Helicobacter pylori-induced fibroblast-derived Serpin E1 promotes gastric cancer growth and peritoneal dissemination through p38 MAPK/VEGFA-mediated angiogenesis.

BACKGROUND: Fibroblasts, especially cancer-associated fibroblasts (CAFs), represent the predominant stromal cell population in the tumor microenvironment and have an important function in tumorigenesis by interacting with tumor cells. However, their interaction remains elusive in an inflammatory tumor microenvironment induced by Helicobacter pylori (H. pylori). METHODS: The expression of Serpin family E member 1 (Serpin E1) was measured in fibroblasts with or without H. pylori infection, and primary gastric cancer (GC) cells. Serpin E1 knockdown and overexpression fibroblasts were generated using Serpin E1 siRNA or lentivirus carrying Serpin E1. Co-culture models of fibroblasts and GC cells or human umbilical vein endothelial cells (HUVECs) were established with direct contact or the Transwell system. In vitro functional experiments and in vivo tumorigenesis assay were employed to study the malignant behaviors of GC cells interacting with fibroblasts. ELISA was used for quantifying the levels of Serpin E1 and VEGFA in the culture supernatant. The tube formation capacity of HUVECs was assessed using a tube formation assay. Recombinant human Serpin E1 (recSerpin E1), anti-Serpin E1 antibody, and a MAPK pathway inhibitor were utilized to treat HUVECs for elucidating the underlying molecular mechanisms. RESULTS: Serpin E1 was predominantly expressed in gastric CAFs. H. pylori infection significantly enhanced the expression and secretion of Serpin E1 by CAFs. Both fibroblast-derived Serpin E1 and recSerpin E1 enhanced the growth, invasion, and migration of GC cells, along with increased VEGFA expression and tube formation in HUVECs. Furthermore, the co-inoculation of GC cells and fibroblasts overexpressing Serpin E1 triggered the expression of Serpin E1 in cancer cells, which facilitated together xenograft tumor growth and peritoneal dissemination of GC cells in nude mice, with an increased expression of Ki67, Serpin E1, CD31 and/or VEGFA. These processes may be mediated by Serpin E1-induced migration and p38 MAPK/VEGFA-mediated angiogenesis of HUVECs. CONCLUSION: H. pylori infection induces Serpin E1 expression in fibroblasts, subsequently triggering its expression in GC cells through their interaction. Serpin E1 derived from these cells promotes the migration and p38 MAPK/VEGFA-mediated angiogenesis of HUVECs, thereby facilitating GC growth and peritoneal metastasis. Targeting Serpin E1 signaling is a potential therapy strategy for H. pylori-induced GC.

Photocatalytic Free Radical-Controlled Synthesis of High-Performance Single-Atom Catalysts.

Single-atom catalysts (SACs) have emerged as crucial players in catalysis research, prompting extensive investigation and application. The precise control of metal atom nucleation and growth has garnered significant attention. In this study, we present a straightforward approach for preparing SACs utilizing a photocatalytic radical control strategy. Notably, we demonstrate for the first time that radicals generated during the photochemical process effectively hinder the aggregation of individual atoms. By leveraging the cooperative anchoring of nitrogen atoms and crystal lattice oxygen on the support, we successfully stabilize the single atom. Our Pd1 /TiO2 catalysts exhibit remarkable catalytic activity and stability in the Suzuki-Miyaura cross-coupling reaction, which was 43 times higher than Pd/C. Furthermore, we successfully depose Pd atoms onto various substrates, including TiO2 , CeO2 , and WO3 . The photocatalytic radical control strategy can be extended to other single-atom catalysts, such as Ir, Pt, Rh, and Ru, underscoring its broad applicability.

Interplay of Helicobacter pylori, fibroblasts, and cancer cells induces fibroblast activation and serpin E1 expression by cancer cells to promote gastric tumorigenesis.

