Translational value of mouse models in oncology drug development

Direct visualization of emergent metastatic features within an ex vivo model of the tumor microenvironment

Metabolic conditions such as hypoxia, nutrient starvation, and media acidification, together with interactions with stromal cells are critical drivers of metastasis. Since these conditions arise deep within tumor tissues with poor access to the bloodstream, the observation of nascent metastases in vivo is exceedingly challenging. On the other hand, conventional cell culture studies cannot capture the complex nature of metastatic processes. We thus designed and implemented an ex vivo model of the tumor microenvironment to study the emergence of metastatic features in tumor cells in their native 3-dimensional (3D) context. In this system, named 3MIC, tumor cells spontaneously create ischemic-like conditions, and it allows the direct visualization of tumor-stroma interactions with high spatial and temporal resolution. We studied how 3D tumor spheroids evolve in the 3MIC when cultured under different metabolic environments and in the presence or absence of stromal cells. Consistent with previous experimental and clinical data, we show that ischemic environments increase cell migration and invasion. Importantly, the 3MIC allowed us to directly observe the emergence of these pro-metastatic features with single-cell resolution allowing us to track how changes in tumor motility were modulated by macrophages and endothelial cells. With these tools, we determined that the acidification of the extracellular media was more important than hypoxia in the induction of pro-metastatic tumor features. We also illustrate how the 3MIC can be used to test the effects of anti-metastatic drugs on cells experiencing different metabolic conditions. Overall, the 3MIC allows us to directly observe the emergence of metastatic tumor features in a physiologically relevant model of the tumor microenvironment. This simple and cost-effective system can dissect the complexity of the tumor microenvironment to test perturbations that may prevent tumors from becoming metastatic.

Bioprinted research models of urological malignancy

Urological malignancy (UM) is among the leading threats to health care worldwide. Recent years have seen much investment in fundamental UM research, including mechanistic investigation, early diagnosis, immunotherapy, and nanomedicine. However, the results are not fully satisfactory. Bioprinted research models (BRMs) with programmed spatial structures and functions can serve as powerful research tools and are likely to disrupt traditional UM research paradigms. Herein, a comprehensive review of BRMs of UM is presented. It begins with a brief introduction and comparison of existing UM research models, emphasizing the advantages of BRMs, such as modeling real tissues and organs. Six kinds of mainstream bioprinting techniques used to fabricate such BRMs are summarized with examples. Thereafter, research advances in the applications of UM BRMs, such as culturing tumor spheroids and organoids, modeling cancer metastasis, mimicking the tumor microenvironment, constructing organ chips for drug screening, and isolating circulating tumor cells, are comprehensively discussed. At the end of this review, current challenges and future development directions of BRMs and UM are highlighted from the perspective of interdisciplinary science.

Mathematical Modeling of Tumor Growth in Preclinical Mouse Models with Applications in Biomarker Discovery and Drug Mechanism Studies

Oncology drug efficacy is evaluated in mouse models by continuously monitoring tumor volumes, which can be mathematically described by growth kinetic models. Although past studies have investigated various growth models, their reliance on small datasets raises concerns about whether their findings are truly representative of tumor growth in diverse mouse models under different vehicle or drug treatments. In this study, we systematically evaluated six parametric models (exponential, exponential quadratic, monomolecular, logistic, Gompertz, and von Bertalanffy) and the semiparametric generalized additive model (GAM) on fitting tumor volume data from more than 30,000 mice in 930 experiments conducted in patient-derived xenografts, cell line-derived xenografts, and syngeneic models. We found that the exponential quadratic model is the best parametric model and can adequately model 87% studies, higher than other models including von Bertalanffy (82%) and Gompertz (80%) models; the latter is often considered the standard growth model. At the mouse group level, 7.5% of growth data could not be fit by any parametric model and were fitted by GAM. We show that endpoint gain integrated in time, a GAM-derived efficacy metric, is equivalent to exponential growth rate, a metric we previously proposed and conveniently calculated by simple algebra. Using five studies on paclitaxel, anti-PD1 antibody, cetuximab, irinotecan, and sorafenib, we showed that exponential and exponential quadratic models achieve similar performance in uncovering drug mechanism and biomarkers. We also compared exponential growth rate-based association analysis and exponential modeling approach in biomarker discovery and found that they complement each other. Modeling methods herein are implemented in an open-source R package freely available at https://github.com/hjzhou988/TuGroMix.

SIGNIFICANCE

We present a general strategy for mathematically modeling tumor growth in mouse models using data from 30,000 mice and show that modeling and nonmodeling approaches are complementary in biomarker discovery and drug mechanism studies.

Preclinical human and murine models of hepatocellular carcinoma (HCC)

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

Unconventional mechanism of action and resistance to rapalogs in renal cancer

mTORC1 is aberrantly activated in renal cell carcinoma (RCC) and is targeted by rapalogs. As for other targeted therapies, rapalogs clinical utility is limited by the development of resistance. Resistance often results from target mutation, but mTOR mutations are rarely found in RCC. As in humans, prolonged rapalog treatment of RCC tumorgrafts (TGs) led to resistance. Unexpectedly, explants from resistant tumors became sensitive both in culture and in subsequent transplants in mice. Notably, resistance developed despite persistent mTORC1 inhibition in tumor cells. In contrast, mTORC1 became reactivated in the tumor microenvironment (TME). To test the role of the TME, we engineered immunocompromised recipient mice with a resistance mTOR mutation (S2035T). Interestingly, TGs became resistant to rapalogs in mTORS2035T mice. Resistance occurred despite mTORC1 inhibition in tumor cells and could be induced by coculturing tumor cells with mutant fibroblasts. Thus, enforced mTORC1 activation in the TME is sufficient to confer resistance to rapalogs. These studies highlight the importance of mTORC1 inhibition in nontumor cells for rapalog antitumor activity and provide an explanation for the lack of mTOR resistance mutations in RCC patients.

Emerging Targets and Therapeutics in Immuno-Oncology: Insights from Landscape Analysis

In the ever-evolving landscape of cancer research, immuno-oncology stands as a beacon of hope, offering novel avenues for treatment. This study capitalizes on the vast repository of immuno-oncology-related scientific documents within the CAS Content Collection, totaling over 350,000, encompassing journals and patents. Through a pioneering approach melding natural language processing with the CAS indexing system, we unveil over 300 emerging concepts, depicted in a comprehensive "Trend Landscape Map". These concepts, spanning therapeutic targets, biomarkers, and types of cancers among others, are hierarchically organized into eight major categories. Delving deeper, our analysis furnishes detailed quantitative metrics showcasing growth trends over the past three years. Our findings not only provide valuable insights for guiding future research endeavors but also underscore the merit of tapping the vast and unparalleled breadth of existing scientific information to derive profound insights.

