Modeling antitumor activity in xenograft tumor treatment

To analyze responses of solid tumors to treatment with antitumor therapy, we applied nonparametric mixed-effects models to investigate tumor volumes measured over a fixed. The population and individual response functions were approximated by penalized splines. Linear mixed-effects modeling was applied in the implementation of the estimation. We applied the approach to an analysis of a real xenograft study of a new antitumor agent, temozolomide, combined with irinotecan. The model fitted the data very well. We conducted a sensitivity analysis to determine the effect of informative dropout. We also propose an intuitive approach to a comparison of the antitumor effects of two different treatments. Biological interpretations and clinical implications are discussed.     

Small interfering RNA targeted to IGF-IR delays tumor growth and induces proinflammatory cytokines in a mouse breast cancer model

Insulin-like growth factor I (IGF-I) and its type I receptor (IGF-IR) play significant roles in tumorigenesis and in immune response. Here, we wanted to know whether an RNA interference approach targeted to IGF-IR could be used for specific antitumor immunostimulation in a breast cancer model. For that, we evaluated short interfering RNA (siRNAs) for inhibition of in vivo tumor growth and immunological stimulation in immunocompetent mice. We designed 2'-O-methyl-modified siRNAs to inhibit expression of IGF-IR in two murine breast cancer cell lines (EMT6, C4HD). Cell transfection of IGF-IR siRNAs decreased proliferation, diminished phosphorylation of downstream signaling pathway proteins, AKT and ERK, and caused a G0/G1 cell cycle block. The IGF-IR silencing also induced secretion of two proinflammatory cytokines, TNF- α and IFN-γ. When we transfected C4HD cells with siRNAs targeting IGF-IR, mammary tumor growth was strongly delayed in syngenic mice. Histology of developing tumors in mice grafted with IGF-IR siRNA treated C4HD cells revealed a low mitotic index, and infiltration of lymphocytes and polymorphonuclear neutrophils, suggesting activation of an antitumor immune response. When we used C4HD cells treated with siRNA as an immunogen, we observed an increase in delayed-type hypersensitivity and the presence of cytotoxic splenocytes against wild-type C4HD cells, indicative of evolving immune response. Our findings show that silencing IGF-IR using synthetic siRNA bearing 2'-O-methyl nucleotides may offer a new clinical approach for treatment of mammary tumors expressing IGF-IR. Interestingly, our work also suggests that crosstalk between IGF-I axis and antitumor immune response can mobilize proinflammatory cytokines.     

IL-21 activates both innate and adaptive immunity to generate potent antitumor responses that require perforin but are independent of IFN-gamma

IL-21 is a key factor in the transition between innate and adaptive immune responses. We have used the cytokine gene therapy approach to study the antitumor responses mediated by IL-21 in the B16F1 melanoma and MethA fibrosarcoma tumor models in mice. Retrovirally transduced tumor cells secreting biologically functional IL-21 have growth patterns in vitro similar to that of control green fluorescent protein-transduced cells, but are completely rejected in vivo. We show that IL-21 activates NK and CD8(+) T cells in vivo, thus mediating complete rejection of poorly immunogenic tumors. Rejection of IL-21-secreting tumors requires the presence of cognate IL-21R and does not depend on CD4(+) T cell help. Interestingly, perforin, but not IFN-gamma or other major Th1 and Th2 cytokines (IL-12, IL-4, or IL-10), is required for the IL-21-mediated antitumor response. Moreover, IL-21 results in 50% protection and 70% cure of nonimmunogenic tumors when given before and after tumor challenge, respectively, in C57BL/6 mice. We conclude that IL-21 immunotherapy warrants clinical evaluation as a potential treatment for cancer.     

