Tumor organoids: Opportunities and challenges to guide precision medicine

Hydrogel-Embedded Precision-Cut Lung Slices Model Lung Cancer Premalignancy Ex Vivo

Lung cancer is the leading global cause of cancer-related deaths. Although smoking cessation is the best prevention, 50% of lung cancer diagnoses occur in people who have quit smoking. Research into treatment options for high-risk patients is constrained to rodent models, which are time-consuming, expensive, and require large cohorts. Embedding precision-cut lung slices (PCLS) within an engineered hydrogel and exposing this tissue to vinyl carbamate, a carcinogen from cigarette smoke, creates an in vitro model of lung cancer premalignancy. Hydrogel formulations are selected to promote early lung cancer cellular phenotypes and extend PCLS viability to six weeks. Hydrogel-embedded PCLS are exposed to vinyl carbamate, which induces adenocarcinoma in mice. Analysis of proliferation, gene expression, histology, tissue stiffness, and cellular content after six weeks reveals that vinyl carbamate induces premalignant lesions with a mixed adenoma/squamous phenotype. Putative chemoprevention agents diffuse through the hydrogel and induce tissue-level changes. The design parameters selected using murine tissue are validated with hydrogel-embedded human PCLS and results show increased proliferation and premalignant lesion gene expression patterns. This tissue-engineered model of human lung cancer premalignancy is the foundation for more sophisticated ex vivo models that enable the study of carcinogenesis and chemoprevention strategies.

Advances in Thyroid Organoids Research and Applications

INTRODUCTION

Organoids are three-dimensional cellular aggregates derived from stem cells or primary tissues that can self-organize into organotypic structures and showcase the physiological functions of that organ. Organoids typically comprise multiple organ-specific cell types that are responsible for organ function in vivo. They may also incorporate various cellular and molecular stromal components to recapitulate the in vivo microenvironment of the target organ.

METHODS

All articles related to thyroid-like organs were synthesized. Articles published between 1959 and 2023 were assessed, categorized, and analyzed using relevant keywords.

RESULTS

As such, organoids provide a model of greater physiological relevance than 2D cell culture for basic and translational research. Murine and human organoids of the thyroid have been established from embryonic stem cells (ESCs), pluripotent stem cells (PSCs) and from various healthy or diseased thyroid tissues. These thyroid organoids have been used in basic and translation research on thyroid-related diseases including hyperthyroidism, Graves' disease, and Hashimoto's thyroiditis. In addition, organoids derived from patients with thyroid cancer retain histopathological features and mutational profile of the original tumor. These patient-derived organoids have been successfully used in in vitro evaluation of drug response of individual patients, demonstrating their potential application in personalized treatment of thyroid cancer.

CONCLUSION

In this review article, we have discussed various techniques for establishing thyroid organoids and their applications in thyroid-related diseases as disease models, regenerative medicines, or a tool for drug testing.

Urine-derived bladder cancer organoids (urinoids) as a tool for cancer longitudinal response monitoring and therapy adaptation

BACKGROUND

Bladder cancer is one of the most common cancer types worldwide. Generally, research relies on invasive sampling strategies.

METHODS

Here, we generate bladder cancer organoids directly from urine (urinoids). In this project, we establish 12 urinoid lines from 22 patients with non-muscle and muscle-invasive bladder tumours, with an efficiency of 55%.

RESULTS

The histopathological features of the urinoids accurately resemble those of the original bladder tumours. Genetically, there is a high concordance of single nucleotide polymorphisms (92.56%) and insertions & deletions (91.54%) between urinoids and original tumours from patient 4. Furthermore, these urinoids show sensitivity to bladder cancer drugs, similar to their tissue-derived organoid counterparts. Genetic analysis of longitudinally generated tumoroids and urinoids from one patient receiving systemic immunotherapy, identify alterations that may guide the choice for second-line therapy. Successful treatment adaptation was subsequently demonstrated in the urinoid setting.

CONCLUSION

Therefore, urinoids can advance precision medicine in bladder cancer as a non-invasive platform for tumour pathogenesis, longitudinal drug-response monitoring, and therapy adaptation.

Organoids derived from patients provide a new opportunity for research and individualized treatment of malignant peritoneal mesothelioma

BACKGROUND

Malignant peritoneal mesothelioma (MPM) is an extremely rare and highly invasive tumor. Due to the lack of accurate models that reflect the biological characteristics of primary tumors, studying MPM remains challenging and is associated with an exceedingly unfavorable prognosis. This study was aimed to establish a new potential preclinical model for MPM using patient-derived MPM organoids (MPMOs) and to comprehensively evaluate the practicality of this model in medical research and its feasibility in guiding individualized patient treatment.

METHODS

MPMOs were constructed using tumor tissue from MPM patients. Histopathological analysis and whole genome sequencing (WGS) were employed to determine the ability of MPMOs to replicate the original tumor's genetic and histological characteristics. The subcutaneous and orthotopic xenograft models were employed to assess the feasibility of establishing an in vivo model of MPM. MPMOs were also used to conduct drug screening and compare the results with retrospective analysis of patients after treatment, in order to evaluate the potential of MPMOs in predicting the effectiveness of drugs in MPM patients.

RESULTS

We successfully established a culture method for human MPM organoids using tumor tissue from MPM patients and provided a comprehensive description of the necessary medium components for MPMOs. Pathological examination and WGS revealed that MPMOs accurately represented the histological characteristics and genomic heterogeneity of the original tumors. In terms of application, the success rate of creating subcutaneous and orthotopic xenograft models using MPMOs was 88% and 100% respectively. Drug sensitivity assays demonstrated that MPMOs have different medication responses, and these differences were compatible with the real situation of the patients.

CONCLUSION

This study presents a method for generating human MPM organoids, which can serve as a valuable research tool and contribute to the advancement of MPM research. Additionally, these organoids can be utilized as a means to evaluate the effectiveness of drug treatments for MPM patients, offering a model for personalized treatment approaches.

A multidimensional platform of patient-derived tumors identifies drug susceptibilities for clinical lenvatinib resistance

Lenvatinib, a second-generation multi-receptor tyrosine kinase inhibitor approved by the FDA for first-line treatment of advanced liver cancer, facing limitations due to drug resistance. Here, we applied a multidimensional, high-throughput screening platform comprising patient-derived resistant liver tumor cells (PDCs), organoids (PDOs), and xenografts (PDXs) to identify drug susceptibilities for conquering lenvatinib resistance in clinically relevant settings. Expansion and passaging of PDCs and PDOs from resistant patient liver tumors retained functional fidelity to lenvatinib treatment, expediting drug repurposing screens. Pharmacological screening identified romidepsin, YM155, apitolisib, NVP-TAE684 and dasatinib as potential antitumor agents in lenvatinib-resistant PDC and PDO models. Notably, romidepsin treatment enhanced antitumor response in syngeneic mouse models by triggering immunogenic tumor cell death and blocking the EGFR signaling pathway. A combination of romidepsin and immunotherapy achieved robust and synergistic antitumor effects against lenvatinib resistance in humanized immunocompetent PDX models. Collectively, our findings suggest that patient-derived liver cancer models effectively recapitulate lenvatinib resistance observed in clinical settings and expedite drug discovery for advanced liver cancer, providing a feasible multidimensional platform for personalized medicine.

