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Tumors can induce systemic disturbances in distant organs, leading to physiological changes that enhance host morbidity. In Drosophila cancer models, tumors have been known for decades to cause hypervolemic "bloating" of the abdominal cavity. Here we use allograft and transgenic tumors to show that hosts display fluid retention associated with autonomously defective secretory capacity of fly renal tubules, which function analogous to those of the human kidney. Excretion from these organs is blocked by abnormal cells that originate from inappropriate activation of normally quiescent renal stem cells (RSCs). Blockage is initiated by IL-6-like oncokines that perturb renal water-transporting cells and trigger a damage response in RSCs that proceeds pathologically. Thus, a chronic inflammatory state produced by the tumor causes paraneoplastic fluid dysregulation by altering cellular homeostasis of host renal units.

Bladder cancer (BCa) poses a significant health challenge, particularly affecting men with higher incidence and mortality rates. Addressing the need for improved predictive models in BCa treatment, this study introduces an innovative 3D in vitro patient-derived bladder cancer tumor model, utilizing decellularized pig bladders as scaffolds. Traditional 2D cell cultures, insufficient in replicating tumor microenvironments, have driven the development of sophisticated 3D models. The study successfully achieved pig bladder decellularization through multiple cycles of immersion in salt solutions, resulting in notable macroscopic and histological changes. This process confirmed the removal of cellular components while preserving the native extracellular matrix (ECM). Quantitative analysis demonstrated the efficacy of decellularization, with a remarkable reduction in DNA concentration, signifying the removal of over 95% of cellular material. In the development of the in vitro bladder cancer model, muscle invasive bladder cancer patients' cells were cultured within decellularized pig bladders, yielding a three-dimensional cancer model. Optimal results were attained using an air–liquid interface technique, with cells injected directly into the scaffold at three distinct time points. Histological evaluations showcased characteristics resembling in vivo tumors derived from bladder cancer patients' cells. To demonstrate the 3D cancer model's effectiveness as a drug screening platform, the study treated it with Cisplatin (Cis), Gemcitabine (Gem), and a combination of both drugs. Comprehensive cell viability assays and histological analyses illustrated changes in cell survival and proliferation. The model exhibited promising correlations with clinical outcomes, boasting an 83.3% reliability rate in predicting treatment responses. Comparison with traditional 2D cultures and spheroids underscored the 3D model's superiority in reliability, with an 83.3% predictive capacity compared to 50% for spheroids and 33.3% for 2D culture. Acknowledging limitations, such as the absence of immune and stromal components, the study suggests avenues for future improvements. In conclusion, this innovative 3D bladder cancer model, combining decellularization and patient-derived cells, marks a significant advancement in preclinical drug testing. Its potential for predicting treatment outcomes and capturing patient-specific responses opens new avenues for personalized medicine in bladder cancer therapeutics. Future refinements and validations with larger patient cohorts hold promise for revolutionizing BCa research and treatment strategies. [ABSTRACT FROM AUTHOR]

Tumors can induce systemic disturbances in distant organs, leading to physiological changes that enhance host morbidity. In Drosophila cancer models, tumors have been known for decades to cause hypervolemic "bloating" of the abdominal cavity. Here we use allograft and transgenic tumors to show that hosts display fluid retention associated with autonomously defective secretory capacity of fly renal tubules, which function analogous to those of the human kidney. Excretion from these organs is blocked by abnormal cells that originate from inappropriate activation of normally quiescent renal stem cells (RSCs). Blockage is initiated by IL-6- like oncokines that perturb renal water-transporting cells and trigger a damage response in RSCs that proceeds pathologically. Thus, a chronic inflammatory state produced by the tumor causes paraneoplastic fluid dysregulation by altering cellular homeostasis of host renal units. [ABSTRACT FROM AUTHOR]

Abstract Bladder cancer (BCa) poses a significant health challenge, particularly affecting men with higher incidence and mortality rates. Addressing the need for improved predictive models in BCa treatment, this study introduces an innovative 3D in vitro patient-derived bladder cancer tumor model, utilizing decellularized pig bladders as scaffolds. Traditional 2D cell cultures, insufficient in replicating tumor microenvironments, have driven the development of sophisticated 3D models. The study successfully achieved pig bladder decellularization through multiple cycles of immersion in salt solutions, resulting in notable macroscopic and histological changes. This process confirmed the removal of cellular components while preserving the native extracellular matrix (ECM). Quantitative analysis demonstrated the efficacy of decellularization, with a remarkable reduction in DNA concentration, signifying the removal of over 95% of cellular material. In the development of the in vitro bladder cancer model, muscle invasive bladder cancer patients’ cells were cultured within decellularized pig bladders, yielding a three-dimensional cancer model. Optimal results were attained using an air–liquid interface technique, with cells injected directly into the scaffold at three distinct time points. Histological evaluations showcased characteristics resembling in vivo tumors derived from bladder cancer patients’ cells. To demonstrate the 3D cancer model’s effectiveness as a drug screening platform, the study treated it with Cisplatin (Cis), Gemcitabine (Gem), and a combination of both drugs. Comprehensive cell viability assays and histological analyses illustrated changes in cell survival and proliferation. The model exhibited promising correlations with clinical outcomes, boasting an 83.3% reliability rate in predicting treatment responses. Comparison with traditional 2D cultures and spheroids underscored the 3D model’s superiority in reliability, with an 83.3% predictive capacity compared to 50% for spheroids and 33.3% for 2D culture. Acknowledging limitations, such as the absence of immune and stromal components, the study suggests avenues for future improvements. In conclusion, this innovative 3D bladder cancer model, combining decellularization and patient-derived cells, marks a significant advancement in preclinical drug testing. Its potential for predicting treatment outcomes and capturing patient-specific responses opens new avenues for personalized medicine in bladder cancer therapeutics. Future refinements and validations with larger patient cohorts hold promise for revolutionizing BCa research and treatment strategies.

