64 research outputs found
Targeting of distinct signaling cascades and cancer-associated fibroblasts define the efficacy of Sorafenib against prostate cancer cells
Sorafenib, a multi-tyrosine kinase inhibitor, kills more effectively the non-metastatic prostate cancer cell line 22Rv1 than the highly metastatic prostate cancer cell line PC3. In 22Rv1 cells, constitutively active STAT3 and ERK are targeted by sorafenib, contrasting with PC3 cells, in which these kinases are not active. Notably, overexpression of a constitutively active MEK construct in 22Rv1 cells stimulates the sustained phosphorylation of Bad and protects from sorafenib-induced cell death. In PC3 cells, Src and AKT are constitutively activated and targeted by sorafenib, leading to an increase in Bim protein levels. Overexpression of constitutively active AKT or knockdown of Bim protects PC3 cells from sorafenib-induced killing. In both PC3 and 22Rv1 cells, Mcl-1 depletion is required for the induction of cell death by sorafenib as transient overexpression of Mcl-1 is protective. Interestingly, co-culturing of primary cancer-associated fibroblasts (CAFs) with 22Rv1 or PC3 cells protected the cancer cells from sorafenib-induced cell death, and this protection was largely overcome by co-administration of the Bcl-2 antagonist, ABT737. In summary, the differential tyrosine kinase profile of prostate cancer cells defines the cytotoxic efficacy of sorafenib and this profile is modulated by CAFs to promote resistance. The combination of sorafenib with Bcl-2 antagonists, such as ABT737, may constitute a promising therapeutic strategy against prostate cancer
In silico Experimentation of Glioma Microenvironment Development and Anti-tumor Therapy
Tumor cells do not develop in isolation, but co-evolve with stromal cells and tumor-associated immune cells in a tumor microenvironment mediated by an array of soluble factors, forming a complex intercellular signaling network. Herein, we report an unbiased, generic model to integrate prior biochemical data and the constructed brain tumor microenvironment in silico as characterized by an intercellular signaling network comprising 5 types of cells, 15 cytokines, and 69 signaling pathways. The results show that glioma develops through three distinct phases: pre-tumor, rapid expansion, and saturation. We designed a microglia depletion therapy and observed significant benefit for virtual patients treated at the early stages but strikingly no therapeutic efficacy at all when therapy was given at a slightly later stage. Cytokine combination therapy exhibits more focused and enhanced therapeutic response even when microglia depletion therapy already fails. It was further revealed that the optimal combination depends on the molecular profile of individual patients, suggesting the need for patient stratification and personalized treatment. These results, obtained solely by observing the in silico dynamics of the glioma microenvironment with no fitting to experimental/clinical data, reflect many characteristics of human glioma development and imply new venues for treating tumors via selective targeting of microenvironmental components
Cellular Phenotype-Dependent and -Independent Effects of Vitamin C on the Renewal and Gene Expression of Mouse Embryonic Fibroblasts
Vitamin C has been shown to delay the cellular senescence and was considered a candidate for chemoprevention and cancer therapy. To understand the reported contrasting roles of vitamin C: growth-promoting in the primary cells and growth-inhibiting in cancer cells, primary mouse embryonic fibroblasts (MEF) and their isogenic spontaneously immortalized fibroblasts with unlimited cell division potential were used as the model pair. We used microarray gene expression profiling to show that the immortalized MEF possess human cancer gene expression fingerprints including a pattern of up-regulation of inflammatory response-related genes. Using the MEF model, we found that a physiological treatment level of vitamin C (10−5 M), but not other unrelated antioxidants, enhanced cell growth. The growth-promoting effect was associated with a pattern of enhanced expression of cell cycle- and cell division-related genes in both primary and immortalized cells. In the immortalized MEF, physiological treatment levels of vitamin C also enhanced the expression of immortalization-associated genes including a down-regulation of genes in the extracellular matrix functional category. In contrast, confocal immunofluorescence imaging of the primary MEF suggested an increase in collagen IV protein upon vitamin C treatment. Similar to the cancer cells, the growth-inhibitory effect of the redox-active form of vitamin C was preferentially observed in immortalized MEF. All effects of vitamin C required its intracellular presence since the transporter-deficient SVCT2−/− MEF did not respond to vitamin C. SVCT2−/− MEF divided and became immortalized readily indicating little dependence on vitamin C for the cell division. Immortalized SVCT2−/− MEF required higher concentration of vitamin C for the growth inhibition compared to the immortalized wildtype MEF suggesting an intracellular vitamin C toxicity. The relevance of our observation in aging and human cancer prevention was discussed
