Organoids as a new approach for improving pediatric cancer research.

A key challenge in cancer research is the meticulous development of models that faithfully emulates the intricacies of the patient scenario, with emphasis on preserving intra-tumoral heterogeneity and the dynamic milieu of the tumor microenvironment (TME). Organoids emerge as promising tool in new drug development, drug screening and precision medicine. Despite advances in the diagnoses and treatment of pediatric cancers, certain tumor subtypes persist in yielding unfavorable prognoses. Moreover, the prognosis for a significant portion of children experiencing disease relapse is dismal. To improve pediatric outcome many groups are focusing on the development of precision medicine approach. In this review, we summarize the current knowledge about using organoid system as model in preclinical and clinical solid-pediatric cancer. Since organoids retain the pivotal characteristics of primary parent tumors, they exert great potential in discovering novel tumor biomarkers, exploring drug-resistance mechanism and predicting tumor responses to chemotherapy, targeted therapy and immunotherapies. We also examine both the potential opportunities and existing challenges inherent organoids, hoping to point out the direction for future organoid development.

Advancement in Cancer Vasculogenesis Modeling through 3D Bioprinting Technology.

Cancer vasculogenesis is a pivotal focus of cancer research and treatment given its critical role in tumor development, metastasis, and the formation of vasculogenic microenvironments. Traditional approaches to investigating cancer vasculogenesis face significant challenges in accurately modeling intricate microenvironments. Recent advancements in three-dimensional (3D) bioprinting technology present promising solutions to these challenges. This review provides an overview of cancer vasculogenesis and underscores the importance of precise modeling. It juxtaposes traditional techniques with 3D bioprinting technologies, elucidating the advantages of the latter in developing cancer vasculogenesis models. Furthermore, it explores applications in pathological investigations, preclinical medication screening for personalized treatment and cancer diagnostics, and envisages future prospects for 3D bioprinted cancer vasculogenesis models. Despite notable advancements, current 3D bioprinting techniques for cancer vasculogenesis modeling have several limitations. Nonetheless, by overcoming these challenges and with technological advances, 3D bioprinting exhibits immense potential for revolutionizing the understanding of cancer vasculogenesis and augmenting treatment modalities.

Harnessing gastrointestinal organoids for cancer therapy.

Gastrointestinal organoids have emerged as a model system that authentically recapitulates the in vivo situation. Despite biomedical and technical challenges, self-assembled 3D structures derived from pluripotent stem cells or healthy and diseased tissues have proved to be invaluable tools for cancer drug discovery, disease modeling, and studying infection with carcinogenic pathogens.

Organoids in ovarian cancer: a platform for disease modeling, precision medicine, and drug assessment.

Ovarian cancer (OC) is a major cause of gynecological cancer mortality, necessitating enhanced research. Organoids, cellular clusters grown in 3D model, have emerged as a disruptive paradigm, transcending the limitations inherent to conventional models by faithfully recapitulating key morphological, histological, and genetic attributes. This review undertakes a comprehensive exploration of the potential in organoids derived from murine, healthy population, and patient origins, encompassing a spectrum that spans foundational principles to pioneering applications. Organoids serve as preclinical models, allowing us to predict how patients will respond to treatments and guiding the development of personalized therapies. In the context of evaluating new drugs, organoids act as versatile platforms, enabling thorough testing of innovative combinations and novel agents. Remarkably, organoids mimic the dynamic nature of OC progression, from its initial formation to the spread to other parts of the body, shedding light on intricate details that hold significant importance. By functioning at an individualized level, organoids uncover the complex mechanisms behind drug resistance, revealing strategic opportunities for effective treatments.

Radiation Therapy for Stage IIA/B Seminoma: Modeling Secondary Cancer Risk for Protons and VMAT versus 3D Photons.

