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.

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.

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.

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.

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.

Assessing the performance of different outcomes for tumor growth studies with animal models

The consistency of reporting results for patient-derived xenograft(PDX) studies is an area of concern. The PDX method commonly starts by implanting a derivative of a human tumor into a mouse, then comparing the tumor growth under different treatment conditions. Currently, a wide array of statistical methods(e.g., t-test, regression, chi-squared test) are used to analyze these data, which ultimately depend on the outcome chosen(e.g., tumor volume, relative growth, categorical growth). In this simulation study, we provide empirical evidence for the outcome selection process by comparing the performance of both commonly used outcomes and novel variations of common outcomes used in PDX studies. Data were simulated to mimic tumor growth under multiple scenarios, then each outcome of interest was evaluated for 10?000 iterations. Comparisons between different outcomes were made with respect to average bias, variance, type-1 error, and power. A total of 18 continuous, categorical, and time-to-event outcomes were evaluated, with ultimately 2 outcomes outperforming the others: final tumor volume and change in tumor volume from baseline.Notably, the novel variations of the tumor growth inhibition index(TGII)— a commonly used outcome in PDX studies— was found to perform poorly in several scenarios with inflated type-1 error rates and a relatively large bias. Finally, all outcomes of interest were applied to a real-world dataset.

Advantages and limitations in the establishment and utilization of patient-derived xenografts in gastric cancer

Owing to the high genetic heterogeneity of tumors, small number of therapeutic strategies available, and frequent presentation of drug resistance, the prognosis for patients with advanced gastric cancer(AGC) are unsatisfactory. The utility of traditional cancer cell lines in translational research is limited by their poor correspondence to the genomic alterations and expression profiles that occur in actual patient tumors. In the last decade, increasing attention has been given to patient-derived tumor xenografts(PDTXs), which can faithfully recapitulate the histopathology, molecular characteristics, and therapeutic responses of the patient's tumor. However, the widespread development and utilization of PDTXs is restricted by factors such as the timeframe of establishment, lymphoma transformation during passaging, the immunodeficient microenvironment, and pharmacokinetic differences between mice and humans. In this review, we summarize the establishment and characterization of PDTX models for gastric cancer(GC). We then weigh the advantages and limitations of PDTXs when used to evaluate novel compounds, identify effective biomarkers, demonstrate resistance mechanisms, and predict clinical outcomes.

Mouse models of colorectal cancer: Past, present and future perspectives

Colorectal cancer(CRC)is the third most common diagnosed malignancy among both sexes in the United States as well as in the European Union.While the incidence and mortality rates in western,high developed countries are declining,reflecting the success of screening programs and improved treatment regimen,a rise of the overall global CRC burden can be observed due to lifestyle changes paralleling an increasing human development index.Despite a growing insight into the biology of CRC and many therapeutic improvements in the recent decades,preclinical in vivo models are still indispensable for the development of new treatment approaches.Since the development of carcinogen-induced rodent models for CRC more than 80 years ago,a plethora of animal models has been established to study colon cancer biology.Despite tenuous invasiveness and metastatic behavior,these models are useful for chemoprevention studies and to evaluate colitis-related carcinogenesis.Genetically engineered mouse models(GEMM)mirror the pathogenesis of sporadic as well as inherited CRC depending on the specific molecular pathways activated or inhibited.Although the vast majority of CRC GEMM lack invasiveness,metastasis and tumor heterogeneity,they still have proven useful for examination of the tumor microenvironment as well as systemic immune responses;thus,supporting development of new therapeutic avenues.Induction of metastatic disease by orthotopic injection of CRC cell lines is possible,but the so generated models lack genetic diversity and the number of suited cell lines is very limited.Patient-derived xenografts,in contrast,maintain the pathological and molecular characteristics of the individual patient's CRC after subcutaneous implantation into immunodeficient mice and are therefore most reliable for preclinical drug development–even in comparison to GEMM or cell line-based analyses.However,subcutaneous patient-derived xenograft models are less suitable for studying most aspects of the tumor microenvironment and anti-tumoral immune responses.The authors review the distinct mouse models of CRC with an emphasis on their clinical relevance and shed light on the latest developments in the field of preclinical CRC models.

