HFD-exacerbated Metabolic Side Effects of Olanzapine Are Suppressed by ER Stress Inhibitor.

OBJECTIVE: Numerous schizophrenic patients are suffering from obesity primarily attributed to antipsychotic medication and poor dietary habits. This study investigated the progressive deterioration of olanzapine-induced metabolic disorders in the presence of a high-fat diet (HFD) and explored the involvement of endoplasmic reticulum (ER) stress. METHODS: Female Sprague-Dawley rats fed on a standard chow diet or HFD were treated with olanzapine (3 mg/kg/day) and the ER stress inhibitor 4-phenylbutyric acid (4-PBA, 1 and 0.5 g/kg/day) for 8 days. Changes in body weight, food intake, and plasma lipids were assessed. Hepatic fat accumulation was evaluated using oil red O staining. Western blotting and immunofluorescence assays were employed to examine the expression of ER stress markers, NOD-like receptor pyrin domain-containing protein 3 (NLRP3), and proopiomelanocortin (POMC) in the hypothalamus or liver. RESULTS: Compared to olanzapine alone, olanzapine+HFD induced greater weight gain, increased hyperlipidemia, and enhanced hepatic fat accumulation (P<0.05). Co-treatment with 4-PBA exhibited a dose-dependent inhibition of these effects (P<0.05). Further mechanistic investigations revealed that olanzapine alone activated ER stress, upregulated NLRP3 expression in the hypothalamus and liver, and downregulated hypothalamic POMC expression. The HFD exacerbated these effects by 50%-100%. Moreover, co-administration of 4-PBA dose-dependently attenuated the olanzapine+HFD-induced alterations in ER stress, NLRP3, and POMC expression in the hypothalamus and liver (P<0.05). CONCLUSION: HFD worsened olanzapine-induced weight gain and lipid metabolic disorders, possibly through ER stress-POMC and ER stress-NLRP3 signaling. ER stress inhibitors could be effective in preventing olanzapine+HFD-induced metabolic disorders.

Individualized pathway activity algorithm identifies oncogenic pathways in pan-cancer analysis.

BACKGROUND: Accumulative evidences have shown that dysregulation of biological pathways contributed to the initiation and progression of malignant tumours. Several methods for pathway activity measurement have been proposed, but they are restricted to making comparisons between groups or sensitive to experimental batch effects. METHODS: We introduced a novel method for individualized pathway activity measurement (IPAM) that is based on the ranking of gene expression levels in individual sample. Taking advantage of IPAM, we calculated the pathway activity of 318 pathways from KEGG database in the 10528 tumour/normal samples of 33 cancer types from TCGA to identify characteristic dysregulated pathways among different cancer types. FINDINGS: IPAM precisely quantified the level of activity of each pathway in pan-cancer analysis and exhibited better performance in cancer classification and prognosis prediction over five widely used tools. The average ROC-AUC of cancer diagnostic model using tumour-educated platelets (TEPs) reached 92.84%, suggesting the potential of our algorithm in early diagnosis of cancer. We identified several pathways significantly deregulated and associated with patient survival in a large fraction of cancer types, such as tyrosine metabolism, fatty acid degradation, cell cycle, p53 signalling pathway and DNA replication. We also confirmed the dominant role of metabolic pathways in cancer pathway dysregulation and identified the driving factors of specific pathway dysregulation, such as PPARA for branched-chain amino acid metabolism and NR1I2, NR1I3 for fatty acid metabolism. INTERPRETATION: Our study will provide novel clues for understanding the pathological mechanisms of cancer, ultimately paving the way for personalized medicine of cancer. FUNDING: A full list of funding can be found in the Acknowledgements section.

Integration of Multifocal Microlens Array on Silicon Microcantilever via Femtosecond-Laser-Assisted Etching Technology.

Micro-opto-electromechanical systems (MOEMSs) are a new class of integrated and miniaturized optical systems that have significant applications in modern optics. However, the integration of micro-optical elements with complex morphologies on existing micro-electromechanical systems is difficult. Herein, we propose a femtosecond-laser-assisted dry etching technology to realize the fabrication of silicon microlenses. The size of the microlens can be controlled by the femtosecond laser pulse energy and the number of pulses. To verify the applicability of this method, multifocal microlens arrays (focal lengths of 7-9 µm) were integrated into a silicon microcantilever using this method. The proposed technology would broaden the application scope of MOEMSs in three-dimensional imaging systems.

