide consistent results across studies due partly to intra- and inter-tumoral heterogeneity as well as technical limitations. In contrast, epigenetic analysis of patient-derived cfDNA is a promising alternative, especially for early detection and disease surveillance, because epigenetic modifications are tissue-specific and reflect the dynamic process of cancer progression. Therefore, cfDNA-based epigenetic assays are emerging to be a highly sensitive, minimally invasive tool for cancer diagnosis and prognosis with great potential in future precise care of cancer patients. The major obstacle for applying epigenetic analysis of cfDNA, however, has been the lack of enabling techniques with high sensitivity and technical robustness. In this review, we summarized the advances in epigenome-wide profiling of 5-hydroxymethylcytosine (5hmC) in cfDNA, focusing on the detection approaches and potential role as biomarkers in different cancer types.

[Tumor banks and complex data management: Current and future challenges]

Tumor banks are asked to clinical and translationnal research project development in oncology. They strongly participate to the assessment, then to the validation of diagnostic, prognostic and predictive biomarkers. The progressive change of these structures leads to induce a professionalization of their functioning and to identify them as key actors in oncology by the stakeholders of the public and private worlds. The progresses made in biotechnologies and therapeutics are rapidly modifying the impact and the proper functioning of the biobanks. These latter are now facing different challenges, in particular for their sustainability. Among the major issues, the integration of the clinical and biological data becoming increasingly complex leads to urgently consider an optimization of the role of different biobanks in France. Their goal is to be an attractive counterpart face to the international competition. The purpose of this review is to briefly describe the current evolution of the biobanks, then their present and future challenges, and finally the role made by the pathologists in these new issues in oncology field.

Murine models based on acute myeloid leukemia-initiating stem cells xenografting

Acute myeloid leukemia (AML) is an aggressive malignant disease defined by abnormal expansion of myeloid blasts. Despite recent advances in understanding AML pathogenesis and identifying their molecular subtypes based on somatic mutations, AML is still characterized by poor outcomes, with a 5-year survival rate of only 30%-40%, the majority of the patients dying due to AML relapse. Leukemia stem cells (LSC) are considered to be at the root of chemotherapeutic resistance and AML relapse. Although numerous studies have tried to better characterize LSCs in terms of surface and molecular markers, a specific marker of LSC has not been found, and still the most universally accepted phenotypic signature remains the surface antigens CD34+CD38- that is shared with normal hematopoietic stem cells. Animal models provides the means to investigate the factors responsible for leukemic transformation, the intrinsic differences between secondary post-myeloproliferative neoplasm AML and de novo AML, especially the signaling pathways involved in inflammation and hematopoiesis. However, AML proved to be one of the hematological malignancies that is difficult to engraft even in the most immunodeficient mice strains, and numerous ongoing attempts are focused to develop "humanized mice" that can support the engraftment of LSC. This present review is aiming to introduce the field of AML pathogenesis and the concept of LSC, to present the current knowledge on leukemic blasts surface markers and recent attempts to develop best AML animal models.