Abstract In order to comprehend the dynamics of disease propagation within a society, mathematical formulations are essential. The purpose of this work is to investigate the diagnosis and treatment of lung cancer in persons with weakened immune systems by introducing cytokines ( $$ IL_{2} \& IL_{12}$$ I L 2 & I L 12 ) and anti-PD-L1 inhibitors. To find the stable position of a recently built system TCD $$IL_{2} IL_{12}$$ I L 2 I L 12 Z, a qualitative and quantitative analysis are taken under sensitive parameters. Reliable bounded findings are ensured by examining the generated system’s boundedness, positivity, uniqueness, and local stability analysis, which are the crucial characteristics of epidemic models. The positive solutions with linear growth are shown to be verified by the global derivative, and the rate of impact across every sub-compartment is determined using Lipschitz criteria. Using Lyapunov functions with first derivative, the system’s global stability is examined in order to evaluate the combined effects of cytokines and anti-PD-L1 inhibitors on people with weakened immune systems. Reliability is achieved by employing the Mittag-Leffler kernel in conjunction with a fractal-fractional operator because FFO provide continuous monitoring of lung cancer in multidimensional way. The symptomatic and asymptomatic effects of lung cancer sickness are investigated using simulations in order to validate the relationship between anti-PD-L1 inhibitors, cytokines, and the immune system. Also, identify the actual state of lung cancer control with early diagnosis and therapy by introducing cytokines and anti-PD-L1 inhibitors, which aid in the patients’ production of anti-cancer cells. Investigating the transmission of illness and creating control methods based on our validated results will both benefit from this kind of research.

In order to comprehend the dynamics of disease propagation within a society, mathematical formulations are essential. The purpose of this work is to investigate the diagnosis and treatment of lung cancer in persons with weakened immune systems by introducing cytokines ( I L 2 & I L 12 ) and anti-PD-L1 inhibitors. To find the stable position of a recently built system TCD I L 2 I L 12 Z, a qualitative and quantitative analysis are taken under sensitive parameters. Reliable bounded findings are ensured by examining the generated system’s boundedness, positivity, uniqueness, and local stability analysis, which are the crucial characteristics of epidemic models. The positive solutions with linear growth are shown to be verified by the global derivative, and the rate of impact across every sub-compartment is determined using Lipschitz criteria. Using Lyapunov functions with first derivative, the system’s global stability is examined in order to evaluate the combined effects of cytokines and anti-PD-L1 inhibitors on people with weakened immune systems. Reliability is achieved by employing the Mittag-Leffler kernel in conjunction with a fractal-fractional operator because FFO provide continuous monitoring of lung cancer in multidimensional way. The symptomatic and asymptomatic effects of lung cancer sickness are investigated using simulations in order to validate the relationship between anti-PD-L1 inhibitors, cytokines, and the immune system. Also, identify the actual state of lung cancer control with early diagnosis and therapy by introducing cytokines and anti-PD-L1 inhibitors, which aid in the patients’ production of anti-cancer cells. Investigating the transmission of illness and creating control methods based on our validated results will both benefit from this kind of research. [ABSTRACT FROM AUTHOR]

Tumour is a very serious and dangerous health risk, which is defined as a mass or lump of tissue formalized by the aggregation of abnormal cells. In this paper, we have presented a comparative and chaotic investigation of tumour and effector cells using non-integer order tumour immune dynamical model. Also, we have looked at the interactions between different tumour cell populations and immunological composition using a model of a real-world medical research problem. Additionally, stability analysis of the proposed model is established with the help of fixed-point iteration. Further bifurcation diagrams, as well as phase portraits, have been used to study the proposed system numerically and to analyse its behaviour. For numerical simulations, we have used the Hermite wavelet operational matrix and Taufik-Atangana methods using Caputo fractional derivatives. models. The main objective of the paper is to convert nonlinear fractional systems into algebraic equations. Our findings will be valuable to biologists in cancer treatment.

Cancer is a group of diseases in which cells grow uncontrollably and can spread into other tissues. Various studies consider the interactions between cancer cells and the immune system as well as different types of treatment. Mathematical models have been used to study the growth of cancerous cells. We study a fractional order model that describes some aspects of the interactions among host, effector immune, and cancer cells. A drug treatment is considered to analyse the cancerous cells proliferation. Due to the chemotherapy, we split the fractional equation of the cancerous cells into drug sensitivity and resistance. We show that not only the chemotherapy but also the drug resistance plays an important role in the growth rate of cancer cells. [ABSTRACT FROM AUTHOR]

Cancer is the world’s second-biggest cause of death, accounting for roughly 10 million deaths in 2020 and estimated to reach 16 million by 2040. In this study, we propose a novel technique for the treatment of tumor models with a power-law kernel with the Sumudu transform. The analysis was made for a generalized form of analytical solution that is unique and Picard K-stable by using Hilbert and Banach space results. The model investigates the Ulam-Hyers-Rassias stability, uniqueness of solutions, and impact of fractional derivatives with the power-law kernel. Reproductive number analysis with an equilibrium point shows the bounded solution in the feasible region. In the end, numerical simulations are drawn through figures at different fractional and fractal dimensions for the dynamics of treatment and the growth of normal cells. The analysis shows crucial criteria for system stability, ensuring the efficacy of therapeutic interventions through novel mathematical and biological insights. [ABSTRACT FROM AUTHOR]