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.

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.

Prediction of Driver Gene Matching in Lung Cancer NOG/PDX Models Based on Artificial Intelligence

Patient-derived tumor xenografts(PDXs)are a powerful tool for drug discovery and screening in cancer.However,current studies have led to little understanding of genotype mismatches in PDXs,leading to massive economic losses.Here,we established PDX models from 53 lung cancer patients with a genotype matching rate of 79.2%(42/53).Furthermore,17 clinicopathological features were examined and input in stepwise logistic regression(LR)models based on the lowest Akaike information criterion(AIC),least absolute shrinkage and selection operator(LASSO)-LR,support vector machine(SVM)recursive feature elimination(SVM-RFE),extreme gradient boosting(XGBoost),gradient boosting and categorical features(Cat Boost),and the synthetic minority oversampling technique(SMOTE).Finally,the performance of all models was evaluated by the accuracy,area under the receiver operating characteristic curve(AUC),and F1 score in 100 testing groups.Two multivariable LR models revealed that age,number of driver gene mutations,epidermal growth factor receptor(EGFR)gene mutations,type of prior chemotherapy,prior tyrosine kinase inhibitor(TKI)therapy,and the source of the sample were powerful predictors.Moreover,Cat Boost(mean accuracy=0.960;mean AUC=0.939;mean F1 score=0.908)and the eight-feature SVM-RFE(mean accuracy=0.950;mean AUC=0.934;mean F1 score=0.903)showed the best performance among the algorithms.Meanwhile,application of the SMOTE improved the predictive capability of most models,except Cat Boost.Based on the SMOTE,the ensemble classifier of single models achieved the highest accuracy(mean=0.975),AUC(mean=0.949),and F1 score(mean=0.938).In conclusion,we established an optimal predictive model to screen lung cancer patients for non-obese diabetic(NOD)/Shi-scid,interleukin-2 receptor(IL-2R)γ^(null)(NOG)/PDX models and offer a general approach for building predictive models.

Evolution of Tumor Model: From Animal Model of Tumor to Tumor Model in Animal

Patient derived xenograft (PDX) is defined as a growth of patients’ tumor in the xenograft setting. The evolution of cancer model in animal has a century old history. The most single reason that exerted the pressure on the traditional animal model of cancer to evolve to PDX is that the traditional models have not delivered as expected and traditional models have not predicted clinical success. In spite of well above 50 drugs developed and approved for oncology over the last several decades, there remains a nirking paucity of clinical success as a reminder that this war on cancer riding on the animal model is far from won. In a backbreaking attempt to analyze the failure, the limitation of the “model” system appeared to be the most rational cause of this shortcoming. It was more of a failure to test a drug rather than a failure to make a drug that stunted our collective growth and success in cancer research. PDX is the product of this age-old failure and its fitness is currently tested in virtually all organ-type solid tumors. This review will present and appraise PDX model in the context of its evolution, its future promise, its limitations and more specifically, the current content of PDX in different solid tumors including breast, lung, colorectal, prostrate, GBM, pancreatic, hepatocellular carcinoma and melanoma.

SPA: A Quantitation Strategy for MS Data in Patient-derived Xenograft Models

With the development of mass spectrometry(MS)-based proteomics technologies,patient-derived xenograft(PDX),which is generated from the primary tumor of a patient,is widely used for the proteome-wide analysis of cancer mechanism and biomarker identification of a drug.However,the proteomics data interpretation is still challenging due to complex data deconvolution from the PDX sample that is a cross-species mixture of human cancerous tissues and immunodeficient mouse tissues.In this study,by using the lab-assembled mixture of human and mouse cells with different mixing ratios as a benchmark,we developed and evaluated a new method,SPA(shared peptide allocation),for protein quantitation by considering the unique and shared peptides of both species.The results showed that SPA could provide more convenient and accurate protein quantitation in human–mouse mixed samples.Further validation on a pair of gastric PDX samples(one bearing FGFR2 amplification while the other one not)showed that our new method not only significantly improved the overall protein identification,but also detected the differential phosphorylation of FGFR2 and its downstream mediators(such as RAS and ERK)exclusively.The tool pdx SPA is freely available at https://github.com/LiLab-Proteomics/pdx SPA.

