Development and validation of a circulating tumor DNA-based optimization-prediction model for short-term postoperative recurrence of endometrial cancer

BACKGROUND Endometrial cancer(EC)is a common gynecological malignancy that typically requires prompt surgical intervention;however,the advantage of surgical management is limited by the high postoperative recurrence rates and adverse outcomes.Previous studies have highlighted the prognostic potential of circulating tumor DNA(ctDNA)monitoring for minimal residual disease in patients with EC.AIM To develop and validate an optimized ctDNA-based model for predicting shortterm postoperative EC recurrence.METHODS We retrospectively analyzed 294 EC patients treated surgically from 2015-2019 to devise a short-term recurrence prediction model,which was validated on 143 EC patients operated between 2020 and 2021.Prognostic factors were identified using univariate Cox,Lasso,and multivariate Cox regressions.A nomogram was created to predict the 1,1.5,and 2-year recurrence-free survival(RFS).Model performance was assessed via receiver operating characteristic(ROC),calibration,and decision curve analyses(DCA),leading to a recurrence risk stratification system.RESULTS Based on the regression analysis and the nomogram created,patients with postoperative ctDNA-negativity,postoperative carcinoembryonic antigen 125(CA125)levels of<19 U/mL,and grade G1 tumors had improved RFS after surgery.The nomogram’s efficacy for recurrence prediction was confirmed through ROC analysis,calibration curves,and DCA methods,highlighting its high accuracy and clinical utility.Furthermore,using the nomogram,the patients were successfully classified into three risk subgroups.CONCLUSION The nomogram accurately predicted RFS after EC surgery at 1,1.5,and 2 years.This model will help clinicians personalize treatments,stratify risks,and enhance clinical outcomes for patients with EC.

A model of five genes of tumor microenvironment predicts prognosis in Cholangiocarcinoma

Background:Cholangiocarcinoma(CCA)is highly malignant and has a poor prognosis has a high malignant degree and poor prognosis.The purpose of this study is to develop a new prognostic model based on genes related to the tumor microenvironment(TME).Methods:Derived from the discerned differentially expressed genes within The Cancer Genome Atlas(TCGA)dataset,this investigation employed the methodology of weighted gene co-expression network analysis(WGCNA)to ascertain gene co-expressed modules intricately linked to the Tumor Microenvironment(TME)among Cholangiocarcinoma(CCA)patients.The genes associated with prognosis,as identified through Cox regression analysis,were employed in the formulation of a predictive model.This model underwent validation,leading to the development of a risk score formula and nomogram.Concurrently,we validated the model’s reliability using data from CCA patients in the Gene Expression Omnibus(GEO)database(accession:GSE107943).Results:6139 DEGs were divided into 10 co-expressed gene modules using WGCNA.Among these,two modules(blue module with 832 genes and brown module with 1379 genes)showed high correlation with the TME.Five prognostic genes(BNIP3,COL4A3,SPRED3,CEBPB,PLOD2)were identified through Cox regression analysis,and a prognostic model and risk score formula were developed based on these genes.Risk score formula:Risk score=BNIP3×1.70520-COL4A3×2.39815+SPRED3×1.17936+CEBPB×0.40456+PLOD2×0.24785.Kaplan-Meier survival analysis revealed that the survival probabilities of the low-risk group were significantly higher than those of the high-risk group.Furthermore,the related evaluation indexes suggested that the model exhibited strong predictive ability.Conclusion:The prognostic model,based on five TME-related genes(BNIP3,COL4A3,SPRED3,CEBPB,PLOD2),could accurately assess the prognosis of CCA patients to aid in guiding clinical decisions.

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

Colorectal cancer(CRC)is one of the most popular malignancies globally,with 930000 deaths in 2020.The evaluation of CRC-related pathogenesis and the discovery of po-tential therapeutic targets will be meaningful and helpful for improving CRC treat-ment.With huge efforts made in past decades,the systematic treatment regimens have been applied to improve the prognosis of CRC patients.However,the sensitivity of CRC to chemotherapy and targeted therapy is different from person to person,which is an important cause of treatment failure.The emergence of patient-derived xenograft(PDX)models shows great potential to alleviate the straits.PDX models possess similar genetic and pathological characteristics as the features of primary tu-mors.Moreover,PDX has the ability to mimic the tumor microenvironment of the original tumor.Thus,the PDX model is an important tool to screen precise drugs for individualized treatment,seek predictive biomarkers for prognosis supervision,and evaluate the unknown mechanism in basic research.This paper reviews the recent advances in constructed methods and applications of the CRC PDX model,aiming to provide new knowledge for CRC basic research and therapeutics.

