Dissecting Effects of Anti-cancer Drugs and Cancer-Associated Fibroblasts by On-Chip Reconstitution of Immunocompetent Tumor Microenvironments

Cell Electrokinetic Fingerprint: A Novel Approach Based on Optically Induced Dielectrophoresis (ODEP) for In-Flow Identification of Single Cells

A novel optically induced dielectrophoresis (ODEP) system that can operate under flow conditions is designed for automatic trapping of cells and subsequent induction of 2D multi-frequency cell trajectories. Like in a "ping-pong" match, two virtual electrode barriers operate in an alternate mode with varying frequencies of the input voltage. The so-derived cell motions are characterized via time-lapse microscopy, cell tracking, and state-of-the-art machine learning algorithms, like the wavelet scattering transform (WST). As a cell-electrokinetic fingerprint, the dynamic of variation of the cell displacements happening, over time, is quantified in response to different frequency values of the induced electric field. When tested on two biological scenarios in the cancer domain, the proposed approach discriminates cellular dielectric phenotypes obtained, respectively, at different early phases of drug-induced apoptosis in prostate cancer (PC3) cells and for differential expression of the lectine-like oxidized low-density lipoprotein receptor-1 (LOX-1) transcript levels in human colorectal adenocarcinoma (DLD-1) cells. The results demonstrate increased discrimination of the proposed system and pose an additional basis for making ODEP-based assays addressing cancer heterogeneity for precision medicine and pharmacological research.

Advancing Intelligent Organ-on-a-Chip Systems with Comprehensive In Situ Bioanalysis

In vitro models are essential to a broad range of biomedical research, such as pathological studies, drug development, and personalized medicine. As a potentially transformative paradigm for 3D in vitro models, organ-on-a-chip (OOC) technology has been extensively developed to recapitulate sophisticated architectures and dynamic microenvironments of human organs by applying the principles of life sciences and leveraging micro- and nanoscale engineering capabilities. A pivotal function of OOC devices is to support multifaceted and timely characterization of cultured cells and their microenvironments. However, in-depth analysis of OOC models typically requires biomedical assay procedures that are labor-intensive and interruptive. Herein, the latest advances toward intelligent OOC (iOOC) systems, where sensors integrated with OOC devices continuously report cellular and microenvironmental information for comprehensive in situ bioanalysis, are examined. It is proposed that the multimodal data in iOOC systems can support closed-loop control of the in vitro models and offer holistic biomedical insights for diverse applications. Essential techniques for establishing iOOC systems are surveyed, encompassing in situ sensing, data processing, and dynamic modulation. Eventually, the future development of iOOC systems featuring cross-disciplinary strategies is discussed.

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.

Vascularized tumor models for the evaluation of drug delivery systems: a paradigm shift

As the conversion rate of preclinical studies for cancer treatment is low, user-friendly models that mimic the pathological microenvironment and drug intake with high throughput are scarce. Animal models are key, but an alternative to reduce their use would be valuable. Vascularized tumor-on-chip models combine great versatility with scalable throughput and are easy to use. Several strategies to integrate both tumor and vascular compartments have been developed, but few have been used to assess drug delivery. Permeability, intra/extravasation, and free drug circulation are often evaluated, but imperfectly recapitulate the processes at stake. Indeed, tumor targeting and chemoresistance bypass must be investigated to design promising cancer therapeutics. In vitro models that would help the development of drug delivery systems (DDS) are thus needed. They would allow selecting good candidates before animal studies based on rational criteria such as drug accumulation, diffusion in the tumor, and potency, as well as absence of side damage. In this review, we focus on vascularized tumor models. First, we detail their fabrication, and especially the materials, cell types, and coculture used. Then, the different strategies of vascularization are described along with their classical applications in intra/extravasation or free drug assessment. Finally, current trends in DDS for cancer are discussed with an overview of the current efforts in the domain.

Cancer-on-chip models for metastasis: importance of the tumor microenvironment

Cancer-on-chip (CoC) models, based on microfluidic chips harboring chambers for 3D tumor-cell culture, enable us to create a controlled tumor microenvironment (TME). CoC models are therefore increasingly used to systematically study effects of the TME on the various steps in cancer metastasis. Moreover, CoC models have great potential for developing novel cancer therapies and for predicting patient-specific response to cancer treatments. We review recent developments in CoC models, focusing on three main TME components: (i) the anisotropic extracellular matrix (ECM) architectures, (ii) the vasculature, and (iii) the immune system. We aim to provide guidance to biologists to choose the best CoC approach for addressing questions about the role of the TME in metastasis, and to inspire engineers to develop novel CoC technologies.

On-chip recapitulation of the tumor microenvironment: A decade of progress

One of the hurdles to the development of new anticancer therapies is the lack of in vitro models which faithfully reproduce the in vivo tumor microenvironment (TME). Understanding the dynamic relationships between the components of the TME in a controllable, scalable, and reliable setting would indeed support the discovery of biological targets impacting cancer diagnosis and therapy. Cancer research is increasingly shifting from traditional two-dimensional (2D) cell culture toward three-dimensional (3D) culture models, which have been demonstrated to increase the significance and predictive value of in vitro data. In this scenario, microphysiological systems (also known as organs-on-chip) have emerged as a relevant technological platform enabling more predictive investigation of cell-cell and cell-ECM interplay in cancer, attracting a significant research effort in the last years. This review illustrates one decade of progress in the field of tumor-microenvironment-on-chip (TMOC) approaches, exploiting either cell-laden microfluidic chambers or microfluidic confined tumor spheroids to model the TME. TMOCs have been designed to recapitulate several aspects of the TME, including tumor cells, the tumor-associated stroma, the immune system, and the vascular component. Significantly, the last aspect has emerged for its pivotal role in orchestrating cellular interactions and modulating drug pharmacokinetics on-chip. A further advancement has been represented by integration of TMOCs into multi-organ microphysiological systems, with the final aim to follow the metastatic cascade to target organs and to study the effects of chemotherapies at a systemic level. We highlight that the increased degree of complexity achieved by the most advanced TMOC models has enabled scientists to shed new light on the role of microenvironmental factors in tumor progression, metastatic cascade, and response to drugs.

Deciphering fibroblast-induced drug resistance in non-small cell lung carcinoma through patient-derived organoids in agarose microwells

Patient-derived organoids (PDOs) serve as invaluable 3D tumor models, retaining the histological complexity and genetic heterogeneity found in primary tumors. However, the limitation of small sample volumes and the lack of tailored platforms have hindered the research using PDOs. Within the tumor microenvironment, cancer-associated fibroblasts play a pivotal role in influencing drug sensitivity. In this study, we introduce an agarose microwell platform designed for PDO-based tumor and tumor microenvironment models, enabling rapid drug screening and resistance studies with small sample volumes. These microwells, constructed using 3D printing molds, feature a U-shaped bottom and 200 μm diameter. We successfully generated co-culture spheroids of non-small cell lung carcinoma (NSCLC) cells, including NCI-H358 or A549, and NSCLC PDOs F231 or F671 with fibroblast cell line, WI-38. Our results demonstrate the production of uniformly-sized spheroids (coefficient of variation <30%), high viability (>80% after 1 week), and fibroblast-induced drug resistance. The PDOs maintained their viability (>81% after 2 weeks) and continued to proliferate. Notably, when exposed to adagrasib, a KRASG12C inhibitor, we observed reduced cytotoxicity in KRASG12C-mutant spheroids when co-cultured with fibroblasts or their supernatant. The fibroblast supernatant sustained proliferative signals in tumor models. Taking into account the physical features, viability, and drug resistance acquired through supernatants from the fibroblasts, our platform emerges as a suitable platform for in vitro tumor modeling and the evaluation of drug efficacy using patient-derived tissues.