Association rule mining based study for identification of clinical parameters akin to occurrence of brain tumor

Healthcare sector is generating a large amount of information corresponding to diagnosis, disease identification and treatment of an individual. Mining knowledge and providing scientific decision-making for the diagnosis & treatment of disease from the clinical dataset is therefore increasingly becoming necessary. Aim of this study was to assess the applicability of knowledge discovery in brain tumor data warehouse, applying data mining techniques for investigation of clinical parameters that can be associated with occurrence of brain tumor. In this study, a brain tumor warehouse was developed comprising of clinical data for 550 patients. Apriori association rule algorithm was applied to discover associative rules among the clinical parameters. The rules discovered in the study suggests - high values of Creatinine, Blood Urea Nitrogen (BUN), SGOT & SGPT to be directly associated with tumor occurrence for patients in the primary stage with atleast 85% confidence and more than 50% support. A normalized regression model is proposed based on these parameters along with Haemoglobin content, Alkaline Phosphatase and Serum Bilirubin for prediction of occurrence of STATE (brain tumor) as 0 (absent) or 1 (present). The results indicate that the methodology followed will be of good value for the diagnostic procedure of brain tumor, especially when large data volumes are involved and screening based on discovered parameters would allow clinicians to detect tumors at an early stage of development.     

Delineating the longitudinal tumor evolution using organoid models

Cancer is an evolutionary process fueled by genetic or epigenetic alterations in the genome. Understanding the evolutionary dynamics that are operative at different stages of tumor progression might inform effective strategies in early detection, diagnosis, and treatment of cancer. However, our understanding on the dynamics of tumor evolution through time is very limited since it is usually impossible to sample patient tumors repeatedly. The recent advances in in vitro 3D organoid culture technologies have opened new avenues for the development of more realistic human cancer models that mimic many in vivo biological characteristics in human tumors. Here, we review recent progresses and challenges in cancer genomic evolution studies and advantages of using tumor organoids to study cancer evolution. We propose to establish an experimental evolution model based on continuous passages of patient-derived organoids and longitudinal sampling to study clonal dynamics and evolutionary patterns over time. Development and integration of population genetic theories and computational models into time-course genomic data in tumor organoids will help to pinpoint the key cellular mechanisms underlying cancer evolutionary dynamics, thus providing novel insights on therapeutic strategies for highly dynamic and heterogeneous tumors.     

Modeling and testing treated tumor growth using cubic smoothing splines

Human tumor xenograft models are often used in preclinical study to evaluate the therapeutic efficacy of a certain compound or a combination of certain compounds. In a typical human tumor xenograft model, human carcinoma cells are implanted to subjects such as severe combined immunodeficient (SCID) mice. Treatment with test compounds is initiated after tumor nodule has appeared, and continued for a certain time period. Tumor volumes are measured over the duration of the experiment. It is well known that untreated tumor growth may follow certain patterns, which can be described by certain mathematical models. However, the growth patterns of the treated tumors with multiple treatment episodes are quite complex, and the usage of parametric models is limited. We propose using cubic smoothing splines to describe tumor growth for each treatment group and for each subject, respectively. The proposed smoothing splines are quite flexible in modeling different growth patterns. In addition, using this procedure, we can obtain tumor growth and growth rate over time for each treatment group and for each subject, and examine whether tumor growth follows certain growth pattern. To examine the overall treatment effect and group differences, the scaled chi-squared test statistics based on the fitted group-level growth curves are proposed. A case study is provided to illustrate the application of this method, and simulations are carried out to examine the performances of the scaled chi-squared tests.     

A Mathematical Model of the Enhancement of Tumor Vaccine Efficacy by Immunotherapy

TGF-β is an immunoregulatory protein that contributes to inadequate antitumor immune responses in cancer patients. Recent experimental data suggests that TGF-β inhibition alone, provides few clinical benefits, yet it can significantly amplify the anti-tumor immune response when combined with a tumor vaccine. We develop a mathematical model in order to gain insight into the cooperative interaction between anti-TGF-β and vaccine treatments. The mathematical model follows the dynamics of the tumor size, TGF-β concentration, activated cytotoxic effector cells, and regulatory T cells. Using numerical simulations and stability analysis, we study the following scenarios: a control case of no treatment, anti-TGF-β treatment, vaccine treatment, and combined anti-TGF-β vaccine treatments. We show that our model is capable of capturing the observed experimental results, and hence can be potentially used in designing future experiments involving this approach to immunotherapy.     