Exploring tumor organoids for cancer treatment

As a life-threatening chronic disease, cancer is characterized by tumor heterogeneity. This heterogeneity is associated with factors that lead to treatment failure and poor prognosis, including drug resistance, relapse, and metastasis. Therefore, precision medicine urgently needs personalized tumor models that accurately reflect the tumor heterogeneity. Currently, tumor organoid technologies are used to generate in vitro 3D tissues, which have been shown to precisely recapitulate structure, tumor microenvironment, expression profiles, functions, molecular signatures, and genomic alterations in primary tumors. Tumor organoid models are important for identifying potential therapeutic targets, characterizing the effects of anticancer drugs, and exploring novel diagnostic and therapeutic options. In this review, we describe how tumor organoids can be cultured and summarize how researchers can use them as an excellent tool for exploring cancer therapies. In addition, we discuss tumor organoids that have been applied in cancer therapy research and highlight the potential of tumor organoids to guide preclinical research.

Dynamic Proteomic Changes in Tumor and Immune Organs Reveal Systemic Immune Response to Tumor Development

In orthotopic mouse tumor models, tumor progression is a complex process, involving interactions among tumor cells, host cell-derived stromal cells, and immune cells. Much attention has been focused on the tumor and its tumor microenvironment, while the host's macroenvironment including immune organs in response to tumorigenesis is poorly understood. Here, we report a temporal proteomic analysis on a subcutaneous tumor and three immune organs (LN, MLN, and spleen) collected on Days 0, 3, 7, 10, 14, and 21 after inoculation of mouse forestomach cancer cells in a syngeneic mouse model. Bioinformatics analysis identified key biological processes during distinct tumor development phases, including an initial acute immune response, the attack by the host immune system, followed by the adaptive immune activation, and the build-up of extracellular matrix. Proteomic changes in LN and spleen largely recapitulated the dynamics of the immune response in the tumor, consistent with an acute defense response on D3, adaptive immune response on D10, and immune evasion by D21. In contrast, the immune response in MLN showed a gradual and sustained activation, suggesting a delayed response from a distal immune organ. Combined analyses of tumors and host immune organs allowed the identification of potential therapeutic targets. A proof-of-concept experiment demonstrated that significant growth reduction can be achieved by dual inhibition of MEK and DDR2. Together, our temporal proteomic dataset of tumors and immune organs provides a useful resource for understanding the interaction between tumors and the immune system and has the potential for identifying new therapeutic targets for cancer treatment.

An osteosarcoma-on-a-chip model for studying osteosarcoma matrix-cell interactions and drug responses

Marrow niches in osteosarcoma (OS) are a specialized microenvironment that is essential for the maintenance and regulation of OS cells. However, existing animal xenograft models are plagued by variability, complexity, and high cost. Herein, we used a decellularized osteosarcoma extracellular matrix (dOsEM) loaded with extracellular vesicles from human bone marrow-derived stem cells (hBMSC-EVs) and OS cells as a bioink to construct a micro-osteosarcoma (micro-OS) through 3D printing. The micro-OS was further combined with a microfluidic system to develop into an OS-on-a-chip (OOC) with a built-in recirculating perfusion system. The OOC system successfully integrated bone marrow niches, cell‒cell and cell-matrix crosstalk, and circulation, allowing a more accurate representation of OS characteristics in vivo. Moreover, the OOC system may serve as a valuable research platform for studying OS biological mechanisms compared with traditional xenograft models and is expected to enable precise and rapid evaluation and consequently more effective and comprehensive treatments for OS.

The loading direction dramatically affects the mechanical properties of the mouse tibia

Introduction: The in vivo tibial loading mouse model has been extensively used to evaluate bone adaptation in the tibia after mechanical loading treatment. However, there is a prevailing assumption that the load is applied axially to the tibia. The aim of this in silico study was to evaluate how much the apparent mechanical properties of the mouse tibia are affected by the loading direction, by using a validated micro-finite element (micro-FE) model of mice which have been ovariectomized and exposed to external mechanical loading over a two-week period. Methods: Longitudinal micro-computed tomography (micro-CT) images were taken of the tibiae of eleven ovariectomized mice at ages 18 and 20 weeks. Six of the mice underwent a mechanical loading treatment at age 19 weeks. Micro-FE models were generated, based on the segmented micro-CT images. Three models using unitary loads were linearly combined to simulate a range of loading directions, generated as a function of the angle from the inferior-superior axis (θ, 0°-30° range, 5° steps) and the angle from the anterior-posterior axis (ϕ, 0°: anterior axis, positive anticlockwise, 0°-355° range, 5° steps). The minimum principal strain was calculated and used to estimate the failure load, by linearly scaling the strain until 10% of the nodes reached the critical strain level of -14,420 με. The apparent bone stiffness was calculated as the ratio between the axial applied force and the average displacement along the longitudinal direction, for the loaded nodes. Results: The results demonstrated a high sensitivity of the mouse tibia to the loading direction across all groups and time points. Higher failure loads were found for several loading directions (θ = 10°, ϕ 205°-210°) than for the nominal axial case (θ = 0°, ϕ = 0°), highlighting adaptation of the bone for loading directions far from the nominal axial one. Conclusion: These results suggest that in studies which use mouse tibia, the loading direction can significantly impact the failure load. Thus, the magnitude and direction of the applied load should be well controlled during the experiments.

