A proliferative melanoma cell phenotype is responsive to RAF/MEK inhibition independent of BRAF mutation status

Oncogenic mutations within the MAPK pathway are frequent in melanoma, and targeting of MAPK signaling has yielded spectacular responses in a significant number of patients that last for several months before relapsing. We investigated the effects of two different inhibitors of MAPK signaling in proliferative and invasive melanoma cell cultures with various mutations in the MAPK pathway. Proliferative melanoma cells were more susceptible to pathway inhibition than invasive phenotype cells, irrespective of BRAF mutation status, while invasive phenotype cell response was dependent on BRAF mutation status. Critically, MAPK pathway inhibition of proliferative phenotype cells resulted in acquisition of invasive phenotype characteristics. These results show that melanoma cell phenotype is an important factor in MAPK pathway inhibition response. This suggests that while current therapeutic strategies target proliferative melanoma cells, future approaches should also account for the invasive phenotype population.     

Transformation of Epithelial Ovarian Cancer Stemlike Cells into Mesenchymal Lineage via EMT Results in Cellular Heterogeneity and Supports Tumor Engraftment

Ovarian cancers are heterogeneous and contain stemlike cells that are able to self-renew and are responsible for sustained tumor growth. Metastasis in the peritoneal cavity occurs more frequently in ovarian cancer than in other malignancies, but the underlying mechanism remains largely unknown. We have identified that ovarian cancer stemlike cells (CSCs), which were defined as side population (SP) cells, were present in patients’ ascitic fluid and mesenchymally transformed cell lines, ES-2 and HO-8910PM. SP cells, which were sorted from both cell lines and implanted into immunocompromised mice, were localized to the xenografted tumor boundary. In addition, SP cells exhibited an epithelial phenotype and showed a distinct gene expression profile with reduced expression of cell adhesion molecules (CAMs), indicating that SP cells exert an important role in ovarian cancer progression on the basis of their delicate interaction with the surrounding microenvironment and anatomical localization in tumors. In contrast, non-SP cells exhibited a more mesenchymal phenotype and showed more increased invasive potential than SP cells. This heterogeneity was observed as an endogenous transformation via the epithelial–mesenchymal transition (EMT) process. Inhibition of the EMT process by Snail1 silencing reduced the SP cell frequency, and affected their invasive capacity and engraftment. These findings illustrate the interplay between epithelial ovarian CSCs and the EMT, and exert a link to explain tumor heterogeneity and its necessity for ovarian cancer maintenance, metastasis and progression.     

Emergent behaviors from a cellular automaton model for invasive tumor growth in heterogeneous microenvironments

Understanding tumor invasion and metastasis is of crucial importance for both fundamental cancer research and clinical practice. In vitro experiments have established that the invasive growth of malignant tumors is characterized by the dendritic invasive branches composed of chains of tumor cells emanating from the primary tumor mass. The preponderance of previous tumor simulations focused on non-invasive (or proliferative) growth. The formation of the invasive cell chains and their interactions with the primary tumor mass and host microenvironment are not well understood. Here, we present a novel cellular automaton (CA) model that enables one to efficiently simulate invasive tumor growth in a heterogeneous host microenvironment. By taking into account a variety of microscopic-scale tumor-host interactions, including the short-range mechanical interactions between tumor cells and tumor stroma, degradation of the extracellular matrix by the invasive cells and oxygen/nutrient gradient driven cell motions, our CA model predicts a rich spectrum of growth dynamics and emergent behaviors of invasive tumors. Besides robustly reproducing the salient features of dendritic invasive growth, such as least-resistance paths of cells and intrabranch homotype attraction, we also predict nontrivial coupling between the growth dynamics of the primary tumor mass and the invasive cells. In addition, we show that the properties of the host microenvironment can significantly affect tumor morphology and growth dynamics, emphasizing the importance of understanding the tumor-host interaction. The capability of our CA model suggests that sophisticated in silico tools could eventually be utilized in clinical situations to predict neoplastic progression and propose individualized optimal treatment strategies.     