Engineering Heterogeneous Tumor Models for Biomedical Applications

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

Next-Generation Preclinical Functional Testing Models in Cancer Precision Medicine: CTC-Derived Organoids

Basic and clinical cancer research requires tumor models that consistently recapitulate the characteristics of prima tumors. As ex vivo 3D cultures of patient tumor cells, patient-derived tumor organoids possess the biological properties of primary tumors and are therefore excellent preclinical models for cancer research. Patient-derived organoids can be established using primary tumor tissues, peripheral blood, pleural fluid, ascites, and other samples containing tumor cells. Circulating tumor cells acquired by non-invasive sampling feature dynamic circulation and high heterogeneity. Circulating tumor cell-derived organoids are prospective tools for the dynamic monitoring of tumor mutation evolution profiles because they reflect the heterogeneity of the original tumors to a certain extent. This review discusses the advantages and applications of patient-derived organoids. Meanwhile, this work highlights the biological functions of circulating tumor cells, the latest advancement in research of circulating tumor cell-derived organoids, and potential application and challenges of this technology.

Bioengineering Approaches for the Pancreatic Tumor Organoids Research and Application

Pancreatic cancer is a highly lethal form of digestive malignancy that poses significant health risks to individuals worldwide. Chemotherapy-based comprehensive treatment is the primary therapeutic approach for midlife and late-life patients. Nevertheless, the heterogeneity of the tumor and individual genetic backgrounds result in substantial variations in drug sensitivity among patients, rendering a single treatment regimen unsuitable for all patients. Conventional pancreatic cancer tumor organoid models are capable of emulating the biological traits of pancreatic cancer and are utilized in drug development and screening. However, these tumor organoids can still not mimic the tumor microenvironment (TME) in vivo, and the poor controllability in the preparation process hinders translation from essential drug screening to clinical pharmacological therapy. In recent years, many engineering methods with remarkable results have been used to develop pancreatic cancer organoid models, including bio-hydrogel, co-culture, microfluidic, and gene editing. Here, this work summarizes and analyzes the recent developments in engineering pancreatic tumor organoid models. In addition, the future direction of improving engineered pancreatic cancer organoids is discussed for their application prospects in clinical treatment.

Experimental models for cancer brain metastasis

Brain metastases are a leading cause of cancer-related mortality. However, progress in their treatment has been limited over the past decade, due to an incomplete understanding of the underlying biological mechanisms. Employing accurate in vitro and in vivo models to recapitulate the complexities of brain metastasis offers the most promising approach to unravel the intricate cellular and physiological processes involved. Here, we present a comprehensive review of the currently accessible models for studying brain metastasis. We introduce a diverse array of in vitro and in vivo models, including cultured cells using the Transwell system, organoids, microfluidic models, syngeneic models, xenograft models, and genetically engineered models. We have also provided a concise summary of the merits and limitations inherent to each model while identifying the optimal contexts for their effective utilization. This review serves as a comprehensive resource, aiding researchers in making well-informed decisions regarding model selection that align with specific research questions.

Quantification of cell death and proliferation of patient-derived ovarian cancer organoids through 3D imaging and image analysis

Patient-derived organoids (PDOs) are ideal ex vivo model systems to study cancer progression and drug resistance mechanisms. Here, we present a protocol for measuring drug efficacy in three-dimensional (3D) high-grade serous ovarian cancer PDO cultures through quantification of cytotoxicity using propidium iodide incorporation in dead cells. We also provide detailed steps to analyze proliferation of PDOs using the Ki67 biomarker. We describe steps for sample processing, immunofluorescent staining, high-throughput confocal imaging, and image-based quantification for 3D cultures. For complete details on the use and execution of this protocol, please refer to Lahtinen et al. (2023).1.

Trellis tree-based analysis reveals stromal regulation of patient-derived organoid drug responses

Patient-derived organoids (PDOs) can model personalized therapy responses; however, current screening technologies cannot reveal drug response mechanisms or how tumor microenvironment cells alter therapeutic performance. To address this, we developed a highly multiplexed mass cytometry platform to measure post-translational modification (PTM) signaling, DNA damage, cell-cycle activity, and apoptosis in >2,500 colorectal cancer (CRC) PDOs and cancer-associated fibroblasts (CAFs) in response to clinical therapies at single-cell resolution. To compare patient- and microenvironment-specific drug responses in thousands of single-cell datasets, we developed "Trellis"-a highly scalable, tree-based treatment effect analysis method. Trellis single-cell screening revealed that on-target cell-cycle blockage and DNA-damage drug effects are common, even in chemorefractory PDOs. However, drug-induced apoptosis is rarer, patient-specific, and aligns with cancer cell PTM signaling. We find that CAFs can regulate PDO plasticity-shifting proliferative colonic stem cells (proCSCs) to slow-cycling revival colonic stem cells (revCSCs) to protect cancer cells from chemotherapy.

An Integrative Bioorthogonal Nanoengineering Strategy for Dynamically Constructing Heterogenous Tumor Spheroids

Although tumor models have revolutionized perspectives on cancer aetiology and treatment, current cell culture methods remain challenges in constructing organotypic tumor with in vivo-like complexity, especially native characteristics, leading to unpredictable results for in vivo responses. Herein, the bioorthogonal nanoengineering strategy (BONE) for building photothermal dynamic tumor spheroids is developed. In this process, biosynthetic machinery incorporated bioorthogonal azide reporters into cell surface glycoconjugates, followed by reacting with multivalent click ligand (ClickRod) that is composed of hyaluronic acid-functionalized gold nanorod carrying dibenzocyclooctyne moieties, resulting in rapid construction of tumor spheroids. BONE can effectively assemble different cancer cells and immune cells together to construct heterogenous tumor spheroids is identified. Particularly, ClickRod exhibited favorable photothermal activity, which precisely promoted cell activity and shaped physiological microenvironment, leading to formation of dynamic features of original tumor, such as heterogeneous cell population and pluripotency, different maturation levels, and physiological gradients. Importantly, BONE not only offered a promising platform for investigating tumorigenesis and therapeutic response, but also improved establishment of subcutaneous xenograft model under mild photo-stimulation, thereby significantly advancing cancer research. Therefore, the first bioorthogonal nanoengineering strategy for developing dynamic tumor models, which have the potential for bridging gaps between in vitro and in vivo research is presented.

Sesamol serves as a p53 stabilizer to relieve rheumatoid arthritis progression and inhibits the growth of synovial organoids

BACKGROUND

Rheumatoid arthritis (RA) is an autoimmune disease known as a leading cause of disability with considerable mortality. Developing alternative drugs and targets for RA treatment is an urgent issue. Sesamol is a phenolic compound isolated from natural food sesame (Sesamum indicum L.) with various biological activities.

PURPOSE

The current research intended to illuminate the bioactivity and mechanisms of sesamol in RA fibroblast-like synoviocytes (FLS), and aimed to estimate the potential clinical application value of sesamol in RA treatment.

