Performance Flexibility Architecture of Core Service Platform for Next-Generation Network

The hardware and software architectures of core service platforms for next-generation networks were analyzed to compute the minimum cost hardware configuration of a core service platform. This method gives a closed form expression for the optimized hardware cost configuration based on the service requirements, the processing features of the computers running the core service platform software, and the processing capabilities of the common object request broker architecture middleware. Three simulation scenarios were used to evaluate the model. The input includes the number of servers for the protocol mapping （PM）, Parlay gateway （PG）, application sever （AS）, and communication handling （CH） functions. The simulation results show that the mean delay meets requirements. When the number of servers for PM, PG, AS, and CH functions were not properly selected, the mean delay was excessive. Simulation results show that the model is valid and can be used to optimize investments in core service platforms.

Scope of machine learning applications for addressing the challenges in next-generation wireless networks

The convenience of availing quality services at affordable costs anytime and anywhere makes mobile technology very popular among users.Due to this popularity,there has been a huge rise in mobile data volume,applications,types of services,and number of customers.Furthermore,due to the COVID-19 pandemic,the worldwide lockdown has added fuel to this increase as most of our professional and commercial activities are being done online from home.This massive increase in demand for multi-class services has posed numerous challenges to wireless network frameworks.The services offered through wireless networks are required to support this huge volume of data and multiple types of traffic,such as real-time live streaming of videos,audios,text,images etc.,at a very high bit rate with a negligible delay in transmission and permissible vehicular speed of the customers.Next-generation wireless networks(NGWNs,i.e.5G networks and beyond)are being developed to accommodate the service qualities mentioned above and many more.However,achieving all the desired service qualities to be incorporated into the design of the 5G network infrastructure imposes large challenges for designers and engineers.It requires the analysis of a huge volume of network data(structured and unstructured)received or collected from heterogeneous devices,applications,services,and customers and the effective and dynamic management of network parameters based on this analysis in real time.In the ever-increasing network heterogeneity and complexity,machine learning(ML)techniques may become an efficient tool for effectively managing these issues.In recent days,the progress of artificial intelligence and ML techniques has grown interest in their application in the networking domain.This study discusses current wireless network research,brief discussions on ML methods that can be effectively applied to the wireless networking domain,some tools available to support and customise efficient mobile system design,and some unresolved issues for future research directions.

Impact of next-generation sequencing on antimicrobial treatment in immunocompromised adults with suspected infections

BACKGROUND:Prompt pathogen identification can have a substantial impact on the optimization of antimicrobial treatment.The objective of the study was to assess the diagnostic value of next-generation sequencing(NGS)for identifying pathogen and its clinical impact on antimicrobial intervention in immunocompromised patients with suspected infections.METHODS:This was a retrospective study.Between January and August 2020,47 adult immunocompromised patients underwent NGS testing under the following clinical conditions:1)prolonged fever and negative conventional cultures;2)new-onset fever despite empiric antimicrobial treatment;and 3)afebrile with suspected infections on imaging.Clinical data,including conventional microbial test results and antimicrobial treatment before and after NGS,were collected.Data were analyzed according to documented changes in antimicrobial treatment(escalated,no change,or deescalated)after the NGS results.RESULTS:The median time from hospitalization to NGS sampling was 19 d.Clinically relevant pathogens were detected via NGS in 61.7% of patients(29/47),more than half of whom suffered from fungemia(n=17),resulting in an antimicrobial escalation in 53.2% of patients(25/47)and antimicrobial de-escalation in 0.2% of patients(1/47).Antimicrobial changes were mostly due to the identification of fastidious organisms such as Legionella,Pneumocystis jirovecii,and Candida.In the remaining three cases,NGS detected clinically relevant pathogens also detected by conventional cultures a few days later.The antimicrobial treatment was subsequently adjusted according to the susceptibility test results.Overall,NGS changed antimicrobial management in 55.3%(26/47)of patients,and conventional culture detected clinically relevant pathogens in 14.9% of the patients(7/47).CONCLUSION:With its rapid identification and high sensitivity,NGS could be a promising tool for identifying relevant pathogens and enabling rapid appropriate treatment in immunocompromised patients with suspected infections.