Inhibitor of DNA Binding 4 (ID4) Is Highly Expressed in Human Melanoma Tissues and May Function to Restrict Normal Differentiation of Melanoma Cells

Melanoma tissues and cell lines are heterogeneous, and include cells with invasive, proliferative, stem cell-like, and differentiated properties. Such heterogeneity likely contributes to the aggressiveness of the disease and resistance to therapy. One model suggests that heterogeneity arises from rare cancer stem cells (CSCs) that produce distinct cancer cell lineages. Another model suggests that heterogeneity arises through reversible cellular plasticity, or phenotype-switching. Recent work indicates that phenotype-switching may include the ability of cancer cells to dedifferentiate to a stem cell-like state. We set out to investigate the phenotype-switching capabilities of melanoma cells, and used unbiased methods to identify genes that may control such switching. We developed a system to reversibly synchronize melanoma cells between 2D-monolayer and 3D-stem cell-like growth states. Melanoma cells maintained in the stem cell-like state showed a striking upregulation of a gene set related to development and neural stem cell biology, which included SRY-box 2 (SOX2) and Inhibitor of DNA Binding 4 (ID4). A gene set related to cancer cell motility and invasiveness was concomitantly downregulated. Intense and pervasive ID4 protein expression was detected in human melanoma tissue samples, suggesting disease relevance for this protein. SiRNA knockdown of ID4 inhibited switching from monolayer to 3D-stem cell-like growth, and instead promoted switching to a highly differentiated, neuronal-like morphology. We suggest that ID4 is upregulated in melanoma as part of a stem cell-like program that facilitates further adaptive plasticity. ID4 may contribute to disease by preventing stem cell-like melanoma cells from progressing to a normal differentiated state. This interpretation is guided by the known role of ID4 as a differentiation inhibitor during normal development. The melanoma stem cell-like state may be protected by factors such as ID4, thereby potentially identifying a new therapeutic vulnerability to drive differentiation to the normal cell phenotype.     

Spatial and Functional Heterogeneities Shape Collective Behavior of Tumor-Immune Networks

Tumor growth involves a dynamic interplay between cancer cells and host cells, which collectively form a tumor microenvironmental network that either suppresses or promotes tumor growth under different conditions. The transition from tumor suppression to tumor promotion is mediated by a tumor-induced shift in the local immune state, and despite the clinical challenge this shift poses, little is known about how such dysfunctional immune states are initiated. Clinical and experimental observations have indicated that differences in both the composition and spatial distribution of different cell types and/or signaling molecules within the tumor microenvironment can strongly impact tumor pathogenesis and ultimately patient prognosis. How such “functional” and “spatial” heterogeneities confer such effects, however, is not known. To investigate these phenomena at a level currently inaccessible by direct observation, we developed a computational model of a nascent metastatic tumor capturing salient features of known tumor-immune interactions that faithfully recapitulates key features of existing experimental observations. Surprisingly, over a wide range of model formulations, we observed that heterogeneity in both spatial organization and cell phenotype drove the emergence of immunosuppressive network states. We determined that this observation is general and robust to parameter choice by developing a systems-level sensitivity analysis technique, and we extended this analysis to generate other parameter-independent, experimentally testable hypotheses. Lastly, we leveraged this model as an in silico test bed to evaluate potential strategies for engineering cell-based therapies to overcome tumor associated immune dysfunction and thereby identified modes of immune modulation predicted to be most effective. Collectively, this work establishes a new integrated framework for investigating and modulating tumor-immune networks and provides insights into how such interactions may shape early stages of tumor formation.     

