Rapid tissue prototyping with micro-organospheres

Emerging artificial intelligence-driven precision therapies in tumor drug resistance: recent advances, opportunities, and challenges

Drug resistance is one of the main reasons for cancer treatment failure, leading to a rapid recurrence/disease progression of the cancer. Recently, artificial intelligence (AI) has empowered physicians to use its powerful data processing and pattern recognition capabilities to extract and mine valuable drug resistance information from large amounts of clinical or omics data, to study drug resistance mechanisms, to evaluate and predict drug resistance, and to develop innovative therapeutic strategies to reduce drug resistance. In this review, we proposed a feasible workflow for incorporating AI into tumor drug resistance research, highlighted current AI-driven tumor drug resistance applications, and discussed the opportunities and challenges encountered in the process. Based on a comprehensive literature analysis, we systematically summarized the role of AI in tumor drug resistance research, including drug development, resistance mechanism elucidation, drug sensitivity prediction, combination therapy optimization, resistance phenotype identification, and clinical biomarker discovery. With the continuous advancement of AI technology and rigorous validation of clinical data, AI models are expected to fuel the development of precision oncology by improving efficacy, guiding therapeutic decisions, and optimizing patient prognosis. In summary, by leveraging clinical and omics data, AI models are expected to pioneer new therapy strategies to mitigate tumor drug resistance, improve efficacy and patient survival, and provide novel perspectives and tools for oncology treatment.

Opportunities of patient-derived organoids in drug development

Various model systems are utilised during drug development starting from basic research, moving to preclinical research and development for clinical applications in order to identify new drugs to improve human health. However, there are characteristics of humans that are not captured by established models. Such models include homogeneous two-dimensional (2D) cell lines, which lack cellular heterogeneity and physiological relevance, and species differences of animal models. Organoids can mitigate these differences by providing more physiologically relevant three-dimensional (3D) cell models that resemble the molecular state in healthy and pathological tissue. This review presents exemplary approaches using patient-derived organoids (PDOs) that have been developed and the new opportunities that are evolving in drug development with a focus on patient adult stem cell (ASC)-derived organoids. These demonstrate the potential of PDOs used alongside established cell and animal models to improve drug development from basic research to clinical applications such as personalised medicine.

Cancer Organoids as reliable disease models to drive clinical development of novel therapies

On September 23-24 (2024) the 6th Workshop IRE on Translational Oncology, titled "Cancer Organoids as Reliable Disease Models to Drive Clinical Development of Novel Therapies," took place at the IRCCS Regina Elena Cancer Institute in Rome. This prominent international conference focused on tumor organoids, bringing together leading experts from around the world.A central challenge in precision oncology is modeling the dynamic tumor ecosystem, which encompasses numerous elements that evolve spatially and temporally. Patient-derived 3D culture models, including organoids, explants, and engineered or bioprinted systems, have recently emerged as sophisticated tools capable of capturing the complexity and diversity of cancer cells interacting within their microenvironments. These models address critical unmet needs in precision medicine, particularly in aiding clinical decision-making. The rapid development of these human tissue avatars has enabled advanced modeling of cellular alterations in disease states and the screening of compounds to uncover novel therapeutic pathways.Throughout the event, distinguished speakers shared their expertise and research findings, illustrating how organoids are transforming our understanding of treatment resistance, metastatic dynamics, and the interaction between tumors and the surrounding microenvironment.This conference served as a pivotal opportunity to strengthen international collaborations and spark innovative translational approaches. Its goal was to accelerate the shift from preclinical research to clinical application, paving the way for increasingly personalized and effective cancer therapies.

Patient-Derived Organoids as Therapy Screening Platforms in Cancer Patients

Patient-derived organoids (PDOs) developed ex vivo and in vitro are increasingly used for therapeutic screening. They provide a more physiologically relevant model for drug discovery and development compared to traditional cell lines. However, several challenges remain to be addressed to fully realize the potential of PDOs in therapeutic screening. This paper summarizes recent advancements in PDO development and the enhancement of PDO culture models. This is achieved by leveraging materials engineering and microfabrication technologies, including organs-on-a-chip and droplet microfluidics. Additionally, this work discusses the application of PDOs in therapy screening to meet diverse requirements and overcome bottlenecks in cancer treatment. Furthermore, this work introduces tools for data processing and analysis of organoids, along with their microenvironment. These tools aim to achieve enhanced readouts. Finally, this work explores the challenges and future perspectives of using PDOs in drug development and personalized screening for cancer patients.

