A Systematic Review of the Efficacy of Preclinical Models of Lung Cancer Drugs

Development of a Bladder Cancer-on-a-Chip Model to Assess Bladder Cancer Cell Invasiveness

We have developed a bladder cancer-on-a-chip model which supports the 3D growth of cells and can be used to assess and quantify bladder cancer cell invasiveness in a physiologically appropriate environment. Three bladder cancer cell lines (T24, J82, and RT4) were resuspended in 50% Matrigel® and grown within a multi-channel organ-on-a-chip system. The ability of live cells to invade across into an adjacent 50% Matrigel®-only channel was assessed over a 2-day period. Cell lines isolated from patients with high-grade bladder cancer (T24 and J82) invaded across into the Matrigel®-only channel at a much higher frequency compared to cells isolated from a patient with low-grade cancer (RT4) (p < 0.001). The T24 and J82 cells also invaded further distances into the Matrigel®-only channel compared to the RT4 cells (p < 0.001). The cell phenotype within the model was maintained as assessed by cell morphology and immunohistochemical analysis of E-cadherin. Treatment with ATN-161, an α5β1 integrin inhibitor and well-known migrastatic drug, caused a dose-dependent decrease in the invasiveness of the J82 cells (p < 0.01). The combined data demonstrate that our bladder cancer-on-a-chip model supports the retention of the bladder cancer cell phenotype and can be used to reproducibly assess and quantify the invasiveness of live bladder cancer cells.

ULK1 Mediated Autophagy-Promoting Effects of Rutin-Loaded Chitosan Nanoparticles Contribute to the Activation of NF-κB Signaling Besides Inhibiting EMT in Hep3B Hepatoma Cells

Background

Liver cancer remains to be one of the leading causes of cancer worldwide. The treatment options face several challenges and nanomaterials have proven to improve the bioavailability of several drug candidates and their applications in nanomedicine. Specifically, chitosan nanoparticles (CNPs) are extremely biodegradable, pose enhanced biocompatibility and are considered safe for use in medicine.

Methods

CNPs were synthesized by ionic gelation, loaded with rutin (rCNPs) and characterized by ultraviolet-visible spectroscopy (UV-Vis), Fourier-transform infrared spectroscopy (FTIR), dynamic light scattering (DLS) and transmission electron microscopy (TEM). The rCNPs were tested for their cytotoxic effects on human hepatoma Hep3B cells, and experiments were conducted to determine the mechanism of such effects. Further, the biocompatibility of the rCNPs was tested on L929 fibroblasts, and their hemocompatibility was determined.

Results

Initially, UV-vis and FTIR analyses indicated the possible loading of rutin on rCNPs. Further, the rutin load was quantitatively measured using Ultra-Performance Liquid Chromatography (UPLC) and the concentration was 88 µg/mL for 0.22 micron filtered rCNPs. The drug loading capacity (LC%) of the rCNPs was observed to be 13.29 ± 0.68%, and encapsulation efficiency (EE%) was 19.55 ± 1.01%. The drug release was pH-responsive as 88.58% of the drug was released after 24 hrs at the lysosomal pH 5.5, whereas 91.44% of the drug was released at physiological pH 7.4 after 102 hrs. The cytotoxic effects were prominent in 0.22 micron filtered samples of 5 mg/mL rutin precursor. The particle size for the rCNPs at this concentration was 144.1 nm and the polydispersity index (PDI) was 0.244, which is deemed to be ideal for tumor targeting. A zeta potential (ζ-potential) value of 16.4 mV indicated rCNPs with good stability. The IC50 value for the cytotoxic effects of rCNPs on human hepatoma Hep3B cells was 9.7 ± 0.19 μg/mL of rutin load. In addition, the increased production of reactive oxygen species (ROS) and changes in mitochondrial membrane potential (MMP) were observed. Gene expression studies indicated that the mechanism for cytotoxic effects of rCNPs on Hep3B cells was due to the activation of Unc-51-like autophagy-activating kinase (ULK1) mediated autophagy and nuclear factor kappa B (NF-κB) signaling besides inhibiting the epithelial-mesenchymal Transition (EMT). In addition, the rCNPs were less toxic on NCTC clone 929 (L929) fibroblasts in comparison to the Hep3B cells and possessed excellent hemocompatibility (less than 2% of hemolysis).

