Cancer models in preclinical research:A chronicle review of advancement in effective cancer research

Cancer is a major stress for public well-being and is the most dreadful disease.The models used in the discovery of cancer treatment are continuously changing and extending toward advanced preclinical studies.Cancer models are either naturally existing or artificially prepared experimental systems that show similar features with human tumors though the heterogeneous nature of the tumor is very familiar.The choice of the most fitting model to best reflect the given tumor system is one of the real difficulties for cancer examination.Therefore,vast studies have been conducted on the cancer models for developing a better understanding of cancer invasion,progression,and early detection.These models give an insight into cancer etiology,molecular basis,host tumor interaction,the role of microenvironment,and tumor heterogeneity in tumor metastasis.These models are also used to predict novel can-cer markers,targeted therapies,and are extremely helpful in drug development.In this review,the potential of cancer models to be used as a platform for drug screening and therapeutic discoveries are highlighted.Although none of the cancer models is regarded as ideal because each is associated with essential caveats that restraint its application yet by bridging the gap between preliminary cancer research and transla-tional medicine.However,they promise a brighter future for cancer treatment.

Dynamics of Advantageous Mutant Spread in Spatial Death-Birth and Birth-Death Moran Models

The spread of an advantageous mutation through a population is of fundamental interest in population genetics. While the classical Moran model is formulated for a well-mixed population, it has long been recognized that in real-world applications, the population usually has an explicit spatial structure which can significantly influence the dynamics. In the context of cancer initiation in epithelial tissue, several recent works have analyzed the dynamics of advantageous mutant spread on integer lattices, using the biased voter model from particle systems theory. In this spatial version of the Moran model, individuals first reproduce according to their fitness and then replace a neighboring individual. From a biological standpoint, the opposite dynamics, where individuals first die and are then replaced by a neighboring individual according to its fitness, are equally relevant. Here, we investigate this death-birth analogue of the biased voter model. We construct the process mathematically, derive the associated dual process, establish bounds on the survival probability of a single mutant, and prove that the process has an asymptotic shape. We also briefly discuss alternative birth-death and death-birth dynamics, depending on how the mutant fitness advantage affects the dynamics. We show that birth-death and death-birth formulations of the biased voter model are equivalent when fitness affects the former event of each update of the model, whereas the birth-death model is fundamentally different from the death-birth model when fitness affects the latter event.

Tissue-specific cancer stem/progenitor cells:Therapeutic implications

Surgical resection,chemotherapy,and radiation are the standard therapeutic modalities for treating cancer.These approaches are intended to target the more mature and rapidly dividing cancer cells.However,they spare the relatively quiescent and intrinsically resistant cancer stem cells(CSCs)subpopulation residing within the tumor tissue.Thus,a temporary eradication is achieved and the tumor bulk tends to revert supported by CSCs'resistant features.Based on their unique expression profile,the identification,isolation,and selective targeting of CSCs hold great promise for challenging treatment failure and reducing the risk of cancer recurrence.Yet,targeting CSCs is limited mainly by the irrelevance of the utilized cancer models.A new era of targeted and personalized anti-cancer therapies has been developed with cancer patient-derived organoids(PDOs)as a tool for establishing pre-clinical tumor models.Herein,we discuss the updated and presently available tissue-specific CSC markers in five highly occurring solid tumors.Additionally,we highlight the advantage and relevance of the threedimensional PDOs culture model as a platform for modeling cancer,evaluating the efficacy of CSC-based therapeutics,and predicting drug response in cancer patients.

