| Abstract | We set out to investigate the emerging intratumoral heterogeneity and to determine the evolutionary trajectories of the combination of cell-intrinsic kinetics that yield aggressive tumor growth . |
| Abstract | Our study suggests that cell proliferation potential is the strongest modulator of tumor growth . |
| Author Summary | We present an in silico computational model of tumor growth and evolution according to the cancer stem cell hypothesis. |
| Introduction | Transformation may occur at any time in all tissue compartments, but the ability of transformed cells to initiate and sustain pathologic tumor growth requires certain kinetic properties including longevity, migration potential, self-renewal and differentiation capacity. |
| Introduction | The kinetics will be inherited by the descendent cells yielding tumor population dynamics ranging from microscopic dormancy to aggressive tumor growth [16]. |
| Spontaneous undirected mutations promote tumor growth | Spontaneous undirected mutations promote tumor growth |
| Spontaneous undirected mutations promote tumor growth | We initialize tumor growth simulations with one CSC with the initial traits probability of symmetric division ps 2 0.05, proliferation capacity p = 10, migration potential [.1 = 15 and probability of spontaneous death or = 0.01, which has previously been shown to simulate fast tumor growth [16,27]. |
| Spontaneous undirected mutations promote tumor growth | We simulate tumor growth for t = 730 days, i.e. |
| Abstract | 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. |
| Author Summary | Over the course of tumor growth , cancer cells interact with normal cells via processes that are difficult to understand by experiment alone. |
| Discussion | Ultimately, the immunological state (or contexture) at the tumor site predicted tumor survival long before an impact on tumor growth was evident. |
| Discussion | If the establishment of a tumor-supporting local network state (vs. one that controls tumor growth ) is supported through positive feedback, then any pro-tumor influence, even one that is stochastic, could tip the balance towards favoring an M2 phenotype that promotes tumor survival. |
| Discussion | More specifically, both strategies that suppressed the polarization of engineered macrophages to an M2 phenotype were effective at controlling tumor growth , even when these engineered cells comprised a minority of macrophages at the tumor site and polarization of native macrophages was not manipulated. |
| Introduction | As ubiquitous cells of the innate immune system, macrophages are present at the earliest stages of tumor establishment, are found in great numbers at tumor sites (along with the related myeloid-derived suppressor cells), and have the capacity to functionally “polarize” to phenotypes that alternatively suppress or promote tumor growth [18—20]. |
| Results | 1B), and the effects of oxygen and vascularization on both tumor growth and death, as well as on macrophage recruitment (Fig. |
| Results | The resulting limited oxygen availability led to asymmetric tumor growth , which is also a general feature of growing tumors [34,45]. |
| Abstract | Angiogenesis plays a key role in tumor growth and cancer progression. |
| Author Summary | Tumor vascularization is essential for tumor growth and cancer progression. |
| Combining computational and experimental approaches to delineate the pathways controlling TEM pro-angiogenic function | The identification of the ligands and the pathways controlling the highly pro-angiogenic activity of tumor TEM is of paramount significance because it represents the rationale for a treatment directing TEM away from being cells supporting tumor growth . |
| Introduction | The VEGFR-1 (Vascular Endothelial Growth Factor Receptor-1), TGFBR-l ( Tumor Growth Factor [3 Receptor-1), TNF-Rl (Tumor Necrosis Factor Receptor-1) pathways have been reported to regulate tumor angiogenesis [36,37], but their activities have not been examined in human TEM. |
| Supporting Information | Tumor tissue processing, TEM differentiation in vitro, TEM stimulation, in vitro angiogenesis assay, migration assay, tumor growth inhibition assay and protein profiling 81 Fig. |
| abundance of genes regulating differentiation and immune response of TEM differentiated in vitro | Taken together, our results suggest that ANG-2/TGF-[3 and PlGF/TGF-B treatments are not only anti-angiogenic but also shift the gene expression profile of monocytes toward the one of cells promoting immune surveillance, thereby limiting tumor growth . |
| Abstract | Our study suggests that downstream signaling from IGFI to H|F1 a, which has been the target of many insulin signaling drugs in clinical trials, plays a smaller role in overall tumor growth . |
| Discussion | When we conducted the glioblastoma growth reduction analyses of the LN229 and U87 cell lines, there was almost no change in growth observed in the U87 cell lines, while the LN229 showed a reduction in the glioblastoma tumors’ growth . |
| Insulin signaling pathway reactions that drive glioma growth | In order to analyze the contribution of each rate constant to glioblastoma growth, the sensitivity index was calculated for each rate constant, for LN229 tumor growth (shown in Table 4 in descending order). |