Integrating cell-cycle progression, drug penetration and energy metabolism to identify improved cancer therapeutic strategies

The effectiveness of chemotherapeutic drugs in tumors is reduced by multiple effects including drug diffusion and variable susceptibility of local cell populations. We hypothesized that quantifying the interactions between drugs and tumor microenvironments could be used to identify more effective anti-cancer strategies. To test this hypothesis we created a mathematical model that integrated intracellular metabolism, nutrient and drug diffusion, cell-cycle progression, cellular drug effects, and drug pharmacokinetics. To our knowledge, this is the first model that combines these elements and has coupled them to experimentally derived parameters. Drug cytotoxicity was assumed to be cell-cycle phase specific, and progression through the cell cycle was assumed to be dependent on ATP generation. The model consisted of a coupled set of nonlinear partial differential, ordinary differential and algebraic equations with an outer free boundary, which was solved using orthogonal collocation on a moving grid of finite elements. Model simulations showed the existence of an optimum drug diffusion coefficient: a low diffusivity prevents effective penetration before the drug is cleared from the blood and a high diffusivity limits drug retention. This result suggests that increasing the molecular weight of the anti-cancer drug paclitaxel from 854 to approximately 20,000 by nano-particle conjugation would improve its efficacy. The simulations also showed that fast growing tumors are less responsive to therapy than are slower tumors with more quiescent cells, demonstrating the competing effects of regrowth and cytotoxicity. The therapeutic implications of the simulation results are that (1) monolayer cultures are inadequate for accurately determining therapeutic effects in vitro, (2) decreasing the diffusivity of paclitaxel could increase its efficacy, and (3) measuring the proliferation fraction in tumors could enhance the prediction of therapeutic efficacy.     

Persistence to anti-cancer treatments in the stationary to proliferating transition

The heterogeneous responses of clonal cancer cells to treatment is understood to be caused by several factors, including stochasticity, cell-cycle dynamics, and different micro-environments. In a tumor, cancer cells may encounter fluctuating conditions and transit from a stationary culture to a proliferating state, for example this may occur following treatment. Here, we undertake a quantitative evaluation of the response of single cancerous lymphoblasts (L1210 cells) to various treatments administered during this transition. Additionally, we developed an experimental system, a “Mammalian Mother Machine,” that tracks the fate of thousands of mammalian cells over several generations under transient exposure to chemotherapeutic drugs. Using our developed system, we were able to follow the same cell under repeated treatments and continuously track many generations. We found that the dynamics of the transition between stationary and proliferative states are highly variable and affect the response to drug treatment. Using cell-cycle markers, we were able to isolate a subpopulation of persister cells with distinctly higher than average survival probability. The higher survival rate encountered with cell-cycle phase specific drugs was associated with a significantly longer time-till-division, and was reduced by a non cell-cycle specific drug. Our results suggest that the variability of transition times from the stationary to the proliferating state may be an obstacle hampering the effectiveness of drugs and should be taken into account when designing treatment regimens.     

A preclinical orthotopic model for glioblastoma recapitulates key features of human tumors and demonstrates sensitivity to a combination of MEK and PI3K pathway inhibitors

