Advances in the preclinical testing of cancer therapeutic hypotheses

Cancer organoids 2.0: modelling the complexity of the tumour immune microenvironment

The development of neoplasia involves a complex and continuous interplay between malignantly transformed cells and the tumour microenvironment (TME). Cancer immunotherapies targeting the immune TME have been increasingly validated in clinical trials but response rates vary substantially between tumour histologies and are often transient, idiosyncratic and confounded by resistance. Faithful experimental models of the patient-specific tumour immune microenvironment, capable of recapitulating tumour biology and immunotherapy effects, would greatly improve patient selection, target identification and definition of resistance mechanisms for immuno-oncology therapeutics. In this Review, we discuss currently available and rapidly evolving 3D tumour organoid models that capture important immune features of the TME. We highlight diverse opportunities for organoid-based investigations of tumour immunity, drug development and precision medicine.

DeepDRA: Drug repurposing using multi-omics data integration with autoencoders

Cancer treatment has become one of the biggest challenges in the world today. Different treatments are used against cancer; drug-based treatments have shown better results. On the other hand, designing new drugs for cancer is costly and time-consuming. Some computational methods, such as machine learning and deep learning, have been suggested to solve these challenges using drug repurposing. Despite the promise of classical machine-learning methods in repurposing cancer drugs and predicting responses, deep-learning methods performed better. This study aims to develop a deep-learning model that predicts cancer drug response based on multi-omics data, drug descriptors, and drug fingerprints and facilitates the repurposing of drugs based on those responses. To reduce multi-omics data's dimensionality, we use autoencoders. As a multi-task learning model, autoencoders are connected to MLPs. We extensively tested our model using three primary datasets: GDSC, CTRP, and CCLE to determine its efficacy. In multiple experiments, our model consistently outperforms existing state-of-the-art methods. Compared to state-of-the-art models, our model achieves an impressive AUPRC of 0.99. Furthermore, in a cross-dataset evaluation, where the model is trained on GDSC and tested on CCLE, it surpasses the performance of three previous works, achieving an AUPRC of 0.72. In conclusion, we presented a deep learning model that outperforms the current state-of-the-art regarding generalization. Using this model, we could assess drug responses and explore drug repurposing, leading to the discovery of novel cancer drugs. Our study highlights the potential for advanced deep learning to advance cancer therapeutic precision.

Organoids derived from metastatic cancers: Present and future

Organoids are three-dimensional structures derived from primary tissue or tumors that closely mimic the architecture, histology, and function of the parental tissue. In recent years, patient-derived organoids (PDOs) have emerged as powerful tools for modeling tumor heterogeneity, drug screening, and personalized medicine. Although most cancer organoids are derived from primary tumors, the ability of organoids from metastatic cancer to serve as a model for studying tumor biology and predicting the therapeutic response is an area of active investigation. Recent studies have shown that organoids derived from metastatic sites can provide valuable insights into tumor biology and may be used to validate predictive models of the drug response. In this comprehensive review, we discuss the feasibility of culturing organoids from multiple metastatic cancers and evaluate their potential for advancing basic cancer research, drug development, and personalized therapy. We also explore the limitations and challenges associated with using metastasis organoids for cancer research. Overall, this review provides a comprehensive overview of the current state and future prospects of metastatic cancer-derived organoids.

Bibliometric analysis of global research on human organoids

The emergence and rapid development of human organoids have provided the possibility to replace animal models in treating human diseases. Intelligence studies help focus on research hotspots and address key mechanistic issues. Currently, few comprehensive studies describe the characteristics of human organoid research. In this study, we extracted 8,591 original articles on organoids from the Web of Science core collection database over the past two decades and conducted intelligence analysis using CiteSpace. The number of publications in this field has experienced rapid growth in the last ten years (almost 70-fold increase since 2009). The United States, China, Germany, Netherlands, and UK have strong collaborations in publishing articles. Clevers Hans, Van Der Laan, Jason R Spence, and Sato Toshiro have made significant contributions to advancing progress in this field. Clustering and burst analysis categorized research hotspots into tissue model and functional construction, intercellular signaling, immune mechanisms, and tumor metastasis. Organoid research in highly cited articles covers four major areas: basic research (38%), involving stem cell developmental processes and cell-cell interactions; biobanking (10%), with a focus on organoid cultivation; precision medicine (16%), emphasizing cell therapy and drug development; and disease modeling (36%), including pathogen analysis and screening for disease-related genetic variations. The main obstacles currently faced in organoid research include cost and technology, vascularization of cells, immune system establishment, international standard protocols, and limited availability of high-quality clinical trial data. Future research will focus on cost-saving measures, technology sharing, development of international standards, and conducting high-level clinical trials.

Colon Cancer Cells Evade Drug Action by Enhancing Drug Metabolism

Colorectal cancer (CRC) is the second most deadly cancer worldwide. One key reason is the failure of therapies that target RAS proteins, which represent approximately 40% of CRC cases. Despite the recent discovery of multiple alternative signalling pathways that contribute to resistance, durable therapies remain an unmet need. Here, we use liquid chromatography/mass spectrometry (LC/MS) analyses on Drosophila CRC tumour models to identify multiple metabolites in the glucuronidation pathway-a toxin clearance pathway-as upregulated in trametinib-resistant RAS/APC/P53 ("RAP") tumours compared to trametinib-sensitive RASG12V tumours. Elevating glucuronidation was sufficient to direct trametinib resistance in RASG12V animals while, conversely, inhibiting different steps along the glucuronidation pathway strongly reversed RAP resistance to trametinib. For example, blocking an initial HDAC1-mediated deacetylation step with the FDA-approved drug vorinostat strongly suppressed trametinib resistance in Drosophila RAP tumours. We provide functional evidence that pairing oncogenic RAS with hyperactive WNT activity strongly elevates PI3K/AKT/GLUT signalling, which in turn directs elevated glucose and subsequent glucuronidation. Finally, we show that this mechanism of trametinib resistance is conserved in an KRAS/APC/TP53 mouse CRC tumour organoid model. Our observations demonstrate a key mechanism by which oncogenic RAS/WNT activity promotes increased drug clearance in CRC. The majority of targeted therapies are glucuronidated, and our results provide a specific path towards abrogating this resistance in clinical trials.

Applications of lung cancer organoids in precision medicine: from bench to bedside

As the leading cause of cancer-related mortality, lung cancer continues to pose a menacing threat to human health worldwide. Lung cancer treatment options primarily rely on chemoradiotherapy, surgery, targeted therapy, or immunotherapy. Despite significant progress in research and treatment, the 5-year survival rate for lung cancer patients is only 10-20%. There is an urgent need to develop more reliable preclinical models and valid therapeutic approaches. Patient-derived organoids with highly reduced tumour heterogeneity have emerged as a promising model for high-throughput drug screening to guide treatment of lung cancer patients. Organoid technology offers a novel platform for disease modelling, biobanking and drug development. The expected benefit of organoids is for cancer patients as the subsequent precision medicine technology. Over the past few years, numerous basic and clinical studies have been conducted on lung cancer organoids, highlighting the significant contributions of this technique. This review comprehensively examines the current state-of-the-art technologies and applications relevant to the formation of lung cancer organoids, as well as the potential of organoids in precision medicine and drug testing. Video Abstract.