Inhibition of growth and metastasis of triple-negative breast cancer targeted by Traditional Chinese Medicine Tubeimu in orthotopic mice models

Objective： Triple-negative breast cancer（TNBC） is highly invasive and metastatic, which is in urgent need of transformative therapeutics. Tubeimu（TBM）, the rhizome of Bolbostemma paniculatum（Maxim.） Franquet, is one of the Chinese medicinal herbs used for breast diseases since the ancient times. The present study evaluated the efficacy, especially the anti-metastatic effects of the dichloromethane extract of Tubeimu（ETBM） on TNBC orthotopic mouse models and cell lines.Methods： We applied real-time imaging on florescent orthotopic TNBC mice model and tested cell migration and invasion abilities with MDA-MB-231 cell line. Digital gene expression sequencing was performed and Kyoto Encyclopedia of Genes and Genomes（KEGG） analysis applied to explore the pathways influenced by ETBM.Moreover, quantitative real-time polymerase chain reactions（q RT-PCR） and Western blot were delivered to confirm the gene expression changes.Results： ETBM exhibited noticeable control on tumor metastasis and growth of TNBC tumors with no obvious toxicity. In compliance with this, it also showed inhibition of cell migration and invasion in vitro. Its impact on the changed biological behavior in TNBC may be a result of decreased expression of integrin β1（ITGβ1）, integrin β8（ITGβ8） and Rho GTPase activating protein 5（ARHGAP5）, which disabled the focal adhesion pathway and caused change in cell morphology.Conclusions： This study reveals that ETBM has anti-metastatic effects on MDA-MB-231-GFP tumor and may lead to a new therapeutic agent for the integrative treatment of highly invasive TNBC.

Design of Computer Methods for the Solution of Cervical Cancer Epidemic Model

Nonlinear modelling has a significant role in different disciplines of sciences such as behavioral,social,physical and biological sciences.The structural properties are also needed for such types of disciplines,as dynamical consistency,positivity and boundedness are the major requirements of the models in these fields.One more thing,this type of nonlinear model has no explicit solutions.For the sake of comparison its computation will be done by using different computational techniques.Regrettably,the aforementioned structural properties have not been restored in the existing computational techniques in literature.Therefore,the construction of structural preserving computational techniques are needed.The nonlinearmodel for cervical cancer is constructed by parametric perturbation technique.Well-known computer methods are considered for the computation of cervical cancer dynamics.The well-known existing methods in literature are Euler Maruyama,Euler and Runge Kutta.Nonstandard finite difference method or Implicitly driven explicit method is first time considered for aforesaid model under the assumptions given byMickens in a stochastic way.Unfortunately,the aforementioned existing methods did not reinstate structural properties of cervical cancer dynamics in the human population.Our plannedmethod is structural preserving and a powerful tool for all nonlinear models of biomedical engineering problems.We have verified that existing computational methods do not preserve dynamical properties.But,the implicitly driven explicit method is a good device for dynamical properties.In the support of assertions,convergence analysis of implicitly driven explicit method is presented.

Individualized prediction of perineural invasion in colorectal cancer: development and validation of a radiomics prediction model

Objective： To develop and validate a radiomics prediction model for individualized prediction of perineural invasion（PNI） in colorectal cancer（CRC）.Methods： After computed tomography（CT） radiomics features extraction, a radiomics signature was constructed in derivation cohort（346 CRC patients）. A prediction model was developed to integrate the radiomics signature and clinical candidate predictors [age, sex, tumor location, and carcinoembryonic antigen（CEA） level]. Apparent prediction performance was assessed. After internal validation, independent temporal validation（separate from the cohort used to build the model） was then conducted in 217 CRC patients. The final model was converted to an easy-to-use nomogram.Results： The developed radiomics nomogram that integrated the radiomics signature and CEA level showed good calibration and discrimination performance [Harrell＇s concordance index（c-index）： 0.817; 95% confidence interval（95% CI）： 0.811–0.823]. Application of the nomogram in validation cohort gave a comparable calibration and discrimination（c-index： 0.803; 95% CI： 0.794–0.812）.Conclusions： Integrating the radiomics signature and CEA level into a radiomics prediction model enables easy and effective risk assessment of PNI in CRC. This stratification of patients according to their PNI status may provide a basis for individualized auxiliary treatment.

