Immune Response to Combination Therapy for Non-Hodgkin Lymphomas

A parametric model of tumor response to combination therapy in the presence of an immune system is described. Synergistic mechanisms which induce tumor regression are simulated with a coupled set of equations. The simulations are first compared to tumor history data obtained with a SCID mouse model to determine key parameters; predictions are then made for an immune-competent animal. The minimum immune cell birth rate relative to malignant B-cell birth rate necessary to induce tumor regression is determined, and optimization of drug combinations in the presence of an immune response is explored. The delayed effect of an immune response relative to drug scheduling is examined, and a mechanism for disease transformation in heterogeneous tumors is proposed.     

Optimal scheduling of radiotherapy and angiogenic inhibitors

We incorporate a previously validated mathematical model of a vascularized tumor into an optimal control problem to determine the temporal scheduling of radiotherapy and angiogenic inhibitors that maximizes the control of a primary tumor. Our results reveal that optimal antiangiogenic monotherapy gives a large initial injection to attain a 20: 1 ratio of tumor cell volume to supporting vasculature volume. It thereafter maintains this 20: 1 ratio via a continuous dose rate that is intensified over time. The optimal radiation monotherapy schedule is characterized by amodest dose intensification over time. The best performance is achieved by our optimal combination regimen, where the antiangiogenic treatment again maintains a constant tumor-to-vasculature ratio, but is administered in a dose-intensified manner only during the latter portion of the radiation fractionation schedule.     

Taking the Lag out of Jet Lag through Model-Based Schedule Design

Travel across multiple time zones results in desynchronization of environmental time cues and the sleep–wake schedule from their normal phase relationships with the endogenous circadian system. Circadian misalignment can result in poor neurobehavioral performance, decreased sleep efficiency, and inappropriately timed physiological signals including gastrointestinal activity and hormone release. Frequent and repeated transmeridian travel is associated with long-term cognitive deficits, and rodents experimentally exposed to repeated schedule shifts have increased death rates. One approach to reduce the short-term circadian, sleep–wake, and performance problems is to use mathematical models of the circadian pacemaker to design countermeasures that rapidly shift the circadian pacemaker to align with the new schedule. In this paper, the use of mathematical models to design sleep–wake and countermeasure schedules for improved performance is demonstrated. We present an approach to designing interventions that combines an algorithm for optimal placement of countermeasures with a novel mode of schedule representation. With these methods, rapid circadian resynchrony and the resulting improvement in neurobehavioral performance can be quickly achieved even after moderate to large shifts in the sleep–wake schedule. The key schedule design inputs are endogenous circadian period length, desired sleep–wake schedule, length of intervention, background light level, and countermeasure strength. The new schedule representation facilitates schedule design, simulation studies, and experiment design and significantly decreases the amount of time to design an appropriate intervention. The method presented in this paper has direct implications for designing jet lag, shift-work, and non-24-hour schedules, including scheduling for extreme environments, such as in space, undersea, or in polar regions.     

Rapamycin Promotes Mouse 4T1 Tumor Metastasis that Can Be Reversed by a Dendritic Cell-Based Vaccine

Suppression of tumor metastasis is a key strategy for successful cancer interventions. Previous studies indicated that rapamycin (sirolimus) may promote tumor regression activity or enhance immune response against tumor targets. However, rapamycin also exhibits immunosuppressant effects and is hence used clinically as an organ transplantation drug. We hypothesized that the immunosuppressive activities of rapamycin might also negatively mediate host immunity, resulting in promotion of tumor metastasis. In this study, the effects of rapamycin and phytochemical shikonin were investigated in vitro and in vivo in a 4T1 mouse mammary tumor model through quantitative assessment of immunogenic cell death (ICD), autophagy, tumor growth and metastasis. Tumor-bearing mice were immunized with test vaccines to monitor their effect on tumor metastasis. We found that intraperitoneal (ip) administration of rapamycin after a tumor-resection surgery drastically increased the metastatic activity of 4T1 tumors. Possible correlation of this finding to human cancers was suggested by epidemiological analysis of data from Taiwan’s National Health Insurance Research Database (NHIRD). Since our previous studies showed that modified tumor cell lysate (TCL)-pulsed, dendritic cell (DC)-based cancer vaccines can effectively suppress metastasis in mouse tumor models, we assessed whether such vaccines may help offset this rapamycin-promoted metastasis. We observed that shikonin efficiently induced ICD of 4T1 cells in culture, and DC vaccines pulsed with shikonin-treated TCL (SK-TCL-DC) significantly suppressed rapamycin-enhanced metastasis and Treg cell expansion in test mice. In conclusion, rapamycin treatment in mice (and perhaps in humans) promotes metastasis and the effect may be offset by treatment with a DC-based cancer vaccine.     

