Overexpression of 14-3-3σ Modulates Cholangiocarcinoma Cell Survival by PI3K/Akt Signaling

Arnicolide C Suppresses Tumor Progression by Targeting 14-3-3θ in Breast Cancer

Background: Arnicolide C, which is isolated from Centipeda minima, has excellent antitumor effects. However, the potential impacts and related mechanisms of action of arnicolide C in breast cancer remain unknown. Methods: The viability of breast cancer cells was measured using MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay and colony formation assays. For analysis of apoptosis and the cell cycle, flow cytometry was used. A molecular docking approach was used to explore the possible targets of arnicolide C. Western blot analysis was used to detect changes in the expression of 14-3-3θ and proteins in related pathways after arnicolide C treatment in breast cancer cells. The anti-breast cancer effect of arnicolide C in vivo was evaluated by establishing cell-derived xenograft (CDX) and patient-derived xenograft (PDX) models. Results: Arnicolide C inhibited proliferation, increased apoptosis, and induced G1 arrest. In particular, molecular docking analysis indicated that arnicolide C binds to 14-3-3θ. Arnicolide C reduced 14-3-3θ expression and inhibited its downstream signaling pathways linked to cell proliferation. Similar results were obtained in the CDX and PDX models. Conclusion: Arnicolide C can have an anti-breast cancer effect both in vitro and in vivo and can induce cell cycle arrest and increase apoptosis in vitro. The molecular mechanism may be related to the effect of arnicolide C on the expression level of 14-3-3θ. However, the specific mechanism through which arnicolide C affects 14-3-3θ protein expression still needs to be determined.

Interactions between 14-3-3 Proteins and Actin Cytoskeleton and Its Regulation by microRNAs and Long Non-Coding RNAs in Cancer

14-3-3s are a family of structurally similar proteins that bind to phosphoserine or phosphothreonine residues, forming the central signaling hub that coordinates or integrates various cellular functions, thereby controlling many pathways important in cancer, cell motility, cell death, cytoskeletal remodeling, neuro-degenerative disorders and many more. Their targets are present in all cellular compartments, and when they bind to proteins they alter their subcellular localization, stability, and molecular interactions with other proteins. Changes in environmental conditions that result in altered homeostasis trigger the interaction between 14-3-3 and other proteins to retrieve or rescue homeostasis. In circumstances where these regulatory proteins are dysregulated, it leads to pathological conditions. Therefore, deeper understanding is needed on how 14-3-3 proteins bind, and how these proteins are regulated or modified. This will help to detect disease in early stages or design inhibitors to block certain pathways. Recently, more research has been devoted to identifying the role of MicroRNAs, and long non-coding RNAs, which play an important role in regulating gene expression. Although there are many reviews on the role of 14-3-3 proteins in cancer, they do not provide a holistic view of the changes in the cell, which is the focus of this review. The unique feature of the review is that it not only focuses on how the 14-3-3 subunits associate and dissociate with their binding and regulatory proteins, but also includes the role of micro-RNAs and long non-coding RNAs and how they regulate 14-3-3 isoforms. The highlight of the review is that it focuses on the role of 14-3-3, actin, actin binding proteins and Rho GTPases in cancer, and how this complex is important for cell migration and invasion. Finally, the reader is provided with super-resolution high-clarity images of each subunit of the 14-3-3 protein family, further depicting their distribution in HeLa cells to illustrate their interactions in a cancer cell.

Differential plasma proteomes of the patients with Opisthorchiasis viverrini and cholangiocarcinoma identify a polymeric immunoglobulin receptor as a potential biomarker