Recent advances in the application of induced pluripotent stem cell technology to the study of myeloid malignancies

Acquired myeloid malignancies are a spectrum of clonal disorders known to be caused by sequential acquisition of genetic lesions in hematopoietic stem and progenitor cells, leading to their aberrant self-renewal and differentiation. The increasing use of induced pluripotent stem cell (iPSC) technology to study myeloid malignancies has helped usher a paradigm shift in approaches to disease modeling and drug discovery, especially when combined with gene-editing technology. The process of reprogramming allows for the capture of the diversity of genetic lesions and mutational burden found in primary patient samples into individual stable iPSC lines. Patient-derived iPSC lines, owing to their self-renewal and differentiation capacity, can thus be a homogenous source of disease relevant material that allow for the study of disease pathogenesis using various functional read-outs. Furthermore, genome editing technologies like CRISPR/Cas9 enable the study of the stepwise progression from normal to malignant hematopoiesis through the introduction of specific driver mutations, individually or in combination, to create isogenic lines for comparison. In this review, we survey the current use of iPSCs to model acquired myeloid malignancies including myelodysplastic syndromes (MDS), myeloproliferative neoplasms (MPN), acute myeloid leukemia and MDS/MPN overlap syndromes. The use of iPSCs has enabled the interrogation of the underlying mechanism of initiation and progression driving these diseases. It has also made drug testing, repurposing, and the discovery of novel therapies for these diseases possible in a high throughput setting.

Patient-derived organoids as personalized avatars and a potential immunotherapy model in cervical cancer

Cervical cancer remains a significant health issue in developing countries. However, finding a preclinical model that accurately reproduces tumor characteristics is challenging. Therefore, we established a patient-derived organoids (PDOs) biobank containing 67 cases of heterogeneous cervical cancer that mimic the histopathological and genomic characteristics of parental tumors. The in vitro response of the organoids indicated their ability to capture the radiological heterogeneity of the patients. To model individual responses to adoptive T cell therapy (ACT), we expanded tumor-infiltrating lymphocytes (TILs) ex vivo and co-cultured them with paired organoids. The PDOs-TILs co-culture system demonstrates clear responses that correspond to established immunotherapy efficiency markers like the proportion of CTLs. This study supports the potential of the PDOs platform to guide treatment in prospective interventional trials in cervical cancer.

Preclinical glioma models in neuro-oncology: enhancing translational research

PURPOSE OF REVIEW

Gliomas represent approximately 25% of all primary brain and other central nervous system (CNS) tumors and 81% of malignant tumors. Unfortunately, standard treatment approaches for most CNS cancers have shown limited improvement in patient survival rates.

RECENT FINDINGS

The current drug development process has been plagued by high failure rates, leading to a shift towards human disease models in biomedical research. Unfortunately, suitable preclinical models for brain tumors have been lacking, hampering our understanding of tumor initiation processes and the discovery of effective treatments. In this review, we will explore the diverse preclinical models employed in neuro-oncology research and their contributions to translational science.

SUMMARY

By utilizing a combination of these preclinical models and fostering interdisciplinary collaborations, researchers can deepen their understanding of glioma brain tumors and develop novel therapeutic strategies to combat these devastating diseases. These models offer promising prospects for personalized and efficacious treatments for these challenging malignancies. Although it is unrealistic to fully replicate the complexity of the human body in vitro, the ultimate goal should be to achieve the closest possible resemblance to the clinical context.

Engineering the glioblastoma microenvironment with bioactive nanoparticles for effective immunotherapy

While immunotherapies have revolutionized treatment for other cancers, glioblastoma multiforme (GBM) patients have not shown similar positive responses. The limited response to immunotherapies is partly due to the unique challenges associated with the GBM tumor microenvironment (TME), which promotes resistance to immunotherapies, causing many promising therapies to fail. There is, therefore, an urgent need to develop strategies that make the TME immune permissive to promote treatment efficacy. Bioactive nano-delivery systems, in which the nanoparticle, due to its chemical composition, provides the pharmacological function, have recently emerged as an encouraging option for enhancing the efficacy of immunotherapeutics. These systems are designed to overcome immunosuppressive mechanisms in the TME to improve the efficacy of a therapy. This review will discuss different aspects of the TME and how they impede therapy success. Then, we will summarize recent developments in TME-modifying nanotherapeutics and the in vitro models utilized to facilitate these advances.

Pan-glioma analyses reveal species- and tumor-specific regulation of neuron-glioma synapse genes by lncRNAs

Gliomas are highly heterogeneous and aggressive. Malignant cells in gliomas can contact normal neurons through a synapse-like structure (called neuron-to-glioma synapse, NGS) to promote their proliferation, but it is unclear whether NGS gene expression and regulation show species- and tumor-specificity. This question is important in that many anti-cancer drugs are developed upon mouse models. To address this question, we conducted a pan-glioma analysis using nine scRNA-seq datasets from humans and mice. We also experimentally validated the key element of our methods and verified a key result using TCGA datasets of the same glioma types. Our analyses revealed that NGS gene expression and regulation by lncRNAs are highly species- and tumor-specific. Importantly, simian-specific lncRNAs are more involved in NGS gene regulation than lncRNAs conserved in mammals, and transgenic mouse gliomas have little in common with PDX mouse models and human gliomas in terms of NGS gene regulation. The analyses suggest that simian-specific lncRNAs are a new and rich class of potential targets for tumor-specific glioma treatment, and provide pertinent data for further experimentally and clinically exmining the targets.

Cancer-on-chip: a 3D model for the study of the tumor microenvironment

The approval of anticancer therapeutic strategies is still slowed down by the lack of models able to faithfully reproduce in vivo cancer physiology. On one hand, the conventional in vitro models fail to recapitulate the organ and tissue structures, the fluid flows, and the mechanical stimuli characterizing the human body compartments. On the other hand, in vivo animal models cannot reproduce the typical human tumor microenvironment, essential to study cancer behavior and progression. This study reviews the cancer-on-chips as one of the most promising tools to model and investigate the tumor microenvironment and metastasis. We also described how cancer-on-chip devices have been developed and implemented to study the most common primary cancers and their metastatic sites. Pros and cons of this technology are then discussed highlighting the future challenges to close the gap between the pre-clinical and clinical studies and accelerate the approval of new anticancer therapies in humans.

The challenge of making the right choice: patient avatars in the era of cancer immunotherapies

Immunotherapies are a key therapeutic strategy to fight cancer. Diverse approaches are used to activate tumor-directed immunity and to overcome tumor immune escape. The dynamic interplay between tumor cells and their tumor(immune)microenvironment (T(I)ME) poses a major challenge to create appropriate model systems. However, those model systems are needed to gain novel insights into tumor (immune) biology and a prerequisite to accurately develop and test immunotherapeutic approaches which can be successfully translated into clinical application. Several model systems have been established and advanced into so-called patient avatars to mimic the patient´s tumor biology. All models have their advantages but also disadvantages underscoring the necessity to pay attention in defining the rationale and requirements for which the patient avatar will be used. Here, we briefly outline the current state of tumor model systems used for tumor (immune)biological analysis as well as evaluation of immunotherapeutic agents. Finally, we provide a recommendation for further development to make patient avatars a complementary tool for testing and predicting immunotherapeutic strategies for personalization of tumor therapies.

