Dual endothelin-converting enzyme/neutral endopeptidase blockade in rats with D-galactosamine-induced liver failure

Secondary activation of the endothelin system is thought to be involved in toxic liver injury. This study tested the hypothesis that dual endothelin-converting enzyme / neutral endopeptidase blockade might be able to attenuate acute toxic liver injury

Stability analysis of mixtures of mutagenetic trees

<p>Abstract</p> <p>Background</p> <p>Mixture models of mutagenetic trees are evolutionary models that capture several pathways of ordered accumulation of genetic events observed in different subsets of patients. They were used to model HIV progression by accumulation of resistance mutations in the viral genome under drug pressure and cancer progression by accumulation of chromosomal aberrations in tumor cells. From the mixture models a genetic progression score (GPS) can be derived that estimates the genetic status of single patients according to the corresponding progression along the tree models. GPS values were shown to have predictive power for estimating drug resistance in HIV or the survival time in cancer. Still, the reliability of the exact values of such complex markers derived from graphical models can be questioned.</p> <p>Results</p> <p>In a simulation study, we analyzed various aspects of the stability of estimated mutagenetic trees mixture models. It turned out that the induced probabilistic distributions and the tree topologies are recovered with high precision by an EM-like learning algorithm. However, only for models with just one major model component, also GPS values of single patients can be reliably estimated.</p> <p>Conclusion</p> <p>It is encouraging that the estimation process of mutagenetic trees mixture models can be performed with high confidence regarding induced probability distributions and the general shape of the tree topologies. For a model with only one major disease progression process, even genetic progression scores for single patients can be reliably estimated. However, for models with more than one relevant component, alternative measures should be introduced for estimating the stage of disease progression.</p

P35. Intratumoral patterns of clonal evolution in meningiomas

Núm. a Art Públic: 1815Digitalitzat per Tecnodo

Genome-wide expression changes induced by bisphenol A, F and S in human stem cell derived hepatocyte-like cells

Acknowledgments BLV and DCH were funded by an award from the Chief Scientist Office (TCS 16/37). This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 681002 (EU-ToxRisk) and from TransQST (no. 116030).Peer reviewedPublisher PD

Factor interaction analysis for chromosome 8 and DNA methylation alterations highlights innate immune response suppression and cytoskeletal changes in prostate cancer

BACKGROUND: Alterations of chromosome 8 and hypomethylation of LINE-1 retrotransposons are common alterations in advanced prostate carcinoma. In a former study including many metastatic cases, they strongly correlated with each other. To elucidate a possible interaction between the two alterations, we investigated their relationship in less advanced prostate cancers. RESULTS: In 50 primary tumor tissues, no correlation was observed between chromosome 8 alterations determined by comparative genomic hybridization and LINE-1 hypomethylation measured by Southern blot hybridization. The discrepancy towards the former study, which had been dominated by advanced stage cases, suggests that both alterations converge and interact during prostate cancer progression. Therefore, interaction analysis was performed on microarray-based expression profiles of cancers harboring both alterations, only one, or none. Application of a novel bioinformatic method identified Gene Ontology (GO) groups related to innate immunity, cytoskeletal organization and cell adhesion as common targets of both alterations. Many genes targeted by their interaction were involved in type I and II interferon signaling and several were functionally related to hereditary prostate cancer genes. In addition, the interaction appeared to influence a switch in the expression pattern of EPB41L genes encoding 4.1 cytoskeleton proteins. Real-time RT-PCR revealed GADD45A, MX1, EPB41L3/DAL1, and FBLN1 as generally downregulated in prostate cancer, whereas HOXB13 and EPB41L4B were upregulated. TLR3 was downregulated in a subset of the cases and associated with recurrence. Downregulation of EPB41L3, but not of GADD45A, was associated with promoter hypermethylation, which was detected in 79% of carcinoma samples. CONCLUSION: Alterations of chromosome 8 and DNA hypomethylation in prostate cancer probably do not cause each other, but converge during progression. The present analysis implicates their interaction in innate immune response suppression and cytoskeletal changes during prostate cancer progression. The study thus highlights novel mechanisms in prostate cancer progression and identifies novel candidate genes for diagnostic and therapeutic purposes. In particular, TLR3 expression might be useful for prostate cancer prognosis and EPB41L3 hypermethylation for its detection

Role of thioredoxin reductase 1 and thioredoxin interacting protein in prognosis of breast cancer

Introduction: The purpose of this work was to study the prognostic influence in breast cancer of thioredoxin reductase 1 (TXNRD1) and thioredoxin interacting protein (TXNIP), key players in oxidative stress control that are currently evaluated as possible therapeutic targets. Methods: Analysis of the association of TXNRD1 and TXNIP RNA expression with the metastasis-free interval (MFI) was performed in 788 patients with node-negative breast cancer, consisting of three individual cohorts (Mainz, Rotterdam and Transbig). Correlation with metagenes and conventional clinical parameters (age, pT stage, grading, hormone and ERBB2 status) was explored. MCF-7 cells with a doxycycline-inducible expression of an oncogenic ERBB2 were used to investigate the influence of ERBB2 on TXNRD1 and TXNIP transcription. Results: TXNRD1 was associated with worse MFI in the combined cohort (hazard ratio = 1.955; P < 0.001) as well as in all three individual cohorts. In contrast, TXNIP was associated with better prognosis (hazard ratio = 0.642; P < 0.001) and similar results were obtained in all three subcohorts. Interestingly, patients with ERBB2-status-positive tumors expressed higher levels of TXNRD1. Induction of ERBB2 in MCF-7 cells caused not only an immediate increase in TXNRD1 but also a strong decrease in TXNIP. A subsequent upregulation of TXNIP as cells undergo senescence was accompanied by a strong increase in levels of reactive oxygen species. Conclusions: TXNRD1 and TXNIP are associated with prognosis in breast cancer, and ERBB2 seems to be one of the factors shifting balances of both factors of the redox control system in a prognostic unfavorable manner