The NCI-60 Human Tumor Cell Line Screen: A Catalyst for Progressive Evolution of Models for Discovery and Development of Cancer Drugs

Following three decades of systematic primary empirical screening against mice bearing two transplantable murine leukemias, the NCI took the bold step of switching to a radically different approach-initial screening of 10,000 diverse compounds/year against a panel of 60 human tumor cell lines in vitro. The establishment of the "NCI-60" screen was announced in the landmark Cancer Research article by Alley and colleagues, published in 1988, which exemplified the technological basis for the new microculture screen, operating at unprecedented scale. The underlying concept was that NCI-60 might expedite the discovery of innovative cancer drugs, especially those with predicted activity against particular solid cancers-not then possible. We discuss how NCI-60 provided a major technological advance and delivered a successful legacy for cancer research and development. While not immediately cracking the thorny problem of model-to-human tumor type prediction, NCI-60 nevertheless provided the conceptual and methodologic foundation for subsequent, much larger-scale human cancer cell panel screens with detailed molecular annotation and sophisticated informatics. Now used in modern molecular target-based drug discovery, these panels help enable the implementation of contemporary biomarker-led precision oncology. See related article by Alley and colleagues, Cancer Res 1988;48:589-601.

Can Organoid Model Reveal a Key Role of Extracellular Vesicles in Tumors? A Comprehensive Review of the Literature

Extracellular vesicles (EVs) are small membrane-bound vesicles that are released by cells into the extracellular environment. The role of EVs in tumors has been extensively studied, and they have been shown to play a crucial role in tumor growth, progression, and metastasis. Past research has mainly used 2D-cultured cell line models to investigate the role of EVs in tumors, which poorly simulate the tumor microenvironment. Organoid technology has gradually matured in recent years. Organoids are similar in composition and behavior to physiological cells and have the potential to recapitulate the architecture and function of the original tissue. It has been widely used in organogenesis, drug screening, gene editing, precision medicine and other fields. The integration of EVs and organoids has the potential to revolutionize the field of cancer research and represents a promising avenue for advancing our understanding of cancer biology and the development of novel therapeutic strategies. Here, we aimed to present a comprehensive overview of studies using organoids to study EVs in tumors.

Esophageal organoids: applications and future prospects

Organoids have been developed in the last decade as a new research tool to simulate organ cell biology and disease. Compared to traditional 2D cell lines and animal models, experimental data based on esophageal organoids are more reliable. In recent years, esophageal organoids derived from multiple cell sources have been established, and relatively mature culture protocols have been developed. Esophageal inflammation and cancer are two directions of esophageal organoid modeling, and organoid models of esophageal adenocarcinoma, esophageal squamous cell carcinoma, and eosinophilic esophagitis have been established. The properties of esophageal organoids, which mimic the real esophagus, contribute to research in drug screening and regenerative medicine. The combination of organoids with other technologies, such as organ chips and xenografts, can complement the deficiencies of organoids and create entirely new research models that are more advantageous for cancer research. In this review, we will summarize the development of tumor and non-tumor esophageal organoids, the current application of esophageal organoids in disease modeling, regenerative medicine, and drug screening. We will also discuss the future prospects of esophageal organoids.

Patient-derived organoids in ovarian cancer: Current research and its clinical relevance

Regardless of recent advances in cancer treatment, ovarian cancer (OC) patients have had a five-year survival rate of 48% in the last few decades. Diagnosis at the advanced stage, disease recurrence, and lack of early biomarkers are the severe clinical challenges associated with disease survival rate. Identifying tumor origin and developing precision drugs will effectively advance OC patient's treatment. The lack of a proper platform to identify and develop new therapeutic strategies in OC treatment necessitates searching for a suitable model to address tumor recurrence and therapeutic resistance. The development of the OC patient-derived organoid model provided a unique platform to identify the exact origin of high-grade serous OC, drug screening, and the development of precision medicine. This review provides an overview of recent progress in developing patient-derived organoids and their clinical relevance. Here, we outline their uses for transcriptomics and genomics profiling, drug screening, translational study, and their future perspective and clinical outlook as a model to advance OC research that could offer a promising approach for developing precision medicine.

Organotypic Models for Functional Drug Testing of Human Cancers

In the era of personalized oncology, there have been accelerated efforts to develop clinically relevant platforms to test drug sensitivities of individual cancers. An ideal assay will serve as a diagnostic companion to inform the oncologist of the various treatments that are sensitive and insensitive, thus improving outcome while minimizing unnecessary toxicities and costs. To date, no such platform exists for clinical use, but promising approaches are on the horizon that take advantage of improved techniques in creating human cancer models that encompass the entire tumor microenvironment, alongside technologies for assessing and analyzing tumor response. This review summarizes a number of current strategies that make use of intact human cancer tissues as organotypic cultures in drug sensitivity testing.

Morphological Characterization of Human Lung Cancer Organoids Cultured in Type I Collagen Hydrogels: A Histological Approach

The malignity of lung cancer is conditioned by the tumor microenvironment (TME), in which cancer-associated fibroblasts (CAFs) are relevant. In this work, we generated organoids by combining A549 cells with CAFs and normal fibroblasts (NF) isolated from adenocarcinoma tumors. We optimized the conditions for their manufacture in a short time. We evaluated the morphology of organoids using confocal microscopy analysis of F-actin, vimentin and pankeratin. We determined the ultrastructure of the cells in the organoids via transmission electron microscopy and the expression of CDH1, CDH2 and VIM via RT-PCR. The addition of stromal cells induces the self-organization of the organoids, which acquired a bowl morphology, as well as their growth and the generation of cell processes. They also influenced the expression of genes related to epithelial mesenchymal transition (EMT). CAFs potentiated these changes. All cells acquired a characteristic secretory phenotype, with cohesive cells appearing inside the organoids. In the periphery, many cells acquired a migratory phenotype, especially in organoids that incorporated CAFs. The deposit of abundant extracellular matrix could also be observed. The results presented here reinforce the role of CAFs in the progression of lung tumors and could lay the foundation for a useful in vitro pharmacological model.