BACKGROUND: Helicobacter pylori (H. pylori) can disrupt the tight junctions between gastric epithelial cells and penetrate the intercellular spaces acting on epithelial cells, normal fibroblasts (NFs), and cancer-associated fibroblasts (CAFs), but their interaction in gastric cancer tumorigenesis and progression remains unclear. METHODS: Primary CAFs and NFs were isolated from paired gastric cancer tissues and adjacent normal tissues and identified by immunofluorescence staining and western blot analysis for FSP-1, α-SMA, FAP, and vimentin expression. RNA-sequencing was used to compare the transcriptomes between CAFs and NFs. The expressions of FAP, lumican, and α-SMA, human cytokine array, and Transwell assay were used to assess the transformation of NFs to CAFs. CCK-8 assay, colony formation, flow cytometry, Transwell assay, and nude mouse xenograft model were used to determine the effects of Serpin E1 on cell proliferation and metastasis in vitro and in vivo. Finally, Serpin E1 and/or FAP expression was measured in H. pylori-infected gerbil gastric mucosa and human gastric cancer tissues. RESULTS: Gastric CAFs are inflammatory CAFs with α-SMAlowFAPhighlumicanhigh. The interplay of H. pylori, fibroblasts, and cancer cells promotes the transition of NFs to CAFs by inducing cytokine release, especially Serpin E1. Long-term H. pylori infection and CAFs induce Serpin E1 expression in gerbil gastric tissues and human gastric cancer cells. Serpin E1 overexpression enhances the growth, migration, invasion of gastric cancer cells in vitro, and xenograft tumor growth in nude mice via inducing angiogenesis. Serpin E1 and FAP were highly expressed in cancer cells and CAFs of gastric cancer tissues, respectively, and a good correlation was observed between their expression. Higher Serpin E1 expression is negatively associated with the overall survival of patients with gastric cancer. CONCLUSIONS: The interplay of H. pylori, fibroblasts, and cancer cells induced Serpin E1 expression to promote the activation of NFs to CAFs and gastric carcinogenesis. Targeting Serpin E1 will provide a promising therapeutic strategy for gastric cancer by disrupting the interaction between H. pylori, CAFs, and gastric cancer cells.

H. pylori CagA activates the NLRP3 inflammasome to promote gastric cancer cell migration and invasion.

OBJECTIVE: The CagA (cytotoxin-related gene A, CagA) protein is an important factor for the pathogenicity of Helicobacter pylori (H. pylori). Although H. pylori has previously been shown to activate the NLRP3 inflammasome, it remains unclear what role CagA plays in this process. In the current study, we aimed to investigate the effect of CagA on NLRP3 activation and how it is linked to gastric cancer cell migration and invasion. METHODS: CagA positive H. pylori strain (Hp/CagA+) and CagA gene knockout mutant (Hp/ΔCagA) infected and the pcDNA3.1/CagA plasmid transfected gastric epithelial cell lines, respectively. The morphological alterations of cells under a microscope; the NLRP3 inflammasome-related markers: NLRP3, caspase-1, and ASC protein levels were detected by Western blot, IL-1ß and IL-18 levels were determined by ELISA; cell migration and invasion were determined by transwell assay; and the pyroptosis levels and intracellular ROS were determined by flow cytometry analysis. Then, pretreated with 5 mM NAC for 2 h and subsequently transfected with the pcDNA3.1/CagA plasmid for 48 h, the effects of NAC pretreatment on CagA-induced NLRP3 inflammasome-related markers expression and cell pyroptosis were examined, finally assessed the effect of CagA on migration and invasion in NLRP3-silenced cells. RESULTS: We found that Hp/CagA+ strain infection and pcDNA3.1/CagA vector transfection result in NLRP3 inflammasome activation, generation of intracellular ROS, and increased invasion and migration of gastric cancer cells. Moreover, we found that ROS inhibition via NAC effectively blocks NLRP3 activation and pyroptosis. Silencing of NLRP3 reduces the effects of CagA on gastric cancer cell migration and invasion. CONCLUSION: Our study shows that CagA can promote the invasion and migration of gastric cancer cells by activating NLRP3 inflammasome pathway. These findings provide novel insights into the mechanism of gastric cancer induction by H. pylori.

Adaptive Tracking of High-Maneuvering Targets Based on Multi-Feature Fusion Trajectory Clustering: LPI's Purpose.