Primarily screening and analyzing ESTs differentially expressed in rats' primary liver cancer

Objective： To screen and analyze key express sequence tags （ESTs） which were differentially displayed in every period of SD rats＇ primary hepatic carcinoma and reveal the molecular mechanism of carcinogenesis. Methods： Using diethylnitrosamine （DENA） as a cancerigenic agent, animal models with different phases of primary hepatic cancer were constructed in SD rats. Rats were respectively sacrificed at d 14, d 28, d 56, d 77, d 105 and d 112 after the rats received DENA by gavage, then the livers were harvested. One part of the livers was classified according to their pathological changes, while the other was reserved for molecular mechanism studies on hepatocarcinogenesis. The differentially expressed genes were isolated from both normal and morbid tissues by mRNA differential display technique （DDRT-PCR）. After the fragments were sequenced, bioinformatics were .used to analyze the results. Results： Twelve differentially expressed cDNA fragments were obtained. Nine fragments had the homology with known cDNA clones, especially EST-7 was similar to BN/SsNHsdMCW mitochondrion gene and the identity was 100% which suggested EST-7 may be the part of BN/SsNHsdMCW mitochondrion gene. In contrast, other three fragments （EST-1, EST-3 and EST-5） had extremely low identity to any genes registered in GENBANK databases. Conclusions： BN/SsNHsdMCW mitochondrion gene was expressed in different periods of hepatocarcinogenesis. Moreover, EST-I, EST-3 and EST-5 were suggested to contribute to the development of rat hepatocarcinogenesis, and thus may be candidates of new targets of oncogenes or cancer suppressor genes.

Photodynamic diagnostics of early gastric cancer:Complexity measures of gastric microcirculation and new model of metastatic adenocarcinoma of rat stomach

The detection of early gastric cancer that often develops asymptomatically is crucial for improving patient survival.The photodynamic diagnosis(PDD)of gastric cancer using 5-aminolevulinic acid/protoporphyrin IX(5-ALA/PpIX)has been reported in several studies.However,the selectivity of PDD of gastric tumor is poor with often false-positive results that require the development of new methods to improve PDD for early gastric cancer.Therefore,a measure of the complexity of gastric microcirculation(multi-scale entropy,MSE)and the detrendedfluctuation analysis(DFA)were applied as additional tools to detect early gastric cancer in rats.In this experimental study,we used our original model of metastatic adenocarcinoma in the stomach of a rat.To induce a gastric tumor,we used a long-term combination(for 9 months,which is 1/2 of the life of rats)of two natural factors,such as chronic stress(overpopulation being typical for modern cities)and the daily presence of nitrites in food and drinks,which are common ingredients added to processed meat andfish to help preserve food.Our results clearly show that both methods,namely,PDD using 5-ALA/PpIX and complexity/correlation analysis,can detect early gastric cancer,which was confirmed by histological analysis.Pre-cancerous areas in the stomach were detected as an intermediatefluorescent signal or MSE level between normal and malignant lesions of the stomach.However,in some cases,PDD with 5-ALA/PpIX produced a false-positivefluorescence of exogenousfluorophores due to its accumulation in benign and inflammatory areas of the mucosa.This fact indicates that the PDD itself is not sufficient for the correct diagnosis of gastric cancer,and the use of additional characteristics,e.g.,complexity measures or scaling exponents,can significantly improve the diagnostic accuracy of PDD of gastric cancer that should be confirmed in further clinical studies and applications.

Drug-adapted cancer cell lines as preclinical models of acquired resistance

Acquired resistance formation limits the efficacy of anti-cancer therapies.Acquired and intrinsic resistance differ conceptually.Acquired resistance is the consequence of directed evolution,whereas intrinsic resistance depends on the(stochastic)presence of pre-existing resistance mechanisms.Preclinical model systems are needed to study acquired drug resistance because they enable:(1)in depth functional studies;(2)the investigation of non-standard treatments for a certain disease condition(which is necessary to identify small groups of responders);and(3)the comparison of multiple therapies in the same system.Hence,they complement data derived from clinical trials and clinical specimens,including liquid biopsies.Many groups have successfully used drug-adapted cancer cell lines to identify and elucidate clinically relevant resistance mechanisms to targeted and cytotoxic anti-cancer drugs.Hence,we argue that drug-adapted cancer cell lines represent a preclinical model system in their own right that is complementary to other preclinical model systems and clinical data.