Application of an Educational Program in Management and Documentation of Nursing Care: Students’ Evaluation
No abstract available
Mutations of microsatellite instability target genes in sporadic basal cell carcinomas
Microsatellite instability (MSI) caused by a defective DNA mismatch repair (MMR) system is one of the phenotypes of genomic instability, accounting for the tumorigenesis of certain types of cancers conveying clinical and prognostic significance. Genes such as TGF-βRII, IGFIIR, hMSH3, and hMSH6 include coding mononucleotide repeats that are known targets for mutations in MSI-high tumors. The aim of our study was to investigate the prevalence of mutations in the above 4 MSI target genes in correlation with the MSI status of 75 basal cell carcinomas (BCCs), including aggressive-growth BCCs and cases with perineural invasion. TGF-βRII or hMSH3 frameshift mutations were identified in 5% of the BCCs, including two cases of aggressive-growth subtype, whereas there were no microsatellite alterations in the IGFIIR and hMSH6 genes. Mutations at the mononucleotide repeats within the hMSH3 and TGF-βRII genes occurred in certain BCCs, not always in association with MSI. It seems likely that microsatellite alterations may be important in the development of individual cases of BCCs despite the low frequency of MSI in our cohort. © 2007 Elsevier GmbH. All rights reserved
Application of an Educational Program in Management and Documentation of Nursing Care: Students’ Evaluation
No abstract available
Expression of hedgehog pathway components in prostate carcinoma microenvironment: Shifting the balance towards autocrine signalling
Aims: The hedgehog (Hh) signalling pathway has been implicated in the pathogenesis and aggressiveness of prostate cancer through epithelial-mesenchymal interactions. The aim of this study was to elucidate the cell-type partitioned expression of the Hh pathway biomarkers in the non-neoplastic and tumour microenvironments and to correlate it with the grade and stage of prostate cancer. Methods and results: Expression of the Hh pathway components (Shh, Smo, Ptch, Gli1) in the microenvironment of non-neoplastic peripheral zone (n=119), hormone-naive primary prostate carcinoma (n=141) and castrate-resistant bone marrow metastases (n=53) was analysed using immunohistochemistry in tissue microarrays and bone marrow sections. Results showed that epithelial Shh, Smo and Ptch expression was up-regulated, whereas stromal Smo, Ptch, and Gli1 expression was down-regulated in prostate carcinomas compared to non-neoplastic peripheral zone tissue. Ptch expression was modulated further in high-grade and high-stage primary tumours and in bone marrow metastases. Hh signalling correlated with ki67 and vascular endothelial growth factor (VEGF) but not with CD31 expression. Conclusion: Our results highlight the importance of Hh-mediated epithelial-mesenchymal interactions in the non-neoplastic prostate and imply that shifting the balance from paracrine towards autocrine signalling is important in the pathogenesis and progression of prostate carcinoma. © 2011 Blackwell Publishing Limited
Information-theory approach to allometric growth of marine organisms
Allometric growth investigations are usually conducted by fitting the allometric model (L) y = axb ⇔ log y = log a + b log x (y, x are morphometric characters and b the allometric exponent), which is quite simple both conceptually and mathematically, and its parameters are easy to estimate by linear regression. However b is not necessarily constant and it may change either continuously or abruptly at specific breakpoints; thus, the simple L model quite often fails to describe allometric growth successfully. In the current context, a better alternative is proposed, based on Kullback-Leibler (K-L) information theory and multi-model inference (MMI). Allometric growth was investigated in eight marine species: the bivalves Pecten jacobaeus and Pinna nobilis, the squids Todarodes sagittatus and Todaropsis eblanae, the crab Pachygrapsus marmoratus (females), the ghost shrimp Pestarella tyrrhena (males), and the fishes Trachurus trachurus and Sparus aurata. In each of the eight species, a pair of body parts was measured and the allometric growth of one body part in relation to the other (reference dimension) was studied, by fitting five different candidate models including: the simple allometric model, two models assuming that b changed continuously and two other assuming that b had a breakpoint. For each species, the 'best' model was selected by minimizing the small-sample, bias-corrected form of the Akaike Information Criterion. To quantify the plausibility of each model, given the data and the set of five models, the 'Akaike weight' wi of each model was calculated; based on wi the average model was estimated for each case. MMI is beneficial, more robust, and may reveal more information than the classical approach. As demonstrated with the given examples, estimation of b from the linear model, when it was not supported by the data, revealed some characteristic pitfalls, such as concluding positive allometry when there is actually negative or vice versa, or reporting allometry when the data in reality support isometric growth or vice versa. © 2006 Springer-Verlag
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