Spontaneous xenogeneic GvHD in Wilms'tumor Patient-Derived xenograft models and potential solutions

Severely immunocompromised NOD.Cg-PrkdcIl2rg(NOG)mice are among the ideal animal recipients for generation of human cancer models.Transplantation of human solid tumors having abundant tumor-i nfiltrating lymphocytes(TILs)can induce xenogeneic graft-versus-host disease(xGvHD)following engraftment and expansion of the TILs inside the animal body.Wilms’tumor(WT)has not been recognized as a lymphocyte-predominant tumor.However,3 consecutive generations of NOG mice bearing WT patient-derived xenografts(PDX)xenotransplanted from a single donor showed different degrees of inflammatory symptoms after transplantation before any therapeutic intervention.In the initial generation,dermatitis,auto-amputation of digits,weight loss,lymphadenopathy,hepatitis,and interstitial pneumonitis were observed.Despite antibiotic treatment,no response was noticed,and thus the animals were prematurely euthanized(day 47 posttransplantation).Laboratory and histopathologic evaluations revealed lymphoid infiltrates positively immunostained with anti-human CD3 and CD8 antibodies in the xenografts and primary tumor,whereas no microbial infection or lymphoproliferative disorder was found.Mice of the next generation that lived longer(91 days)developed sclerotic skin changes and more severe pneumonitis.Cutaneous symptoms were milder in the last generation.The xenografts of the last 2 generations also contained TILs,and lacked lymphoproliferative transformation.The systemic immunoinflammatory syndrome in the absence of microbial infection and posttransplant lymphoproliferative disorder was suggestive of xGvHD.While there are few reports of xGvHD in severely immunodeficient mice xenotransplanted from lymphodominant tumor xenografts,this report for the first time documented serial xGvHD in consecutive passages of WT PDX-bearing models and discussed potential solutions to prevent such an undesired complication.

The promises and challenges of patient-derived tumor organoids in drug development and precision oncology

In the era of precision medicine,cancer researchers and oncologists are eagerly searching for more realistic,cost effective,and timely tumor models to aid drug development and precision oncology.Tumor models that can faithfully recapitulate the histological and molecular characteristics of various human tumors will be extremely valuable in increasing the successful rate of oncology drug development and discovering the most efficacious treatment regimen for cancer patients.Two‐dimensional(2D)cultured cancer cell lines,genetically engineered mouse tumor(GEMT)models,and patient‐derived tumor xenograft(PDTX)models have been widely used to investigate the biology of various types of cancers and test the efficacy of oncology drug candidates.However,due to either the failure to faithfully recapitulate the complexity of patient tumors in the case of 2D cultured cancer cells,or high cost and untimely for drug screening and testing in the case of GEMT and PDTX,new tumor models are urgently needed.The recently developed patient‐derived tumor organoids(PDTO)offer great potentials in uncovering novel biology of cancer development,accelerating the discovery of oncology drugs,and individualizing the treatment of cancers.In this review,we will summarize the recent progress in utilizing PDTO for oncology drug discovery.In addition,we will discuss the potentials and limitations of the current PDTO tumor models.

Patient-derived non-small cell lung cancer xenograft mirrors complex tumor heterogeneity