On-chip modeling of tumor evolution: Advances, challenges and opportunities

Tumor evolution is the accumulation of various tumor cell behaviors from tumorigenesis to tumor metastasis and is regulated by the tumor microenvironment (TME). However, the mechanism of solid tumor progression has not been completely elucidated, and thus, the development of tumor therapy is still limited. Recently, Tumor chips constructed by culturing tumor cells and stromal cells on microfluidic chips have demonstrated great potential in modeling solid tumors and visualizing tumor cell behaviors to exploit tumor progression. Herein, we review the methods of developing engineered solid tumors on microfluidic chips in terms of tumor types, cell resources and patterns, the extracellular matrix and the components of the TME, and summarize the recent advances of microfluidic chips in demonstrating tumor cell behaviors, including proliferation, epithelial-to-mesenchymal transition, migration, intravasation, extravasation and immune escape of tumor cells. We also outline the combination of tumor organoids and microfluidic chips to elaborate tumor organoid-on-a-chip platforms, as well as the practical limitations that must be overcome.

Radiomics and Radiogenomics in Preclinical Imaging on Murine Models: A Narrative Review

Over the past decade, medical imaging technologies have become increasingly significant in both clinical and preclinical research, leading to a better understanding of disease processes and the development of new diagnostic and theranostic methods. Radiomic and radiogenomic approaches have furthered this progress by exploring the relationship between imaging characteristics, genomic information, and outcomes that qualitative interpretations may have overlooked, offering valuable insights for personalized medicine. Preclinical research allows for a controlled environment where various aspects of a pathology can be replicated in animal models, providing radiomic and radiogenomic approaches with the unique opportunity to investigate the causal connection between imaging and molecular factors. The aim of this review is to present the current state of the art in the application of radiomics and radiogenomics on murine models. This review will provide a brief description of relevant articles found in the literature with a discussion on the implications and potential translational relevance of these findings.

A PKPD Case Study: Achieving Clinically Relevant Exposures of AZD5991 in Oncology Mouse Models

Capturing human equivalent drug exposures preclinically is a key challenge in the translational process. Motivated by the need to recapitulate the pharmacokinetic (PK) profile of the clinical stage Mcl-1 inhibitor AZD5991 in mice, we describe the methodology used to develop a refined mathematical model relating clinically relevant concentration profiles to efficacy. Administration routes were explored to achieve target exposures matching the clinical exposure of AZD5991. Intravenous infusion using vascular access button (VAB) technology was found to best reproduce clinical target exposures of AZD5991 in mice. Exposure-efficacy relationships were evaluated, demonstrating that dissimilar PK profiles result in differences in target engagement and efficacy outcomes. Thus, these data underscore the importance of accurately ascribing key PK metrics in the translational process to enable clinically meaningful predictions of efficacy.

Nanoconstructs for theranostic application in cancer: Challenges and strategies to enhance the delivery

Nanoconstructs are made up of nanoparticles and ligands, which can deliver the loaded cargo at the desired site of action. Various nanoparticulate platforms have been utilized for the preparation of nanoconstructs, which may serve both diagnostic as well as therapeutic purposes. Nanoconstructs are mostly used to overcome the limitations of cancer therapies, such as toxicity, nonspecific distribution of the drug, and uncontrolled release rate. The strategies employed during the design of nanoconstructs help improve the efficiency and specificity of loaded theranostic agents and make them a successful approach for cancer therapy. Nanoconstructs are designed with a sole purpose of targeting the requisite site, overcoming the barriers which hinders its right placement for desired benefit. Therefore, instead of classifying modes for delivery of nanoconstructs as actively or passively targeted systems, they are suitably classified as autonomous and nonautonomous types. At large, nanoconstructs offer numerous benefits, however they suffer from multiple challenges, too. Hence, to overcome such challenges computational modelling methods and artificial intelligence/machine learning processes are being explored. The current review provides an overview on attributes and applications offered by nanoconstructs as theranostic agent in cancer.

Role of natural killer and B cell interaction in inducing pathogen specific immune responses

The innate lymphoid cell (ILC) system comprising of the circulating and tissue-resident cells is known to clear infectious pathogens, establish immune homeostasis as well as confer antitumor immunity. Human natural killer cells (hNKs) and other ILCs carry out mopping of the infectious pathogens and perform cytolytic activity regulated by the non-adaptive immune system. The NK cells generate immunological memory and rapid recall response tightly regulated by the adaptive immunity. The interaction of NK and B cell, and its role to induce the pathogen specific immunity is not fully understood. Hence, present article sheds light on the interaction between NK and B cells and resulting immune responses in the infectious diseases. The immune responses elicited by the NK-B cell interaction is of particular importance for developing therapeutic vaccines against the infectious pathogens. Further, experimental evidences suggest the immune-response driven by NK cell population elicits the host-specific antibodies and memory B cells. Also, recently developed humanized immune system (HIS) mice and their importance in to understanding the NK-B cell interaction and resulting pathogen specific immunity has been discussed.

A biomimetic nanodrug for enhanced chemotherapy of pancreatic tumors

Pancreatic ductal adenocarcinoma (PDAC) remains to be one of the highest malignant tumors due to its poor chemotherapeutic efficacy and multidrug resistance. A major reason for the failure in chemotherapy is poor drug accumulation into PDAC tumor tissues due to the overexpressed extracellular matrix (ECM) stroma, which forms a major obstacle limiting the deep tissue penetration of chemotherapeutics. Herein, we report a tumor microenvironment (TME)-responsive nanodrug, based on PDAC cell membrane-coated gold nanocages (AuNCs), to co-deliver the chemotherapeutics (GEM) and nitrogen oxide (NO) donor (L-Arg) to enhance drug accumulation and reduce chemoresistance. The high glutathione (GSH) level can trigger the cleavage of the disulfide bond on nanodrug to release GEM. Moreover, the elevated ROS level could activate L-Arg to generate NO, which synergistically facilitate GEM to penetrate into deep tissues by means of vasodilation and normalization of blood vessels in the PDAC tumor tissue. In addition, AuNCs not only serve as a photothermal agent for chemotherapy, but also generate photoacoustic signals to monitor drug accumulation and distribution. As expected, the strategy demonstrates to be remarkable in treating different xenograft mice models, especially in orthotopic and patient-derived xenograft (PDX) models. The current study defines a useful therapeutic tool for treating PDAC tumors.

