Modeling tumor development and metastasis using paired organoids derived from patients with colorectal cancer liver metastases

CAR T cells in solid tumors and metastasis: paving the way forward

CAR T cell therapy, hailed as a breakthrough in cancer treatment due to its remarkable outcomes in hematological malignancies, encounters significant hurdles when applied to solid tumors. While notable responses to CAR T cells remain sporadic in these patients, challenges persist due to issues such as on-target off-tumor toxicity, difficulties in their trafficking and infiltration into the tumor, and the presence of a hostile and immunosuppressive microenvironment. This review aims to explore recent endeavors aimed at overcoming these obstacles in CAR T cell therapy for solid tumors. Specifically, we will delve into promising strategies for enhancing tumor specificity through antigen targeting, addressing tumor heterogeneity, overcoming physical barriers, and counteracting the immune-suppressive microenvironment.

Exploring tumor organoids for cancer treatment

As a life-threatening chronic disease, cancer is characterized by tumor heterogeneity. This heterogeneity is associated with factors that lead to treatment failure and poor prognosis, including drug resistance, relapse, and metastasis. Therefore, precision medicine urgently needs personalized tumor models that accurately reflect the tumor heterogeneity. Currently, tumor organoid technologies are used to generate in vitro 3D tissues, which have been shown to precisely recapitulate structure, tumor microenvironment, expression profiles, functions, molecular signatures, and genomic alterations in primary tumors. Tumor organoid models are important for identifying potential therapeutic targets, characterizing the effects of anticancer drugs, and exploring novel diagnostic and therapeutic options. In this review, we describe how tumor organoids can be cultured and summarize how researchers can use them as an excellent tool for exploring cancer therapies. In addition, we discuss tumor organoids that have been applied in cancer therapy research and highlight the potential of tumor organoids to guide preclinical research.

Organoids derived from metastatic cancers: Present and future

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

Cancer organoids: A platform in basic and translational research

An accumulation of previous work has established organoids as good preclinical models of human tumors, facilitating translation from basic research to clinical practice. They are changing the paradigm of preclinical cancer research because they can recapitulate the heterogeneity and pathophysiology of human cancers and more closely approximate the complex tissue environment and structure found in clinical tumors than in vitro cell lines and animal models. However, the potential applications of cancer organoids remain to be comprehensively summarized. In the review, we firstly describe what is currently known about cancer organoid culture and then discuss in depth the basic mechanisms, including tumorigenesis and tumor metastasis, and describe recent advances in patient-derived tumor organoids (PDOs) for drug screening and immunological studies. Finally, the present challenges faced by organoid technology in clinical practice and its prospects are discussed. This review highlights that organoids may offer a novel therapeutic strategy for cancer research.

Human intestinal organoids: Modeling gastrointestinal physiology and immunopathology - current applications and limitations

Human intestinal organoids are an ideal model system for studying gastrointestinal physiology and immunopathology. Altered physiology and mucosal immune response are hallmarks of numerous intestinal functional and inflammatory diseases, including inflammatory bowel disease (IBD), coeliac disease, irritable bowel syndrome (IBS), and obesity. These conditions impact the normal epithelial functions of the intestine, such as absorption, barrier function, secretion, and host-microbiome communication. They are accompanied by characteristic intestinal symptoms and have significant societal, economic, and healthcare burdens. To develop new treatment options, cutting-edge research is required to investigate their etiology and pathology. Human intestinal organoids derived from patient tissue recapitulate the key physiological and immunopathological aspects of these conditions, providing a promising platform for elucidating disease mechanisms. This review will summarize recent reports on patient-derived human small intestinal and colonic organoids and highlight how these models have been used to study intestinal epithelial functions in the context of inflammation, altered physiology, and immune response. Furthermore, it will elaborate on the various organoid systems in use and the techniques/assays currently available to study epithelial functions. Finally, it will conclude by discussing the limitations and future perspectives of organoid technology.