Objective:Patient-derived xenograft(PDX)models have shown great promise in preclinical and translational applications,but their consistency with primary tumors in phenotypic,genetic,and pharmacodynamic heterogeneity has not been well-studied.This study aimed to establish a PDX repository for non-small cell lung cancer(NSCLC)and to further elucidate whether it could preserve the heterogeneity within and between tumors in patients.Methods:A total of 75 surgically resected NSCLC specimens were implanted into immunodeficient NOD/SCID mice.Based on the successful establishment of the NSCLC PDX model,we compared the expressions of vimentin,Ki67,EGFR,and PD-L1 proteins between cancer tissues and PDX models using hematoxylin and eosin staining and immunohistochemical staining.In addition,we detected whole gene expression profiling between primary tumors and PDX generations.We also performed whole exome sequencing(WES)analysis in 17 first generation xenografts to further assess whether PDXs retained the patient heterogeneities.Finally,paclitaxel,cisplatin,doxorubicin,atezolizumab,afatininb,and AZD4547 were used to evaluate the responses of PDX models to the standard-of-care agents.Results:A large collection of serially transplantable PDX models for NSCLC were successfully developed.The histology and pathological immunohistochemistry of PDX xenografts were consistent with the patients’tumor samples.WES and RNA-seq further confirmed that PDX accurately replicated the molecular heterogeneities of primary tumors.Similar to clinical patients,PDX models responded differentially to the standard-of-care treatment,including chemo-,targeted-and immuno-therapeutics.Conclusions:Our established PDX models of NSCLC faithfully reproduced the molecular,histopathological,and therapeutic characteristics,as well as the corresponding tumor heterogeneities,which provides a clinically relevant platform for drug screening,biomarker discovery,and translational research.

Translational pancreatic cancer research:a comparative study on patient-derived xenograft models

AIM To assess the viability of orthotopic and heterotopic patient-derived pancreatic cancer xenografts implanted into nude mice.METHODS This study presents a prospective experimental analytical follow-up of the development of tumours in mice upon implantation of human pancreatic adenocarcinoma samples. Specimens were obtained surgically from patients with a pathological diagnosis of pancreatic adenocarcinoma. Tumour samples from pancreatic cancer patients were transplanted into nude mice in three different locations(intraperitoneal, subcutaneous and pancreatic). Histological analysis(haematoxylin-eosin and Masson's trichrome staining) and immunohistochemical assessment of apoptosis(TUNEL), proliferation(Ki-67), angiogenesis(CD31) and fibrogenesis(α-SMA) were performed. When a tumour xenograft reached the target size, it was reimplanted in a new nude mouse. Three sequential tumour xenograft generations were generated(F1, F2 and F3).RESULTS The overall tumour engraftment rate was 61.1%. The subcutaneous model was most effective in terms of tissue growth(69.9%), followed by intraperitoneal(57.6%) and pancreatic(55%) models. Tumour development was faster in the subcutaneous model(17.7 ± 2.6 wk) compared with the pancreatic(23.1 ± 2.3 wk) and intraperitoneal(25.0 ± 2.7 wk) models(P = 0.064). There was a progressive increase in the tumour engraftment rate over successive generations for all three models(F1 28.1% vs F2 71.4% vs F3 80.9%, P < 0.001). There were no significant differences in tumour xenograft differentiation and cell proliferation between human samples and the three experimental models among the sequential generations of tumour xenografts. However, a progressive decrease in fibrosis, fibrogenesis, tumour vascularisation and apoptosis was observed in the three experimental models compared with the human samples. All three pancreatic patient-derived xenograft models presented similar histological and immunohistochemical characteristics.CONCLUSION In our experience, the faster development andgreatest number of viable xenografts could make the subcutaneous model the best option for experimentation in pancreatic cancer.

Modeling One Dimensional Two-Cell Model with Tumor Interaction Using Krylov Subspace Methods

A brain tumor occurs when abnormal cells grow, sometimes very rapidly, into an abnormal mass of tissue. The tumor can infect normal tissue, so there is an interaction between healthy and infected cell. The aim of this paper is to propose some efficient and accurate numerical methods for the computational solution of one-dimensional continuous basic models for the growth and control of brain tumors. After computing the analytical solution, we construct approximations of the solution to the problem using a standard second order finite difference method for space discretization and the Crank-Nicolson method for time discretization. Then, we investigate the convergence behavior of Conjugate gradient and generalized minimum residual as Krylov subspace methods to solve the tridiagonal toeplitz matrix system derived.