Animal-derived products in science and current alternatives

More than fifty years after the 3Rs definition and despite the continuous implementation of regulatory measures, animals continue to be widely used in basic research. Their use comprises not only in vivo experiments with animal models, but also the production of a variety of supplements and products of animal origin for cell and tissue culture, cell-based assays, and therapeutics. The animal-derived products most used in basic research are fetal bovine serum (FBS), extracellular matrix proteins such as Matrigel™, and antibodies. However, their production raises several ethical issues regarding animal welfare. Additionally, their biological origin is associated with a high risk of contamination, resulting, frequently, in poor scientific data for clinical translation. These issues support the search for new animal-free products able to replace FBS, Matrigel™, and antibodies in basic research. In addition, in silico methodologies play an important role in the reduction of animal use in research by refining the data previously to in vitro and in vivo experiments. In this review, we depicted the current available animal-free alternatives in in vitro research.

Gamma distribution based predicting model for breast cancer drug response based on multi-layer feature selection

In the pursuit of precision medicine for cancer, a promising step is to predict drug response based on data mining, which can provide clinical decision support for cancer patients. Although some machine learning methods for predicting drug response from genomic data already exist, most of them focus on point prediction, which cannot reveal the distribution of predicted results. In this paper, we propose a three-layer feature selection combined with a gamma distribution based GLM and a two-layer feature selection combined with an ANN. The two regression methods are applied to the Encyclopedia of Cancer Cell Lines (CCLE) and the Cancer Drug Sensitivity Genomics (GDSC) datasets. Using ten-fold cross-validation, our methods achieve higher accuracy on anticancer drug response prediction compared to existing methods, with an R ² and RMSE of 0.87 and 0.53, respectively. Through data validation, the significance of assessing the reliability of predictions by predicting confidence intervals and its role in personalized medicine are illustrated. The correlation analysis of the genes selected from the three layers of features also shows the effectiveness of our proposed methods.

Targeting cancer drug resistance utilizing organoid technology

Cancer organoids generated from 3D in vitro cell cultures have contributed to the study of drug resistance. Maintenance of genomic and transcriptomic similarity between organoids and parental cancer allows organoids to have the ability of accurate prediction in drug resistance testing. Protocols of establishing therapy-sensitive and therapy-resistant organoids are concluded in two aspects, which are generated directly from respective patients' cancer and by induction of anti-cancer drug. Genomic and transcriptomic analyses and gene editing have been applied to organoid studies to identify key targets in drug resistance and FGFR3, KHDRBS3, lnc-RP11-536 K7.3 and FBN1 were found to be key targets. Furthermore, mechanisms contributing to resistance have been identified, including metabolic adaptation, activation of DNA damage response, defects in apoptosis, reduced cellular senescence, cellular plasticity, subpopulation interactions and gene fusions. Additionally, cancer stem cells (CSCs) have been verified to be involved in drug resistance utilizing organoid technology. Reversal of drug resistance can be achieved by targeting key genes and CSCs in cancer organoids. In this review, we summarize applications of organoids to cancer drug resistance research, indicating prospects and limitations.

Organoid technology and applications in lung diseases: Models, mechanism research and therapy opportunities

The prevalency of lung disease has increased worldwide, especially in the aging population. It is essential to develop novel disease models, that are superior to traditional models. Organoids are three-dimensional (3D) in vitro structures that produce from self-organizing and differentiating stem cells, including pluripotent stem cells (PSCs) or adult stem cells (ASCs). They can recapitulate the in vivo cellular heterogeneity, genetic characteristics, structure, and functionality of original tissues. Drug responses of patient-derived organoids (PDOs) are consistent with that of patients, and show correlations with genetic alterations. Thus, organoids have proven to be valuable in studying the biology of disease, testing preclinical drugs and developing novel therapies. In recent years, organoids have been successfully applied in studies of a variety of lung diseases, such as lung cancer, influenza, cystic fibrosis, idiopathic pulmonary fibrosis, and the recent severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic. In this review, we provide an update on the generation of organoid models for these diseases and their applications in basic and translational research, highlighting these signs of progress in pathogenesis study, drug screening, personalized medicine and immunotherapy. We also discuss the current limitations and future perspectives in organoid models of lung diseases.

Organoids from patient biopsy samples can predict the response of BC patients to neoadjuvant chemotherapy

PROPOSE

Neoadjuvant chemotherapy has been widely used in locally advanced and inflammatory breast cancer. Generally, complete pathological response after neoadjuvant chemotherapy treatment predicts survival. Studies have shown that patient-derived organoids can be used in cancer research and drug development. Therefore, we aimed to generate a living organoid biobank from biopsy samples to predict the response of patients to neoadjuvant chemotherapy.

METHOD

We generated a living organoid biobank from locally advanced breast cancer patients receiving neoadjuvant chemotherapy. When the patient received neoadjuvant chemotherapy, the organoids were treated with similar drugs, thereby simulating the situation of the patient receiving treatment.

RESULT

We successfully constructed organoids from breast cancer biopsies, demonstrating that organoids can be generated from a small sample of tissue. The phenotype of breast cancer organoid often agreed with the original breast cancer according to the blinded histopathological analysis of H&E stain tissue and organoid sections. In addition, our data confirm that the patient's response to chemotherapy closely matches the organoids' response to drugs.

CONCLUSION

Our data indicate that patient-derived organoids can be used to predict the clinical response of breast cancer patients to neoadjuvant chemotherapy in vitro and to screen drugs that have different effects on different patients. Key messageComplete pathological response (pCR) after adjuvant chemotherapy can predict, survival, therefore, predicting patient response to neoadjuvant chemotherapy is critical.Patient-derived organoids (PDOs) matched the original tumour in terms of histopathology, hormone receptor levels and HER2 receptor status.Patient-derived organoids can predict the responsiveness of patient to neoadjuvant chemotherapy.

A DFX-based iron nanochelator for cancer therapy

Iron as an essential element, is involved in various cellular functions and maintaining cell viability, cancer cell is more dependent on iron than normal cell due to its chief characteristic of hyper-proliferation. Despite that some of the iron chelators exhibited potent and broad antitumor activity, severe systemic toxicities have limited their clinical application. Polyaminoacids, as both drug-delivery platform and therapeutic agents, have attracted great interests owing to their different medical applications and biocompatibility. Herein, we have developed a novel iron nanochelator PL-DFX, which composed of deferasirox and hyperbranched polylysine. PL-DFX has higher cytotoxicity than DFX and this effect can be partially reversed by Fe2+ supplementation. PL-DFX also inhibited migration and invasion of cancer cells, interfere with iron metabolism, induce phase G1/S arrest and depolarize mitochondria membrane potential. Additionally, the anti-tumor potency of PL-DFX was also supported by organoids derived from clinical specimens. In this study, DFX-based iron nanochelator has provided a promising and prospective strategy for cancer therapy via iron metabolism disruption.

Focus on organoids: cooperation and interconnection with extracellular vesicles - Is this the future of in vitro modeling?