Patient-derived xenograft models for oncology drug discovery

The success of targeted therapies for cancer patients rests on three major components:the right target(s),the right drug and drug combination,and the right patient population.Although much progress has been made in understanding the mechanism of disease and in refi ning pharmaceutical properties of therapeutic agents,the attrition rates between target discovery and drug marketing approval have been high,especially in oncology.One of the main reasons underlying this undesirable statistics is believed to be the lack of predictive power of the model systems used in the preclinical setting.Several strategies have been employed with the aim of improving the predictive value of the preclinical studies,such as incorporating genomic profi ling and molecular segmentation into model selection,and enhancing the development and application of patient-derived xenograft models even during early stage of drug discovery.This brief review will summarize some of the recent concept and practice in incorporating patient-derived models into all stages of drug discovery process,from target to clinical development.

Patient-derived tumor models and their distinctive applications in personalized drug therapy

Tumor models in vitro are conventional methods for developing anti-cancer drugs,evaluating drug delivery,or calculating drug efficacy.However,traditional cell line-derived tumor models are unable to capture the tumor heterogeneity in patients or mimic the interaction between tumors and their surroundings.Recently emerging patient-derived preclinical cancer models,including of patient-derived xenograft(PDX)model,circulating tumor cell(CTC)-derived model,and tumor organoids-on-chips,are promising in personalized drug therapy by reca-pitulating the complexities and personalities of tumors and surroundings.These patient-derived models have demonstrated potential advantages in satisfying the rigorous demands of specificity,accuracy,and efficiency necessary for personalized drug therapy.However,the selection of suitable models is depending on the specific therapeutic requirements dictated by cancer types,progressions,or the assay scale.As an example,PDX models show remarkable advantages to reconstruct solid tumors in vitro to understand drug delivery and metabolism.Similarly,CTC-derived models provide a sensitive platform for drug testing in advanced-stage patients,while also facilitating the development of drugs aimed at suppressing tumor metastasis.Meanwhile,the demand for large-scale testing has promoted the development of tumor organoids-on-chips,which serves as an optimal tool for high-throughput drug screening.This review summarizes the establishment and development of PDX,CTC-derived models,and tumor organoids-on-chips and addresses their distinctive advantages in drug discovery,sensitive testing,and screening,which demonstrate the potential to aid in the selection of suitable models for fundamental cancer research and clinical trials,and further developing the personalized drug therapy.

Patient-derived xenograft platform of OSCC： a renewable human bio-bank for preclinical cancer research and a new co-clinical model for treatment optimization

Advances in next-generation sequencing and bioinformatics have begun to reveal the complex genetic landscape in human cancer genomes, including oral squamous cell carcinoma （OSCC）. Sophisticated preclinical models that fully represent intra- and inter-tumoral heterogeneity are required to understand the molecular diversity of cancer and achieve the goal of personalized therapies. Patient-derived xenograft （PDX） models generated from human tumor samples that can retain the histological and genetic features of their donor tumors have been shown to be the preferred preclinical tool in translational cancer research compared with other conventional preclinical models. Specifically, genetically well-defined PDX models can be applied to accelerate targeted antitumor drug development and biomarker discovery. Recently, we have successfully established and characterized an OSCC PDX panel as part of our tumor bio-bank for translational cancer research. In this paper, we discuss the establishment, characterization, and preclinical applications of the PDX models. In particular, we focus on the classification and applications of the PDX models based on validated annotations, including clinicopathological features, genomic profiles, and pharmacological testing information. We also explore the translational value of this well-annotated PDX panel in the development of co-clinical trials for patient stratification and treatment optimization in the near future. Although various limitations still exist, this preclinical approach should be further tested and improved.

