Discovery, Validation and Mechanistic Study of XPO1 Inhibition in the Treatment of Triple-Negative Breast Cancer.

: Triple-negative breast cancer (TNBC) is an aggressive form of breast cancer with limited treatment options. The nuclear export protein XPO1 has emerged as a potential therapeutic target in cancer, but its role in TNBC has not been fully characterized. This study investigates the potential of repurposing selinexor, an FDA-approved XPO1 inhibitor, as a novel therapeutic options for TNBC.

Integration of Pan-Cancer Cell Line and Single-Cell Transcriptomic Profiles Enables Inference of Therapeutic Vulnerabilities in Heterogeneous Tumors.

Unlabelled: Single-cell RNA sequencing (scRNA-seq) greatly advanced the understanding of intratumoral heterogeneity by identifying distinct cancer cell subpopulations. However, translating biological differences into treatment strategies is challenging due to a lack of tools to facilitate efficient drug discovery that tackles heterogeneous tumors. Developing such approaches requires accurate prediction of drug response at the single-cell level to offer therapeutic options to specific cell subpopulations.

A Web Application for Predicting Drug Combination Efficacy Using Monotherapy Data and IDACombo.

We recently reported a computational method (IDACombo) designed to predict the efficacy of cancer drug combinations using monotherapy response data and the assumptions of independent drug action. Given the strong agreement between IDACombo predictions and measured drug combination efficacy in vitro and in clinical trials, we believe IDACombo can be of immediate use to researchers who are working to develop novel drug combinations. While we previously released our method as an R package, we have now created an R Shiny application to allow researchers without programming experience to easily utilize this method.

Revealing Pan-Histology Immunomodulatory Targets in Pediatric Central Nervous System Tumors.

Background: The application of immunotherapy for pediatric CNS malignancies has been limited by the poorly understood immune landscape in this context. The aim of this study was to uncover the mechanisms of immune suppression common among pediatric brain tumors.

Methods: We apply an immunologic clustering algorithm validated by The Cancer Genome Atlas Project to an independent pediatric CNS transcriptomic dataset.

Inferring therapeutic vulnerability within tumors through integration of pan-cancer cell line and single-cell transcriptomic profiles.

Single-cell RNA sequencing greatly advanced our understanding of intratumoral heterogeneity through identifying tumor subpopulations with distinct biologies. However, translating biological differences into treatment strategies is challenging, as we still lack tools to facilitate efficient drug discovery that tackles heterogeneous tumors. One key component of such approaches tackles accurate prediction of drug response at the single-cell level to offer therapeutic options to specific cell subpopulations.

Simplicity: web-based visualization and analysis of high-throughput cancer cell line screens.

High-throughput drug screens are a powerful tool for cancer drug development. However, the results of such screens are often made available only as raw data, which is intractable for researchers without informatic skills, or as highly processed summary statistics, which can lack essential information for translating screening results into clinically meaningful discoveries. To improve the usability of these datasets, we developed Simplicity, a robust and user-friendly web interface for visualizing, exploring, and summarizing raw and processed data from high-throughput drug screens.

Cooperativity between H3.3K27M and PDGFRA poses multiple therapeutic vulnerabilities in human iPSC-derived diffuse midline glioma avatars.

Diffuse midline glioma (DMG) is a leading cause of brain tumor death in children. In addition to hallmark H3.3K27M mutations, significant subsets also harbor alterations of other genes, such as and .

Simplicity: Web-Based Visualization and Analysis of High-Throughput Cancer Cell Line Screens.

High-throughput drug screens are a powerful tool for cancer drug development. However, the results of such screens are often made available only as raw data, which is intractable for researchers without informatics skills, or as highly processed summary statistics, which can lack essential information for translating screening results into clinically meaningful discoveries. To improve the usability of these datasets, we developed Simplicity, a robust and user-friendly web interface for visualizing, exploring, and summarizing raw and processed data from high- throughput drug screens.

oncoPredict: an R package for predicting in vivo or cancer patient drug response and biomarkers from cell line screening data.