Diagnostic Value of Targeted Next-generation Sequencing in Pulmonary Mycobacterial Infections

Objective This study aimed to explore the diagnostic value of novel technique-targeted next-generation sequencing(tNGS)of bronchoalveolar lavage fluid(BALF)in pulmonary mycobacterial infections.Methods This retrospective study was conducted on patients who underwent bronchoscopy and tNGS,smear microscopy,and mycobacterial culture of BALF.Patients with positive Mycobacterium tuberculosis(MTB)culture or GeneXpert results were classified into the tuberculosis case group.Those diagnosed with nontuberculous mycobacteria(NTM)-pulmonary disease(NTM-PD)composed the case group of NTM-PD patients.The control group comprised patients without tuberculosis or NTM-PD.Sensitivity,specificity,and receiver operating characteristic(ROC)curves were used to evaluate the diagnostic performance.Results For tuberculosis patients with positive mycobacterial culture results,the areas under the ROC curves(AUCs)for tNGS,GeneXpert,and smear microscopy were 0.975(95%CI:0.935,1.000),0.925(95%CI:0.859,0.991),and 0.675(95%CI:0.563,0.787),respectively.For tuberculosis patients with positive GeneXpert results,the AUCs of tNGS,culture,and smear microscopy were 0.970(95%CI:0.931,1.000),0.850(95%CI:0.770,0.930),and 0.680(95%CI:0.579,0.781),respectively.For NTM-PD,the AUCs of tNGS,culture,and smear-positive but GeneXpert-negative results were 0.987(95%CI:0.967,1.000),0.750(95%CI:0.622,0.878),and 0.615(95%CI:0.479,0.752),respectively.The sensitivity and specificity of tNGS in NTM-PD patients were 100%and 97.5%,respectively.Conclusion tNGS demonstrated superior diagnostic efficacy in mycobacterial infection,indicating its potential for clinical application.

Bronchoalveolar lavage fluid metagenomic next-generation sequencing assay for identifying pathogens in lung cancer patients

Background:For patients with lung cancer,timely identification of new lung lesions as infectious or non-infectious,and accurate identification of pathogens is very important in improving OS of patients.As a new auxiliary examination,metagenomic next-generation sequencing(mNGS)is believed to be more accurate in diagnosing infectious diseases in patients without underlying diseases,compared with conventional microbial tests(CMTs).We designed this study tofind out whether mNGS has better performance in distinguishing infectious and non-infectious diseases in lung cancer patients using bronchoalveolar lavagefluid(BALF).Materials and Methods:This study was a real-world retrospective review based on electronic medical records of lung cancer patients with bronchoalveolar lavage(BAL)and BALF commercial mNGS testing as part of clinical care from 1 April 2019 through 30 April 2022 at The First Affiliated Hospital of Sun Yat-sen University.164 patients were included in this study.Patients were categorized into the pulmonary non-infectious disease(PNID)group(n=64)and the pulmonary infectious disease(PID)group(n=100)groups based onfinal diagnoses.Results:BALF mNGS increased the sensitivity rate by 60%compared to CMTs(81%vs.21%,p<0.05),whereas there was no significant difference in specificity(75%vs.98.4%,p>0.1).Among the patients with PID,bacteria were the most common cause of infection.Fungal infections occurred in 32%of patients,and Pneumocystis Yersini was most common.Patients with Tyrosine kinase inhibitors(TKIs)therapy possess longer overall survival(OS)than other anti-cancer agents,the difference between TKIs and immuno-checkpoint inhibitors(ICIs)was insignificant(median OS TKIs vs.ICIs vs.Anti-angiogenic vs.Chemo vs.Radiotherapy=76 vs.84 vs.61 vs.58 vs.60).Conclusions:our study indicates that BALF mNGS can add value by improving overall sensitivity in lung cancer patients with potential pulmonary infection,and was outstanding in identifying Pneumocystis infection.It could be able to help physicians adjust the follow-up treatment to avoid the abuse of antibiotics.