We examine the ultimate dynamics of the four-dimensional model describing interactions between host cells, immune cells, tumor cells, and immune-tumor conjugate cells proposed by Abernethy and Gooding in 2018. In our paper, the ultimate upper bounds for all variables of this model are obtained. Formulas for positively invariant sets are deduced. Using these results, we establish conditions for the existence of the global attractor, derive formulas for its location, and present conditions under which immune and immune-tumor conjugate cells asymptotically die out. Next, we study equilibrium points, including the stability property for most of the equilibrium points. We discuss the existence of very low cancer-burden equilibrium points. Next, parametric conditions are derived under which the derivative of the density of the immune-tumor conjugate cell population eventually tends to zero; this mathematically rigorously confirms the correctness of the application of model reduction for this model in studies of its ultimate dynamics. In the final section, we summarize the results of this work and outline how to continue this study. [ABSTRACT FROM AUTHOR]

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Methods accurately predicting the responses of colorectal cancer (CRC) and colorectal cancer liver metastasis (CRLM) to personalized chemotherapy remain limited due to tumor heterogeneity. This study introduces an innovative patient‐derived CRC and CRLM tumor model for preclinical investigation, utilizing 3d‐bioprinting (3DP) technology. Efficient construction of homogeneous in vitro 3D models of CRC/CRLM is achieved through the application of patient‐derived primary tumor cells and 3D bioprinting with bioink. Genomic and histological analyses affirm that the CRC/CRLM 3DP tumor models effectively retain parental tumor biomarkers and mutation profiles. In vitro tests evaluating chemotherapeutic drug sensitivities reveal substantial tumor heterogeneity in chemotherapy responses within the 3DP CRC/CRLM models. Furthermore, a robust correlation is evident between the drug response in the CRLM 3DP model and the clinical outcomes of neoadjuvant chemotherapy. These findings imply a significant potential for the application of patient‐derived 3DP cancer models in precision chemotherapy prediction and preclinical research for CRC/CRLM. [ABSTRACT FROM AUTHOR]

Canine hemangiosarcoma (HSA) is a highly malignant tumor derived from hematopoietic stem cells and commonly occurs in visceral organs or skin. Visceral HSAs are particularly aggressive and progress rapidly despite multimodal treatment. Tumor-associated macrophages (TAMs) play a central role in carcinogenesis, tumor progression, and metastasis in humans and murine models. In this retrospective study, we investigated the prevalence and phenotype of TAMs in privately owned, treatment-naïve dogs with naturally occurring HSA. We used CD204 as a general macrophage marker and CD206 as a marker for M2-polarized macrophages. Formalin-fixed paraffin-embedded tissues from HSAs in the spleen (n = 9), heart (n = 6), and other locations (n = 12) from 17 dogs were sectioned and immunohistochemically labeled with CD204 and CD206 antibodies. The mean number of log(CD204)- and log(CD206)-positive cells and the ratio of log(CD206/CD204)-positive cells were compared with normal surrounding tissues and between tumor locations. There were significantly more macrophages and M2 macrophages, and a higher ratio of M2 macrophages to total macrophages in tumor hot spots (P =.0002, P <.0001, and P =.0002, respectively) and in tumor tissues outside of hot spots (P =.009, P =.002, and P =.007, respectively) than in normal surrounding tissues. There were no significant differences between tumor locations, but there was a trend toward higher numbers of CD204-positive macrophages within the splenic tumors. There was no association between histological parameters or clinical stage and TAM numbers or phenotype. As in humans, TAMs in dogs with HSA have a predominantly M2-skewed phenotype. Dogs with HSA could serve as excellent models to evaluate new TAM-reprogramming therapies. [ABSTRACT FROM AUTHOR]

In this paper, a biophysical fractional diffusive cancer model with virotherapy is thoroughly analyzed and analytically simulated. The goal of this biophysical model is to represent both the dynamics of cancer development and the results of virotherapy, which uses viruses to target and destroy cancer cells. The Caputo sense is applied to the fractional derivatives. We look at the governing model's existence and uniqueness. For analytical solutions, the Laplace residual power series approach is used. The study investigates the model's dynamic behavior, shedding light on the development of cancer and the effects of virotherapy. The research advances our knowledge of cancer modeling and treatment options. Numerical simulations show the agreement between the analytical results and the related numerical solutions, proving the usefulness of the analytical solution.

Cancer patients often die from symptoms that manifest at a distance from any tumor. Mechanisms underlying these systemic physiological perturbations, called paraneoplastic syndromes, may benefit from investigation in non-mammalian systems. Using a non-metastatic Drosophila adult model, we find that malignant-tumor-produced cytokines drive widespread host activation of JAK-STAT signaling and cause premature lethality. STAT activity is particularly high in cells of the blood-brain barrier (BBB), where it induces aberrant BBB permeability. Remarkably, inhibiting STAT in the BBB not only rescues barrier function but also extends the lifespan of tumor-bearing hosts. We identify BBB damage in other pathological conditions that cause elevated inflammatory signaling, including obesity and infection, where BBB permeability also regulates host survival. IL-6-dependent BBB dysfunction is further seen in a mouse tumor model, and it again promotes host morbidity. Therefore, BBB alterations constitute a conserved lethal tumor-host interaction that also underlies other physiological morbidities.

Abstract Methods accurately predicting the responses of colorectal cancer (CRC) and colorectal cancer liver metastasis (CRLM) to personalized chemotherapy remain limited due to tumor heterogeneity. This study introduces an innovative patient‐derived CRC and CRLM tumor model for preclinical investigation, utilizing 3d‐bioprinting (3DP) technology. Efficient construction of homogeneous in vitro 3D models of CRC/CRLM is achieved through the application of patient‐derived primary tumor cells and 3D bioprinting with bioink. Genomic and histological analyses affirm that the CRC/CRLM 3DP tumor models effectively retain parental tumor biomarkers and mutation profiles. In vitro tests evaluating chemotherapeutic drug sensitivities reveal substantial tumor heterogeneity in chemotherapy responses within the 3DP CRC/CRLM models. Furthermore, a robust correlation is evident between the drug response in the CRLM 3DP model and the clinical outcomes of neoadjuvant chemotherapy. These findings imply a significant potential for the application of patient‐derived 3DP cancer models in precision chemotherapy prediction and preclinical research for CRC/CRLM.