Zebrafish Cancer Avatars: A Translational Platform for Analyzing Tumor Heterogeneity and Predicting Patient Outcomes

The increasing number of available anti-cancer drugs presents a challenge for oncologists, who must choose the most effective treatment for the patient. Precision cancer medicine relies on matching a drug with a tumor's molecular profile to optimize the therapeutic benefit. However, current precision medicine approaches do not fully account for intra-tumoral heterogeneity. Different mutation profiles and cell behaviors within a single heterogeneous tumor can significantly impact therapy response and patient outcomes. Patient-derived avatar models recapitulate a patient's tumor in an animal or dish and provide the means to functionally assess heterogeneity's impact on drug response. Mouse xenograft and organoid avatars are well-established, but the time required to generate these models is not practical for clinical decision-making. Zebrafish are emerging as a time-efficient and cost-effective cancer avatar model. In this review, we highlight recent developments in zebrafish cancer avatar models and discuss the unique features of zebrafish that make them ideal for the interrogation of cancer heterogeneity and as part of precision cancer medicine pipelines.

Organ-on-a-Chip and Microfluidic Platforms for Oncology in the UK

Organ-on-chip systems are capable of replicating complex tissue structures and physiological phenomena. The fine control of biochemical and biomechanical cues within these microphysiological systems provides opportunities for cancer researchers to build complex models of the tumour microenvironment. Interest in applying organ chips to investigate mechanisms such as metastatsis and to test therapeutics has grown rapidly, and this review draws together the published research using these microfluidic platforms to study cancer. We focus on both in-house systems and commercial platforms being used in the UK for fundamental discovery science and therapeutics testing. We cover the wide variety of cancers being investigated, ranging from common carcinomas to rare sarcomas, as well as secondary cancers. We also cover the broad sweep of different matrix microenvironments, physiological mechanical stimuli and immunological effects being replicated in these models. We examine microfluidic models specifically, rather than organoids or complex tissue or cell co-cultures, which have been reviewed elsewhere. However, there is increasing interest in incorporating organoids, spheroids and other tissue cultures into microfluidic organ chips and this overlap is included. Our review includes a commentary on cancer organ-chip models being developed and used in the UK, including work conducted by members of the UK Organ-on-a-Chip Technologies Network. We conclude with a reflection on the likely future of this rapidly expanding field of oncological research.

A Telomerase-Activated Magnetic Resonance Imaging Probe for Consecutively Monitoring Tumor Growth Kinetics and In Situ Screening Inhibitors

Telomerase has long been considered as a biomarker for cancer diagnosis and a therapeutic target for drug discovery. Detecting telomerase activity in vivo could provide more direct information of tumor progression and response to drug treatment, which, however, is hampered by the lack of an effective probe that can generate an output signal without a tissue penetration depth limit. In this study, using the principle of distance-dependent magnetic resonance tuning, we constructed a telomerase-activated magnetic resonance imaging probe (TAMP) by connecting superparamagnetic ferroferric oxide nanoparticles (SPFONs) and paramagnetic Gd-DOTA (Gd(III) 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid) complexes via telomerase-responsive DNA motifs. Upon telomerase-catalyzed extension of the primer in TAMP, Gd-DOTA-conjugated oligonucleotides can be liberated from the surface of SPFONs through a DNA strand displacement reaction, restoring the T₁ signal of the Gd-DOTA for a direct readout of the telomerase activity. Here we show that, by tracking telomerase activity, this probe provides consistent monitoring of tumor growth kinetics during progression and in response to drug treatment and enables in situ screening of telomerase inhibitors in whole-animal models. This study provides an alternative toolkit for cancer diagnosis, treatment response assessment, and anticancer drug screening.

Pre-clinical models for evaluating glioma targeted immunotherapies

Gliomas have an extremely poor prognosis in both adult and pediatric patient populations as these tumors are known to grow aggressively and respond poorly to standard of care treatment. Currently, treatment for gliomas involves surgical resection followed by chemoradiation therapy. However, some gliomas, such as diffuse midline glioma, have more limited treatment options such as radiotherapy alone. Even with these interventions, the prognosis for those diagnosed with a glioma remains poor. Immunotherapy is highly effective for some cancers and there is great interest in the development of effective immunotherapies for the treatment of gliomas. Clinical trials evaluating the efficacy of immunotherapies targeted to gliomas have largely failed to date, and we believe this is partially due to the poor choice in pre-clinical mouse models that are used to evaluate these immunotherapies. A key consideration in evaluating new immunotherapies is the selection of pre-clinical models that mimic the glioma-immune response in humans. Multiple pre-clinical options are currently available, each one with their own benefits and limitations. Informed selection of pre-clinical models for testing can facilitate translation of more promising immunotherapies in the clinical setting. In this review we plan to present glioma cell lines and mouse models, as well as alternatives to mouse models, that are available for pre-clinical glioma immunotherapy studies. We plan to discuss considerations of model selection that should be made for future studies as we hope this review can serve as a guide for investigators as they choose which model is best suited for their study.

Assessing the Efficacy of Immune Checkpoint Inhibitors in Preclinical Tumor Models

The identification of novel immune-related targets that can reactivate or enhance antitumor immunity is a very active field of cancer research. In this context, syngeneic tumor models are often used during the preclinical development of immunotherapies to assess their efficacy and analyze the immune system and tumor cell interaction. Here, we present the practical procedures to generate subcutaneous tumors and experimental lung metastases used to evaluate the antitumor activity of your immunotherapy of interest. We also describe a method to quantify contrasted lung metastasis burden by imaging. Finally, we present a protocol to perform orthotopic injection of breast tumor cells in the mammary fat pad followed by tumor resection for the study of spontaneous metastases and evaluation of neoadjuvant immunotherapy.

