Microfluidic 3D models of cancer

Studying breast cancer lung metastasis using a multi-compartment microfluidic device with a mimetic tumor-stroma interaction model

BACKGROUND

Understanding the mechanisms underlying the metastasis of breast cancer cells to the lungs is challenging, and appropriate simulation of the tumor microenvironment with mimetic cancer-stroma crosstalk is essential. β4 integrin is known to contribute to triggering a variety of different signaling cues involved in the malignant phenotype of cancer but its role in organ-specific metastasis needs further study. In this work, a multi-compartment microfluidic tumor model was developed to evaluate cancer cell invasion.

MATERIALS AND METHODS

To model the primary tumor microenvironment, breast cancer cells (MCF7) and cancer-associated fibroblasts (CAFs) were co-cultured within the tumor compartment of the microfluidic chip while normal lung fibroblasts (NLFs) were seeded in a different compartment, as the secondary tumor site, separated from the tumor compartment via a Matrigel™ layer resembling the extracellular matrix.

RESULTS

The cytotoxic effect of β4 integrin blockade on cancer cells gradually increased after 48 and 72 h of co-culture. Invasion of breast cancer cells in both single and coculture models was characterized in response to β4 integrin blockade. The invasion rate and gap closure of MCF7/CAF_NLF was significantly higher than MCF7_NLF (P < 0.0001). β4 integrin inhibition reduced the rate of gap closure and invasion of both (P < 0.0001).

CONCLUSIONS

Biomimetic microfluidic-based tumor models hold promise for studying cancer metastasis mechanisms. Precise manipulation, simulation, and analysis of the cancer microenvironment are made possible by microfluidics.

The Latest Advances in Microfluidic DLD Cell Sorting Technology: The Optimization of Channel Design

Cell sorting plays a crucial role in both medical and biological research. As a key passive sorting technique in the field of microfluidics, deterministic lateral displacement (DLD) has been widely applied to cell separation and sorting. This review aims to summarize the latest advances in the optimization of channel design for microfluidic DLD cell sorting. First, we provide an overview of the design elements of microfluidic DLD cell sorting channels, focusing on key factors that affect separation efficiency and accuracy, including channel geometry, fluid dynamics, and the interaction between cells and channel surfaces. Subsequently, we review recent innovations and progress in channel design for microfluidic DLD technology, exploring its applications in biomedical fields and its integration with machine learning. Additionally, we discuss the challenges currently faced in optimizing channel design for microfluidic DLD cell sorting. Finally, based on existing research, we make a summary and put forward prospective views on the further development of this field.

Gastrointestinal Cancer Patient Derived Organoids at the Frontier of Personalized Medicine and Drug Screening

Cancer is a leading cause of death worldwide. Around one-third of the total global cancer incidence and mortality are related to gastrointestinal (GI) cancers. Over the past few years, rapid developments have been made in patient-derived organoid (PDO) models for gastrointestinal cancers. By closely mimicking the molecular properties of their parent tumors in vitro, PDOs have emerged as powerful tools in personalized medicine and drug discovery. Here, we review the current literature on the application of PDOs of common gastrointestinal cancers in the optimization of drug treatment strategies in the clinic and their rising importance in pre-clinical drug development. We discuss the advantages and limitations of gastrointestinal cancer PDOs and outline the microfluidics-based strategies that improve the throughput of PDO models in order to extract the maximal benefits in the personalized medicine and drug discovery process.

Unveiling Nanoparticles: Recent Approaches in Studying the Internalization Pattern of Iron Oxide Nanoparticles in Mono- and Multicellular Biological Structures

Nanoparticle (NP)-based solutions for oncotherapy promise an improved efficiency of the anticancer response, as well as higher comfort for the patient. The current advancements in cancer treatment based on nanotechnology exploit the ability of these systems to pass biological barriers to target the tumor cell, as well as tumor cell organelles. In particular, iron oxide NPs are being clinically employed in oncological management due to this ability. When designing an efficient anti-cancer therapy based on NPs, it is important to know and to modulate the phenomena which take place during the interaction of the NPs with the tumor cells, as well as the normal tissues. In this regard, our review is focused on highlighting different approaches to studying the internalization patterns of iron oxide NPs in simple and complex 2D and 3D in vitro cell models, as well as in living tissues, in order to investigate the functionality of an NP-based treatment.

Emerging In Vitro and In Vivo Models: Hope for the Better Understanding of Cancer Progression and Treatment

Various cancer models have been developed to aid the understanding of the underlying mechanisms of tumor development and evaluate the effectiveness of various anticancer drugs in preclinical studies. These models accurately reproduce the critical stages of tumor initiation and development to mimic the tumor microenvironment better. Using these models for target validation, tumor response evaluation, resistance modeling, and toxicity comprehension can significantly enhance the drug development process. Herein, various in vivo or animal models are presented, typically consisting of several mice and in vitro models ranging in complexity from transwell models to spheroids and CRISPR-Cas9 technologies. While in vitro models have been used for decades and dominate the early stages of drug development, they are still limited primary to simplistic tests based on testing on a single cell type cultivated in Petri dishes. Recent advancements in developing new cancer therapies necessitate the generation of complicated animal models that accurately mimic the tumor's complexity and microenvironment. Mice make effective tumor models as they are affordable, have a short reproductive cycle, exhibit rapid tumor growth, and are simple to manipulate genetically. Human cancer mouse models are crucial to understanding the neoplastic process and basic and clinical research improvements. The following review summarizes different in vitro and in vivo metastasis models, their advantages and disadvantages, and their ability to serve as a model for cancer research.

Assessing personalized responses to anti-PD-1 treatment using patient-derived lung tumor-on-chip

There is a compelling need for approaches to predict the efficacy of immunotherapy drugs. Tumor-on-chip technology exploits microfluidics to generate 3D cell co-cultures embedded in hydrogels that recapitulate simplified tumor ecosystems. Here, we present the development and validation of lung tumor-on-chip platforms to quickly and precisely measure ex vivo the effects of immune checkpoint inhibitors on T cell-mediated cancer cell death by exploiting the power of live imaging and advanced image analysis algorithms. The integration of autologous immunosuppressive FAP+ cancer-associated fibroblasts impaired the response to anti-PD-1, indicating that tumors-on-chips are capable of recapitulating stroma-dependent mechanisms of immunotherapy resistance. For a small cohort of non-small cell lung cancer patients, we generated personalized tumors-on-chips with their autologous primary cells isolated from fresh tumor samples, and we measured the responses to anti-PD-1 treatment. These results support the power of tumor-on-chip technology in immuno-oncology research and open a path to future clinical validations.

Application and prospect of microfluidic devices for rapid assay of cell activities in the tumor microenvironment

The global impact of cancer on human health has raised significant concern. In this context, the tumor microenvironment (TME) plays a pivotal role in the tumorigenesis and malignant progression. In order to enhance the accuracy and efficacy of therapeutic outcomes, there is an imminent requirement for in vitro models that can accurately replicate the intricate characteristics and constituents of TME. Microfluidic devices exhibit notable advantages in investigating the progression and treatment of tumors and have the potential to become a novel methodology for evaluating immune cell activities in TME and assist clinicians in assessing the prognosis of patients. In addition, it shows great advantages compared to traditional cell experiments. Therefore, the review first outlines the applications and advantages of microfluidic chips in facilitating tumor cell culture, constructing TME and investigating immune cell activities. Second, the roles of microfluidic devices in the analysis of circulating tumor cells, tumor prognosis, and drug screening have also been mentioned. Moreover, a forward-looking perspective is discussed, anticipating the widespread clinical adoption of microfluidic devices in the future.

