Prediction of a gene regulatory network linked to prostate cancer from gene expression, microRNA and clinical data

Motivation: Cancer is a complex disease, triggered by mutations in multiple genes and pathways. There is a growing interest in the application of systems biology approaches to analyze various types of cancer-related data to understand the overwhelming complexity of changes induced by the disease

WNT signaling regulates self-renewal and differentiation of prostate cancer cells with stem cell characteristics

Prostate cancer cells with stem cell characteristics were identified in human prostate cancer cell lines by their ability to form from single cells self-renewing prostaspheres in non-adherent cultures. Prostaspheres exhibited heterogeneous expression of proliferation, differentiation and stem cell-associated makers CD44, ABCG2 and CD133. Treatment with WNT inhibitors reduced both prostasphere size and self-renewal. In contrast, addition of Wnt3a caused increased prostasphere size and self-renewal, which was associated with a significant increase in nuclear Β-catenin, keratin 18, CD133 and CD44 expression. As a high proportion of LNCaP and C4-2B cancer cells express androgen receptor we determined the effect of the androgen receptor antagonist bicalutamide. Androgen receptor inhibition reduced prostasphere size and expression of PSA, but did not inhibit prostasphere formation. These effects are consistent with the androgen-independent self-renewal of cells with stem cell characteristics and the androgen-dependent proliferation of transit amplifying cells. As the canonical WNT signaling effector Β-catenin can also associate with the androgen receptor, we propose a model for tumour propagation involving a balance between WNT and androgen receptor activity. That would affect the self-renewal of a cancer cell with stem cell characteristics and drive transit amplifying cell proliferation and differentiation. In conclusion, we provide evidence that WNT activity regulates the self-renewal of prostate cancer cells with stem cell characteristics independently of androgen receptor activity. Inhibition of WNT signaling therefore has the potential to reduce the self-renewal of prostate cancer cells with stem cell characteristics and improve the therapeutic outcome.Peer reviewe

Detection of regulator genes and eQTLs in gene networks

Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression levels of nearby genes (they are "expression quantitative trait loci" or eQTLs for short) and presumably play a gene regulatory role, affecting the status of molecular networks of interacting genes, proteins and metabolites. Computational systems biology approaches to reconstruct causal gene networks from large-scale omics data have therefore become essential to understand the structure of networks controlled by eQTLs together with other regulatory genes, and to generate detailed hypotheses about the molecular mechanisms that lead from genotype to phenotype. Here we review the main analytical methods and softwares to identify eQTLs and their associated genes, to reconstruct co-expression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.Comment: minor revision with typos corrected; review article; 24 pages, 2 figure

OC6 Phase I: Investigating the underprediction of low-frequency hydrodynamic loads and responses of a floating wind turbine

Phase I of the OC6 project is focused on examining why offshore wind design tools underpredict the response (loads/motion) of the OC5-DeepCwind semisubmersible at its surge and pitch natural frequencies. Previous investigations showed that the underprediction was primarily related to nonlinear hydrodynamic loading, so two new validation campaigns were performed to separately examine the different hydrodynamic load components. In this paper, we validate a variety of tools against this new test data, focusing on the ability to accurately model the low-frequency loads on a semisubmersible floater when held fixed under wave excitation and when forced to oscillate in the surge direction. However, it is observed that models providing better load predictions in these two scenarios do not necessarily produce a more accurate motion response in a moored configuration.The authors would like to acknowledge the support of the MARINET2 project (European Union’s Horizon 2020 grant agreement 731084), which supplied the tank test time and travel support to accomplish the testing campaign. The support of MARIN in the preparation, execution of the modeltests, and the evaluation of the uncertainties was essential for this study. MARIN’s contribution was partly funded by the Dutch Ministry of Economic Affairs through TKI-ARD funding programs. This work was authored in part by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36- 08GO28308. Funding provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Wind Energy Technologies Office. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes

Applying unmixing to gene expression data for tumor phylogeny inference

<p>Abstract</p> <p>Background</p> <p>While in principle a seemingly infinite variety of combinations of mutations could result in tumor development, in practice it appears that most human cancers fall into a relatively small number of "sub-types," each characterized a roughly equivalent sequence of mutations by which it progresses in different patients. There is currently great interest in identifying the common sub-types and applying them to the development of diagnostics or therapeutics. Phylogenetic methods have shown great promise for inferring common patterns of tumor progression, but suffer from limits of the technologies available for assaying differences between and within tumors. One approach to tumor phylogenetics uses differences between single cells within tumors, gaining valuable information about intra-tumor heterogeneity but allowing only a few markers per cell. An alternative approach uses tissue-wide measures of whole tumors to provide a detailed picture of averaged tumor state but at the cost of losing information about intra-tumor heterogeneity.</p> <p>Results</p> <p>The present work applies "unmixing" methods, which separate complex data sets into combinations of simpler components, to attempt to gain advantages of both tissue-wide and single-cell approaches to cancer phylogenetics. We develop an unmixing method to infer recurring cell states from microarray measurements of tumor populations and use the inferred mixtures of states in individual tumors to identify possible evolutionary relationships among tumor cells. Validation on simulated data shows the method can accurately separate small numbers of cell states and infer phylogenetic relationships among them. Application to a lung cancer dataset shows that the method can identify cell states corresponding to common lung tumor types and suggest possible evolutionary relationships among them that show good correspondence with our current understanding of lung tumor development.</p> <p>Conclusions</p> <p>Unmixing methods provide a way to make use of both intra-tumor heterogeneity and large probe sets for tumor phylogeny inference, establishing a new avenue towards the construction of detailed, accurate portraits of common tumor sub-types and the mechanisms by which they develop. These reconstructions are likely to have future value in discovering and diagnosing novel cancer sub-types and in identifying targets for therapeutic development.</p

Heterogeneity assessment of functional T cell avidity.

The potency of cellular immune responses strongly depends on T cell avidity to antigen. Yet, functional avidity measurements are rarely performed in patients, mainly due to the technical challenges of characterizing heterogeneous T cells. The mean functional T cell avidity can be determined by the IFN-γ Elispot assay, with titrated amounts of peptide. Using this assay, we developed a method revealing the heterogeneity of functional avidity, represented by the steepness/hillslope of the peptide titration curve, documented by proof of principle experiments and mathematical modeling. Our data show that not only natural polyclonal CD8 T cell populations from cancer patients, but also monoclonal T cells differ strongly in their heterogeneity of functional avidity. Interestingly, clones and polyclonal cells displayed comparable ranges of heterogeneity. We conclude that besides the mean functional avidity, it is feasible and useful to determine its heterogeneity (hillslope) for characterizing T cell responses in basic research and patient investigation

Epstein-Barr virus as a marker of biological aggressiveness in breast cancer

International audienceAlthough a potential role of the Epstein-Barr virus (EBV) in the pathogenesis of breast cancer (BC) has been underlined, results remain conflicting. Particularly, the impact of EBV infection on biological markers of BC has received little investigation

Analysis of the 10q23 chromosomal region and the PTEN gene in human sporadic breast carcinoma

We examined a panel of sporadic breast carcinomas for loss of heterozygosity (LOH) in a 10-cM interval on chromosome 10 known to encompass the PTEN gene. We detected allele loss in 27 of 70 breast tumour DNAs. Fifteen of these showed loss limited to a subregion of the area studied. The most commonly deleted region was flanked by D10S215 and D10S541 and encompasses the PTEN locus. We used a combination of denaturing gradient gel electrophoresis and single-strand conformation polymorphism analyses to investigate the presence of PTEN mutations in tumours with LOH in this region. We did not detect mutations of PTEN in any of these tumours. Our data show that, in sporadic breast carcinoma, loss of heterozygosity of the PTEN locus is frequent, but mutation of PTEN is not. These results are consistent with loss of another unidentified tumour suppressor in this region in sporadic breast carcinoma. © 1999 Cancer Research Campaig