Senescence and the tumor-immune landscape: Implications for cancer immunotherapy

Cancer therapies, including conventional chemotherapy, radiation, and molecularly targeted agents, can lead to tumor eradication through a variety of mechanisms. In addition to their effects on tumor cell growth and survival, these regimens can also influence the surrounding tumor-immune microenvironment in ways that ultimately impact therapy responses. A unique biological outcome of cancer therapy is induction of cellular senescence. Senescence is a damage-induced stress program that leads to both the durable arrest of tumor cells and remodeling the tumor-immune microenvironment through activation of a collection pleiotropic cytokines, chemokines, growth factors, and proteinases known as the senescence-associated secretory phenotype (SASP). Depending on the cancer context and the mechanism of action of the therapy, the SASP produced following therapy-induced senescence (TIS) can promote anti-tumor immunity that enhances therapeutic efficacy, or alternatively chronic inflammation that leads to therapy failure and tumor relapse. Thus, a deeper understanding of the mechanisms regulating the SASP and components necessary for robust anti-tumor immune surveillance in different cancer and therapy contexts are key to harnessing senescence for tumor control. Here we draw a roadmap to modulate TIS and its immune-stimulating features for cancer immunotherapy.

Antihypertension Nanoblockers Increase Intratumoral Perfusion of Sequential Cytotoxic Nanoparticles to Enhance Chemotherapy Efficacy against Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC), one of the worst prognosis types of tumors, is characterized by dense extracellular matrix, which compresses tumor vessels and forms a physical barrier to inhibit therapeutic drug penetration and efficacy. Herein, losartan, an antihypertension agent, is applied as a tumor stroma modulator and developed into a nanosystem. A series of lipophilic losartan prodrugs are constructed by esterification of the hydroxyl group on losartan to fatty acids. Based on the self-assembly ability and hydrodynamic diameter, the losartan-linoleic acid conjugate is selected for further investigation. To improve the stability in vivo, nanoassemblies are refined with PEGylation to form losartan nanoblocker (Los NB), and administered via intravenous injection for experiments. On murine models of pancreatic cancer, Los NB shows a greater ability to remodel the tumor microenvironment than free losartan, including stromal depletion, vessel perfusion increase, and hypoxia relief. Furthermore, Los NB pretreatment remarkably enhances the accumulation and penetration of 7-ethyl-10-hydroxycamptothecin (SN38)-loaded nanodrugs (SN38 NPs) in tumor tissues. Expectedly, overall therapeutic efficacy of SN38 NPs is significantly enhanced after Los NB pretreatment. Since losartan is one of the most commonly used antihypertension agents, this study may provide a potential for clinical transformation in stroma-rich PDAC treatment.

In vitro models as tools for screening treatment options of head and neck cancer

Various in vitro models using primary and established 2- and 3-dimensional cultures, multicellular tumor spheroids, standardized tumor slice cultures, tumor organoids, and microfluidic systems obtained from tumor lesions/biopsies of head and neck cancer (HNC) have been employed for exploring and monitoring treatment options. All of these in vitro models are to a different degree able to capture the diversity of tumors, recapitulate the disease genetically, histologically, and functionally and retain their tumorigenic potential upon xenotransplantation. The models were used for the characterization of the malignant features of the tumors and for in vitro screens of drugs approved for the treatment of HNC, including chemotherapy and radiotherapy as well as recently developed targeted therapies and immunotherapies, or for novel treatments not yet licensed for these tumor entities. The implementation of the best suitable model will enlarge our knowledge of the oncogenic properties of HNC, expand the drug repertoire and help to develop individually tailored treatment strategies resulting in the translation of these findings into the clinic. This review summarizes the different approaches using preclinical in vitro systems with their advantages and disadvantages and their implementation as preclinical platforms to predict disease course, evaluate biomarkers and test therapy efficacy.

Challenges and opportunities in metastatic breast cancer treatments: Nano-drug combinations delivered preferentially to metastatic cells may enhance therapeutic response

Despite advances in breast cancer treatments and related 5-year survival outcomes, metastatic breast cancer cures remain elusive. The current standard of care includes a combination of surgery, radiation therapy and drug therapy. However, even the most advanced procedures and treatments do not prevent breast cancer recurrence and metastasis. Once metastasis occurs, patient prognosis is poor. Recent elucidation of the spatiotemporal transit of metastatic cancer cells from primary tumor sites to distant sites provide an opportunity to integrate knowledge of drug disposition in our effort to enhance drug localization and exposure in cancer laden tissues . Novel technologies have been developed, but could be further refined to facilitate the distribution of drugs to target cancer cells and tissues. The purpose of this review is to highlight the challenges in metastatic breast cancer treatment and focus on novel drug combination and nanotechnology approaches to overcome the challenges. With improved definition of metastatic tissue target, directed localization and retention of multiple, pharmacologically active drugs to tissues and cells of interest may overcome the limitations in breast cancer treatment that may lead to a cure for breast cancer.

Tumor-on-a-chip model for advancement of anti-cancer nano drug delivery system

Despite explosive growth in the development of nano-drug delivery systems (NDDS) targeting tumors in the last few decades, clinical translation rates are low owing to the lack of efficient models for evaluating and predicting responses. Microfluidics-based tumor-on-a-chip (TOC) systems provide a promising approach to address these challenges. The integrated engineered platforms can recapitulate complex in vivo tumor features at a microscale level, such as the tumor microenvironment, three-dimensional tissue structure, and dynamic culture conditions, thus improving the correlation between results derived from preclinical and clinical trials in evaluating anticancer nanomedicines. The specific focus of this review is to describe recent advances in TOCs for the evaluation of nanomedicine, categorized into six sections based on the drug delivery process: circulation behavior after infusion, endothelial and matrix barriers, tumor uptake, therapeutic efficacy, safety, and resistance. We also discuss current issues and future directions for an end-use perspective of TOCs.

Evaluating Translational Methods for Personalized Medicine—A Scoping Review

The introduction of personalized medicine, through the increasing multi-omics characterization of disease, brings new challenges to disease modeling. The scope of this review was a broad evaluation of the relevance, validity, and predictive value of the current preclinical methodologies applied in stratified medicine approaches. Two case models were chosen: oncology and brain disorders. We conducted a scoping review, following the Joanna Briggs Institute guidelines, and searched PubMed, EMBASE, and relevant databases for reports describing preclinical models applied in personalized medicine approaches. A total of 1292 and 1516 records were identified from the oncology and brain disorders search, respectively. Quantitative and qualitative synthesis was performed on a final total of 63 oncology and 94 brain disorder studies. The complexity of personalized approaches highlights the need for more sophisticated biological systems to assess the integrated mechanisms of response. Despite the progress in developing innovative and complex preclinical model systems, the currently available methods need to be further developed and validated before their potential in personalized medicine endeavors can be realized. More importantly, we identified underlying gaps in preclinical research relating to the relevance of experimental models, quality assessment practices, reporting, regulation, and a gap between preclinical and clinical research. To achieve a broad implementation of predictive translational models in personalized medicine, these fundamental deficits must be addressed.