Radiation therapy (RT) is an effective treatment for stage IIA and select stage IIB seminomas. However, given the long life expectancy of seminoma patients, there are concerns about the risk of secondary cancers from RT. This study assessed differences in secondary cancer risk for stage II seminoma patients following proton pencil-beam scanning (PBS) and photon VMAT, compared to 3D conformal photon RT. Ten seminoma patients, five with a IIA staging who received 30 GyRBE and five with a IIB staging who received 36 GyRBE, had three RT plans generated. Doses to organs at risk (OAR) were evaluated, and secondary cancer risks were calculated as the Excess Absolute Risk (EAR) and Lifetime Attributable Risk (LAR). PBS reduced the mean OAR dose by 60% on average compared to 3D, and reduced the EAR and LAR for all OAR, with the greatest reductions seen for the bowel, liver, and stomach. VMAT reduced high doses but increased the low-dose bath, leading to an increased EAR and LAR for some OAR. PBS provided superior dosimetric sparing of OAR compared to 3D and VMAT in stage II seminoma cases, with models demonstrating that this may reduce secondary cancer risk. Therefore, proton therapy shows the potential to reduce acute and late side effects of RT for this population.

Applications of CRISPR-Cas9 for advancing precision medicine in oncology: from target discovery to disease modeling.

The clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein 9 (Cas9) (CRISPR/Cas9) system is a powerful tool that enables precise and efficient gene manipulation. In a relatively short time, CRISPR has risen to become the preferred gene-editing system due to its high efficiency, simplicity, and programmability at low costs. Furthermore, in the recent years, the CRISPR toolkit has been rapidly expanding, and the emerging advancements have shown tremendous potential in uncovering molecular mechanisms and new therapeutic strategies for human diseases. In this review, we provide our perspectives on the recent advancements in CRISPR technology and its impact on precision medicine, ranging from target identification, disease modeling, and diagnostics. We also discuss the impact of novel approaches such as epigenome, base, and prime editing on preclinical cancer drug discovery.

A Novel NCI-H69AR Drug-Resistant Small-Cell Lung Cancer Mini-Tumor Model for Anti-Cancer Treatment Screening.

Small-cell lung cancer is a fast-growing carcinoma with a poor prognosis and a high level of relapse due to multi-drug resistance (MDR). Genetic mutations that lead to the overexpression of efflux transporter proteins can contribute to MDR. In vitro cancer models play a tremendous role in chemotherapy development and the screening of possible anti-cancer molecules. Low-cost and simple in vitro models are normally used. Traditional two-dimensional (2D) models have numerous shortcomings when considering the physiological resemblance of an in vivo setting. Three-dimensional (3D) models aim to bridge the gap between conventional 2D models and the in vivo setting. Some of the advantages of functional 3D spheroids include better representation of the in vivo physiology and tumor characteristics when compared to traditional 2D cultures. During this study, an NCI-H69AR drug-resistant mini-tumor model (MRP1 hyperexpressive) was developed by making use of a rotating clinostat bioreactor system (ClinoStar®; CelVivo ApS, Odense, Denmark). Spheroid growth and viability were assessed over a 25-day period to determine the ideal experimental period with mature and metabolically stable constructs. The applicability of this model for anti-cancer research was evaluated through treatment with irinotecan, paclitaxel and cisplatin for 96 h, followed by a 96 h recovery period. Parameters measured included planar surface area measurements, estimated glucose consumption, soluble protein content, intracellular adenosine triphosphate levels, extracellular adenylate kinase levels, histology and efflux transporter gene expression. The established functional spheroid model proved viable and stable during the treatment period, with retained relative hyperexpression of the MRP1 efflux transporter gene but increased expression of the P-gp transporter gene compared to the cells cultured in 2D. As expected, treatment with the abovementioned anti-cancer drugs at clinical doses (100 mg/m2 irinotecan, 80 mg/m2 paclitaxel and 75 mg/m2 cisplatin) had minimal impact on the drug-resistant mini-tumors, and the functional spheroid models were able to recover following the removal of treatment.

Cell Reprogramming Techniques: Contributions to Cancer Therapy.

The reprogramming of terminally differentiated cells over the past few years has become important for induced pluripotent stem cells (iPSCs) in the field of regenerative medicine and disease drug modeling. At the same time, iPSCs have also played an important role in human cancer research. iPSCs derived from cancer patients can be used to simulate the early progression of cancer, for drug testing, and to study the molecular mechanism of cancer occurrence. In recent years, with the application of cellular immunotherapy in cancer therapy, patient-derived iPSC-induced immune cells (T, natural killer, and macrophage cells) solve the problem of immune rejection and have higher immunogenicity, which greatly improves the therapeutic efficiency of immune cell therapy. With the continuous progress of cancer differentiation therapy, iPSC technology can reprogram cancer cells to a more primitive pluripotent undifferentiated state, and successfully reverse cancer cells to a benign phenotype by changing the epigenetic inheritance of cancer cells. This article reviews the recent progress of cell reprogramming technology in human cancer research, focuses on the application of reprogramming technology in cancer immunotherapy and the problems solved, and summarizes the malignant phenotype changes of cancer cells in the process of reprogramming and subsequent differentiation.

