Allele-specific endogenous tagging and quantitative analysis of β-catenin in colorectal cancer cells

Wnt signaling plays important roles in development, homeostasis, and tumorigenesis. Mutations in β-catenin that activate Wnt signaling have been found in colorectal and hepatocellular carcinomas. However, the dynamics of wild-type and mutant forms of β-catenin are not fully understood. Here, we genome-engineered fluorescently tagged alleles of endogenous β-catenin in a colorectal cancer cell line. Wild-type and oncogenic mutant alleles were tagged with different fluorescent proteins, enabling the analysis of both variants in the same cell. We analyzed the properties of both β-catenin alleles using immunoprecipitation, immunofluorescence, and fluorescence correlation spectroscopy approaches, revealing distinctly different biophysical properties. In addition, activation of Wnt signaling by treatment with a GSK3β inhibitor or a truncating APC mutation modulated the wild-type allele to mimic the properties of the mutant β-catenin allele. The one-step tagging strategy demonstrates how genome engineering can be employed for the parallel functional analysis of different genetic variants

Refining Pathways: A Model Comparison Approach

Cellular signalling pathways consolidate multiple molecular interactions into working models of signal propagation, amplification, and modulation. They are described and visualized as networks. Adjusting network topologies to experimental data is a key goal of systems biology. While network reconstruction algorithms like nested effects models are well established tools of computational biology, their data requirements can be prohibitive for their practical use. In this paper we suggest focussing on well defined aspects of a pathway and develop the computational tools to do so. We adapt the framework of nested effect models to focus on a specific aspect of activated Wnt signalling in HCT116 colon cancer cells: Does the activation of Wnt target genes depend on the secretion of Wnt ligands or do mutations in the signalling molecule beta-catenin make this activation independent from them? We framed this question into two competing classes of models: Models that depend on Wnt ligands secretion versus those that do not. The model classes translate into restrictions of the pathways in the network topology. Wnt dependent models are more flexible than Wnt independent models. Bayes factors are the standard Bayesian tool to compare different models fairly on the data evidence. In our analysis, the Bayes factors depend on the number of potential Wnt signalling target genes included in the models. Stability analysis with respect to this number showed that the data strongly favours Wnt ligands dependent models for all realistic numbers of target genes

Wnt secretion is required to maintain high levels of Wnt activity in colon cancer cells

Aberrant regulation of the Wnt/β-catenin pathway has an important role during the onset and progression of colorectal cancer, with over 90% of cases of sporadic colon cancer featuring mutations in APC or β-catenin. However, it has remained a point of controversy whether these mutations are sufficient to activate the pathway or require additional upstream signals. Here we show that colorectal tumours express elevated levels of Wnt3 and Evi/Wls/GPR177. We found that in colon cancer cells, even in the presence of mutations in APC or β-catenin, downstream signalling remains responsive to Wnt ligands and receptor proximal signalling. Furthermore, we demonstrate that truncated APC proteins bind β-catenin and key components of the destruction complex. These results indicate that cells with mutations in APC or β-catenin depend on Wnt ligands and their secretion for a sufficient level of β-catenin signalling, which potentially opens new avenues for therapeutic interventions by targeting Wnt secretion via Evi/Wls

Experiments’ efficiency and reproducibility.

<p>Panel <b>A</b> reports the relative expression of the direct siRNA targets with respect to the control in the corresponding experiment. log-cpm measured in the two replicates of the EVI silencing experiment are shown in panel <b>B</b>. Panel <b>C</b> shows the log fold changes between the cpm measured in two pairs of experiment, namely EVI silencing and CTRL.</p

Model comparison for network structural features.

<p>Panel <b>A</b> is a schematic representation of the two topology classes compared. Panel <b>B</b> summarizes the main result of our statistical case study. Log Bayes Factors were obtained from NEMs including different numbers of potential target genes (x-axis, top), which are included according to a cut-off on the posterior probability that a gene is affected for at least one perturbation. Positive log Bayes factor reflect evidence in favour of a Wnt secretion dependent model. The dashed purple line indicates the smallest cut-off that still favours this topology class. A cut-off of 95% posterior probability is marked by the yellow dashed line.</p

Nested effect models and structural features.

<p>An example of a NEM network, its expected observation pattern and structural features. <b>A</b> shows a signalling network including S- and E-genes. <b>B</b> shows the corresponding expected downstream effects of E-genes that are attached to S-genes (columns), if the S-genes in the rows are blocked. <b>C</b> shows classes of topologies that share a specific feature. In this case the distinguishing feature is the existence of an edge that connects the sub-networks formed by (<i>S</i>₁, <i>S</i>₂, <i>S</i>₃) and (<i>S</i>₄, <i>S</i>₅). The topologies on the right have this feature while those on the left do not.</p

Posterior probabilities of differential expression.

<p>Heat-map of the posterior probabilities of differential expression in the silencing experiments. Only genes which have a posterior probability larger than .5 in at least one of the knock-down experiments are shown. The green line leaves about 750 genes on its left. The pattern there shows that the majority of those genes respond not only to intervention on <i>CTNNB1/β-catenin</i>, but also to <i>EVI/WLS</i>.</p

TRAIL-R deficiency in mice enhances lymph node metastasis without affecting primary tumor development

TRAIL is a promising anticancer agent due to its ability to selectively induce apoptosis in established tumor cell lines but not nontransformed cells. Herein, we demonstrate a role for the apoptosis-inducing TRAIL receptor (TRAIL-R) as a metastasis suppressor. Although mouse models employing tumor transplantation have shown that TRAIL can reduce tumor growth, autochthonous tumor models have generated conflicting results with respect to the physiological role of the TRAIL system during tumorigenesis. We used a multistage model of squamous cell carcinoma to examine the role of TRAIL-R throughout all steps of tumor development. DMBA/TPA-treated TRAIL-R–deficient mice showed neither an increase in number or growth rate of benign papillomas nor an increase in the rate of progression to squamous cell carcinoma. However, metastasis to lymph nodes was significantly enhanced, indicating a role for TRAIL-R specifically in the suppression of metastasis. We also found that adherent TRAIL-R–expressing skin carcinoma cells were TRAIL resistant in vitro but were sensitized to TRAIL upon detachment by inactivation of the ERK signaling pathway. As detachment from the primary tumor is an obligatory step in metastasis, this provides a possible mechanism by which TRAIL-R could inhibit metastasis. Hence, treatment of cancer patients with agonists of the apoptosis-inducing receptors for TRAIL may prove useful in reducing the incidence of metastasis