Since the passive sensor has the property that it does not radiate signals, the use of passive sensors for target tracking is beneficial to improve the low probability of intercept (LPI) performance of the combat platform. However, for the high-maneuvering targets, its motion mode is unknown in advance, so the passive target tracking algorithm using a fixed motion model or interactive multi-model cannot match the actual motion mode of the maneuvering target. In order to solve the problem of low tracking accuracy caused by the unknown motion model of high-maneuvering targets, this paper firstly proposes a state transition matrix update-based extended Kalman filter (STMU-EKF) passive tracking algorithm. In this algorithm, the multi-feature fusion-based trajectory clustering is proposed to estimate the target state, and the state transition matrix is updated according to the estimated value of the motion model and the observation value of multi-station passive sensors. On this basis, considering that only using passive sensors for target tracking cannot often meet the requirements of high target tracking accuracy, this paper introduces active radar for indirect radiation and proposes a multi-sensor collaborative management model based on trajectory clustering. The model performs the optimal allocation of active radar and passive sensors by judging the accumulated errors of the eigenvalue of the error covariance matrix and makes the decision to update the state transition matrix according to the magnitude of the fluctuation parameter of the error difference between the prediction value and the observation value. The simulation results verify that the proposed multi-sensor collaborative target tracking algorithm can effectively improve the high-maneuvering target tracking accuracy to satisfy the radar's LPI performance.

Spatial Information-Theoretic Optimal LPI Radar Waveform Design.

In this paper, the design of low probability of intercept (LPI) radar waveforms considers not only the performance of passive interception systems (PISs), but also radar detection and resolution performance. Waveform design is an important considerations for the LPI ability of radar. Since information theory has a powerful performance-bound description ability from the perspective of information flow, LPI waveforms are designed in this paper within the constraints of the detection performance metrics of radar and PISs, both of which are measured by the Kullback-Leibler divergence, and the resolution performance metric, which is measured by joint entropy. The designed optimization model of LPI waveforms can be solved using the sequential quadratic programming (SQP) method. Simulation results verify that the designed LPI waveforms not only have satisfactory target-detecting and resolution performance, but also have a superior low interception performance against PISs.

Comprehensive analysis of Helicobacter pylori infection-associated diseases based on miRNA-mRNA interaction network.

Helicobacter pylori (H. pylori) infection remains a cause of significant morbidity and mortality worldwide. Comprehensive understanding of the pathogenic mechanism of H. pylori and its interaction with host will contribute to developing novel prophylactical and therapeutical strategies. Here, we first determined microRNA (miRNA) levels in H. pylori-infected patients with gastritis, duodenal ulcer, gastric cancer or mucosa-associated lymphoid tissue lymphoma using miRNA data sets. Thirty-four differentially expressed miRNAs were identified and functional enrichment analysis of those miRNA target genes revealed that H. pylori infection were strongly associated with pathway in cancer and regulation of mRNA synthesis. Using disease connectivity analysis of 28 hub genes, we found that H. pylori may increase the risk of many extragastric diseases (e.g. cardiovascular disease, hemic and lymphatic diseases and nervous system disease). Altogether, our integrated analysis provided a new method to predict pathogen-human disease connectivity based on miRNA-mRNA interaction network and indicated anti-H. pylori therapy as an effective means of human diseases prevention.

XB130, regulated by miR-203, miR-219, and miR-4782-3p, mediates the proliferation and metastasis of non-small-cell lung cancer cells.

XB130 is a novel adapter protein that behaves as a tumor promoter or suppressor mediating cell proliferation and metastasis in the development of different human tumors. Altered expression of XB130 has been verified in human non-small cell-lung cancer (NSCLC). However, the exact effect of XB130 on NSCLC is not well-understood. In this study, we investigated the biological function and posttranscriptional regulation of XB130 in NSCLC. First, the effects of XB130 silence on NSCLC cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) were examined. Then the targeting relationship between XB130 and miR-203, miR-219, or miR-4782-3p was demonstrated by dual-luciferase reporter assay. Finally, the effects of miR-203, miR-219, and miR-4782-3p on NSCLC cell function were studied, respectively. We found that XB130 silence significantly inhibited cell growth, migration and invasion, and reversed EMT. Furthermore, XB130 was posttranscriptionally regulated by miR-203, miR-219, and miR-4782-3p. Overexpression of miR-203, miR-219, or miR-4782-3p inhibited cell growth, migration and invasion, and reversed EMT, just like the role of XB130 in NSCLC cells, whereas the suppressive effects of microRNA (miRNA) overexpression were weakened by miRNA inhibitors or ectopic expression of XB130 in NSCLC cells. These data demonstrate that XB130 is posttranscriptionally regulated by miR-203, miR-219, and miR-4782-3p and mediates the proliferation and metastasis of NSCLC cells.

