Circular RNA circHIPK2 inhibits colon cancer cells through miR-373-3p/RGMA axis.

Circular RNAs (circRNAs) have been implicated in cancer development. However, their regulation, function, and underlying mechanisms of action remain unclear. We found that circHIPK2 was downregulated in colon cancer, and low expression levels of circHIPK2 were associated with high tumor grade and poor patient survival. The expression of circHIPK2 was observed to be regulated by the transcription factor HOXD10, which was downregulated in colon cancer. Consequently, low circHIPK2 expression promoted colon cancer cell proliferation, migration, and invasion in vitro and tumor growth and metastasis in vivo. Mechanistically, circHIPK2 sponges miR-373-3p to upregulate the expression of the tumor suppressor RGMA, leading to the activation of BMP/Smad signaling and, ultimately, the inhibition of colon cancer cells, indicating that circHIPK2 inhibits colon cancer cells through the miR-373-3p/RGMA/BMP pathway. These findings revealed a previously unknown regulation, function, and underlying mechanism of circHIPK2 in cancer cells. Hence, circHIPK2 may have a prognostic value and serve as a potential target for colon cancer treatment.

Enhanced Thermostability of Geobacillus stearothermophilus α-Amylase by Rational Design of Disulfide Bond and Application in Corn Starch Liquefaction and Bread Quality Improvement.

α-Amylase (EC 3.2.1.1) from Geobacillus stearothermophilus (generally recognized as safe) exhibited thermal inactivation, hampering its further application in starch-based industries. To address this, we performed structural analyses based on molecular dynamics targeting the flexible regions of α-amylase. Subsequently, we rationally designed a thermostable mutant, AmyS1, by introducing disulfide bonds to stabilize the flexible regions. AmyS1 showed excellent thermostability without any stability-activity trade-off, giving a 40-fold longer T1/2 (1359 min) at 90 °C. Thermostability mechanism analysis revealed that the introduction of disulfide bonds in AmyS1 refined weak spots and reconfigured the protein's force network. Moreover, AmyS1 exhibited improved pH compatibility and enhanced corn starch liquefaction at 100 °C with a 5.1-fold increased product concentration. Baking tests confirmed that AmyS1 enhanced bread quality and extended the shelf life. Therefore, mutant AmyS1 is a robust candidate for the starch-based industry.

Corrigendum: MicroRNA-608 Promotes Apoptosis in Non-Small Cell Lung Cancer Cells Treated With Doxorubicin Through the Inhibition of TFAP4.

[This corrects the article DOI: 10.3389/fgene.2019.00809.].

Development and Validation of an Individualized Nomogram for Predicting Overall Survival in Patients With Typical Lung Carcinoid Tumors.

OBJECTIVE: We aim to develop and validate an effective nomogram prognostic model for patients with typical lung carcinoid tumors using a large patient cohort from the Surveillance, Epidemiology, and End Results (SEER) database. MATERIALS AND METHODS: Data from patients with typical lung carcinoid tumors between 2010 and 2015 were selected from the SEER database for retrospective analysis. Univariate and multivariate Cox analysis was performed to clarify independent prognostic factors. Next, a nomogram was formulated to predict the probability of 3- and 5-year overall survival (OS). Concordance indexes (c-index), receiver operating characteristic analysis and calibration curves were used to evaluate the model. RESULTS: The selected patients were randomly divided into a training and a validation cohort. A nomogram was established based on the training cohort. Cox analysis results indicated that age, sex, T stage, N stage, surgery, and bone metastasis were independent variables for OS. All these factors, except surgery, were included in the nomogram model for predicting 3- and 5-year OS. The internally and externally validated c-indexes were 0.787 and 0.817, respectively. For the 3-year survival prediction, receiver operating characteristic analysis showed that the areas under the curve in the training and validation cohorts were 0.824 and 0.795, respectively. For the 5-year survival prediction, the area under the curve in the training and validation cohorts were 0.812 and 0.787, respectively. The calibration plots for probability of survival were in good agreement. CONCLUSION: The nomogram brings us closer to personalized medicine and the maximization of predictive accuracy in the prediction of OS in patients with typical lung carcinoid tumors.

Blood cell parameters as prognostic predictors of disease development for patients with advanced non-small cell lung cancer.