Brain abscess from oral microbiota approached by metagenomic next-generation sequencing: A case report and review of literature

BACKGROUND Brain abscess is a serious and potentially fatal disease caused primarily by microbial infection.Although progress has been made in the diagnosis and treatment of brain abscesses,the diagnostic timeliness of pathogens needs to be improved.CASE SUMMARY We report the case of a 54-year-old male with a brain abscess caused by oral bacteria.The patient recovered well after receiving a combination of metagenomic next-generation sequencing(mNGS)-assisted guided medication and surgery.CONCLUSION Therefore,mNGS may be widely applied to identify the pathogenic microor-ganisms of brain abscesses and guide precision medicine.

Metagenomic next-generation sequencing may assist diagnosis of osteomyelitis caused by Mycobacterium houstonense:A case report

BACKGROUND Mycobacterium houstonense(M.houstonense)belongs to the nontuberculous mycobacterium group.Infection caused by M.houstonense is prone to recurrence.CASE SUMMARY We present a patient who was diagnosed with osteomyelitis caused by M.houstonense and treated with a combination of cefoxitin,and amikacin combined with linezolid.CONCLUSION The emergence of metagenomic next-generation sequencing(NGS)has brought new hope for the diagnosis and treatment of listeria meningitis.NGS can analyze a large number of nucleic acid sequences in a short time and quickly determine the pathogen species in the sample.Compared with traditional cerebrospinal fluid culture,NGS can greatly shorten the diagnosis time and provide strong support for the timely treatment of patients.Regarding treatment,NGS can also play an important role.Rapid and accurate diagnosis can enable patients to start targeted treatment as soon as possible and improve the treatment effect.At the same time,by monitoring the changes in pathogen resistance,the treatment plan can be adjusted in time to avoid treatment failure.

Application of an Artificial Neural Network for a Direct Estimation of Atmospheric Instability from a Next-Generation Imager

Atmospheric instability information derived from satellites plays an important role in short-term weather forecasting, especially the forecasting of severe convective storms. For the next generation of weather satellites for Korea＇s multi-purpose geostationary satellite program, a new imaging instrument has been developed. Although this imaging instrument is not de- signed to perform full sounding missions and its capability is limited, its multi-spectral infrared channels provide information on vertical sounding. To take full advantage of the observation data from the much improved spatiotemporal resolution of the imager, the feasibility of an artificial neural network approach for the derivation of the atmospheric instability is investigated. The multi-layer perceptron model with a feed-forward and back-propagation training algorithm shows quite a sensitive re- sponse to the selection of the training dataset and model architecture. Through an extensive performance test with a carefully selected training dataset of 7197 independent profiles, the model architectures are selected to be 12, 5000, and 0.3 for the number of hidden nodes, number of epochs, and learning rate, respectively. The selected model gives a mean absolute error, RMSE, and correlation coefficient of 330 J kg-1, 420 J kg-1, and 0.9, respectively. The feasibility is further demonstrated via application of the model to real observation data from a similar instrument that has comparable observation channels with the planned imager.

Powering Next-Generation Broadband Networks: ZTE's World-First Flexible, Configurable Router

16 September 2013, Shenzhen--ZTE today unveiled the world＇s first flexible, reconfigurable terabit router that allows customers to build the highest-performance broadband networks. The terabit router supports the deployment of multiple line cards with processing capabilities of 10 Gbps to 1 Tbps. It also supports the deployment of modules that can scale throughput from 200 Gbps to 18 Tbps. For easy installation in a range of environments, the router interfaces are flexible and the component design is loose-coupled. This allows customers to customize networks to their needs and promotes adaptability, consistency, and continuity.

Diagnosis of Acute Q Fever in an Elderly Patient Using Metagenomic Next-Generation Sequencing:A Case Report

Query fever(Q fever)is a globally spread zoonotic disease caused by Coxiella burnetii,commonly found in natural foci but rarely seen in Hebei Province.The clinical manifestations of Q fever are diverse and nonspecific,which often leads to missed or incorrect diagnoses in clinical practice.This article reports a case of acute Q fever diagnosed in an elderly patient using metagenomic next-generation sequencing.