A Multi-Component Model of Hodgkin's Lymphoma

Hodgkin’s lymphoma is an example for a tumor with an extremely tight interaction of tumor cells with cells from the tumor micro-environment. These so-called bystander cells are not inert but interact actively with the tumor cells. Some of these cells support tumor growth by delivery of co-stimulating and anti-apoptotic signals (“helper cells”). Other cells (“killer cells”) are involved in the anti-tumor immune response which is obviously not efficient enough for tumor elimination. The activity of both helper cells and killer cells is regulated by additional cells in the stroma (“regulatory cells”). The dynamic behavior of such multi-component systems is difficult to predict. In the present paper we propose a model that can be used for simulation of essential features of this system. In this model, tumor growth depends on (i) presence of few cancer stem cells, (ii) co-stimulation of cancer cells by the tumor stroma, (iii) activity of regulatory cells that suppress killer cells without suppression of helper cells. The success of cytotoxic/cytostatic therapy in this model varies depending on the therapy-related toxicity for each of the cell populations. The model also allows the analysis of immunotherapeutic interventions. Under certain conditions, paradox enhancement of tumor growth can occur after therapeutic intervention. The model might be useful for the design of new treatment strategies for Hodgkin’s lymphoma and other tumors with prominent tumor-stroma interaction.     

A Microenvironment Based Model of Antimitotic Therapy of Gompertzian Tumor Growth

A model of tumor growth, based on two-compartment cell population dynamics, and an overall Gompertzian growth has been previously developed. The main feature of the model is an inter-compartmental transfer function that describes the net exchange between proliferating (P) and quiescent (Q) cells and yields Gompertzian growth for tumor cell population N = P + Q. Model parameters provide for cell reproduction and cell death. This model is further developed here and modified to simulate antimitotic therapy. Therapy decreases the reproduction-rate constant and increases the death-rate constant of proliferating cells with no direct effect on quiescent cells. The model results in a system of two ODE equations (in N and P/N) that has an analytical solution. Net tumor growth depends on support from the microenvironment. Indirectly, this is manifested in the transfer function, which depends on the proliferation ratio, P/N. Antimitotic therapy will change P/N, and the tumor responds by slowing the transfer rate from P to Q. While the cellular effects of therapy are modeled as dependent only on antimitotic activity of the drug, the tumor response also depends on the tumor age and any previous therapies—after therapy, it is not the same tumor. The strength of therapy is simulated by the parameter λ, which is the ratio of therapy induced net proliferation rate constant versus the original. A pharmacodynamic factor inversely proportional to tumor size is implemented. Various chemotherapy regimens are simulated and the outcomes of therapy administered at different time points in the life history of the tumor are explored. Our analysis shows: (1) for a constant total dose administered, a decreasing dose schedule is marginally superior to an increasing or constant scheme, with more pronounced benefit for faster growing tumors, (2) the minimum dose to stop tumor growth is age dependent, and (3) a dose-dense schedule is favored. Faster growing tumors respond better to dose density.     

In vivo functional efficacy of tumor-specific T cells expanded using HLA-Ig based artificial antigen presenting cells (aAPC)

Adoptive immunotherapy for treatment of cancers and infectious diseases is often hampered by a high degree of variability in the final T cell product and in the limited in vivo function and survival of ex vivo expanded antigen-specific cytotoxic T cells (CTL). This has stimulated interest in development of standardized artificial antigen presenting cells (aAPC) to reliably expand antigen specific CTL. However, for successful immunotherapy the aAPC ex vivo generated CTL must have anti-tumor activity in vivo. Here, we demonstrate that HLA-Ig based aAPC stimulated tumor-specific CTL from human peripheral blood T lymphocytes showed robust expansion and functional activity in a human/SCID mouse melanoma model. HLA-Ig based aAPC expanded CTL were detected in the peripheral blood up to 15 days after transfer. Non-invasive bioluminescence imaging of tumor bearing mice demonstrated antigen dependent localization of transferred CTL to the tumor site. Moreover, adoptive transfer of HLA-Ig based aAPC generated CTL inhibited the tumor growth both in prevention and treatment modes of therapy and was comparable to that achieved by dendritic cell expanded CTL. Thus, our data demonstrate potential therapeutic in vivo activity of HLA-Ig based aAPC expanded CTL to control tumor growth.     