In Southeast Asian countries, nitrosamine compounds and the liver fluke Opisthorchis viverrini have long been identified as carcinogens for cholangiocarcinoma (CHCA). In order to effectively treat O. viverrini infections and prevent the development of CHCA, methods for disease detection are needed. This study aims to identify biomarkers for O. viverrini infection and CHCA. In the discovery phase, technical triplicates of five pooled plasma pools (10 plasma each) of healthy control subjects (noOVCCA), O. viverrini subjects (OV), and cholangiocarcinoma subjects (CCA), underwent solution-based digestion, with the label-free method, using a Thermo Scientific™ Q Exactive™ HF hybrid quadrupole-Orbitrap mass spectrometer and UltiMate 300 LC systems. The noOVCCA, OV, and CCA groups demonstrated different profiles and were clustered, as illustrated by PCA and heat map analysis. The STRING and reactome analysis showed that both OV and CCA groups up-regulated proteins targeting immune system-related proteins. Differential proteomic profiles, S100A9, and polymeric immunoglobulin receptor (PIGR) were specifically expressed in the CCA group. During the validation phase, another 50 plasma samples were validated via the PIGR sandwich ELISA. Using PIGR >1.559 ng/ml as a cut-off point, 78.00% sensitivity, 71.00% specificity, and AUC = 0.8216, were obtained. It is sufficient to differentially diagnose cholangiocarcinoma patients from healthy patients and those with Opisthorchiasis viverrini. Hence, in this study, PIGR was identified and validated as a potential biomarker for CHCA. Plasma PIGR is suggested for screening CHCA, especially in an endemic region of O. viverrini infection.

Quantitative Expression of SFN, lncRNA CCDC18-AS1, and lncRNA LINC01343 in Human Breast Cancer as the Regulator Biomarkers in a Novel ceRNA Network: Based on Bioinformatics and Experimental Analyses

Breast cancer (BC) is one of the leading cancers in the world, which has become an increasing serious problem. In this context, reports demonstrate that some long noncoding RNAs (lncRNAs) play significant regulatory roles in breast tumorigenesis and BC progression via various pathways and act as endogenous RNAs. Finding their dysregulation in cancer and evaluating their interaction with other molecules, such as short noncoding RNAs “microRNA (miRNAs)” as well as various genes, are the most important parts in cancer diagnostics. In this study, after performing GSEA and microarray analysis on the GSE71053 dataset, a new ceRNA network of CCDC18-AS1, LINC01343, hsa-miR4462, and SFN in BC was detected by bioinformatics analysis. Therefore, the expression of SFN, CCDC18-AS1, and LINC01343 was quantitatively measured in 24 BC and normal paired tissues using qRT-PCR. CCDC18-AS1, LINC01343, and SFN were expressed higher in BC than in the control (normal paired) tissues based on qRT-PCR data. Furthermore, a significant positive correlation was observed between CCDC18-AS1 and LINC01343 expression in the samples investigated in this study. The investigation of clinicopathological parameters showed that SFN was highly expressed in tumor size of <5 cm and in nonmenopausal ages, while CCDC18-AS1 and LINC01343 indicated a high expression in stages II-III and III of BC, respectively. The overall survival analysis displayed high and low survival in patients with high expression of SFN and CCDC18-AS1, respectively. The ROC curve analysis disclosed that SFN, CCDC18-AS1, and LINC01343 might be suggested as potential biological markers in BC patients. The high expression of CCDC18-AS1, LINC01343, and SFN in BC samples suggests their potential role in BC tumorigenesis and could be considered hallmarks for the diagnosis and prognosis of BC, although this will require further clinical investigations.

Construction and validation of a bronchoalveolar lavage cell-associated gene signature for prognosis prediction in idiopathic pulmonary fibrosis

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive interstitial lung disease. It is urgent to identify biomarkers to precisely predict mortality.

METHODS

Gene expression data of bronchoalveolar lavage (BAL) cells and clinical information were downloaded from the Gene Expression Omnibus database. We identified key modules associated with prognosis using weighted gene co-expression network analysis (WGCNA). Then we screened genes with the least absolute shrinkage and selection operator Cox regression. Finally, we constructed a prognostic gene signature using multivariate Cox regression. The risk model was evaluated using the time-dependent receiver operating characteristic (ROC) curve and the concordance index. Additionally, the risk model was validated using an external independent dataset.

RESULTS

Two key modules, strongly associated with inflammation and immune response, were identified by WGCNA. Four genes, including TLR2, CCR2, HTRA1, and SFN, were screened to construct the prognostic model. The patients with a high-risk score had a significantly worse prognosis than patients with a low-risk score. Time-dependent ROC analysis showed that the risk model had a moderate predictive performance for overall survival in the training and external validation datasets.

CONCLUSIONS

Our study provides new insights into the prognostic value of BAL cells in IPF and it may be helpful to assist clinicians in making treatment decisions for the personalized management of IPF.