Application of virtual reality technology improves the functionality of brain networks in individuals experiencing pain

Medical procedures are inherently invasive and carry the risk of inducing pain to the mind and body.Recently,efforts have been made to alleviate the discomfort associated with invasive medical procedures through the use of virtual reality(VR)technology.VR has been demonstrated to be an effective treatment for pain associated with medical procedures,as well as for chronic pain conditions for which no effective treatment has been established.The precise mechanism by which the diversion from reality facilitated by VR contributes to the diminution of pain and anxiety has yet to be elucidated.However,the provision of positive images through VR-based visual stimulation may enhance the functionality of brain networks.The salience network is diminished,while the default mode network is enhanced.Additionally,the medial prefrontal cortex may establish a stronger connection with the default mode network,which could result in a reduction of pain and anxiety.Further research into the potential of VR technology to alleviate pain could lead to a reduction in the number of individuals who overdose on painkillers and contribute to positive change in the medical field.

Unlocking the future:Mitochondrial genes and neural networks in predicting ovarian cancer prognosis and immunotherapy response

BACKGROUND Mitochondrial genes are involved in tumor metabolism in ovarian cancer(OC)and affect immune cell infiltration and treatment responses.AIM To predict prognosis and immunotherapy response in patients diagnosed with OC using mitochondrial genes and neural networks.METHODS Prognosis,immunotherapy efficacy,and next-generation sequencing data of patients with OC were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus.Mitochondrial genes were sourced from the MitoCarta3.0 database.The discovery cohort for model construction was created from 70% of the patients,whereas the remaining 30% constituted the validation cohort.Using the expression of mitochondrial genes as the predictor variable and based on neural network algorithm,the overall survival time and immunotherapy efficacy(complete or partial response)of patients were predicted.RESULTS In total,375 patients with OC were included to construct the prognostic model,and 26 patients were included to construct the immune efficacy model.The average area under the receiver operating characteristic curve of the prognostic model was 0.7268[95% confidence interval(CI):0.7258-0.7278]in the discovery cohort and 0.6475(95%CI:0.6466-0.6484)in the validation cohort.The average area under the receiver operating characteristic curve of the immunotherapy efficacy model was 0.9444(95%CI:0.8333-1.0000)in the discovery cohort and 0.9167(95%CI:0.6667-1.0000)in the validation cohort.CONCLUSION The application of mitochondrial genes and neural networks has the potential to predict prognosis and immunotherapy response in patients with OC,providing valuable insights into personalized treatment strategies.

A novel strategy of smart manipulation by micro-scale oscillatory networks of the reactionary zones for enhanced extreme thrust control of the next-generation solid propulsion systems

The main aim of this research is to get a better knowledge and understanding of the micro-scale oscillatory networks behavior in the solid propellants reactionary zones. Fundamental understanding of the micro-and nano-scale combustion mechanisms is essential to the development and further improvement of the next-generation technologies for extreme control of the solid propellant thrust. Both experiments and theory confirm that the micro-and nano-scale oscillatory networks excitation in the solid propellants reactionary zones is a rather universal phenomenon. In accordance with our concept,the micro-and nano-scale structures form both the fractal and self-organized wave patterns in the solid propellants reactionary zones. Control by the shape, the sizes and spacial orientation of the wave patterns allows manipulate by the energy exchange and release in the reactionary zones. A novel strategy for enhanced extreme thrust control in solid propulsion systems are based on manipulation by selforganization of the micro-and nano-scale oscillatory networks and self-organized patterns formation in the reactionary zones with use of the system of acoustic waves and electro-magnetic fields, generated by special kind of ring-shaped electric discharges along with resonance laser radiation. Application of special kind of the ring-shaped electric discharges demands the minimum expenses of energy and opens prospects for almost inertia-free control by combustion processes. Nano-sized additives will enhance self-organizing and self-synchronization of the micro-and nano-scale oscillatory networks on the nanometer scale. Suggested novel strategy opens the door for completely new ways for enhanced extreme thrust control of the solid propulsion systems.