Interleukin-8 has antitumor effects in the rat which are not associated with polymorphonuclear leukocyte cytotoxicity

The antitumor effect of lipopolysaccharides (LPS) has been observed in several experimental models and is likely to be mediated by macrophages. Stimulation of macrophages with LPS results in the release of several cytokines, including tumor necrosis factor, interleukin-1 and neutrophil-activating peptide-1/interleukin-8 (IL-8), which activates polymorphonuclear leukocytes (PMN) in vitro. Since PMN have an antitumor activity, we tested the in vivo effect of IL-8 on the growth of peritoneal carcinomatoses induced by PROb colon cancer cells in syngeneic rat. IL-8 induced a significant regression of tumors measuring 1–5 mm, and a complete regression was observed in 8 out of 40 rats in four independent experiments. IL-8 was not directly cytotoxic in vitro for tumor cells and was effective in vivo in a narrow range of doses. IL-8 had a significant chemotactic effect for peritoneal PMN in both normal and tumor-bearing rats. PMN taken from the peritoneum of tumor-bearing rats during IL-8 treatment had the same cytotoxic activity against PROb tumor cells as PMN from untreated control rats. Microscopic examinations of tumors during the treatment showed poor infiltrating by PMN. We conclude that the antitumor activity of IL-8 in this model is not mediated by PMN cytotoxicity.     

IL-2 immunotoxin therapy modulates tumor-associated regulatory T cells and leads to lasting immune-mediated rejection of breast cancers in neu-transgenic mice

Studies in cancer patients have suggested that breast tumors recruit regulatory T cells (Tregs) into the tumor microenvironment. The extent to which local Tregs suppress antitumor immunity in breast cancer is unknown. We questioned whether inhibiting systemic Tregs with an IL-2 immunotoxin in a model of neu-mediated breast cancer, the neu-transgenic mouse, could impact disease progression and survival. As in human breast cancer, cancers that develop in these mice attract Tregs into the tumor microenvironment to levels of approximately 10-25% of the total CD4+ T cells. To examine the role of Tregs in blocking immune-mediated rejection of tumor, we depleted CD4+CD25+ T cells with an IL-2 immunotoxin. The treatment depleted Tregs without concomitant lymphopenia and markedly inhibited tumor growth. Depletion of Tregs resulted in a persistent antitumor response that was maintained over a month after the last treatment. The clinical response was immune-mediated because adoptive transfer of Tregs led to a complete abrogation of the therapeutic effects of immunotoxin treatment. Further, Treg down-modulation was accompanied by increased Ag-specific immunity against the neu protein, a self Ag. These results suggest that Tregs play a major role in preventing an effective endogenous immune response against breast cancer and that depletion of Tregs, without any additional immunotherapy, may mediate a significant antitumor response.     

7-Allyl-8-oxoguanosine (loxoribine) inhibits the metastasis of B16 melanoma cells and has adjuvant activity in mice immunized with a B16 tumor vaccine