Advances in screening hyperthermic nanomedicines in 3D tumor models

Hyperthermic nanomedicines are particularly relevant for tackling human cancer, providing a valuable alternative to conventional therapeutics. The early-stage preclinical performance evaluation of such anti-cancer treatments is conventionally performed in flat 2D cell cultures that do not mimic the volumetric heat transfer occurring in human tumors. Recently, improvements in bioengineered 3D in vitro models have unlocked the opportunity to recapitulate major tumor microenvironment hallmarks and generate highly informative readouts that can contribute to accelerating the discovery and validation of efficient hyperthermic treatments. Leveraging on this, herein we aim to showcase the potential of engineered physiomimetic 3D tumor models for evaluating the preclinical efficacy of hyperthermic nanomedicines, featuring the main advantages and design considerations under diverse testing scenarios. The most recent applications of 3D tumor models for screening photo- and/or magnetic nanomedicines will be discussed, either as standalone systems or in combinatorial approaches with other anti-cancer therapeutics. We envision that breakthroughs toward developing multi-functional 3D platforms for hyperthermia onset and follow-up will contribute to a more expedited discovery of top-performing hyperthermic therapies in a preclinical setting before their in vivo screening.

A comprehensive review of 3D cancer models for drug screening and translational research

The 3D cancer models fill the discovery gap of 2D cancer models and play an important role in cancer research. In addition to cancer cells, a range of other factors include the stroma, density and composition of extracellular matrix, cancer-associated immune cells (e.g., cancer-associated fibroblasts cancer cell-stroma interactions and subsequent interactions, and a number of other factors (e.g., tumor vasculature and tumor-like microenvironment in vivo) has been widely ignored in the 2D concept of culture. Despite this knowledge, the continued use of monolayer cell culture methods has led to the failure of a series of clinical trials. This review discusses the immense importance of tumor microenvironment (TME) recapitulation in cancer research, prioritizing the individual roles of TME elements in cancer histopathology. The TME provided by the 3D model fulfills the requirements of in vivo spatiotemporal arrangement, components, and is helpful in analyzing various different aspects of drug sensitivity in preclinical and clinical trials, some of which are discussed here. Furthermore, it discusses models for the co-assembly of different TME elements in vitro and focuses on their synergistic function and responsiveness as tumors. Furthermore, this review broadly describes of a handful of recently developed 3D models whose main focus is limited to drug development and their screening and/or the impact of this approach in preclinical and translational research.

Engineering Heterogeneous Tumor Models for Biomedical Applications

Tumor tissue engineering holds great promise for replicating the physiological and behavioral characteristics of tumors in vitro. Advances in this field have led to new opportunities for studying the tumor microenvironment and exploring potential anti-cancer therapeutics. However, the main obstacle to the widespread adoption of tumor models is the poor understanding and insufficient reconstruction of tumor heterogeneity. In this review, the current progress of engineering heterogeneous tumor models is discussed. First, the major components of tumor heterogeneity are summarized, which encompasses various signaling pathways, cell proliferations, and spatial configurations. Then, contemporary approaches are elucidated in tumor engineering that are guided by fundamental principles of tumor biology, and the potential of a bottom-up approach in tumor engineering is highlighted. Additionally, the characterization approaches and biomedical applications of tumor models are discussed, emphasizing the significant role of engineered tumor models in scientific research and clinical trials. Lastly, the challenges of heterogeneous tumor models in promoting oncology research and tumor therapy are described and key directions for future research are provided.

Selection and Optimization of a Bioink Based on PANC-1- Plasma/Alginate/Methylcellulose for Pancreatic Tumour Modelling

3D bioprinting involves using bioinks that combine biological and synthetic materials. The selection of the most appropriate cell-material combination for a specific application is complex, and there is a lack of consensus on the optimal conditions required. Plasma-loaded alginate and alginate/methylcellulose (Alg/MC) inks were chosen to study their viscoelastic behaviour, degree of recovery, gelation kinetics, and cell survival after printing. Selected inks showed a shear thinning behavior from shear rates as low as 0.2 s-1, and the ink composed of 3% w/v SA and 9% w/v MC was the only one showing a successful stacking and 96% recovery capacity. A 0.5 × 106 PANC-1 cell-laden bioink was extruded with an Inkredible 3D printer (Cellink) through a D = 410 μm tip conical nozzle into 6-well culture plates. Cylindrical constructs were printed and crosslinked with CaCl2. Bioinks suffered a 1.845 Pa maximum pressure at the tip that was not deleterious for cellular viability. Cell aggregates can be appreciated for the cut total length observed in confocal microscopy, indicating a good proliferation rate at different heights of the construct, and suggesting the viability of the selected bioink PANC-1/P-Alg3/MC9 for building up three-dimensional bioprinted pancreatic tumor constructs.

Cancer 3D Models for Metallodrug Preclinical Testing

Despite being standard tools in research, the application of cellular and animal models in drug development is hindered by several limitations, such as limited translational significance, animal ethics, and inter-species physiological differences. In this regard, 3D cellular models can be presented as a step forward in biomedical research, allowing for mimicking tissue complexity more accurately than traditional 2D models, while also contributing to reducing the use of animal models. In cancer research, 3D models have the potential to replicate the tumor microenvironment, which is a key modulator of cancer cell behavior and drug response. These features make cancer 3D models prime tools for the preclinical study of anti-tumoral drugs, especially considering that there is still a need to develop effective anti-cancer drugs with high selectivity, minimal toxicity, and reduced side effects. Metallodrugs, especially transition-metal-based complexes, have been extensively studied for their therapeutic potential in cancer therapy due to their distinctive properties; however, despite the benefits of 3D models, their application in metallodrug testing is currently limited. Thus, this article reviews some of the most common types of 3D models in cancer research, as well as the application of 3D models in metallodrug preclinical studies.

Vessel Delineation Using U-Net: A Sparse Labeled Deep Learning Approach for Semantic Segmentation of Histological Images

Semantic segmentation is an important imaging analysis method enabling the identification of tissue structures. Histological image segmentation is particularly challenging, having large structural information while providing only limited training data. Additionally, labeling these structures to generate training data is time consuming. Here, we demonstrate the feasibility of a semantic segmentation using U-Net with a novel sparse labeling technique. The basic U-Net architecture was extended by attention gates, residual and recurrent links, and dropout regularization. To overcome the high class imbalance, which is intrinsic to histological data, under- and oversampling and data augmentation were used. In an ablation study, various architectures were evaluated, and the best performing model was identified. This model contains attention gates, residual links, and a dropout regularization of 0.125. The segmented images show accurate delineations of the vascular structures (with a precision of 0.9088 and an AUC-ROC score of 0.9717), and the segmentation algorithm is robust to images containing staining variations and damaged tissue. These results demonstrate the feasibility of sparse labeling in combination with the modified U-Net architecture.