Adaptive Cell Zooming Strategy Toward Next-Generation Cellular Networks with Joint Transmission

The Internet subscribers are expected to increase up to 69.7%(6 billion)from 45.3%and 25 billion Internet-of-things connections by 2025.Thus,the ubiquitous availability of data-hungry smart multimedia devices urges research attention to reduce the energy consumption in the fifthgeneration cloud radio access network to meet the future traffic demand of high data rates.We propose a new cell zooming paradigm based on joint transmission(JT)coordinated multipoint to optimize user connection by controlling the cell coverage in the downlink communications with a hybrid power supply.The endeavoring cell zooming technique adjusts the coverage area in a given cluster based on five different JT schemes,which will help in reducing the overall power consumption with minimum inter-cell interference.We provide heuristic solutions to assess wireless network performances in terms of aggregate throughput,energy efficiency index(EEI),and energy consumption gain under a different scale of network settings.The suggested algorithm allows efficient allocation of resource block and increases energy and spectral efficiency over the conventional location-centric cell zooming mechanism.Extensive system-level simulations show that the proposed framework reduces energy consumption yielding up to 17.5%and increases EEI by 14%.Subsequently,a thorough comparison among different JT-based load shifting schemes is pledged for further validation of varying system bandwidths.

Resting-state brain network remodeling after different nerve reconstruction surgeries:a functional magnetic resonance imaging study in brachial plexus injury rats

Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network level have not been elucidated.This study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve transfer.Sprague–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper trunk.Resting-state brain functional magnetic resonance imaging was obtained 7 months after surgery.The independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the component.Alterations in intra-network resting-state functional connectivity were compared among the groups.Target muscle reinnervation was assessed by behavioral observation(elbow flexion)and electromyography.The results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural pathway.Nerve repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor representation.The thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve transfer.Brain areas related to cognition and emotion were enhanced after end-to-side nerve transfer.Our study revealed important brain networks related to different nerve reconstructions.These networks may be potential targets for enhancing motor recovery.

Intelligent Modulation Recognition of Communication Signal for Next-Generation 6G Networks

In recent years,the need for a fast,efficient and a reliable wireless network has increased dramatically.Numerous 5G networks have already been tested while a few are in the early stages of deployment.In noncooperative communication scenarios,the recognition of digital signal modulations assists people in identifying the communication targets and ensures an effective management over them.The recent advancements in both Machine Learning(ML)and Deep Learning(DL)models demand the development of effective modulation recognition models with self-learning capability.In this background,the current research article designs aDeep Learning enabled Intelligent Modulation Recognition of Communication Signal(DLIMR-CS)technique for next-generation networks.The aim of the proposed DLIMR-CS technique is to classify different kinds of digitally-modulated signals.In addition,the fractal feature extraction process is appliedwith the help of the Sevcik Fractal Dimension(SFD)approach.Then,the extracted features are fed into the Deep Variational Autoencoder(DVAE)model for the classification of the modulated signals.In order to improve the classification performance of the DVAE model,the Tunicate Swarm Algorithm(TSA)is used to finetune the hyperparameters involved in DVAE model.A wide range of simulations was conducted to establish the enhanced performance of the proposed DLIMR-CS model.The experimental outcomes confirmed the superior recognition rate of the DLIMR-CS model over recent state-of-the-art methods under different evaluation parameters.

Application of next-generation sequencing technology to precision medicine in cancer: joint consensus of the Tumor Biomarker Committee of the Chinese Society of Clinical Oncology

Next-generation sequencing(NGS) technology is capable of sequencing millions or billions of DNA molecules simultaneously.Therefore, it represents a promising tool for the analysis of molecular targets for the initial diagnosis of disease, monitoring of disease progression, and identifying the mechanism of drug resistance. On behalf of the Tumor Biomarker Committee of the Chinese Society of Clinical Oncology(CSCO) and the China Actionable Genome Consortium(CAGC), the present expert group hereby proposes advisory guidelines on clinical applications of NGS technology for the analysis of cancer driver genes for precision cancer therapy. This group comprises an assembly of laboratory cancer geneticists, clinical oncologists, bioinformaticians,pathologists, and other professionals. After multiple rounds of discussions and revisions, the expert group has reached a preliminary consensus on the need of NGS in clinical diagnosis, its regulation, and compliance standards in clinical sample collection. Moreover, it has prepared NGS criteria, the sequencing standard operation procedure(SOP), data analysis, report, and NGS platform certification and validation.