Intracellular accumulation and mechanism of action of doxorubicin in a spatio-temporal tumor model

A spatio-temporal model of tumor response to sequestered, intracellular doxorubicin is presented and simulated. An important feature of the model is the characterization of different mechanisms by which doxorubicin initiates the cell death cascade. The model predicts that the long-term response of the tumor to repeated rounds of therapy is very sensitive to changes in the threshold level of doxorubicin required to initiate apoptosis at the maximum rate. In fact, perturbations of this parameter mediate the difference between effective tumor regression and minimal growth delays. The model is also used to investigate which parameters are most influential in rendering the tumor drug resistant. Sensitivity analysis shows that decreasing cellular permeability, as opposed to decreasing sequestration rate or increasing cellular efflux, is the most effective way for tumor cells to overcome the growth control afforded by successive rounds of treatment.     

Phenomenological modeling of tumor diameter growth based on a mixed effects model

Over the last few years, taking advantage of the linear kinetics of the tumor growth during the steady-state phase, tumor diameter-based rather than tumor volume-based models have been developed for the phenomenological modeling of tumor growth. In this study, we propose a new tumor diameter growth model characterizing early, late and steady-state treatment effects. Model parameters consist of growth rhythms, growth delays and time constants and are meaningful for biologists. Biological experiments provide in vivo longitudinal data. The latter are analyzed using a mixed effects model based on the new diameter growth function, to take into account inter-mouse variability and treatment factors. The relevance of the tumor growth mixed model is firstly assessed by analyzing the effects of three therapeutic strategies for cancer treatment (radiotherapy, concomitant radiochemotherapy and photodynamic therapy) administered on mice. Then, effects of the radiochemotherapy treatment duration are estimated within the mixed model. The results highlight the model suitability for analyzing therapeutic efficiency, comparing treatment responses and optimizing, when used in combination with optimal experiment design, anti-cancer treatment modalities.     

Model-Based Tumor Growth Dynamics and Therapy Response in a Mouse Model of De Novo Carcinogenesis

Tumorigenesis is a complex, multistep process that depends on numerous alterations within the cell and contribution from the surrounding stroma. The ability to model macroscopic tumor evolution with high fidelity may contribute to better predictive tools for designing tumor therapy in the clinic. However, attempts to model tumor growth have mainly been developed and validated using data from xenograft mouse models, which fail to capture important aspects of tumorigenesis including tumor-initiating events and interactions with the immune system. In the present study, we investigate tumor growth and therapy dynamics in a mouse model of de novo carcinogenesis that closely recapitulates tumor initiation, progression and maintenance in vivo. We show that the rate of tumor growth and the effects of therapy are highly variable and mouse specific using a Gompertz model to describe tumor growth and a two-compartment pharmacokinetic/ pharmacodynamic model to describe the effects of therapy in mice treated with 5-FU. We show that inter-mouse growth variability is considerably larger than intra-mouse variability and that there is a correlation between tumor growth and drug kill rates. Our results show that in vivo tumor growth and regression in a double transgenic mouse model are highly variable both within and between subjects and that mathematical models can be used to capture the overall characteristics of this variability. In order for these models to become useful tools in the design of optimal therapy strategies and ultimately in clinical practice, a subject-specific modelling strategy is necessary, rather than approaches that are based on the average behavior of a given subject population which could provide erroneous results.     

High lipid content of irradiated human melanoma cells does not affect cytokine-matured dendritic cell function