Current therapies for glioblastoma multiforme (GBM), the highest grade malignant brain tumor, are mostly ineffective, and better preclinical model systems are needed to increase the successful translation of drug discovery efforts into the clinic. Previous work describes a genetically engineered mouse (GEM) model that contains perturbations in the most frequently dysregulated networks in GBM (driven by RB, KRAS and/or PI3K signaling and PTEN) that induce development of Grade IV astrocytoma with properties of the human disease. Here, we developed and characterized an orthotopic mouse model derived from the GEM that retains the features of the GEM model in an immunocompetent background; however, this model is also tractable and efficient for preclinical evaluation of candidate therapeutic regimens. Orthotopic brain tumors are highly proliferative, invasive and vascular, and express histology markers characteristic of human GBM. Primary tumor cells were examined for sensitivity to chemotherapeutics and targeted drugs. PI3K and MAPK pathway inhibitors, when used as single agents, inhibited cell proliferation but did not result in significant apoptosis. However, in combination, these inhibitors resulted in a substantial increase in cell death. Moreover, these findings translated into the in vivo orthotopic model: PI3K or MAPK inhibitor treatment regimens resulted in incomplete pathway suppression and feedback loops, whereas dual treatment delayed tumor growth through increased apoptosis and decreased tumor cell proliferation. Analysis of downstream pathway components revealed a cooperative effect on target downregulation. These concordant results, together with the morphologic similarities to the human GBM disease characteristics of the model, validate it as a new platform for the evaluation of GBM treatment.KEY WORDS: Glioblastoma, Mouse model, PI3K and MEK inhibition, Apoptosis     

Apoptosis in non-small cell lung cancer as related to drug resistance and prognosis

The percentage of apoptotic cells among the tumor cells (apoptotic index) was determined in a series of 178 non-small cell lung carcinomas with a long term clinical follow-up by a terminal desoxynucleotidyl transferase mediated dUTP nick end labelling technique. In survival analysis, we found no statistically significant correlation between the apoptotic index and survival times. We estimated also the sensitivity of specimens to doxorubicin by a short term test. Tumors with a high apoptotic activity were more sensitive to doxorubicin than tumors with a less apoptotic index. Thus, our data indicate that apoptosis may be involved in drug response of lung tumors and it could be useful for the chemotherapeutic strategy to design drugs which trigger apoptosis.     

Three tumor sensitivity tests evaluated with mouse tumors

The predictive value of three types of tumor sensitivity tests was evaluated using mouse tumors. Sensitivities of osteosarcoma C22LR, Lewis lung and M2661 carcinoma were determined for the following drugs: DNA interacting or alkylating agent (doxorubicin, cisplatin, 1,3-bis(2-chloroethyl)-1-nitrosourea, melphalan), antimetabolite (5-fluorouracil, methotrexate) and microtubule inhibitor (vinblastine, vincristine). Volume measurements of the subcutaneously growing tumors after treatment with the same drugs were considered to be the traditional reference system with which the results of the in vitro clonogenic assay, the labeled precursor incorporation assay and the subrenal capsule assay were compared. Results obtained with the in vitro clonogenic assay were highly reproducible. With the 1-h drug exposure technique the predictive accuracy was 71%. This result is in the same range as those found by others for human tumors. Predictive accuracy after continuous drug exposure was only 25%. Vinblastine, vincristine and cisplatin caused no inhibition of labeled precursor incorporation. However, the assay is too unreliable to use, due to the extreme variability when used with the other drugs. From 31 consecutively performed duplicate tests in the subrenal capsule assay, nine showed opposite results. This degree of disagreement between duplicate test results was considered too high to make reliable predictions of tumor sensitivity with this assay.     

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.     

Dynamic BH3 profiling identifies active BH3 mimetic combinations in non-small cell lung cancer

Conventional chemotherapy is still of great utility in oncology and rationally constructing combinations with it remains a top priority. Drug-induced mitochondrial apoptotic priming, measured by dynamic BH3 profiling (DBP), has been shown in multiple cancers to identify drugs that promote apoptosis in vivo. We therefore hypothesized that we could use DBP to identify drugs that would render cancers more sensitive to conventional chemotherapy. We found that targeted agents that increased priming of non-small cell lung cancer (NSCLC) tumor cells resulted in increased sensitivity to chemotherapy in vitro. To assess whether targeted agents that increase priming might enhance the efficacy of cytotoxic agents in vivo as well, we carried out an efficacy study in a PC9 xenograft mouse model. The BH3 mimetic navitoclax, which antagonizes BCL-xL, BCL-w, and BCL-2, consistently primed NSCLC tumors in vitro and in vivo. The BH3 mimetic venetoclax, which electively antagonizes BCL-2, did not. Combining navitoclax with etoposide significantly reduced tumor burden compared to either single agent, while adding venetoclax to etoposide had no effect on tumor burden. Next, we assessed priming of primary patient NSCLC tumor cells on drugs from a clinically relevant oncology combination screen (CROCS). Results confirmed for the first time the utility of BCL-xL inhibition by navitoclax in priming primary NSCLC tumor cells and identified combinations that primed further. This is a demonstration of the principle that DBP can be used as a functional precision medicine tool to rationally construct combination drug regimens that include BH3 mimetics in solid tumors like NSCLC.Subject terms: Non-small-cell lung cancer, Apoptosis, Predictive markers     