Three-dimensional heterotypic colorectal cancer spheroid models for evaluation of drug response

Colorectal cancer (CRC) is a leading cause of death worldwide. Improved preclinical tumor models are needed to make treatment screening clinically relevant and address disease mortality. Advancements in 3D cell culture have enabled a greater recapitulation of the architecture and heterogeneity of the tumor microenvironment (TME). This has enhanced their pathophysiological relevance and enabled more accurate predictions of tumor progression and drug response in patients. An increasing number of 3D CRC spheroid models include cell populations such as cancer-associated fibroblasts (CAFs), endothelial cells (ECs), immune cells, and gut bacteria to better mimic the in vivo regulation of signaling pathways. Furthermore, cell heterogeneity within the 3D spheroid models enables the identification of new therapeutic targets to develop alternative treatments and test TME-target therapies. In this mini review, we present the advances in mimicking tumor heterogeneity in 3D CRC spheroid models by incorporating CAFs, ECs, immune cells, and gut bacteria. We introduce how, in these models, the diverse cells influence chemoresistance and tumor progression of the CRC spheroids. We also highlight important parameters evaluated during drug screening in the CRC heterocellular spheroids.

Combinatorial drug screening on 3D Ewing sarcoma spheroids using droplet-based microfluidics

Culturing and screening cells in microfluidics, particularly in three-dimensional formats, has the potential to impact diverse areas from fundamental biology to cancer precision medicine. Here, we use a platform based on anchored droplets for drug screening. The response of spheroids of Ewing sarcoma (EwS) A673 cells to simultaneous or sequential combinations of etoposide and cisplatin was evaluated. This was done by culturing spheroids of EwS cells inside 500 nL droplets then merging them with secondary droplets containing fluorescent-barcoded drugs at different concentrations. Differences in EwS spheroid growth and viability were measured by microscopy. After drug exposure such measurements enabled estimation of their IC50 values, which were in agreement with values obtained in standard multiwell plates. Then, synergistic drug combination was evaluated. Sequential combination treatment of EwS with etoposide applied 24 h before cisplatin resulted in amplified synergistic effect. As such, droplet-based microfluidics offers the modularity required for evaluation of drug combinations.

3D porous sodium alginate-silk fibroin composite bead based in vitro tumor model for screening of anti-cancer drug and induction of magneto-apoptosis

The development of 3D scaffold-based in vitro tumor models can help to address the limitations of cell culture and animal models for designing and screening anticancer drugs. In this study, in vitro 3D tumor models using sodium alginate (SA) and sodium alginate/silk fibroin (SA/SF) porous beads were developed. The beads were non-toxic and A549 cells had a high tendency to adhere, proliferate, and form tumor-like aggregates within SA/SF beads. The 3D tumor model based on these beads had better efficacy for anti-cancer drug screening than the 2D cell culture model. Additionally, the SA/SF porous beads loaded with superparamagnetic iron oxide nanoparticles were used to explore their magneto-apoptosis ability. The cells exposed to a high magnetic field were more likely to undergo apoptosis than those exposed to a low magnetic field. These findings suggest that the SA/SF porous beads and SPIONs loaded SA/SF porous beads-based tumor models could be useful for drug screening, tissue engineering, and mechanobiology studies.

Tumor microenvironment signaling and therapeutics in cancer progression

Tumor development and metastasis are facilitated by the complex interactions between cancer cells and their microenvironment, which comprises stromal cells and extracellular matrix (ECM) components, among other factors. Stromal cells can adopt new phenotypes to promote tumor cell invasion. A deep understanding of the signaling pathways involved in cell-to-cell and cell-to-ECM interactions is needed to design effective intervention strategies that might interrupt these interactions. In this review, we describe the tumor microenvironment (TME) components and associated therapeutics. We discuss the clinical advances in the prevalent and newly discovered signaling pathways in the TME, the immune checkpoints and immunosuppressive chemokines, and currently used inhibitors targeting these pathways. These include both intrinsic and non-autonomous tumor cell signaling pathways in the TME: protein kinase C (PKC) signaling, Notch, and transforming growth factor (TGF-β) signaling, Endoplasmic Reticulum (ER) stress response, lactate signaling, Metabolic reprogramming, cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) and Siglec signaling pathways. We also discuss the recent advances in Programmed Cell Death Protein 1 (PD-1), Cytotoxic T-Lymphocyte Associated Protein 4 (CTLA4), T-cell immunoglobulin mucin-3 (TIM-3) and Lymphocyte Activating Gene 3 (LAG3) immune checkpoint inhibitors along with the C-C chemokine receptor 4 (CCR4)- C-C class chemokines 22 (CCL22)/ and 17 (CCL17), C-C chemokine receptor type 2 (CCR2)- chemokine (C-C motif) ligand 2 (CCL2), C-C chemokine receptor type 5 (CCR5)- chemokine (C-C motif) ligand 3 (CCL3) chemokine signaling axis in the TME. In addition, this review provides a holistic understanding of the TME as we discuss the three-dimensional and microfluidic models of the TME, which are believed to recapitulate the original characteristics of the patient tumor and hence may be used as a platform to study new mechanisms and screen for various anti-cancer therapies. We further discuss the systemic influences of gut microbiota in TME reprogramming and treatment response. Overall, this review provides a comprehensive analysis of the diverse and most critical signaling pathways in the TME, highlighting the associated newest and critical preclinical and clinical studies along with their underlying biology. We highlight the importance of the most recent technologies of microfluidics and lab-on-chip models for TME research and also present an overview of extrinsic factors, such as the inhabitant human microbiome, which have the potential to modulate TME biology and drug responses.

3D Bioprinting for Tumor Metastasis Research

Tumor metastasis is a multiple cascade process where tumor cells disseminate from the primary site to distant organs and subsequently adapt to the foreign microenvironment. Simulating the physiology of tumor metastatic events in a realistic and three-dimensional (3D) manner is a challenge for in vitro modeling. 3D bioprinting strategies, which can generate well-customized and bionic structures, enable the exploration of dynamic tumor metastasis process in a species-homologous, high-throughput and reproducible way. In this review, we summarize the recent application of 3D bioprinting in constructing in vitro tumor metastatic models and discuss its advantages and current limitations. Further perspectives on how to harness the potential of accessible 3D bioprinting strategies to better model tumor metastasis and guide anti-cancer therapies are also provided.

Functional biomaterials for biomimetic 3D in vitro tumor microenvironment modeling

The translational potential of promising anticancer medications and treatments may be enhanced by the creation of 3D in vitro models that can accurately reproduce native tumor microenvironments. Tumor microenvironments for cancer treatment and research can be built in vitro using biomaterials. Three-dimensional in vitro cancer models have provided new insights into the biology of cancer. Cancer researchers are creating artificial three-dimensional tumor models based on functional biomaterials that mimic the microenvironment of the real tumor. Our understanding of tumor stroma activity over the course of cancer has improved because of the use of scaffold and matrix-based three-dimensional systems intended for regenerative medicine. Scientists have created synthetic tumor models thanks to recent developments in materials engineering. These models enable researchers to investigate the biology of cancer and assess the therapeutic effectiveness of available medications. The emergence of biomaterial engineering technologies with the potential to hasten treatment outcomes is highlighted in this review, which also discusses the influence of creating in vitro biomimetic 3D tumor microenvironments utilizing functional biomaterials. Future cancer treatments will rely much more heavily on biomaterials engineering.