Multiomics dissection of molecular regulatory mechanisms underlying autoimmune-associated noncoding SNPs.

More than 90% of autoimmune-associated variants are located in noncoding regions, leading to challenges in deciphering the underlying causal roles of functional variants and genes and biological mechanisms. Therefore, to reduce the gap between traditional genetic findings and mechanistic understanding of disease etiologies and clinical drug development, it is important to translate systematically the regulatory mechanisms underlying noncoding variants. Here, we prioritized functional noncoding SNPs with regulatory gene targets associated with 19 autoimmune diseases by incorporating hundreds of immune cell-specific multiomics data. The prioritized SNPs are associated with transcription factor (TF) binding, histone modification, or chromatin accessibility, indicating their allele-specific regulatory roles. Their target genes are significantly enriched in immunologically related pathways and other known immunologically related functions. We found that 90.1% of target genes are regulated by distal SNPs involving several TFs (e.g., the DNA-binding protein CCCTC-binding factor [CTCF]), suggesting the importance of long-range chromatin interaction in autoimmune diseases. Moreover, we predicted potential drug targets for autoimmune diseases, including 2 genes (NFKB1 and SH2B3) with known drug indications on other diseases, highlighting their potential drug repurposing opportunities. Taken together, these findings may provide useful information for future experimental follow-up and drug applications on autoimmune diseases.

Modeling circRNA expression pattern with integrated sequence and epigenetic features demonstrates the potential involvement of H3K79me2 in circRNA expression.

MOTIVATION: CircRNAs are an abundant class of non-coding RNAs with widespread, cell-/tissue-specific patterns. Previous work suggested that epigenetic features might be related to circRNA expression. However, the contribution of epigenetic changes to circRNA expression has not been investigated systematically. Here, we built a machine learning framework named CIRCScan, to predict circRNA expression in various cell lines based on the sequence and epigenetic features. RESULTS: The predicted accuracy of the expression status models was high with area under the curve of receiver operating characteristic (ROC) values of 0.89-0.92 and the false-positive rates of 0.17-0.25. Predicted expressed circRNAs were further validated by RNA-seq data. The performance of expression-level prediction models was also good with normalized root-mean-square errors of 0.28-0.30 and Pearson's correlation coefficient r over 0.4 in all cell lines, along with Spearman's correlation coefficient ρ of 0.33-0.46. Noteworthy, H3K79me2 was highly ranked in modeling both circRNA expression status and levels across different cells. Further analysis in additional nine cell lines demonstrated a significant enrichment of H3K79me2 in circRNA flanking intron regions, supporting the potential involvement of H3K79me2 in circRNA expression regulation. AVAILABILITY AND IMPLEMENTATION: The CIRCScan assembler is freely available online for academic use at https://github.com/johnlcd/CIRCScan. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Untangling knots between autophagic targets and candidate drugs, in cancer therapy.

Autophagy is an evolutionarily conserved lysosomal mechanism implicated in a wide variety of pathological processes, such as cancer. Autophagy can be regulated by a limited number of autophagy-related genes (Atgs) such as oncogenic Bcl-2/Bcl-XL , mTORC1, Akt and PI3KCI, and tumour suppressive proteins PI3KCIII, Beclin-1, Bif-1, p53, DAPKs, PTEN and UVRAG, which play their crucial roles in regulating autophagy-related cancer. As autophagy has a dual role in cancer cells, with tumour-promoting and tumour-suppressing properties, it has become an attractive target for a series of emerging small molecule drugs. In this review, we reveal new discoveries of related small molecules or chemical compounds that can regulate autophagic pathways and lead to pro-death or pro-survival autophagy, in different types of cancer. We discuss the knots between autophagic targets and candidate drugs, in the hope of shedding new light on exploiting new anti-tumour small molecule drugs for future cancer therapy.