Although the prognostic value of the neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR) and lymphocyte/white blood cell ratio (LWR) has been described in advanced non-small cell lung cancer (NSCLC), the association between complete blood cell parameters prior to disease treatment and NSCLC have yet to be identified. The aim of the present study was to assess the complete blood cell parameters prior to disease treatment in patients with advanced NSCLC. A total of 268 patients with advanced NSCLC were enrolled in this study. Clinical and laboratory data of the patients were acquired through medical records. Receiver operating characteristic curve analysis was used to determine the optimal cut-off values of the neutrophil/white blood cell ratio (NWR), NLR, platelet/white blood cell ratio (PWR), PLR, monocyte/white blood cell ratio (MWR), monocyte/lymphocyte ratio (MLR) and LWR. Kaplan-Meier univariate and multivariate Cox regression analyses were used to evaluate the effect of complete blood parameters on progression-free survival (PFS) and overall survival (OS). The optimal cut-off values were identified as 0.67 for NWR, 2.85 for NLR, 37.23 for PWR, 166.56 for PLR, 0.074 for MWR, 0.31 for MLR and 0.24 for LWR. Univariate analysis revealed that sex (P=0.038), histological type (P<0.0001), NWR (P=0.026), NLR (P=0.044) and MLR (P=0.012) were all associated with PFS, whereas histological type (P=0.003), NWR (P=0.003), NLR (P=0.015), MLR (P=0.006) and LWR (P=0.043) were significantly associated with OS in patients with advanced NSCLC. Histological type (P=0.002) was an independent prognostic factor for PFS in patients with advanced NSCLC. Whereas histological type (P=0.005), NWR (P=0.005), NLR (P=0.014), MLR (P=0.006), and LWR (P=0.034) were independent prognostic factors for OS. Taken together, the present study identified high NWR, NLR and MLR, and low LWR as independent prognostic factors for poor OS in patients with NSCLC.

Identification of potential key genes and key pathways related to clear cell renal cell carcinoma through bioinformatics analysis.

Clear cell renal cell carcinoma (ccRCC) is a common malignancy of the genitourinary system and is associated with high mortality rates. However, the molecular mechanism of ccRCC pathogenesis is still unclear, which translates to few effective diagnostic and prognostic biomarkers. In this study, we conducted a bioinformatics analysis on three Gene Expression Omnibus datasets and identified 437 differentially expressed genes (DEGs) related to ccRCC development and prognosis, of which 311 and 126 genes are respectively down-regulated and up-regulated. The protein-protein interaction network of these DEGs consists of 395 nodes and 1872 interactions and 2 prominent modules. The Staphylococcus aureus infection and complement and coagulation cascades are significantly enriched in module 1 and are likely involved in ccRCC progression. Forty-two hub genes were screened, of which von Willebrand factor, TIMP metallopeptidase inhibitor 1, plasminogen, formimidoyltransferase cyclodeaminase, solute carrier family 34 member 1, hydroxyacid oxidase 2, alanine-glyoxylate aminotransferase 2, phosphoenolpyruvate carboxykinase 1, and 3-hydroxy-3-methylglutaryl-CoA synthase 2 are possibly related to the prognosis of ccRCC. The differential expression of all nine genes was confirmed by quantitative real-time polymerase chain reaction analysis of the ccRCC and normal renal tissues. These key genes are potential biomarkers for the diagnosis and prognosis of ccRCC and warrant further investigation.

Common and distinct features of potentially predictive biomarkers in small cell lung carcinoma and large cell neuroendocrine carcinoma of the lung by systematic and integrated analysis.

BACKGROUND: Large-cell neuroendocrine carcinoma of the lung (LCNEC) and small-cell lung carcinoma (SCLC) are neuroendocrine neoplasms. However, the underlying mechanisms of common and distinct genetic characteristics between LCNEC and SCLC are currently unclear. Herein, protein expression profiles and possible interactions with miRNAs were provided by integrated bioinformatics analysis, in order to explore core genes associated with tumorigenesis and prognosis in SCLC and LCNEC. METHODS: GSE1037 gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in LCNEC and SCLC, as compared with normal lung tissues, were selected using the GEO2R online analyzer and Venn diagram software. Gene ontology (GO) analysis was performed using Database for Annotation, Visualization and Integrated Discovery. The biological pathway analysis was performed using the FunRich database. Subsequently, a protein-protein interaction (PPI) network of DEGs was generated using Search Tool for the Retrieval of Interacting Genes and displayed via Cytoscape software. The PPI network was analyzed by the Molecular Complex Detection app from Cytoscape, and 16 upregulated hub genes were selected. The Oncomine database was used to detect expression patterns of hub genes for validation. Furthermore, the biological pathways of these 16 hub genes were re-analyzed, and potential interactions between these genes and miRNAs were explored via FunRich. RESULTS: A total of 384 DEGs were identified. A Venn diagram determined 88 common DEGs. The PPI network was constructed with 48 nodes and 221 protein pairs. Among them, 16 hub genes were extracted, 14 of which were upregulated in SCLC samples, as compared with normal lung specimens, and 10 were correlated with the cell cycle pathway. Furthermore, 57 target miRNAs for 8 hub genes were identified, among which 31 miRNAs were correlated with the progression of carcinoma, drug-resistance, radio-sensitivity, or autophagy in lung cancer. CONCLUSION: This study provided effective biomarkers and novel therapeutic targets for diagnosis and prognosis of SCLC and LCNEC.