3D bioprinting and the revolution in experimental cancer model systems-A review of developing new models and experiences with in vitro 3D bioprinted breast cancer tissue-mimetic structures

Growing evidence propagates those alternative technologies (relevant human cell-based-e.g., organ-on-chips or biofabricated models-or artificial intelligence-combined technologies) that could help in vitro test and predict human response and toxicity in medical research more accurately. In vitro disease model developments have great efforts to create and serve the need of reducing and replacing animal experiments and establishing human cell-based in vitro test systems for research use, innovations, and drug tests. We need human cell-based test systems for disease models and experimental cancer research; therefore, in vitro three-dimensional (3D) models have a renaissance, and the rediscovery and development of these technologies are growing ever faster. This recent paper summarises the early history of cell biology/cellular pathology, cell-, tissue culturing, and cancer research models. In addition, we highlight the results of the increasing use of 3D model systems and the 3D bioprinted/biofabricated model developments. Moreover, we present our newly established 3D bioprinted luminal B type breast cancer model system, and the advantages of in vitro 3D models, especially the bioprinted ones. Based on our results and the reviewed developments of in vitro breast cancer models, the heterogeneity and the real in vivo situation of cancer tissues can be represented better by using 3D bioprinted, biofabricated models. However, standardising the 3D bioprinting methods is necessary for future applications in different high-throughput drug tests and patient-derived tumour models. Applying these standardised new models can lead to the point that cancer drug developments will be more successful, efficient, and consequently cost-effective in the near future.

Dynamic Tumor Perfusion and Real-Time Monitoring in a Multiplexed 3D Printed Microdevice

Stereolithography based additive manufacturing ("3D printing") has become a useful tool for the development of novel microfluidic in vitro platforms. This method of manufacturing can reduce production time while allowing for rapid design iteration and complex monolithic structures. The platform described in this chapter has been designed for the capture and evaluation of cancer spheroids in perfusion. Spheroids are created in 3D Petri dishes, stained, and loaded into these 3D printed devices and imaged over time under flow conditions. This design allows for active perfusion into complex 3D cellular constructs resulting in longer viability while providing results which better mimic in vivo conditions compared to traditional monolayer static culture.

Advances in Tumor Organoids for the Evaluation of Drugs: A Bibliographic Review

Tumor organoids are defined as self-organized three-dimensional assemblies of heterogeneous cell types derived from patient samples that mimic the key histopathological, genetic, and phenotypic characteristics of the original tumor. This technology is proposed as an ideal candidate for the evaluation of possible therapies against cancer, presenting advantages over other models which are currently used. However, there are no reports in the literature that relate the techniques and material development of tumor organoids or that emphasize in the physicochemical and biological properties of materials that intent to biomimicry the tumor extracellular matrix. There is also little information regarding the tools to identify the correspondence of native tumors and tumoral organoids (tumoroids). Moreover, this paper relates the advantages of organoids compared to other models for drug evaluation. A growing interest in tumoral organoids has arisen from 2009 to the present, aimed at standardizing the process of obtaining organoids, which more accurately resemble patient-derived tumor tissue. Likewise, it was found that the characteristics to consider for the development of organoids, and therapeutic responses of them, are cell morphology, physiology, the interaction between cells, the composition of the cellular matrix, and the genetic, phenotypic, and epigenetic characteristics. Currently, organoids have been used for the evaluation of drugs for brain, lung, and colon tumors, among others. In the future, tumor organoids will become closer to being considered a better model for studying cancer in clinical practice, as they can accurately mimic the characteristics of tumors, in turn ensuring that the therapeutic response aligns with the clinical response of patients.

The impact of tumor associated macrophages on tumor biology under the lens of mathematical modelling: A review

In this article, we review the role of mathematical modelling to elucidate the impact of tumor-associated macrophages (TAMs) in tumor progression and therapy design. We first outline the biology of TAMs, and its current application in tumor therapies, and their experimental methods that provide insights into tumor cell-macrophage interactions. We then focus on the mechanistic mathematical models describing the role of macrophages as drug carriers, the impact of macrophage polarized activation on tumor growth, and the role of tumor microenvironment (TME) parameters on the tumor-macrophage interactions. This review aims to identify the synergies between biological and mathematical approaches that allow us to translate knowledge on fundamental TAMs biology in addressing current clinical challenges.

The SUMO protease SENP1 promotes aggressive behaviors of high HIF2α expressing renal cell carcinoma cells

While an important role for the SUMO protease SENP1 is recognized in multiple solid cancers, its role in renal cell carcinoma (RCC) pathogenesis, particularly the most dominant subtype, clear cell RCC (ccRCC), is poorly understood. Here we show that a combination of high HIF2α and SENP1 expression in ccRCC samples predicts poor patient survival. Using ccRCC cell models that express high HIF2α but low SENP1, we show that overexpression of SENP1 reduces sumoylation and ubiquitination of HIF2α, increases HIF2α transcriptional activity, and enhances expression of genes associated with cancer cell invasion, stemness and epithelial-mesenchymal transition. Accordingly, ccRCC cells with high HIF2α and SENP1 showed increased invasion and sphere formation in vitro, and local invasion and metastasis in vivo. Finally, SENP1 overexpression caused high HIF2α ccRCC cells to acquire resistance to a clinical mTOR inhibitor, everolimus. These results reveal a combination of high SENP1 and HIF2α expression gives particularly poor prognosis for ccRCC patients and suggest that SENP1 may be an attractive new target for treating metastatic RCC (mRCC).

Tumor microenvironment: barrier or opportunity towards effective cancer therapy

Tumor microenvironment (TME) is a specialized ecosystem of host components, designed by tumor cells for successful development and metastasis of tumor. With the advent of 3D culture and advanced bioinformatic methodologies, it is now possible to study TME’s individual components and their interplay at higher resolution. Deeper understanding of the immune cell’s diversity, stromal constituents, repertoire profiling, neoantigen prediction of TMEs has provided the opportunity to explore the spatial and temporal regulation of immune therapeutic interventions. The variation of TME composition among patients plays an important role in determining responders and non-responders towards cancer immunotherapy. Therefore, there could be a possibility of reprogramming of TME components to overcome the widely prevailing issue of immunotherapeutic resistance. The focus of the present review is to understand the complexity of TME and comprehending future perspective of its components as potential therapeutic targets. The later part of the review describes the sophisticated 3D models emerging as valuable means to study TME components and an extensive account of advanced bioinformatic tools to profile TME components and predict neoantigens. Overall, this review provides a comprehensive account of the current knowledge available to target TME.

3D printed devices with integrated collagen scaffolds for cell culture studies including transepithelial/transendothelial electrical resistance (TEER) measurements

In this paper, we describe the use of 3D printed devices for both static and flow studies that contain electrospun collagen scaffolds and can accommodate transepithelial/transendothelial electrical resistance (TEER) measurements. Electrospinning was used to create the collagen scaffold, followed by an optimized 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide/N-Hydroxysuccinimide (EDC/NHS) cross-linking procedure to produce stable collagen fibers that are similar in size to fibers in vivo. LC/MS was used to study the leaching of solvent and NHS from the scaffold, with several rinsing steps being shown to eliminate the leaching and promote the culture of Madin-Darby Canine Kidney (MDCK) epithelial cells on the scaffold. Both static and flow 2-part devices were successfully fabricated by 3D printing using either VeroClear or MED610 material (PolyJet printing) and assembling the scaffold between laser cut Teflon gaskets. The devices were designed to easily accommodate commonly used STX2 chopstick electrodes for TEER measurements. A detailed comparison was made between the use of collagen scaffolds vs other electrospun materials for cell culture. The collagen extracellular matrix model displayed a high barrier functionality for up to 7 days. In addition, a different 3D printed device with a collagen scaffold is described to incorporate continuous flow and replenishment of media under the cell layer in a manner that also enables periodic recording of TEER measurements. Overall, this work shows that the combination of biological ECM materials such as collagen into microfluidic devices that incorporate flow have great potential to form more realistic cell culture models in areas such as blood brain barrier research.