3D bioprinting of in vitro porous hepatoma models:establishment,evaluation,and anticancer drug testing

Traditional tumor models do not tend to accurately simulate tumor growth in vitro or enable personalized treatment and are particularly unable to discover more beneficial targeted drugs.To address this,this study describes the use of threedimensional(3D)bioprinting technology to construct a 3D model with human hepatocarcinoma SMMC-7721 cells(3DP-7721)by combining gelatin methacrylate(GelMA)and poly(ethylene oxide)(PEO)as two immiscible aqueous phases to form a bioink and innovatively applying fluorescent carbon quantum dots for long-term tracking of cells.The GelMA(10%,mass fraction)and PEO(1.6%,mass fraction)hydrogel with 3:1 volume ratio offered distinct pore-forming characteristics,satisfactorymechanical properties,and biocompatibility for the creation of the 3DP-7721 model.Immunofluorescence analysis and quantitative real-time fluorescence polymerase chain reaction(PCR)were used to evaluate the biological properties of the model.Compared with the two-dimensional culture cell model(2D-7721)and the 3D mixed culture cell model(3DM-7721),3DP-7721 significantly improved the proliferation of cells and expression of tumor-related proteins and genes.Moreover,we evaluated the differences between the three culture models and the effectiveness of antitumor drugs in the three models and discovered that the efficacy of antitumor drugs varied because of significant differences in resistance proteins and genes between the three models.In addition,the comparison of tumor formation in the three models found that the cells cultured by the 3DP-7721 model had strong tumorigenicity in nude mice.Immunohistochemical evaluation of the levels of biochemical indicators related to the formation of solid tumors showed that the 3DP-7721 model group exhibited pathological characteristics of malignant tumors,the generated solid tumors were similar to actual tumors,and the deterioration was higher.This research therefore acts as a foundation for the application of 3DP-7721 models in drug development research.

Computed tomography radiogenomics:A potential tool for prediction of molecular subtypes in gastric stromal tumor

BACKGROUND Preoperative knowledge of mutational status of gastrointestinal stromal tumors(GISTs)is essential to guide the individualized precision therapy.AIM To develop a combined model that integrates clinical and contrast-enhanced computed tomography(CE-CT)features to predict gastric GISTs with specific genetic mutations,namely KIT exon 11 mutations or KIT exon 11 codons 557-558 deletions.METHODS A total of 231 GIST patients with definitive genetic phenotypes were divided into a training dataset and a validation dataset in a 7:3 ratio.The models were constructed using selected clinical features,conventional CT features,and radiomics features extracted from abdominal CE-CT images.Three models were developed:ModelCT sign,modelCT sign+rad,and model CTsign+rad+clinic.The diagnostic performance of these models was evaluated using receiver operating characteristic(ROC)curve analysis and the Delong test.RESULTS The ROC analyses revealed that in the training cohort,the area under the curve(AUC)values for model_(CT sign),model_(CT sign+rad),and modelCT_(sign+rad+clinic)for predicting KIT exon 11 mutation were 0.743,0.818,and 0.915,respectively.In the validation cohort,the AUC values for the same models were 0.670,0.781,and 0.811,respectively.For predicting KIT exon 11 codons 557-558 deletions,the AUC values in the training cohort were 0.667,0.842,and 0.720 for model_(CT sign),model_(CT sign+rad),and modelCT_(sign+rad+clinic),respectively.In the validation cohort,the AUC values for the same models were 0.610,0.782,and 0.795,respectively.Based on the decision curve analysis,it was determined that the model_(CT sign+rad+clinic)had clinical significance and utility.CONCLUSION Our findings demonstrate that the combined modelCT_(sign+rad+clinic)effectively distinguishes GISTs with KIT exon 11 mutation and KIT exon 11 codons 557-558 deletions.This combined model has the potential to be valuable in assessing the genotype of GISTs.

Visualization analysis of research hotspots and trends on gastrointestinal tumor organoids

BACKGROUND Gastrointestinal tumor organoids serve as an effective model for simulating cancer in vitro and have been applied in basic biology and preclinical research.Despite over a decade of development and increasing research achievements in this field,a systematic and comprehensive analysis of the research hotspots and future trends is lacking.AIM To address this problem by employing bibliometric tools to explore the publication years,countries/regions,institutions,journals,authors,keywords,and references in this field.METHODS The literature was collected from Web of Science databases.CiteSpace-6.2R4,a widely used bibliometric analysis software package,was used for institutional analysis and reference burst analysis.VOSviewer 1.6.19 was used for journal cocitation analysis,author co-authorship and co-citation analysis.The‘online platform for bibliometric analysis(https://bibliometric.com/app)’was used to assess the total number of publications and the cooperation relationships between countries.Finally,we employed the bibliometric R software package(version R.4.3.1)in R-studio,for a comprehensive scientific analysis of the literature.RESULTS Our analysis included a total of 1466 publications,revealing a significant yearly increase in articles on the study of gastrointestinal tumor organoids.The United States(n=393)and Helmholtz Association(n=93)have emerged as the leading countries and institutions,respectively,in this field,with Hans Clevers and Toshiro Sato being the most contributing authors.The most influential journal in this field is Gastroenterology.The most impactful reference is"Long term expansion of epithelial organs from human colon,adenoma,adenocarcinoma,and Barrett's epithelium".Keywords analysis and citation burst analysis indicate that precision medicine,disease modeling,drug development and screening,and regenerative medicine are the most cutting-edge directions.These focal points were further detailed based on the literature.CONCLUSION This bibliometric study offers an objective and quantitative analysis of the research in this field,which can be considered as an important guide for next scientific research.