Targeting PI3K-AKT pathway for cancer therapy

The phosphatidilinositol 3-kinase/protein kinase B (PI3K-AKT) pathway presents an exciting new target for molecular therapeutics. While exhibiting great promise, additional preclinical and clinical studies will be required to determine how best to target this pathway to improve patient outcome. A number of questions need to be answered prior to the implementation into patient care practices. As described below, the PI3K-AKT pathway regulates a broad spectrum of cellular processes, some of which are necessary to maintain normal physiological functions, which potentially contribute to the toxicity of the drugs targeting the pathway. Elucidation of the precise function of the PI3K-AKT isoforms, could promote the development of isoform specific approaches to provide a selective action on tumor cells. However, whether this will be possible due to conservation of structural domains is not yet clear. Inhibition of the PI3K-AKT pathway at multiple sites or a combination with inhibitors of different signaling pathways may allow the development of an acceptable therapeutic index for cancer management. Further, inhibition of the PI3K-AKT pathway combined with conventional chemotherapy or radiation therapy may provide a more effective strategy to improve patient outcome. As molecular therapeutics target the underlying defects in patient tumors, molecular diagnostics are required to identify patients with particular genetic aberrations in the pathway. It will be critical to provide adequate therapeutic strategies tailored to each patient. In addition, patients with different genetic backgrounds or in different health conditions could respond adversely to particular therapeutics. Therefore, identification of patients for particular drugs based on the underlying genetic defects in the tumor as well as the characteristics of the host would be of benefit for improving patient outcome. Linking the targeted therapeutics to molecular imaging approaches will determine appropriate biologically relevant dose for patients. It will also define expected tumor responsiveness and eventually will improve efficacy and decrease toxicity. In this regard, personalized molecular medicine is likely to soon provide effective cancer treatment.     

斑马鱼胚胎和肿瘤细胞评价细胞毒药物活性比较研究*

目的:比较斑马鱼胚胎和肿瘤细胞作为药物筛选模型的优缺点.方法:采用MTT法检测顺铂、紫杉醇、阿霉素、5-氟尿嘧啶四种药物对HL-60和Hela细胞的增殖影响;同时,观察药物对斑马鱼胚胎发育的影响.结果:阿霉素、顺铂及紫杉醇作用于HL-60及Hela细胞的IC50均显著高于作用于斑马鱼胚胎的LD50;而5-FU作用于肿瘤细胞和斑马鱼胚胎的结果与其它药物相反;四种抗肿瘤药物对斑马鱼胚胎的生长发育均有致畸作用.结论:斑马鱼胚胎作为细胞毒类药物筛选模型,对于抗微管类药物较为敏感,但对于抗代谢药敏感性较肿瘤细胞差.     

Cell cycle control and cancer chemotherapy

As detailed information accumulates about how cell cycle events are regulated, we can expect new opportunities for application to cancer therapy. The altered expression of oncogenes and tumor suppressor genes that commonly occurs in human cancers may impair the ability of the cells to respond to metabolic perturbations or stress. Impaired cell cycle regulation would make cells vulnerable to pharmacologic intervention by drug regimens tailored to the defects existing in particular tumors. Recent findings that may become applicable to therapy are reviewed, and the possible form of new therapeutic stratagems is considered.     