Scaffold-based 3D cell culture models in cancer research

Three-dimensional (3D) cell cultures have emerged as valuable tools in cancer research, offering significant advantages over traditional two-dimensional (2D) cell culture systems. In 3D cell cultures, cancer cells are grown in an environment that more closely mimics the 3D architecture and complexity of in vivo tumors. This approach has revolutionized cancer research by providing a more accurate representation of the tumor microenvironment (TME) and enabling the study of tumor behavior and response to therapies in a more physiologically relevant context. One of the key benefits of 3D cell culture in cancer research is the ability to recapitulate the complex interactions between cancer cells and their surrounding stroma. Tumors consist not only of cancer cells but also various other cell types, including stromal cells, immune cells, and blood vessels. These models bridge traditional 2D cell cultures and animal models, offering a cost-effective, scalable, and ethical alternative for preclinical research. As the field advances, 3D cell cultures are poised to play a pivotal role in understanding cancer biology and accelerating the development of effective anticancer therapies. This review article highlights the key advantages of 3D cell cultures, progress in the most common scaffold-based culturing techniques, pertinent literature on their applications in cancer research, and the ongoing challenges.

Revolutionizing digestive system tumor organoids research: Exploring the potential of tumor organoids

Digestive system tumors are the leading cause of cancer-related deaths worldwide. Despite ongoing research, our understanding of their mechanisms and treatment remain inadequate. One promising tool for clinical applications is the use of gastrointestinal tract tumor organoids, which serve as an important in vitro model. Tumor organoids exhibit a genotype similar to the patient's tumor and effectively mimic various biological processes, including tissue renewal, stem cell, and ecological niche functions, and tissue response to drugs, mutations, or injury. As such, they are valuable for drug screening, developing novel drugs, assessing patient outcomes, and supporting immunotherapy. In addition, innovative materials and techniques can be used to optimize tumor organoid culture systems. Several applications of digestive system tumor organoids have been described and have shown promising results in related aspects. In this review, we discuss the current progress, limitations, and prospects of this model for digestive system tumors.

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.

In Vitro Organoid-Based Assays Reveal SMAD4 Tumor-Suppressive Mechanisms for Serrated Colorectal Cancer Invasion

Colon cancer is the third most prominent cancer and second leading cause of cancer-related deaths in the United States. Up to 20% of colon cancers follow the serrated tumor pathway driven by mutations in the MAPK pathway. Loss of SMAD4 function occurs in the majority of late-stage colon cancers and is associated with aggressive cancer progression. Therefore, it is important to develop technology to accurately model and better understand the genetic mechanisms behind cancer invasion. Organoids derived from tumors found in the Smad4KO BRAFV600E/+ mouse model present multiple phenotypes characteristic of invasion both in ex vivo and in vivo systems. Smad4KO BRAFV600E/+ tumor organoids can migrate through 3D culture and infiltrate through transwell membranes. This invasive behavior can be suppressed when SMAD4 is re-expressed in the tumor organoids. RNA-Seq analysis reveals that SMAD4 expression in organoids rapidly regulates transcripts associated with extracellular matrix and secreted proteins, suggesting that the mechanisms employed by SMAD4 to inhibit invasion are associated with regulation of extracellular matrix and secretory pathways. These findings indicate new models to study SMAD4 regulation of tumor invasion and an additional layer of complexity in the tumor-suppressive function of the SMAD4/Tgfβ pathway.

Organoids: approaches and utility in cancer research

ABSTRACT

Organoids are three-dimensional cellular structures with self-organizing and self-differentiation capacities. They faithfully recapitulate structures and functions of in vivo organs as represented by functionality and microstructural definitions. Heterogeneity in in vitro disease modeling is one of the main reasons for anti-cancer therapy failures. Establishing a powerful model to represent tumor heterogeneity is crucial for elucidating tumor biology and developing effective therapeutic strategies. Tumor organoids can retain the original tumor heterogeneity and are commonly used to mimic the cancer microenvironment when co-cultured with fibroblasts and immune cells; therefore, considerable effort has been made recently to promote the use of this new technology from basic research to clinical studies in tumors. In combination with gene editing technology and microfluidic chip systems, engineered tumor organoids show promising abilities to recapitulate tumorigenesis and metastasis. In many studies, the responses of tumor organoids to various drugs have shown a positive correlation with patient responses. Owing to these consistent responses and personalized characteristics with patient data, tumor organoids show excellent potential for preclinical research. Here, we summarize the properties of different tumor models and review their current state and progress in tumor organoids. We further discuss the substantial challenges and prospects in the rapidly developing tumor organoid field.