Organoids are simplified in vitro model systems of organs that are used for modeling tissue development and disease, drug screening, cell therapy, and personalized medicine. Despite considerable success in the design of organoids, challenges remain in achieving real-life applications. Organoids serve as unique and organized groups of micro physiological systems that are capable of self-renewal and self-organization. Moreover, they exhibit similar organ functionality(ies) as that of tissue(s) of origin. Organoids can be designed from adult stem cells, induced pluripotent stem cells, or embryonic stem cells. They consist of most of the important cell types of the desired tissue/organ along with the topology and cell-cell interactions that are highly similar to those of an in vivo tissue/organ. Organoids have gained interest in human biomedical research, as they demonstrate high promise for use in basic, translational, and applied research. As in vitro models, organoids offer significant opportunities for reducing the reliance and use of experimental animals. In this review, we will provide an overview of organoids, as well as those intercellular communications mediated by extracellular vesicles (EVs), and discuss the importance of organoids in modeling a tumor immune microenvironment (TIME). Organoids can also be exploited to develop a better understanding of intercellular communications mediated by EVs. Also, organoids are useful in mimicking TIME, thereby offering a better-controlled environment for studying various associated biological processes and immune cell types involved in tumor immunity, such as T-cells, macrophages, dendritic cells, and myeloid-derived suppressor cells, among others.

Chick Early Amniotic Fluid (ceAF) Deters Tumorigenesis via Cell Cycle Arrest and Apoptosis

In recent years, amniotic fluids have gained attention in cancer research. They have an influential role in protecting embryos against several anomalies. Chick early amniotic fluid (ceAF)-amniotic fluid isolated from growing chicken-has been used in many other studies, including myocardial infarctions and skin regeneration. In this study, we employed ceAF's promising therapeutic applications against tumorigenesis in both in vitro and in vivo studies. We selected three robust proliferating tumor cell lines: BCaP37, MCF7, and RKO. We found that selective dosage is required to obtain maximum impact to deter tumorigenesis. ceAF not only disrupted the uniform colonies of tumor cell lines via disturbing mitochondrial transmembrane potential, but also arrested many cells at growing G1 state via working agonistically with aphidicolin. The significant inhibition of tumor metastasis by ceAF was indicated by in vivo models. This leads to apoptosis analysis as verified by annexin-V staining stays and immunoblotting of critical proteins as cell cycle meditators and apoptosis regulators. Not only on the protein level, but we also tested ceAF's therapeutic potentials on mRNA levels as indicated by quantitative real-time PCR summarizing the promising role of ceAF in deterring tumor progression. In conclusion, our study reveals the potent role of ceAF against tumorigenesis in breast cancer and colon carcinoma. Further studies will be required to determine the critical components present in ceAF and its purification to narrow down this study.

Anti-glioblastoma activity of monensin and its analogs in an organoid model of cancer

Glioblastoma (GBM) remains the most frequently diagnosed primary malignant brain cancer in adults. Despite recent progress in understanding the biology of GBM, the clinical outcome for patients remains poor, with a median survival of approximately one year after diagnosis. One factor contributing to failure in clinical trials is the fact that traditional models used in GBM drug discovery poorly recapitulate patient tumors. Previous studies have shown that monensin (MON) analogs, namely esters and amides on C-26 were potent towards various types of cancer cell lines. In the present study we have investigated the activity of these molecules in GBM organoids, as well as in a host:tumor organoid model. Using a mini-ring cell viability assay we have identified seven analogs (IC₅₀ = 91.5 ± 54.4–291.7 ± 68.8 nM) more potent than parent MON (IC₅₀ = 612.6 ± 184.4 nM). Five of these compounds induced substantial DNA fragmentation in GBM organoids, suggestive of apoptotic cell death. The most active analog, compound 1, significantly reduced GBM cell migration, induced PARP degradation, diminished phosphorylation of STAT3, Akt and GSK3β, increased ɣH2AX signaling and upregulated expression of the autophagy associated marker LC3-II. To investigate the activity of MON and compound 1 in a tumor microenvironment, we developed human cerebral organoids (COs) from human induced pluripotent stem cells (iPSCs). The COs showed features of early developing brain such as multiple neural rosettes with a proliferative zone of neural stem cells (Nestin+), neurons (TUJ1 +), primitive ventricular system (SOX2 +/Ki67 +), intermediate zone (TBR2 +) and cortical plate (MAP2 +). In order to generate host:tumor organoids, we co-cultured RFP-labeled U87MG cells with fully formed COs. Compound 1 and MON reduced U87MG tumor size in the COs after four days of treatment and induced a significant reduction of PARP expression. These findings highlight the therapeutic potential of MON analogs towards GBM and support the application of organoid models in anti-cancer drug discovery.

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.

Patient-derived rectal cancer organoids—applications in basic and translational cancer research

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers and among the leading causes of death in both men and women. Rectal cancer (RC) is particularly challenging compared with colon cancer as the treatment after diagnosis of RC is more complex on account of its narrow anatomical location in the pelvis adjacent to the urogenital organs. More and more existing studies have begun to refine the research on RC and colon cancer separately. Early diagnosis and multiple treatment strategies optimize outcomes for individual patients. However, the need for more accurate and precise models to facilitate RC research is underscored due to the heterogeneity of clinical response and morbidity interrelated with radical surgery. Organoids generated from biopsies of patients have developed as powerful models to recapitulate many aspects of their primary tissue, consisting of 3-D self-organizing structures, which shed great light on the applications in both biomedical and clinical research. As the preclinical research models for RC are usually confused with colon cancer, research on patient-derived RC organoid models enable personalized analysis of cancer pathobiology, organizational function, and tumor initiation and progression. In this review, we discuss the various applications of patient-derived RC organoids over the past two years in basic cancer biology and clinical translation, including sequencing analysis, drug screening, precision therapy practice, tumor microenvironment studies, and genetic engineering opportunities.

Patient-derived Tumour Organoids: A Bridge between Cancer Biology and Personalised Therapy

Patient-derived tumour organoids (PDOs) have revolutionised our understanding of cancer biology and the applications of personalised therapies. These advancements are principally ascribed to the ability of PDOs to consistently recapitulate and maintain the genomic, proteomic and morphological characteristics of parental tumours. Given these characteristics, PDOs (and their extended biobanks) are a representative preclinical model eminently suited to translate relevant scientific findings into personalized therapies rapidly. Here, we summarise recent advancements in PDOs from the perspective of cancer biology and clinical applications, focusing on the current challenges and opportunities of reconstructing and standardising more sophisticated PDO models. STATEMENT OF SIGNIFICANCE: Patient-derived tumour organoids (PDOs), three-dimensional (3D) self-assembled organotypic structures, have revolutionised our understanding of cancer biology and the applications of personalised therapies. These advancements are principally ascribed to the ability of PDOs to consistently recapitulate and maintain the genomic, proteomic and morphological characteristics of parental tumours. Given these characteristics, PDOs (and their extended biobanks) are a representative preclinical model eminently suited to translate relevant scientific findings into personalized therapies rapidly.