METHODS

CCK-8, EdU, and flow cytometry assays, as well as transwell tests were applied to observe the effects of sesamol on the abnormal functions of RA-FLS. Moreover, synovial organoids and a collagen-induced arthritis (CIA) mouse model were constructed to further explore the therapeutic capacity of sesamol on RA. Furthermore, RNA sequencing combined with quantitative real-time PCR assay, Western blot as well as co-immunoprecipitation were employed to clarify the mechanism of sesamol in regulating RA progression.

RESULTS

Sesamol suppressed the proliferation through inhibiting DNA replication, triggering cell cycle arrest and apoptosis of RA-FLS. Besides, sesamol impaired RA-FLS migration and invasion. Interestingly, sesamol inhibited the growth of constructed synovial organoids and alleviated RA symptoms in CIA mice. Moreover, RNA sequencing further implicated p53 signaling as a downstream pathway of sesamol. Furthermore, sesamol was shown to decrease p53 ubiquitination and degradation, thereby activating p53 signaling. Finally, bioinformatics analyses also highlighted the importance of sesamol-regulated networks in the progression of RA.

CONCLUSIONS

Our investigation demonstrated that sesamol served as a novel p53 stabilizer to attenuate the abnormal functions of RA-FLS via facilitating the activation of p53 signaling. Moreover, our study highlighted that sesamol might be an effective lead compound or candidate drug and p53 could be a promising target for the therapy of RA.

Tamoxifen induces ferroptosis in MCF-7 organoid

BACKGROUND

Breast cancer is the most common female malignant tumor type globally. The occurrence and development of breast cancer involve ferroptosis, which is closely related to its treatment. The development of breast cancer organoids facilitates the analysis of breast cancer molecular background and tumor biological behavior, including clinical pathological characteristics, drug response, or drug resistance relationship, and promotes the advancement of precision treatment for breast cancer. The three-dimensional (3D) cell culture of breast cancer MCF-7 organoid is more similar to the in vivo environment and thus obtains more realistic results than 2D cell culture. Our study examined the new mechanism of tamoxifen in treating breast cancer through breast cancer MCF-7 organoids.

METHODS

We used 3D cells to culture breast cancer MCF-7 organoid, as well as tamoxifen-treated MCF-7 and tamoxifen-resistant MCF-7 (MCF-7 TAMR) cells. We used transcriptome sequencing. We detected GPX4 and SLC7A11 protein levels using Western blotting and the content of ATP, glutathione, and ferrous ions using the Cell Counting Lite 3D Kit. We assessed cell viability using the Cell Counting Kit-8 (CCK-8) assay.

RESULTS

Tamoxifen significantly inhibited the growth of MCF-7 organoids and significantly induced ferroptosis in MCF-7 organoids. The ferroptosis inhibitor reversed the significant tamoxifen-induced MCF-7 organoid inhibition activity. Moreover, the ferroptosis activator enhanced the tamoxifen-induced MCF-7 TAMR cell activity inhibition.

CONCLUSION

Our study revealed that ferroptosis plays an important role in tamoxifen-induced MCF-7 organoid cell death and provides a new research idea for precise treatment of breast cancer through an organoid model.

3D bioprinted breast tumor-stroma models for pre-clinical drug testing

The use of three-dimensional (3D) bioprinting has been proposed for the reproducible production of 3D disease models that can be used for high-throughput drug testing and personalized medicine. However, most such models insufficiently reproduce the features and environment of real tumors. We report the development of bioprinted in vitro 3D tumor models for breast cancer, which physically and biochemically mimic important aspects of the native tumor microenvironment, designed to study therapeutic efficacy. By combining a mix of breast decellularized extracellular matrix and methacrylated hyaluronic acid with tumor-derived cells and non-cancerous stromal cells of biological relevance to breast cancer, we show that biological signaling pathways involved in tumor progression can be replicated in a carefully designed tumor-stroma environment. Finally, we demonstrate proof-of-concept application of these models as a reproducible platform for investigating therapeutic responses to commonly used chemotherapeutic agents.

The potential of patient-derived organoids in precision medicine of biliary tract cancer

Chemotherapy resistance in biliary tract cancer (BTC) presents a major clinical hurdle. Ren et al.1 developed and characterized an extensive collection of BTC patient-derived organoid (PDO) models, enabling advanced investigation of chemotherapy response prediction.

Personalized drug screening in patient-derived organoids of biliary tract cancer and its clinical application

Patients with biliary tract cancer (BTC) show different responses to chemotherapy, and there is no effective way to predict chemotherapeutic response. We have generated 61 BTC patient-derived organoids (PDOs) from 82 tumors (74.4%) that show similar histological and genetic characteristics to the corresponding primary BTC tissues. BTC tumor tissues with enhanced stemness- and proliferation-related gene expression by RNA sequencing can more easily form organoids. As expected, BTC PDOs show different responses to the chemotherapies of gemcitabine, cisplatin, 5-fluoruracil, oxaliplatin, etc. The drug screening results in PDOs are further validated in PDO-based xenografts and confirmed in 92.3% (12/13) of BTC patients with actual clinical response. Moreover, we have identified gene expression signatures of BTC PDOs with different drug responses and established gene expression panels to predict chemotherapy response in BTC patients. In conclusion, BTC PDO is a promising precision medicine tool for anti-cancer therapy in BTC patients.

Modeling Liver Development and Disease in a Dish

Historically, biological research has relied primarily on animal models. While this led to the understanding of numerous human biological processes, inherent species-specific differences make it difficult to answer certain liver-related developmental and disease-specific questions. The advent of 3D organoid models that are either derived from pluripotent stem cells or generated from healthy or diseased tissue-derived stem cells have made it possible to recapitulate the biological aspects of human organs. Organoid technology has been instrumental in understanding the disease mechanism and complements animal models. This review underscores the advances in organoid technology and specifically how liver organoids are used to better understand human-specific biological processes in development and disease. We also discuss advances made in the application of organoid models in drug screening and personalized medicine.

Antitumor effect of luteolin proven by patient-derived organoids of gastric cancer

Luteolin (Lut) has been shown to inhibit gastric cancer (GC); however, its efficacy compared to other clinical drugs has not been examined in human samples. This study aimed to elucidate the antitumor activity of Lut in GC patient-derived organoids (PDOs). PDOs were established from GC cancer tissues, and the characterization of tissues and PDOs was performed using whole-exome sequencing. Drug sensitivity tests were performed by treating PDOs with Lut, norcantharidin (NCTD), and carboplatin (CP). RNA sequencing of PDOs was performed to elucidate the antitumor mechanism of Lut, which was further verified in three GC cell lines. Eleven PDOs were successfully constructed, and were highly consistent with the pathophysiology and genetic changes in the corresponding tumors. The IC50s of Lut, NCTD, and CP of PDOs were 27.19, 23.9, and 37.87 μM, respectively. Lut treatment upregulated FOXO3, DUSP1, and CDKN1A expression and downregulated IL1R1 and FGFR4 expression in GC cell lines, which was consistent with the results of PDOs. We demonstrate that Lut exerted stronger antitumor effects than CP, but a similar effect to that of NCTD, which was obtained in an in vitro PDO system. Additionally, Lut exerted varying degrees of antitumor effects against the PDOs, thereby indicating that PDO may be a useful preclinical drug screening tool for personalized treatment.