Breast cancer brain metastasis: from etiology to state-of-the-art modeling.

Currently, breast carcinoma is the most common form of malignancy and the main cause of cancer mortality in women worldwide. The metastasis of cancer cells from the primary tumor site to other organs in the body, notably the lungs, bones, brain, and liver, is what causes breast cancer to ultimately be fatal. Brain metastases occur in as many as 30% of patients with advanced breast cancer, and the 1-year survival rate of these patients is around 20%. Many researchers have focused on brain metastasis, but due to its complexities, many aspects of this process are still relatively unclear. To develop and test novel therapies for this fatal condition, pre-clinical models are required that can mimic the biological processes involved in breast cancer brain metastasis (BCBM). The application of many breakthroughs in the area of tissue engineering has resulted in the development of scaffold or matrix-based culture methods that more accurately imitate the original extracellular matrix (ECM) of metastatic tumors. Furthermore, specific cell lines are now being used to create three-dimensional (3D) cultures that can be used to model metastasis. These 3D cultures satisfy the requirement for in vitro methodologies that allow for a more accurate investigation of the molecular pathways as well as a more in-depth examination of the effects of the medication being tested. In this review, we talk about the latest advances in modeling BCBM using cell lines, animals, and tissue engineering methods.

In vitro modeling of hepatocellular carcinoma niche on decellularized tomato thorny leaves: a novel natural three-dimensional (3D) scaffold for liver cancer therapeutics.

Liver cancer is now one of the main causes leading to death worldwide. To achieve reliable therapeutic effects, it is crucial to develop efficient approaches to test novel anticancer drugs. Considering the significant contribution of tumor microenvironment to cell's response to medications, in vitro 3D bioinspiration of cancer cell niches can be regarded as an advanced strategy to improve the accuracy and reliability of the drug-based treatment. In this regard, decellularized plant tissues can perform as suitable 3D scaffolds for mammalian cell culture to create a near-to-real condition to test drug efficacy. Here, we developed a novel 3D natural scaffold made from decellularized tomato hairy leaves (hereafter called as DTL) to mimic the microenvironment of human hepatocellular carcinoma (HCC) for pharmaceutical purposes. The surface hydrophilicity, mechanical properties, and topography measurement and molecular analyses revealed that the 3D DTL scaffold is an ideal candidate for liver cancer modeling. The cells exhibited a higher growth and proliferation rate within the DTL scaffold, as verified by quantifying the expression of related genes, DAPI staining, and SEM imaging of the cells. Moreover, prilocaine, an anticancer drug, showed a higher effectiveness against the cancer cells cultured on the 3D DTL scaffold, compared to a 2D platform. Taken together, this new cellulosic 3D scaffold can be confidently proposed for chemotherapeutic testing of drugs on hepatocellular carcinoma.

Toward Practical Integration of Omic and Imaging Data in Co-Clinical Trials.

Co-clinical trials are the concurrent or sequential evaluation of therapeutics in both patients clinically and patient-derived xenografts (PDX) pre-clinically, in a manner designed to match the pharmacokinetics and pharmacodynamics of the agent(s) used. The primary goal is to determine the degree to which PDX cohort responses recapitulate patient cohort responses at the phenotypic and molecular levels, such that pre-clinical and clinical trials can inform one another. A major issue is how to manage, integrate, and analyze the abundance of data generated across both spatial and temporal scales, as well as across species. To address this issue, we are developing MIRACCL (molecular and imaging response analysis of co-clinical trials), a web-based analytical tool. For prototyping, we simulated data for a co-clinical trial in "triple-negative" breast cancer (TNBC) by pairing pre- (T0) and on-treatment (T1) magnetic resonance imaging (MRI) from the I-SPY2 trial, as well as PDX-based T0 and T1 MRI. Baseline (T0) and on-treatment (T1) RNA expression data were also simulated for TNBC and PDX. Image features derived from both datasets were cross-referenced to omic data to evaluate MIRACCL functionality for correlating and displaying MRI-based changes in tumor size, vascularity, and cellularity with changes in mRNA expression as a function of treatment.