Conclusion

The synthesized rCNPs were pH-responsive and possessed the physicochemical properties suitable for tumor targeting. The particles were effectively cytotoxic on Hep3B cells in comparison to normal cells and possessed excellent hemocompatibility. The very low hemolytic profile of rCNPs indicates that the drug could be administered intravenously for cancer therapy.

Early, precise, and safe clinical evaluation of the pharmacodynamic effects of novel agents in the intact human tumor microenvironment

Introduction: Drug development is systemically inefficient. Research and development costs for novel therapeutics average hundreds of millions to billions of dollars, with the overall likelihood of approval estimated to be as low as 6.7% for oncology drugs. Over half of these failures are due to a lack of drug efficacy. This pervasive and repeated low rate of success exemplifies how preclinical models fail to adequately replicate the complexity and heterogeneity of human cancer. Therefore, new methods of evaluation, early in the development trajectory, are essential both to rule-in and rule-out novel agents with more rigor and speed, but also to spare clinical trial patients from the potentially toxic sequelae (high risk) of testing investigational agents that have a low likelihood of producing a response (low benefit). Methods: The clinical in vivo oncology (CIVO®) platform was designed to change this drug development paradigm. CIVO precisely delivers microdose quantities of up to 8 drugs or combinations directly into patient tumors 4-96 h prior to planned surgical resection. Resected tissue is then analyzed for responses at each site of intratumoral drug exposure. Results: To date, CIVO has been used safely in 6 clinical trials, including 68 subjects, with 5 investigational and 17 approved agents. Resected tissues were analyzed initially using immunohistochemistry and in situ hybridization assays (115 biomarkers). As technology advanced, the platform was paired with spatial biology analysis platforms, to successfully track anti-neoplastic and immune-modulating activity of the injected agents in the intact tumor microenvironment. Discussion: Herein we provide a report of the use of CIVO technology in patients, a depiction of the robust analysis methods enabled by this platform, and a description of the operational and regulatory mechanisms used to deploy this approach in synergistic partnership with pharmaceutical partners. We further detail how use of the CIVO platform is a clinically safe and scientifically precise alternative or complement to preclinical efficacy modeling, with outputs that inform, streamline, and de-risk drug development.

Sonosensitive Cavitation Nuclei-A Customisable Platform Technology for Enhanced Therapeutic Delivery

Ultrasound-mediated cavitation shows great promise for improving targeted drug delivery across a range of clinical applications. Cavitation nuclei-sound-sensitive constructs that enhance cavitation activity at lower pressures-have become a powerful adjuvant to ultrasound-based treatments, and more recently emerged as a drug delivery vehicle in their own right. The unique combination of physical, biological, and chemical effects that occur around these structures, as well as their varied compositions and morphologies, make cavitation nuclei an attractive platform for creating delivery systems tuned to particular therapeutics. In this review, we describe the structure and function of cavitation nuclei, approaches to their functionalization and customization, various clinical applications, progress toward real-world translation, and future directions for the field.

Polyurethane scaffold-based 3D lung cancer model recapitulates in vivo tumor biological behavior for nanoparticulate drug screening

Lung cancer is the leading cause of cancer mortality worldwide. Preclinical studies in lung cancer hold the promise of screening for effective antitumor agents, but mechanistic studies and drug discovery based on 2D cell models have a high failure rate in getting to the clinic. Thus, there is an urgent need to explore more reliable and effective in vitro lung cancer models. Here, we prepared a series of three-dimensional (3D) waterborne biodegradable polyurethane (WBPU) scaffolds as substrates to establish biomimetic tumor models in vitro. These 3D WBPU scaffolds were porous and could absorb large amounts of free water, facilitating the exchange of substances (nutrients and metabolic waste) and cell growth. The scaffolds at wet state could simulate the mechanics (elastic modulus ∼1.9 kPa) and morphology (porous structures) of lung tissue and exhibit good biocompatibility. A549 lung cancer cells showed adherent growth pattern and rapidly formed 3D spheroids on WBPU scaffolds. Our results showed that the scaffold-based 3D lung cancer model promoted the expression of anti-apoptotic and epithelial-mesenchymal transition-related genes, giving it a more moderate growth and adhesion pattern compared to 2D cells. In addition, WBPU scaffold-established 3D lung cancer model revealed a closer expression of proteins to in vivo tumor, including tumor stem cell markers, cell proliferation, apoptosis, invasion and tumor resistance proteins. Based on these features, we further demonstrated that the 3D lung cancer model established by the WBPU scaffold was very similar to the in vivo tumor in terms of both resistance and tolerance to nanoparticulate drugs. Taken together, WBPU scaffold-based lung cancer model could better mimic the growth, microenvironment and drug response of tumor in vivo. This emerging 3D culture system holds promise to shorten the formulation cycle of individualized treatments and reduce the use of animals while providing valid research data for clinical trials.