Dys-psychological Stress Effect on Expressions of P53 and NFκBp65 in Human Ovarian Carcinoma In Vivo

Objective： To investigate the dys-psychological stress effect on the growth of subcutaneous xenotransplanted tumor in nude mice bearing human epithelium ovarian carcinoma, and the influence on P53 and NFκBp65 expressions. Methods： The subcutaneous tumor xenografts were established by implanting human epithelium ovarian carcinoma tissues into nude mice and the dys-psychological stress model was established with restraint. The mice were randomized into the following four treatment groups with each group six mice respectively： tumor group （group A）, normal saline intraperitoneal injection; tumor with stress group （group B）, normal saline intraperitoneal injection; tumor therapy group （group C）, cisplatin intraperitoneal injection; and tumor therapy with stress group （group D）, cisplatin intraperitoneal injection. The expressions of P53 and NFκBp65 in tumor tissues were determined by Western blotting. Results： The expressions of P53 and NFκBp65 in each restraint group were enhanced compared with the control groups （P0.05）. Conclusion： The dys-psychological stress may induce the high expressions of P53 and NFκBp65 proteins and further promote tumor growth.

High-dose dietary zinc promotes prostate intraepithelial neoplasia in a murine tumor induction mode

To evaluate the role of high-dose dietary zinc in the process of prostate malignancy,60 Sprague-Dawley rats were randomly divided into four groups：tumor induction with carcinogen and hormone （group 1）,oral zinc administration without tumor induction （group 2）,oral zinc administration with tumor induction （group 3） and a control without zinc administration or tumor induction （group 4）. Zinc was supplied orally in the form of zinc sulfate heptahydrate dissolved in drinking water to groups 2 and 3 for 20 weeks. Although the serum level of zinc measured at 20 weeks was maintained similarly in each group （P = 0.082）,intraprostatic zinc concentrations were statistically different. Group 1 prostates contained the least amount of zinc in both the dorsolateral and ventral lobes at levels of 36.3 and 4.8 μg g^-1,respectively. However,in group 3,zinc levels increased in both lobes to 59.3 and 12.1 μg g^-1,respectively,comparable with that of group 4 （54.5±14.6 and 14.1±2.4 μg g^-1）. In spite of these increases in zinc concentration,the prevalence of prostate intraepithelial neoplasm was rather increased in group 3 （53.3% and 46.7%） compared with group 1 （33.3% and 33.3%） in both dorsolateral and ventral prostate lobes. Although prostate intraepithelial neoplasm did not develop in any prostate in group 4,zinc administration did induce prostate intraepithelial neoplasm in group 2 （46.7% and 40.0%）. Thus,although high dietary zinc increased intraprostatic zinc concentrations,it promoted,instead of preventing,prostate intraepithelial neoplasm in a murine prostate malignancy induction model.

Computational solution of an acid-mediated tumor-growth radial model under logistic growth regimes for normal and cancer cells

Tumor invasion follows a complex mechanism which involves cell migration and proliferation.To study the processes in which primary and secondary metastases invade and damage the normal cells,mathematical models are often extremely useful.In this paper,we present a mathematical model of acid-mediated tumor growth consisting of radially symmetric reaction-diffusion equations.The assumption on the radial symmetry of the solutions is imposed here in view that tumors present spherical symmetry at the microscopic level.Moreover,we consider various empirical mechanisms which describe the propagation of tumors by considering cancer cells,normal cells,and the concentration of H+ions.Among other assumptions,we suppose that these components follow logistictype growth rates.Evidently,this is an important difference with respect to various other mathematical models for tumor growth available in the literature.Moreover,we also add competition terms of normal and tumor cells growth.We carry out a balancing study of the equations of the model,and a numerical model is proposed to produce simulations.Various practical remarks derived from our assumptions are provided in the discussion of our simulations.