Establishment,functional and genetic characterization of three novel patient-derived rectal cancer cell lines

AIM To establish patient-individual tumor models of rectal cancer for analyses of novel biomarkers, individual response prediction and individual therapy regimens.METHODS Establishment of cell lines was conducted by direct in vitro culturing and in vivo xenografting with subsequent in vitro culturing. Cell lines were in-depth characterized concerning morphological features, invasive and migratory behavior, phenotype, molecular profile including mutational analysis, protein expression, and confirmation of origin by DNA fingerprint. Assessment of chemosensitivity towards an extensive range of current chemotherapeutic drugs and of radiosensitivity was performed including analysis of a combined radioand chemotherapeutic treatment. In addition, glucose metabolism was assessed with 18 F-fluorodeoxyglucose(FDG) and proliferation with 18 F-fluorothymidine.RESULTS We describe the establishment of ultra-low passage rectal cancer cell lines of three patients suffering from rectal cancer. Two cell lines(HROC126, HROC284 Met) were established directly from tumor specimens while HROC239 T0 M1 was established subsequent to xenografting of the tumor. Molecular analysis classified all three cell lines as CIMP-0/non-MSI-H(sporadic standard) type. Mutational analysis revealed following mutational profiles: HROC126: APC^(wt), TP53^(wt), KRAS^(wt), BRAF^(wt), PTEN^(wt); HROC239 T0 M1: APC^(mut), P53^(wt), KRAS^(mut), BRAF^(wt), PTEN^(mut) and HROC284 Met: APC^(wt), P53^(mut), KRAS^(mut), BRAF^(wt), PTEN^(mut). All cell lines could be characterized as epithelial(EpCAM+) tumor cells with equivalent morphologic features and comparable growth kinetics. The cell lines displayed a heterogeneous response toward chemotherapy, radiotherapy and their combined application. HROC126 showed a highly radio-resistant phenotype and HROC284 Met was more susceptible to a combined radiochemotherapy than HROC126 and HROC239 T0 M1. Analysis of 18 F-FDG uptake displayed a markedly reduced FDG uptake of all three cell lines after combined radiochemotherapy. CONCLUSION These newly established and in-depth characterized ultra-low passage rectal cancer cell lines provide a useful instrument for analysis of biological characteristics of rectal cancer.

A multidimensional platform of patient-derived tumors identifies drug susceptibilities for clinical lenvatinib resistance

Lenvatinib,a second-generation multi-receptor tyrosine kinase inhibitor approved by the FDA for first-line treatment of advanced liver cancer,facing limitations due to drug resistance.Here,we applied a multidimensional,high-throughput screening platform comprising patient-derived resistant liver tumor cells(PDCs),organoids(PDOs),and xenografts(PDXs)to identify drug susceptibilities for conquering lenvatinib resistance in clinically relevant settings.Expansion and passaging of PDCs and PDOs from resistant patient liver tumors retained functional fidelity to lenvatinib treatment,expediting drug repurposing screens.Pharmacological screening identified romidepsin,YM155,apitolisib,NVP-TAE684 and dasatinib as potential antitumor agents in lenvatinib-resistant PDC and PDO models.Notably,romidepsin treatment enhanced antitumor response in syngeneic mouse models by triggering immunogenic tumor cell death and blocking the EGFR signaling pathway.A combination of romidepsin and immunotherapy achieved robust and synergistic antitumor effects against lenvatinib resistance in humanized immunocompetent PDX models.Collectively,our findings suggest that patient-derived liver cancer models effectively recapitulate lenvatinib resistance observed in clinical settings and expedite drug discovery for advanced liver cancer,providing a feasible multidimensional platform for personalized medicine.