Legumain/pH dual-responsive lytic peptide-paclitaxel conjugate for synergistic cancer therapy

After molecule targeted drug, monoclonal antibody and antibody–drug conjugates (ADCs), peptide–drug conjugates (PDCs) have become the next generation targeted anti-tumor drugs due to its properties of low molecule weight, efficient cell penetration, low immunogenicity, good pharmacokinetic and large-scale synthesis by solid phase synthesis. Herein, we present a lytic peptide PTP7-drug paclitaxel conjugate assembling nanoparticles (named PPP) that can sequentially respond to dual stimuli in the tumor microenvironment, which was designed for passive tumor-targeted delivery and on-demand release of a tumor lytic peptide (PTP-7) as well as a chemotherapeutic agent of paclitaxel (PTX). To achieve this, tumor lytic peptide PTP-7 was connected with polyethylene glycol by a peptide substrate of legumain to serve as hydrophobic segments of nanoparticles to protect the peptide from enzymatic degradation. After that, PTX was connected to the amino group of the polypeptide side chain through an acid-responsive chemical bond (2-propionic-3-methylmaleic anhydride, CDM). Therefore, the nanoparticle (PPP) collapsed when it encountered the weakly acidic tumor microenvironment where PTX molecules fell off, and further triggered the cleavage of the peptide substrate by legumain that is highly expressed in tumor stroma and tumor cell surface. Moreover, PPP presents improved stability, improved drug solubility, prolonged blood circulation and significant inhibition ability on tumor growth, which gives a reasonable strategy to accurately deliver small molecule drugs and active peptides simultaneously to tumor sites.

Paradoxical Behavior of Oncogenes Undermines the Somatic Mutation Theory

The currently accepted theory on the influence of DNA mutations on carcinogenesis (the Somatic Mutation Theory, SMT) is facing an increasing number of controversial results that undermine the explanatory power of mutated genes considered as "causative" factors. Intriguing results have demonstrated that several critical genes may act differently, as oncogenes or tumor suppressors, while phenotypic reversion of cancerous cells/tissues can be achieved by modifying the microenvironment, the mutations they are carrying notwithstanding. Furthermore, a high burden of mutations has been identified in many non-cancerous tissues without any apparent pathological consequence. All things considered, a relevant body of unexplained inconsistencies calls for an in depth rewiring of our theoretical models. Ignoring these paradoxes is no longer sustainable. By avoiding these conundrums, the scientific community will deprive itself of the opportunity to achieve real progress in this important biomedical field. To remedy this situation, we need to embrace new theoretical perspectives, taking the cell-microenvironment interplay as the privileged pathogenetic level of observation, and by assuming new explanatory models based on truly different premises. New theoretical frameworks dawned in the last two decades principally focus on the complex interaction between cells and their microenvironment, which is thought to be the critical level from which carcinogenesis arises. Indeed, both molecular and biophysical components of the stroma can dramatically drive cell fate commitment and cell outcome in opposite directions, even in the presence of the same stimulus. Therefore, such a novel approach can help in solving apparently inextricable paradoxes that are increasingly observed in cancer biology.

An Easy-to-Fabricate Microfluidic Shallow Trench Induced Three-Dimensional Cell Culturing and Imaging (STICI3D) Platform

Compared to the established monolayer approach of two-dimensional cell cultures, three-dimensional (3D) cultures more closely resemble in vivo models; that is, the cells interact and form clusters mimicking their organization in native tissue. Therefore, the cellular microenvironment of these 3D cultures proves to be more clinically relevant. In this study, we present a novel easy-to-fabricate microfluidic shallow trench induced 3D cell culturing and imaging (STICI3D) platform, suitable for rapid fabrication as well as mass manufacturing. Our design consists of a shallow trench, within which various hydrogels can be formed in situ via capillary action, between and fully in contact with two side channels that allow cell seeding and media replenishment, as well as forming concentration gradients of various molecules. Compared to a micropillar-based burst valve design, which requires sophisticated microfabrication facilities, our capillary-based STICI3D can be fabricated using molds prepared with simple adhesive tapes and razors alone. The simple design supports the easy applicability of mass-production methods such as hot embossing and injection molding as well. To optimize the STICI3D design, we investigated the effect of individual design parameters such as corner radii, trench height, and surface wettability under various inlet pressures on the confinement of a hydrogel solution within the shallow trench using Computational Fluid Dynamics simulations supported with experimental validation. We identified ideal design values that improved the robustness of hydrogel confinement and reduced the effect of end-user dependent factors such as hydrogel solution loading pressure. Finally, we demonstrated cultures of human mesenchymal stem cells and human umbilical cord endothelial cells in the STICI3D to show that it supports 3D cell cultures and enables precise control of cellular microenvironment and real-time microscopic imaging. The easy-to-fabricate and highly adaptable nature of the STICI3D platform makes it suitable for researchers interested in fabricating custom polydimethylsiloxane devices as well as those who are in need of ready-to-use plastic platforms. As such, STICI3Ds can be used in imaging cell-cell interactions, angiogenesis, semiquantitative analysis of drug response in cells, and measurement of transport through cell sheet barriers.

Instructive Hydrogels for Primary Tumor Cell Culture: Current Status and Outlook

Primary tumor organoids (PTOs) growth in hydrogels have emerged as an important in vitro model that recapitulates many characteristics of the native tumor tissue, and have important applications in fundamental cancer research and for the development of useful therapeutic treatment. This paper begins with reviewing the methods of isolation of primary tumor cells. Then, recent advances on the instructive hydrogels as biomimetic extracellular matrix for primary tumor cell culture and construction of PTO models are summarized. Emerging microtechnology for growth of PTOs in microscale hydrogels and the applications of PTOs are highlighted. This paper concludes with an outlook on the future directions in the investigation of instructive hydrogels for PTO growth.

Regulation of Tumor Invasion by the Physical Microenvironment: Lessons from Breast and Brain Cancer

The success of anticancer therapies is often limited by heterogeneity within and between tumors. While much attention has been devoted to understanding the intrinsic molecular diversity of tumor cells, the surrounding tissue microenvironment is also highly complex and coevolves with tumor cells to drive clinical outcomes. Here, we propose that diverse types of solid tumors share common physical motifs that change in time and space, serving as universal regulators of malignancy. We use breast cancer and glioblastoma as instructive examples and highlight how invasion in both diseases is driven by the appropriation of structural guidance cues, contact-dependent heterotypic interactions with stromal cells, and elevated interstitial fluid pressure and flow. We discuss how engineering strategies show increasing value for measuring and modeling these physical properties for mechanistic studies. Moreover, engineered systems offer great promise for developing and testing novel therapies that improve patient prognosis by normalizing the physical tumor microenvironment. Expected final online publication date for the Annual Review of Biomedical Engineering, Volume 24 is June 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Organ on Chip Technology to Model Cancer Growth and Metastasis

Organ on chip (OOC) has emerged as a major technological breakthrough and distinct model system revolutionizing biomedical research and drug discovery by recapitulating the crucial structural and functional complexity of human organs in vitro. OOC are rapidly emerging as powerful tools for oncology research. Indeed, Cancer on chip (COC) can ideally reproduce certain key aspects of the tumor microenvironment (TME), such as biochemical gradients and niche factors, dynamic cell-cell and cell-matrix interactions, and complex tissue structures composed of tumor and stromal cells. Here, we review the state of the art in COC models with a focus on the microphysiological systems that host multicellular 3D tissue engineering models and can help elucidate the complex biology of TME and cancer growth and progression. Finally, some examples of microengineered tumor models integrated with multi-organ microdevices to study disease progression in different tissues will be presented.