Liver organoids: a promising three-dimensional model for insights and innovations in tumor progression and precision medicine of liver cancer

Primary liver cancer (PLC) is one type of cancer with high incidence rate and high mortality rate in the worldwide. Systemic therapy is the major treatment for PLC, including surgical resection, immunotherapy and targeted therapy. However, mainly due to the heterogeneity of tumors, responses to the above drug therapy differ from person to person, indicating the urgent needs for personalized treatment for PLC. Organoids are 3D models derived from adult liver tissues or pluripotent stem cells. Based on the ability to recapitulate the genetic and functional features of in vivo tissues, organoids have assisted biomedical research to make tremendous progress in understanding disease origin, progression and treatment strategies since their invention and application. In liver cancer research, liver organoids contribute greatly to reflecting the heterogeneity of liver cancer and restoring tumor microenvironment (TME) by co-organizing tumor vasculature and stromal components in vitro. Therefore, they provide a promising platform for further investigation into the biology of liver cancer, drug screening and precision medicine for PLC. In this review, we discuss the recent advances of liver organoids in liver cancer, in terms of generation methods, application in precision medicine and TME modeling.

Artificial intelligence in liver cancers: Decoding the impact of machine learning models in clinical diagnosis of primary liver cancers and liver cancer metastases

Liver cancers are the fourth leading cause of cancer-related mortality worldwide. In the past decade, breakthroughs in the field of artificial intelligence (AI) have inspired development of algorithms in the cancer setting. A growing body of recent studies have evaluated machine learning (ML) and deep learning (DL) algorithms for pre-screening, diagnosis and management of liver cancer patients through diagnostic image analysis, biomarker discovery and predicting personalized clinical outcomes. Despite the promise of these early AI tools, there is a significant need to explain the 'black box' of AI and work towards deployment to enable ultimate clinical translatability. Certain emerging fields such as RNA nanomedicine for targeted liver cancer therapy may also benefit from application of AI, specifically in nano-formulation research and development given that they are still largely reliant on lengthy trial-and-error experiments. In this paper, we put forward the current landscape of AI in liver cancers along with the challenges of AI in liver cancer diagnosis and management. Finally, we have discussed the future perspectives of AI application in liver cancer and how a multidisciplinary approach using AI in nanomedicine could accelerate the transition of personalized liver cancer medicine from bench side to the clinic.

Patient-derived xenograft model in colorectal cancer basic and translational research

Colorectal cancer (CRC) is one of the most popular malignancies globally, with 930 000 deaths in 2020. The evaluation of CRC-related pathogenesis and the discovery of potential therapeutic targets will be meaningful and helpful for improving CRC treatment. With huge efforts made in past decades, the systematic treatment regimens have been applied to improve the prognosis of CRC patients. However, the sensitivity of CRC to chemotherapy and targeted therapy is different from person to person, which is an important cause of treatment failure. The emergence of patient-derived xenograft (PDX) models shows great potential to alleviate the straits. PDX models possess similar genetic and pathological characteristics as the features of primary tumors. Moreover, PDX has the ability to mimic the tumor microenvironment of the original tumor. Thus, the PDX model is an important tool to screen precise drugs for individualized treatment, seek predictive biomarkers for prognosis supervision, and evaluate the unknown mechanism in basic research. This paper reviews the recent advances in constructed methods and applications of the CRC PDX model, aiming to provide new knowledge for CRC basic research and therapeutics.

Panomics reveals patient individuality as the major driver of colorectal cancer progression

BACKGROUND

Colorectal cancer (CRC) is one of the most prevalent cancers, with over one million new cases per year. Overall, prognosis of CRC largely depends on the disease stage and metastatic status. As precision oncology for patients with CRC continues to improve, this study aimed to integrate genomic, transcriptomic, and proteomic analyses to identify significant differences in expression during CRC progression using a unique set of paired patient samples while considering tumour heterogeneity.

METHODS

We analysed fresh-frozen tissue samples prepared under strict cryogenic conditions of matched healthy colon mucosa, colorectal carcinoma, and liver metastasis from the same patients. Somatic mutations of known cancer-related genes were analysed using Illumina's TruSeq Amplicon Cancer Panel; the transcriptome was assessed comprehensively using Clariom D microarrays. The global proteome was evaluated by liquid chromatography-coupled mass spectrometry (LC‒MS/MS) and validated by two-dimensional difference in-gel electrophoresis. Subsequent unsupervised principal component clustering, statistical comparisons, and gene set enrichment analyses were calculated based on differential expression results.