同源肿瘤克隆细胞蛋白表达和侵袭能力的异质性研究

摘要 目的：比较同源肿瘤细胞来源的不同单克隆表型差异。方法：采用极限稀释法,在悬浮培养条件下获取HCT116结肠癌细胞系的单个细胞,对每孔含单个的细胞进行扩增培养,获得子代单克隆,并以同样方法继续挑取单克隆,连续获得子三代克隆。根据单克隆形态特点,选取第三代的三株代表性的单克隆,采用Western blot和免疫荧光法比较其SOX2、EpCAM和Vimentin蛋白表达差异。采用放疗观察三株单克隆的Vimentin蛋白的动态变化,研究其放疗干预的时间异质性,Transwell体外侵袭实验比较克隆侵袭力的差异。结果：三株由单细胞扩增培养的同源第三代子克隆依然存在明显生物学差异。形态有明显区别的球形与不规则的克隆形态。不规则形态克隆更表现为SOX2低表达及Vimentin的高表达。并且在单个细胞水平上,同个单克隆群体内也存在个体细胞间蛋白的表达差异（Vimentin; EpCAM）。通过观察放疗前后Vimentin蛋白在不同时间点上的荧光强度,发现肿瘤单克隆细胞存在时间异质性。Transwell体外侵袭实验也显示三个同源克隆间存在明显的差异性。结论：同源的、连续单细胞扩增获得的第三代单克隆依然存在明显生物学差异,提示肿瘤内部异质性是其固有特征,并且在治疗干预下,也会引起肿瘤时间异质性的产生。     

Immunophenotype of thymoma-associated lymphoid cell component of T-cell type. A new analytic procedure in keeping with structural heterogeneities

The phenotype of the lymphoid cell component of 35 thymomas was investigated by analyzing cryostat sections and lymphocyte suspensions. The morphology in each case was determined by examining multiple tissue samples from different parts of the tumor. Structural heterogeneity was shown in 14 thymomas, and a homogeneous morphology of cortical or medullary or mixed types in the others. To assess whether this heterogeneity was correlated with differences in the lymphoid phenotype, we analyzed both lymphocyte suspensions and frozen sections from the same samples. Phenotypical differences in the suspensions of each thymoma in the heterogeneous group were noted and similar differences were also observed in the cryostat sections. Phenotypical abnormalities were found in some thymomas. They consisted of the simultaneous expression of cortical and medullary markers, which was most marked in the heterogenous mixed-type thymomas invading the lung. Furthermore, the global phenotype was tested on a pool of lymphocyte suspensions in all thymomas. This procedure distinguished cortical, medullary and intermediate cortico-medullary immunophenotype models which closely correlated with the tumor histology. It was concluded that, due to the frequent structural and immunological heterogeneity of thymomas, correct assessment of their lymphoid component requires a two-step analysis. This comprises: 1) individual suspensions from samples taken from different areas of the same thymoma, and 2) a pool of these suspensions. The first step will reveal the different immunological characteristics. In the second, the lymphocyte phenotype, which may vary widely throughout the tumor, will be represented in its totality. These findings may be of great help in predicting clinical patterns, especially possible malignant evolution.     

A Multilayer Grow-or-Go Model for GBM: Effects of Invasive Cells and Anti-Angiogenesis on Growth

The recent use of anti-angiogenesis (AA) drugs for the treatment of glioblastoma multiforme (GBM) has uncovered unusual tumor responses. Here, we derive a new mathematical model that takes into account the ability of proliferative cells to become invasive under hypoxic conditions; model simulations generate the multilayer structure of GBM, namely proliferation, brain invasion, and necrosis. The model is able to replicate and justify the clinical observation of rebound growth when AA therapy is discontinued in some patients. The model is interrogated to derive fundamental insights int cancer biology and on the clinical and biological effects of AA drugs. Invasive cells promote tumor growth, which in the long run exceeds the effects of angiogenesis alone. Furthermore, AA drugs increase the fraction of invasive cells in the tumor, which explain progression by fluid-attenuated inversion recovery (FLAIR) signal and the rebound tumor growth when AA is discontinued.     