Apoptosis in anititumor strategies: Modulation of cell cycle or differentiation

There is a strong evidence that administration of antitumor drugs triggers apoptotic death of target cells. A characteristic feature of appotosis is active participation of the affected cell in its demise. Attempts have been made, therefore, to potentiate the cytotoxicity of a variety of agents by modulating the propensity of cells to respond by apoptosis. Several strategies to enhance apoptosis that involve modulation of the cell cycle or differentiation are discussed. Loss of control of the G₁ checkpoint in tumor cells allows one to design treatments that arrest normal cells at the checkpoint and attempt to selectively kill tumor cells with S phase specific drugs. The possibility of a restoration of the apoptosis triggering function of the tumor suppressor gene p53 when the G₁ checkpoint function is abolished is expected to increase tumor cells' sensitivity to S phase poisons. Because induction of apoptosis by many antitumor drugs is cell cycle phase specific, drug combinations that preferentially trigger apoptosis at different phases of the cycle, or recruitment of cells to the sensitive phase, offer another antitumor strategy. There is also evidence that apoptosis is potentiated when cell differentiation is triggered follwing DNA damage. This observation suggests that strategies which combine DNA damaging and differentiating drugs, under conditions where the latter are administered following DNA damage caused by the former, may be successful.     

What Makes Tumors Multidrug Resistant?

Tumors arising “spontaneously” in genetically modified mice now make it possible to study mechanisms of drug resistance in animal tumors resembling their human counterparts. We have studied mouse mammary tumors induced by conditional deletion of Brca1 and p53. These tumors respond to monotherapy with the maximal tolerable dose of doxorubicin, or docetaxel, but eventually always become resistant to the drugs. Resistance in most tumors is caused by upregulation of drug transporters and not by interference with apoptosis/senescence. The tumors also respond to cisplatin, but do not become resistant, even after repeated treatments at the maximum tolerable dose. We conclude that resistance due to interference with cell death effector pathways (apoptosis/senescence) is not an option in these tumors, re-emphasizing doubts that such mechanisms play a role in epithelial tumors. Tumors responding to drug may shrink to less than 5% of their volume before relapsing. We argue that this resistant remnant fraction may provide a test for the tumor stem cell hypothesis and, more generally, that “spontaneous” mouse tumors resembling their human counterparts provide a useful new tool for drug development and for improving treatment regimens.     

Impact of atorvastatin loaded exosome as an anti-glioblastoma carrier to induce apoptosis of U87 cancer cells in 3D culture model

Exosomes (EXOs) are naturally occurring nanosized lipid bilayers that can be efficiently used as a drug delivery system to carry small pharmaceutical, biological molecules and pass major biological barriers such as the blood-brain barrier. It was hypothesized that EXOs derived from human endometrial stem cells (hEnSCs-EXOs) can be utilized as a drug carrier to enhance tumor-targeting drugs, especially for those have low solubility and limited oral bioactivity. In this study, atorvastatin (Ato) loaded EXOs (AtoEXOs) was prepared and characterized for its physical and biological activities in tumor growth suppression of 3 D glioblastoma model. The AtoEXOs were obtained in different methods to maximize drug encapsulation efficacy. The characterization of AtoEXOs was performed for its size, stability, drug release, and in vitro anti-tumor efficacy evaluated comprising inhibition of proliferation, apoptosis induction of tumor cells. Expression of apoptotic genes by Real time PCR, Annexin V/PI, tunnel assay was studied after 72 h exposing U87 cells where encapsulated in matrigel in different concentrations of AtoEXOs (5, 10 μM). The results showed that the prepared AtoEXOs possessed diameter ranging from 30–150 nm, satisfying stability and sustainable Ato release rate. The AtoEXOs was up taken by U87 and generated significant apoptotic effects while this inhibited tumor growth of U87 cells. Altogether, produced AtoEXOs formulation due to its therapeutic efficacy has the potential to be an adaptable approach to treat glioblastoma brain tumors.     