We have shown previously that loxoribine exhibits adjuvant activity for B cells, activates natural killer (NK) cells, and enhances the activation of lymphokine-activated killer cells by interleukin-2 (IL-2). In this study, we examined loxoribine for protective effects in a B16 melanoma lung tumor metastasis model. Significant inhibition of B16 metastasis was seen in mice given a single injection of 2 mg loxoribine as late as day 3 of tumor growth but the greatest inhibition (96%) was seen in mice given four injections of loxoribine on alternate days starting the day before tumor injection. In experiments in which both IL-2 and loxoribine were administered, both agents were active when tested alone, but the combination of IL-2 and loxoribine gave significantly greater inhibition of metastasis. Loxoribine partially inhibited the development of tumors in mice that had been depleted of NK cells by the administration of anti-asialo-GM1 or anti-NK1. 1 antibodies and in NK-deficient beige mice. In all cases, protection was seen only when smaller tumor inocula were injected. Taken together, these data suggest that both NK and non-NK cell populations or effector mechanisms with antitumor activity were activated by loxoribine. Since substituted guanosine analogs have been shown to have adjuvant activity in B cell systems, we evaluated whether loxoribine was active as an adjuvant in a tumor protection model. Mice immunized with both irradiated tumor cells and loxoribine developed a significantly lower number of lung tumors when challenged by live B16 tumor cells, whereas mice injected with either vaccine or loxoribine alone were not protected. There was a clear dose response seen with both loxoribine and the vaccine preparations. These data suggest that loxoribine may be useful in tumor therapy as an immunomodulator or as an adjuvant for use with tumor vaccines.     

Three-dimensional environment renders cancer cells profoundly less susceptible to a single amino acid starvation

Increased amino acid requirement of malignant cells is exploited in metabolic antitumor therapy, e.g., enzymotherapies based on arginine or methionine deprivation. However, studies on animal models and clinical trials revealed that solid tumors are much less susceptible to single amino acid starvation than could be expected from the in vitro data. We conducted a comparative analysis of the response of several tumor cell lines to single amino acid starvation in 2-D monolayer versus 3-D spheroid culture. We revealed for the first time that in comparison with monolayer culture tumor cells, spheroids are much less susceptible to the deprivation of individual amino acids (i.e., arginine, leucine, lysine or methionine). Accordingly, even after prolonged (up to 10 days) starvation, spheroid cells could readily resume proliferation when appropriate amino acid was resupplemented. In the case of arginine deprivation, similar apoptosis induction was detected both in 2-D and 3-D culture, suggesting that this process does not determine the level of tumor cell sensitivity to this kind of treatment. It was also observed that spheroids much better mimic the in vivo ability of tumor cells to utilize citrulline as arginine precursor for growth in amino acid deficient environment. We conclude that 3-D spheroid culture better reflects in vivo tumor cell response to single amino acid starvation than 2-D monolayer culture and should be used as an integral model in the studies of this type of antitumor metabolic targeting.     

Cancer therapy by biological response modifiers

Biological response modifiers (BRMs) are agents or approaches which can modify the biological response of the host to tumors and thereby are expected to augment the resistance to development or progression of cancer. Recent advances in the technology of genetic engineering and monoclonal antibodies have led to rapid progress in this field. There is an increasing number of genetically engineered cytokines, which appear promising for cancer treatment and are becoming available for clinical trials. These include the interferons, leukin-2, tumor necrosis factor, and colony-stimulating factors. For development of optimal therapeutic protocols with these and a variety of immunomodulatory agents, it appears necessary to develop a detailed understanding of the possible mechanisms of their antitumor effects, and to determine the optimal dose and schedule for altering the antitumor effector mechanisms. BRMs would also be expected to be quite useful in the prevention of cancer. Indeed, in a variety of animal tumor model systems, potent protective effects can be demonstrated. However, the strategies for clinical application of such information have yet to be adequately worked out. One more immediate application of this approach is for the prevention of metastatic spread of tumor cells. BRMs, which stimulate natural killer cell activity, have been shown to strongly protect against dissemination of tumors, and clinical strategies for this important aspect of cancer treatment are being developed.     

