Comprehensive characterization of PTEN mutational profile in a series of 34,129 colorectal cancers

Loss of expression or activity of the tumor suppressor PTEN acts similarly to an activating mutation in the oncogene PIK3CA in elevating intracellular levels of phosphatidylinositol (3,4,5)-trisphosphate (PIP3), inducing signaling by AKT and other pro-tumorigenic signaling proteins. Here, we analyze sequence data for 34,129 colorectal cancer (CRC) patients, capturing 3,434 PTEN mutations. We identify specific patterns of PTEN mutation associated with microsatellite stability/instability (MSS/MSI), tumor mutational burden (TMB), patient age, and tumor location. Within groups separated by MSS/MSI status, this identifies distinct profiles of nucleotide hotspots, and suggests differing profiles of protein-damaging effects of mutations. Moreover, discrete categories of PTEN mutations display non-identical patterns of co-occurrence with mutations in other genes important in CRC pathogenesis, including KRAS, APC, TP53, and PIK3CA. These data provide context for clinical targeting of proteins upstream and downstream of PTEN in distinct CRC cohorts.Loss of the tumour suppressor gene PTEN leads to the activation of pro-tumourigenic signalling pathways. Here, the authors analyse sequencing data from a large cohort of colorectal cancer patients harbouring PTEN mutations and identify distinct patterns of associations with genomic and clinical features

Feed-Forward Inhibition of Androgen Receptor Activity by Glucocorticoid Action in Human Adipocytes

SummaryWe compared transcriptomes of terminally differentiated mouse 3T3-L1 and human adipocytes to identify cell-specific differences. Gene expression and high content analysis (HCA) data identified the androgen receptor (AR) as both expressed and functional, exclusively during early human adipocyte differentiation. The AR agonist dihydrotestosterone (DHT) inhibited human adipocyte maturation by downregulation of adipocyte marker genes, but not in 3T3-L1. It is interesting that AR induction corresponded with dexamethasone activation of the glucocorticoid receptor (GR); however, when exposed to the differentiation cocktail required for adipocyte maturation, AR adopted an antagonist conformation and was transcriptionally repressed. To further explore effectors within the cocktail, we applied an image-based support vector machine (SVM) classification scheme to show that adipocyte differentiation components inhibit AR action. The results demonstrate human adipocyte differentiation, via GR activation, upregulates AR but also inhibits AR transcriptional activity

Cerebral Blood Flow and Brain Functional Connectivity Changes in Older Adults Participating in a Mindfulness-Based Stress Reduction Program

There is a growing interest in the potential beneficial effects of mindfulness meditation training in protecting against age-related physical, emotional, and cognitive decline. The current prospective, single-center, single-arm study investigated if functional magnetic resonance imaging-based changes in cerebral blood flow and brain functional connectivity could be observed in 11 elderly adults (mean age 79) after participation in a Mindfulness-Based Stress Reduction (MBSR) program. The results showed significantly (p \u3c 0.05) altered cerebral blood flow and functional connectivity in the cingulate gyrus, limbic structures, and subregions of the temporal and frontal lobes, similar to findings of other meditation-related studies in younger populations. Furthermore, these changes were also associated with significant improvements in depression symptoms. This study suggests that the MBSR program can potentially modify cerebral blood flow and connectivity in this population

High Throughput Method to Quantify Anterior-Posterior Polarity of T-Cells and Epithelial Cells

The virologic synapse (VS), which is formed between a virus-infected and uninfected cell, plays a central role in the transmission of certain viruses, such as HIV and HTLV-1. During VS formation, HTLV-1-infected T-cells polarize cellular and viral proteins toward the uninfected T-cell. This polarization resembles anterior-posterior cell polarity induced by immunological synapse (IS) formation, which is more extensively characterized than VS formation and occurs when a T-cell interacts with an antigen-presenting cell. One measure of cell polarity induced by both IS or VS formation is the repositioning of the microtubule organizing center (MTOC) relative to the contact point with the interacting cell. Here we describe an automated, high throughput system to score repositioning of the MTOC and thereby cell polarity establishment. The method rapidly and accurately calculates the angle between the MTOC and the IS for thousands of cells. We also show that the system can be adapted to score anterior-posterior polarity establishment of epithelial cells. This general approach represents a significant advancement over manual cell polarity scoring, which is subject to experimenter bias and requires more time and effort to evaluate large numbers of cells

Automated analysis of Human Protein Atlas immunofluorescence images

The Human Protein Atlas is a rich source of location proteomics data. In this work, we present an automated approach for processing and classifying major subcellular patterns in the Atlas images. We demonstrate that two different classification frameworks (support vector machine and random forest) are effective at determining subcellular locations; we can analyze over 3500 Atlas images with a high degree of accuracy, up to 87.5 % for all of the samples and 98.5 % when only considering samples in whose classification assignments we are most confident. Moreover, the features obtained in both of these frameworks are observed to be highly consistent and generalizable. Additionally, we observe that the features relating the proteins to cell markers are especially important in automated learning approaches. Index Terms Image classification; microscopy; location proteomics; machine learning; feature selection 1

Automated analysis and reannotation of subcellular locations in confocal images from the Human Protein Atlas.

The Human Protein Atlas contains immunofluorescence images showing subcellular locations for thousands of proteins. These are currently annotated by visual inspection. In this paper, we describe automated approaches to analyze the images and their use to improve annotation. We began by training classifiers to recognize the annotated patterns. By ranking proteins according to the confidence of the classifier, we generated a list of proteins that were strong candidates for reexamination. In parallel, we applied hierarchical clustering to group proteins and identified proteins whose annotations were inconsistent with the remainder of the proteins in their cluster. These proteins were reexamined by the original annotators, and a significant fraction had their annotations changed. The results demonstrate that automated approaches can provide an important complement to visual annotation.</p