Innovative three-dimensional models for understanding mechanisms underlying lung diseases: powerful tools for translational research

Chronic lung diseases result from alteration and/or destruction of lung tissue, inevitably causing decreased breathing capacity and quality of life for patients. While animal models have paved the way for our understanding of pathobiology and the development of therapeutic strategies for disease management, their translational capacity is limited. There is, therefore, a well-recognised need for innovative in vitro models to reflect chronic lung diseases, which will facilitate mechanism investigation and the advancement of new treatment strategies. In the last decades, lungs have been modelled in healthy and diseased conditions using precision-cut lung slices, organoids, extracellular matrix-derived hydrogels and lung-on-chip systems. These three-dimensional models together provide a wide spectrum of applicability and mimicry of the lung microenvironment. While each system has its own limitations, their advantages over traditional two-dimensional culture systems, or even over animal models, increases the value of in vitro models. Generating new and advanced models with increased translational capacity will not only benefit our understanding of the pathobiology of lung diseases but should also shorten the timelines required for discovery and generation of new therapeutics. This article summarises and provides an outline of the European Respiratory Society research seminar "Innovative 3D models for understanding mechanisms underlying lung diseases: powerful tools for translational research", held in Lisbon, Portugal, in April 2022. Current in vitro models developed for recapitulating healthy and diseased lungs are outlined and discussed with respect to the challenges associated with them, efforts to develop best practices for model generation, characterisation and utilisation of models and state-of-the-art translational potential.

Bridging the gap between tumor-on-chip and clinics: a systematic review of 15 years of studies

Over the past 15 years, the field of oncology research has witnessed significant progress in the development of new cell culture models, such as tumor-on-chip (ToC) systems. In this comprehensive overview, we present a multidisciplinary perspective by bringing together physicists, biologists, clinicians, and experts from pharmaceutical companies to highlight the current state of ToC research, its unique features, and the challenges it faces. To offer readers a clear and quantitative understanding of the ToC field, we conducted an extensive systematic analysis of more than 300 publications related to ToC from 2005 to 2022. ToC offer key advantages over other in vitro models by enabling precise control over various parameters. These parameters include the properties of the extracellular matrix, mechanical forces exerted on cells, the physico-chemical environment, cell composition, and the architecture of the tumor microenvironment. Such fine control allows ToC to closely replicate the complex microenvironment and interactions within tumors, facilitating the study of cancer progression and therapeutic responses in a highly representative manner. Importantly, by incorporating patient-derived cells or tumor xenografts, ToC models have demonstrated promising results in terms of clinical validation. We also examined the potential of ToC for pharmaceutical industries in which ToC adoption is expected to occur gradually. Looking ahead, given the high failure rate of clinical trials and the increasing emphasis on the 3Rs principles (replacement, reduction, refinement of animal experimentation), ToC models hold immense potential for cancer research. In the next decade, data generated from ToC models could potentially be employed for discovering new therapeutic targets, contributing to regulatory purposes, refining preclinical drug testing and reducing reliance on animal models.

Clinical development of new drugs for adults and children with cancer, 2010-2020

BACKGROUND

Many new molecular entities enter clinical development to evaluate potential therapeutic benefits for oncology patients. We characterized adult and pediatric development of the set of new molecular entities that started clinical testing in 2010-2015 worldwide.