Interferon Regulatory Factor-8 Is Important for Histone Deacetylase Inhibitor-Mediated Antitumor Activity

The notion that epigenetic alterations in neoplasia are reversible has provided the rationale to identify epigenetic modifiers for their ability to induce or enhance tumor cell death. Histone deacetylase inhibitors (HDACi) represent one such class of anti-neoplastic agents. Despite great interest for clinical use, little is known regarding the molecular targets important for response to HDACi-based cancer therapy. We had previously shown that interferon regulatory factor (IRF)-8, originally discovered as a leukemia suppressor gene by regulating apoptosis, also regulates Fas-mediated killing in non-hematologic tumor models. Furthermore, we and others have shown that epigenetic mechanisms are involved in repression of IRF-8 in tumors. Therefore, in our preclinical tumor model, we tested the hypothesis that IRF-8 expression is important for response to HDACi-based antitumor activity. In the majority of experiments, we selected the pan-HDACi, Trichostatin A (TSA), because it was previously shown to restore Fas sensitivity to tumor cells. Overall, we found that: 1) TSA alone and more so in combination with IFN-γ enhanced both IRF-8 expression and Fas-mediated death of tumor cells in vitro; 2) TSA treatment enhanced IRF-8 promoter activity via a STAT1-dependent pathway; and 3) IRF-8 was required for this death response, as tumor cells rendered IRF-8 incompetent were significantly less susceptible to Fas-mediated killing in vitro and to HDACi-mediated antitumor activity in vivo. Thus, IRF-8 status may underlie a novel molecular basis for response to HDACi-based antitumor treatment.     

Analysis of a three-way race between tumor growth,a replication-competent virus and an immune response

Replication-competent viruses have the potential to overcome the delivery barrier in tumors that has plagued traditional gene-therapy approaches to cancer treatment. However, recent clinical data suggests that a cytokine-based immune response against the virus-infected tumor cells may severely limit the efficacy of the replication-competent approach. This paper generalizes our earlier spatial model to incorporate an immune response against the infected tumor cells. An approximate but accurate condition is derived for the virus—if uniformly injected throughout the tumor—to eradicate the tumor in the presence of the immune response. To validate the model using clinical data describing the temporal interaction of tumor necrosis factor and free virus in the plasma, we needed the immune response to be time-delayed and experience either saturated stimulation or second-order clearance. The resulting estimates of some unknown parameters provide some implications for the delivery of treatment.     

A mathematical model of tumor growth and its response to single irradiation

Background

Mathematical modeling of biological processes is widely used to enhance quantitative understanding of bio-medical phenomena. This quantitative knowledge can be applied in both clinical and experimental settings. Recently, many investigators began studying mathematical models of tumor response to radiation therapy. We developed a simple mathematical model to simulate the growth of tumor volume and its response to a single fraction of high dose irradiation. The modelling study may provide clinicians important insights on radiation therapy strategies through identification of biological factors significantly influencing the treatment effectiveness.

Methods

We made several key assumptions of the model. Tumor volume is composed of proliferating (or dividing) cancer cells and non-dividing (or dead) cells. Tumor growth rate (or tumor volume doubling time) is proportional to the ratio of the volumes of tumor vasculature and the tumor. The vascular volume grows slower than the tumor by introducing the vascular growth retardation factor, θ. Upon irradiation, the proliferating cells gradually die over a fixed time period after irradiation. Dead cells are cleared away with cell clearance time. The model was applied to simulate pre-treatment growth and post-treatment radiation response of rat rhabdomyosarcoma tumors and metastatic brain tumors of five patients who were treated with Gamma Knife stereotactic radiosurgery (GKSRS).

Results

By selecting appropriate model parameters, we showed the temporal variation of the tumors for both the rat experiment and the clinical GKSRS cases could be easily replicated by the simple model. Additionally, the application of our model to the GKSRS cases showed that the α-value, which is an indicator of radiation sensitivity in the LQ model, and the value of θ could be predictors of the post-treatment volume change.