Gamma irradiation is one of the methods used to sterilize melanoma cells prior to coculturing them with monocyte-derived immature dendritic cells in order to develop antitumor vaccines. However, the changes taking place in tumor cells after irradiation and their interaction with dendritic cells have been scarcely analyzed. We demonstrate here for the first time that after irradiation a fraction of tumor cells present large lipid bodies, which mainly contain triglycerides that are several-fold increased as compared to viable cells as determined by staining with Oil Red O and BODIPY 493/503 and by biochemical analysis. Phosphatidyl-choline, phosphatidyl-ethanolamine and sphingomyelin are also increased in the lipid bodies of irradiated cells. Lipid bodies do not contain the melanoma-associated antigen MART-1. After coculturing immature dendritic cells with irradiated melanoma cells, tumor cells tend to form clumps to which dendritic cells adhere. Under such conditions, dendritic cells are unable to act as stimulating cells in a mixed leukocyte reaction. However, when a maturation cocktail composed of TNF-alpha, IL-6, IL-1beta and prostaglandin E2 is added to the coculture, the tumor cells clumps disaggregate, dendritic cells remain free in suspension and their ability to efficiently stimulate allogeneic lymphocytes is restored. These results help to understand the events following melanoma cell irradiation, shed light about interactions between irradiated cells and dendritic cells, and may help to develop optimized dendritic cell vaccines for cancer therapy.     

Optimal Control in a Model of Dendritic Cell Transfection Cancer Immunotherapy

We construct a population dynamics model of the competition among immune system cells and generic tumor cells. Then, we apply the theory of optimal control to find the optimal schedule of injection of autologous dendritic cells used as immunotherapeutic agent.The optimization method works for a general ODE system and can be applied to find the optimal schedule in a variety of medical treatments that have been described by a mathematical model.     

Dynamic contrast-enhanced magnetic resonance imaging of sunitinib-induced vascular changes to schedule chemotherapy in renal cell carcinoma xenograft tumors

In an attempt to develop better therapeutic approaches for metastatic renal cell carcinoma (RCC), the combination of the antiangiogenic drug sunitinib with gemcitabine was studied. Using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), we have previously determined that a sunitinib dosage of 20 mg/kg per day increased kidney tumor perfusion and decreased vascular permeability in a preclinical murine RCC model. This sunitinib dosage causing regularization of tumor vessels was selected to improve delivery of gemcitabine to the tumor. DCE-MRI was used to monitor regularization of vasculature with sunitinib in kidney tumors to schedule gemcitabine. We established an effective and nontoxic schedule of sunitinib combined with gemcitabine consisting of pretreatment with sunitinib for 3 days followed by four treatments of gemcitabine at 20 mg/kg given 3 days apart while continuing daily sunitinib treatment. This treatment caused significant tumor growth inhibition resulting in small residual tumor nodules exhibiting giant tumor cells with degenerative changes, which were observed both in kidney tumors and in spontaneous lung metastases, suggesting a systemic antitumor response. The combined therapy caused a significant increase in mouse survival. DCE-MRI monitoring of vascular changes induced by sunitinib, gemcitabine, and both combined showed increased tumor perfusion and decreased vascular permeability in kidney tumors. These findings, confirmed histologically by thinning of tumor blood vessels, suggest that both sunitinib and gemcitabine exert antiangiogenic effects in addition to cytotoxic antitumor activity. These studies show that DCE-MRI can be used to select the dose and schedule of antiangiogenic drugs to schedule chemotherapy and improve its efficacy.     

腺病毒携带IL-12增强抗原致敏树突细胞在肝癌基因治疗中的研究

目的:近年来通过应用白介素-12治疗肿瘤取得良好效果,因此对国内外应用腺病毒携带IL-12增强抗原致敏树突细胞在肝癌基因治疗中的研究进展进行总结,以探索更为可行治疗方法。方法:运用Pubmed、Elsevier Sciencedirect、CNKI及万方全文数据库检索系统,以腺病毒,IL-12,肝癌,树突细胞为关键词,检索2008-01至2012-11月发表的文献。纳入标准:1)IL-12的生物学特性,在抗肿瘤过程中的免疫作用,2)应用腺病毒携带IL-12对抗肝癌治疗研究,3)肿瘤抗原致敏树突细胞对肿瘤的影响。根据纳入标准分析文献26篇。结果:通过腺病毒携带IL-12可以增强肿瘤抗原致敏树突细胞的免疫应答。并通过诱导肿瘤细胞的凋亡,减少新生血管的生成而对肿瘤产生直接抑制,有效抑制肝癌的生长和转移。结论:本文通过对IL-12的生物学特征、抗肿瘤通路、作用机制及在腺病毒介导下肿瘤抗原致敏树突细胞研究进展的概述,为腺病毒携带IL-12作为肝癌的基因治疗进一步提供理论依据和探索,期待在将来应用IL-12为基础的基因治疗一定会为包括肝癌在内的肿瘤治疗提供新的途径。     