Cancer-on-a-chip model shows that the adenomatous polyposis coli mutation impairs T cell engagement and killing of cancer spheroids

Evaluating the ability of cytotoxic T lymphocytes (CTLs) to eliminate tumor cells is crucial, for instance, to predict the efficiency of cell therapy in personalized medicine. However, the destruction of a tumor by CTLs involves CTL migration in the extra-tumoral environment, accumulation on the tumor, antigen recognition, and cooperation in killing the cancer cells. Therefore, identifying the limiting steps in this complex process requires spatio-temporal measurements of different cellular events over long periods. Here, we use a cancer-on-a-chip platform to evaluate the impact of adenomatous polyposis coli (APC) mutation on CTL migration and cytotoxicity against 3D tumor spheroids. The APC mutated CTLs are found to have a reduced ability to destroy tumor spheroids compared with control cells, even though APC mutants migrate in the extra-tumoral space and accumulate on the spheroids as efficiently as control cells. Once in contact with the tumor however, mutated CTLs display reduced engagement with the cancer cells, as measured by a metric that distinguishes different modes of CTL migration. Realigning the CTL trajectories around localized killing cascades reveals that all CTLs transition to high engagement in the 2 h preceding the cascades, which confirms that the low engagement is the cause of reduced cytotoxicity. Beyond the study of APC mutations, this platform offers a robust way to compare cytotoxic cell efficiency of even closely related cell types, by relying on a multiscale cytometry approach to disentangle complex interactions and to identify the steps that limit the tumor destruction.

YAP/TEAD involvement in resistance to paclitaxel chemotherapy in lung cancer

The Yes-associated protein (YAP) oncoprotein has been linked to both metastases and resistance to targeted therapy of lung cancer cells. We aimed to investigate the effect of YAP pharmacological inhibition, using YAP/TEA domain (TEAD) transcription factor interaction inhibitors in chemo-resistant lung cancer cells. YAP subcellular localization, as a readout for YAP activation, cell migration, and TEAD transcription factor functional transcriptional activity were investigated in cancer cell lines with up-regulated YAP, with and without YAP/TEAD interaction inhibitors. Parental (A549) and paclitaxel-resistant (A549R) cell transcriptomes were analyzed. The half-maximal inhibitory concentration (IC50) of paclitaxel or trametinib, which are Mitogen-Activated protein kinase and Erk Kinase (MEK) inhibitors, combined with a YAP/TEAD inhibitor (IV#6), was determined. A three-dimensional (3D) microfluidic culture device enabled us to study the effect of IV#6/paclitaxel combination on cancer cells isolated from fresh resected lung cancer samples. YAP activity was significantly higher in paclitaxel-resistant cell lines. The YAP/TEAD inhibitor induced a decreased YAP activity in A549, PC9, and H2052 cells, with reduced YAP nuclear staining. Wound healing assays upon YAP inhibition revealed impaired cell motility of lung cancer A549 and mesothelioma H2052 cells. Combining YAP pharmacological inhibition with trametinib in K-Ras mutated A549 cells recapitulated synthetic lethality, thereby sensitizing these cells to MEK inhibition. The YAP/TEAD inhibitor lowered the IC50 of paclitaxel in A549R cells. Differential transcriptomic analysis of parental and A549R cells revealed an increased YAP/TEAD transcriptomic signature in resistant cells, downregulated upon YAP inhibition. The YAP/TEAD inhibitor restored paclitaxel sensitivity of A549R cells cultured in a 3D microfluidic system, with lung cancer cells from a fresh tumor efficiently killed by YAP/TEAD inhibitor/paclitaxel doublet. Evidence of the YAP/TEAD transcriptional program's role in chemotherapy resistance paves the way for YAP therapeutic targeting.

Prediction of anticancer drug resistance using a 3D microfluidic bladder cancer model combined with convolutional neural network-based image analysis

Bladder cancer is the most common urological malignancy worldwide, and its high recurrence rate leads to poor survival outcomes. The effect of anticancer drug treatment varies significantly depending on individual patients and the extent of drug resistance. In this study, we developed a validation system based on an organ-on-a-chip integrated with artificial intelligence technologies to predict resistance to anticancer drugs in bladder cancer. As a proof-of-concept, we utilized the gemcitabine-resistant bladder cancer cell line T24 with four distinct levels of drug resistance (parental, early, intermediate, and late). These cells were co-cultured with endothelial cells in a 3D microfluidic chip. A dataset comprising 2,674 cell images from the chips was analyzed using a convolutional neural network (CNN) to distinguish the extent of drug resistance among the four cell groups. The CNN achieved 95.2% accuracy upon employing data augmentation and a step decay learning rate with an initial value of 0.001. The average diagnostic sensitivity and specificity were 90.5% and 96.8%, respectively, and all area under the curve (AUC) values were over 0.988. Our proposed method demonstrated excellent performance in accurately identifying the extent of drug resistance, which can assist in the prediction of drug responses and in determining the appropriate treatment for bladder cancer patients.

miRNAs Delivery for Cancer-associated Fibroblasts' Activation and Drug Resistance in Cancer Microenvironment

Cancer-associated fibroblasts (CAFs) as a major component of cancer stroma contribute to diverse procedures of most solid tumors and might be a targeted cancer therapy approach. Their specified features, related signaling pathways, distinct biomarkers, and sub-populations need to be deciphered. There is a need for CAF extraction or induction for in vitro investigations. Some miRNAs could activate CAF-like phenotype and they also interfere in CAF-mediated drug resistance, aggressiveness, and metastatic behaviors of several cancer cell types. Due to the complex relevance of miRNA and CAFs, these non-coding oligonucleotides may serve as attractive scope for anti-cancer targeted therapies, but the lack of an efficient delivery system is still a major hurdle. Here, we have summarized the investigated information on CAF features, isolation, and induction procedures, and highlighted the miRNA-CAF communications, providing special insight into nano-delivery systems.

Microphysiological systems for solid tumor immunotherapy: opportunities and challenges

Immunotherapy remains more effective for hematologic tumors than for solid tumors. One of the main challenges to immunotherapy of solid tumors is the immunosuppressive microenvironment these tumors generate, which limits the cytotoxic capabilities of immune effector cells (e.g., cytotoxic T and natural killer cells). This microenvironment is characterized by hypoxia, nutrient starvation, accumulated waste products, and acidic pH. Tumor-hijacked cells, such as fibroblasts, macrophages, and T regulatory cells, also contribute to this inhospitable microenvironment for immune cells by secreting immunosuppressive cytokines that suppress the antitumor immune response and lead to immune evasion. Thus, there is a strong interest in developing new drugs and cell formulations that modulate the tumor microenvironment and reduce tumor cell immune evasion. Microphysiological systems (MPSs) are versatile tools that may accelerate the development and evaluation of these therapies, although specific examples showcasing the potential of MPSs remain rare. Advances in microtechnologies have led to the development of sophisticated microfluidic devices used to recapitulate tumor complexity. The resulting models, also known as microphysiological systems (MPSs), are versatile tools with which to decipher the molecular mechanisms driving immune cell antitumor cytotoxicity, immune cell exhaustion, and immune cell exclusion and to evaluate new targeted immunotherapies. Here, we review existing microphysiological platforms to study immuno-oncological applications and discuss challenges and opportunities in the field.