Cell line drug screening datasets can be utilized for a range of different drug discovery applications from drug biomarker discovery to building translational models of drug response. Previously, we described three separate methodologies to (1) correct for general levels of drug sensitivity to enable drug-specific biomarker discovery, (2) predict clinical drug response in patients and (3) associate these predictions with clinical features to perform in vivo drug biomarker discovery. Here, we unite and update these methodologies into one R package (oncoPredict) to facilitate the development and adoption of these tools.

Facilitating Drug Discovery in Breast Cancer by Virtually Screening Patients Using In Vitro Drug Response Modeling.

(1) Background: Drug imputation methods often aim to translate in vitro drug response to in vivo drug efficacy predictions. While commonly used in retrospective analyses, our aim is to investigate the use of drug prediction methods for the generation of novel drug discovery hypotheses. Triple-negative breast cancer (TNBC) is a severe clinical challenge in need of new therapies.

More than fishing for a cure: The promises and pitfalls of high throughput cancer cell line screens.

High-throughput screens in cancer cell lines (CCLs) have been used for decades to help researchers identify compounds with the potential to improve the treatment of cancer and, more recently, to identify genomic susceptibilities in cancer via genome-wide shRNA and CRISPR/Cas9 screens. Additionally, rich genomic and transcriptomic data of these CCLs has allowed researchers to pair this screening data with biological features, enabling efforts to identify biomarkers of treatment response and gene dependencies. In this paper, we review the major CCL screening efforts and the large datasets these screens have made available.

Discovering novel pharmacogenomic biomarkers by imputing drug response in cancer patients from large genomics studies.

Obtaining accurate drug response data in large cohorts of cancer patients is very challenging; thus, most cancer pharmacogenomics discovery is conducted in preclinical studies, typically using cell lines and mouse models. However, these platforms suffer from serious limitations, including small sample sizes. Here, we have developed a novel computational method that allows us to impute drug response in very large clinical cancer genomics data sets, such as The Cancer Genome Atlas (TCGA).

Thielavialides A-E, nor-spiro-azaphilones, and a bis-spiro-azaphilone from Thielavia sp. PA0001, an endophytic fungus isolated from aeroponically grown Physalis alkekengi.

Four new nor-spiro-azaphilones, thielavialides A-D (1- 4), a new bis-spiro-azaphilone, thielavialide E (5), together with pestafolide A (6), were isolated from the endophytic fungal strain, Thielavia sp. PA0001, occurring in the healthy leaf tissue of aeroponically grown Physalis alkekengi. The structures and relative configurations of 1-5 were established on the basis of their MS and NMR data.

Microarray analysis of spaceflown murine thymus tissue reveals changes in gene expression regulating stress and glucocorticoid receptors.

The detrimental effects of spaceflight and simulated microgravity on the immune system have been extensively documented. We report here microarray gene expression analysis, in concert with quantitative RT-PCR, in young adult C57BL/6NTac mice at 8 weeks of age after exposure to spaceflight aboard the space shuttle (STS-118) for a period of 13 days. Upon conclusion of the mission, thymus lobes were extracted from space flown mice (FLT) as well as age- and sex-matched ground control mice similarly housed in animal enclosure modules (AEM).

Use of a microgravity organ culture dish system to demonstrate the signal dampening effects of modeled microgravity during T cell development.

Recently, we have shown that exposure of fetal thymus organ cultures (FTOC) to modeled microgravity (MMG) using a clinostat with a microgravity organ culture dish system (MOCDS) blocks T cell development in a manner independent of steroid stress hormones present in vivo. In this study, we describe the development of the MOCDS system, as well as its use in attempting to understand the mechanism by which T cell development is inhibited in MMG. We show that after MMG exposure FTOC exhibited a significant reduction in CD4+CD8+ double positive (DP) cell production, but those DP cells which remained expressed higher levels of the T cell receptor (TCR) associated molecule, CD3.