In this work, we analyze the effects of fractional derivatives in the chaotic dynamics of a cancer model. We begin by studying the dynamics of a standard model, i.e., with integer derivatives. We study the dynamical behavior by means of the bifurcation diagram, Lyapunov exponents, and recurrence quantification analysis (RQA), such as the recurrence rate (RR), the determinism (DET), and the recurrence time entropy (RTE). We find a high correlation coefficient between the Lyapunov exponents and RTE. Our simulations suggest that the tumor growth parameter ( ρ 1 ) is associated with a chaotic regime. Our results suggest a high correlation between the largest Lyapunov exponents and RTE. After understanding the dynamics of the model in the standard formulation, we extend our results by considering fractional operators. We fix the parameters in the chaotic regime and investigate the effects of the fractional order. We demonstrate how fractional dynamics can be properly characterized using RQA measures, which offer the advantage of not requiring knowledge of the fractional Jacobian matrix. We find that the chaotic motion is suppressed as α decreases, and the system becomes periodic for α ⪅ 0.9966 . We observe limit cycles for α ∈ (0.9966 , 0.899) and fixed points for α < 0.899 . The fixed point is determined analytically for the considered parameters. Finally, we discover that these dynamics are separated by an exponential relationship between α and ρ 1 . Also, the transition depends on a supper transient which obeys the same relationship. [ABSTRACT FROM AUTHOR]

The Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein 9 (CRISPR/Cas9) system, an RNA-based adaptive immune system found in bacteria and archaea, has catalyzed the development and application of a new generation of gene editing tools. Numerous studies have shown that this system can precisely target a wide range of human genes, including those associated with diseases such as cancer. In cancer research, the intricate genetic mutations in tumors have promoted extensive utilization of the CRISPR/Cas9 system due to its efficient and accurate gene editing capabilities. This includes improvements in Chimeric Antigen Receptor (CAR)-T-cell therapy, the establishment of tumor models, and gene and drug target screening. Such progress has propelled the investigation of cancer molecular mechanisms and the advancement of precision medicine. However, the therapeutic potential of genome editing remains underexplored, and lingering challenges could elevate the risk of additional genetic mutations. Here, we elucidate the fundamental principles of CRISPR/Cas9 gene editing and its practical applications in tumor research. We also briefly discuss the primary challenges faced by CRISPR technology and existing solutions, intending to enhance the efficacy of this gene editing therapy and shed light on the underlying mechanisms of tumors. [ABSTRACT FROM AUTHOR]

In this paper we consider the ultimate dynamics of one 4D cancer model which was created for studying the immune response to the two-phenotype tumors. Our approach is based on the localization method of compact invariant sets. The existence of a positively invariant polytope is shown and its size is calculated depending on the parameters of this cancer model. Various convergence conditions to the tumor free equilibrium point were proposed. This property has the biological meaning of global asymptotic tumor eradication (GATE). Further, the case in which local asymptotic tumor eradication (LATE) conditions entail GATE conditions was found. Our theoretical studies of ultimate dynamics are complemented by numerical simulation results. [ABSTRACT FROM AUTHOR]

In this paper, a biophysical fractional diffusive cancer model with virotherapy is thoroughly analyzed and analytically simulated. The goal of this biophysical model is to represent both the dynamics of cancer development and the results of virotherapy, which uses viruses to target and destroy cancer cells. The Caputo sense is applied to the fractional derivatives. We look at the governing model's existence and uniqueness. For analytical solutions, the Laplace residual power series approach is used. The study investigates the model's dynamic behavior, shedding light on the development of cancer and the effects of virotherapy. The research advances our knowledge of cancer modeling and treatment options. Numerical simulations show the agreement between the analytical results and the related numerical solutions, proving the usefulness of the analytical solution. [ABSTRACT FROM AUTHOR]

From pre-historic era, all scientific discoveries have evolved around a concept – THINK BIG but for a change zebrafish as a model organism in research had managed to halt the entire medical community and made us realize that it's time to think small. From a barely imagined being in research few years ago to around 4,000 publications in just last year, zebrafish has definitely come a long way. Through these tiny fish, scientists have managed to find genes that caused human diseases and have also developed various specific models to know more about the pathology behind such diseases. This review will focus on zebrafish as a model organism from the time it was introduced to the most novel targets with particular emphasis on central nervous system (CNS) as it is rapidly evolving branch in zebrafish research these days. This review will try to shed light on the early stages of zebrafish as a model organism and will try to cover the journey of it developing as a successful model organism to map many diseases like diabetes, Alzheimer's and autism describing the rationale for using this specific model and briefly the techniques under each category and finally will summarize the pros and cons of the model with its expected future directions. [ABSTRACT FROM AUTHOR]

In this paper, we have studied a three-dimensional model to describe the behavior of tumor cells in the absence of the immune response, which is composed of tumor, normal and fat cells (TNF) under time delay effect. The center manifold theory has been used to study the bifurcation behavior. It is proven that TNF model undergoes codimension-1 bifurcation, while Hopf bifurcation does not occur in the non-delay model. For delayed TNF, we take into the late response of fat cells to tumor cells. Consequently, the delay factor is a considerable parameter in TNF model. Hence, we presented a formula of the time delay value for the occurrence of periodic solutions. Additionally, the stability of Hopf bifurcation was analysed. Numerical simulations are provided to illustrate and extend the theoretical results, we provide our study with numerical simulations inclusive families of periodic solutions.

