STIP overexpression confers oncogenic potential to human non-small cell lung cancer cells by regulating cell cycle and apoptosis

Drosophila septin interacting protein 1 regulates neurogenesis in the early developing larval brain

Neurogenesis in the Drosophila central brain progresses dynamically in order to generate appropriate numbers of neurons during different stages of development. Thus, a central challenge in neurobiology is to reveal the molecular and genetic mechanisms of neurogenesis timing. Here, we found that neurogenesis is significantly impaired when a novel mutation, Nuwa, is induced at early but not late larval stages. Intriguingly, when the Nuwa mutation is induced in neuroblasts of olfactory projection neurons (PNs) at the embryonic stage, embryonic-born PNs are generated, but larval-born PNs of the same origin fail to be produced. Through molecular characterization and transgenic rescue experiments, we determined that Nuwa is a loss-of-function mutation in Drosophila septin interacting protein 1 (sip1). Furthermore, we found that SIP1 expression is enriched in neuroblasts, and RNAi knockdown of sip1 using a neuroblast driver results in formation of small and aberrant brains. Finally, full-length SIP1 protein and truncated SIP1 proteins lacking either the N- or C-terminus display different subcellular localization patterns, and only full-length SIP1 can rescue the Nuwa-associated neurogenesis defect. Taken together, these results suggest that SIP1 acts as a crucial factor for specific neurogenesis programs in the early developing larval brain.

Xiaoai Jiedu Recipe Inhibits Proliferation and Metastasis of Non-Small Cell Lung Cancer Cells by Blocking the P38 Mitogen-Activated Protein Kinase (MAPK) Pathway

BACKGROUND Lung cancer is the leading cause of cancer deaths in the world. Its major histopathological subtype is non-small cell lung cancer (NSCLC). Xiaoai Jiedu recipe (XJR) is a traditional Chinese medicine formula that can suppress growth and invasion of tumor cells. Here, we assessed the antitumor effect of XJR on NSCLC explored the underlying mechanisms. MATERIAL AND METHODS Three concentrations of XJR (low, middle, and high) were used to treat A549 cells. Cell Counting Kit-8 and colony formation assay were used to measure proliferation of A549 cells. Apoptosis was evaluated by Hoechst 33342 staining and flow cytometry. The expression of apoptosis-associated proteins was measured by Western blot analysis. Transwell and scratch wound healing assay were used to assess invasion and migration, respectively, of A549 cells. The expression of p38 MAPK pathway-associated proteins were measured using Western blot analysis. RESULTS XJR suppressed proliferation and promoted apoptosis of A549 cells, especially in the high-dose group. The expression of Bcl-2 was reduced with increasing expression of Bax, cleaved caspase-3, and cleaved caspase-9. Invasion and migration abilities of A549 cells were inhibited after XJR treatment. XJR treatment decreased the expression levels of phosphorylated p38 (p-p38), p-ERK, and p-JNK in a dose-dependent manner. CONCLUSIONS The results demonstrated that XJR can inhibit proliferation, invasion, and migration, and induce apoptosis of NSCLC by blocking the p38 MAPK pathway, which shows the potential of XJR as a new treatment of NSCLC.

A graph-embedded deep feedforward network for disease outcome classification and feature selection using gene expression data

Motivation

Gene expression data represents a unique challenge in predictive model building, because of the small number of samples (n) compared with the huge amount of features (p). This 'n≪p' property has hampered application of deep learning techniques for disease outcome classification. Sparse learning by incorporating external gene network information could be a potential solution to this issue. Still, the problem is very challenging because (i) there are tens of thousands of features and only hundreds of training samples, (ii) the scale-free structure of the gene network is unfriendly to the setup of convolutional neural networks.