A human mucosal melanoma organoid platform for modeling tumor heterogeneity and exploring immunotherapy combination options

Mucosal melanoma (MM), an aggressive rare subtype of melanoma, is distinct from cutaneous melanoma and has poor prognoses. We addressed the lack of cell models for MM by establishing 30 organoids of human oral MM (OMM), which retained major histopathological and functional features of parental tumors. Organoid groups derived from chronologically or intratumorally distinct lesions within the same individual displayed heterogeneous genetics, expression profiles, and drug responses, indicating rapid tumor evolution and poor clinical response. Furthermore, transcriptome analysis revealed receptor tyrosine kinases (RTKs) signaling, particularly NGFR, a nerve growth factor receptor, was significantly up-regulated in OMMs and organoids from patients resistant to anti-programmed cell death protein 1 (anti-PD-1) therapy. Combining anti-PD-1 with anlotinib (a phase 2 multitarget RTK inhibitor for OMM) or NGFR knockdown enhanced the effective activity of immune cells in organoid-immune cell coculture systems. Together, our study suggested that OMM organoids serve as faithful models for exploring tumor evolution and immunotherapy combination strategies.

Embedded Bioprinting of Breast Tumor Cells and Organoids Using Low-Concentration Collagen-Based Bioinks

Bioinks for 3D bioprinting of tumor models should not only meet printability requirements but also accurately maintain and support phenotypes of tumor surrounding cells to recapitulate key tumor hallmarks. Collagen is a major extracellular matrix protein for solid tumors, but low viscosity of collagen solution has made 3D bioprinted cancer models challenging. This work produces embedded, bioprinted breast cancer cells and tumor organoid models using low-concentration collagen I based bioinks. The biocompatible and physically crosslinked silk fibroin hydrogel is used to generate the support bath for the embedded 3D printing. The composition of the collagen I based bioink is optimized with a thermoresponsive hyaluronic acid-based polymer to maintain the phenotypes of both the noninvasive epithelial and invasive breast cancer cells, as well as cancer-associated fibroblasts. Mouse breast tumor organoids are bioprinted using optimized collagen bioink to mimic in vivo tumor morphology. A vascularized tumor model is also created using a similar strategy, with significantly enhanced vasculature formation under hypoxia. This study shows the great potential of embedded bioprinted breast tumor models utilizing a low-concentration collagen-based bioink for advancing the understanding of tumor cell biology and facilitating drug discovery research.

Exploring Tumor-Immune Interactions in Co-Culture Models of T Cells and Tumor Organoids Derived from Patients

The use of patient-derived tumor tissues and cells has led to significant advances in personalized cancer therapy and precision medicine. The advent of genomic sequencing technologies has enabled the comprehensive analysis of tumor characteristics. The three-dimensional tumor organoids derived from self-organizing cancer stem cells are valuable ex vivo models that faithfully replicate the structure, unique features, and genetic characteristics of tumors. These tumor organoids have emerged as innovative tools that are extensively employed in drug testing, genome editing, and transplantation to guide personalized therapy in clinical settings. However, a major limitation of this emerging technology is the absence of a tumor microenvironment that includes immune and stromal cells. The therapeutic efficacy of immune checkpoint inhibitors has underscored the importance of immune cells, particularly cytotoxic T cells that infiltrate the vicinity of tumors, in patient prognosis. To address this limitation, co-culture techniques combining tumor organoids and T cells have been developed, offering diverse avenues for studying individualized drug responsiveness. By integrating cellular components of the tumor microenvironment, including T cells, into tumor organoid cultures, immuno-oncology has embraced this technology, which is rapidly advancing. Recent progress in co-culture models of tumor organoids has allowed for a better understanding of the advantages and limitations of this novel model, thereby exploring its full potential. This review focuses on the current applications of organoid-T cell co-culture models in cancer research and highlights the remaining challenges that need to be addressed for its broader implementation in anti-cancer therapy.

The TRIPLEX study: use of patient-derived tumor organoids as an innovative tool for precision medicine in triple-negative breast cancer

BACKGROUND

Triple negative breast cancers (TNBC) account for approximately 15% of all breast cancers and are associated with a shorter median survival mainly due to locally advanced tumor and high risk of metastasis. The current neoadjuvant treatment for TNBC consists of a regimen of immune checkpoint blocker and chemotherapy (chemo-ICB). Despite the frequent use of this combination for TNBC treatment, moderate results are observed and its clinical benefit in TNBC remains difficult to predict. Patient-derived tumor organoids (PDTO) are 3D in vitro cellular structures obtained from patient's tumor samples. More and more evidence suggest that these models could predict the response of the tumor from which they are derived. PDTO may thus be used as a tool to predict chemo-ICB efficacy in TNBC patients.

METHOD

The TRIPLEX study is a single-center observational study conducted to investigate the feasibility of generating PDTO from TNBC and to evaluate their ability to predict clinical response. PDTO will be obtained after the dissociation of biopsies and embedding into extra cellular matrix. PDTO will be cultured in a medium supplemented with growth factors and signal pathway inhibitors. Molecular and histological analyses will be performed on established PDTO lines to validate their phenotypic proximity with the original tumor. Response of PDTO to chemo-ICB will be assessed using co-cultures with autologous immune cells collected from patient blood samples. PDTO response will finally be compared with the response of the patient to evaluate the predictive potential of the model.

DISCUSSION

This study will allow to assess the feasibility of using PDTO as predictive tools for the evaluation of the response of TNBC patients to treatments. In the event that PDTO could faithfully predict patient response in clinically relevant time frames, a prospective clinical trial could be designed to use PDTO to guide clinical decision. This study will also permit the establishment of a living biobank of TNBC PDTO usable for future innovative strategies evaluation.

TRIAL REGISTRATION

The clinical trial (version 1.2) has been validated by local research ethic committee on December 30th 2021 and registered at ClinicalTrials.gov with the identifier NCT05404321 on June 3rd 2022, version 1.2.

Global cluster analysis and network visualization in organoids in cancer research: a scientometric mapping from 1991 to 2021

Objective

In the last three decades, there has been a surge in research on cancer organoids using 3D culture technologies, which has resulted in the development of physiological human cancer models. This study aims to provide an overview of the global trends and frontiers in research on cancer organoids.

Methods

A total of 3189 publications on organoids in cancer research from 1991 to 2021 were collected from the Science Citation Index-Expanded (SCIE) of Web of Science (WoS). Bibliometric methods such as the R package "Bibliometrix," Citespace, and VOS viewer software were employed to investigate and visualize bibliographic coupling, co-citation, co-authorship, and co-occurrence trends, as well as publication trends in the field of organoids in cancer research.

Results

From 1991 to 2021, there has been a significant increase in publications on cancer organoids, with most articles being from North America, Eastern Asia, and Western Europe. The USA had the highest number of publications, citations, prolific authors, and research funding globally. Cancers was the journal with the most publications, while Nature had the best total link strength. Harvard University were the most contributive institutions. The global research in this field could be classified into five clusters: chemotherapy study, organoids for drug screening, different models, molecular mechanism study, and organoid construction. These areas are expected to remain hotspots for future research.