Early changes of hepatic hemodynamics measured by functional CT perfusion in a rabbit model of liver tumor

BACKGROUND:Early detection and treatment of hepatocellular carcinoma is crucial to improving the patients’ survival.The hemodynamic changes caused by tumors can be serially measured using CT perfusion.In this study,we used a CT perfusion technique to demonstrate the changes of hepatic hemodynamics in early tumor growth,as a proof-of-concept study for human early hepatocellular carcinoma.METHODS:VX2 tumors were implanted in the liver of ten New Zealand rabbits.CT perfusion scans were made 1 week(early) and 2 weeks(late) after tumor implantation.Ten normal rabbits served as controls.CT perfusion parameters were obtained at the tumor rim,normal tissue surrounding the tumor,and control liver;the parameters were hepatic blood flow,hepatic blood volume,mean transit time,permeability of capillary vessel surface,hepatic arterial index,hepatic arterial perfusion and hepatic portal perfusion.Microvessel density and vascular endothelial growth factor were correlated.RESULTS:At the tumor rim,compared to the controls,hepatic blood flow,hepatic blood volume,permeability of capillary vessel surface,hepatic arterial index,and hepatic arterial perfusion increased,while mean transit time and hepatic portal perfusion decreased on both early and late scans(P<0.05).Hepatic arterial index increased(135%,P<0.05),combined with a sharp increase in hepatic arterial perfusion(182%,P<0.05) and a marked decrease in hepatic portal perfusion(-76%,P<0.05) at 2 weeks rather than at 1 week(P<0.05).Microvessel density and vascular endothelial growth factor showed significant linear correlations with hepatic blood flow,permeability of capillary vessel surface and hepatic arterial index,but not with hepatic blood volume or mean transit time.CONCLUSION:The CT perfusion technique demonstrated early changes of hepatic hemodynamics in this tumor model as proof-of-concept for early hepatocellular carcinoma detection in humans.

Hepatocellular carcinoma mouse models:Hepatitis B virusassociatedhepatocarcinogenesis and haploinsufficienttumor suppressor genes

The multifactorial and multistage pathogenesis of hepatocellular carcinoma(HCC)has fascinated a wide spectrum of scientists for decades.While a number of major risk factors have been identified,their mechanistic roles in hepatocarcinogenesis still need to be elucidated.Many tumor suppressor genes(TSGs)have been identified as being involved in HCC.These TSGs can be classified into two groups depending on the situation with respect to allelic mutation/loss in the tumors:the recessive TSGs with two required mutated alleles and the haploinsufficient TSGs with one required mutated allele.Hepatitis B virus(HBV)is one of the most important risk factors associated with HCC.Although mice cannot be infected with HBV due to the narrow host range of HBV and the lack of a proper receptor,one advantage of mouse models for HBV/HCC research is the numerous and powerfulgenetic tools that help investigate the phenotypic effects of viral proteins and allow the dissection of the dose-dependent action of TSGs.Here,we mainly focus on the application of mouse models in relation to HBV-associated HCC and on TSGs that act either in a recessive or in a haploinsufficient manner.Discoveries obtained using mouse models will have a great impact on HCC translational medicine.

Effects of Lvy noise and immune delay on the extinction behavior in a tumor growth model

The combined effects of Ltvy noise and immune delay on the extinction behavior in a tumor growth model are explored, The extinction probability of tumor with certain density is measured by exit probability. The expression of the exit probability is obtained using the Taylor expansion and the infinitesimal generator theory. Based on numerical calculations, it is found that the immune delay facilitates tumor extinction when the stability index α〈 1, but inhibits tumor extinction when the stability index α 〉 1. Moreover, larger stability index and smaller noise intensity are in favor of the extinction for tumor with low density. While for tumor with high density, the stability index and the noise intensity should be reduced to promote tumor extinction.