Microfluidic Arrays of Breast Tumor Spheroids for Drug Screening and Personalized Cancer Therapies

One of the obstacles limiting progress in the development of effective cancer therapies is the shortage of preclinical models that capture the dynamic nature of tumor microenvironments. Interstitial flow strongly impacts tumor response to chemotherapy; however, conventional in vitro cancer models largely disregard this key feature. Here, a proof of principle microfluidic platform for the generation of large arrays of breast tumor spheroids that are grown under close-to-physiological flow in a biomimetic hydrogel is reported. This cancer spheroids-on-a-chip model is used for time- and labor-efficient studies of the effects of drug dose and supply rate on the chemosensitivity of breast tumor spheroids. The capability to grow large arrays of tumor spheroids from patient-derived cells of different breast cancer subtypes is shown, and the correlation between in vivo drug efficacy and on-chip spheroid drug response is demonstrated. The proposed platform can serve as an in vitro preclinical model for the development of personalized cancer therapies and effective screening of new anticancer drugs.

Microfluidic Biosensor-Based Devices for Rapid Diagnosis and Effective Anti-cancer Therapeutic Monitoring for Breast Cancer Metastasis

Breast cancer with unpredictable metastatic recurrence is the leading cause of cancer-related mortality. Early cancer detection and optimized therapy are the principal determining factors for increased survival rate. Worldwide, researchers and clinicians are in search of efficient strategies for the timely management of cancer progression. Efficient preclinical models provide information on cancer initiation, malignancy progression, relapse, and drug efficacy. The distinct histopathological features and clinical heterogeneity allows no single model to mimic breast tumor. However, engineering three-dimensional (3D) in vitro models incorporating cells and biophysical cues using a combination of organoid culture, 3D printing, and microfluidic technology could recapitulate the tumor microenvironment. These models serve to be preferable predictive models bridging the translational research gap in drug development. Microfluidic device is a cost-effective advanced in vitro model for cancer research, diagnosis, and drug assay under physiologically relevant conditions. Integrating a biosensor with microfluidics allows rapid real-time analytical validation to provide highly sensitive, specific, reproducible, and reliable outcomes. In this manner, the multi-system approach in identifying biomarkers associated with cancer facilitates early detection, therapeutic window optimization, and post-treatment evaluation.This chapter showcases the advancements related to in vitro breast cancer metastasis models focusing on microfluidic devices. The chapter aims to provide an overview of microfluidic biosensor-based devices for cancer detection and high-throughput chemotherapeutic drug screening.

Microfluidic Systems for Cancer Diagnosis and Applications

Microfluidic devices have led to novel biological advances through the improvement of micro systems that can mimic and measure. Microsystems easily handle sub-microliter volumes, obviously with guidance presumably through laminated fluid flows. Microfluidic systems have production methods that do not need expert engineering, away from a centralized laboratory, and can implement basic and point of care analysis, and this has attracted attention to their widespread dissemination and adaptation to specific biological issues. The general use of microfluidic tools in clinical settings can be seen in pregnancy tests and diabetic control, but recently microfluidic platforms have become a key novel technology for cancer diagnostics. Cancer is a heterogeneous group of diseases that needs a multimodal paradigm to diagnose, manage, and treat. Using advanced technologies can enable this, providing better diagnosis and treatment for cancer patients. Microfluidic tools have evolved as a promising tool in the field of cancer such as detection of a single cancer cell, liquid biopsy, drug screening modeling angiogenesis, and metastasis detection. This review summarizes the need for the low-abundant blood and serum cancer diagnosis with microfluidic tools and the progress that has been followed to develop integrated microfluidic platforms for this application in the last few years.

Advances on colorectal cancer 3D models: The needed translational technology for nanomedicine screening

Colorectal cancer (CRC) is a heterogeneous and molecularly complex disease, associated with high mortality worldwide, exposing the urgent need for novel therapeutic approaches. Their development and translation to the clinic have been hampered, partially due to the absence of reliable cellular models that resemble key features of the human disease. While traditional 2D models are not able to provide consistent and predictive responses about the in vivo efficiency of the formulation, animal models frequently fail to recapitulate cancer progression and to reproduce adverse effects. On its turn, multicellular 3D systems, by mimicking key genetic, physical and mechanical cues of the tumor microenvironment, constitute a promising tool in cancer research. In addition, they constitute more physiological and relevant environment for anticancer drugs screening and for predicting patient's response towards personalized approaches, bridging the gap between simplified 2D models and unrepresentative animal models. In this review, we provide an overview of CRC 3D models for translational research, with focus on their potential for nanomedicines screening.

Tumor grafted - chick chorioallantoic membrane as an alternative model for biological cancer research and conventional/nanomaterial-based theranostics evaluation

Introduction: Advancements in cancer management and treatment are associated with strong preclinical research data, in which reliable cancer models are demanded. Indeed, inconsistent preclinical findings and stringent regulations following the 3Rs principle of reduction, refinement, and replacement of conventional animal models currently pose challenges in the development and translation of efficient technologies. The chick embryo chorioallantoic membrane (CAM) is a system for the evaluation of treatment effects on the vasculature, therefore suitable for studies on angiogenesis. Apart from vascular effects, the model is now increasingly employed as a preclinical cancer model following tumor-grafting procedures.Areas covered: The broad application of CAM tumor model is highlighted along with the methods for analyzing the neoplasm and vascular system. The presented and cited investigations focus on cancer biology and treatment, encompassing both conventional and emerging nanomaterial-based modalities.Expert opinion: The CAM tumor model finds increased significance given the influences of angiogenesis and the tumor microenvironment in cancer behavior, then providing a qualified miniature system for oncological research. Ultimately, the establishment and increased employment of such a model may resolve some of the limitations present in the standard preclinical tumor models, thereby redefining the preclinical research workflow.

Immunocompetent cancer-on-chip models to assess immuno-oncology therapy

The advances in cancer immunotherapy come with several obstacles, limiting its widespread use and benefits so far only to a small subset of patients. One of the underlying challenges remains to be the lack of representative nonclinical models that translate to human immunity and are able to predict clinical efficacy and safety outcomes. In recent years, immunocompetent Cancer-on-Chip models emerge as an alternative human-based platform that enables the integration and manipulation of complex tumor microenvironment. In this review, we discuss novel opportunities offered by Cancer-on-Chip models to advance (mechanistic) immuno-oncology research, ranging from design flexibility to multimodal analysis approaches. We then exemplify their (potential) applications for the research and development of adoptive cell therapy, immune checkpoint therapy, cytokine therapy, oncolytic virus, and cancer vaccines.