Microfluidic-based platforms for cell-to-cell communication studies

Intercellular communication is critical to the understanding of human health and disease progression. However, compared to traditional methods with inefficient analysis, microfluidic co-culture technologies developed for cell-cell communication research can reliably analyze crucial biological processes, such as cell signaling, and monitor dynamic intercellular interactions under reproducible physiological cell co-culture conditions. Moreover, microfluidic-based technologies can achieve precise spatial control of two cell types at the single-cell level with high throughput. Herein, this review focuses on recent advances in microfluidic-based 2D and 3D devices developed to confine two or more heterogeneous cells in the study of intercellular communication and decipher the advantages and limitations of these models in specific cellular research scenarios. This review will stimulate the development of more functionalized microfluidic platforms for biomedical research, inspiring broader interests across various disciplines to better comprehend cell-cell communication and other fields, such as tumor heterogeneity and drug screening.

Immunity-on-a-Chip: Integration of Immune Components into the Scheme of Organ-on-a-Chip Systems

Studying the immune system in vitro aims to understand how, when, and where the immune cells migrate/differentiate and respond to the various triggering events and the decision points along the immune response journey. It becomes evident that organ-on-a-chip (OOC) technology has a superior capability to recapitulate the cell-cell and tissue-tissue interaction in the body, with a great potential to provide tools for tracking the paracrine signaling with high spatial-temporal precision and implementing in situ real-time, non-destructive detection assays, therefore, enabling extraction of mechanistic information rather than phenotypic information. However, despite the rapid development in this technology, integration of the immune system into OOC devices stays among the least navigated tasks, with immune cells still the major missing components in the developed models. This is mainly due to the complexity of the immune system and the reductionist methodology of the OOC modules. Dedicated research in this field is demanded to establish the understanding of mechanism-based disease endotypes rather than phenotypes. Herein, we systemically present a synthesis of the state-of-the-art of immune-cantered OOC technology. We comprehensively outlined what is achieved and identified the technology gaps emphasizing the missing components required to establish immune-competent OOCs and bridge these gaps.

Bridging live-cell imaging and next-generation cancer treatment

By providing spatial, molecular and morphological data over time, live-cell imaging can provide a deeper understanding of the cellular and signalling events that determine cancer response to treatment. Understanding this dynamic response has the potential to enhance clinical outcome by identifying biomarkers or actionable targets to improve therapeutic efficacy. Here, we review recent applications of live-cell imaging for uncovering both tumour heterogeneity in treatment response and the mode of action of cancer-targeting drugs. Given the increasing uses of T cell therapies, we discuss the unique opportunity of time-lapse imaging for capturing the interactivity and motility of immunotherapies. Although traditionally limited in the number of molecular features captured, novel developments in multidimensional imaging and multi-omics data integration offer strategies to connect single-cell dynamics to molecular phenotypes. We review the effect of these recent technological advances on our understanding of the cellular dynamics of tumour targeting and discuss their implication for next-generation precision medicine.

Immune microenvironment dynamics of HER2 overexpressing breast cancer under dual anti-HER2 blockade

Introduction

The clinical prognosis of the HER2-overexpressing (HER2-OE) subtype of breast cancer (BC) is influenced by the immune infiltrate of the tumor. Specifically, monocytic cells, which are promoters of pro-tumoral immunosuppression, and NK cells, whose basal cytotoxic function may be enhanced with therapeutic antibodies. One of the standards of care for HER2+ BC patients includes the combination of the anti-HER2 antibodies trastuzumab and pertuzumab. This dual combination was a breakthrough against trastuzumab resistance; however, this regimen does not yield complete clinical benefit for a large fraction of patients. Further therapy refinement is still hampered by the lack of knowledge on the immune mechanism of action of this antibody-based dual HER2 blockade.

Methods

To explore how the dual antibody challenge influences the phenotype and function of immune cells infiltrating the HER2-OE BC microenvironment, we developed in vitro 3D heterotypic cell models of this subtype. The models comprised aggregates of HER2+ BC cell lines and human peripheral blood mononuclear cells. Cells were co-encapsulated in a chemically inert alginate hydrogel and maintained in agitation-based culture system for up to 7 days.

Results

The 3D models of the HER2-OE immune microenvironment retained original BC molecular features; the preservation of the NK cell compartment was achieved upon optimization of culture time and cytokine supplementation. Challenging the models with the standard-of-care combination of trastuzumab and pertuzumab resulted in enhanced immune cytotoxicity compared with trastuzumab alone. Features of the response to therapy within the immune tumor microenvironment were recapitulated, including induction of an immune effector state with NK cell activation, enhanced cell apoptosis and decline of immunosuppressive PD-L1+ immune cells.

Conclusions

This work presents a unique human 3D model for the study of immune effects of anti-HER2 biologicals, which can be used to test novel therapy regimens and improve anti-tumor immune function.

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.

Micro-engineering and nano-engineering approaches to investigate tumour ecosystems

The interactions among tumour cells, the tumour microenvironment (TME) and non-tumour tissues are of interest to many cancer researchers. Micro-engineering approaches and nanotechnologies are under extensive exploration for modelling these interactions and measuring them in situ and in vivo to investigate therapeutic vulnerabilities in cancer and extend a systemic view of tumour ecosystems. Here we highlight the greatest opportunities for improving the understanding of tumour ecosystems using microfluidic devices, bioprinting or organ-on-a-chip approaches. We also discuss the potential of nanosensors that can transmit information from within the TME or elsewhere in the body to address scientific and clinical questions about changes in chemical gradients, enzymatic activities, metabolic and immune profiles of the TME and circulating analytes. This Review aims to connect the cancer biology and engineering communities, presenting biomedical technologies that may expand the methodologies of the former, while inspiring the latter to develop approaches for interrogating cancer ecosystems.

Cancer Models on Chip: Paving the Way to Large-Scale Trial Applications

Cancer kills millions of individuals every year all over the world (Global Cancer Observatory). The physiological and biomechanical processes underlying the tumor are still poorly understood, hindering researchers from creating new, effective therapies. Inconsistent results of preclinical research, in vivo testing, and clinical trials decrease drug approval rates. 3D tumor-on-a-chip (ToC) models integrate biomaterials, tissue engineering, fabrication of microarchitectures, and sensory and actuation systems in a single device, enabling reliable studies in fundamental oncology and pharmacology. This review includes a critical discussion about their ability to reproduce the tumor microenvironment (TME), the advantages and drawbacks of existing tumor models and architectures, major components and fabrication techniques. The focus is on current materials and micro/nanofabrication techniques used to manufacture reliable and reproducible microfluidic ToC models for large-scale trial applications.