Effects of viral infection and microbial diversity on patients with sepsis:A retrospective study based on metagenomic next-generation sequencing

BACKGROUND: The study aims to investigate the performance of a metagenomic next-generationsequencing (NGS)-based diagnostic technique for the identifi cation of potential bacterial and viral infectionsand eff ects of concomitant viral infection on the survival rate of intensive care unit (ICU) sepsis patients.METHODS: A total of 74 ICU patients with sepsis who were admitted to our institution from February1, 2018 to June 30, 2019 were enrolled. Separate blood samples were collected from patients for bloodcultures and metagenomic NGS when the patients’ body temperature was higher than 38 °C. Patients’demographic data, including gender, age, ICU duration, ICU scores, and laboratory results, were recorded.The correlations between pathogen types and sepsis severity and survival rate were evaluated.RESULTS: NGS produced higher positive results (105 of 118;88.98%) than blood cultures(18 of 118;15.25%) over the whole study period. Concomitant viral infection correlated closelywith sepsis severity and had the negative effect on the survival of patients with sepsis. However,correlation analysis indicated that the bacterial variety did not correlate with the severity of sepsis.CONCLUSIONS: Concurrent viral load correlates closely with the severity of sepsis and thesurvival rate of the ICU sepsis patients. This suggests that prophylactic administration of antiviraldrugs combined with antibiotics may be benefi cial to ICU sepsis patients.

Genomic characterization of esophageal squamous cellcarcinoma:insights from next-generation sequencing

Two major types of cancer occur in the esophagus: squamous cell carcinoma, which is associated with chronic smoking and alcohol consumption, and adenocarcinoma, which typically arises in gastric reflux-associated Barrett's esophagus. Although there is increasing incidence of esophageal adenocarcinoma in Western counties, esophageal squamous cell carcinoma(ESCC) accounts for most esophageal malignancies in East Asia, including China and Japan. Technological advances allowing for massively parallel, high-throughput next-generation sequencing(NGS) of DNA have enabled comprehensive characterization of somatic mutations in large numbers of tumor samples. Recently, several studies were published in which whole exome or whole genome sequencing was performed in ESCC tumors and compared with matched normal DNA. Mutations were validated in several genes, including in TP53, CDKN2 A, FAT1, NOTCH1, PIK3 CA, KMT2 D and NFE2L2, which had been previously implicated in ESCC. Several new recurrent alterations have also been identified in ESCC. Combining the clinicopathological characteristics of patients with information obtained from NGS studies may lead to the development of effective diagnostic and therapeutic approaches for ESCC. As this research becomes more prominent, it is important that gastroenterologist become familiar with the various NGS technologies and the results generated using these methods. In the present study, we describe recent research approaches using NGS in ESCC.

An updated review of gastric cancer in the next-generation sequencing era:Insights from bench to bedside and vice versa

Gastric cancer(GC)is one of the most common malignancies and remains the second leading cause of cancer-related death worldwide.There is an increasing understanding of the roles that genetic and epigenetic alterations play in GCs.Recent studies using nextgeneration sequencing(NGS)have revealed a number of potential cancer-driving genes in GC.Whole-exome sequencing of GC has identified recurrent somatic mutations in the chromatin remodeling gene ARID1A and alterations in the cell adhesion gene FAT4,a member of the cadherin gene family.Mutations in chromatin remodeling genes(ARID1A,MLL3 and MLL)have been found in 47%of GCs.Whole-genome sequencing and whole-transcriptome sequencing analyses have also discovered novel alterations in GC.Recent studies of cancer epigenetics have revealed widespread alterations in genes involved in the epigenetic machinery,such as DNA methylation,histone modifications,nucleosome positioning,noncoding RNAs and microRNAs.Recent advances in molecular research on GC have resulted in the introduction of new diagnostic and therapeutic strategies into clinical settings.The antihuman epidermal growth receptor 2(HER2)antibody trastuzumab has led to an era of personalized therapy in GC.In addition,ramucirumab,a monoclonal antibody targeting vascular endothelial growth factor receptor(VEGFR)-2,is the first biological treatment that showed survival benefits as a single-agent therapy in patients with advanced GC who progressed after firstline chemotherapy.Using NGS to systematically identify gene alterations in GC is a promising approach with remarkable potential for investigating the pathogenesis of GC and identifying novel therapeutic targets,as well as useful biomarkers.In this review,we will summarize the recent advances in the understanding of the molecular pathogenesis of GC,focusing on the potential use of these genetic and epigenetic alterations as diagnostic biomarkers and novel therapeutic targets.