Conclusions

The number of publications on organoids in cancer research is expected to increase based on current global trends.

Medical gas plasma technology: Roadmap on cancer treatment and immunotherapy

Despite continuous therapeutic progress, cancer remains an often fatal disease. In the early 2010s, first evidence in rodent models suggested promising antitumor action of gas plasma technology. Medical gas plasma is a partially ionized gas depositing multiple physico-chemical effectors onto tissues, especially reactive oxygen and nitrogen species (ROS/RNS). Today, an evergrowing body of experimental evidence suggests multifaceted roles of medical gas plasma-derived therapeutic ROS/RNS in targeting cancer alone or in combination with oncological treatment schemes such as ionizing radiation, chemotherapy, and immunotherapy. Intriguingly, gas plasma technology was recently unraveled to have an immunological dimension by inducing immunogenic cell death, which could ultimately promote existing cancer immunotherapies via in situ or autologous tumor vaccine schemes. Together with first clinical evidence reporting beneficial effects in cancer patients following gas plasma therapy, it is time to summarize the main concepts along with the chances and limitations of medical gas plasma onco-therapy from a biological, immunological, clinical, and technological point of view.

Flourishing tumor organoids: History, emerging technology, and application

Malignant tumors are one of the leading causes of death which impose an increasingly heavy burden on all countries. Therefore, the establishment of research models that closely resemble original tumor characteristics is crucial to further understanding the mechanisms of malignant tumor development, developing safer and more effective drugs, and formulating personalized treatment plans. Recently, organoids have been widely used in tumor research owing to their advantages including preserving the structure, heterogeneity, and cellular functions of the original tumor, together with the ease of manipulation. This review describes the history and characteristics of tumor organoids and the synergistic combination of three-dimensional (3D) culture approaches for tumor organoids with emerging technologies, including tissue-engineered cell scaffolds, microfluidic devices, 3D bioprinting, rotating wall vessels, and clustered regularly interspaced short palindromic repeats-CRISPR-associated protein 9 (CRISPR-Cas9). Additionally, the progress in research and the applications in basic and clinical research of tumor organoid models are summarized. This includes studies of the mechanism of tumor development, drug development and screening, precision medicine, immunotherapy, and simulation of the tumor microenvironment. Finally, the existing shortcomings of tumor organoids and possible future directions are discussed.

Nanoparticle-Based Combination Therapy Enhances Fulvestrant Efficacy and Overcomes Tumor Resistance in ER-Positive Breast Cancer

Nanoparticles (NP) spanning diverse materials and properties have the potential to encapsulate and to protect a wide range of therapeutic cargos to increase bioavailability, to prevent undesired degradation, and to mitigate toxicity. Fulvestrant, a selective estrogen receptor degrader, is commonly used for treating patients with estrogen receptor (ER)-positive breast cancer, but its broad and continual application is limited by poor solubility, invasive muscle administration, and drug resistance. Here, we developed an active targeting motif-modified, intravenously injectable, hydrophilic NP that encapsulates fulvestrant to facilitate its delivery via the bloodstream to tumors, improving bioavailability and systemic tolerability. In addition, the NP was coloaded with abemaciclib, an inhibitor of cyclin-dependent kinases 4 and 6 (CDK4/6), to prevent the development of drug resistance associated with long-term fulvestrant treatment. Targeting peptide modifications on the NP surface assisted in the site-specific release of the drugs to ensure specific toxicity in the tumor tissues and to spare normal tissue. The NP formulation (PPFA-cRGD) exhibited efficient tumor cell killing in both in vitro organoid models and in vivo orthotopic ER-positive breast cancer models without apparent adverse effects, as verified in mouse and Bama miniature pig models. This NP-based therapeutic provides an opportunity for continual and extensive clinical application of fulvestrant, thus indicating its promise as a treatment option for patients with ER-positive breast cancer.

SIGNIFICANCE

A smart nanomedicine encapsulating fulvestrant to improve its half-life, bioavailability, and tumor-targeting and coloaded with CDK4/6 inhibitor abemaciclib to block resistance is a safe and effective therapy for ER-positive breast cancer.

Patient-Derived Ex Vivo Cultures and Endpoint Assays with Surrogate Biomarkers in Functional Testing for Prediction of Therapeutic Response

Prediction of therapeutic outcomes is important for cancer patients in order to reduce side effects and improve the efficacy of anti-cancer drugs. Currently, the most widely accepted method for predicting the efficacy of anti-cancer drugs is gene panel testing based on next-generation sequencing. However, gene panel testing has several limitations. For example, only 10% of cancer patients are estimated to have druggable mutations, even if whole-exome sequencing is applied. Additionally, even if optimal drugs are selected, a significant proportion of patients derive no benefit from the indicated drug treatment. Furthermore, most of the anti-cancer drugs selected by gene panel testing are molecularly targeted drugs, and the efficacies of cytotoxic drugs remain difficult to predict. Apart from gene panel testing, attempts to predict chemotherapeutic efficacy using ex vivo cultures from cancer patients have been increasing. Several groups have retrospectively demonstrated correlations between ex vivo drug sensitivity and clinical outcome. For ex vivo culture, surgically resected tumor tissue is the most abundant source. However, patients with recurrent or metastatic tumors do not usually undergo surgery, and chemotherapy may be the only option for those with inoperable tumors. Therefore, predictive methods using small amounts of cancer tissue from diagnostic materials such as endoscopic, fine-needle aspirates, needle cores and liquid biopsies are needed. To achieve this, various types of ex vivo culture and endpoint assays using effective surrogate biomarkers of drug sensitivity have recently been developed. Here, we review the variety of ex vivo cultures and endpoint assays currently available.

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.

Tumor organoid model of colorectal cancer (Review)

The establishment of self-organizing 'mini-gut' organoid models has brought about a significant breakthrough in biomedical research. Patient-derived tumor organoids have emerged as valuable tools for preclinical studies, offering the retention of genetic and phenotypic characteristics of the original tumor. These organoids have applications in various research areas, including in vitro modelling, drug discovery and personalized medicine. The present review provided an overview of intestinal organoids, focusing on their unique characteristics and current understanding. The progress made in colorectal cancer (CRC) organoid models was then delved into, discussing their role in drug development and personalized medicine. For instance, it has been indicated that patient-derived tumor organoids are able to predict response to irinotecan-based neoadjuvant chemoradiotherapy. Furthermore, the limitations and challenges associated with current CRC organoid models were addressed, along with proposed strategies for enhancing their utility in future basic and translational research.

Organoids: opportunities and challenges of cancer therapy

Organoids are a class of multicellular structures with the capability of self-organizing and the characteristic of original tissues, they are generated from stem cells in 3D culture in vitro. Organoids can mimic the occurrence and progression of original tissues and widely used in disease models in recent years. The ability of tumor organoids to retain characteristic of original tumors make them unique for tumorigenesis and cancer therapy. However, the history of organoid development and the application of organoid technology in cancer therapy are not well understood. In this paper, we reviewed the history of organoids development, the culture methods of tumor organoids establishing and the applications of organoids in cancer research for better understanding the process of tumor development and providing better strategies for cancer therapy. The standardization of organoids cultivation facilitated the large-scale production of tumor organoids. Moreover, it was found that combination of tumor organoids and other cells such as immune cells, fibroblasts and nervous cells would better mimic the microenvironment of tumor progression. This might be important developing directions for tumor organoids in the future.