In situbiosensing technologies for an organ-on-a-chip

Thein vitrosimulation of organs resolves the accuracy, ethical, and cost challenges accompanyingin vivoexperiments. Organoids and organs-on-chips have been developed to model thein vitro, real-time biological and physiological features of organs. Numerous studies have deployed these systems to assess thein vitro, real-time responses of an organ to external stimuli. Particularly, organs-on-chips can be most efficiently employed in pharmaceutical drug development to predict the responses of organs before approving such drugs. Furthermore, multi-organ-on-a-chip systems facilitate the close representations of thein vivoenvironment. In this review, we discuss the biosensing technology that facilitates thein situ, real-time measurements of organ responses as readouts on organ-on-a-chip systems, including multi-organ models. Notably, a human-on-a-chip system integrated with automated multi-sensing will be established by further advancing the development of chips, as well as their assessment techniques.

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

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

Reassessing Breast Cancer-Associated Fibroblasts (CAFs) Interactions with Other Stromal Components and Clinico-Pathologic Parameters by Using Immunohistochemistry and Digital Image Analysis (DIA)

BACKGROUND

Breast cancer (BC) stroma has CD34- and αSMA-positive cancer-associated fibroblasts (CAFs) differently distributed. During malignant transformation, CD34-positive fibroblasts decrease while αSMA-positive CAFs increase. The prevalence of αSMA-positive CAFs in BC stroma makes microscopic examination difficult without digital image analysis processing (DIA). DIA was used to compare CD34- and αSMA-positive CAFs among breast cancer molecular subgroups. DIA-derived data were linked to age, survival, tumor stroma vessels, tertiary lymphoid structures (TLS), invasion, and recurrence.

METHODS

Double immunostaining for CD34 and αSMA showed different CAF distribution patterns in normal and BC tissues. Single CD34 immunohistochemistry on supplemental slides quantified tumor stroma CD34_CAFs. Digital image analysis (DIA) data on CAF density, intensity, stromal score, and H-score were correlated with clinico-pathologic factors.

RESULTS

CD34/αSMA CAF proportion was significantly related to age in Luminal A (LA), Luminal B (LB), and HER2 subtypes. CD34_CAF influence on survival, invasion, and recurrence of LA, LB-HER2, and TNBC subtypes was found to be significant. The CD34/αSMA-expressing CAFs exhibited a heterogeneous impact on stromal vasculature and TLS.

CONCLUSION

BC stromal CD34_CAFs/αSMA_CAFs have an impact on survival, invasion, and recurrence differently between BC molecular subtypes. The tumor stroma DIA assessment may have predictive potential to prognosis and long-term follow-up of patients with breast cancer.

Microphysiological Systems for Cancer Immunotherapy Research and Development

Cancer immunotherapy focuses on the use of patients' adaptive immune systems to combat cancer. In the past decade, FDA has approved many immunotherapy products for cancer patients who suffer from primary tumors, tumor relapse, and metastases. However, these immunotherapies still show resistance in many patients and often lead to inconsistent responses in patients due to variations in tumor genetic mutations and tumor immune microenvironment. Microfluidics-based organ-on-a-chip technologies or microphysiological systems have opened new ways that can provide relatively fast screening for personalized immunotherapy and help researchers and clinicians understand tumor-immune interactions in a patient-specific manner. They also have the potential to overcome the limitations of traditional drug screening and testing, given the models provide a more realistic 3D microenvironment with better controllability, reproducibility, and physiological relevance. This review focuses on the cutting-edge microphysiological organ-on-a-chip devices developed in recent years for studying cancer immunity and testing cancer immunotherapeutic agents, as well as some of the largest challenges of translating this technology to clinical applications in immunotherapy and personalized medicine.

Possible molecular mechanisms underlying the development of atherosclerosis in cancer survivors

Cancer survivors undergone treatment face an increased risk of developing atherosclerotic cardiovascular disease (CVD), yet the underlying mechanisms remain elusive. Recent studies have revealed that chemotherapy can drive senescent cancer cells to acquire a proliferative phenotype known as senescence-associated stemness (SAS). These SAS cells exhibit enhanced growth and resistance to cancer treatment, thereby contributing to disease progression. Endothelial cell (EC) senescence has been implicated in atherosclerosis and cancer, including among cancer survivors. Treatment modalities for cancer can induce EC senescence, leading to the development of SAS phenotype and subsequent atherosclerosis in cancer survivors. Consequently, targeting senescent ECs displaying the SAS phenotype hold promise as a therapeutic approach for managing atherosclerotic CVD in this population. This review aims to provide a mechanistic understanding of SAS induction in ECs and its contribution to atherosclerosis among cancer survivors. We delve into the mechanisms underlying EC senescence in response to disturbed flow and ionizing radiation, which play pivotal role in atherosclerosis and cancer. Key pathways, including p90RSK/TERF2IP, TGFβR1/SMAD, and BH4 signaling are explored as potential targets for cancer treatment. By comprehending the similarities and distinctions between different types of senescence and the associated pathways, we can pave the way for targeted interventions aim at enhancing the cardiovascular health of this vulnerable population. The insights gained from this review may facilitate the development of novel therapeutic strategies for managing atherosclerotic CVD in cancer survivors.

The role of tumor microenvironment in drug resistance: emerging technologies to unravel breast cancer heterogeneity

Breast cancer is a highly heterogeneous disease, at both inter- and intra-tumor levels, and this heterogeneity is a crucial determinant of malignant progression and response to treatments. In addition to genetic diversity and plasticity of cancer cells, the tumor microenvironment contributes to tumor heterogeneity shaping the physical and biological surroundings of the tumor. The activity of certain types of immune, endothelial or mesenchymal cells in the microenvironment can change the effectiveness of cancer therapies via a plethora of different mechanisms. Therefore, deciphering the interactions between the distinct cell types, their spatial organization and their specific contribution to tumor growth and drug sensitivity is still a major challenge. Dissecting intra-tumor heterogeneity is currently an urgent need to better define breast cancer biology and to develop therapeutic strategies targeting the microenvironment as helpful tools for combined and personalized treatment. In this review, we analyze the mechanisms by which the tumor microenvironment affects the characteristics of tumor heterogeneity that ultimately result in drug resistance, and we outline state of the art preclinical models and emerging technologies that will be instrumental in unraveling the impact of the tumor microenvironment on resistance to therapies.

The Variety of 3D Breast Cancer Models for the Study of Tumor Physiology and Drug Screening

Breast cancer is the most common cancer in women and responsible for multiple deaths worldwide. 3D cancer models enable a better representation of tumor physiology than the conventional 2D cultures. This review summarizes the important components of physiologically relevant 3D models and describes the spectrum of 3D breast cancer models, e.g., spheroids, organoids, breast cancer on a chip and bioprinted tissues. The generation of spheroids is relatively standardized and easy to perform. Microfluidic systems allow control over the environment and the inclusion of sensors and can be combined with spheroids or bioprinted models. The strength of bioprinting relies on the spatial control of the cells and the modulation of the extracellular matrix. Except for the predominant use of breast cancer cell lines, the models differ in stromal cell composition, matrices and fluid flow. Organoids are most appropriate for personalized treatment, but all technologies can mimic most aspects of breast cancer physiology. Fetal bovine serum as a culture supplement and Matrigel as a scaffold limit the reproducibility and standardization of the listed 3D models. The integration of adipocytes is needed because they possess an important role in breast cancer.