Cancers of the breast, prostate and intestinal tract account for most cancer-associated deaths in humans and represent several of the highest incidence human neoplasms. Therefore, understanding the underlying pathophysiology, including the formation and propagation of these cancers, is key to designing potential treatments. Over the last 50 years or more, genetically engineered mouse models (GEMMs) have been instrumental platforms to our discovery of neoplastic disease as many follow near-identical molecular and histological progression as human tumours. In this mini review, we summarize three key preclinical models and focus on some of the major findings in relation to clinical care. We discuss the MMTV-PyMT (polyomavirus middle T antigen) mouse, TRAMP (transgenic adenocarcinoma mouse prostate) mouse and APCMin (multiple intestinal neoplasm mutation of APC gene) mouse, which mimic breast, prostate and intestinal cancers, respectively. We aim to describe the significant contributions these GEMMs have made to our collective understanding of high-incidence cancers as well as briefly discuss the limitations of each model as a device for therapeutic discovery. [ABSTRACT FROM AUTHOR]

Lung cancer still has one of the highest morbidity and mortality rates among all types of cancer. Its incidence continues to increase, especially in developing countries. Although the medical field has witnessed the development of targeted therapies, new treatment options need to be developed urgently. For the discovery of new drugs, human cancer models are required to study drug efficiency in a relevant setting. Here, we report the generation of a non-small cell lung cancer model with a perfusion system. The bioprinted model was produced by digital light processing (DLP). This technique has the advantage of including simulated human blood vessels, and its simple assembly and maintenance allow for easy testing of drug candidates. In a proof-of-concept study, we applied gemcitabine and determined the IC50 values in the 3D models and 2D monolayer cultures and compared the response of the model under static and dynamic cultivation by perfusion. As the drug must penetrate the hydrogel to reach the cells, the IC50 value was three orders of magnitude higher for bioprinted constructs than for 2D cell cultures. Compared to static cultivation, the viability of cells in the bioprinted 3D model was significantly increased by approximately 60% in the perfusion system. Dynamic cultivation also enhanced the cytotoxicity of the tested drug, and the drug-mediated apoptosis was increased with a fourfold higher fraction of cells with a signal for the apoptosis marker caspase-3 and a sixfold higher fraction of cells positive for PARP-1. Altogether, this easily reproducible cancer model can be used for initial testing of the cytotoxicity of new anticancer substances. For subsequent in-depth characterization of candidate drugs, further improvements will be necessary, such as the generation of a multi-cell type lung cancer model and the lining of vascular structures with endothelial cells. [ABSTRACT FROM AUTHOR]

Abstract Background Preclinical models like cancer cell lines and patient‐derived xenografts (PDXs) are vital for studying disease mechanisms and evaluating treatment options. It is essential that they accurately recapitulate the disease state of interest to generate results that will translate in the clinic. Prior studies have demonstrated that preclinical models do not recapitulate all biological aspects of human tissues, particularly with respect to the tissue of origin gene expression signatures. Therefore, it is critical to assess how well preclinical model gene expression profiles correlate with human cancer tissues to inform preclinical model selection and data analysis decisions. Aims Here we evaluated how well preclinical models recapitulate human cancer and non‐diseased tissue gene expression patterns in silico with respect to the full gene expression profile as well as subsetting by the most variable genes, genes significantly correlated with tumor purity, and tissue‐specific genes. Methods By using publicly available gene expression profiles across multiple sources, we evaluated cancer cell line and patient‐derived xenograft recapitulation of tumor and non‐diseased tissue gene expression profiles in silico. Results We found that using the full gene set improves correlations between preclinical model and tissue global gene expression profiles, confirmed that glioblastoma (GBM) PDX global gene expression correlation to GBM tumor global gene expression outperforms GBM cell line to GBM tumor global gene expression correlations, and demonstrated that preclinical models in our study often failed to reproduce tissue‐specific expression. While including additional genes for global gene expression comparison between cell lines and tissues decreases the overall correlation, it improves the relative rank between a cell line and its tissue of origin compared to other tissues. Our findings underscore the importance of using the full gene expression set measured when comparing preclinical models and tissues and confirm that tissue‐specific patterns are better preserved in GBM PDX models than in GBM cell lines. Conclusion Future studies can build on these findings to determine the specific pathways and gene sets recapitulated by particular preclinical models to facilitate model selection for a given study design or goal.

This research proposes a mathematical model of cancer treatment with chemotherapy using a fractal fractional Mittag-Leffler operator with non-integer order. The model is analyzed both qualitatively and quantitatively. The control of cancer treatment with chemotherapy effects is established using a fractal fractional operator with a Mittag-Leffler kernel and control theory. The effect of global derivative, existence of unique solutions, and boundedness of proposed system is verified. Solutions are produced using a two-step Lagrange polynomial, and numerical simulations are carried out to illustrate the theoretical results. Cancer treatment with chemotherapy effects are verified from our justified results and predictions are made by simulation using MATLAB. Controllability and observability of the proposed system is also treated for linear control system to observe the close loop design with chemotherapy as an input and treated cells as the output.

We examine the ultimate dynamics of the four-dimensional model describing interactions between host cells, immune cells, tumor cells, and immune-tumor conjugate cells proposed by Abernethy and Gooding in 2018. In our paper, the ultimate upper bounds for all variables of this model are obtained. Formulas for positively invariant sets are deduced. Using these results, we establish conditions for the existence of the global attractor, derive formulas for its location, and present conditions under which immune and immune-tumor conjugate cells asymptotically die out. Next, we study equilibrium points, including the stability property for most of the equilibrium points. We discuss the existence of very low cancer-burden equilibrium points. Next, parametric conditions are derived under which the derivative of the density of the immune-tumor conjugate cell population eventually tends to zero; this mathematically rigorously confirms the correctness of the application of model reduction for this model in studies of its ultimate dynamics. In the final section, we summarize the results of this work and outline how to continue this study.

