The phosphoinositide 3-kinase (PI3-K)/Akt signaling pathway is important in the regulation of cell proliferation through its production of phosphatidylinositol 3,4,5-triphosphate (PIP3). Activation of this pathway is frequently observed in human cancers, including non-small cell lung carcinoma. The PI3-K/Akt pathway is negatively regulated by the dual-specificity phosphatase and tensin homolog (PTEN) protein. PTEN acts as a direct antagonist of PI3-K by dephosphorylating PIP3. Studies have shown that PTEN phosphatase activity is inhibited by PREX2, a guanine nucleotide exchanger factor (GEF). Multiple studies revealed that CELF2, an RNA binding protein, cooperates synergistically with PTEN as a tumor suppressor in multiple cancers. However, the underlying mechanism as to how CELF2 enhances PTEN activity remains unclear. Here, we report that CELF2 interacts with PREX2 and reduces the association of PREX2 with PTEN. Consistent with this observation, PTEN phosphatase activity is upregulated with CELF2 overexpression. In addition, overexpression of CELF2 represses both Akt phosphorylation and cell proliferation only in the presence of PTEN. In an ex vivo study, CELF2 gene delivery could significantly inhibit patient-derived xenografts (PDX) tumor growth. To further investigate the clinical relevance of this finding, we analyzed 87 paired clinical lung adenocarcinoma samples and the results showed that CELF2 protein expression is downregulated in tumor tissues and associated with poor prognosis. The CELF2 gene is located on the chromosome 10p arm, a region frequently lost in human cancers, including breast invasive carcinoma, low-grade glioma and glioblastoma. Analysis of TCGA datasets showed that CELF2 expression is also associated with shorter patient survival time in all these cancers. Overall, our work suggests that CELF2 plays a novel role in PI3-K signaling by antagonizing the oncogenic effect of PREX2.

Background Esophageal squamous cell carcinoma (ESCC) is an aggressive and lethal cancer with a low 5 year survival rate. Identification of new therapeutic targets and its inhibitors remain essential for ESCC prevention and treatment. Methods TYK2 protein levels were checked by immunohistochemistry. The function of TYK2 in cell proliferation was investigated by MTT [(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] and anchorage-independent cell growth. Computer docking, pull-down assay, surface plasmon resonance, and kinase assay were used to confirm the binding and inhibition of TYK2 by cirsiliol. Cell proliferation, western blot and patient-derived xenograft tumor model were used to determine the inhibitory effects and mechanism of cirsiliol in ESCC. Results TYK2 was overexpressed and served as an oncogene in ESCC. Cirsiliol could bind with TYK2 and inhibit its activity, thereby decreasing dimer formation and nucleus localization of signal transducer and activator of transcription 3 (STAT3). Cirsiliol could inhibit ESCC growth in vitro and in vivo. Conclusions TYK2 is a potential target in ESCC, and cirsiliol could inhibit ESCC by suppression of TYK2.

Hepatocellular carcinoma (HCC) is one of the primary hepatic malignancies and is the third most common cause of cancer related death worldwide. Although a wealth of knowledge has been gained concerning the initiation and progression of HCC over the last half century, efforts to improve our understanding of its pathogenesis at a molecular level are still greatly needed, to enable clinicians to enhance the standards of the current diagnosis and treatment of HCC. In the post‐genome era, advanced mass spectrometry driven multi‐omics technologies (e.g., profiling of DNA damage adducts, RNA modification profiling, proteomics, and metabolomics) stand at the interface between chemistry and biology, and have yielded valuable outcomes from the study of a diversity of complicated diseases. Particularly, these technologies are being broadly used to dissect various biological aspects of HCC with the purpose of biomarker discovery, interrogating pathogenesis as well as for therapeutic discovery. This proof of knowledge‐based critical review aims at exploring the selected applications of those defined omics technologies in the HCC niche with an emphasis on translational applications driven by advanced mass spectrometry, toward the specific clinical use for HCC patients. This approach will enable the biomedical community, through both basic research and the clinical sciences, to enhance the applicability of mass spectrometry‐based omics technologies in dissecting the pathogenesis of HCC and could lead to novel therapeutic discoveries for HCC. © 2014 Wiley Periodicals, Inc. Mass Spec Rev 35:331–349, 2016.

The high-pathogenicity island (HPI) is an important determinant of the pathogenicity of pathogenic Yersinia microbes. The HPI carries a cluster of virulence genes that chiefly account for the biosynthesis, transportation and regulation of a virulence-associated siderophore, yersiniabactin. This siderophore is also present in uropathogenic E. coli (UTI89) but not in non-uropathogenic E. coli. We sought to perform metabolic phenotyping and to understand how the presence of the HPI influences central carbon metabolism, which remains poorly understood, by combining targeted metabolomics with a genetic approach. Unexpectedly, our results revealed that uropathogenic E. coli (UPEC) with an HPI had superior metabolic homeostasis to a non-UPEC K12 strain without an HPI, thereby allowing UPEC with an HPI to flexibly adapt to a variety of growth environments. In this study, we elucidate the unrecognized regulatory effects of the HPI virulence genes on central carbon metabolism, in addition to their roles in directing yersiniabactin. These regulatory effects may be implicated in differentiating UPEC from non-UPEC.

Aristolochic acid (AA) is the major active component of medicinal plants from the Aristolochiaceae family of flowering plants widely utilized for medicinal purposes. However, the molecular mechanisms of AA systems effects remain poorly understood. Here, we employed a joint network analysis that combines network pharmacology, a protein–protein interaction (PPI) database, biological processes analysis and functional annotation analysis to explore system effects. Firstly, we selected 15 protein targets (14 genes) in the PubChem database as the potential target genes and used PPI knowledge to incorporate these genes into an AA-specific gene network that contains 129 genes. Secondly, we performed biological processes analysis for these AA-related targets using ClueGO, some of new targeted genes were randomly selected and experimentally verified by employing the Quantitative Real-Time PCR assay for targeting the systems effects of AA in HK-2 cells with observed dependency of concentration. Thirdly, the pathway-based functional enrichment analysis was manipulated using WebGestalt to identify the mostly significant pathways associated with AA. At last, we built an AA target pathway network of significant pathways to predict the system effects. Taken together, this joint network analysis revealed that the systematic regulatory effects of AA on multidimensional pathways involving both therapeutic action and toxicity.