Advances of Patient-Derived Organoids in Personalized Radiotherapy

Patient-derived organoids (PDO), based on the advanced three-dimensional (3D) culture technology, can provide more relevant physiological and pathological cancer models, which is especially beneficial for developing and optimizing cancer therapeutic strategies. Radiotherapy (RT) is a cornerstone of curative and palliative cancer treatment, which can be performed alone or integrated with surgery, chemotherapy, immunotherapy, or targeted therapy in clinical care. Among all cancer therapies, RT has great local control, safety and effectiveness, and is also cost-effective per life-year gained for patients. It has been reported that combing RT with chemotherapy or immunotherapy or radiosensitizer drugs may enhance treatment efficacy at faster rates and lower cost. However, very few FDA-approved combinations of RT with drugs or radiosensitizers exist due to the lack of accurate and relevant preclinical models. Meanwhile, radiation dose escalation may increase treatment efficacy and induce more toxicity of normal tissue as well, which has been studied by conducting various clinical trials, very expensive and time-consuming, often burdensome on patients and sometimes with controversial results. The surged PDO technology may help with the preclinical test of RT combination and radiation dose escalation to promote precision radiation oncology, where PDO can recapitulate individual patient’ tumor heterogeneity, retain characteristics of the original tumor, and predict treatment response. This review aims to introduce recent advances in the PDO technology and personalized radiotherapy, highlight the strengths and weaknesses of the PDO cancer models, and finally examine the existing RT-related PDO trials or applications to harness personalized and precision radiotherapy.

Overcome Drug Resistance in Cholangiocarcinoma: New Insight Into Mechanisms and Refining the Preclinical Experiment Models

Cholangiocarcinoma (CCA) is an aggressive tumor characterized by a poor prognosis. Therapeutic options are limited in patients with advanced stage of CCA, as a result of the intrinsic or acquired resistance to currently available chemotherapeutic agents, and the lack of new drugs entering into clinical application. The challenge in translating basic research to the clinical setting, caused by preclinical models not being able to recapitulate the tumor characteristics of the patient, seems to be an important reason for the lack of effective and specific therapies for CCA. So, there seems to be two ways to improve patient outcomes. The first one is developing the combination therapies based on a better understanding of the mechanisms contributing to the resistance to currently available chemotherapeutic agents. The second one is developing novel preclinical experimental models that better recapitulate the genetic and histopathological features of the primary tumor, facilitating the screening of new drugs for CCA patients. In this review, we discussed the evidence implicating the mechanisms underlying treatment resistance to currently investigated drugs, and the development of preclinical experiment models for CCA.

Stem Cells, Helicobacter pylori, and Mutational Landscape: Utility of Preclinical Models to Understand Carcinogenesis and to Direct Management of Gastric Cancer

Several genetic and environmental factors increase gastric cancer (GC) risk, with Helicobacter pylori being the main environmental agent. GC is thought to emerge through a sequence of morphological changes that have been elucidated on the molecular level. New technologies have shed light onto pathways that are altered in GC, involving mutational and epigenetic changes and altered signaling pathways. Using various new model systems and innovative approaches, the relevance of such alterations for the emergence and progression of GC has been validated. Here, we highlight the key strategies and the resulting achievements. A major step is the characterization of epithelial stem cell behavior in the healthy stomach. These data, obtained through new reporter mouse lines and lineage tracing, enabled insights into the processes that control cellular proliferation, self-renewal, and differentiation of gastric stem cells. It has become evident that these cells and pathways are often deregulated in carcinogenesis. Second, insights into how H pylori colonizes gastric glands, directly interacts with stem cells, and alters cellular and genomic integrity, as well as the characterization of tissue responses to infection, provide a comprehensive picture of how this bacterium contributes to gastric carcinogenesis. Third, the development of stem cell- and tissue-specific reporter mice have driven our understanding of the signals and mutations that promote different types of GC and now also enable the study of more advanced, metastasized stages. Finally, organoids from human tissue have allowed insights into gastric carcinogenesis by validating mutational and signaling alterations in human primary cells and opening a route to predicting responses to personalized treatment.

Honeycomb-Like Hydrogel Microspheres for 3D Bulk Construction of Tumor Models

A two-dimensional (2D) cell culture-based model is widely applied to study tumorigenic mechanisms and drug screening. However, it cannot authentically simulate the three-dimensional (3D) microenvironment of solid tumors and provide reliable and predictable data in response to in vivo, thus leading to the research illusions and failure of drug screening. In this study, honeycomb-like gelatin methacryloyl (GelMA) hydrogel microspheres are developed by synchronous photocrosslinking microfluidic technique to construct a 3D model of osteosarcoma. The in vitro study shows that osteosarcoma cells (K7M2) cultured in 3D GelMA microspheres have stronger tumorous stemness, proliferation and migration abilities, more osteoclastogenetic ability, and resistance to chemotherapeutic drugs (DOX) than that of cells in 2D cultures. More importantly, the 3D-cultured K7M2 cells show more tumorigenicity in immunologically sound mice, characterized by shorter tumorigenesis time, larger tumor volume, severe bone destruction, and higher mortality. In conclusion, honeycomb-like porous microsphere scaffolds are constructed with uniform structure by microfluidic technology to massively produce tumor cells with original phenotypes. Those microspheres could recapitulate the physiology microenvironment of tumors, maintain cell-cell and cell-extracellular matrix interactions, and thus provide an effective and convenient strategy for tumor pathogenesis and drug screening research.

Patient-Derived Organoids in Precision Medicine: Drug Screening, Organoid-on-a-Chip and Living Organoid Biobank

Organoids are in vitro self-assembling, organ-like, three-dimensional cellular structures that stably retain key characteristics of the respective organs. Organoids can be generated from healthy or pathological tissues derived from patients. Cancer organoid culture platforms have several advantages, including conservation of the cellular composition that captures the heterogeneity and pharmacotypic signatures of the parental tumor. This platform has provided new opportunities to fill the gap between cancer research and clinical outcomes. Clinical trials have been performed using patient-derived organoids (PDO) as a tool for personalized medical decisions to predict patients' responses to therapeutic regimens and potentially improve treatment outcomes. Living organoid biobanks encompassing several cancer types have been established, providing a representative collection of well-characterized models that will facilitate drug development. In this review, we highlight recent developments in the generation of organoid cultures and PDO biobanks, in preclinical drug discovery, and methods to design a functional organoid-on-a-chip combined with microfluidic. In addition, we discuss the advantages as well as limitations of human organoids in patient-specific therapy and highlight possible future directions.

Advance in Human Epithelial-Derived Organoids Research

Organoids have complex three-dimensional structures that exhibit functionalities and feature architectures similar to those of in vivo organs and are developed from adult stem cells, embryonic stem cells, and pluripotent stem cells through a self-organization process. Organoids derived from adult epithelial stem cells are the most mature and extensive. In recent years, using organoid culture techniques, researchers have established various adult human tissue-derived epithelial organoids, including intestinal, colon, lung, liver, stomach, breast, and oral mucosal organoids, all of which exhibit strong research and application prospects. Studies have shown that epithelial organoids are mainly applied in drug discovery, personalized drug response testing, disease mechanism research, and regenerative medicine. In this review, we mainly discuss current organoid culture systems and potential applications of this technique with human epithelial tissue.