Pharmaco-proteogenomic characterization of liver cancer organoids for precision oncology

Organoid models have the potential to recapitulate the biological and pharmacotypic features of parental tumors. Nevertheless, integrative pharmaco-proteogenomics analysis for drug response features and biomarker investigation for precision therapy of patients with liver cancer are still lacking. We established a patient-derived liver cancer organoid biobank (LICOB) that comprehensively represents the histological and molecular characteristics of various liver cancer types as determined by multiomics profiling, including genomic, epigenomic, transcriptomic, and proteomic analysis. Proteogenomic profiling of LICOB identified proliferative and metabolic organoid subtypes linked to patient prognosis. High-throughput drug screening revealed distinct response patterns of each subtype that were associated with specific multiomics signatures. Through integrative analyses of LICOB pharmaco-proteogenomics data, we identified the molecular features associated with drug responses and predicted potential drug combinations for personalized patient treatment. The synergistic inhibition effect of mTOR inhibitor temsirolimus and the multitargeted tyrosine kinase inhibitor lenvatinib was validated in organoids and patient-derived xenografts models. We also provide a user-friendly web portal to help serve the biomedical research community. Our study is a rich resource for investigation of liver cancer biology and pharmacological dependencies and may help enable functional precision medicine.

Glioblastoma modeling with 3D organoids: progress and challenges

Glioblastoma (GBM) is the most aggressive adult primary brain tumor with nearly universal treatment resistance and recurrence. The mainstay of therapy remains maximal safe surgical resection followed by concurrent radiation therapy and temozolomide chemotherapy. Despite intensive investigation, alternative treatment options, such as immunotherapy or targeted molecular therapy, have yielded limited success to achieve long-term remission. This difficulty is partly due to the lack of pre-clinical models that fully recapitulate the intratumoral and intertumoral heterogeneity of GBM and the complex tumor microenvironment. Recently, GBM 3D organoids originating from resected patient tumors, genetic manipulation of induced pluripotent stem cell (iPSC)-derived brain organoids and bio-printing or fusion with non-malignant tissues have emerged as novel culture systems to portray the biology of GBM. Here, we highlight several methodologies for generating GBM organoids and discuss insights gained using such organoid models compared to classic modeling approaches using cell lines and xenografts. We also outline limitations of current GBM 3D organoids, most notably the difficulty retaining the tumor microenvironment, and discuss current efforts for improvements. Finally, we propose potential applications of organoid models for a deeper mechanistic understanding of GBM and therapeutic development.

3D Biomimetic Models to Reconstitute Tumor Microenvironment In Vitro: Spheroids, Organoids, and Tumor-on-a-Chip

Decades of efforts in engineering in vitro cancer models have advanced drug discovery and the insight into cancer biology. However, the establishment of preclinical models that enable fully recapitulating the tumor microenvironment remains challenging owing to its intrinsic complexity. Recent progress in engineering techniques has allowed the development of a new generation of in vitro preclinical models that can recreate complex in vivo tumor microenvironments and accurately predict drug responses, including spheroids, organoids, and tumor-on-a-chip. These biomimetic 3D tumor models are of particular interest as they pave the way for better understanding of cancer biology and accelerating the development of new anticancer therapeutics with reducing animal use. Here, the recent advances in developing these in vitro platforms for cancer modeling and preclinical drug screening, focusing on incorporating hydrogels are reviewed to reconstitute physiologically relevant microenvironments. The combination of spheroids/organoids with microfluidic technologies is also highlighted to better mimic in vivo tumors and discuss the challenges and future directions in the clinical translation of such models for drug screening and personalized medicine.

In Vitro and In Vivo Drug-Response Profiling Using Patient-Derived High-Grade Glioma

BACKGROUND

Genomic profiling cannot solely predict the complexity of how tumor cells behave in their in vivo microenvironment and their susceptibility to therapies. The aim of the study was to establish a functional drug prediction model utilizing patient-derived GBM tumor samples for in vitro testing of drug efficacy followed by in vivo validation to overcome the disadvantages of a strict pharmacogenomics approach.

METHODS

High-throughput in vitro pharmacologic testing of patient-derived GBM tumors cultured as 3D organoids offered a cost-effective, clinically and phenotypically relevant model, inclusive of tumor plasticity and stroma. RNAseq analysis supplemented this 128-compound screening to predict more efficacious and patient-specific drug combinations with additional tumor stemness evaluated using flow cytometry. In vivo PDX mouse models rapidly validated (50 days) and determined mutational influence alongside of drug efficacy. We present a representative GBM case of three tumors resected at initial presentation, at first recurrence without any treatment, and at a second recurrence following radiation and chemotherapy, all from the same patient.

RESULTS

Molecular and in vitro screening helped identify effective drug targets against several pathways as well as synergistic drug combinations of cobimetinib and vemurafenib for this patient, supported in part by in vivo tumor growth assessment. Each tumor iteration showed significantly varying stemness and drug resistance.

CONCLUSIONS

Our integrative model utilizing molecular, in vitro, and in vivo approaches provides direct evidence of a patient's tumor response drifting with treatment and time, as demonstrated by dynamic changes in their tumor profile, which may affect how one would address that drift pharmacologically.

Patient-derived tumor organoids with p53 mutations, and not wild-type p53, are sensitive to synergistic combination PARP inhibitor treatment

Poly (ADP-ribose) polymerase inhibitors (PARPi) are used for patients with BRCA1/2 mutations, but patients with other mutations may benefit from PARPi treatment. Another mutation that is present in more cancers than BRCA1/2 is mutation to the TP53 gene. In 2D breast cancer cell lines, mutant p53 (mtp53) proteins tightly associate with replicating DNA and Poly (ADP-ribose) polymerase (PARP) protein. Combination drug treatment with the alkylating agent temozolomide and the PARPi talazoparib kills mtp53 expressing 2D grown breast cancer cell lines. We evaluated the sensitivity to the combination of temozolomide plus PARPi talazoparib treatment to breast and lung cancer patient-derived tumor organoids (PDTOs). The combination of the two drugs was synergistic for a cytotoxic response in PDTOs with mtp53 but not for PDTOs with wtp53. The combination of talazoparib and temozolomide induced more DNA double-strand breaks in mtp53 expressing organoids than in wild-type p53 expressing organoids as shown by increased γ-H2AX protein expression. Moreover, breast cancer tissue microarrays (TMAs) showed a positive correlation between stable p53 and high PARP1 expression in sub-groups of breast cancers, which may indicate sub-classes of breast cancers sensitive to PARPi therapy. These results suggest that mtp53 could be a biomarker to predict response to the combination of PARPi talazoparib-temozolomide treatment.