Joint Dwell Time and Bandwidth Optimization for Multi-Target Tracking in Radar Network Based on Low Probability of Intercept.

Radar network systems have been demonstrated to offer numerous advantages for target tracking. In this paper, a low probability of intercept (LPI)-based joint dwell time and bandwidth optimization strategy is proposed for multi-target tracking in a radar network. Since the Bayesian Cramer-Rao lower bound (BCRLB) provides a lower bound on parameter estimation, it can be utilized as the accuracy metric for target tracking. In this strategy, in order to improve the LPI performance of the radar network, the total dwell time consumption of the underlying system is minimized, while guaranteeing a predetermined tracking accuracy. There are two adaptable parameters in the optimization problem: one for dwell time, and the other for bandwidth allocation. Since the nonlinear programming-based genetic algorithm (NPGA) can solve the nonlinear problem well, we develop a method based upon NPGA to solve the resulting problem. The simulation results demonstrate that the proposed strategy has superiority over traditional algorithms, and can achieve a better LPI performance of this radar network.

Low Probability of Intercept-Based Radar Waveform Design for Spectral Coexistence of Distributed Multiple-Radar and Wireless Communication Systems in Clutter.

In this paper, the problem of low probability of intercept (LPI)-based radar waveform design for distributed multiple-radar system (DMRS) is studied, which consists of multiple radars coexisting with a wireless communication system in the same frequency band. The primary objective of the multiple-radar system is to minimize the total transmitted energy by optimizing the transmission waveform of each radar with the communication signals acting as interference to the radar system, while meeting a desired target detection/characterization performance. Firstly, signal-to-clutter-plus-noise ratio (SCNR) and mutual information (MI) are used as the practical metrics to evaluate target detection and characterization performance, respectively. Then, the SCNR- and MI-based optimal radar waveform optimization methods are formulated. The resulting waveform optimization problems are solved through the well-known bisection search technique. Simulation results demonstrate utilizing various examples and scenarios that the proposed radar waveform design schemes can evidently improve the LPI performance of DMRS without interfering with friendly communications.

Nash Bargaining Game-Theoretic Framework for Power Control in Distributed Multiple-Radar Architecture Underlying Wireless Communication System.

This paper presents a novel Nash bargaining solution (NBS)-based cooperative game-theoretic framework for power control in a distributed multiple-radar architecture underlying a wireless communication system. Our primary objective is to minimize the total power consumption of the distributed multiple-radar system (DMRS) with the protection of wireless communication user's transmission, while guaranteeing each radar's target detection requirement. A unified cooperative game-theoretic framework is proposed for the optimization problem, where interference power constraints (IPCs) are imposed to protect the communication user's transmission, and a minimum signal-to-interference-plus-noise ratio (SINR) requirement is employed to provide reliable target detection for each radar. The existence, uniqueness and fairness of the NBS to this cooperative game are proven. An iterative Nash bargaining power control algorithm with low computational complexity and fast convergence is developed and is shown to converge to a Pareto-optimal equilibrium for the cooperative game model. Numerical simulations and analyses are further presented to highlight the advantages and testify to the efficiency of our proposed cooperative game algorithm. It is demonstrated that the distributed algorithm is effective for power control and could protect the communication system with limited implementation overhead.

Optimal Power Allocation Strategy in a Joint Bistatic Radar and Communication System Based on Low Probability of Intercept.