MicroRNA-608 Promotes Apoptosis in Non-Small Cell Lung Cancer Cells Treated With Doxorubicin Through the Inhibition of TFAP4.

Lung cancer is the most commonly diagnosed type of cancer and the leading cause of cancer-associated death worldwide. MicroRNAs (miRNAs) are non-coding single-stranded RNA molecules of ∼20-25 nucleotides in length. Single nucleotide polymorphisms are a class of genetic variation in the human genome, which when present in miRNA genes are associated with the risk of developing cancer. This study aimed to identify whether the miRNA (miR)-608 polymorphism rs4919510 influenced the incidence of lung cancer, and to explore the underlying mechanisms of miR-608 in the pathogenesis of the disease. A total of 37 patients with non-small cell lung cancer (NSCLC) were selected to determine the expression levels of miR-608; 96 NSCLC patients and 136 cancer-free healthy controls were recruited to determine the incidence of miR-608 rs4919510 in lung cancer patients. Additionally, the impact of miR-608 on the expression of predicted target genes, cell migration, viability, proliferation, and apoptosis was also assessed. We found that the presence of miR-608 rs4919510 did not affect the susceptibility of patients to NSCLC or the maturation of miR-608. miR-608 expression levels were found to be downregulated in NSCLC tissues. Furthermore, overexpression of miR-608 promoted doxorubicin-induced apoptosis in NSCLC cell lines A549 and HCC4006 by inhibiting the expression of transcription factor activating enhancer-binding protein 4 (TFAP4), and high expression levels of TFAP4 were observed in NSCLC tissues. Therefore, our results may provide valuable insights for the chemotherapeutical treatment of NSCLC.

Role of long non-coding RNA in drug resistance in non-small cell lung cancer.

Lung cancer is the leading cause of cancer-associated death, and non-small cell lung cancer (NSCLC) accounts for 85% of all lung cancer cases. Many drugs have been used to treat NSCLC in order to improve patient prognosis. Platinum-based chemotherapy is the first-line treatment for locally advanced or metastatic patients. For patients with activating EGFR mutations, tyrosine kinase inhibitors are the best treatment choice. NSCLC initially exhibits an excellent response to treatment; however, acquired resistance has been observed in many patients, leading to ineffective treatment. Clinical resistance is an impediment in the treatment of patients with advanced NSCLC. Many sequencing technologies have shown that long non-coding RNA (lncRNA) is expressed differently between drug-resistant and drug-sensitive lung cancer cells. We review the literature on lncRNA in drug resistance of NSCLC. The aim of this review is to gain insight into the molecular mechanisms of drug resistance, mainly focusing on the role of lncRNA in NSCLC.

Evaluation on the Toxic Effects of NanoAg to Catalase.

Protein is the functional actor of life. Research on protein damage induced by nanomaterials may give insight into the toxicity mechanisms of nanoparticles. Studying nano silver over the impact of the structure and function of catalase (CAT) at the molecular level, is of great significance for a comprehensive evaluation of their toxic effects. The toxic effects of nanoAg on catalase were thoroughly investigated using steady state and time resolved fluorescence quenching measurements, ultraviolet-visible absorption spectroscopy, resonance light scattering spectroscopy (RLS), circular dichroism spectroscopy (CD) and transmission electron microscopy (TEM). NanoAg could decrease the amount of alpha-helix and increase the beta sheet structure, leading to loose the skeleton structure of catalase. The characteristic fluorescence of catalase was obviously quenched, which showed the exposal of internal hydrophobic amino acids enhanced, and its quenching type is dynamic quenching. The result of RLS and TEM showed that the distribution and size of nanoAg become more uniform and smaller after their interaction, resulting in a decrease of RLS intensity. NanoAg could make the activity of catalase rise. By changing the structure of catalase, nanoAg increases its enzymatic activity to a certain extent, breaking down its balance in vivo, thereby affecting the normal physiological activities. NanoAg has obvious toxic effects on catalase. This paper provided a new perspective and method for the toxic effects of nanoAg to biological macromolecules; provided basic data and reference gist for the hygienics and toxicology studies of nanoAg. It is conducive to the toxicity prevention and control work of nanoAg, promoting nano-technology applied to human production and living better.