Drug screening at single-organoid resolution via bioprinting and interferometry

High throughput drug screening is an established approach to investigate tumor biology and identify therapeutic leads. Traditional platforms use two-dimensional cultures which do not accurately reflect the biology of human tumors. More clinically relevant model systems such as three-dimensional tumor organoids can be difficult to scale and screen. Manually seeded organoids coupled to destructive endpoint assays allow for the characterization of treatment response, but do not capture transitory changes and intra-sample heterogeneity underlying clinically observed resistance to therapy. We present a pipeline to generate bioprinted tumor organoids linked to label-free, time-resolved imaging via high-speed live cell interferometry (HSLCI) and machine learning-based quantitation of individual organoids. Bioprinting cells gives rise to 3D structures with unaltered tumor histology and gene expression profiles. HSLCI imaging in tandem with machine learning-based segmentation and classification tools enables accurate, label-free parallel mass measurements for thousands of organoids. We demonstrate that this strategy identifies organoids transiently or persistently sensitive or resistant to specific therapies, information that could be used to guide rapid therapy selection.

Viability Analysis and High-Content Live-Cell Imaging for Drug Testing in Prostate Cancer Xenograft-Derived Organoids

Tumor organoids have been pushed forward as advanced model systems for in vitro oncology drug testing, with the eventual goal to direct personalized cancer treatments. However, drug testing efforts suffer from a large variation in experimental conditions for organoid culturing and organoid treatment. Moreover, most drug tests are restricted to whole-well viability as the sole read-out, thereby losing important information about key biological aspects that might be impacted due to the use of administered drugs. These bulk read-outs also discard potential inter-organoid heterogeneity in drug responses. To tackle these issues, we developed a systematic approach for processing organoids from prostate cancer (PCa) patient-derived xenografts (PDXs) for viability-based drug testing and identified essential conditions and quality checks for consistent results. In addition, we generated an imaging-based drug testing procedure using high-content fluorescence microscopy in living PCa organoids to detect various modalities of cell death. Individual organoids and cell nuclei in organoids were segmented and quantified using a dye combination of Hoechst 33342, propidium iodide and Caspase 3/7 Green, allowing the identification of cytostatic and cytotoxic treatment effects. Our procedures provide important insights into the mechanistic actions of tested drugs. Moreover, these methods can be adapted for tumor organoids originating from other cancer types to increase organoid-based drug test validity, and ultimately, accelerate clinical implementation.

A platform for efficient establishment and drug-response profiling of high-grade serous ovarian cancer organoids

The broad research use of organoids from high-grade serous ovarian cancer (HGSC) has been hampered by low culture success rates and limited availability of fresh tumor material. Here, we describe a method for generation and long-term expansion of HGSC organoids with efficacy markedly improved over previous reports (53% vs. 23%-38%). We established organoids from cryopreserved material, demonstrating the feasibility of using viably biobanked tissue for HGSC organoid derivation. Genomic, histologic, and single-cell transcriptomic analyses revealed that organoids recapitulated genetic and phenotypic features of original tumors. Organoid drug responses correlated with clinical treatment outcomes, although in a culture conditions-dependent manner and only in organoids maintained in human plasma-like medium (HPLM). Organoids from consenting patients are available to the research community through a public biobank and organoid genomic data are explorable through an interactive online tool. Taken together, this resource facilitates the application of HGSC organoids in basic and translational ovarian cancer research.

Novel organoid construction strategy for non-involuting congenital hemangioma for drug validation

BACKGROUND

Non-involuting congenital hemangiomas (NICHs) are fully formed vascular tumors at birth with distinctive clinical, radiologic, and histopathological profiles. In the literature, there is no effective therapy strategy for patients with NICH except surgery. Currently, no cell line or animal model exists for studying the mechanism of NICH and drug validation. We plan to construct a new strategy by constructing NICH organoids for further study.

RESULT

Here, we report a novel NICH organoid system construction and optimization process. Both HE and immunohistological staining exactly matched NICH tissue. We further performed transcriptome analysis to elucidate the characteristics of NICH organoids. Both NICH tissue and NICH organoids manifested similar trends in download sites. NICH organoids display novel features to new cells derived from organoids and show spectacular multiplication capacity. In the preliminary verification, we found that cells splitting from NICH organoids were human endothelial cells. Drug validation demonstrated that trametinib, sirolimus, and propranolol showed no inhibitory effects on NICH organoids.

CONCLUSION

Our data show that this new NICH-derived organoid faithfully captured the features of this rare vascular tumor. Our study will boost further research on the mechanism of NICH and drug filtering in the future.

Patient-derived organoid culture of gastric cancer for disease modeling and drug sensitivity testing

BACKGROUND

Gastric cancer treatment is complicated by the molecular heterogeneity of human tumor cells, which limits the efficacy of standard therapy and necessitates the need for personalized treatment development. Patient-derived organoids (PDOs) are promising preclinical cancer models, exhibiting high clinical efficacy in predicting drug sensitivity, thus providing a new means for personalized precision medicine.

METHODS

PDOs were established from surgically resected gastric cancer tumor tissues. Molecular characterization of the tumor tissues and PDOs was performed using whole-exome sequencing analysis. Drug sensitivity tests were performed by treating the PDO cultures with 21 standard-of-care drugs corresponding to patient treatment. We evaluated whether the PDO drug phenotype reflects the corresponding patient's treatment response by comparing the drug sensitivity test results with clinical data.

RESULTS

Twelve PDOs that satisfied the drug sensitivity test criteria were successfully constructed. PDOs closely recapitulated the pathophysiology and genetic changes in the corresponding tumors, and exhibited different sensitivities to the tested drugs. In one clinical case study, the PDO accurately predicted the patient's sensitivity to capecitabine and oxaliplatin, and in a second case study the PDO successfully predicted the patient's insensitivity to S-1 chemotherapy. In summary, six of the eight cases exhibited consistency between PDO drug susceptibility test results and the clinical response of the matched patient.

CONCLUSIONS

PDO drug sensitivity tests can predict the clinical response of patients with gastric cancer to drugs, and PDOs can therefore be used as a preclinical platform to guide the development of personalized cancer treatment.

Metastasis

Most cancer-associated deaths occur due to metastasis, yet our understanding of metastasis as an evolving, heterogeneous, systemic disease and of how to effectively treat it is still emerging. Metastasis requires the acquisition of a succession of traits to disseminate, variably enter and exit dormancy, and colonize distant organs. The success of these events is driven by clonal selection, the potential of metastatic cells to dynamically transition into distinct states, and their ability to co-opt the immune environment. Here, we review the main principles of metastasis and highlight emerging opportunities to develop more effective therapies for metastatic cancer.