Conclusions

The proposed model was successful in representing both the animal experimental data and the clinically observed tumor volume changes. We showed that the model can be used to find the potential biological parameters, which may be able to predict the treatment outcome. However, there is a large statistical uncertainty of the result due to the small sample size. Therefore, a future clinical study with a larger number of patients is needed to confirm the finding.

     

Combined immunization with adjuvant molecules poly(I:C) and anti-CD40 plus a tumor antigen has potent prophylactic and therapeutic antitumor effects

The low immunogenicity of malignant cells is one of the causes responsible for the lack of antitumor immune responses. Thus, development of new therapeutic strategies aimed at enhancing presentation of tumor antigens to T cells is a main goal of cancer immunotherapy. With this aim, we studied the efficacy of administering adjuvants poly(I:C) and agonistic anti-CD40 antibody plus a tumor antigen. Joint intravenous immunization with these adjuvants and a model tumor antigen (ovalbumin) was able to synergistically induce potent and long lasting antitumor T-cell responses. These responses protected against challenge with E.G7–OVA tumor cells in prophylactic short- and long-term vaccination. In a therapeutic setting, repeated intratumor administration of adjuvants plus antigen was able to reject established tumors in all treated animals, leading in some cases to the rejection of both locally treated and untreated tumors. Antitumor immune responses induced by these protocols were mediated not only by T-cells but also by NK cells. In conclusion, combined administration of adjuvants poly(I:C) and anti-CD40 plus a tumor antigen is an efficient strategy for prophylactic and therapeutic antitumor vaccination.     

Computational challenges of tumor spheroid modeling

The speed and the versatility of today's computers open up new opportunities to simulate complex biological systems. Here we review a computational approach recently proposed by us to model large tumor cell populations and spheroids, and we put forward general considerations that apply to any fine-grained numerical model of tumors. We discuss ways to bypass computational limitations and discuss our incremental approach, where each step is validated by experimental observations on a quantitative basis. We present a few results on the growth of tumor cells in closed and open environments and of tumor spheroids. This study suggests new ways to explore the initial growth phase of solid tumors and to optimize antitumor treatments.     

肠道微生物对肿瘤发生发展及化疗药物的影响

肠道微生物群在多种肿瘤发生发展过程中的作用引起了人们的广泛关注,近几年大量研究表明微生物群与肿瘤之间有着密切的关系。它们不仅可以与宿主共代谢,对肿瘤治疗产生正面或负面影响,还可以直接促进或消除化疗药物的疗效并介导药物的毒性,从而干预肿瘤的治疗。此外,肠道微生物能够介导免疫疗法,增强患者对肿瘤的免疫应答能力。在此综述中,我们概述了肠道微生物在肿瘤治疗中的意义,揭示其对化疗药物及免疫疗法的影响,并总结多种治疗肿瘤的潜在机制。不仅展现了肠道微生物研究对临床治疗肿瘤的意义,也为临床协助肿瘤治疗提供更多的思路。     

不同场强下IRE的肿瘤消融作用及对抗肿瘤免疫的影响

目的:探讨不同电场强度的不可逆电穿孔(IRE)对于肿瘤的消融效果以及其所引起的肿瘤免疫反应。方法:将B16黑色素瘤细胞接种于C57小鼠,制作黑色素瘤小鼠模型,应用不可逆电穿孔仪对肿瘤进行消融,通过测量肿瘤生长大小研究不同场强下的消融效果。通过CD4、CD8a免疫组化染色初步了解不同场强激发的免疫反应的强弱,从而选择最佳消融参数。结果:随着电场强度增加,肿瘤消融效果逐渐趋于理想,然而平板电极夹之间过高电场引发的热效应则不利于后续抗肿瘤免疫反应的激活。选择合适的电场,通过增加电击组数可以达到良好的治疗效果。结论:IRE对肿瘤的消融优势在于它能够很好的激活机体的抗肿瘤免疫反应,因此,选择合适的电场增加电击组数可以起到很好的抗肿瘤作用,具有很好的应用前景。