头颈部恶性肿瘤研究模型的演化

恶性肿瘤发生发展的机制探索以及抗癌药物治疗疗效的评估均有赖于各种体内与体外研究模型的建立。近几十年间,随着生物医学技术的快速发展,恶性肿瘤的体内外研究模型也发生了巨大的变化。基因检测技术从单基因到多基因的进展促进了生物信息学飞速发展和恶性肿瘤概念的转变;体外细胞研究模型从单层的二维培养、原代培养向立体的三维构型发展,从而更好地重现肿瘤组织的细胞间交互作用与功能;体内动物研究模型由传统的致癌物诱导、细胞或组织形成移植瘤逐渐演变为基因编辑的动物模型或人源性肿瘤异种移植模型,从而可以针对性地研究相关基因在肿瘤发生发展中的作用;传统的临床研究也从简单的临床回顾性研究更多地向前瞻性研究转变,Ⅰ期/Ⅱ期/Ⅲ期临床研究,研究者发起的临床研究以及真实世界临床研究,这些研究为临床研究增添了活力。目前恶性肿瘤研究模型存在的主要不足包括模型的单一性、对肿瘤微环境的模拟不足、动物肿瘤模型与人类肿瘤差异性,以及缺乏对个性化医疗的考量。未来仍需要进一步研发和优化研究模型,并更有效地将不同模型整合起来,形成一个优化的整体实验模型系统。本文将系统回顾恶性肿瘤研究模型的演化并对相关模型进行阐述,为科研工作者进行恶性肿瘤的研究提供合理的研究模型。

Novel dual inhibitor for targeting PIM1 and FGFR1 kinases inhibits colorectal cancer growth in vitro and patient-derived xenografts in vivo

Colorectal cancer(CRC) is the second most common cause of cancer-related death in the world. The pro-viral integration site for Moloney murine leukemia virus 1(PIM1) is a proto-oncogene and belongs to the serine/threonine kinase family, which are involved in cell proliferation, migration,and apoptosis. Fibroblast growth factor receptor 1(FGFR1) is a tyrosine kinase that has been implicated in cell proliferation, differentiation and migration. Small molecule HCI-48 is a derivative of chalcone, a class of compounds known to possess anti-tumor, anti-inflammatory and antibacterial effects. However,the underlying mechanism of chalcones against colorectal cancer remains unclear. This study reports that HCI-48 mainly targets PIM1 and FGFR1 kinases, thereby eliciting antitumor effects on colorectal cancer growth in vitro and in vivo. HCI-48 inhibited the activity of both PIM1 and FGFR1 kinases in an ATPdependent manner, as revealed by computational docking models. Cell-based assays showed that HCI-48inhibited cell proliferation in CRC cells(HCT-15, DLD1, HCT-116 and SW620), and induced cell cycle arrest in the G2/M phase through modulation of cyclin A2. HCI-48 also induced cellular apoptosis, as evidenced by an increase in the expression of apoptosis biomarkers such as cleaved PARP, cleaved caspase 3 and cleaved caspase 7. Moreover, HCI-48 attenuated the activation of downstream components of the PIM1 and FGFR1 signaling pathways. Using patient-derived xenograft(PDX) murine tumor models,we found that treatment with HCI-48 diminished the PDX tumor growth of implanted CRC tissue expressing high protein levels of PIM1 and FGFR1. This study suggests that the inhibitory effect of HCI-48 on colorectal tumor growth is mainly mediated through the dual-targeting of PIM1 and FGFR1kinases. This work provides a theoretical basis for the future application of HCI-48 in the treatment of clinical CRC.