Modularity of RBC hitchhiking with polymeric nanoparticles: testing the limits of non-covalent adsorption

Red blood cell (RBC) hitchhiking has great potential in enhancing drug therapy, by improving targeting and reducing rapid clearance of nanoparticles (NPs). However, to improve the potential for clinical translation of RBC hitchhiking, a more thorough understanding of the RBC-NP interface is needed. Here, we evaluate the effects of NP surface parameters on the success and biocompatibility of NP adsorption to extracted RBCs from various species. Major differences in RBC characteristics between rabbit, mouse and human were proven to significantly impact NP adsorption outcomes. Additionally, the effects of NP design parameters, including NP hydrophobicity, zeta potential, surfactant concentration and drug encapsulation, on RBC hitchhiking are investigated. Our studies demonstrate the importance of electrostatic interactions in balancing NP adsorption success and biocompatibility. We further investigated the effect of varying the anti-coagulant used for blood storage. The results presented here offer new insights into the parameters that impact NP adsorption on RBCs that will assist researchers in experimental design choices for using RBC hitchhiking as drug delivery strategy.

Modeling Brain Tumors: A Perspective Overview of in vivo and Organoid Models

Brain tumors are a large and heterogeneous group of neoplasms that affect the central nervous system and include some of the deadliest cancers. Almost all the conventional and new treatments fail to hinder tumoral growth of the most malignant brain tumors. This is due to multiple factors, such as intra-tumor heterogeneity, the microenvironmental properties of the human brain, and the lack of reliable models to test new therapies. Therefore, creating faithful models for each tumor and discovering tailored treatments pose great challenges in the fight against brain cancer. Over the years, different types of models have been generated, and, in this review, we investigated the advantages and disadvantages of the models currently used.

Evolutionary rewiring of regulatory networks contributes to phenotypic differences between human and mouse orthologous genes

Mouse models have been engineered to reveal the biological mechanisms of human diseases based on an assumption. The assumption is that orthologous genes underlie conserved phenotypes across species. However, genetically modified mouse orthologs of human genes do not often recapitulate human disease phenotypes which might be due to the molecular evolution of phenotypic differences across species from the time of the last common ancestor. Here, we systematically investigated the evolutionary divergence of regulatory relationships between transcription factors (TFs) and target genes in functional modules, and found that the rewiring of gene regulatory networks (GRNs) contributes to the phenotypic discrepancies that occur between humans and mice. We confirmed that the rewired regulatory networks of orthologous genes contain a higher proportion of species-specific regulatory elements. Additionally, we verified that the divergence of target gene expression levels, which was triggered by network rewiring, could lead to phenotypic differences. Taken together, a careful consideration of evolutionary divergence in regulatory networks could be a novel strategy to understand the failure or success of mouse models to mimic human diseases. To help interpret mouse phenotypes in human disease studies, we provide quantitative comparisons of gene expression profiles on our website (http://sbi.postech.ac.kr/w/RN).

Targeted Drug Delivery for the Treatment of Blood Cancers

Blood cancers are a type of liquid tumor which means cancer is present in the body fluid. Multiple myeloma, leukemia, and lymphoma are the three common types of blood cancers. Chemotherapy is the major therapy of blood cancers by systemic administration of anticancer agents into the blood. However, a high incidence of relapse often happens, due to the low efficiency of the anticancer agents that accumulate in the tumor site, and therefore lead to a low survival rate of patients. This indicates an urgent need for a targeted drug delivery system to improve the safety and efficacy of therapeutics for blood cancers. In this review, we describe the current targeting strategies for blood cancers and recently investigated and approved drug delivery system formulations for blood cancers. In addition, we also discuss current challenges in the application of drug delivery systems for treating blood cancers.

Advancements in 3D Cell Culture Systems for Personalizing Anti-Cancer Therapies

Over 90% of potential anti-cancer drug candidates results in translational failures in clinical trials. The main reason for this failure can be attributed to the non-accurate pre-clinical models that are being currently used for drug development and in personalised therapies. To ensure that the assessment of drug efficacy and their mechanism of action have clinical translatability, the complexity of the tumor microenvironment needs to be properly modelled. 3D culture models are emerging as a powerful research tool that recapitulates in vivo characteristics. Technological advancements in this field show promising application in improving drug discovery, pre-clinical validation, and precision medicine. In this review, we discuss the significance of the tumor microenvironment and its impact on therapy success, the current developments of 3D culture, and the opportunities that advancements that in vitro technologies can provide to improve cancer therapeutics.

Translational challenges in pancreatic neuroendocrine tumor immunotherapy

Pancreatic neuroendocrine tumors are rare types of pancreatic cancer formed from islet cells of pancreas. Clinical presentation of pancreatic neuroendocrine tumors depends on both tumor progression and hormone secretion status, which generate several complications in both diagnosis and treatment. Despite numerous strategies, treatment of patients with pancreatic neuroendocrine tumors still needs improvement. It is suggested that immune response modulation may be essential in the regulation of pancreatic neuroendocrine tumor progression and patient's symptomology. Accumulating evidence indicates that immunotherapy seems to be a promising treatment option for patients with pancreatic neuroendocrine tumors. Nevertheless, several challenges in pre-clinical and clinical studies are present. This review provides knowledge about microenvironment of pancreatic neuroendocrine tumors including significance of cytokine and chemokine as well as specific immune cell types. Additionally, in vitro and in vivo models of pancreatic neuroendocrine tumors and translational challenges are highlighted.

Preclinical Models for the Study of Lung Cancer Pathogenesis and Therapy Development

Experimental preclinical models have been a cornerstone of lung cancer translational research. Work in these model systems has provided insights into the biology of lung cancer subtypes and their origins, contributed to our understanding of the mechanisms that underlie tumor progression, and revealed new therapeutic vulnerabilities. Initially patient-derived lung cancer cell lines were the main preclinical models available. The landscape is very different now with numerous preclinical models for research each with unique characteristics. These include genetically engineered mouse models (GEMMs), patient-derived xenografts (PDXs) and three-dimensional culture systems ("organoid" cultures). Here we review the development and applications of these models and describe their contributions to lung cancer research.