RESULTS

Although panomics revealed low RNA and protein expression of CA1, CLCA1, MATN2, AHCYL2, and FCGBP in malignant tissues compared to healthy colon mucosa, no differentially expressed RNA or protein targets were detected between tumour and metastatic tissues. Subsequent intra-patient comparisons revealed highly specific expression differences (e.g., SRSF3, OLFM4, and CEACAM5) associated with patient-specific transcriptomes and proteomes.

CONCLUSION

Our research results highlight the importance of inter- and intra-tumour heterogeneity as well as individual, patient-paired evaluations for clinical studies. In addition to changes among groups reflecting CRC progression, we identified significant expression differences between normal colon mucosa, primary tumour, and liver metastasis samples from individuals, which might accelerate implementation of precision oncology in the future.

Bufalin Inhibits Tumorigenesis, Stemness, and Epithelial-Mesenchymal Transition in Colorectal Cancer through a C-Kit/Slug Signaling Axis

Colorectal cancer (CRC) is a major source of morbidity and mortality, characterized by intratumoral heterogeneity and the presence of cancer stem cells (CSCs). Bufalin has potent activity against many tumors, but studies of its effect on CRC stemness are limited. We explored bufalin's function and mechanism using CRC patient-derived organoids (PDOs) and cell lines. In CRC cells, bufalin prevented nuclear translocation of β-catenin and down-regulated CSC markers (CD44, CD133, LGR5), pluripotency factors, and epithelial-mesenchymal transition (EMT) markers (N-Cadherin, Slug, ZEB1). Functionally, bufalin inhibited CRC spheroid formation, aldehyde dehydrogenase activity, migration, and invasion. Network analysis identified a C-Kit/Slug signaling axis accounting for bufalin's anti-stemness activity. Bufalin treatment significantly downregulated C-Kit, as predicted. Furthermore, overexpression of C-Kit induced Slug expression, spheroid formation, and bufalin resistance. Similarly, overexpression of Slug resulted in increased expression of C-Kit and identical functional effects, demonstrating a pro-stemness feedback loop. For further study, we established PDOs from diagnostic colonoscopy. Bufalin differentially inhibited PDO growth and proliferation, induced apoptosis, restored E-cadherin, and downregulated CSC markers CD133 and C-Myc, dependent on C-Kit/Slug. These findings suggest that the C-Kit/Slug axis plays a pivotal role in regulating CRC stemness, and reveal that targeting this axis can inhibit CRC growth and progression.

Applications of human organoids in the personalized treatment for digestive diseases

Digestive system diseases arise primarily through the interplay of genetic and environmental influences; there is an urgent need in elucidating the pathogenic mechanisms of these diseases and deploy personalized treatments. Traditional and long-established model systems rarely reproduce either tissue complexity or human physiology faithfully; these shortcomings underscore the need for better models. Organoids represent a promising research model, helping us gain a more profound understanding of the digestive organs; this model can also be used to provide patients with precise and individualized treatment and to build rapid in vitro test models for drug screening or gene/cell therapy, linking basic research with clinical treatment. Over the past few decades, the use of organoids has led to an advanced understanding of the composition of each digestive organ and has facilitated disease modeling, chemotherapy dose prediction, CRISPR-Cas9 genetic intervention, high-throughput drug screening, and identification of SARS-CoV-2 targets, pathogenic infection. However, the existing organoids of the digestive system mainly include the epithelial system. In order to reveal the pathogenic mechanism of digestive diseases, it is necessary to establish a completer and more physiological organoid model. Combining organoids and advanced techniques to test individualized treatments of different formulations is a promising approach that requires further exploration. This review highlights the advancements in the field of organoid technology from the perspectives of disease modeling and personalized therapy.

Patient-derived cancer models: Valuable platforms for anticancer drug testing

Molecularly targeted treatments and immunotherapy are cornerstones in oncology, with demonstrated efficacy across different tumor types. Nevertheless, the overwhelming majority metastatic disease is incurable due to the onset of drug resistance. Preclinical models including genetically engineered mouse models, patient-derived xenografts and two- and three-dimensional cell cultures have emerged as a useful resource to study mechanisms of cancer progression and predict efficacy of anticancer drugs. However, variables including tumor heterogeneity and the complexities of the microenvironment can impair the faithfulness of these platforms. Here, we will discuss advantages and limitations of these preclinical models, their applicability for drug testing and in co-clinical trials and potential strategies to increase their reliability in predicting responsiveness to anticancer medications.