METHODS

We extracted data from AdisInsight, an extensive database of global pharmaceutical development, and the FDA.gov website. We followed the cohort of new molecular entities initiating first-in-human phase I clinical trials in 2010-2015 to the end of 2020. For each new molecular entity, we determined whether it was granted US Food and Drug Administration (FDA) approval, studied in a trial open to pediatric enrollment, or stalled during development. We characterized the cumulative incidence of these endpoints using statistical methods for censored data.

RESULTS

The 572 new molecular entities starting first-in-human studies in 2010-2015 were studied in 6142 trials by the end of 2020. Most new molecular entities were small molecules (n = 316, 55.2%), antibodies (n = 148, 25.9%), or antibody-drug conjugates (n = 44, 7.7%). After a mean follow-up of 8.0 years, 173 new molecular entities did not advance beyond first-in-human trials, and 39 were approved by the FDA. New molecular entities had a 10.4% estimated probability (95% confidence interval = 6.6% to 14.1%) of being approved by the FDA within 10 years of first-in-human trials. After a median of 4.6 years since start of first-in-human trials, 67 (11.7%) new molecular entities were tested in trials open to pediatric patients, and 5 (0.9%) were approved for pediatric indications.

CONCLUSIONS

More efficient clinical development strategies are needed to evaluate new cancer therapies, especially for children, and incorporate approaches to ensure knowledge gain from investigational products that stall in development.

Repurposing of Chronically Used Drugs in Cancer Therapy: A Chance to Grasp

Despite the advancement in drug discovery for cancer therapy, drug repurposing remains an exceptional opportunistic strategy. This approach offers many advantages (faster, safer, and cheaper drugs) typically needed to overcome increased challenges, i.e., side effects, resistance, and costs associated with cancer therapy. However, not all drug classes suit a patient's condition or long-time use. For that, repurposing chronically used medications is more appealing. This review highlights the importance of repurposing anti-diabetic and anti-hypertensive drugs in the global fight against human malignancies. Extensive searches of all available evidence (up to 30 March 2023) on the anti-cancer activities of anti-diabetic and anti-hypertensive agents are obtained from multiple resources (PubMed, Google Scholar, ClinicalTrials.gov, Drug Bank database, ReDo database, and the National Institutes of Health). Interestingly, more than 92 clinical trials are evaluating the anti-cancer activity of 14 anti-diabetic and anti-hypertensive drugs against more than 15 cancer types. Moreover, some of these agents have reached Phase IV evaluations, suggesting promising official release as anti-cancer medications. This comprehensive review provides current updates on different anti-diabetic and anti-hypertensive classes possessing anti-cancer activities with the available evidence about their mechanism(s) and stage of development and evaluation. Hence, it serves researchers and clinicians interested in anti-cancer drug discovery and cancer management.

Poor correlation between preclinical and patient efficacy data for tumor targeted monotherapies in glioblastoma: the results of a systematic review

PURPOSE

Limited progress has been made in treating glioblastoma, and we hypothesise that poor concordance between preclinical and clinical efficacy in this disease is a major barrier to drug development. We undertook a systematic review to quantify this issue.

METHODS

We identified phase I trials (P1Ts) of tumor targeted drugs, subsequent trial results and preceding relevant preclinical data published in adult glioblastoma patients between 2006-2019 via structured searches of EMBASE/MEDLINE/PUBMED. Detailed clinical/preclinical information was extracted. Associations between preclinical and clinical efficacy metrics were determined using appropriate non-parametric statistical tests.

RESULTS

A total of 28 eligible P1Ts were identified, with median ORR of 2.9% (range 0.0-33.3%). Twenty-three (82%) had published relevant preclinical data available. Five (18%) had relevant later phase clinical trial data available. There was overall poor correlation between preclinical and clinical efficacy metrics on univariate testing. However, drugs that had undergone in vivo testing had significantly longer median overall survival (7.9 vs 5.6mo, p = 0.02). Additionally, drugs tested in ≥ 2 biologically-distinct in vivo models ('multiple models') had a significantly better median response rate than those tested using only one ('single model') or those lacking in vivo data (6.8% vs 1.2% vs. 0.0% respectively, p = 0.027).

CONCLUSION

Currently used preclinical models poorly predict subsequent activity in P1Ts, and generally over-estimate the anti-tumor activity of these drugs. This underscores the need for better preclinical models to aid the development of novel anti-glioblastoma drugs. Until these become widely available and used, the use of multiple biologically-distinct in vivo models should be strongly encouraged.