BEHAV3D: a 3D live imaging platform for comprehensive analysis of engineered T cell behavior and tumor response

Modeling immuno-oncology by using patient-derived material and immune cell co-cultures can advance our understanding of immune cell tumor targeting in a patient-specific manner, offering leads to improve cellular immunotherapy. However, fully exploiting these living cultures requires analysis of the dynamic cellular features modeled, for which protocols are currently limited. Here, we describe the application of BEHAV3D, a platform that implements multi-color live 3D imaging and computational tools for: (i) analyzing tumor death dynamics at both single-organoid or cell and population levels, (ii) classifying T cell behavior and (iii) producing data-informed 3D images and videos for visual inspection and further insight into obtained results. Together, this enables a refined assessment of how solid and liquid tumors respond to cellular immunotherapy, critically capturing both inter- and intratumoral heterogeneity in treatment response. In addition, BEHAV3D uncovers T cell behavior involved in tumor targeting, offering insight into their mode of action. Our pipeline thereby has strong implications for comparing, prioritizing and improving immunotherapy products by highlighting the behavioral differences between individual tumor donors, distinct T cell therapy concepts or subpopulations. The protocol describes critical wet lab steps, including co-culture preparations and fast 3D imaging with live cell dyes, a segmentation-based image processing tool to track individual organoids, tumor and immune cells and an analytical pipeline for behavioral profiling. This 1-week protocol, accessible to users with basic cell culture, imaging and programming expertise, can easily be adapted to any type of co-culture to visualize and exploit cell behavior, having far-reaching implications for the immuno-oncology field and beyond.

Next-Generation Modeling of Cancer Using Organoids

In the last decade, organoid technology has become a cornerstone in cancer research. Organoids are long-term primary cell cultures, usually of epithelial origin, grown in a three-dimensional (3D) protein matrix and a fully defined medium. Organoids can be derived from many organs and cancer types and sites, encompassing both murine and human tissues. Importantly, they can be established from various stages during tumor evolution and recapitulate with high accuracy patient genomics and phenotypes in vitro, offering a platform for personalized medicine. Additionally, organoids are remarkably amendable for experimental manipulation. Taken together, these features make organoids a powerful tool with applications in basic cancer research and personalized medicine. Here, we will discuss the origins of organoid culture, applications in cancer research, and how cancer organoids can synergize with other models of cancer to drive basic discoveries as well as to translate these toward clinical solutions.

Application status and optimization suggestions of tumor organoids and CAR-T cell co-culture models

Tumor organoids, especially patient-derived organoids (PDOs) exhibit marked similarities in histopathological morphology, genomic alterations, and specific marker expression profiles to those of primary tumour tissues. They are applied in various fields including drug screening, gene editing, and identification of oncogenes. However, CAR-T therapy in the treatment of solid tumours is still at an exploratory stage. Tumour organoids offer unique advantages over other preclinical models commonly used for CAR-T therapy research, which the preservation of the biological characteristics of primary tumour tissue is critical for the study of early-stage solid tumour CAR-T therapies. Although some investigators have used this co-culture model to validate newly targeted CAR-T cells, optimise existing CAR-T cells and explore combination therapy strategies, there is still untapped potential in the co-culture models used today. This review introduces the current status of the application of tumour organoid and CAR-T cell co-culture models in recent years and commented on the limitations of the current co-cultivation model. Meanwhile, we compared the tumour organoid model with two pre-clinical models commonly used in CAR-T therapy research. Eventually, combined with the new progress of organoid technologies, optimization suggestions were proposed for the co-culture model from five perspectives: preserving or reconstructing the tumor microenvironment, systematization, vascularization, standardized culture procedures, and expanding the tumor organoids resource library, aimed at assisting related researchers to better utilize co-culture models.