Organoids as a Model for Precision Medicine in Malignant Pleural Mesothelioma: Where Are We Today?

MPM is an aggressive tumor originating from pleural mesothelial cells. A characteristic feature of the disease is the dominant prevalence of therapeutically intractable inactivating alterations in TSGs, making MPM one of the most difficult cancers to treat and the epitome of a cancer characterized by a significant lack of therapy options and an extremely poor prognosis (5-year survival rate of only 5% to 10%). Extensive interpatient heterogeneity poses another major challenge for targeted therapy of MPM, warranting stratified therapy for specific subgroups of MPM patients. Accurate preclinical models are critical for the discovery of new therapies and the development of personalized medicine. Organoids, an in vitro 'organ-like' 3D structure derived from patient tumor tissue that faithfully mimics the biology and complex architecture of cancer and largely overcomes the limitations of other existing models, are the next-generation tumor model. Although organoids have been successfully produced and used in many cancers, the development of MPM organoids is still in its infancy. Here, we provide an overview of recent advances in cancer organoids, focusing on the progress and challenges in MPM organoid development. We also elaborate the potential of MPM organoids for understanding MPM pathobiology, discovering new therapeutic targets, and developing personalized treatments for MPM patients.

Breast cancer metastasis: is it a matter of OMICS and proper ex-vivo models?

Genomics has greatly increased the understanding of the study of breast cancer (BC) and has shaped the concept of intra-tumor heterogeneity, currently recognized as a propelling force for cancer progression. In this context, knowledge and understanding of metastatic breast cancer (mBC) has somehow lagged behind that of primary breast cancer. This may be explained by the relative scarcity of matched mBC samples, however it is possible that the mutation spectrum obtained from primary BC does not capture the full complexity of the metastatic disease. Here, we provide a few examples supporting this possibility, from public databases. We evoke the need to perform an integrated multi-OMICS characterization of mBC, to obtain a broad understanding of this complex disease, whose evolution cannot be explained solely by genomics. Pertinent to this, we suggest that rather an infrequent use of Patient-Derived –Tumor-Organoids (PDTOs) may be influenced by assuming that the metastatic conditions of PDTOs growth (mPDTOs) should be similar to those of the tissue of origin. We challenge this view by suggesting that the use of “target-organ inspired” growth conditions for mPDTOs, may better fit the emerging knowledge of metastatic disease. Thus, the integrated use of multi-OMICS and of clinically relevant mPDTOs may allow a further understanding of such disease and foster therapeutically relevant advances. We believe that our points may be valid for other solid cancers.

Tumor organoids: applications in cancer modeling and potentials in precision medicine

Cancer is a top-ranked life-threatening disease with intratumor heterogeneity. Tumor heterogeneity is associated with metastasis, relapse, and therapy resistance. These factors contribute to treatment failure and an unfavorable prognosis. Personalized tumor models faithfully capturing the tumor heterogeneity of individual patients are urgently needed for precision medicine. Advances in stem cell culture have given rise to powerful organoid technology for the generation of in vitro three-dimensional tissues that have been shown to more accurately recapitulate the structures, specific functions, molecular characteristics, genomic alterations, expression profiles, and tumor microenvironment of primary tumors. Tumoroids in vitro serve as an important component of the pipeline for the discovery of potential therapeutic targets and the identification of novel compounds. In this review, we will summarize recent advances in tumoroid cultures as an excellent tool for accurate cancer modeling. Additionally, vascularization and immune microenvironment modeling based on organoid technology will also be described. Furthermore, we will summarize the great potential of tumor organoids in predicting the therapeutic response, investigating resistance-related mechanisms, optimizing treatment strategies, and exploring potential therapies. In addition, the bottlenecks and challenges of current tumoroids will also be discussed in this review.