Utilization of 3D printing technology in hepatopancreatobiliary surgery

The technology of three-dimensional(3D)printing emerged in the late 1970s and has since undergone considerable development to find numerous applications in mechanical engineering,industrial design,and biomedicine.In biomedical science,several studies have initially found that 3D printing technology can play an important role in the treatment of diseases in hepatopancreatobiliary surgery.For example,3D printing technology has been applied to create detailed anatomical models of disease organs for preoperative personalized surgical strategies,surgical simulation,intraoperative navigation,medical training,and patient education.Moreover,cancer models have been created using 3D printing technology for the research and selection of chemotherapy drugs.With the aim to clarify the development and application of 3D printing technology in hepatopancreatobiliary surgery,we introduce seven common types of 3D printing technology and review the status of research and application of 3D printing technology in the field of hepatopancreatobiliary surgery.

Efficient growth suppression in pancreatic cancer PDX model by fully human anti-mesothelin CAR-T cells

Dear Editor, Pancreatic cancer is a devastating disease ranked as the 4th leading cause of cancer-related deaths in the United States, and its incidence rate is increasing according to the latest statistics. The overall survival rates for patients with pan- creatic cancer have not significantly improved over the past thirty years （Siegel et al., 2012; Simard et al., 2012）. One of the reasons for the high mortality rates is the high resistance of pancreatic cancer to chemotherapy and radiation. Most patients are diagnosed at late stages of the disease. Approximately 15%-20% of patients diagnosed with pan- creatic cancer are eligible for surgical resection, and 85% of these patients eventually experience relapse and ultimately cancer-related death （Siegel et al., 2012）. In recent years, increasing evidence indicates that the fibro-inflammatory stroma is a source of cellular and molecular components contributing to tumor progression and metastasis （Feig et al., 2012; Waghray et al., 2013）. Importantly, increased levels of stroma are positively related to a poor prognosis （Erkan et al., 2008）. Despite the broader understanding of pancre- atic cancer biology, gemcitabine, a chemotherapeutic approved for pancreatic cancer treatment approximately twenty years ago, still remains the standard of care （Burris et al., 1997）. Thus, the development of novel treatment strategies for this devastating disease is urgently needed.

Tumor organoids to study gastroesophageal cancer: a primer

Gastroesophageal cancers are leading causes of cancer death.Our attempts at adopting molecularly based treatment approaches have been slow and ineffective even though we begin to identify specific targetable gene mutations and pathways.It is dear that we should no longer treat all gastroesophageal cancers as a homogeneous disease,which is what we do when we use nonspecific chemotherapy.However,we currently cannot monitor successful gene/pathway targeting,nor understand how/when tumors develop resistance,nor predict which patients will derive maximal benefit.To improve outcomes,we must precisely detail the heterogeneity of these tumors to then individualize cancer therapy as well as develop novel avenues to study and predict treatment effects in individual patients.To this end,patient-derived organoids,in which tumor cells from individual patients are grown in a Petri dish,are a new versatile system that allows for timely expandability,detailed molecular characterization,and genetic manipulation with the promise of enabling predictive assessment of treatment response.In this review,we will explore the development and basic techniques for organoid generation,and discuss the current and potential future applications of this exciting technology to study the basic science of carcinogenesis and to predict/guide cancer patient care in the clinics.

A new exploration on the creation of grafted breast cancer model for MA891 cells in TA2 mice

Animal experimental systems are particularly useful for the study of human breast cancer. An ideal model shoulcl be easy to use, closely mimicking human physiopathology and has a stable tumor morbidity. The cell line MA891 was established from a spontaneous TA2 mouse mammary carcinoma by Cancer Institute of Chinese Academy of Medical Sciences. 3 Some researches indicated that MA891 had a very low immunogenecity and maintained a high metastatic potential in vivo. So it has been used as a better grafted mouse tumor model for studying cancer physiopathology and metastasis in human for years. However, about the biological characteristic and the histopathologic feature of this model there has been a lack of investigations.