An Integrated Computational/Experimental Model of Lymphoma Growth

Non-Hodgkin''s lymphoma is a disseminated, highly malignant cancer, with resistance to drug treatment based on molecular- and tissue-scale characteristics that are intricately linked. A critical element of molecular resistance has been traced to the loss of functionality in proteins such as the tumor suppressor p53. We investigate the tissue-scale physiologic effects of this loss by integrating in vivo and immunohistological data with computational modeling to study the spatiotemporal physical dynamics of lymphoma growth. We compare between drug-sensitive Eμ-myc Arf-/- and drug-resistant Eμ-myc p53-/- lymphoma cell tumors grown in live mice. Initial values for the model parameters are obtained in part by extracting values from the cellular-scale from whole-tumor histological staining of the tumor-infiltrated inguinal lymph node in vivo. We compare model-predicted tumor growth with that observed from intravital microscopy and macroscopic imaging in vivo, finding that the model is able to accurately predict lymphoma growth. A critical physical mechanism underlying drug-resistant phenotypes may be that the Eμ-myc p53-/- cells seem to pack more closely within the tumor than the Eμ-myc Arf-/- cells, thus possibly exacerbating diffusion gradients of oxygen, leading to cell quiescence and hence resistance to cell-cycle specific drugs. Tighter cell packing could also maintain steeper gradients of drug and lead to insufficient toxicity. The transport phenomena within the lymphoma may thus contribute in nontrivial, complex ways to the difference in drug sensitivity between Eμ-myc Arf-/- and Eμ-myc p53-/- tumors, beyond what might be solely expected from loss of functionality at the molecular scale. We conclude that computational modeling tightly integrated with experimental data gives insight into the dynamics of Non-Hodgkin''s lymphoma and provides a platform to generate confirmable predictions of tumor growth.     

Altered expression of the cell cycle regulatory molecules pRb, p53 and MDM2 exert a synergetic effect on tumor growth and chromosomal instability in non-small cell lung carcinomas (NSCLCs)

BACKGROUND: Recent in vitro studies provide evidence that the cell cycle molecules pRb, p53 and MDM2 form a tightly regulated protein network. In this study, we examined the relationship of this protein network in a series of non-small cell lung carcinomas (NSCLCs), with the kinetic parameters, including proliferative activity or proliferation index (PI) and apoptotic index (AI), and ploidy status of the tumors. MATERIAL AND METHODS: A total of 87 NSCLCs were examined using immunohistochemical and molecular methods in order to estimate the status of the pRb-p53-MDM2 network. The kinetic parameters and the ploidy status of the tumors were assessed by in situ assays. The possible associations between alterations of the network, kinetic parameters and ploidy status of the carcinomas were assessed with a series of statistical methods. RESULTS: Aberrant expression of pRb (Ab) and overexpression of p53 (P) and MDM2 (P) proteins were observed in 39%, 57%, and 68% of the carcinomas, respectively. The comprehensive analysis revealed that concurrent alterations in all three cell cycle regulatory molecules were the most frequent pattern, pRb(Ab)/p53(P)/MDM2(P); this "full abnormal" phenotype represented approximately 27% of the cases. This immunoprofile obtained the highest PI/AI value; whereas, the "normal" phenotype was the lowest one (p = 0.004). Furthermore, the pattern pRb(Ab)/p53(P)/MDM2(P) acquired the highest PI (p < 0.001) and lowest AI (p < 0.001) scores. Interestingly, the groups of carcinomas with impaired expression of one or two molecules attained PI/AI ratio values clustered in a narrow range placed in the middle of the scores exhibited by the "normal" and "full abnormal" phenotypes. These tumors had significantly lower AI, but similar PI values, compared with those noticed in the normal pattern. In addition, it was observed that the pRb(Ab)/p53(P)/MDM2(P) phenotype was also significantly associated with aneuploidy (p = 0.002) and a tendency was observed when the expression of two components was altered (p = 0.055). CONCLUSIONS: Our findings suggest that simultaneous deregulation of all members of the pRb-p53-MDM2 network confers an additive effect on tumor growth. The apoptotic pathway seems to be more susceptible to its defects than the cell proliferation machinery. The findings of the ploidy analysis, which are in parallel with those regarding the proliferative activity and the apoptotic rate study, further support the concept that these molecules constitute a tightly regulated network participating in cell cycle control and chromosomal stability.     