Microsystem Advances through Integration with Artificial Intelligence

Microfluidics is a rapidly growing discipline that involves studying and manipulating fluids at reduced length scale and volume, typically on the scale of micro- or nanoliters. Under the reduced length scale and larger surface-to-volume ratio, advantages of low reagent consumption, faster reaction kinetics, and more compact systems are evident in microfluidics. However, miniaturization of microfluidic chips and systems introduces challenges of stricter tolerances in designing and controlling them for interdisciplinary applications. Recent advances in artificial intelligence (AI) have brought innovation to microfluidics from design, simulation, automation, and optimization to bioanalysis and data analytics. In microfluidics, the Navier-Stokes equations, which are partial differential equations describing viscous fluid motion that in complete form are known to not have a general analytical solution, can be simplified and have fair performance through numerical approximation due to low inertia and laminar flow. Approximation using neural networks trained by rules of physical knowledge introduces a new possibility to predict the physicochemical nature. The combination of microfluidics and automation can produce large amounts of data, where features and patterns that are difficult to discern by a human can be extracted by machine learning. Therefore, integration with AI introduces the potential to revolutionize the microfluidic workflow by enabling the precision control and automation of data analysis. Deployment of smart microfluidics may be tremendously beneficial in various applications in the future, including high-throughput drug discovery, rapid point-of-care-testing (POCT), and personalized medicine. In this review, we summarize key microfluidic advances integrated with AI and discuss the outlook and possibilities of combining AI and microfluidics.

Spatiotemporal dissection of tumor microenvironment via in situ sensing and monitoring in tumor-on-a-chip

Real-time monitoring in the tumor microenvironment provides critical insights of cancer progression and mechanistic understanding of responses to cancer treatments. However, clinical challenges and significant questions remain regarding assessment of limited clinical tissue samples, establishment of validated, controllable pre-clinical cancer models, monitoring of static versus dynamic markers, and the translation of insights gained from in vitro tumor microenvironments to systematic investigation and understanding in clinical practice. State-of-art tumor-on-a-chip strategies will be reviewed herein, and emerging real-time sensing and monitoring platforms for on-chip analysis of tumor microenvironment will also be examined. The integration of the sensors with tumor-on-a-chip platforms to provide spatiotemporal information of the tumor microenvironment and the associated challenges will be further evaluated. Though optimal integrated systems for in situ monitoring are still in evolution, great promises lie ahead that will open new paradigm for rapid, comprehensive analysis of cancer development and assist clinicians with powerful tools to guide the diagnosis, prognosis and treatment course in cancer.

Machine learning in additive manufacturing & Microfluidics for smarter and safer drug delivery systems

A new technological passage has emerged in the pharmaceutical field, concerning the management, application, and transfer of knowledge from humans to machines, as well as the implementation of advanced manufacturing and product optimisation processes. Machine Learning (ML) methods have been introduced to Additive Manufacturing (AM) and Microfluidics (MFs) to predict and generate learning patterns for precise fabrication of tailor-made pharmaceutical treatments. Moreover, regarding the diversity and complexity of personalised medicine, ML has been part of quality by design strategy, targeting towards the development of safe and effective drug delivery systems. The utilisation of different and novel ML techniques along with Internet of Things sensors in AM and MFs, have shown promising aspects regarding the development of well-defined automated procedures towards the production of sustainable and quality-based therapeutic systems. Thus, the effective data utilisation, prospects on a flexible and broader production of "on demand" treatments. In this study, a thorough overview has been achieved, concerning scientific achievements of the past decade, which aims to trigger the research interest on incorporating different types of ML in AM and MFs, as essential techniques for the enhancement of quality standards of customised medicinal applications, as well as the reduction of variability potency, throughout a pharmaceutical process.

Deep-Manager: a versatile tool for optimal feature selection in live-cell imaging analysis

One of the major problems in bioimaging, often highly underestimated, is whether features extracted for a discrimination or regression task will remain valid for a broader set of similar experiments or in the presence of unpredictable perturbations during the image acquisition process. Such an issue is even more important when it is addressed in the context of deep learning features due to the lack of a priori known relationship between the black-box descriptors (deep features) and the phenotypic properties of the biological entities under study. In this regard, the widespread use of descriptors, such as those coming from pre-trained Convolutional Neural Networks (CNNs), is hindered by the fact that they are devoid of apparent physical meaning and strongly subjected to unspecific biases, i.e., features that do not depend on the cell phenotypes, but rather on acquisition artifacts, such as brightness or texture changes, focus shifts, autofluorescence or photobleaching. The proposed Deep-Manager software platform offers the possibility to efficiently select those features having lower sensitivity to unspecific disturbances and, at the same time, a high discriminating power. Deep-Manager can be used in the context of both handcrafted and deep features. The unprecedented performances of the method are proven using five different case studies, ranging from selecting handcrafted green fluorescence protein intensity features in chemotherapy-related breast cancer cell death investigation to addressing problems related to the context of Deep Transfer Learning. Deep-Manager, freely available at https://github.com/BEEuniroma2/Deep-Manager , is suitable for use in many fields of bioimaging and is conceived to be constantly upgraded with novel image acquisition perturbations and modalities.

Organoids and organs-on-chips: insights into predicting the efficacy of systemic treatment in colorectal cancer

Cancer heterogeneity has posed a great challenge to traditional cancer treatment, with the reappearance of cancer heterogeneity of inter and intra patients being especially critical. Based on this, personalized therapy has emerged as significant research focus in recent and even future years. Cancer-related therapeutic models are developing, including cell lines, patient-derived xenografts, organoids, etc. Organoids are three-dimensional in vitro models emerged in the past dozen years and are able to reproduce the cellular and molecular composition of the original tumor. These advantages demonstrate the great potential for patient-derived organoids to develop personalized anticancer therapies, including preclinical drug screening and the prediction of patient treatment response. The impact of microenvironment on cancer treatment cannot be underestimated, and the remodeling of microenvironment also allows organoids to interact with other technologies, among which organs-on-chips is a representative one. This review highlights the use of organoids and organs-on-chips as complementary reference tools in treating colorectal cancer from the perspective of clinical efficacy predictability. We also discuss the limitations of both techniques and how they complement each other well.

The Applications and Challenges of the Development of In Vitro Tumor Microenvironment Chips

The tumor microenvironment (TME) plays a critical, yet mechanistically elusive role in tumor development and progression, as well as drug resistance. To better understand the pathophysiology of the complex TME, a reductionist approach has been employed to create in vitro microfluidic models called "tumor chips". Herein, we review the fabrication processes, applications, and limitations of the tumor chips currently under development for use in cancer research. Tumor chips afford capabilities for real-time observation, precise control of microenvironment factors (e.g. stromal and cellular components), and application of physiologically relevant fluid shear stresses and perturbations. Applications for tumor chips include drug screening and toxicity testing, assessment of drug delivery modalities, and studies of transport and interactions of immune cells and circulating tumor cells with primary tumor sites. The utility of tumor chips is currently limited by the ability to recapitulate the nuances of tumor physiology, including extracellular matrix composition and stiffness, heterogeneity of cellular components, hypoxic gradients, and inclusion of blood cells and the coagulome in the blood microenvironment. Overcoming these challenges and improving the physiological relevance of in vitro tumor models could provide powerful testing platforms in cancer research and decrease the need for animal and clinical studies.