A mechanistic modeling framework reveals the key principles underlying tumor metabolism

While aerobic glycolysis, or the Warburg effect, has for a long time been considered a hallmark of tumor metabolism, recent studies have revealed a far more complex picture. Tumor cells exhibit widespread metabolic heterogeneity, not only in their presentation of the Warburg effect but also in the nutrients and the metabolic pathways they are dependent on. Moreover, tumor cells can switch between different metabolic phenotypes in response to environmental cues and therapeutic interventions. A framework to analyze the observed metabolic heterogeneity and plasticity is, however, lacking. Using a mechanistic model that includes the key metabolic pathways active in tumor cells, we show that the inhibition of phosphofructokinase by excess ATP in the cytoplasm can drive a preference for aerobic glycolysis in fast-proliferating tumor cells. The differing rates of ATP utilization by tumor cells can therefore drive heterogeneity with respect to the presentation of the Warburg effect. Building upon this idea, we couple the metabolic phenotype of tumor cells to their migratory phenotype, and show that our model predictions are in agreement with previous experiments. Next, we report that the reliance of proliferating cells on different anaplerotic pathways depends on the relative availability of glucose and glutamine, and can further drive metabolic heterogeneity. Finally, using treatment of melanoma cells with a BRAF inhibitor as an example, we show that our model can be used to predict the metabolic and gene expression changes in cancer cells in response to drug treatment. By making predictions that are far more generalizable and interpretable as compared to previous tumor metabolism modeling approaches, our framework identifies key principles that govern tumor cell metabolism, and the reported heterogeneity and plasticity. These principles could be key to targeting the metabolic vulnerabilities of cancer.     

HGF／SF-Met signaling in tumor progression

Tumor progression is a multi-step process that requires a sequential selection of specific malignant phenotypes. Met activation may induce different phenotypes depending on tumor stage: inducing proliferation and angiogenesis in primary tumors, stimulating motility to form micrometastases, and regaining the proliferation phenotype to form overt metastases. To study how HGF/SF-induced proliferative phenotypes switch to the invasive phenotype is important for understanding the mechanism of tumor progression and will provide an attractive target for cancer intervention and therapy.     

Origins and evolution of cell phenotypes in breast tumors

This study presents a stochastic model that correlates genomic instability with tumor formation. The model describes the time- and space-variant volumetric concentrations of cancer cells of various phenotypes in a breast tumor. The cells of epithelial origin in the cancerous breast tissue are classified into four different phenotypes, normal epithelial cells and the grade 1, grade 2 and grade 3 cancer cell types with increasing potential for growth and invasion. Equations governing the time course of volumetric concentrations of cell phenotypes are derived by using the principle of conservation of mass. Cell migration into and from the stroma is taken into account. The transformations between cell phenotypes are due to genetic inheritance and chromosome aberrations. These transformations are assumed to be stochastic functions of the local cell concentration. The simulations of the model for planar geometry replicate the shapes of human breast tumors and capture the time history of tumor growth in animal models. Simulations point to transformation of tumor cell population from heterogeneous compositions to a single phenotype at advanced stages of invasive tumors. Systematic variations of model parameters in the computations indicate the important roles the migration capacity, proliferation rate, and phenotype transition probability play in tumor growth. The model developed provides realistic simulations for standard breast cancer therapies and can be used in the optimization studies of chemotherapy, radiotherapy, hormone therapy and emerging individualized therapies for cancer.     

Discriminating healthy from tumor and necrosis tissue in rat brain tissue samples by Raman spectral imaging

The purpose of this study was to investigate molecular changes associated with glioma tissues by Raman microspectroscopy in order to develop its use in clinical practice. Spectroscopic markers obtained from C6 glioma tissues were compared to conventional histological and histochemical techniques. Cholesterol and phospholipid contents were highest in corpus callosum and decreased gradually towards the cortex surface as well as in the tumor. Two different necrotic areas have been identified: a fully necrotic zone characterized by the presence of plasma proteins and a peri-necrotic area with a high lipid content. This result was confirmed by Nile Red staining. Additionally, one structure was detected in the periphery of the tumor. Invisible with histopathological hematoxylin and eosin staining, it was revealed by immunohistochemical Ki-67 and MT1-MMP staining used to visualize the proliferative and invasive activities of glioma, respectively. Hierarchical cluster analysis on the only cluster averaged spectra showed a clear distinction between normal, tumoral, necrotic and edematous tissues. Raman microspectroscopy can discriminate between healthy and tumoral brain tissue and yield spectroscopic markers associated with the proliferative and invasive properties of glioblastoma. Development of in vivo Raman spectroscopy could thus accurately define tumor margins, identify tumor remnants, and help in the development of novel therapies for glioblastoma.     