The Mathematical modeling of Cancer growth and angiogenesis by an individual based interacting system.

We present a mathematical model for the complex system for the growth of a solid tumor. The system embeds proliferation of cells depending on the surrounding oxygen field, hypoxia caused by insufficient oxygen when the tumor reaches a certain size, consequent VEGF release and angiogenic new vasculature growth, re-oxygenation of the tumor and subsequent tumor growth restart. Specifically cancerous cells are represented by individual units, interacting as proliferating particles of a solid body, oxygen, and VEGF are fields with a source and a sink, and new angiogenic vasculature is described by a network of growing curves. The model, as shown by numerical simulations, captures both the time-evolution of the tumor growth before and after angiogenesis and its spatial properties, with different distribution of proliferating and hypoxic cells in the external and deep layers of the tumor, and the spatial structure of the angiogenic network. The microscopic description of the growth opens the possibility of tuning the model to patient-specific scenarios.

A Porous Gelatin Methacrylate-Based Material for 3D Cell-Laden Constructs.

3D constructs are fundamental in tissue engineering and cancer modeling, generating a demand for tailored materials creating a suitable cell culture microenvironment and amenable to be bioprinted. Gelatin methacrylate (GelMA) is a well-known functionalized natural polymer with good printability and binding motifs allowing cell adhesion; however, its tight micropores induce encapsulated cells to retain a non-physiological spherical shape. To overcome this problem, blended GelMa is here blended with Pluronic F-127 (PLU) to modify the hydrogel internal porosity by inducing the formation of larger mesoscale pores. The change in porosity also leads to increased swelling and a slight decrease in Young's modulus. All blends form stable hydrogels both when cast in annular molds and bioprinted in complex structures. Embedded cells maintain high viability, and while Neuroblastoma cancer cells typically aggregate inside the mesoscale pores, Mesenchymal Stem Cells stretch in all three dimensions, forming cell-cell and cell-ECM interactions. The results of this work prove that the combination of tailored porous materials with bioprinting techniques enables to control both the micro and macro architecture of cell-laden constructs, a fundamental aspect for the development of clinically relevant in vitro constructs.

Bio-Mechanical Model of Osteosarcoma Tumor Microenvironment: A Porous Media Approach.

Osteosarcoma is the most common malignant bone tumor in children and adolescents with a poor prognosis. To describe the progression of osteosarcoma, we expanded a system of data-driven ODE from a previous study into a system of Reaction-Diffusion-Advection (RDA) equations and coupled it with Biot equations of poroelasticity to form a bio-mechanical model. The RDA system includes the spatio-temporal information of the key components of the tumor microenvironment. The Biot equations are comprised of an equation for the solid phase, which governs the movement of the solid tumor, and an equation for the fluid phase, which relates to the motion of cells. The model predicts the total number of cells and cytokines of the tumor microenvironment and simulates the tumor's size growth. We simulated different scenarios using this model to investigate the impact of several biomedical settings on tumors' growth. The results indicate the importance of macrophages in tumors' growth. Particularly, we have observed a high co-localization of macrophages and cancer cells, and the concentration of tumor cells increases as the number of macrophages increases.

CRISPR/Cas9 as precision and high-throughput genetic engineering tools in gastrointestinal cancer research and therapy.

Gastrointestinal cancer (GI) is one of the most serious and health-threatening diseases worldwide. Many countries have encountered an escalating prevalence of shock. Therefore, there is a pressing need to clarify the molecular pathogenesis of these cancers. The use of high-throughput technologies that allow the precise and simultaneous investigation of thousands of genes, proteins, and metabolites is a critical step in disease diagnosis and cure. Recent innovations have provided easy and reliable methods for genome investigation, including TALENs, ZFNs, and the CRISPR/Cas9 (clustered regularly interspaced palindromic repeats system). Among these, CRISPR/Cas9 has been revolutionary tool in genetic research. Recent years were prosperous years for CRISPR by the discovery of novel Cas enzymes, the Nobel Prize, and the development of critical clinical trials. This technology utilizes comprehensive information on genes associated with tumor development, provides high-throughput libraries for tumor therapy by developing screening platforms, and generates rapid tools for cancer therapy. This review discusses the various applications of CRISPR/Cas9 in genome editing, with a particular focus on genome manipulation, including infection-related genes, RNAi targets, pooled library screening for identification of unknown driver mutations, and molecular targets for gastrointestinal cancer modeling. Finally, it provides an overview of CRISPR/Cas9 clinical trials, as well as the challenges associated with its use.