Stability analysis of a fractional-order cancer model with chaotic dynamics

In this paper,we develop a three-dimensional fractional-order cancer model.The proposed model involves the interaction among tumor cells,healthy tissue cells and activated effector cells.The detailed analysis of the equilibrium points is studied.Also,the existence and uniqueness of the solution are investigated.The fractional derivative is considered in the Caputo sense.Numerical simulations are performed to illustrate the effectiveness of the obtained theoretical results.The outcome of the study reveals that the order of the fractional derivative has a significant effect on the dynamic process.Further,the calculated Lyapunov exponents give the existence of chaotic behavior of the proposed model.Also,it is observed from the obtained results that decrease in fractional-order p increases the chaotic behavior of the model.

A Bistable FieldModel of Cancer Dynamics

Cancer spread is a dynamical process occurring not only in time but also in space which,for solid tumors at least,can be modeled quantitatively by reaction and diffusion equations with a bistable behavior:tumor cell colonization happens in a portion of tissue and propagates,but in some cases the process is stopped.Such a cancer proliferation/extintion dynamics is obtained in many mathematical models as a limit of complicated interacting biological fields.In this article we present a very basic model of cancer proliferation adopting the bistable equation for a single tumor cell dynamics.The reaction-diffusion theory is numerically and analytically studied and then extended in order to take into account dispersal effects in cancer progression in analogy with ecological models based on the porous medium equation.Possible implications of this approach for explanation and prediction of tumor development on the lines of existing studies on brain cancer progression are discussed.The potential role of continuum models in connecting the two predominant interpretative theories about cancer,once formalized in appropriatemathematical terms,is discussed。

A peroxidase-like single-atom Fe-N_(5)active site for effective killing human lung adenocarcinoma cells

Single-atom catalyst(SAC)is one of the newest catalysts,and attracts people’s wide attention in cancer therapy based on their characteristics of maximum specific catalytic activity and high stability.We designed and synthesized a Fe-N decorated graphene nanosheet(Fe-N5/GN SAC)with the coordination number of five.Through enzymology and theoretical calculations,the Fe-N5/GN SAC has outstanding intrinsic peroxidase-like catalytic activity due to single-atom Fe site with five-N-coordination structure.We explored its potential on lung cancer therapy,and found that it could kill human lung adenocarcinoma cells(A549)by decomposing hydrogen peroxide(H_(2)O_(2))into toxic reactive oxygen species(ROS)under acidic microenvironment in threedimensional(3D)lung cancer cell model.Our study demonstrates a promising application of SAC with highly efficient single-atom catalytic sites for cancer treatment.

Aberrant cholesterol metabolic signaling impairs antitumor immunosurveillance through natural killer T cell dysfunction in obese liver

Obesity is a major risk factor for cancers including hepatocellular carcinoma(HCC)that develops from a background of non-alcoholic fatty liver disease(NAFLD).Hypercholesterolemia is a common comorbidity of obesity.Although cholesterol biosynthesis mainly occurs in the liver,its role in HCC development of obese people remains obscure.Using high-fat high-carbohydrate diet-associated orthotopic and spontaneous NAFLD-HCC mouse models,we found that hepatic cholesterol accumulation in obesity selectively suppressed natural killer T(NKT)cell-mediated antitumor immunosurveillance.Transcriptome analysis of human liver revealed aberrant cholesterol metabolism and NKT cell dysfunction in NAFLD patients.Notably,cholesterol-lowering rosuvastatin restored NKT expansion and cytotoxicity to prevent obesogenic diet-promoted HCC development.Moreover,suppression of hepatic cholesterol biosynthesis by a mammalian target of rapamycin(mTOR)inhibitor vistusertib preceded tumor regression,which was abolished by NKT inactivation but not CD8^(+)T cell depletion.Mechanistically,sterol regulatory element-binding protein 2(SREBP2)-driven excessive cholesterol production from hepatocytes induced lipid peroxide accumulation and deficient cytotoxicity in NKT cells,which were supported by findings in people with obesity,NAFLD and NAFLD-HCC.This study highlights mTORC1/SREBP2/cholesterol-mediated NKT dysfunction in the tumor-promoting NAFLD liver microenvironment,providing intervention strategies that invigorating NKT cells to control HCC in the obesity epidemic.