Widespread Molecular Patterns Associated with Drug Sensitivity in Breast Cancer Cell Lines,with Implications for Human Tumors

Background

Recent landmark studies have profiled cancer cell lines for molecular features, along with measuring the corresponding growth inhibitory effects for specific drug compounds. These data present a tool for determining which subsets of human cancer might be more responsive to particular drugs. To this end, the NCI-DREAM-sponsored DREAM7: Drug Sensitivity Prediction Challenge (sub-challenge 1) set out to predict the sensitivities of 18 breast cancer cell lines to 31 previously untested compounds, on the basis of molecular profiling data and a training subset of cell lines.

Methods and Results

With 47 teams submitting blinded predictions, team Creighton scored third in terms of overall accuracy. Team Creighton''s method was simple and straightforward, incorporated multiple expression data types (RNA-seq, gene array, RPPA), and incorporated all profiled features (not only the “best” predictive ones). As an extension of the approach, cell line data, from public datasets of expression profiling coupled with drug sensitivities (Barretina, Garnett, Heiser) were used to “predict” the drug sensitivities in human breast tumors (using data from The Cancer Genome Atlas). Drug sensitivity correlations within human breast tumors showed differences by expression-based subtype, with many associations in line with the expected (e.g. Lapatinib sensitivity in HER2-enriched cancers) and others inviting further study (e.g. relative resistance to PI3K inhibitors in basal-like cancers).

Conclusions

Molecular patterns associated with drug sensitivity are widespread, with potentially hundreds of genes that could be incorporated into making predictions, as well as offering biological clues as to the mechanisms involved. Applying the cell line patterns to human tumor data may help generate hypotheses on what tumor subsets might be more responsive to therapies, where multiple cell line datasets representing various drugs may be used, in order to assess consistency of patterns.     

Breast cancer: implications of tumor cell kinetics on clinical outcome

The relevance of tumor proliferative activity as an indicator of biologic aggressiveness was analyzed on a series of 506 patients with primary breast cancer. In 258 patients with operable tumors without nodal and distant metastases, none of whom was subjected to postoperative irradiation or systemic adjuvant therapy, proliferative activity was significantly correlated with prognosis; 6-year relapse-free survival (RFS) and overall survival (OS) were higher for patients with slowly proliferating tumors for patient with fast-proliferating tumors (RFS: 80.5% vs 59.6%, p = 0.00004; OS: 90.8% vs 74.4%, p = 0.002). On a series of 196 patients with node-positive operable tumors, subjected to 6 or 12 cycles of cyclophosphamide, methotrexate and 5-fluorouracil, a trend in favor of longer 6-year RFS was observed for patients with slowly proliferating tumors than for patients with fast-proliferating tumors (62.5% vs 48.3%, p = 0.08), whereas proliferative activity did not influence OS. In 52 patients with locally advanced disease treated with a multimodality approach, including chemotherapy (adriamycin and vincristine), surgery or radiotherapy, tumor proliferative activity was a strong indicator of biologic aggressivity, since women with slowly proliferating cancers had a higher 4-year probability of OS than women with fast-proliferating tumors (68.1% vs 36.7%, p = 0.02).