The potential application of organoids in breast cancer research and treatment

Tumor heterogeneity is a major challenge for breast cancer researchers who have struggled to find effective treatments despite recent advances in oncology. Although the use of 2D cell culture methods in breast cancer research has been effective, it cannot model the heterogeneity of breast cancer as found within the body. The development of 3D culture of tumor cells and breast cancer organoids has provided a new approach in breast cancer research, allowing the identification of biomarkers, study of the interaction of tumor cells with the microenvironment, and for drug screening and discovery. In addition, the possibility of gene editing in organoids, especially using the CRISPR/Cas9 system, is convenient, and has allowed a more detailed study of tumor behavior in models closer to the physiological condition. The present review covers the application of organoids in breast cancer research. The recent use of gene-editing systems to provide insights into therapeutic approaches for breast cancer, is highlighted. The study of organoids and the possibility of gene manipulation may be a step towards the personalized treatment of breast cancer, which has so far remained unattainable due to the high heterogeneity of breast cancer.

Gastrointestinal cancer organoids-applications in basic and translational cancer research

Cancer is a major health problem and a leading cause of death worldwide. Early cancer detection and continuous changes in treatment strategies have improved overall patient survival. The recent development of targeted drugs offers new opportunities for personalized cancer treatment. Nevertheless, individualized treatment is accompanied by the need for biomarkers predicting the response of a patient to a certain drug. One of the most promising breakthroughs in recent years that might help to overcome this problem is the organoid technology. Organoid cultures exhibit self-renewal capacity, self-organization, and long-term proliferation, while recapitulating many aspects of their primary tissue. Generated patient-derived organoid (PDO) libraries constitute "living" biobanks, allowing the in-depth analysis of tissue function, development, tumor initiation, and cancer pathobiology. Organoids can be derived from all gastrointestinal tissues, including esophageal, gastric, liver, pancreatic, small intestinal and colorectal tissues, and cancers of these tissues. PDOs are amenable to various techniques, including sequencing analyses, drug screening, targeted therapy testing, tumor microenvironment studies, and genetic engineering capabilities. In this review, we discuss the different applications of gastrointestinal organoids in basic cancer biology and clinical translation.

Stem Cell Based Preclinical Drug Development and Toxicity Prediction

Stem cell based toxicity prediction plays a very important role in the development of the drug. Unexpected adverse effects of the drugs during clinical trials are a major reason for the termination or withdrawal of drugs. Methods for predicting toxicity employ in vitro as well as in vivo models; however, the major drawback seen in the data derived from these animal models is the lack of extrapolation, owing to interspecies variations. Due to these limitations, researchers have been striving to develop more robust drug screening platforms based on stem cells. The application of stem cells based toxicity testing has opened up robust methods to study the impact of new chemical entities on not only specific cell types, but also organs. Pluripotent stem cells, as well as cells derived from them, can be evaluated for modulation of cell function in response to drugs. Moreover, the combination of state-of-the -art techniques such as tissue engineering and microfluidics to fabricate organ- on-a-chip, has led to assays which are amenable to high throughput screening to understand the adverse and toxic effects of chemicals and drugs. This review summarizes the important aspects of the establishment of the embryonic stem cell test (EST), use of stem cells, pluripotent, induced pluripotent stem cells and organoids for toxicity prediction and drug development.

Transcending toward Advanced 3D-Cell Culture Modalities: A Review about an Emerging Paradigm in Translational Oncology

Cancer is a disorder characterized by an uncontrollable overgrowth and a fast-moving spread of cells from a localized tissue to multiple organs of the body, reaching a metastatic state. Throughout years, complexity of cancer progression and invasion, high prevalence and incidence, as well as the high rise in treatment failure cases leading to a poor patient prognosis accounted for continuous experimental investigations on animals and cellular models, mainly with 2D- and 3D-cell culture. Nowadays, these research models are considered a main asset to reflect the physiological events in many cancer types in terms of cellular characteristics and features, replication and metastatic mechanisms, metabolic pathways, biomarkers expression, and chemotherapeutic agent resistance. In practice, based on research perspective and hypothesis, scientists aim to choose the best model to approach their understanding and to prove their hypothesis. Recently, 3D-cell models are seen to be highly incorporated as a crucial tool for reflecting the true cancer cell microenvironment in pharmacokinetic and pharmacodynamics studies, in addition to the intensity of anticancer drug response in pharmacogenomics trials. Hence, in this review, we shed light on the unique characteristics of 3D cells favoring its promising usage through a comparative approach with other research models, specifically 2D-cell culture. Plus, we will discuss the importance of 3D models as a direct reflector of the intrinsic cancer cell environment with the newest multiple methods and types available for 3D-cells implementation.

Organoid models of the tumor microenvironment and their applications

A small percentage of data obtained from animal/2D culture models can be translated to humans. Therefore, there is a need to using native tumour microenvironment mimicking models to improve preclinical screening and reduce this attrition rate. For this purpose, currently, the utilization of organoids is expanding. Tumour organoids can recapitulate tumour microenvironment that is including cancer cells and non-neoplastic host components. Indeed, tumour organoids, both phenotypically and genetically, resemble the tumour tissue that originated from it. The unique properties of the tumour microenvironment can significantly affect drug response and cancer progression. In this review, we will discuss about various organoid culture strategies for modelling the tumour immune microenvironment, their applications and advantages in cancer research such as testing cancer immunotherapeutics, developing novel approaches for personalized medicine, testing drug toxicity, drug screening, study cancer initiation and progression, and we will also review the limitations of organoid culture systems.

Integrative microphysiological tissue systems of cancer metastasis to the liver

The liver is the most commonly involved organ in metastases from a wide variety of solid tumors. The use of biologically and cellularly complex liver tissue systems have shown that tumor cell behavior and therapeutic responses are modulated within the liver microenvironment and in ways distinct from the behaviors in the primary locations. These microphysiological systems have provided unexpected and powerful insights into the tumor cell biology of metastasis. However, neither the tumor nor the liver exist in an isolated tissue situation, having to function within a complete body and respond to systemic events as well as those in other organs. To examine the influence of one organ on the function of other tissues, microphysiological systems are being linked. Herein, we discuss extending this concept to tumor metastases by integrating complex models of the primary tumor with the liver metastatic environment. In addition, inflammatory organs and the immune system can be incorporated into these multi-organ systems to probe the effects on tumor behavior and cancer treatments.