In this paper, we investigate a low probability of intercept (LPI)-based optimal power allocation strategy for a joint bistatic radar and communication system, which is composed of a dedicated transmitter, a radar receiver, and a communication receiver. The joint system is capable of fulfilling the requirements of both radar and communications simultaneously. First, assuming that the signal-to-noise ratio (SNR) corresponding to the target surveillance path is much weaker than that corresponding to the line of sight path at radar receiver, the analytically closed-form expression for the probability of false alarm is calculated, whereas the closed-form expression for the probability of detection is not analytically tractable and is approximated due to the fact that the received signals are not zero-mean Gaussian under target presence hypothesis. Then, an LPI-based optimal power allocation strategy is presented to minimize the total transmission power for information signal and radar waveform, which is constrained by a specified information rate for the communication receiver and the desired probabilities of detection and false alarm for the radar receiver. The well-known bisection search method is employed to solve the resulting constrained optimization problem. Finally, numerical simulations are provided to reveal the effects of several system parameters on the power allocation results. It is also demonstrated that the LPI performance of the joint bistatic radar and communication system can be markedly improved by utilizing the proposed scheme.

Performance Analysis for Joint Target Parameter Estimation in UMTS-Based Passive Multistatic Radar with Antenna Arrays Using Modified Cramér-Rao Lower Bounds.

In this study, the modified Cramér-Rao lower bounds (MCRLBs) on the joint estimation of target position and velocity is investigated for a universal mobile telecommunication system (UMTS)-based passive multistatic radar system with antenna arrays. First, we analyze the log-likelihood redfunction of the received signal for a complex Gaussian extended target. Then, due to the non-deterministic transmitted data symbols, the analytically closed-form expressions of the MCRLBs on the Cartesian coordinates of target position and velocity are derived for a multistatic radar system with N t UMTS-based transmit station of L t antenna elements and N r receive stations of L r antenna elements. With the aid of numerical simulations, it is shown that increasing the number of receiving elements in each receive station can reduce the estimation errors. In addition, it is demonstrated that the MCRLB is not only a function of signal-to-noise ratio (SNR), the number of receiving antenna elements and the properties of the transmitted UMTS signals, but also a function of the relative geometric configuration between the target and the multistatic radar system.The analytical expressions for MCRLB will open up a new dimension for passive multistatic radar system by aiding the optimal placement of receive stations to improve the target parameter estimation performance.

A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network.

Radar networks are proven to have numerous advantages over traditional monostatic and bistatic radar. With recent developments, radar networks have become an attractive platform due to their low probability of intercept (LPI) performance for target tracking. In this paper, a joint sensor selection and power allocation algorithm for multiple-target tracking in a radar network based on LPI is proposed. It is found that this algorithm can minimize the total transmitted power of a radar network on the basis of a predetermined mutual information (MI) threshold between the target impulse response and the reflected signal. The MI is required by the radar network system to estimate target parameters, and it can be calculated predictively with the estimation of target state. The optimization problem of sensor selection and power allocation, which contains two variables, is non-convex and it can be solved by separating power allocation problem from sensor selection problem. To be specific, the optimization problem of power allocation can be solved by using the bisection method for each sensor selection scheme. Also, the optimization problem of sensor selection can be solved by a lower complexity algorithm based on the allocated powers. According to the simulation results, it can be found that the proposed algorithm can effectively reduce the total transmitted power of a radar network, which can be conducive to improving LPI performance.

Cramer-Rao Lower Bound Evaluation for Linear Frequency Modulation Based Active Radar Networks Operating in a Rice Fading Environment.

This paper investigates the joint target parameter (delay and Doppler) estimation performance of linear frequency modulation (LFM)-based radar networks in a Rice fading environment. The active radar networks are composed of multiple radar transmitters and multichannel receivers placed on moving platforms. First, the log-likelihood function of the received signal for a Rician target is derived, where the received signal scattered off the target comprises of dominant scatterer (DS) component and weak isotropic scatterers (WIS) components. Then, the analytically closed-form expressions of the Cramer-Rao lower bounds (CRLBs) on the Cartesian coordinates of target position and velocity are calculated, which can be adopted as a performance metric to access the target parameter estimation accuracy for LFM-based radar network systems in a Rice fading environment. It is found that the cumulative Fisher information matrix (FIM) is a linear combination of both DS component and WIS components, and it also demonstrates that the joint CRLB is a function of signal-to-noise ratio (SNR), target's radar cross section (RCS) and transmitted waveform parameters, as well as the relative geometry between the target and the radar network architectures. Finally, numerical results are provided to indicate that the joint target parameter estimation performance of active radar networks can be significantly improved with the exploitation of DS component.