Prediction of tumor biological characteristics in different colorectal cancer liver metastasis animal models using^(18)F-FDG and^(18)F-FLT

Background: Positron emission tomography(PET) is a noninvasive method to characterize different metabolic activities of tumors, providing information for staging, prognosis, and therapeutic response of patients with cancer. The aim of this study was to evaluate the feasibility of18F-fludeoxyglucose(18F-FDG) and 3’-deoxy-3’-18F-fluorothymidine(18F-FLT) PET in predicting tumor biological characteristics of colorectal cancer liver metastasis.Methods: The uptake rate of18F-FDG and18F-FLT in SW480 and SW620 cells was measured via an in vitro cell uptake assay. The region of interest was drawn over the tumor and liver to calculate the maximum standardized uptake value ratio(tumor/liver) from PET images in liver metastasis model. The correlation between tracer uptake in liver metastases and VEGF, Ki67 and CD44 expression was evaluated by linear regression.Results: Compared to SW620 tumor-bearing mice, SW480 tumor-bearing mice presented a higher rate of liver metastases. The uptake rate of18F-FDG in SW480 and SW620 cells was 6.07% ± 1.19% and2.82% ± 0.15%, respectively(t = 4.69, P = 0.04); that of18F-FLT was 24.81% ± 0.45% and 15.57% ± 0.66%, respectively(t = 19.99, P < 0.001). Micro-PET scan showed that all parameters of FLT were significantly higher in SW480 tumors than those in SW620 tumors. A moderate relationship was detected between metastases in the liver and18F-FLT uptake in primary tumors(r = 0.73, P = 0.0019).18F-FLT uptake was also positively correlated with the expression of CD44 in liver metastases(r = 0.81, P = 0.0049).Conclusions: The uptake of18F-FLT in metastatic tumor reflects different biological behaviors of colon cancer cells.18F-FLT can be used to evaluate the metastatic potential of colorectal cancer in nude mice.

Advances in prostate cancer research models:From transgenic mice to tumor xenografting models

The identification of the origin and molecular characteristics of prostate cancer(PCa)has crucial implications for personalized treatment.The development of effective treatments for PCa has been limited;however,the recent establishment of several transgenicmouse lines and/or xenografting models is better reflecting the disease in vivo.With appropriate models,valuable tools for elucidating the functions of specific genes have gone deep into prostate development and carcinogenesis.In the present review,we summarize a number of important PCa research models established in our laboratories(PSA-Cre-ERT2/PTEN transgenic mouse models,AP-OX model,tissue recombination-xenografting models and PDX models),which represent advances of translational models from transgenic mouse lines to human tumor xenografting.Better understanding of the developments of these models will offer new insights into tumor progression and may help explain the functional significance of genetic variations in PCa.Additionally,this understanding could lead to new modes for curing PCa based on their particular biological phenotypes.

Similarity on neural stem cells and brain tumor stem cells in transgenic brain tumor mouse models

Although it is believed that glioma is derived from brain tumor stem cells, the source and molecular signal pathways of these cells are still unclear. In this study, we used stable doxycycline-inducible transgenic mouse brain tumor models （c-myc/SV40Tag＋/Tet-on＋） to explore the malignant trans- formation potential of neural stem cells by observing the differences of neural stem cells and brain tumor stem cells in the tumor models. Results showed that chromosome instability occurred in brain tumor stem cells. The numbers of cytolysosomes and autophagosomes in brain tumor stem cells and induced neural stem cells were lower and the proliferative activity was obviously stronger than that in normal neural stem cells. Normal neural stem cells could differentiate into glial fibrillary acidic protein-positive and microtubule associated protein-2-positive cells, which were also negative for nestin. However, glial fibrillary acidic protein/nestin, microtubule associated protein-2/nestin, and glial fibrillary acidic protein/microtubule associated protein-2 double-positive cells were found in induced neural stem cells and brain tumor stem cells. Results indicate that induced neural stem cells are similar to brain tumor stem cells, and are possibly the source of brain tumor stem cells.

3D tumor model biofabrication

Animal models have been extensively used in cancer pathology studies and drug discovery.These models,however,fail to reflect the complex human tumor microenvironment and do not allow for high-throughput drug screening in more human-like physiological conditions.Three-dimensional(3D)cancer models present an alternative to automated high-throughput cancer drug discovery and oncology.In this review,we highlight recent technology innovations in building 3D tumor models that simulate the complex human tumor microenvironment and responses of patients to treatment.We discussed various biofabrication technologies,including 3D bioprinting techniques developed for characterizing tumor progression,metastasis,and response to treatment.