Contemporary chemotherapeutic treatments incorporate the use of several agents in combination. However, selecting the most appropriate drugs for such therapy is not necessarily an easy or straightforward task. Here, we describe a targeted approach that can facilitate the reliable selection of chemotherapeutic drug combinations through the interrogation of drug-resistance gene networks. Our method employed single-cell eukaryote fission yeast (Schizosaccharomyces pombe) as a model of proliferating cells to delineate a drug resistance gene network using a synthetic lethality workflow. Using the results of a previous unbiased screen, we assessed the genetic overlap of doxorubicin with six other drugs harboring varied mechanisms of action. Using this fission yeast model, drug-specific ontological sub-classifications were identified through the computation of relative hypersensitivities. We found that human gastric adenocarcinoma cells can be sensitized to doxorubicin by concomitant treatment with cisplatin, an intra-DNA strand crosslinking agent, and suberoylanilide hydroxamic acid, a histone deacetylase inhibitor. Our findings point to the utility of fission yeast as a model and the differential targeting of a conserved gene interaction network when screening for successful chemotherapeutic drug combinations for human cells.

Total vitamin D levels had been commonly reported to be lowered in patients with chronic psychotic illnesses in countries from the higher latitudes. However, studies on patients with first episode psychosis (FEP) are limited. In this study we investigated serum concentrations of total and bioavailable vitamin D levels in FEP patients compared to healthy controls and the association between symptom severity and vitamin D components. A total of 31 FEP patients and 31 healthy controls were recruited from Institute of Mental Health, Singapore. FEP patients were identified using Structured Clinical Interview for DSM-IV Axis I disorders (SCID-1) and severity symptoms were assessed using the positive and negative syndrome scale (PANSS). Sera from participants were analyzed for total vitamin D, vitamin D-binding protein (DBP) and bioavailable vitamin D. Linear regressions were performed to examine the associations between serum total and bioavailable vitamin D and the PANSS subscales. Current study noted a significantly lower bioavailable vitamin D was in the FEP group and an association between bioavailable vitamin D and negative symptoms in FEP patients in a population with a consistent supply of sun exposure throughout the year.

The current study provides information on HP, A1T and A2M gene expression profiles in FEP patients and their associations with psychopathology. This provides support for the hypothesis that inflammation is related to schizophrenia and further encourages studies on immune-inflammatory markers to understand the relationship between inflammation and schizophrenia.

The ultra-high risk (UHR) state was originally conceived to identify individuals at imminent risk of developing psychosis. Although recent studies have suggested that most individuals designated UHR do not, they constitute a distinctive group, exhibiting cognitive and functional impairments alongside multiple psychiatric morbidities. UHR characterization using molecular markers may improve understanding, provide novel insight into pathophysiology, and perhaps improve psychosis prediction reliability. Whole-blood gene expressions from 56 UHR subjects and 28 healthy controls are checked for existence of a consistent gene expression profile (signature) underlying UHR, across a variety of normalization and heterogeneity-removal techniques, including simple log-conversion, quantile normalization, gene fuzzy scoring (GFS), and surrogate variable analysis. During functional analysis, consistent and reproducible identification of important genes depends largely on how data are normalized. Normalization techniques that address sample heterogeneity are superior. The best performer, the unsupervised GFS, produced a strong and concise 12-gene signature, enriched for psychosis-associated genes. Importantly, when applied on random subsets of data, classifiers built with GFS are “meaningful” in the sense that the classifier models built using genes selected after other forms of normalization do not outperform random ones, but GFS-derived classifiers do. Data normalization can present highly disparate interpretations on biological data. Comparative analysis has shown that GFS is efficient at preserving signals while eliminating noise. Using this, we demonstrate confidently that the UHR designation is well correlated with a distinct blood-based gene signature.