The Challenging Melanoma Landscape: From Early Drug Discovery to Clinical Approval

Melanoma is recognized as the most dangerous type of skin cancer, with high mortality and resistance to currently used treatments. To overcome the limitations of the available therapeutic options, the discovery and development of new, more effective, and safer therapies is required. In this review, the different research steps involved in the process of antimelanoma drug evaluation and selection are explored, including information regarding in silico, in vitro, and in vivo experiments, as well as clinical trial phases. Details are given about the most used cell lines and assays to perform both two- and three-dimensional in vitro screening of drug candidates towards melanoma. For in vivo studies, murine models are, undoubtedly, the most widely used for assessing the therapeutic potential of new compounds and to study the underlying mechanisms of action. Here, the main melanoma murine models are described as well as other animal species. A section is dedicated to ongoing clinical studies, demonstrating the wide interest and successful efforts devoted to melanoma therapy, in particular at advanced stages of the disease, and a final section includes some considerations regarding approval for marketing by regulatory agencies. Overall, considerable commitment is being directed to the continuous development of optimized experimental models, important for the understanding of melanoma biology and for the evaluation and validation of novel therapeutic strategies.

Harnessing the predictive power of preclinical models for oncology drug development

Recent progress in understanding the molecular basis of cellular processes, identification of promising therapeutic targets and evolution of the regulatory landscape makes this an exciting and unprecedented time to be in the field of oncology drug development. However, high costs, long development timelines and steep rates of attrition continue to afflict the drug development process. Lack of predictive preclinical models is considered one of the key reasons for the high rate of attrition in oncology. Generating meaningful and predictive results preclinically requires a firm grasp of the relevant biological questions and alignment of the model systems that mirror the patient context. In doing so, the ability to conduct both forward translation, the process of implementing basic research discoveries into practice, as well as reverse translation, the process of elucidating the mechanistic basis of clinical observations, greatly enhances our ability to develop effective anticancer treatments. In this Review, we outline issues in preclinical-to-clinical translatability of molecularly targeted cancer therapies, present concepts and examples of successful reverse translation, and highlight the need to better align tumour biology in patients with preclinical model systems including tracking of strengths and weaknesses of preclinical models throughout programme development.

Charting oncogenicity of genes and variants across lineages via multiplexed screens in teratomas

Deconstructing tissue-specific effects of genes and variants on proliferation is critical to understanding cellular transformation and systematically selecting cancer therapeutics. This requires scalable methods for multiplexed genetic screens tracking fitness across time, across lineages, and in a suitable niche, since physiological cues influence functional differences. Towards this, we present an approach, coupling single-cell cancer driver screens in teratomas with hit enrichment by serial teratoma reinjection, to simultaneously screen drivers across multiple lineages in vivo. Using this system, we analyzed population shifts and lineage-specific enrichment for 51 cancer associated genes and variants, profiling over 100,000 cells spanning over 20 lineages, across two rounds of serial reinjection. We confirmed that c-MYC alone or combined with myristoylated AKT1 potently drives proliferation in progenitor neural lineages, demonstrating signatures of malignancy. Additionally, mutant MEK1 S218D/S222D provides a proliferative advantage in mesenchymal lineages like fibroblasts. Our method provides a powerful platform for multi-lineage longitudinal study of oncogenesis.

Carboplatin response in preclinical models for ovarian cancer: comparison of 2D monolayers, spheroids, ex vivo tumors and in vivo models

Epithelial ovarian cancer (EOC) is the most lethal gynecological cancer. Among the key challenges in developing effective therapeutics is the poor translation of preclinical models used in the drug discovery pipeline. This leaves drug attrition rates and costs at an unacceptably high level. Previous work has highlighted the discrepancies in therapeutic response between current in vitro and in vivo models. To address this, we conducted a comparison study to differentiate the carboplatin chemotherapy response across four different model systems including 2D monolayers, 3D spheroids, 3D ex vivo tumors and mouse xenograft models. We used six previously characterized EOC cell lines of varying chemosensitivity and performed viability assays for each model. In vivo results from the mouse model correlated with 2D response in 3/6 cell lines while they correlated with 3D spheroids and the ex vivo model in 4/6 and 5/5 cell lines, respectively. Our results emphasize the variability in therapeutic response across models and demonstrate that the carboplatin response in EOC cell lines cultured in a 3D ex vivo model correlates best with the in vivo response. These results highlight a more feasible, reliable, and cost-effective preclinical model with the highest translational potential for drug screening and prediction studies in EOC.

Reconstructing the tumor architecture into organoids

Cancer remains a leading health burden worldwide. One of the challenges hindering cancer therapy development is the substantial discrepancies between the existing cancer models and the tumor microenvironment (TME) of human patients. Constructing tumor organoids represents an emerging approach to recapitulate the pathophysiological features of the TME in vitro. Over the past decade, various approaches have been demonstrated to engineer tumor organoids as in vitro cancer models, such as incorporating multiple cellular populations, reconstructing biophysical and chemical traits, and even recapitulating structural features. In this review, we focus on engineering approaches for building tumor organoids, including biomaterial-based, microfabrication-assisted, and synthetic biology-facilitated strategies. Furthermore, we summarize the applications of engineered tumor organoids in basic cancer research, cancer drug discovery, and personalized medicine. We also discuss the challenges and future opportunities in using tumor organoids for broader applications.

Nanotechnologies for the delivery of biologicals: Historical perspective and current landscape

Biological macromolecule-based therapeutics irrupted in the pharmaceutical scene generating a great hope due to their outstanding specificity and potency. However, given their susceptibility to degradation and limited capacity to overcome biological barriers new delivery technologies had to be developed for them to reach their targets. This review aims at analyzing the historical seminal advances that shaped the development of the protein/peptide delivery field, along with the emerging technologies on the lead of the current landscape. Particularly, focus is made on technologies with a potential for transmucosal systemic delivery of protein/peptide drugs, followed by approaches for the delivery of antigens as new vaccination strategies, and formulations of biological drugs in oncology, with special emphasis on mAbs. Finally, a discussion of the key challenges the field is facing, along with an overview of prospective advances are provided.