Microvascularized tumor organoids-on-chips: advancing preclinical drug screening with pathophysiological relevance

Recent developments of organoids engineering and organ-on-a-chip microfluidic technologies have enabled the recapitulation of the major functions and architectures of microscale human tissue, including tumor pathophysiology. Nevertheless, there remain challenges in recapitulating the complexity and heterogeneity of tumor microenvironment. The integration of these engineering technologies suggests a potential strategy to overcome the limitations in reconstituting the perfusable microvascular system of large-scale tumors conserving their key functional features. Here, we review the recent progress of in vitro tumor-on-a-chip microfluidic technologies, focusing on the reconstruction of microvascularized organoid models to suggest a better platform for personalized cancer medicine.

DeepDRK: a deep learning framework for drug repurposing through kernel-based multi-omics integration

Recent pharmacogenomic studies that generate sequencing data coupled with pharmacological characteristics for patient-derived cancer cell lines led to large amounts of multi-omics data for precision cancer medicine. Among various obstacles hindering clinical translation, lacking effective methods for multimodal and multisource data integration is becoming a bottleneck. Here we proposed DeepDRK, a machine learning framework for deciphering drug response through kernel-based data integration. To transfer information among different drugs and cancer types, we trained deep neural networks on more than 20 000 pan-cancer cell line-anticancer drug pairs. These pairs were characterized by kernel-based similarity matrices integrating multisource and multi-omics data including genomics, transcriptomics, epigenomics, chemical properties of compounds and known drug-target interactions. Applied to benchmark cancer cell line datasets, our model surpassed previous approaches with higher accuracy and better robustness. Then we applied our model on newly established patient-derived cancer cell lines and achieved satisfactory performance with AUC of 0.84 and AUPRC of 0.77. Moreover, DeepDRK was used to predict clinical response of cancer patients. Notably, the prediction of DeepDRK correlated well with clinical outcome of patients and revealed multiple drug repurposing candidates. In sum, DeepDRK provided a computational method to predict drug response of cancer cells from integrating pharmacogenomic datasets, offering an alternative way to prioritize repurposing drugs in precision cancer treatment. The DeepDRK is freely available via https://github.com/wangyc82/DeepDRK.

Comparison of Proteomics Profiles Between Xenografts Derived from Cell Lines and Primary Tumors of Thyroid Carcinoma

Patient-consistent xenograft model is a challenge for all cancers but particularly for thyroid cancer, which shows some of the greatest genetic divergence between human tumors and cell lines. In this study, proteomic profiles of tumor tissues from patients, included anaplastic thyroid carcinoma (ATC) and papillary thyroid carcinoma, and xenografts (8305C, 8505C, FRO, BAPAP and IHH4) were obtained using HPLC-tandem mass spectrometry and compared based on all proteins detected (3,961), cancer-related proteins and druggable proteins using pairwise Pearson's correlation analysis. The human tissue showed low proteomic similarity to the ATC cell lines (8305C, r = 0.344-0.416; 8505C, 0.47-0.579; FRO, 0.267-0.307) and to PTC cell lines (BCPAP, 0.303-0.468; IHH4, 0.262-0.509). Human tissue showed the following similarity to cell lines at the level of 135 cancer-related pathways. The ATC cell lines contained 47.4% of the cancer-related pathways (19.26%-33.33%), while the PTC cell lines contained 40% (BCPAP, 25.93%; IHH4, 28.89%). In patient tumor tissues, 44-60 of 76 and 52-53 of 93 druggable proteins were identified in ATC and PTC tumors, respectively. Ten and 29 druggable proteins were not identified in any of the ATC and PTC xenografts, respectively. We provide a reference for CDX selecting in in vivo studies of thyroid cancer.

Liver Buds and Liver Organoids: New Tools for Liver Development, Disease and Medical Application

The current understanding and effective treatment of liver disease is far from satisfactory. Liver organoids and liver buds (LBs) transforming cell culture from two dimensions(2D) to three dimensions(3D) has provided infinite possibilities for stem cells to use in clinic. Recent technological advances in the 3D culture have shown the potentiality of liver organoids and LBs as the promising tool to model in vitro liver diseases. The induced LBs and liver organoids provide a platform for cell-based therapy, liver disease models, liver organogenesis and drugs screening. And its genetic heterogeneity supplies a way for the realization of precision medicine.

Modeling neoplastic disease with spheroids and organoids

Cancer is a complex disease in which both genetic defects and microenvironmental components contribute to the development, progression, and metastasization of disease, representing major hurdles in the identification of more effective and safer treatment regimens for patients. Three-dimensional (3D) models are changing the paradigm of preclinical cancer research as they more closely resemble the complex tissue environment and architecture found in clinical tumors than in bidimensional (2D) cell cultures. Among 3D models, spheroids and organoids represent the most versatile and promising models in that they are capable of recapitulating the heterogeneity and pathophysiology of human cancers and of filling the gap between conventional 2D in vitro testing and animal models. Such 3D systems represent a powerful tool for studying cancer biology, enabling us to model the dynamic evolution of neoplastic disease from the early stages to metastatic dissemination and the interactions with the microenvironment. Spheroids and organoids have recently been used in the field of drug discovery and personalized medicine. The combined use of 3D models could potentially improve the robustness and reliability of preclinical research data, reducing the need for animal testing and favoring their transition to clinical practice. In this review, we summarize the recent advances in the use of these 3D systems for cancer modeling, focusing on their innovative translational applications, looking at future challenges, and comparing them with most widely used animal models.

Organoid models in lung regeneration and cancer

Improper regeneration is associated with lung diseases including lung cancer. Lung cancer is one of the leading causes of death worldwide, with nearly 2 million new cases diagnosed each year. The diagnosis is often too late for successful therapeutic intervention. Lung cancer shows substantial phenotypic and genetic heterogeneity between individuals, making it difficult to model in animals. Organoids, derived from regional stem/progenitor cells in lung epithelia, have attracted extensive interest in both research studies and the clinic, because of their great potential for use in cancer treatment. Various lung cancer organoids have been established to recapitulate the tissue architecture of primary lung tumors and maintain the genomic alterations of the original tumors during long-term expansion in vitro. In this review, we summarize the current data on lung epithelial regeneration by regional endogenous stem/progenitor cells, describe the development of organoid technology, and present its applications in lung cancer research. Furthermore, recent challenges and future directions to improve organoid technologies for lung cancer treatment are discussed.

A thioredoxin reductase inhibitor ethaselen induces growth inhibition and apoptosis in gastric cancer

Gastric cancer (GC) is the third leading cause of cancer deaths worldwide. Conventional chemotherapy has been proven useful to only a portion of the patients. Previous developed targeted drugs are more effective and tolerable than conventional drugs. Thus the development of novel drugs targeting markers is an urgent task and the main direction for future research. Ethaselen, an inhibitor of thioredoxin reductase (TrxR), has been considered an important anticancer target drug. Previous studies show that it is effective on treating many kinds of cancers. In this paper, we examined that ethaselen effectively inhibited the growth of gastric cancer cells and promoted apoptosis. Organoids were cultured from patient-derived cells in a three-dimension form which are widely used in cancer research to help us understand cancer cells behavior at the sub-organ level and develop novel drugs. We established a drug testing and screening system using GC-derived organoids by recapitulating tumor microenvironment. We confirmed that the TrxR-targeting ethaselen could be a novel and effective drug for gastric cancer treatment.

