Regression Adjustment for Noncrossing Bayesian Quantile Regression

<p>A two-stage approach is proposed to overcome the problem in quantile regression, where separately fitted curves for several quantiles may cross. The standard Bayesian quantile regression model is applied in the first stage, followed by a Gaussian process regression adjustment, which monotonizes the quantile function while borrowing strength from nearby quantiles. The two-stage approach is computationally efficient, and more general than existing techniques. The method is shown to be competitive with alternative approaches via its performance in simulated examples. Supplementary materials for the article are available online.</p

Approximate Bayesian Computation and Bayes’ Linear Analysis: Toward High-Dimensional ABC

<div><p>Bayes’ linear analysis and approximate Bayesian computation (ABC) are techniques commonly used in the Bayesian analysis of complex models. In this article, we connect these ideas by demonstrating that regression-adjustment ABC algorithms produce samples for which first- and second-order moment summaries approximate adjusted expectation and variance for a Bayes’ linear analysis. This gives regression-adjustment methods a useful interpretation and role in exploratory analysis in high-dimensional problems. As a result, we propose a new method for combining high-dimensional, regression-adjustment ABC with lower-dimensional approaches (such as using Markov chain Monte Carlo for ABC). This method first obtains a rough estimate of the joint posterior via regression-adjustment ABC, and then estimates each univariate marginal posterior distribution separately in a lower-dimensional analysis. The marginal distributions of the initial estimate are then modified to equal the separately estimated marginals, thereby providing an improved estimate of the joint posterior. We illustrate this method with several examples. Supplementary materials for this article are available online.</p></div

Exosomes promote cetuximab resistance via the PTEN/Akt pathway in colon cancer cells

<div><p>Cetuximab is widely used in patients with metastatic colon cancer expressing wildtype KRAS. However, acquired drug resistance limits its clinical efficacy. Exosomes are nanosized vesicles secreted by various cell types. Tumor cell-derived exosomes participate in many biological processes, including tumor invasion, metastasis, and drug resistance. In this study, exosomes derived from cetuximab-resistant RKO colon cancer cells induced cetuximab resistance in cetuximab-sensitive Caco-2 cells. Meanwhile, exosomes from RKO and Caco-2 cells showed different levels of phosphatase and tensin homolog (PTEN) and phosphor-Akt. Furthermore, reduced PTEN and increased phosphorylated Akt levels were found in Caco-2 cells after exposure to RKO cell-derived exosomes. Moreover, an Akt inhibitor prevented RKO cell-derived exosome-induced drug resistance in Caco-2 cells. These findings provide novel evidence that exosomes derived from cetuximab-resistant cells could induce cetuximab resistance in cetuximab-sensitive cells, by downregulating PTEN and increasing phosphorylated Akt levels.</p></div