Pan-cancer in silico analysis of somatic mutations in G-protein coupled receptors: The effect of evolutionary conservation and natural variance

G protein-coupled receptors (GPCRs) form the most frequently exploited drug target family, moreover they are often found mutated in cancer. Here we used an aggregated dataset of mutations found in cancer patient samples derived from the Genomic Data Commons and compared it to the natural human variance as exemplified by data from the 1000 Genomes project. While the location of these mutations across the protein domains did not differ significantly in the two datasets, a mutation enrichment was observed in cancer patients among conserved residues in GPCRs such as the 'DRY' motif. We subsequently created a ranking of high scoring GPCRs, using a multi-objective approach (Pareto Front Ranking). The validity of our approach was confirmed by re-discovery of established cancer targets such as the LPA and mGlu receptor families, and we identified novel GPCRs that had not been directly linked to cancer before such as the P2Y Receptor 10 (P2RY10). As a proof of concept, we projected the structurally investigated mutations in the crystal structure of the C-C Chemokine (CCR) 5 receptor, one of the high-ranking GPCRs previously linked to cancer. Several positions were pinpointed that relate to either structural integrity or endogenous and synthetic ligand binding, providing a rationale to their mechanism of influence in cancer. In conclusion, this study identifies a list of GPCRs that are prioritized for experimental follow up characterization to elucidate their role in cancer. The computational approach here described can be adapted to investigate the roles in cancer of any protein family.

The effect of Antarctic ice-shelf extent on ice discharge

<div>The buttressing strength of Antarctic ice shelves directly effects the amount of ice discharge across the grounding line, with buttressing strength affected by both the thickness and extent of an ice shelf. Recent work has shown that a reduction in ice-shelf buttressing due to ocean induced ice-shelf thinning is responsible for a significant portion of increased Antarctic ice discharge (Gudmundsson et al., 2019, but few studies have attempted to show the effect of variability in ice-shelf extent on ice discharge. This variability arises due to ice-shelf calving following a cycle of long periods of slow, continuous calving interposed with calving of large, discrete sections.  These discrete calving events tend to occur on a comparative timeframe to that of the observational record. As such, when determining observed changes in ice discharge it is crucial that this natural variability is separated from any observed trends.  </div><div> </div><div>In this work we use the numerical ice-flow model Úa in combination with observations of ice shelf extent to diagnostically calculate Antarctic ice discharge. These observations primarily date back to the 1970s, though for some ice shelves records exist back to the 1940s. We assemble an Antarctic wide model for two scenarios: 1) with ice shelves at their maximum observed extent and 2) with ice shelves at their minimum observed extent. We then compare these two scenarios to differences in the observed changes in Antarctic ice-discharge to determine how much can be attributed to natural variance .</div><p> </p><p><span>Gudmundsson, G. H.</span><span>, Paolo, F. S., Adusumilli, S., & Fricker, H. A. (2019). </span>Instantaneous Antarctic ice‐ sheet mass loss driven by thinning ice shelves. <em>Geophysical Research Letters</em>, 46, 13903– 13909. </p>

Effect-Directed Profiling of Powdered Tea Extracts for Catechins, Theaflavins, Flavonols and Caffeine

The antioxidative activity of Camelia sinensis tea and especially powdered tea extracts on the market, among others used as added value in functional foods, can considerably vary due to not only natural variance, but also adulteration and falsification. Thus, an effect-directed profiling was developed to prove the functional effects or health-promoting claims. It took 3–12 min per sample, depending on the assay incubation time, for 21 separations in parallel. Used as a fast product quality control, it can detect known and unknown bioactive compounds. Twenty tea extracts and a reference mixture of 11-bioactive compounds were investigated in parallel under the same chromatographic conditions by a newly developed reversed phase high-performance thin-layer chromatographic method. In eight planar on-surface assays, effect-directed tea profiles were revealed. Catechins and theaflavins turned out to be not only highly active, but also multi-potent compounds, able to act in a broad range of metabolic pathways. The flavan-3-ols acted as radical scavengers (DPPH∙ assay), antibacterials against Gram-positive Bacillus subtilis bacteria, and inhibitors of tyrosinase, α-glucosidase, β-glucosidase, and acetylcholinesterase. Further effects against Gram-negative Aliivibrio fischeri bacteria and β-glucuronidase were assigned to other components in the powdered tea extracts. According to their specifications, the activity responses of the powdered tea extracts were higher than in mere leaf extracts of green, white and black tea. The multi-imaging and effect-directed profiling was not only able to identify known functional food ingredients, but also to detect unknown bioactive compounds (including bioactive contaminants, residues or adulterations).