A multilayered blood vessel/tumor tissue chip to investigate T cell infiltration into solid tumor tissues

Cancer immunotherapies based on the ability of T cells to recognize and kill tumor cells (TCs), including immune checkpoint blockade (ICB) therapy and chimeric antigen receptor (CAR) T cell therapy, have been greatly successful recently, but they are applicable for only a fraction of patients. One of the main challenges in cancer immunotherapy is the improvement of T cell infiltration into solid tumor tissues, as T cells can exert cytotoxicity against TCs only when they are in contact with TCs. T cells in the bloodstream infiltrate into solid tumor tissues by following two steps known as extravasation and interstitial migration. Herein, we developed a multilayered blood vessel/tumor tissue chip (MBTC) that allows systematic investigation on T cell tumor infiltration. The MBTC is composed of a top fluidic chamber, a porous membrane covered with an endothelial cell (EC) monolayer, and a collagen gel block encapsulating TCs. The full sequence of T cell tumor infiltration, including extravasation and interstitial migration, required for TC killing is demonstrated in the MBTCs: T cells applied through the top fluidic chamber of the MBTCs exhibited dynamic interactions with ECs for extravasation, including intraluminal crawling and transendothelial migration (TEM). After extravasation, T cells migrate toward TCs located at the bottom of a collagen block to kill them. Key characteristics of T cell dynamics in tumor microenvironments are recapitulated in the MBTCs: the vascular endothelial growth factor (VEGF) produced by TCs suppressed EC activation by inflammatory cytokines, or induced EC anergy, thereby significantly reducing T cell extravasation, whereas chemokines produced by TCs triggered T cell chemotaxis toward TCs. Anti-VEGF treatment in the MBTCs reverts EC anergy and promotes T cell infiltration, similar to the clinical effects of anti-VEGF. The MBTC is a useful model for pre-clinical evaluation of immunotherapeutics and the fundamental study of tumor immunology.

A Hybrid In Silico and Tumor-on-a-Chip Approach to Model Targeted Protein Behavior in 3D Microenvironments

Simple Summary

Engineered proteins possess a great therapeutic potential, but the development of such therapies is impeded during preclinical studies by the lack of in vitro models that accurately simulate the human physiology. Animal models, on the other hand, also have difficulties predicting human responses, and are ethically concerning. In this study, we employed a hybrid approach where we combined mathematical modeling with 3D in vitro models that mimic aspects of the tumor microenvironment, in order to simulate the delivery of therapeutic proteins targeting cancer cells and to predict the biological activity. By cross-comparing simulated and experimental data from 3D models, we were able to correctly predict the best dose needed to deliver toxic proteins specifically to tumor cells, while leaving the surrounding non-tumor cells untouched. This study shows the potential of combining computational approaches with novel in vitro models to advance the development of protein therapeutics.

Abstract

To rationally improve targeted drug delivery to tumor cells, new methods combining in silico and physiologically relevant in vitro models are needed. This study combines mathematical modeling with 3D in vitro co-culture models to study the delivery of engineered proteins, called designed ankyrin repeat proteins (DARPins), in biomimetic tumor microenvironments containing fibroblasts and tumor cells overexpressing epithelial cell adhesion molecule (EpCAM) or human epithelial growth factor receptor (HER2). In multicellular tumor spheroids, we observed strong binding-site barriers in combination with low apparent diffusion coefficients of 1 µm²·s⁻¹ and 2 µm² ·s⁻¹ for EpCAM- and HER2-binding DARPin, respectively. Contrasting this, in a tumor-on-a-chip model for investigating delivery in real-time, transport was characterized by hindered diffusion as a consequence of the lower local tumor cell density. Finally, simulations of the diffusion of an EpCAM-targeting DARPin fused to a fragment of Pseudomonas aeruginosa exotoxin A, which specifically kills tumor cells while leaving fibroblasts untouched, correctly predicted the need for concentrations of 10 nM or higher for extensive tumor cell killing on-chip, whereas in 2D models picomolar concentrations were sufficient. These results illustrate the power of combining in vitro models with mathematical modeling to study and predict the protein activity in complex 3D models.

Using 3D in vitro cell culture models in anti-cancer drug discovery

INTRODUCTION

The high failure rate in drug discovery remains a costly and time-consuming challenge. Improving the odds of success in the early steps of drug development requires disease models with high biological relevance for biomarker discovery and drug development. The adoption of three-dimensional (3D) cell culture systems over traditional monolayers in cell-based assays is considered a promising step toward improving the success rate in drug discovery.

AREAS COVERED

In this article, the author focuses on new technologies for 3D cell culture and their applications in cancer drug discovery. Besides the most common 3D cell-culture systems for tumor cells, the article emphasizes the need for 3D cell culture technologies that can mimic the complex tumor microenvironment and cancer stem cell niche.

EXPERT OPINION

There has been a rapid increase in 3D cell culture technologies in recent years in an effort to more closely mimic in vivo physiology. Each 3D cell culture system has its own strengths and weaknesses with regard to in vivo tumor growth and the tumor microenvironment. This requires careful consideration of which 3D cell culture system is chosen for drug discovery and should be based on factors like drug target and tumor origin.

Apoptosis mapping in space and time of 3D tumor ecosystems reveals transmissibility of cytotoxic cancer death

The emerging tumor-on-chip (ToC) approaches allow to address biomedical questions out of reach with classical cell culture techniques: in biomimetic 3D hydrogels they partially reconstitute ex vivo the complexity of the tumor microenvironment and the cellular dynamics involving multiple cell types (cancer cells, immune cells, fibroblasts, etc.). However, a clear bottleneck is the extraction and interpretation of the rich biological information contained, sometime hidden, in the cell co-culture videos. In this work, we develop and apply novel video analysis algorithms to automatically measure the cytotoxic effects on human cancer cells (lung and breast) induced either by doxorubicin chemotherapy drug or by autologous tumor-infiltrating cytotoxic T lymphocytes (CTL). A live fluorescent dye (red) is used to selectively pre-stain the cancer cells before co-cultures and a live fluorescent reporter for caspase activity (green) is used to monitor apoptotic cell death. The here described open-source computational method, named STAMP (spatiotemporal apoptosis mapper), extracts the temporal kinetics and the spatial maps of cancer death, by localizing and tracking cancer cells in the red channel, and by counting the red to green transition signals, over 2-3 days. The robustness and versatility of the method is demonstrated by its application to different cell models and co-culture combinations. Noteworthy, this approach reveals the strong contribution of primary cancer-associated fibroblasts (CAFs) to breast cancer chemo-resistance, proving to be a powerful strategy to investigate intercellular cross-talks and drug resistance mechanisms. Moreover, we defined a new parameter, the 'potential of death induction', which is computed in time and in space to quantify the impact of dying cells on neighbor cells. We found that, contrary to natural death, cancer death induced by chemotherapy or by CTL is transmissible, in that it promotes the death of nearby cancer cells, suggesting the release of diffusible factors which amplify the initial cytotoxic stimulus.