The potent MYC oncoprotein is deregulated in many human cancers, including breast carcinoma, and is associated with aggressive disease. To understand the mechanisms and vulnerabilities of MYC-driven breast cancer, we have generated an in vivo model that mimics human disease in response to MYC deregulation. MCF10A cells ectopically expressing a common breast cancer mutation in the phosphoinositide 3 kinase pathway (PIK3CAH1047R) led to the development of organised acinar structures in mice. Expressing both PIK3CAH1047R and deregulated MYC led to the development of invasive ductal carcinoma. Therefore, the deregulation of MYC expression in this setting creates a MYC-dependent normal-to-tumour switch that can be measured in vivo These MYC-driven tumours exhibit classic hallmarks of human breast cancer at both the pathological and molecular level. Moreover, tumour growth is dependent upon sustained deregulated MYC expression, further demonstrating addiction to this potent oncogene and regulator of gene transcription. We therefore provide a MYC-dependent model of breast cancer, which can be used to assay in vivo tumour signalling pathways, proliferation and transformation from normal breast acini to invasive breast carcinoma. We anticipate that this novel MYC-driven transformation model will be a useful research tool to better understand the oncogenic function of MYC and for the identification of therapeutic vulnerabilities.

Introduction: Two-dimensional cell cultures have contributed substantially to lung cancer research, but 3D cultures are gaining attention as a new, more efficient, and effective research model. A model reproducing the 3D characteristics and tumor microenvironment of the lungs in vivo, including the co-existence of healthy alveolar cells with lung cancer cells, is ideal. Here, we describe the creation of a successful ex vivo lung cancer model based on bioengineered lungs formed by decellularization and recellularization.Methods: Human cancer cells were directly implanted into a bioengineered rat lung, which was created with a decellularized rat lung scaffold reseeded with epithelial cells, endothelial cells and adipose-derived stem cells. Four human lung cancer cell lines (A549, PC-9, H1299, and PC-6) were applied to demonstrate forming cancer nodules on recellularized lungs and histopathological assessment were made among these models. MUC-1 expression analysis, RNA-seq analysis and drug response test were performed to demonstrate the superiority of this cancer model.Results: The morphology and MUC-1 expression of the model were like those of lung cancer in vivo. RNA sequencing revealed an elevated expression of genes related to epithelial-mesenchymal transition, hypoxia, and TNF-α signaling via NF-κB; but suppression of cell cycle-related genes including E2F. Drug response assays showed that gefitinib suppressed PC-9 cell proliferation equally well in the 3D lung cancer model as in 2D culture dishes, albeit over a smaller volume of cells, suggesting that fluctuations in gefitinib resistance genes such as JUN may affect drug sensitivity.Conclusions: A novel ex vivo lung cancer model was closely reproduced the 3D structure and microenvironment of the actual lungs, highlighting its possible use as a platform for lung cancer research and pathophysiological 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.

Cancer is dangerous and one of the major diseases affecting normal human life. In this paper, a fractional-order cancer model with stem cells and chemotherapy is analyzed to check the effects of infection in individuals. The model is investigated by the Sumudu transform and a very effective numerical method. The positivity of solutions with the ABC operator of the proposed technique is verified. Fixed point theory is used to derive the existence and uniqueness of the solutions for the fractional order cancer system. Our derived solutions analyze the actual behavior and effect of cancer disease in the human body using different fractional values. Modern mathematical control with the fractional operator has many applications including the complex and crucial study of systems with symmetry. Symmetry analysis is a powerful tool that enables the user to construct numerical solutions of a given fractional differential equation in a fairly systematic way. Such an analysis will provide a better understanding to control the of cancer disease in the human body. [ABSTRACT FROM AUTHOR]

• Impulsive differential equations are used to capture the characteristics of intermittent androgen deprivation therapy. • The dynamics of tumours are sensitive to stochastic noise and tumour antigenicity. • The sufficient conditions for the existence of ergodic stationary distribution are established. • The results show that comprehensive therapy is more effective than a single therapy. Intermittent androgen deprivation therapy is one of the most commonly used therapeutic regimens for treating prostate cancer. Immunotherapy with dendritic cells, which act as the most robust antigen-presenting cells, are regarded as an effective method for the treatment of advanced prostate cancer. This paper utilizes impulsive differential equations to describe the combinations of a dendritic cell vaccine and intermittent androgen therapy with white noise. The tumour-free solution is obtained and the unique global positive solution of the system is explored. Then it is proved that the solutions of the system are stochastic ultimately bounded and stochastically permanent. In addition, threshold conditions for the extinction and persistence of prostate cancer cells are derived, and the stationary distribution and ergodicity of the system are investigated. Finally, numerical studies and the biological significance of the results are discussed. [ABSTRACT FROM AUTHOR]

The lack of physiologically relevant human esophageal cancer models has as a result that many esophageal cancer studies are encountering major bottleneck challenges in achieving breakthrough progress. To address the issue, here we engineered a 3D esophageal tumor tissue model using a biomimetic decellularized esophageal matrix in a customized bioreactor. To obtain a biomimetic esophageal matrix, we developed a detergent-free, rapid decellularization method to decellularize porcine esophagus. We characterized the decellularized esophageal matrix (DEM) and utilized the DEM for the growth of esophageal cancer cell KYSE30 in well plates and the bioreactor. We then analyzed the expression of cancer-related markers of KYSE30 cells and compared them with formalin-fixed, paraffin-embedded (FFPE) esophageal squamous cell carcinoma (ESCC) tissue biospecimens. Our results show that the detergent-free decellularization method preserved the esophageal matrix components and effectively removed cell nucleus. KYSE30 cancer cells proliferated well on and inside the DEM. KYSE30 cells cultured on the DEM in the dynamic bioreactor show different cancer marker expressions than those in the static well plate, and also share some similarities to the FFPE-ESCC biospecimens. These findings built a foundation with potential for further study of esophageal cancer behavior in a biomimetic microenvironment using this new esophageal cancer model. [ABSTRACT FROM AUTHOR]

In this paper we consider the ultimate dynamics of one 4D cancer model which was created for studying the immune response to the two-phenotype tumors. Our approach is based on the localization method of compact invariant sets. The existence of a positively invariant polytope is shown and its size is calculated depending on the parameters of this cancer model. Various convergence conditions to the tumor free equilibrium point were proposed. This property has the biological meaning of global asymptotic tumor eradication (GATE). Further, the case in which local asymptotic tumor eradication (LATE) conditions entail GATE conditions was found. Our theoretical studies of ultimate dynamics are complemented by numerical simulation results.