Results

To address these issues and build a robust classification model, we propose the Graph-Embedded Deep Feedforward Networks (GEDFN), to integrate external relational information of features into the deep neural network architecture. The method is able to achieve sparse connection between network layers to prevent overfitting. To validate the method's capability, we conducted both simulation experiments and real data analysis using a breast invasive carcinoma RNA-seq dataset and a kidney renal clear cell carcinoma RNA-seq dataset from The Cancer Genome Atlas. The resulting high classification accuracy and easily interpretable feature selection results suggest the method is a useful addition to the current graph-guided classification models and feature selection procedures.

Availability and implementation

The method is available at https://github.com/yunchuankong/GEDFN.

Supplementary information

Supplementary data are available at Bioinformatics online.

A meta-analysis of transcriptome datasets characterizes malignant transformation from melanocytes and nevi to melanoma

Melanoma represents one of the most aggressive malignancies and has a high tendency to metastasize. The present study aims to investigate the molecular mechanisms of two pathways to cancer transformation with the purpose of identifying potential biomarkers. Our approach is based on a meta-analysis of gene expression profiling contrasting two scenarios: A model that describes a transformation pathway from melanocyte to melanoma and a second model where transformation occurs through an intermediary nevus. Data consists of three independent, publicly available microarray datasets from the Gene Expression Omnibus (GEO) database comprising samples from melanocytes, nevi and melanoma. The present analysis identified 808 differentially expressed genes (528 upregulated and 360 downregulated) in melanoma compared with nevi, and 2,331 differentially expressed genes (946 upregulated and 1,385 downregulated) in melanoma compared with melanocytes. Further analysis narrowed down this list, since 682 differentially expressed genes were found in both models (417 upregulated and 265 downregulated). Enrichment analysis identified relevant dysregulated pathways. This article also presented a discussion on significant genes including ADAM like decysin 1, neudesin neurotrophic factor, MMP19, apolipoprotein L6, C-X-C motif chemokine ligand (CXCL)8, basic, immunoglobulin-like variable motif containing and CXCL16. These are of particular interest because they encode secreted proteins hence represent potential blood biomarkers for the early detection of malignant transformation in both scenarios. Cytotoxic T-lymphocyte associated protein 4, an important therapeutic target in melanoma treatment, was also upregulated in both comparisons indicating a potential involvement in immune tolerance, not only at advanced stages but also during the early transformation to melanoma. The results of the present study may provide a research direction for studying the mechanisms underlying the development of melanoma, depending on its origin.

13-Methyl-palmatrubine induces apoptosis and cell cycle arrest in A549 cells in vitro and in vivo

Corydalis yanhusuo, a well-known herbaceous plant, is commonly used in the treatment of inflammation, injury and pain. One natural agent isolated from Corydalis yanhusuo, 13-methyl-palmatrubine, was found to have a cytotoxic effect on cancer cells as reported in published studies. In the present study, we synthesized a potential anti-lung tumor agent, 13-methyl-palmatrubine and analyzed its activity. 13-Methyl-palmatrubine exhibited a cytotoxic effect on a panel of cancer cell lines in a time- and concentration-dependent manner. Among all the tested cancer cell lines, lung cancer A549 cells were most sensitive to 13-methyl-palmatrubine treatment. Meanwhile 13-methyl-palmatrubine showed less cytotoxicity in human normal cells. Our investigation revealed that 13-methyl-palmatrubine induced apoptosis and cell cycle arrest in A549 cells in a dose-dependent manner. Furthermore, 13-methyl-palmatrubine treatment caused activation of P38 and JNK pathways and blocked the EGFR pathway. In conclusion, our findings demonstrated that 13-methyl-palmatrubine inhibited the growth of A549 cells mediated by blocking of the EGFR signaling pathway and activation of the MAPK signaling pathway and provides a better understanding of the molecular mechanisms of 13-methyl-palmatrubine.

Design, synthesis and biological evaluation of rhein derivatives as anticancer agents

A series of novel derivatives of rhein were synthesized and evaluated for their in vitro antiproliferative activity against six kinds of tumor cell lines. All derivatives displayed more potent anti-tumor activity than rhein, and most of them were even stronger than 5-FU. Compound 4v was the most promising candidate among the investigated compounds.