3D cancer models: One step closer to in vitro human studies

Cancer immunotherapy is the great breakthrough in cancer treatment as it displayed prolonged progression-free survival over conventional therapies, yet, to date, in only a minority of patients. In order to broad cancer immunotherapy clinical applicability some roadblocks need to be overcome, first among all the lack of preclinical models that faithfully depict the local tumor microenvironment (TME), which is known to dramatically affect disease onset, progression and response to therapy. In this review, we provide the reader with a detailed overview of current 3D models developed to mimick the complexity and the dynamics of the TME, with a focus on understanding why the TME is a major target in anticancer therapy. We highlight the advantages and translational potentials of tumor spheroids, organoids and immune Tumor-on-a-Chip models in disease modeling and therapeutic response, while outlining pending challenges and limitations. Thinking forward, we focus on the possibility to integrate the know-hows of micro-engineers, cancer immunologists, pharmaceutical researchers and bioinformaticians to meet the needs of cancer researchers and clinicians interested in using these platforms with high fidelity for patient-tailored disease modeling and drug discovery.

piTracer - Automatic reconstruction of molecular cascades for the identification of synergistic drug targets

Cancer cells frequently undergo metabolic reprogramming as a mechanism of resistance against chemotherapeutic drugs. Metabolomic profiling provides a direct readout of metabolic changes and can thus be used to identify these tumor escape mechanisms. Here, we introduce piTracer, a computational tool that uses multi-scale molecular networks to identify potential combination therapies from pre- and post-treatment metabolomics data. We first demonstrate piTracer’s core ability to reconstruct cellular cascades by inspecting well-characterized molecular pathways and previously studied associations between genetic variants and metabolite levels. We then apply a new gene ranking algorithm on differential metabolomic profiles from human breast cancer cells after glutaminase inhibition. Four of the automatically identified gene targets were experimentally tested by simultaneous inhibition of the respective targets and glutaminase. Of these combination treatments, two were be confirmed to induce synthetic lethality in the cell line. In summary, piTracer integrates the molecular monitoring of escape mechanisms into comprehensive pathway networks to accelerate drug target identification. The tool is open source and can be accessed at https://github.com/krumsieklab/pitracer .

From organoids to bedside: Advances in modeling, decoding and targeting of colorectal cancer

Patient derived organoids closely resemble the biology of tissues and tumors. They are enabling ex vivo modeling of human diseases and dissecting key features of tumor biology like anatomical diversity or inter- and intra-tumoral heterogeneity. In the last years, organoids were established as models for drug discovery and explored to guide clinical decision making. In this review, we discuss the recent developments in organoid based research, elaborating on the developments in colorectal cancer as a prime example. We focus our review on the role of organoids to decode cancer cell dynamics and tumor microenvironmental complexity with the underlying bi-directional crosstalk. Additionally, advancements in the development of living biobanks, screening approaches, organoid based precision medicine and challenges of co-clinical trials are highlighted. We discuss ongoing efforts to overcome challenges that the field faces and indicate potential future directions.

Tissue-engineered models of lung cancer premalignancy

Lung cancer is the leading global cause of cancer-related deaths. Although smoking cessation is the best preventive action, nearly 50% of all lung cancer diagnoses occur in people who have already quit smoking. Research into treatment options for these high-risk patients has been constrained to rodent models of chemical carcinogenesis, which are time-consuming, expensive, and require large numbers of animals. Here we show that embedding precision-cut lung slices within an engineered hydrogel and exposing this tissue to a carcinogen from cigarette smoke creates an in vitro model of lung cancer premalignancy. Hydrogel formulations were selected to promote early lung cancer cellular phenotypes and extend PCLS viability up to six weeks. In this study, hydrogel-embedded lung slices were exposed to the cigarette smoke derived carcinogen vinyl carbamate, which induces adenocarcinoma in mice. At six weeks, analysis of proliferation, gene expression, histology, tissue stiffness, and cellular content revealed that vinyl carbamate induced the formation of premalignant lesions with a mixed adenoma/squamous phenotype. Two putative chemoprevention agents were able to freely diffuse through the hydrogel and induce tissue-level changes. The design parameters selected using murine tissue were validated with hydrogel-embedded human PCLS and results showed increased proliferation and premalignant lesion gene expression patterns. This tissue-engineered model of human lung cancer premalignancy is the starting point for more sophisticated ex vivo models and a foundation for the study of carcinogenesis and chemoprevention strategies.

Functional precision oncology using patient-derived assays: bridging genotype and phenotype

Genomics-based precision medicine has revolutionized oncology but also has inherent limitations. Functional precision oncology is emerging as a complementary approach that aims to bridge the gap between genotype and phenotype by modelling individual tumours in vitro. These patient-derived ex vivo models largely preserve several tumour characteristics that are not captured by genomics approaches and enable the functional dissection of tumour vulnerabilities in a personalized manner. In this Review, we discuss several examples of personalized functional assays involving tumour organoids, spheroids and explants and their potential to predict treatment responses and drug-induced toxicities in individual patients. These developments have opened exciting new avenues for precision oncology, with the potential for successful clinical applications in contexts in which genomic data alone are not informative. To implement these assays into clinical practice, we outline four key barriers that need to be overcome: assay success rates, turnaround times, the need for standardized conditions and the definition of in vitro responders. Furthermore, we discuss novel technological advances such as microfluidics that might reduce sample requirements, assay times and labour intensity and thereby enable functional precision oncology to be implemented in routine clinical practice.

Human Bone Marrow Organoids for Disease Modeling, Discovery, and Validation of Therapeutic Targets in Hematologic Malignancies

A lack of models that recapitulate the complexity of human bone marrow has hampered mechanistic studies of normal and malignant hematopoiesis and the validation of novel therapies. Here, we describe a step-wise, directed-differentiation protocol in which organoids are generated from induced pluripotent stem cells committed to mesenchymal, endothelial, and hematopoietic lineages. These 3D structures capture key features of human bone marrow-stroma, lumen-forming sinusoids, and myeloid cells including proplatelet-forming megakaryocytes. The organoids supported the engraftment and survival of cells from patients with blood malignancies, including cancer types notoriously difficult to maintain ex vivo. Fibrosis of the organoid occurred following TGFβ stimulation and engraftment with myelofibrosis but not healthy donor-derived cells, validating this platform as a powerful tool for studies of malignant cells and their interactions within a human bone marrow-like milieu. This enabling technology is likely to accelerate the discovery and prioritization of novel targets for bone marrow disorders and blood cancers.

SIGNIFICANCE

We present a human bone marrow organoid that supports the growth of primary cells from patients with myeloid and lymphoid blood cancers. This model allows for mechanistic studies of blood cancers in the context of their microenvironment and provides a much-needed ex vivo tool for the prioritization of new therapeutics. See related commentary by Derecka and Crispino, p. 263. This article is highlighted in the In This Issue feature, p. 247.

Artificial intelligence aids in development of nanomedicines for cancer management

Over the last decade, the nanomedicine has experienced unprecedented development in diagnosis and management of diseases. A number of nanomedicines have been approved in clinical use, which has demonstrated the potential value of clinical transition of nanotechnology-modified medicines from bench to bedside. The application of artificial intelligence (AI) in development of nanotechnology-based products could transform the healthcare sector by realizing acquisition and analysis of large datasets, and tailoring precision nanomedicines for cancer management. AI-enabled nanotechnology could improve the accuracy of molecular profiling and early diagnosis of patients, and optimize the design pipeline of nanomedicines by tuning the properties of nanomedicines, achieving effective drug synergy, and decreasing the nanotoxicity, thereby, enhancing the targetability, personalized dosing and treatment potency of nanomedicines. Herein, the advances in AI-enabled nanomedicines in cancer management are elaborated and their application in diagnosis, monitoring and therapy as well in precision medicine development is discussed.