Capturing the spatial and temporal dynamics of tumor stroma for on-chip optimization of microenvironmental targeting nanomedicine

Malignant cells grow in a complex microenvironment that plays a key role in cancer progression. The "dynamic reciprocity" existing between cancer cells and their microenvironment is involved in cancer differentiation, proliferation, invasion, metastasis, and drug response. Therefore, understanding the molecular mechanisms underlying the crosstalk between cancer cells and their surrounding tissue (i.e., tumor stroma) and how this interplay affects the disease progression is fundamental to design and validate novel nanotherapeutic approaches. As an important regulator of tumor progression, metastasis and therapy resistance, the extracellular matrix of tumors, the acellular component of the tumor microenvironment, has been identified as very promising target of anticancer treatment, revolutionizing the traditional therapeutic paradigm that sees the neoplastic cells as the preferential objective to fight cancer. To design and to validate such a target therapy, advanced 3D preclinical models are necessary to correctly mimic the complex, dynamic and heterogeneous tumor microenvironment. In addition, the recent advancement in microfluidic technology allows fine-tuning and controlling microenvironmental parameters in tissue-on-chip devices in order to emulate the in vivo conditions. In this review, after a brief description of the origin of tumor microenvironment heterogeneity, some examples of nanomedicine approaches targeting the tumor microenvironment have been reported. Further, how advanced 3D bioengineered tumor models coupled with a microfluidic device can improve the design and testing of anti-cancer nanomedicine targeting the tumor microenvironment has been discussed. We highlight that the presence of a dynamic extracellular matrix, able to capture the spatiotemporal heterogeneity of tumor stroma, is an indispensable requisite for tumor-on-chip model and nanomedicine testing.

In Vitro Veritas: From 2D Cultures to Organ-on-a-Chip Models to Study Immunogenic Cell Death in the Tumor Microenvironment

Immunogenic cell death (ICD) is a functionally unique form of cell death that promotes a T-cell-dependent anti-tumor immune response specific to antigens originating from dying cancer cells. Many anticancer agents and strategies induce ICD, but despite their robust effects in vitro and in vivo on mice, translation into the clinic remains challenging. A major hindrance in antitumor research is the poor predictive ability of classic 2D in vitro models, which do not consider tumor biological complexity, such as the contribution of the tumor microenvironment (TME), which plays a crucial role in immunosuppression and cancer evasion. In this review, we describe different tumor models, from 2D cultures to organ-on-a-chip technology, as well as spheroids and perfusion bioreactors, all of which mimic the different degrees of the TME complexity. Next, we discuss how 3D cell cultures can be applied to study ICD and how to increase the translational potential of the ICD inducers. Finally, novel research directions are provided regarding ICD in the 3D cellular context which may lead to novel immunotherapies for cancer.

Precise and fast control of the dissolved oxygen level for tumor-on-chip

In vitro cell cultures are most often performed in unphysiological hyperoxia since the oxygen partial pressure of conventional incubators is set at 141 mmHg (18.6%, close to ambient air oxygen 20.1%). This value is higher than human tissue oxygen levels, as the in vivo oxygen partial pressures range from 104 mmHg (lung alveoli) to 8 mmHg (skin epidermis). Importantly, under pathological conditions such as cancer, cells can experience oxygen pressure lower than the healthy tissue. Although hypoxic incubators can regulate gas oxygen, they do not take into account the dissolved oxygen concentration in the cell culture medium. In the context of organ on chip and micro-physiological system development, we present here a new system, called Oxalis (OXygen ALImentation System) that allows fine control of the dissolved oxygen level in the cell culture medium. Oxalis regulates simultaneously the gas composition and the inlet reservoir pressure by modulating the pneumatic valve opening. This dual regulation allows both the pressure driven liquid flowrate and the level of oxygen dissolved in the chip to be controlled independently. Oxalis offers unprecedented features such as an oxygen equilibration time lower than 3 minutes and an accuracy of 3 mmHg. These performances can be reached for chip perfusion flow as low as 1 μL min^-1. This low flow rate allows the shear stress experienced by the cells in the chip to be accurately controlled. In addition, the system enables modulation of the pH in the cell culture medium through the modulation of CO₂. The fine control and monitoring of both O₂ and pH pave the way for new precise investigations on physiological and pathological biological processes. Using Oxalis in the context of tumor-on-chip, we demonstrate the capacity of the system to recapitulate hypoxia-induced gene expression, offering an innovative strategy for future studies on the role of hypoxia in malignant progression and drug resistance.

Technological and computational advances driving high-throughput oncology

Engineering and computational advances have opened many new avenues in cancer research, particularly when being exploited in interdisciplinary approaches. For example, the combination of microfluidics, novel sequencing technologies, and computational analyses has been crucial to enable single-cell assays, giving a detailed picture of tumor heterogeneity for the very first time. In a similar way, these 'tech' disciplines have been elementary for generating large data sets in multidimensional cancer 'omics' approaches, cell-cell interaction screens, 3D tumor models, and tissue level analyses. In this review we summarize the most important technology and computational developments that have been or will be instrumental for transitioning classical cancer research to a large data-driven, high-throughput, high-content discipline across all biological scales.

Three-Dimensional in Vitro Models: A Promising Tool To Scale-Up Breast Cancer Research

Common models used in breast cancer studies, including two-dimensional (2D) cultures and animal models, do not precisely model all aspects of breast tumors. These models do not well simulate the cell-cell and cell-stromal interactions required for normal tumor growth in the body and lake tumor like microenvironment. Three-dimensional (3D) cell culture models are novel approaches to studying breast cancer. They do not have the restrictions of these conventional models and are able to recapitulate the structural architecture, complexity, and specific function of breast tumors and provide similar in vivo responses to therapeutic regimens. These models can be a link between former traditional 2D culture and in vivo models and are necessary for further studies in cancer. This review attempts to summarize the most common 3D in vitro models used in breast cancer studies, including scaffold-free (spheroid and organoid), scaffold-based, and chip-based models, particularly focused on the basic and translational application of these 3D models in drug screening and the tumor microenvironment in breast cancer.

Clinical application of advanced multi-omics tumor profiling: Shaping precision oncology of the future

Next-generation DNA sequencing technology has dramatically advanced clinical oncology through the identification of therapeutic targets and molecular biomarkers, leading to the personalization of cancer treatment with significantly improved outcomes for many common and rare tumor entities. More recent developments in advanced tumor profiling now enable dissection of tumor molecular architecture and the functional phenotype at cellular and subcellular resolution. Clinical translation of high-resolution tumor profiling and integration of multi-omics data into precision treatment, however, pose significant challenges at the level of prospective validation and clinical implementation. In this review, we summarize the latest advances in multi-omics tumor profiling, focusing on spatial genomics and chromatin organization, spatial transcriptomics and proteomics, liquid biopsy, and ex vivo modeling of drug response. We analyze the current stages of translational validation of these technologies and discuss future perspectives for their integration into precision treatment.

Targeted immunotherapy against distinct cancer-associated fibroblasts overcomes treatment resistance in refractory HER2+ breast tumors

About 50% of human epidermal growth factor receptor 2 (HER2)+ breast cancer patients do not benefit from HER2-targeted therapy and almost 20% of them relapse after treatment. Here, we conduct a detailed analysis of two independent cohorts of HER2+ breast cancer patients treated with trastuzumab to elucidate the mechanisms of resistance to anti-HER2 monoclonal antibodies. In addition, we develop a fully humanized immunocompetent model of HER2+ breast cancer recapitulating ex vivo the biological processes that associate with patients’ response to treatment. Thanks to these two approaches, we uncover a population of TGF-beta-activated cancer-associated fibroblasts (CAF) specific from tumors resistant to therapy. The presence of this cellular subset related to previously described myofibroblastic (CAF-S1) and podoplanin+ CAF subtypes in breast cancer associates with low IL2 activity. Correspondingly, we find that stroma-targeted stimulation of IL2 pathway in unresponsive tumors restores trastuzumab anti-cancer efficiency. Overall, our study underscores the therapeutic potential of exploiting the tumor microenvironment to identify and overcome mechanisms of resistance to anti-cancer treatment.