Prognostic Impact of Immunoglobulin Kappa C (IGKC) in Early Breast Cancer

We studied the prognostic impact of tumor immunoglobulin kappa C (IGKC) mRNA expression as a marker of the humoral immune system in the FinHer trial patient population, where 1010 patients with early breast cancer were randomly allocated to either docetaxel-containing or vinorelbine-containing adjuvant chemotherapy. HER2-positive patients were additionally allocated to either trastuzumab or no trastuzumab. Hormone receptor-positive patients received tamoxifen. IGKC was evaluated in 909 tumors using quantitative real-time polymerase chain reaction, and the influence on distant disease-free survival (DDFS) was examined using univariable and multivariable Cox regression and Kaplan–Meier estimates. Interactions were analyzed using Cox regression. IGKC expression, included as continuous variable, was independently associated with DDFS in a multivariable analysis also including age, molecular subtype, grade, and pT and pN stage (HR 0.930, 95% CI 0.870–0.995, p = 0.034). An independent association with DDFS was also found in a subset analysis of triple-negative breast cancers (TNBC) (HR 0.843, 95% CI 0.724–0.983, p = 0.029), but not in luminal (HR 0.957, 95% CI 0.867–1.056, p = 0.383) or HER2-positive (HR 0.933, 95% CI 0.826–1.055, p = 0.271) cancers. No significant interaction between IGKC and chemotherapy or trastuzumab administration was detected (Pinteraction = 0.855 and 0.684, respectively). These results show that humoral immunity beneficially influences the DDFS of patients with early TNBC

Computational Cancer Biology: An Evolutionary Perspective

ISSN:1553-734XISSN:1553-735

Survival models with preclustered gene groups as covariates

<p>Abstract</p> <p>Background</p> <p>An important application of high dimensional gene expression measurements is the risk prediction and the interpretation of the variables in the resulting survival models. A major problem in this context is the typically large number of genes compared to the number of observations (individuals). Feature selection procedures can generate predictive models with high prediction accuracy and at the same time low model complexity. However, interpretability of the resulting models is still limited due to little knowledge on many of the remaining selected genes. Thus, we summarize genes as gene groups defined by the hierarchically structured Gene Ontology (GO) and include these gene groups as covariates in the hazard regression models. Since expression profiles within GO groups are often heterogeneous, we present a new method to obtain subgroups with coherent patterns. We apply preclustering to genes within GO groups according to the correlation of their gene expression measurements.</p> <p>Results</p> <p>We compare Cox models for modeling disease free survival times of breast cancer patients. Besides classical clinical covariates we consider genes, GO groups and preclustered GO groups as additional genomic covariates. Survival models with preclustered gene groups as covariates have similar prediction accuracy as models built only with single genes or GO groups.</p> <p>Conclusions</p> <p>The preclustering information enables a more detailed analysis of the biological meaning of covariates selected in the final models. Compared to models built only with single genes there is additional functional information contained in the GO annotation, and compared to models using GO groups as covariates the preclustering yields coherent representative gene expression profiles.</p

Changes in cortical cytoskeletal and extracellular matrix gene expression in prostate cancer are related to oncogenic ERG deregulation

Abstract Background The cortical cytoskeleton network connects the actin cytoskeleton to various membrane proteins, influencing cell adhesion, polarity, migration and response to extracellular signals. Previous studies have suggested changes in the expression of specific components in prostate cancer, especially of 4.1 proteins (encoded by EPB41 genes) which form nodes in this network. Methods Expression of EPB41L1, EPB41L2, EPB41L3 (protein: 4.1B), EPB41L4B (EHM2), EPB41L5, EPB49 (dematin), VIL2 (ezrin), and DLG1 (summarized as „cortical cytoskeleton" genes) as well as ERG was measured by quantitative RT-PCR in a well-characterized set of 45 M0 prostate adenocarcinoma and 13 benign tissues. Hypermethylation of EPB41L3 and GSTP1 was compared in 93 cancer tissues by methylation-specific PCR. Expression of 4.1B was further studied by immunohistochemistry. Results EPB41L1 and EPB41L3 were significantly downregulated and EPB41L4B was upregulated in cancer tissues. Low EPB41L1 or high EPB41L4B expression were associated with earlier biochemical recurrence. None of the other cortical cytoskeleton genes displayed expression changes, in particular EPB49 and VIL2, despite hints from previous studies. EPB41L3 downregulation was significantly associated with hypermethylation of its promoter and strongly correlated with GSTP1 hypermethylation. Protein 4.1B was detected most strongly in the basal cells of normal prostate epithelia. Its expression in carcinoma cells was similar to the weaker one in normal luminal cells. EPB41L3 downregulation and EPB41L4B upregulation were essentially restricted to the 22 cases with ERG overexpression. Expression changes in EPB41L3 and EPB41L4B closely paralleled those previously observed for the extracellular matrix genes FBLN1 and SPOCK1, respectively. Conclusions Specific changes in the cortical cytoskeleton were observed during prostate cancer progression. They parallel changes in the expression of extracellular matrix components and all together appear to be associated with oncogenic ERG overexpression. We hypothesize that these alterations may contribute to the increased invasivity conferred to prostate cancer cells by ERG deregulation.</p