Activation of cytotoxic lymphocytes through CD6 enhances killing of cancer cells

Immune checkpoint inhibitors (ICIs) have demonstrated efficacy and improved survival in a growing number of cancers. Despite their success, ICIs are associated with immune-related adverse events that can interfere with their use. Therefore, safer approaches are needed. CD6, expressed by T-lymphocytes and human NK cells, engages in cell-cell interactions by binding to its ligands CD166 (ALCAM) and CD318 (CDCP1). CD6 is a target protein for regulating immune responses and is required for the development of several mouse models of autoimmunity. Interestingly, CD6 is exclusively expressed on immune cells while CD318 is strongly expressed on most cancers. Here we demonstrate that disrupting the CD6-CD318 axis with UMCD6, an anti-CD6 monoclonal antibody, prolongs survival of mice in xenograft mouse models of human breast and prostate cancer, treated with infusions of human lymphocytes. Analysis of tumor-infiltrating immune cells showed that augmentation of lymphocyte cytotoxicity by UMCD6 is due to effects of this antibody on NK, NKT and CD8 + T cells. In particular, tumor-infiltrating cytotoxic lymphocytes from UMCD6-treated mice expressed higher levels of perforin and were found in higher proportions than those from IgG-treated mice. Moreover, RNA-seq analysis of human NK-92 cells treated with UMCD6 revealed that UMCD6 up-regulates the NKG2D-DAP10 receptor complex, important in NK cell activation, as well as its downstream target PI3K. Our results now describe the phenotypic changes that occur on immune cells upon treatment with UMCD6 and further confirm that the CD6-CD318 axis can regulate the activation state of cytotoxic lymphocytes and their positioning within the tumor microenvironment.

Bridging live-cell imaging and next-generation cancer treatment

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

Activation of Cytotoxic Lymphocytes Through CD6 Enhances Killing of Cancer Cells

Immune checkpoint inhibitors (ICIs) have demonstrated efficacy and improved survival in a growing number of cancers. Despite their success, ICIs are associated with immune-related adverse events that can interfere with their use. Therefore, safer approaches are needed. CD6, expressed by T-lymphocytes and human NK cells, engages in cell-cell interactions by binding to its ligands CD166 (ALCAM) and CD318 (CDCP1). CD6 is a target protein for regulating immune responses and is required for the development of several mouse models of autoimmunity. Interestingly, CD6 is exclusively expressed on immune cells while CD318 is strongly expressed on most cancers. Here we demonstrate that disrupting the CD6-CD318 axis with UMCD6, an anti-CD6 monoclonal antibody, prolongs survival of mice in xenograft models of human breast and prostate cancer, treated with infusions of human lymphocytes. Analysis of tumor-infiltrating immune cells showed that augmentation of lymphocyte cytotoxicity by UMCD6 is due to effects of this antibody on NK, NKT and CD8+ T cells. Tumor-infiltrating cytotoxic lymphocytes were found in higher proportions and were activated in UMCD6-treated mice compared to controls. Similar changes in gene expression were observed by RNA-seq analysis of NK cells treated with UMCD6. Particularly, UMCD6 up-regulated the NKG2D-DAP10 complex and activated PI3K. Thus, the CD6-CD318 axis can regulate the activation state of cytotoxic lymphocytes and their positioning within the tumor microenvironment.

Probing organoid metabolism using fluorescence lifetime imaging microscopy (FLIM): The next frontier of drug discovery and disease understanding

Organoid models have been used to address important questions in developmental and cancer biology, tissue repair, advanced modelling of disease and therapies, among other bioengineering applications. Such 3D microenvironmental models can investigate the regulation of cell metabolism, and provide key insights into the mechanisms at the basis of cell growth, differentiation, communication, interactions with the environment and cell death. Their accessibility and complexity, based on 3D spatial and temporal heterogeneity, make organoids suitable for the application of novel, dynamic imaging microscopy methods, such as fluorescence lifetime imaging microscopy (FLIM) and related decay time-assessing readouts. Several biomarkers and assays have been proposed to study cell metabolism by FLIM in various organoid models. Herein, we present an expert-opinion discussion on the principles of FLIM and PLIM, instrumentation and data collection and analysis protocols, and general and emerging biosensor-based approaches, to highlight the pioneering work being performed in this field.