Recent Advances of Organ-on-a-Chip in Cancer Modeling Research.

Although many studies have focused on oncology and therapeutics in cancer, cancer remains one of the leading causes of death worldwide. Due to the unclear molecular mechanism and complex in vivo microenvironment of tumors, it is challenging to reveal the nature of cancer and develop effective therapeutics. Therefore, the development of new methods to explore the role of heterogeneous TME in individual patients' cancer drug response is urgently needed and critical for the effective therapeutic management of cancer. The organ-on-chip (OoC) platform, which integrates the technology of 3D cell culture, tissue engineering, and microfluidics, is emerging as a new method to simulate the critical structures of the in vivo tumor microenvironment and functional characteristics. It overcomes the failure of traditional 2D/3D cell culture models and preclinical animal models to completely replicate the complex TME of human tumors. As a brand-new technology, OoC is of great significance for the realization of personalized treatment and the development of new drugs. This review discusses the recent advances of OoC in cancer biology studies. It focuses on the design principles of OoC devices and associated applications in cancer modeling. The challenges for the future development of this field are also summarized in this review. This review displays the broad applications of OoC technique and has reference value for oncology development.

The Tumor Invasion Paradox in Cancer Stem Cell-Driven Solid Tumors.

Cancer stem cells (CSCs) are key in understanding tumor growth and tumor progression. A counterintuitive effect of CSCs is the so-called tumor growth paradox: the effect where a tumor with a higher death rate may grow larger than a tumor with a lower death rate. Here we extend the modeling of the tumor growth paradox by including spatial structure and considering cancer invasion. Using agent-based modeling and a corresponding partial differential equation model, we demonstrate and prove mathematically a tumor invasion paradox: a larger cell death rate can lead to a faster invasion speed. We test this result on a generic hypothetical cancer with typical growth rates and typical treatment sensitivities. We find that the tumor invasion paradox may play a role for continuous and intermittent treatments, while it does not seem to be essential in fractionated treatments. It should be noted that no attempt was made to fit the model to a specific cancer, thus, our results are generic and theoretical.

A cancer model with nonlocal free boundary dynamics.

Cancer cells at the tumor boundary move in the direction of the oxygen gradient, while cancer cells far within the tumor are in a necrotic state. This paper introduces a simple mathematical model that accounts for these facts. The model consists of cancer cells, cytotoxic T cells, and oxygen satisfying a system of partial differential equations. Some of the model parameters represent the effect of anti-cancer drugs. The tumor boundary is a free boundary whose dynamics is determined by the movement of cancer cells at the boundary. The model is simulated for radially symmetric and axially symmetric tumors, and it is shown that the tumor may increase or decrease in size, depending on the "strength" of the drugs. Existence theorems are proved, global in-time in the radially symmetric case, and local in-time for any shape of tumor. In the radially symmetric case, it is proved, under different conditions, that the tumor may shrink monotonically, or expand monotonically.

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

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

Endogenous spacing enables co-processing of microRNAs and efficient combinatorial RNAi.

We present Multi-miR, a microRNA-embedded shRNA system modeled after endogenous microRNA clusters that enables simultaneous expression of up to three or four short hairpin RNAs (shRNAs) from a single promoter without loss of activity, enabling robust combinatorial RNA interference (RNAi). We further developed complementary all-in-one vectors that are over one log-scale more sensitive to doxycycline-mediated activation in vitro than previous methods and resistant to shRNA inactivation in vivo. We demonstrate the utility of this system for intracranial expression of shRNAs in a glioblastoma model. Additionally, we leverage this platform to target the redundant RAF signaling node in a mouse model of KRAS-mutant cancer and show that robust combinatorial synthetic lethality efficiently abolishes tumor growth.