Dynamic regulation of P-TEFb by 7SK snRNP is integral to the DNA damage response to regulate chemotherapy sensitivity

Testicular germ cell tumors and closely related embryonal stem cells are exquisitely sensitive to cisplatin, a feature thought to be linked to their pluripotent state and p53 status. It remains unclear whether and how cellular state is coordinated with p53 to confer cisplatin sensitivity. Here, we report that positive transcription elongation factor b (P-TEFb) determines cell fate upon DNA damage. We find that cisplatin rapidly activates P-TEFb by releasing it from inhibitory 7SK small nuclear ribonucleoprotein complex. P-TEFb directly phosphorylates pluripotency factor estrogen-related receptor beta (ESRRB), and induces its proteasomal degradation to enhance pro-survival glycolysis. On the other hand, P-TEFb is required for the transcription of a substantial portion of p53 target genes, triggering cell death during prolonged cisplatin treatment. These results reveal previously underappreciated roles of P-TEFb to coordinate the DNA damage response. We discuss the implications for using P-TEFb inhibitors to treat cancer and ameliorate cisplatin-induced ototoxicity.

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P-TEFb regulates pro-survival and pro-death pathways during DNA damage response

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P-TEFb promotes ESRRB proteasomal degradation to enhance pro-survival glycolysis

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P-TEFb induces a substantial portion of p53 target genes to trigger cell death

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Chemical inhibitors of P-TEFb blocks cisplatin- or UV-induced cell death

A novel NCI-H69V small cell lung cancer functional mini-tumor model for future treatment screening applications

Small cell lung cancer (SCLC) is aggressive and despite multiple clinical trials, its standard of care is unchanged for the past three decades. In vitro cancer models are crucial in chemotherapy development, and three-dimensional (3D) models aim to bridge the gap between two-dimensional (2D) flat cultures and in vivo testing. Functional 3D spheroids can better represent the in vivo situation and tumor characteristics than 2D models. An NCI-H69V SCLC mini-tumor model was developed in a clinostat-based rotating bioreactor system. Spheroid growth and viability were characterized for 30 days, and the ideal experimental window with mature and metabolically stable spheroids was determined. Application of the model for anticancer treatment screening was validated with the standard chemotherapeutic drug irinotecan, for an exposure period of 72 h. The following parameters were measured: soluble protein content, planar surface area measurements, intracellular adenosine triphosphate and extracellular adenylate kinase levels, and glucose consumption. Histological morphology of the spheroids was observed. The established model proved viable and stable, while treatment with irinotecan caused a decrease in cell growth, viability, and glucose consumption demonstrating reactivity of the model to chemotherapy. Therefore, this NCI-H69V SCLC functional spheroid model could be used for future anticancer compound screening.

Preclinical studies of the antitumor effect of curcumin-loaded polymeric nanocapsules: A systematic review and meta-analysis

Curcumin, a plant-derived compound, has various well-known biological effects (anti-inflammatory, antioxidant, antitumor, among others) as well as some important limitations for formulators, such as poor water solubility and low oral bioavailability. Its nanoencapsulation is reported to overcome these drawbacks and to improve its in vivo efficacy. Here, data from preclinical in vivo studies evaluating the antitumor efficacy of curcumin-loaded polymeric nanocapsules are collected, analyzed, and discussed as a systematic review. Meta-analyses are performed to assess the contribution of this nanoencapsulation compared with nonencapsulated curcumin. Eighteen studies (116 animals) meet the inclusion criteria. The evidence that curcumin-loaded polymeric nanocapsules inhibits tumor growth (SMD: -3.03; 95% CI: -3.84, -2.21; p < 0.00001) and decreases tumor weight (SMD: -3.96; 95% CI: -6.22, -1.70; p = 0.0006) in rodents is established, regardless of the solid tumor model. To assess the quality of the studies included in the review a bias risk analysis was performed using the SYRCLE's RoB tool. Therefore, encapsulation in polymeric nanocapsules represents an important tool to improve the antitumor effects of curcumin, and this systematic review paves the way for future clinical studies and the translation of curcumin formulations into novel nanomedicines for human cancer treatment.

