Smoking and Suicidal Behaviors in the National Comorbidity Survey-Replication

Controversy exists about the role of mental disorders in the consistently documented association between smoking and suicidal behavior. This controversy is addressed here with data from the nationally representative National Comorbidity Survey Replication (NCS-R). Assessments were made of 12-month smoking, suicidal behaviors (ideation, plans, attempts), and DSM-IV disorders (anxiety, mood, impulse-control, and substance use disorders). Statistically significant odds-ratios (2.9-3.1) were found between 12-month smoking and 12-month suicidal behaviors. However, the associations of smoking with the outcomes became insignificant with controls for DSM-IV mental disorders. Although clear adjudication among contending hypotheses about causal mechanisms cannot be made from the cross-sectional NCS-R data, the results make it clear that future research on smoking and suicidal behaviors should focus more centrally than previous research on mental disorders either as common causes, markers, or mediators

Causal Network Models for Predicting Compound Targets and Driving Pathways in Cancer

Gene expression data is often used to infer pathways regulating transcriptional responses. For example, differentially expressed genes (DEGs) induced by compound treatment can help characterize hits from phenotypic screens, either by correlation with known drug signatures or by pathway enrichment. However, pathway enrichment is typically computed with DEGs rather than ‘upstream’ nodes that are potentially causal of ‘downstream’ changes. Here we present graph-based models to predict causal targets using compound-microarray data. We test several approaches to traversing network topology for interactions of varying confidence levels. We found that larger, less-canonical networks outperformed linear canonical interactions. In addition, combining network topology scoring methods with a consensus minimum-rank score beat individual methods and could highly rank compound targets among all network nodes. Importantly, pathway enrichment using causal nodes rather than DEGs recovers relevant pathways more often. To extend our validation, we used integrated datasets from the The Cancer Genome Atlas to define driving pathways in triple-negative breast cancer. Critical pathways were uncovered, including EGFR/PI3K/AKT/MAPK growth pathway and ATR/p53/BRCA DNA damage pathway, as well as unexpected pathways, such as TGF/WNT cytoskeleton remodeling, TNFR/IAP apoptosis, and IL12-induced IFN-gamma production. Overall, our approach can bridge transcriptional profiles to compound targets and driving pathways in cancer

Smoking and Suicidal Behaviors in the National Comorbidity Survey-Replication

Controversy exists about the role of mental disorders in the consistently documented association between smoking and suicidal behavior. This controversy is addressed here with data from the nationally representative National Comorbidity Survey Replication (NCS-R). Assessments were made of 12-month smoking, suicidal behaviors (ideation, plans, attempts), and DSM-IV disorders (anxiety, mood, impulse-control, and substance use disorders). Statistically significant odds-ratios (2.9-3.1) were found between 12-month smoking and 12-month suicidal behaviors. However, the associations of smoking with the outcomes became insignificant with controls for DSM-IV mental disorders. Although clear adjudication among contending hypotheses about causal mechanisms cannot be made from the cross-sectional NCS-R data, the results make it clear that future research on smoking and suicidal behaviors should focus more centrally than previous research on mental disorders either as common causes, markers, or mediators.Psycholog

The multidimensional perturbation value: A single metric to measure similarity and activity of treatments in high-throughput multidimensional screens

Screens using high-throughput, information-rich technologies such as microarrays, high-content screening (HCS), and next-generation sequencing (NGS) have become increasingly widespread. Compared with single-readout assays, these methods produce a more comprehensive picture of the effects of screened treatments. However, interpreting such multidimensional readouts is challenging. Univariate statistics such as t-tests and Z-factors cannot easily be applied to multidimensional profiles, leaving no obvious way to answer common screening questions such as "Is treatment X active in this assay?" and "Is treatment X different from (or equivalent to) treatment Y?" We have developed a simple, straightforward metric, the multidimensional perturbation value (mp-value), which can be used to answer these questions. Here, we demonstrate application of the mp-value to three data sets: a multiplexed gene expression screen of compounds and genomic reagents, a microarray-based gene expression screen of compounds, and an HCS compound screen. In all data sets, active treatments were successfully identified using the mp-value, and simulations and follow-up analyses supported the mp-value's statistical and biological validity. We believe the mp-value represents a promising way to simplify the analysis of multidimensional data while taking full advantage of its richness. © 2012 Society for Laboratory Automation and Screening

Phosphoglycerate dehydrogenase is dispensable for breast tumor maintenance and growth

Cancer cells have the ability to use aerobic glycolysis to maintain cell growth and proliferation via the Warburg effect. Phosphoglycerate dehydrogenase (PHDGH) catalyzes the first step of the serine biosynthetic pathway, which is a metabolic gatekeeper both for macromolecular biosynthesis and serine-dependent DNA synthesis. PHGDH is amplified or overexpressed in a subset of breast cancer and melanoma, and critical for the viability of those cells. Here, we report that PHDGH is overexpressed in many ER-negative human breast cancer cell lines and PHGDH knockdown in these cells leads to a decrease in the levels of serine production and impairment of cancer cell proliferation. However, PHGDH knockdown does not affect tumor maintenance and growth in established xenograft tumor mouse models, suggesting that PHGDH-dependent cell growth is only observed in the in vitro context. Our finding indicates that PHGDH is dispensable for tumor maintenance and growth in vivo, which suggests that other mechanisms or pathways may bypass the function of PHGDH in human breast cancer cells

Targeting HSF1 sensitizes cancer cells to HSP90 inhibitor

The molecular chaperone heat shock protein 90 (HSP90) facilitates the appropriate folding of oncoprotein and is hence thought to be necessary for the survival of certain oncogene-driven cancer cells. This specific hypothesis is being tested in clinical trials involving a number of distinct LWM HSP90 inhibitors including NVP-AUY922 and NVP-HSP990. Signs of clinical activity have been observed, most notably in trastuzumab-refractory, HER2-positive breast cancer, in EGFR-driven lung adenocarcinoma and in ALK-driven lung cancer. Through a pooled RNA interference screen, we showed that heat shock factor 1 (HSF1) is the top sensitizer of HSP90 inhibitor and knockdown of HSF1 specifically enhanced cell death induced by the HSP90 inhibitor. A striking combinational effect was observed when HSF1 knockdown plus with HSP90 inhibitors treatment in a various cell lines and tumor mouse models. In particularly, HSF1 is highly expressed in hepatocellular carcinoma (HCC) patient samples and knockdown of HSF1 sensitizes HSP90 inhibitor in liver cancer model, which might be a new indication for the combinational treatment. To understand the mechanism of the combinational effect, we identified a novel HSF1-target gene DEDD2, which is also involved in attenuation of the activity of HSP90 inhibitors. Interestingly, high expression of DEDD2 is associated with poor prognosis of breast cancer. Thus, the transcriptional activities of HSF1 induced by HSP90 inhibitors suggest a feedback mechanism to attenuate the HSP90 inhibitor activity and targeting HSF1 may provide a new avenue to enhance HSP90 inhibitor efficacy in human cancer, such as HCC