转导蛋白β样1X连接受体1表达对卵巢癌A2780细胞增殖和迁移的影响

目的:研究转导蛋白β样1X连接受体1(transducin beta-like 1X-linked receptor,TBL1XR1)在卵巢癌患者组织中表达,及其对卵巢癌A2780细胞增殖和迁移的影响。方法:采用实时荧光定量PCR(qRT-PCR)检测10对卵巢癌组织、癌旁组织中及人卵巢癌IOSE80、A2780、CP70、SKOV-3中TBL1XR1 mRNA表达,筛选TBL1XR1 mRNA高表达细胞株。选择4~6周龄雌性BALB/C裸鼠,建立卵巢癌人源肿瘤异种移植(patient-derived tumor xenografts,PDTX)模型;将10只模型鼠均分为siR-NC组和si-TBL1XR1组,每组5只,分别给予siR-NC、si-TBL1XR1局部注射,10 mg/kg,每3 d注射1次,18 d后取各组瘤组织,计算其体积与重量。取卵巢癌A2780细胞,将其分为siR-NC组、si-TBL1XR1组、pcDNA3.1组和pcDNA3.1-TBL1XR1组,分别予以siR-NC、si-TBL1XR1、pcDNA3.1空载质粒和pcDNA3.1-TBL1XR1质粒处理;采用蛋白免疫印迹法检测各组卵巢癌细胞周期蛋白表达,MTT比色法检测细胞活力,流式细胞术检测细胞周期和凋亡细胞比例,以及Transwell细胞迁移实验检测细胞迁移能力。结果:卵巢癌组织中TBL1XR1 mRNA表达明显高于癌旁组织(P<0.05);人卵巢癌A2780细胞系TBL1XR1 mRNA表达明显高于卵巢癌IOSE80、CP70、SKOV-3细胞系(P<0.05)。与siR-NC组相比,第18天si-TBL1XR1组瘤体积明显减小(P<0.05),重量明显降低(P<0.05)。与siR-NC组相比,si-TBL1XR1组促癌细胞周期蛋白表达明显降低(P<0.05),与pcDNA3.1组相比,pcDNA3.1-TBL1XR1组表达则明显升高(P<0.05);与siR-NC组相比,si-TBL1XR1组卵巢癌细胞迁移数明显降低(P<0.05),早期凋亡和晚期凋亡细胞比例明显升高(P<0.05);与pcDNA3.1组相比,pcDNA3.1-TBL1XR1组卵巢癌细胞迁移数明显增多(P<0.05),早期凋亡和晚期凋亡细胞比例明显降低(P<0.05)。结论:TBL1XR1在卵巢癌组织中呈高表达,降低TBL1XR1 mRNA表达可抑制卵巢癌A2780细胞增殖和迁移。

白桦脂醇通过抑制PI3K/AKT途径抑制宫颈癌小鼠移植瘤增殖

目的:阐明白桦脂醇对宫颈癌细胞系c4-1移植瘤模型裸鼠的影响和机制。方法:皮下注射宫颈癌细胞系c4-1建立异种移植瘤模型,将移植瘤BALB/c裸鼠模型随机分为3组:对照组(DMSO)、白桦脂醇低剂量组(Betulin50)、白桦脂醇高剂量组(Betulin200),进行后续使用。白桦脂醇治疗后,检测移植瘤体积和裸鼠存活率;免疫组化检测Ki67和血管内皮生长因子(VEGF)表达水平;TUNEL实验检测移植瘤细胞凋亡情况;Westernblot检测磷脂酰肌醇3-激酶(PI3K)/AKT通路蛋白表达情况和磷酸化情况。结果:与对照组(DMSO)相比较,白桦脂醇低剂量组(Betulin50)、白桦脂醇高剂量组(Betulin200)肿瘤体积明显减小(P<0.01),裸鼠存活率明显增加(P<0.01),Ki67和VEGF表达水平明显下降(P<0.01),且PI3K/AKT磷酸化水平明显被抑制(P<0.01)。结论:白桦脂醇能抑制c4-1移植瘤体积,增加移植瘤裸鼠存活率,下调Ki67和VEGF表达水平和PI3K/AKT磷酸化水平。白桦脂醇可能通过抑制PI3K/AKT信号通路抑制宫颈癌细胞系c4-1移植瘤。