Adoptive transfer of mammaglobin-a epitope specific CD8 T cells combined with a single low dose of total body irradiation eradicates breast tumors

Adoptive T cell therapy has proven to be beneficial in a number of tumor systems by targeting the relevant tumor antigen. The tumor antigen targeted in our model is Mammaglobin-A, expressed by approximately 80% of human breast tumors. Here we evaluated the use of adoptively transferred Mammaglobin-A specific CD8 T cells in combination with low dose irradiation to induce breast tumor rejection and prevent relapse. We show Mammaglobin-A specific CD8 T cells generated by DNA vaccination with all epitopes (Mammaglobin-A2.1, A2.2, A2.4 and A2.6) and full-length DNA in vivo resulted in heterogeneous T cell populations consisting of both effector and central memory CD8 T cell subsets. Adoptive transfer of spleen cells from all Mammaglobin-A2 immunized mice into tumor-bearing SCID/beige mice induced tumor regression but this anti-tumor response was not sustained long-term. Additionally, we demonstrate that only the adoptive transfer of Mammaglobin-A2 specific CD8 T cells in combination with a single low dose of irradiation prevents tumors from recurring. More importantly we show that this single dose of irradiation results in the down regulation of the macrophage scavenger receptor 1 on dendritic cells within the tumor and reduces lipid uptake by tumor resident dendritic cells potentially enabling the dendritic cells to present tumor antigen more efficiently and aid in tumor clearance. These data reveal the potential for adoptive transfer combined with a single low dose of total body irradiation as a suitable therapy for the treatment of established breast tumors and the prevention of tumor recurrence.     

Lymph Node Colonization Dynamics after Oral Salmonella Typhimurium Infection in Mice

An understanding of how pathogens colonize their hosts is crucial for the rational design of vaccines or therapy. While the molecular factors facilitating the invasion and systemic infection by pathogens are a central focus of research in microbiology, the population biological aspects of colonization are still poorly understood. Here, we investigated the early colonization dynamics of Salmonella enterica subspecies 1 serovar Typhimurium (S. Tm) in the streptomycin mouse model for diarrhea. We focused on the first step on the way to systemic infection — the colonization of the cecal lymph node (cLN) from the gut — and studied roles of inflammation, dendritic cells and innate immune effectors in the colonization process. To this end, we inoculated mice with mixtures of seven wild type isogenic tagged strains (WITS) of S. Tm. The experimental data were analyzed with a newly developed mathematical model describing the stochastic immigration, replication and clearance of bacteria in the cLN. We estimated that in the beginning of infection only 300 bacterial cells arrive in the cLN per day. We further found that inflammation decreases the net replication rate in the cLN by 23%. In mice, in which dendritic cell movement is impaired, the bacterial migration rate was reduced 10-fold. In contrast, mice that cannot generate toxic reactive oxygen species displayed a 4-fold higher migration rate from gut to cLN than wild type mice. Thus, combining infections with mixed inocula of barcoded strains and mathematical analysis represents a powerful method for disentangling immigration into the cLN from replication in this compartment. The estimated parameters provide an important baseline to assess and predict the efficacy of interventions.     

Dendritic Cell-Based Immunotherapy for Solid Tumors

As a treatment for solid tumors, dendritic cell (DC)-based immunotherapy has not been as effective as expected. Here, we review the reasons underlying the limitations of DC-based immunotherapy for solid tumors and ask what can be done to improve immune cell-based cancer therapies. Several reports show that, rather than a lack of immune induction, the limited efficacy of DC-based immunotherapy in cases of renal cell carcinoma (RCC) likely results from inhibition of immune responses by tumor-secreted TGF-β and an increase in the number of regulatory T (Treg) cells in and around the solid tumor. Indeed, unlike DC therapy for solid tumors, cytotoxic T lymphocyte (CTL) responses induced by DC therapy inhibit tumor recurrence after surgery; CTL responses also limit tumor metastasis induced by additional tumor-challenge in RCC tumor-bearing mice. Here, we discuss the mechanisms underlying the poor efficacy of DC-based therapy for solid tumors and stress the need for new and improved DC immunotherapies and/or combination therapies with killer cells to treat resistant solid tumors.     

Optimal control of tumor size used to maximize survival time when cells are resistant to chemotherapy.