[Establishment of Mongolian gerbil model of gastric cancer induced by Helicobacter pylori infection and its proteomics analysis].

OBJECTIVE: To establish an animal model of gastric cancer by long-term infection of Helicobacter pylori (H.pylori) and to elucidate the pathogenesis by proteomics analysis. METHODS: Fifty male Mongolian gerbils (4-5 week-old and weighted 60-100 g) were infected with H.pylori and the gastric tissues were obtained after the infection at 3, 6, 12 and 24 months. Histological changes were evaluated by H-E staining of the gastric tissue sections. Detection of H.pylori was performed by in-vitro culture of fresh gastric tissue samples, PCR amplification of H.pylori 16s rRNA and localization by silver staining. In addition, proteins extracted from gastric tissue samples were subjected to two-dimensional electrophoresis (2-DE) at various infection time points. Protein spots with increased quantity over the course of H.pylori infection were selected and analyzed by LC-MS/MS. Finally, differentially expressed proteins between human gastric cancer tissue samples and lymph nodes were analyzed by real-time RT-PCR. RESULTS: Colonization of H.pylori was observed in gastric tissue of gerbils as early as 3 months after H.pylori infection, and persisted till 24 months. Pathological examination of infected animals showed various histological changes including acute gastritis, atrophic gastritis, intestinal metaplasia and gastric carcinoma. Seventy-eight differentially expressed proteins were identified by proteomics analysis, among which 36 proteins were up-regulated and 42 were down-regulated. Analyzed by LC-MS/MS, ten proteins were identified, including lactate dehydrogenase, ATP synthase, fatty acid-binding protein, COX5B, peroxiredoxin-4, peroxide reductase, transgelin, succinyl-CoA ligase, keratin and protein disulfide-isomerase A2, among which transgelin, ATP synthase and lactate dehydrogenase were highly expressed in human gastric carcinoma and lymph nodes. CONCLUSIONS: H.pylori infection induces the expression of transgelin, ATP synthase and lactate dehydrogenase, implying possible roles in the pathogenesis of gastric diseases including cancer.

Helicobacter pylori CagA mediated mitophagy to attenuate the NLRP3 inflammasome activation and enhance the survival of infected cells.

Helicobacter pylori (H. pylori) is one of the most common bacterial infections in the world, and its key virulence component CagA is the leading cause of gastric cancer. Mitophagy is a form of selective autophagy that eliminates damaged mitochondria and is essential for some viruses and bacteria to evade the immune system. However, the mechanisms by which CagA mediates H. pylori-induced mitophagy and NLRP3 inflammasome activation remain elusive. In this study, we reported that H. pylori primarily uses its CagA to induce mitochondrial oxidative damage, mitochondrial dysfunction, dynamic imbalance, and to block autophagic flux. Inhibition of mitophagy led to an increase in NLRP3 inflammasome activation and apoptosis and a decrease in the viability of H. pylori-infected cells. Our findings suggested that H. pylori induces mitochondrial dysfunction and mitophagy primarily via CagA. It reduces NLRP3 inflammasome activation to evade host immune surveillance and increases the survival and viability of infected cells, potentially leading to gastric cancer initiation and development. Our findings provide new insights into the pathogenesis of H. pylori-induced gastric cancer, and inhibition of mitophagy may be one of the novel techniques for the prevention and treatment of this disease.

A prominent role of LncRNA H19 in H. pylori CagA induced DNA damage response and cell malignancy.

Helicobacter pylori (H. pylori), together with its CagA, has been implicated in causing DNA damage, cell cycle arrest, apoptosis, and the development of gastric cancer. Although lncRNA H19 is abundantly expressed in gastric cancer and functions as a pro-oncogene, it remains unclear whether lncRNA H19 contributes to the oncogenic process of H. pylori CagA. This study investigates the role of H19 in the DNA damage response and malignancy induced by H. pylori. It was observed that cells infected with CagA+ H. pylori strain (GZ7/cagA) showed significantly higher H19 expression, resulting in increased γH2A.X and p-ATM expression and decreased p53 and Rad51 expression. Faster cell migration and invasion was also observed, which was reversed by H19 knockdown in H. pylori. YWHAZ was identified as an H19 target protein, and its expression was increased in H19 knockdown cells. GZ7/cagA infection responded to the increased YWHAZ expression induced by H19 knockdown. In addition, H19 knockdown stimulated cells to enter the G2-phase and attenuated the effect of GZ7/cagA infection on the cellular S-phase barrier. The results suggest that H. pylori CagA can upregulate H19 expression, participate in the DNA damage response and promote cell migration and invasion, and possibly affect cell cycle arrest via regulation of YWHAZ.