Application of Organoids in Carcinogenesis Modeling and Tumor Vaccination

Organoids well recapitulate organ-specific functions from their tissue of origin and remain fundamental aspects of organogenesis. Organoids are widely applied in biomedical research, drug discovery, and regenerative medicine. There are various cultivated organoid systems induced by adult stem cells and pluripotent stem cells, or directly derived from primary tissues. Researchers have drawn inspiration by combination of organoid technology and tissue engineering to produce organoids with more physiological relevance and suitable for translational medicine. This review describes the value of applying organoids for tumorigenesis modeling and tumor vaccination. We summarize the application of organoids in tumor precision medicine. Extant challenges that need to be conquered to make this technology be more feasible and precise are discussed.

Application Progress of Organoids in Colorectal Cancer

Currently, colorectal cancer is still the third leading cause of cancer-related mortality, and the incidence is rising. It is a long time since the researchers used cancer cell lines and animals as the study subject. However, these models possess various limitations to reflect the cancer progression in the human body. Organoids have more clinical significance than cell lines, and they also bridge the gap between animal models and humans. Patient-derived organoids are three-dimensional cultures that simulate the tumor characteristics in vivo and recapitulate tumor cell heterogeneity. Therefore, the emergence of colorectal cancer organoids provides an unprecedented opportunity for colorectal cancer research. It retains the molecular and cellular composition of the original tumor and has a high degree of homology and complexity with patient tissues. Patient-derived colorectal cancer organoids, as personalized tumor organoids, can more accurately simulate colorectal cancer patients’ occurrence, development, metastasis, and predict drug response in colorectal cancer patients. Colorectal cancer organoids show great potential for application, especially preclinical drug screening and prediction of patient response to selected treatment options. Here, we reviewed the application of colorectal cancer organoids in disease model construction, basic biological research, organoid biobank construction, drug screening and personalized medicine, drug development, drug toxicity and safety, and regenerative medicine. In addition, we also displayed the current limitations and challenges of organoids and discussed the future development direction of organoids in combination with other technologies. Finally, we summarized and analyzed the current clinical trial research of organoids, especially the clinical trials of colorectal cancer organoids. We hoped to lay a solid foundation for organoids used in colorectal cancer research.

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

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

Functional metabolome profiling may improve individual outcomes in colorectal cancer management implementing concepts of predictive, preventive, and personalized medical approach

Objectives

Colorectal cancer (CRC) is one of the most common solid tumors worldwide, but its diagnosis and treatment are limited. The objectives of our study were to compare the metabolic differences between CRC patients and healthy controls (HC), and to identify potential biomarkers in the serum that can be used for early diagnosis and as effective therapeutic targets. The aim was to provide a new direction for CRC predictive, preventive, and personalized medicine (PPPM).

Methods

In this study, CRC patients (n = 30) and HC (n = 30) were recruited. Serum metabolites were assayed using an ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) technology. Subsequently, CRC cell lines (HCT116 and HCT8) were treated with metabolites to verify their function. Key targets were identified by molecular docking, thermal shift assay, and protein overexpression/inhibition experiments. The inhibitory effect of celastrol on tumor growth was also assessed, which included IC50 analysis, nude mice xenografting, molecular docking, protein overexpression/inhibition experiments, and network pharmacology technology.

Results

In the CRC group, 15 serum metabolites were significantly different in comparison with the HC group. The level of glycodeoxycholic acid (GDCA) was positively correlated with CRC and showed high sensitivity and specificity for the clinical diagnostic reference (AUC = 0.825). In vitro findings showed that GDCA promoted the proliferation and migration of CRC cell lines (HCT116 and HCT8), and Poly(ADP-ribose) polymerase-1 (PARP-1) was identified as one of the key targets of GDCA. The IC50 of celastrol in HCT116 cells was 121.1 nM, and the anticancer effect of celastrol was supported by in vivo experiments. Based on the potential of GDCA in PPPM, PARP-1 was found to be significantly correlated with the anticancer functions of celastrol.

Conclusion

These findings suggest that GDCA is an abnormally produced metabolite of CRC, which may provide an innovative molecular biomarker for the predictive identification and targeted prevention of CRC. In addition, PARP-1 was found to be an important target of GDCA that promotes CRC; therefore, celastrol may be a potential targeted therapy for CRC via its effects on PARP-1. Taken together, the pathophysiology and progress of tumor molecules mediated by changes in metabolite content provide a new perspective for predictive, preventive, and personalized medical of clinical cancer patients based on the target of metabolites in vivo.Clinical trials registration number: ChiCTR2000039410.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-021-00269-8.