Discriminating healthy from tumor and necrosis tissue in rat brain tissue samples by Raman spectral imaging

The purpose of this study was to investigate molecular changes associated with glioma tissues by Raman microspectroscopy in order to develop its use in clinical practice. Spectroscopic markers obtained from C6 glioma tissues were compared to conventional histological and histochemical techniques. Cholesterol and phospholipid contents were highest in corpus callosum and decreased gradually towards the cortex surface as well as in the tumor. Two different necrotic areas have been identified: a fully necrotic zone characterized by the presence of plasma proteins and a peri-necrotic area with a high lipid content. This result was confirmed by Nile Red staining. Additionally, one structure was detected in the periphery of the tumor. Invisible with histopathological hematoxylin and eosin staining, it was revealed by immunohistochemical Ki-67 and MT1-MMP staining used to visualize the proliferative and invasive activities of glioma, respectively. Hierarchical cluster analysis on the only cluster averaged spectra showed a clear distinction between normal, tumoral, necrotic and edematous tissues. Raman microspectroscopy can discriminate between healthy and tumoral brain tissue and yield spectroscopic markers associated with the proliferative and invasive properties of glioblastoma. Development of in vivo Raman spectroscopy could thus accurately define tumor margins, identify tumor remnants, and help in the development of novel therapies for glioblastoma.     

Genetic Variation in a Heterogeneous Environment. I. Temporal Heterogeneity and the Absolute Dominance Model

The conditions for a stable polymorphism and the equilibrium gene frequency in an infinite population are compared when there is spatial or temporal environmental heterogeneity for the absolute dominance model. For temporal variation the conditions for stability are more restrictive and the equilibrium gene frequency is often at a low gene frequency. In a finite population, temporal environmental heterogeneity for the absolute dominance model was found to be quite ineffective in maintaining genetic variation and is often less effective than no selection at all. For comparison, the maximum maintenance for temporal variation is related to the overdominant model. In general, cyclic environmental variation was found to be more effective at maintaining genetic variation than where the environment varies stochastically. The importance of temporal environmental variation and the maintenance of genetic variation is discussed.     

Regional heterogeneity of EGFR gene amplification and nuclear morphology in glioblastomas. An investigation using laser microdissection and pressure catapulting

OBJECTIVE: To study the regional heterogeneity of epidermal growth factor receptor (EGFR) gene amplification (EGFR-GA) in glioblastomas, considering the relationship between this mutation and morphology of tumor cell nuclei. STUDY DESIGN: Tissue samples gained by laser microdissection and pressure catapulting were used for the performance of differential polymerase chain reaction in 32 morphologically different regions from 7 glioblastomas. Semiquantitative determination of EGFR expression and image analysis of tumor cell nuclei were performed in the same regions. RESULTS: Distinct regional differences concerning the degree of EGFR-GA were found in 2 tumor cases. When comparing regions with different degrees of gene amplification within these cases, morphologic differences in tumor cell nuclei were observed. The other tumor cases also showed distinct intratumoral heterogeneity concerning histomorphology but no regional heterogeneity in the degree of EGFR-GA. When comparing regions with a low densitometric EGFR/interferon (INF) band ratio (< 2.19, n = 18) and a high EGFR/IFN band ratio (> 4.39, n = 14), the latter type of region showed a significantly higher percentage of Ki-67--positive tumor cell nuclei and lower values for several shape variables (Fourier amplitudes), indicating a tendency toward a more regular nuclear shape in regions with distinct EGFR-GA. For the EGFR/IFN band ratio, a significant correlation was found with several morphometric variables, especially those of nuclear shape and distances between nuclei. CONCLUSION: In glioblastomas showing regional heterogeneity in the degree of EGFR-GA, morphology of tumor cell nuclei has been shown to be different when comparing regions with different degrees of EGFR-GA. Glioblastomas may also show distinct regional heterogeneity of histomorphology without evidence of regional heterogeneity of EGFR-GA. A significant statistical association has been confirmed between the degree of EGFR-GA and quantitative morphology of tumor cell nuclei.