Loss of T cell precursors after spaceflight and exposure to vector-averaged gravity.

Using fetal thymus organ culture (FTOC), we examined the effects of spaceflight and vector-averaged gravity on T cell development. Under both conditions, the development of T cells was significantly attenuated. Exposure to spaceflight for 16 days resulted in a loss of precursors for CD4+, CD8+, and CD4+CD8+ T cells in a rat/mouse xenogeneic co-culture.

Neuronal responses to vector-averaged gravity: a search for gravisensing and adaptation mechanisms--a preliminary report.

This paper serves as a milepost in our work using the clinostat as a tool for mimicking certain aspects of altered gravity conditions (vector-nulled gravity) in order to gain insights into the adaptation of cells (and hence organisms) to the microgravity environment of space. I review here recent data, limited to cellular adaptation to altered gravity environments, from others in the field, and including some of our work using the clinostat and from spaceflight experiments. Finally, I report here preliminary results of experiments, carried out initially at Nagoya University's RIEM with follow-up experiments at the University of Arizona, to test the applicability of PC12 cells as neuronal models in which to assess adaptation to altered gravity conditions.

TNF-alpha-dependent activation of NF-kappa B in human osteoblastic HOS-TE85 cells is repressed in vector-averaged gravity using clinostat rotation.

Effects of vector-averaged gravity on tumor necrosis factor (TNF)-alpha-dependent activation of nuclear factor kappa B (NF-kappa B) in human osteoblastic HOS-TE85 cells were investigated by culturing the cells using clinostat rotation (clinorotation). Cell cultures were rotated for 72 h at 40 rpm in a clinostat. At the end of clinorotation, the cells were treated with TNF-alpha for 30 min under stationary conditions.

Culture in vector-averaged gravity under clinostat rotation results in apoptosis of osteoblastic ROS 17/2.8 cells.

Space flight experiments and studies carried out in altered gravity environments have revealed that exposure to altered gravity conditions results in (mal)adaptation of cellular function. In the present study, we used a clinostat to generate a vector-averaged gravity environment. We then evaluated the responses of osteoblast-like ROS 17/2.

Dependence of nicotinic acetylcholine receptor recovery from desensitization on the duration of agonist exposure.

When subjected to prolonged exposure to nicotinic agonists, nicotinic acetylcholine receptors undergo desensitization, resulting in an inactive receptor that does not allow for the passage of ions. The induction of desensitization of diverse nicotinic acetylcholine receptor subtypes in muscle, ganglia, or brain is likely to play important modulatory roles in synaptic transmission. Furthermore, nicotinic receptor desensitization may contribute to behavioral changes in humans or animals subjected to prolonged nicotine exposure pharmacologically or through the use of tobacco products.

Lipid-ion channel interactions: increasing phospholipid headgroup size but not ordering acyl chains alters reconstituted channel behavior.

We have recently shown (Chang et al., 1995) that lipid-channel interactions, exemplified by the effects of cholesterol on the calcium-activated potassium (BK) channel, profoundly affect channel properties. The present study further explores such interactions by monitoring changes in BK channel behavior after reconstitution into bilayers where the size of phospholipid (PL) headgroups is increased and where the freedom of motion (inverse order) of fatty acid chains is incremented.

Attenuation of channel kinetics and conductance by cholesterol: an interpretation using structural stress as a unifying concept.

The ubiquity of cholesterol in cell membranes and changes in its concentration during development, aging and in various diseases suggest that it plays an important role in modulating cell function. We examined this possibility by monitoring the effects of cholesterol on the activity of the calcium-activated potassium (BK) channel reconstituted into lipid bilayers from rat brain homogenates. Increasing the cholesterol concentration to 11% of total lipid weight resulted in a 70% reduction in channel mean open time and a reduction of the open probability of the channel by 80%.