Application of artificial intelligence in a real-world research for predicting the risk of liver metastasis in T1 colorectal cancer

Background

Liver is the most common metastatic site of colorectal cancer (CRC) and liver metastasis (LM) determines subsequent treatment as well as prognosis of patients, especially in T1 patients. T1 CRC patients with LM are recommended to adopt surgery and systematic treatments rather than endoscopic therapy alone. Nevertheless, there is still no effective model to predict the risk of LM in T1 CRC patients. Hence, we aim to construct an accurate predictive model and an easy-to-use tool clinically.

Methods

We integrated two independent CRC cohorts from Surveillance Epidemiology and End Results database (SEER, training dataset) and Xijing hospital (testing dataset). Artificial intelligence (AI) and machine learning (ML) methods were adopted to establish the predictive model.

Results

A total of 16,785 and 326 T1 CRC patients from SEER database and Xijing hospital were incorporated respectively into the study. Every single ML model demonstrated great predictive capability, with an area under the curve (AUC) close to 0.95 and a stacking bagging model displaying the best performance (AUC = 0.9631). Expectedly, the stacking model exhibited a favorable discriminative ability and precisely screened out all eight LM cases from 326 T1 patients in the outer validation cohort. In the subgroup analysis, the stacking model also demonstrated a splendid predictive ability for patients with tumor size ranging from one to50mm (AUC = 0.956).

Conclusion

We successfully established an innovative and convenient AI model for predicting LM in T1 CRC patients, which was further verified in the external dataset. Ultimately, we designed a novel and easy-to-use decision tree, which only incorporated four fundamental parameters and could be successfully applied in clinical practice.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02424-7.

Patient-derived organoids as a model for tumor research

Cancer represents a leading cause of death, despite the rapid progress of cancer research, leading to urgent need for accurate preclinical model to further study of tumor mechanism and accelerate translational applications. Cancer cell lines cannot fully recapitulate tumors of different patients due to the lack of tumor complexity and specification, while the high technical difficulty, long time, and substantial cost of patient-derived xenograft model makes it unable to be used extensively for all types of tumors and large-scale drug screening. Patient-derived organoids can be established rapidly with a high success rate from many tumors, and precisely replicate the key histopathological, genetic, and phenotypic features, as well as therapeutic response of patient tumor. Therefore, they are extensively used in cancer basic research, biobanking, disease modeling and precision medicine. The combinations of cancer organoids with other advanced technologies, such as 3D bio-printing, organ-on-a-chip, and CRISPR-Cas9, contributes to the more complete replication of complex tumor microenvironment and tumorigenesis. In this review, we discuss the various methods of the establishment and the application of patient-derived organoids in diverse tumors as well as the limitations and future prospects of these models. Further advances of tumor organoids are expected to bridge the huge gap between bench and bedside and provide the unprecedented opportunities to advance cancer research.

Tumor organoids: synergistic applications, current challenges, and future prospects in cancer therapy

Patient-derived cancer cells (PDCs) and patient-derived xenografts (PDXs) are often used as tumor models, but have many shortcomings. PDCs not only lack diversity in terms of cell type, spatial organization, and microenvironment but also have adverse effects in stem cell cultures, whereas PDX are expensive with a low transplantation success rate and require a long culture time. In recent years, advances in three-dimensional (3D) organoid culture technology have led to the development of novel physiological systems that model the tissues of origin more precisely than traditional culture methods. Patient-derived cancer organoids bridge the conventional gaps in PDC and PDX models and closely reflect the pathophysiological features of natural tumorigenesis and metastasis, and have led to new patient-specific drug screening techniques, development of individualized treatment regimens, and discovery of prognostic biomarkers and mechanisms of resistance. Synergistic combinations of cancer organoids with other technologies, for example, organ-on-a-chip, 3D bio-printing, and CRISPR-Cas9-mediated homology-independent organoid transgenesis, and with treatments, such as immunotherapy, have been useful in overcoming their limitations and led to the development of more suitable model systems that recapitulate the complex stroma of cancer, inter-organ and intra-organ communications, and potentially multiorgan metastasis. In this review, we discuss various methods for the creation of organ-specific cancer organoids and summarize organ-specific advances and applications, synergistic technologies, and treatments as well as current limitations and future prospects for cancer organoids. Further advances will bring this novel 3D organoid culture technique closer to clinical practice in the future.