The high failure rates encountered in the chemotherapy of some cancers suggest that drug resistance is a common phenomenon. In the current study, the tumor burden during therapy is used to slow the growth of the drug-resistant cells, thereby maximizing the survival time of the host. Three types of tumor growth model are investigated--Gompertz, logistic, and exponential. For each model, feedback controls are constructed that specify the optimal tumor mass as a function of the size of the resistant subpopulation. For exponential and logistic tumor growth, the tumor burden during therapy is shown to have little impact upon survival time. When the tumor is in Gompertz growth, therapies maintaining a large tumor burden double and sometimes triple the survival time under aggressive therapies. Aggressive therapies aim for a rapid reduction in the sensitive cell subpopulation. These conclusions are not dependent upon the values of the model constants that determine the mass of resistant cells. Since treatments maintaining a high tumor burden are optimal for Gompertz tumor growth and close to optimal for exponential and logistic tumor growth, it may no longer be necessary to know the growth characteristics of a tumor to schedule anticancer drugs.     

Downregulation of STAT3 phosphorylation enhances tumoricidal effect of IL-15-activated dendritic cell against doxorubicin-resistant lymphoma and leukemia via TNF-α

Although disputed by some, increasing evidence suggests that TNF-α synergies with traditional chemotherapeutic drugs to exert a heightened antitumor effect. The present study investigated the antitumor efficacy of recombinant IL-15 in combination with the STAT3 inhibitor cucurbitacin-I in a doxorubicin-resistant murine lymphoma model. The significance of the work is to understand and design effective strategies in doxorubicin resistant lymphomas. TNF-α is downregulated in dendritic cells from mice with Dalton's lymphoma and shows an inverse relationship with disease progression. Doxorubicin-resistant DL cells have elevated levels of Bcl-2 and Mcl-1 and increased phosphorylation of STAT3. These cells are refractory to dendritic cell derived TNF-α. Doxorubicin resistant Dalton's lymphoma is susceptible to dendritic cell derived TNF-α upon stimulation with the STAT3 inhibitor cucurbitacin-I, which downregulates STAT3 and other survival molecules. The combined treatment of low dose of cucurbitacin-I and rIL-15 is ineffective in mice with doxorubicin resistant Dalton's lymphoma, but a similar therapy prolongs the survival of mice transplanted with parental Dalton's lymphoma. Doxorubicin resistant Dalton's lymphoma responds to therapy with high doses of cucurbitacin-I and rIL-15. Dendritic cell derived from mice responded positively to the therapy and regained their tumoricidal properties with respect to growth inhibition and killing of DL tumor cells. Similar to DL, DC derived from CML patients are impaired in TNF-α expression and are unable to restrict the growth of drug-resistant lymphoma and leukemia cells. This combination approach could be used as a new therapeutic strategy for aggressive and highly metastatic doxorubicin resistant lymphoma.     

Key genes and pathways in tumor-educated dendritic cells by bioinformatical analysis

Specific tumor microenvironment signaling might prevent the maturation of dendritic cells (DCs) with tolerogenic and immunosuppressive potential accounting for antigen-specific unresponsiveness in the lymphoid organs and in the periphery. In the present study, dendritic cells treated with LLC lung cancer cell or 4T1 breast cancer cell culture supernatants significantly down-regulated the expression of co-stimulatory molecules MHC-II, CD40, CD80, but up-regulated the inhibitory molecule PD-L1/L2, VISTA, and increased the messengerRNA levels of interleukin (IL)-6, arginase I, and IL-10, but decreased tumor necrosis factor-α and IL-12a. RNA was isolated from the dendritic cells with or without tumor supernatant stimulation and RNA sequencing was done. Then the differential expression genes were sorted, the candidate genes were analyzed and pathway enrichment analysis was done, and the associated protein–protein interaction network (PPI) was established. After integrated bioinformatical analysis, 405 (279 up-regulated and 126 down-regulated) consistently differential expression genes were identified. Using gene ontology and pathway analysis, it was found that differential expression genes were mainly enriched in the immune response, cell–cell interaction, hemostasis, and cell surface interactions with the vascular wall. The PPI data demonstrated that 236 nodes were classified with 1072 edges, and the most remarkable three modules involved 53 central node genes associated with cell survival, cell-substrate adhesion, chemotaxis, migration, immune response, and complement receptor mediated signaling pathway. These findings revealed the immune status of dendritic cells in the tumor environment.