The MAPK/ERK pathway regulates a variety of physiological cellular functions, including cell proliferation and survival. It is abnormally activated in many types of human cancers in response to driver mutations in regulators of this pathway that trigger tumor initiation. The early steps of oncogenic progression downstream of ERK overactivation are poorly understood due to a lack of appropriate models. We show here that ERK1/2 overactivation in the trunk neural tube of the chicken embryo through expression of a constitutively active form of the upstream kinase MEK1 (MEK1ca), rapidly provokes a profound change in the transcriptional signature of developing spinal cord cells. These changes are concordant with a previously established role of the tyrosine kinase receptor ligand FGF8 acting via the ERK1/2 effectors to maintain an undifferentiated state. Furthermore, we show that MEK1ca-transfected spinal cord cells lose neuronal identity, retain caudal markers, and ectopically express potential effector oncogenes, such as AQP1. MEK1ca expression in the developing spinal cord from the chicken embryo is thus a tractable in vivo model to identify the mechanisms fostering neoplasia and malignancy in ERK-induced tumorigenesis of neural origins.

In this paper, we have studied a three-dimensional model to describe the behavior of tumor cells in the absence of the immune response, which is composed of tumor, normal and fat cells (TNF) under time delay effect. The center manifold theory has been used to study the bifurcation behavior. It is proven that TNF model undergoes codimension-1 bifurcation, while Hopf bifurcation does not occur in the non-delay model. For delayed TNF, we take into the late response of fat cells to tumor cells. Consequently, the delay factor is a considerable parameter in TNF model. Hence, we presented a formula of the time delay value for the occurrence of periodic solutions. Additionally, the stability of Hopf bifurcation was analysed. Numerical simulations are provided to illustrate and extend the theoretical results, we provide our study with numerical simulations inclusive families of periodic solutions. [ABSTRACT FROM AUTHOR]

Cancer is one of the leading diseases for human mortality. Although substantial research works have been conducted to investigate the initiation and progression of cancer disease, it is still an active debate regarding the function of mutations conferring a clone advantage and the importance of mutator phenotypes caused by the mutation of stability genes. To address this issue further, we develop a mathematical model based on the incidence data of non-small cell lung cancer and small cell lung cancer from the Surveillance Epidemiology and End Results registry in the USA. The key biological parameters have been analyzed to investigate the potential effective measures for inhibiting the risk of lung cancer. Although the first event is the gene mutation that leads to clonal expansion of cells for lung cancer, the simulation results show that the clonal advantage of cancer cells alone is insufficient to cause tumorigenesis. Our analysis suggests that mutations in genes that keep genetic stability are critical in the development of lung cancer. This implies that mutator phenotype is an important indicator for the diagnosis of lung cancer, which can enable early detection and treatment to reduce the risk of lung cancer effectively. Furthermore, the parameter analysis indicates that it would be highly effective to control the risk of lung cancer by inhibiting the transformation rate from the normal cells to mutated cells and the clonal expansion of cells with fewer gene mutations. [ABSTRACT FROM AUTHOR]

Feline mammary carcinoma (FMC) shares key molecular and clinicopathological features with human breast cancer. We have herein studied the inflammatory infiltrate of FMC in order to uncover potential therapeutic targets and prognostic markers. To this end, the expression of different markers (CD3, CD4, CD8, CD20, CD56, FoxP3, CD68 and CD163) was analyzed in total, stromal (s) and intratumoral (i) tumor-infiltrating lymphocytes (TILs) and tumor-associated macrophages (TAMs), in 73 feline mammary carcinomas. The results revealed that higher percentages of sCD8+ TILs were associated with longer disease-free survival (p = 0.05) and overall survival (p = 0.021). Additionally, higher percentages of iCD4+ TILs correlated with positive lymph node status (p = 0.003), whereas CD163+ TAMs were associated with undifferentiated tumors (p = 0.013). In addition, sCD3+ (p = 0.033), sCD8+ (p = 0.044) and sCD68+ (p = 0.023) immune cells were enriched in triple negative normal-like carcinomas compared to other subtypes. Altogether, our results suggest that specific subsets of immune cells may play a major role in clinical outcome of cats with mammary carcinoma, resembling what has been reported in human breast cancer. These data further support the relevance of the feline model in breast cancer studies. [ABSTRACT FROM AUTHOR]

Small cell lung cancer (SCLC) is aggressive and despite multiple clinical trials, its standard of care is unchanged for the past three decades. In vitro cancer models are crucial in chemotherapy development, and three‐dimensional (3D) models aim to bridge the gap between two‐dimensional (2D) flat cultures and in vivo testing. Functional 3D spheroids can better represent the in vivo situation and tumor characteristics than 2D models. An NCI‐H69V SCLC mini‐tumor model was developed in a clinostat‐based rotating bioreactor system. Spheroid growth and viability were characterized for 30 days, and the ideal experimental window with mature and metabolically stable spheroids was determined. Application of the model for anticancer treatment screening was validated with the standard chemotherapeutic drug irinotecan, for an exposure period of 72 h. The following parameters were measured: soluble protein content, planar surface area measurements, intracellular adenosine triphosphate and extracellular adenylate kinase levels, and glucose consumption. Histological morphology of the spheroids was observed. The established model proved viable and stable, while treatment with irinotecan caused a decrease in cell growth, viability, and glucose consumption demonstrating reactivity of the model to chemotherapy. Therefore, this NCI‐H69V SCLC functional spheroid model could be used for future anticancer compound screening. [ABSTRACT FROM AUTHOR]