Simplified ARCHITECT microfluidic chip through a dual-flip strategy enables stable and versatile tumoroid formation combined with label-free quantitative proteomic analysis

Recent years, microfluidic three-dimensional(3D) tumor culture technique has made great progress in tumor microenvironment simulation and drug screening. Meanwhile, as their functionality and complexity increase, it is more difficult for current chip models to selectively collect specific-layer cells from tumoroids for further analysis. Moreover, a simplified and robust method for tumoroid formation with highly consistent size and repeatable 3D morphology is relatively ncessary. Here, we report an ARCHITECT (ARtificial CHIp for Tumor Enables Confocal Topography observation) chip, through a dual-flip strategy to implement straightforward tumoroid establishment. This platform guarantees stable batch-to-batch tumoroids formation and allows high resolution confocal imaging. Moreover, an initial cell density as low as 65 cells per chamber is efficient to deliver a tumoroid. With this ARCHITECT chip, different-layer cells of interest could be collected from tumoroid for label-free quantitative(LFQ) proteomic analysis. For application demonstration, we mainly verified this platform for lung carcinoma (A549) tumoroid construction and proteomic analysis at out layer. Our data indicate that the out-layer cells of A549 tumoroid show extensively distinct proteomic expressions compared to two-dimensional cultured A549 cells. The up-regulated proteins are mainly related to tumorigenicity, proliferation and metastasis. And the differentially expressed proteins are mainly relevant to lipid metabolism pathway which is essential to tumor progression and proliferation. This platform provides a simplified yet robust technique to connect microfluidic tumoroid construction and LFQ proteomic analysis. The simplicity of this technique should open the way to numerous applications such as discovering the innovative targets for cancer treatment, and studying the mophological and proteomic heterogeneity of different-layer cells across the tumoroid.

Hybrid Graphene-Gold Nanoparticle-based Nucleic Acid Conjugates for Cancer-Specific Multimodal Imaging and Combined Therapeutics

Nanoparticle-based nucleic acid conjugates (NP-NACs) hold great promise for theragnostic (diagnostic and therapeutic) applications. However, several limitations have hindered the realization of their full potential in the clinical treatment of cancer and other diseases. In diagnosis, NP-NACs, combined with conventional optical sensing systems, have been applied for cancer detection in vitro, but low signal-to-noise ratios limit their broad in vivo applications. Meanwhile, the efficiency of NP-NAC-mediated cancer therapies has been limited through the adaptation of alternative pro-survival pathways in cancer cells. The recent emergence of personalized and precision medicine has outlined the importance of both accurate diagnosis and efficient therapeutics in a single platform. As such, we report the controlled assembly of hybrid graphene oxide/gold nanoparticle-based cancer-specific NACs (Au@GO NP-NACs) for multimodal imaging and combined therapeutics. Our developed Au@GO NP-NACs shows excellent surface-enhanced Raman scattering (SERS)-mediated live-cell cancer detection and multimodal synergistic cancer therapy through the use of photothermal, genetic, and chemotherapeutic strategies. Synergistic and selective killing of cancer cells were then demonstrated by using in vitro microfluidic models and nine different cancer cell lines by further incorporating near-infrared photothermal hyperthermia, a Topoisomerase II anti-cancer drug, and cancer targeting peptides. Moreover, with distinctive advantages of the Au@GO NP-NACs for cancer theragnostics, we further demonstrated precision cancer treatment through the detection of cancer cells in vivo using SERS followed by efficient ablation of the tumor. Therefore, our Au@GO NP-NACs could pave a new road for the advanced theragnostics of cancer as well as many other diseases.

Toward improved in vitro models of human cancer

Cancer is a leading cause of death across the world and continues to increase in incidence. Despite years of research, multiple tumors (e.g., glioblastoma, pancreatic cancer) still have limited treatment options in the clinic. Additionally, the attrition rate and cost of drug development have continued to increase. This trend is partly explained by the poor predictive power of traditional in vitro tools and animal models. Moreover, multiple studies have highlighted that cell culture in traditional Petri dishes commonly fail to predict drug sensitivity. Conversely, animal models present differences in tumor biology compared with human pathologies, explaining why promising therapies tested in animal models often fail when tested in humans. The surging complexity of patient management with the advent of cancer vaccines, immunotherapy, and precision medicine demands more robust and patient-specific tools to better inform our understanding and treatment of human cancer. Advances in stem cell biology, microfluidics, and cell culture have led to the development of sophisticated bioengineered microscale organotypic models (BMOMs) that could fill this gap. In this Perspective, we discuss the advantages and limitations of patient-specific BMOMs to improve our understanding of cancer and how these tools can help to confer insight into predicting patient response to therapy.

High blood flow shear stress values are associated with circulating tumor cells cluster disaggregation in a multi-channel microfluidic device

Metastasis represents a dynamic succession of events involving tumor cells which disseminate through the organism via the bloodstream. Circulating tumor cells (CTCs) can flow the bloodstream as single cells or as multicellular aggregates (clusters), which present a different potential to metastasize. The effects of the bloodstream-related physical constraints, such as hemodynamic wall shear stress (WSS), on CTC clusters are still unclear. Therefore, we developed, upon theoretical and CFD modeling, a new multichannel microfluidic device able to simultaneously reproduce different WSS characterizing the human circulatory system, where to analyze the correlation between SS and CTC clusters behavior. Three physiological WSS levels (i.e. 2, 5, 20 dyn/cm2) were generated, reproducing values typical of capillaries, veins and arteries. As first validation, triple-negative breast cancer cells (MDA-MB-231) were injected as single CTCs showing that higher values of WSS are correlated with a decreased viability. Next, the SS-mediated disaggregation of CTC clusters was computationally investigated in a vessels-mimicking domain. Finally, CTC clusters were injected within the three different circuits and subjected to the three different WSS, revealing that increasing WSS levels are associated with a raising clusters disaggregation after 6 hours of circulation. These results suggest that our device may represent a valid in vitro tool to carry out systematic studies on the biological significance of blood flow mechanical forces and eventually to promote new strategies for anticancer therapy.

Microengineered 3D Tumor Models for Anti-Cancer Drug Discovery in Female-Related Cancers

The burden of cancer continues to increase in society and negatively impacts the lives of numerous patients. Due to the high cost of current treatment strategies, there is a crucial unmet need to develop inexpensive preclinical platforms to accelerate the process of anti-cancer drug discovery to improve outcomes in cancer patients, most especially in female patients. Many current methods employ expensive animal models which not only present ethical concerns but also do not often accurately predict human physiology and the outcomes of anti-cancer drug responsiveness. Conventional treatment approaches for cancer generally include systemic therapy after a surgical procedure. Although this treatment technique is effective, the outcome is not always positive due to various complex factors such as intratumor heterogeneity and confounding factors within the tumor microenvironment (TME). Patients who develop metastatic disease still have poor prognosis. To that end, recent efforts have attempted to use 3D microengineered platforms to enhance the predictive power and efficacy of anti-cancer drug screening, ultimately to develop personalized therapies. Fascinating features of microengineered assays, such as microfluidics, have led to the advancement in the development of the tumor-on-chip technology platforms, which have shown tremendous potential for meaningful and physiologically relevant anti-cancer drug discovery and screening. Three dimensional microscale models provide unprecedented ability to unveil the biological complexities of cancer and shed light into the mechanism of anti-cancer drug resistance in a timely and resource efficient manner. In this review, we discuss recent advances in the development of microengineered tumor models for anti-cancer drug discovery and screening in female-related cancers. We specifically focus on female-related cancers to draw attention to the various approaches being taken to improve the survival rate of women diagnosed with cancers caused by sex disparities. We also briefly discuss other cancer types like colon adenocarcinomas and glioblastoma due to their high rate of occurrence in females, as well as the high likelihood of sex-biased mutations which complicate current treatment strategies for women. We highlight recent advances in the development of 3D microscale platforms including 3D tumor spheroids, microfluidic platforms as well as bioprinted models, and discuss how they have been utilized to address major challenges in the process of drug discovery, such as chemoresistance, intratumor heterogeneity, drug toxicity, etc. We also present the potential of these platform technologies for use in high-throughput drug screening approaches as a replacements of conventional assays. Within each section, we will provide our perspectives on advantages of the discussed platform technologies.