Integrating mechanism-based modeling with biomedical imaging to build practical digital twins for clinical oncology

Digital twins employ mathematical and computational models to virtually represent a physical object (e.g., planes and human organs), predict the behavior of the object, and enable decision-making to optimize the future behavior of the object. While digital twins have been widely used in engineering for decades, their applications to oncology are only just emerging. Due to advances in experimental techniques quantitatively characterizing cancer, as well as advances in the mathematical and computational sciences, the notion of building and applying digital twins to understand tumor dynamics and personalize the care of cancer patients has been increasingly appreciated. In this review, we present the opportunities and challenges of applying digital twins in clinical oncology, with a particular focus on integrating medical imaging with mechanism-based, tissue-scale mathematical modeling. Specifically, we first introduce the general digital twin framework and then illustrate existing applications of image-guided digital twins in healthcare. Next, we detail both the imaging and modeling techniques that provide practical opportunities to build patient-specific digital twins for oncology. We then describe the current challenges and limitations in developing image-guided, mechanism-based digital twins for oncology along with potential solutions. We conclude by outlining five fundamental questions that can serve as a roadmap when designing and building a practical digital twin for oncology and attempt to provide answers for a specific application to brain cancer. We hope that this contribution provides motivation for the imaging science, oncology, and computational communities to develop practical digital twin technologies to improve the care of patients battling cancer.

Immune cell infiltration pattern in non-small cell lung cancer PDX models is a model immanent feature and correlates with a distinct molecular and phenotypic make-up

BACKGROUND

The field of cancer immunology is rapidly moving towards innovative therapeutic strategies, resulting in the need for robust and predictive preclinical platforms reflecting the immunological response to cancer. Well characterized preclinical models are essential for the development of predictive biomarkers in the oncology as well as the immune-oncology space. In the current study, gold standard preclinical models are being refined and combined with novel image analysis tools to meet those requirements.

METHODS

A panel of 14 non-small cell lung cancer patient-derived xenograft models (NSCLC PDX) was propagated in humanized NOD/Shi-scid/IL-2Rnull mice. The models were comprehensively characterized for relevant phenotypic and molecular features, including flow cytometry, immunohistochemistry, histology, whole exome sequencing and cytokine secretion.

RESULTS

Models reflecting hot (>5% tumor-infiltrating lymphocytes/TILs) as opposed to cold tumors (<5% TILs) significantly differed regarding their cytokine profiles, molecular genetic aberrations, stroma content, and programmed cell death ligand-1 status. Treatment experiments including anti cytotoxic T-lymphocyte-associated protein 4, anti-programmed cell death 1 or the combination thereof across all 14 models in the single mouse trial format showed distinctive tumor growth response and spatial immune cell patterns as monitored by computerized analysis of digitized whole-slide images. Image analysis provided for the first time qualitative evaluation of the extent to which PDX models retain the histological features from their original human donors.

CONCLUSIONS

Deep phenotyping of PDX models in a humanized setting by combinations of computational pathology, immunohistochemistry, flow cytometry and proteomics enables the exhaustive analysis of innovative preclinical models and paves the way towards the development of translational biomarkers for immuno-oncology drugs.

Patient-Derived Cancer Organoids for Precision Oncology Treatment

The emergence of three-dimensional human organoids has opened the door for the development of patient-derived cancer organoid (PDO) models, which closely recapitulate parental tumor tissue. The mainstays of preclinical cancer modeling include in vitro cell lines and patient-derived xenografts, but these models lack the cellular heterogeneity seen in human tumors. Moreover, xenograft establishment is resource and time intensive, rendering these models difficult to use to inform clinical trials and decisions. PDOs, however, can be created efficiently and retain tumor-specific properties such as cellular heterogeneity, cell-cell and cell-stroma interactions, the tumor microenvironment, and therapeutic responsiveness. PDO models and drug-screening protocols have been described for several solid tumors and, more recently, for gliomas. Since PDOs can be developed in clinically relevant time frames and share many characteristics of parent tumors, they may enhance the ability to provide precision oncologic care for patients. This review explores the current literature on cancer organoids, highlighting the history of PDO development, organoid models of glioma, and potential clinical applications of PDOs.