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 applications and techniques of organoids in head and neck cancer therapy

Head and neck cancer (HNC) is one of the most common cancers on the planet, with approximately 600,000 new cases diagnosed and 300,000 deaths every year. Research into the biological basis of HNC has advanced slowly over the past decades, which has made it difficult to develop new, more effective treatments. The patient-derived organoids (PDOs) are made from patient tumor cells, resembling the features of their tumors, which are high-fidelity models for studying cancer biology and designing new precision medicine therapies. In recent years, considerable effort has been focused on improving "organoids" technologies and identifying tumor-specific medicine using head and neck samples and a variety of organoids. A review of improved techniques and conclusions reported in publications describing the application of these techniques to HNC organoids is presented here. Additionally, we discuss the potential application of organoids in head and neck cancer research as well as the limitations associated with these models. As a result of the integration of organoid models into future precision medicine research and therapeutic profiling programs, the use of organoids will be extremely significant in the future.

Patient-derived models facilitate precision medicine in liver cancer by remodeling cell-matrix interaction

Liver cancer is an aggressive tumor originating in the liver with a dismal prognosis. Current evidence suggests that liver cancer is the fifth most prevalent cancer worldwide and the second most deadly type of malignancy. Tumor heterogeneity accounts for the differences in drug responses among patients, emphasizing the importance of precision medicine. Patient-derived models of cancer are widely used preclinical models to study precision medicine since they preserve tumor heterogeneity ex vivo in the study of many cancers. Patient-derived models preserving cell-cell and cell-matrix interactions better recapitulate in vivo conditions, including patient-derived xenografts (PDXs), induced pluripotent stem cells (iPSCs), precision-cut liver slices (PCLSs), patient-derived organoids (PDOs), and patient-derived tumor spheroids (PDTSs). In this review, we provide a comprehensive overview of the different modalities used to establish preclinical models for precision medicine in liver cancer.

Organoids as an Enabler of Precision Immuno-Oncology

Since the dawn of the past century, landmark discoveries in cell-mediated immunity have led to a greater understanding of the innate and adaptive immune systems and revolutionised the treatment of countless diseases, including cancer. Today, precision immuno-oncology (I/O) involves not only targeting immune checkpoints that inhibit T-cell immunity but also harnessing immune cell therapies. The limited efficacy in some cancers results mainly from a complex tumour microenvironment (TME) that, in addition to adaptive immune cells, comprises innate myeloid and lymphoid cells, cancer-associated fibroblasts, and the tumour vasculature that contribute towards immune evasion. As the complexity of TME has called for more sophisticated human-based tumour models, organoids have allowed the dynamic study of spatiotemporal interactions between tumour cells and individual TME cell types. Here, we discuss how organoids can study the TME across cancers and how these features may improve precision I/O. We outline the approaches to preserve or recapitulate the TME in tumour organoids and discuss their potential, advantages, and limitations. We will discuss future directions of organoid research in understanding cancer immunology in-depth and identifying novel I/O targets and treatment strategies.

Boosting the Clinical Translation of Organ-on-a-Chip Technology

Organ-on-a-chip devices have become a viable option for investigating critical physiological events and responses; this technology has matured substantially, and many systems have been reported for disease modeling or drug screening over the last decade. Despite the wide acceptance in the academic community, their adoption by clinical end-users is still a non-accomplished promise. The reasons behind this difficulty can be very diverse but most likely are related to the lack of predictive power, physiological relevance, and reliability necessary for being utilized in the clinical area. In this Perspective, we briefly discuss the main attributes of organ-on-a-chip platforms in academia and how these characteristics impede their easy translation to the clinic. We also discuss how academia, in conjunction with the industry, can contribute to boosting their adoption by proposing novel design concepts, fabrication methods, processes, and manufacturing materials, improving their standardization and versatility, and simplifying their manipulation and reusability.