A substantial proportion of HER2+ breast cancer patients do not benefit from HER2-targeted therapy. Here, the authors identify a population of cancer-associated fibroblasts involved in the suppression of trastuzumab-induced ADCC that can be pharmacologically targeted to raise treatment effectiveness in unresponsive tumors.

Organ-on-a-chip platforms as novel advancements for studying heterogeneity, metastasis, and drug efficacy in breast cancer

Breast cancer has the highest cancer incidence rate in women worldwide. Therapies for breast cancer have shown high success rates, yet many cases of recurrence and drug resistance are still reported. Developing innovative strategies for studying breast cancer may improve therapeutic outcomes of the disease by providing better insight into the associated molecular mechanisms. A novel advancement in breast cancer research is the utilization of organ-on-a-chip (OOAC) technology to establish in vitro physiologically relevant breast cancer biomimetic models. This emerging technology combines microfluidics and tissue culturing methods to establish organ-specific micro fabricated culture models. Here, we shed light on the advantages of OOAC platforms over conventional in vivo and in vitro models in terms of mimicking tissue heterogeneity, disease progression, and facilitating pharmacological drug testing with a focus on models of the mammary gland in both normal and breast cancer states. By highlighting the various designs and applications of the breast-on-a-chip platforms, we show that the latter propose means to facilitate breast cancer-related studies and provide an efficient approach for therapeutic drug screening in vitro.

Engineered Microphysiological Systems for Testing Effectiveness of Cell-Based Cancer Immunotherapies

Cell therapies, including adoptive immune cell therapies and genetically engineered chimeric antigen receptor (CAR) T or NK cells, have shown promise in treating hematologic malignancies. Yet, immune cell infiltration and expansion has proven challenging in solid tumors due to immune cell exclusion and exhaustion and the presence of vascular barriers. Testing next-generation immune therapies remains challenging in animals, motivating sophisticated ex vivo models of human tumor biology and prognostic assays to predict treatment response in real-time while comprehensively recapitulating the human tumor immune microenvironment (TIME). This review examines current strategies for testing cell-based cancer immunotherapies using ex vivo microphysiological systems and microfluidic technologies. Insights into the multicellular interactions of the TIME will identify novel therapeutic strategies to help patients whose tumors are refractory or resistant to current immunotherapies. Altogether, these microphysiological systems (MPS) have the capability to predict therapeutic vulnerabilities and biological barriers while studying immune cell infiltration and killing in a more physiologically relevant context, thereby providing important insights into fundamental biologic mechanisms to expand our understanding of and treatments for currently incurable malignancies.

Designing Organoid Models to Monitor Cancer Progression, Plasticity and Resistance: The Right Set Up for the Right Question

The recent trend in 3D cell modeling has fostered the emergence of a wide range of models, addressing very distinct goals ranging from the fundamental exploration of cell–cell interactions to preclinical assays for personalized medicine. It is clear that no single model will recapitulate the complexity and dynamics of in vivo situations. The key is to define the critical points, achieve a specific goal and design a model where they can be validated. In this report, we focused on cancer progression. We describe our model which is designed to emulate breast carcinoma progression during the invasive phase. We chose to provide topological clues to the target cells by growing them on microsupports, favoring a polarized epithelial organization before they are embedded in a 3D matrix. We then watched for cell organization and differentiation for these models, adding stroma cells then immune cells to follow and quantify cell responses to drug treatment, including quantifying cell death and viability, as well as morphogenic and invasive properties. We used model cell lines including Comma Dβ, MCF7 and MCF10A mammary epithelial cells as well as primary breast cancer cells from patient-derived xenografts (PDX). We found that fibroblasts impacted cell response to Docetaxel and Palbociclib. We also found that NK92 immune cells could target breast cancer cells within the 3D configuration, providing quantitative monitoring of cell cytotoxicity. We also tested several sources for the extracellular matrix and selected a hyaluronan-based matrix as a promising alternative to mouse tumor basement membrane extracts for primary human cancer cells. Overall, we validated a new 3D model designed for breast cancer for preclinical use in personalized medicine.

Immunotherapy discovery on tumor organoid-on-a-chip platforms that recapitulate the tumor microenvironment

Cancer immunotherapy has achieved remarkable success over the past decade by modulating patients' own immune systems and unleashing pre-existing immunity. However, only a minority of cancer patients across different cancer types are able to benefit from immunotherapy treatment; moreover, among those small portions of patients with response, intrinsic and acquired resistance remains a persistent challenge. Because the tumor microenvironment (TME) is well recognized to play a critical role in tumor initiation, progression, metastasis, and the suppression of the immune system and responses to immunotherapy, understanding the interactions between the TME and the immune system is a pivotal step in developing novel and efficient cancer immunotherapies. With unique features such as low reagent consumption, dynamic and precise fluid control, versatile structures and function designs, and 3D cell co-culture, microfluidic tumor organoid-on-a-chip platforms that recapitulate key factors of the TME and the immune contexture have emerged as innovative reliable tools to investigate how tumors regulate their TME to counteract antitumor immunity and the mechanism of tumor resistance to immunotherapy. In this comprehensive review, we focus on recent advances in tumor organoid-on-a-chip platforms for studying the interaction between the TME and the immune system. We first review different factors of the TME that recent microfluidic in vitro systems reproduce to generate advanced tools to imitate the crosstalk between the TME and the immune system. Then, we discuss their applications in the assessment of different immunotherapies' efficacy using tumor organoid-on-a-chip platforms. Finally, we present an overview and the outlook of engineered microfluidic platforms in investigating the interactions between cancer and immune systems, and the adoption of patient-on-a-chip models in clinical applications toward personalized immunotherapy.

Machine learning phenomics (MLP) combining deep learning with time-lapse-microscopy for monitoring colorectal adenocarcinoma cells gene expression and drug-response

High-throughput phenotyping is becoming increasingly available thanks to analytical and bioinformatics approaches that enable the use of very high-dimensional data and to the availability of dynamic models that link phenomena across levels: from genes to cells, from cells to organs, and through the whole organism. The combination of phenomics, deep learning, and machine learning represents a strong potential for the phenotypical investigation, leading the way to a more embracing approach, called machine learning phenomics (MLP). In particular, in this work we present a novel MLP platform for phenomics investigation of cancer-cells response to therapy, exploiting and combining the potential of time-lapse microscopy for cell behavior data acquisition and robust deep learning software architectures for the latent phenotypes extraction. A two-step proof of concepts is designed. First, we demonstrate a strict correlation among gene expression and cell phenotype with the aim to identify new biomarkers and targets for tailored therapy in human colorectal cancer onset and progression. Experiments were conducted on human colorectal adenocarcinoma cells (DLD-1) and their profile was compared with an isogenic line in which the expression of LOX-1 transcript was knocked down. In addition, we also evaluate the phenotypic impact of the administration of different doses of an antineoplastic drug over DLD-1 cells. Under the omics paradigm, proteomics results are used to confirm the findings of the experiments.