The 3'­untranslated region of XB130 regulates its mRNA stability and translational efficiency in non­small cell lung cancer cells.

Silencing XB130 inhibits cell proliferation and epithelial-mesenchymal transition in non-small cell lung cancer (NSCLC), suggesting that downregulating XB130 expression may impede NSCLC progression. However, the molecular mechanism underlying the regulation of XB130 expression remains unclear. In the present study, the role of the 3'-untranslated region (3'-UTR) in the regulation of XB130 expression was investigated. Recombinant psiCHECK-2 vectors with wild-type, truncated, or mutant XB130 3'-UTR were constructed, and the effects of these insertions on reporter gene expression were examined using a dual-luciferase reporter assay and reverse transcription-quantitative PCR. Additionally, candidate proteins that regulated XB130 expression by binding to critical regions of the XB130 3'-UTR were screened for using an RNA pull-down assay, followed by mass spectrometry and western blotting. The results revealed that insertion of the entire XB130 3'-UTR (1,218 bp) enhanced reporter gene expression. Positive regulatory elements were primarily found in nucleotides 113-989 of the 3'-UTR, while negative regulatory elements were found in the 1-112 and 990-1,218 regions of the 3'-UTR. Deletion analyses identified nucleotides 113-230 and 503-660 of the 3'-UTR as two major fragments that likely promote XB130 expression by increasing mRNA stability and translation rate. Additionally, a U-rich element in the 970-1,053 region of the 3'-UTR was identified as a negative regulatory element that inhibited XB130 expression by suppressing translation. Furthermore, seven candidate proteins that potentially regulated XB130 expression by binding to the 113-230, 503-660, and 970-1,053 regions of the 3'-UTR were identified, shedding light on the regulatory mechanism of XB130 expression. Collectively, these results suggested that complex sequence integrations in the mRNA 3'-UTR variably affected XB130 expression in NSCLC cells.

Effects of Helicobacter pylori on the expression of the FTO gene and its biological role in gastric cancer.

Helicobacter pylori (Hp) is a primary risk factor for gastric cancer. The fat mass and obesity-associated (FTO) gene is associated with the development and progression of various cancer types such as glioma, leukemia, breast cancer and colorectal cancer. The aim of the present study was to investigate the effect of Hp infection on the expression of FTO and its roles in gastric cancer. It was found that the expression levels of both FTO mRNA and protein were significantly increased in Hp-infected human gastric mucosal epithelial cells and Mongolian gerbil gastric tissues. The expression of FTO in gastric cancer tissues was higher than that in para-cancer tissues. Data from The Cancer Genome Atlas demonstrated that FTO expression in gastric cancer tissues was significantly higher than that in normal tissues. Patient survival rate was significantly decreased in patients with high expression levels of FTO. It was also demonstrated that FTO expression was associated with several pathological parameters, such as tumor stage, metastasis stage and the American Joint Committee on Cancer stage. The FTO gene was positively correlated with 16,601 genes in gastric cancer and negatively correlated with 3,623 genes. Gene Ontology enrichment analysis demonstrated that FTO was significantly enriched in the regulation of gene expression and oxidative RNA demethylase activity, and it was associated with components such as the RNA N6-methyladenosine methyltransferase complex and nuclear speckle. In addition, knockdown of the FTO gene inhibited the migration and invasion of Hp-infected cells. In conclusion, the data suggests that Hp infection leads to upregulation of the FTO gene, which may be related to patient survival rate, tumor staging and other pathological parameters of patients with gastric cancer. It also suggests that FTO promotes proliferation and migration of gastric cancer cells, which may be involved in the pathogenesis of Hp-induced gastric cancer.