Model-Based Inference of Punctuated Molecular Evolution

In standard models of molecular evolution, DNA sequences evolve through asynchronous substitutions according to Poisson processes with a constant rate (called the molecular clock) or a rate that can vary (relaxed clock). However, DNA sequences can also undergo episodes of fast divergence that will appear as synchronous substitutions affecting several sites simultaneously at the macroevolutionary timescale. Here, we develop a model, which we call the Relaxed Clock with Spikes model, combining basal, clock-like molecular substitutions with episodes of fast divergence called spikes arising at speciation events. Given a multiple sequence alignment and its time-calibrated species phylogeny, our model is able to detect speciation events (including hidden ones) cooccurring with spike events and to estimate the probability and amplitude of these spikes on the phylogeny. We identify the conditions under which spikes can be distinguished from the natural variance of the clock-like component of molecular substitutions and from variations of the clock. We apply the method to genes underlying snake venom proteins and identify several spikes at gene-specific locations in the phylogeny. This work should pave the way for analyses relying on whole genomes to inform on modes of species diversification.

Model-based inference of punctuated molecular evolution

In standard models of molecular evolution, DNA sequences evolve through asynchronous substitutions according to Poisson processes with a constant rate (called the molecular clock) or a time-varying rate (relaxed clock). However, DNA sequences can also undergo episodes of fast divergence that will appear as synchronous substitutions affecting several sites simultaneously at the macroevolutionary time scale. Here, we develop a model combining basal, clock-like molecular evolution with episodes of fast divergence called spikes arising at speciation events. Given a multiple sequence alignment and its time-calibrated species phylogeny, our model is able to detect speciation events (including hidden ones) co-occurring with spike events and to estimate the probability and amplitude of these spikes on the phylogeny. We identify the conditions under which spikes can be distinguished from the natural variance of the clock-like component of molecular evolution and from temporal variations of the clock. We apply the method to genes underlying snake venom proteins and identify several spikes at gene-specific locations in the phylogeny. This work should pave the way for analyses relying on whole genomes to inform on modes of species diversification.

Debiasing Training Improves Decision Making in the Field

The primary objection to debiasing-training interventions is a lack of evidence that they improve decision making in field settings, where reminders of bias are absent. We gave graduate students in three professional programs ( N = 290) a one-shot training intervention that reduces confirmation bias in laboratory experiments. Natural variance in the training schedule assigned participants to receive training before or after solving an unannounced business case modeled on the decision to launch the Space Shuttle Challenger. We used case solutions to surreptitiously measure participants’ susceptibility to confirmation bias. Trained participants were 19% less likely to choose the inferior hypothesis-confirming solution than untrained participants. Analysis of case write-ups suggests that a reduction in confirmatory hypothesis testing accounts for their improved decision making in the case. The results provide promising evidence that debiasing-training effects transfer to field settings and can improve decision making in professional and private life.

ANOVA model for network meta-analysis of diagnostic test accuracy data

Procedures combining and summarising direct and indirect evidence from independent studies assessing the diagnostic accuracy of different tests for the same disease are referred to network meta-analysis. Network meta-analysis provides a unified inference framework and uses the data more efficiently. Nonetheless, handling the inherent correlation between sensitivity and specificity continues to be a statistical challenge. We developed an arm-based hierarchical model which expresses the logit transformed sensitivity and specificity as the sum of fixed effects for test, correlated study-effects to model the inherent correlation between sensitivity and specificity and a random error associated with various tests evaluated in a given study. We present the accuracy of 11 tests used to triage women with minor cervical lesions to detect cervical precancer. Finally, we compare the results with those from a contrast-based model which expresses the linear predictor as a contrast to a comparator test. The proposed arm-based model is more appealing than the contrast-based model since the former permits more straightforward interpretation of the parameters, makes use of all available data yielding shorter credible intervals, and models more natural variance–covariance matrix structures.