Cancer-associated fibroblasts in breast cancer: Challenges and opportunities

The tumor microenvironment is proposed to contribute substantially to the progression of cancers, including breast cancer. Cancer-associated fibroblasts (CAFs) are the most abundant components of the tumor microenvironment. Studies have revealed that CAFs in breast cancer originate from several types of cells and promote breast cancer malignancy by secreting factors, generating exosomes, releasing nutrients, reshaping the extracellular matrix, and suppressing the function of immune cells. CAFs are also becoming therapeutic targets for breast cancer due to their specific distribution in tumors and their unique biomarkers. Agents interrupting the effect of CAFs on surrounding cells have been developed and applied in clinical trials. Here, we reviewed studies examining the heterogeneity of CAFs in breast cancer and expression patterns of CAF markers in different subtypes of breast cancer. We hope that summarizing CAF-related studies from a historical perspective will help to accelerate the development of CAF-targeted therapeutic strategies for breast cancer.

Organ-on-Chip platforms to study tumor evolution and chemosensitivity

Despite tremendous advancements in oncology research and therapeutics, cancer remains a primary cause of death worldwide. One of the significant factors in this critical challenge is a precise diagnosis and limited knowledge on how the tumor microenvironment (TME) behaves to the treatment and its role in chemo-resistance. Therefore, it is critical to understand the contribution of a heterogeneous TME in cancer drug response in individual patients for effective therapy management. Micro-physiological systems along with tissue engineering have facilitated the development of more physiologically relevant platforms, known as Organ-on-Chips (OoC). OoC platforms recapitulate the critical hallmarks of the TME in vitro and subsequently abet in sensitivity and efficacy testing of anti-cancer drugs before clinical trials. The OoC platforms incorporating conventional in vitro models enable researchers to control the cellular, molecular, chemical, and biophysical parameters of the TME in precise combinations while analyzing how they contribute to tumor progression and therapy response. This review discusses the application of OoC platforms integrated with conventional 2D cell lines, 3D organoids and spheroid models, and the organotypic tissue slices, including patient-derived and xenograft tumor slice cultures in cancer treatment responses. We summarize the relevance and drawbacks of conventional in vitro models in assessing cancer treatment response, challenges and limitations associated with OoC models, and future opportunities enabled by the OoC technologies towards developing personalized cancer diagnostics and therapeutics.

Tumor Microenvironment and Hydrogel-Based 3D Cancer Models for In Vitro Testing Immunotherapies

Simple Summary

Immunotherapies are emerging as promising strategies to cure cancer and extend patients’ survival. Efforts should be focused, however, on the development of preclinical tools better able to predict the therapeutic benefits in individual patients. In this context, the availability of reliable preclinical models capable of recapitulating the tumor milieu while overcoming the limitations of traditional systems is mandatory. Here, we review the tumor immune responses, escape mechanisms, and the most recent 3D biomaterial-based cancer in vitro models useful for investigating the effects of the different immunotherapeutic approaches. The main challenges and possible future trends are also discussed.

Abstract

In recent years, immunotherapy has emerged as a promising novel therapeutic strategy for cancer treatment. In a relevant percentage of patients, however, clinical benefits are lower than expected, pushing researchers to deeply analyze the immune responses against tumors and find more reliable and efficient tools to predict the individual response to therapy. Novel tissue engineering strategies can be adopted to realize in vitro fully humanized matrix-based models, as a compromise between standard two-dimensional (2D) cell cultures and animal tests, which are costly and hardly usable in personalized medicine. In this review, we describe the main mechanisms allowing cancer cells to escape the immune surveillance, which may play a significant role in the failure of immunotherapies. In particular, we discuss the role of the tumor microenvironment (TME) in the establishment of a milieu that greatly favors cancer malignant progression and impact on the interactions with immune cells. Then, we present an overview of the recent in vitro engineered preclinical three-dimensional (3D) models that have been adopted to resemble the interplays between cancer and immune cells and for testing current therapies and immunotherapeutic approaches. Specifically, we focus on 3D hydrogel-based tools based on different types of polymers, discussing the suitability of each of them in reproducing the TME key features based on their intrinsic or tunable characteristics. Finally, we introduce the possibility to combine the 3D models with technological fluid dynamics platforms, reproducing the dynamic complex interactions between tumor cells and immune effectors migrated in situ via the systemic circulation, pointing out the challenges that still have to be overcome for setting more predictive preclinical assays.

Organ-on-a-Chip Platforms for Drug Screening and Delivery in Tumor Cells: A Systematic Review

Simple Summary

Cancer is one of the diseases with a high mortality rate worldwide. Of the current strategies to study new diagnostic and treating tools, organs-on-chip are quite promising regarding the achievement of more personalized medicine. In this work, 75 out of 820 of the most recent published scientific articles were selected and analyzed through a systematic process. The selected articles present the different microfluidic platforms where cell culture was introduced and was used for the evaluation of cancer treatments efficacy and/or toxicity.

Abstract

The development of cancer models that rectify the simplicity of monolayer or static cell cultures physiologic microenvironment and, at the same time, replicate the human system more accurately than animal models has been a challenge in biomedical research. Organ-on-a-chip (OoC) devices are a solution that has been explored over the last decade. The combination of microfluidics and cell culture allows the design of a dynamic microenvironment suitable for the evaluation of treatments’ efficacy and effects, closer to the response observed in patients. This systematic review sums the studies from the last decade, where OoC with cancer cell cultures were used for drug screening assays. The studies were selected from three databases and analyzed following the research guidelines for systematic reviews proposed by PRISMA. In the selected studies, several types of cancer cells were evaluated, and the majority of treatments tested were standard chemotherapeutic drugs. Some studies reported higher drug resistance of the cultures on the OoC devices than on 2D cultures, which indicates the better resemblance to in vivo conditions of the former. Several studies also included the replication of the microvasculature or the combination of different cell cultures. The presence of vasculature can influence positively or negatively the drug efficacy since it contributes to a greater diffusion of the drug and also oxygen and nutrients. Co-cultures with liver cells contributed to the evaluation of the systemic toxicity of some drugs metabolites. Nevertheless, few studies used patient cells for the drug screening assays.

Human immunocompetent choroid-on-chip: a novel tool for studying ocular effects of biological drugs

Disorders of the eye leading to visual impairment are a major issue that affects millions of people. On the other side ocular toxicities were described for e.g. molecularly targeted therapies in oncology and may hamper their development. Current ocular model systems feature a number of limitations affecting human-relevance and availability. To find new options for pharmacological treatment and assess mechanisms of toxicity, hence, novel complex model systems that are human-relevant and readily available are urgently required. Here, we report the development of a human immunocompetent Choroid-on-Chip (CoC), a human cell-based in vitro model of the choroid layer of the eye integrating melanocytes and microvascular endothelial cells, covered by a layer of retinal pigmented epithelial cells. Immunocompetence is achieved by perfusion of peripheral immune cells. We demonstrate controlled immune cell recruitment into the stromal compartments through a vascular monolayer and in vivo-like cytokine release profiles. To investigate applicability for both efficacy testing of immunosuppressive compounds as well as safety profiling of immunoactivating antibodies, we exposed the CoCs to cyclosporine and tested CD3 bispecific antibodies.