Organoid of ovarian cancer: genomic analysis and drug screening

Ovarian cancer is the most common malignant tumors of the female reproductive system, and its standard treatments are cytoreductive surgery and platinum-based adjuvant chemotherapy. Great advances have been achieved in novel treatment strategies, including targeted therapy and immunotherapy. However, ovarian cancer has the highest mortality rate among gynecological tumors due to therapeutic resistance and the gap between preclinical data and actual clinical efficacy. Organoids are a 3D culture model that markedly affects gene analysis, drug screening, and drug sensitivity determination of tumors, especially when used in targeted therapy and immunotherapy. In addition, organoid can lead to advances in the preclinical research of ovarian cancer due to its convenient cultivation, good genetic stability, and high homology with primary tumors.

Metastasis-on-a-chip mimicking the progression of kidney cancer in the liver for predicting treatment efficacy

Metastasis is one of the most important factors that lead to poor prognosis in cancer patients, and effective suppression of the growth of primary cancer cells in a metastatic site is paramount in averting cancer progression. However, there is a lack of biomimetic three-dimensional (3D) in vitro models that can closely mimic the continuous growth of metastatic cancer cells in an organ-specific extracellular microenvironment (ECM) for assessing effective therapeutic strategies. Methods: In this metastatic tumor progression model, kidney cancer cells (Caki-1) and hepatocytes (i.e., HepLL cells) were co-cultured at an increasing ratio from 1:9 to 9:1 in a decellularized liver matrix (DLM)/gelatin methacryloyl (GelMA)-based biomimetic liver microtissue in a microfluidic device. Results:Via this model, we successfully demonstrated a linear anti-cancer relationship between the concentration of anti-cancer drug 5-Fluorouracil (5-FU) and the percentage of Caki-1 cells in the co-culture system (R2 = 0.89). Furthermore, the Poly(lactide-co-glycolide) (PLGA)-poly(ethylene glycol) (PEG)-based delivery system showed superior efficacy to free 5-FU in killing Caki-1 cells. Conclusions: In this study, we present a novel 3D metastasis-on-a-chip model mimicking the progression of kidney cancer cells metastasized to the liver for predicting treatment efficacy. Taken together, our study proved that the tumor progression model based on metastasis-on-a-chip with organ-specific ECM would provide a valuable tool for rapidly assessing treatment regimens and developing new chemotherapeutic agents.

Associating lncRNAs with small molecules via bilevel optimization reveals cancer-related lncRNAs

Long noncoding RNA (lncRNA) transcripts have emerging impacts in cancer studies, which suggests their potential as novel therapeutic agents. However, the molecular mechanism behind their treatment effects is still unclear. Here, we designed a computational model to Associate LncRNAs with Anti-Cancer Drugs (ALACD) based on a bilevel optimization model, which optimized the gene signature overlap in the upper level and imputed the missing lncRNA-gene association in the lower level. ALACD predicts genes coexpressed with lncRNAs mean while matching drug’s gene signatures. This model allows us to borrow the target gene information of small molecules to understand the mechanisms of action of lncRNAs and their roles in cancer. The ALACD model was systematically applied to the 10 cancer types in The Cancer Genome Atlas (TCGA) that had matched lncRNA and mRNA expression data. Cancer type-specific lncRNAs and associated drugs were identified. These lncRNAs show significantly different expression levels in cancer patients. Follow-up functional and molecular pathway analysis suggest the gene signatures bridging drugs and lncRNAs are closely related to cancer development. Importantly, patient survival information and evidence from the literature suggest that the lncRNAs and drug-lncRNA associations identified by the ALACD model can provide an alternative choice for cancer targeting treatment and potential cancer pognostic biomarkers. The ALACD model is freely available at https://github.com/wangyc82/ALACD-v1.

LncRNAs are RNA transcripts that are longer than 200 bp and do not encode proteins. Recent experimental studies have indicated the crucial role of lncRNAs in cancer. We proposed a computational model, ALACD, to understand a lncRNA’s molecular mechanism by associating it with a drug through the drug’s target genes. ALACD reveals lncRNAs, the associated anti-cancer drug, and the induced gene signatures that are involved in the regulation of cancer. Furthermore, these cancer-related lncRNAs are differentially expressed in cancer patients and closely associated with patient survival.

Sensor-free and Sensor-based Heart-on-a-chip Platform: A Review of Design and Applications

Drug efficacy and toxicity are key factors of drug development. Conventional 2D cell models or animal models have their limitations for the efficacy or toxicity assessment in preclinical assays, which induce the failure of candidate drugs or withdrawal of approved drugs. Human organs-on-chips (OOCs) emerged to present human-specific properties based on their 3D bioinspired structures and functions in the recent decade. In this review, the basic definition and superiority of OOCs will be introduced. Moreover, a specific OOC, heart-on-achip (HOC) will be focused. We introduce HOC modeling in the sensor-free and sensor-based way and illustrate the advantages of sensor-based HOC in detail by taking examples of recent studies. We provide a new perspective on the integration of HOC technology and biosensing to develop a new sensor-based HOC platform.

High expression of apoptosis protein (Api-5) in chemoresistant triple-negative breast cancers: an innovative target

Anti-apoptotic protein-5 (API-5) is a survival protein interacting with the protein acinus, preventing its cleavage by caspase-3 and thus inhibiting apoptosis. We studied the effect of targeting API-5 in chemoresistant triple negative breast cancers (TNBCs), to reverse chemoresistance.

78 TNBC biopsies from patients with different responses to chemotherapy were analysed for API-5 expression before any treatment. Further studies on API-5 expression and inhibition were performed on patient-derived TNBC xenografts, one highly sensitive to chemotherapies (XBC-S) and the other resistant to most tested drugs (XBC-R). In situ assessments of necrosis, cell proliferation, angiogenesis, and apoptosis in response to anti-API-5 peptide were performed on the TNBC xenografts.

Clinical analyses of the 78 TNBC biopsies revealed that API-5 was more markedly expressed in endothelial cells before any treatment among patients with chemoresistant TNBC, and this was associated with greater micro-vessel density. A transcriptomic analysis of xenografted tumors showed an involvement of anti-apoptotic genes in the XBC-R model, and API-5 expression was higher in XBC-R endothelial cells. API-5 expression was also correlated with hypoxic stress conditions both in vitro and in vivo. 28 days of anti-API-5 peptide efficiently inhibited the XBC-R xenograft via caspase-3 apoptosis. This inhibition was associated with major inhibition of angiogenesis associated with necrosis and apoptosis.

API-5 protein could be a valid therapeutic target in chemoresistant metastatic TNBC.