Liver cancer is one of the most prevalent cancers in humans. Hepatocytes normally undergo dedifferentiation after the onset of hepatocellular carcinoma, which in turn facilitates the progression of cancer. Although the process of hepatocellular carcinoma dedifferentiation is of significant research and clinical value, the cellular and molecular mechanisms underlying it are still not fully characterized. We constructed a zebrafish liver cancer model based on overexpression of the oncogene krasG12V to investigate the hepatocyte dedifferentiation in hepatocellular carcinoma. We found that, after hepatocarcinogenesis, hepatocytes dedifferentiated and the Notch signaling pathway was upregulated in this progress. Furthermore, we found that inhibition of the Notch signaling pathway or deficiency of sox9b both prevented hepatocyte dedifferentiation following hepatocellular carcinoma induction, reducing cancer metastasis and improving survival. In conclusion, we found that hepatocytes undergo dedifferentiation after hepatocarcinogenesis, a process that requires Notch signaling and likewise the activation of Sox9. [ABSTRACT FROM AUTHOR]

The MAPK/ERK pathway regulates a variety of physiological cellular functions, including cell proliferation and survival. It is abnormally activated in many types of human cancers in response to driver mutations in regulators of this pathway that trigger tumor initiation. The early steps of oncogenic progression downstream of ERK overactivation are poorly understood due to a lack of appropriate models. We show here that ERK1/2 overactivation in the trunk neural tube of the chicken embryo through expression of a constitutively active form of the upstream kinase MEK1 (MEK1ca), rapidly provokes a profound change in the transcriptional signature of developing spinal cord cells. These changes are concordant with a previously established role of the tyrosine kinase receptor ligand FGF8 acting via the ERK1/2 effectors to maintain an undifferentiated state. Furthermore, we show that MEK1ca-transfected spinal cord cells lose neuronal identity, retain caudal markers, and ectopically express potential effector oncogenes, such as AQP1. MEK1ca expression in the developing spinal cord from the chicken embryo is thus a tractable in vivo model to identify the mechanisms fostering neoplasia and malignancy in ERK-induced tumorigenesis of neural origins. [ABSTRACT FROM AUTHOR]

Breast cancer is the second leading cause of death in women after lung cancer, and only 5% of patients with metastatic breast cancer survive beyond ten years of diagnosis. Considering the heterogeneous subclasses of breast cancer, current cancer models have shortfalls due to copy number variants, and genetic differences of humans and immunocompromised animal models. Preclinical studies indicate stem cell activity in early post-natal mammary development may be reactivated in the human adult as a trigger to initiate cell proliferation leading to breast cancer. The goal of the work reported herein was to compare genetic expression of early development, post-natal pig mammary glands to the literature reported genes implicated in different subclasses of human breast cancer. Differentially expressed genes associated with breast cancer and present in early developing pig samples include NUCB2 , ANGPTL4 and ACE. Histological staining confirmed E-cadherin, Vimentin, N-cadherin, and Claudin-1, which are all implicated in malignant cancer. Due to the homology of gene expression patterns in the developing pig mammary gland and reported genes in human breast cancer profiles, this research is worthy of further study to address a potential model using mammary development cues to unravel breast cancer biology. [Display omitted] • Early development of pig mammary glands may serve as a model for human breast cancer research. • Pig mammary transcriptome expression correlates with previously reported breast cancer genes. • Discoveries in breast cancer research could be evaluated from alternative mouse models. [ABSTRACT FROM AUTHOR]

Cancer is dangerous and one of the major diseases affecting normal human life. In this paper, a fractional-order cancer model with stem cells and chemotherapy is analyzed to check the effects of infection in individuals. The model is investigated by the Sumudu transform and a very effective numerical method. The positivity of solutions with the ABC operator of the proposed technique is verified. Fixed point theory is used to derive the existence and uniqueness of the solutions for the fractional order cancer system. Our derived solutions analyze the actual behavior and effect of cancer disease in the human body using different fractional values. Modern mathematical control with the fractional operator has many applications including the complex and crucial study of systems with symmetry. Symmetry analysis is a powerful tool that enables the user to construct numerical solutions of a given fractional differential equation in a fairly systematic way. Such an analysis will provide a better understanding to control the of cancer disease in the human body.

The lack of physiologically relevant human esophageal cancer models has as a result that many esophageal cancer studies are encountering major bottleneck challenges in achieving breakthrough progress. To address the issue, here we engineered a 3D esophageal tumor tissue model using a biomimetic decellularized esophageal matrix in a customized bioreactor. To obtain a biomimetic esophageal matrix, we developed a detergent-free, rapid decellularization method to decellularize porcine esophagus. We characterized the decellularized esophageal matrix (DEM) and utilized the DEM for the growth of esophageal cancer cell KYSE30 in well plates and the bioreactor. We then analyzed the expression of cancer-related markers of KYSE30 cells and compared them with formalin-fixed, paraffin-embedded (FFPE) esophageal squamous cell carcinoma (ESCC) tissue biospecimens. Our results show that the detergent-free decellularization method preserved the esophageal matrix components and effectively removed cell nucleus. KYSE30 cancer cells proliferated well on and inside the DEM. KYSE30 cells cultured on the DEM in the dynamic bioreactor show different cancer marker expressions than those in the static well plate, and also share some similarities to the FFPE-ESCC biospecimens. These findings built a foundation with potential for further study of esophageal cancer behavior in a biomimetic microenvironment using this new esophageal cancer model.