Genomic analyses of cell-free DNA (cfDNA) in plasma are enabling noninvasive blood-based biomarker approaches to cancer detection and disease monitoring. Current approaches for identification of circulating tumour DNA typically use targeted tumour-specific mutations or methylation analyses. An emerging approach is based on the recognition of altered genome-wide cfDNA fragmentation in patients with cancer. Recent studies have revealed a multitude of characteristics that can affect the compendium of cfDNA fragments across the genome, collectively called the 'cfDNA fragmentome'. These changes result from genomic, epigenomic, transcriptomic and chromatin states of an individual and affect the size, position, coverage, mutation, structural and methylation characteristics of cfDNA. Identifying and monitoring these changes has the potential to improve early detection of cancer, especially using highly sensitive multi-feature machine learning approaches that would be amenable to broad use in populations at increased risk. This Review highlights the rapidly evolving field of genome-wide analyses of cfDNA characteristics, their comparison to existing cfDNA methods, and recent related innovations at the intersection of large-scale sequencing and artificial intelligence. As the breadth of clinical applications of cfDNA fragmentome methods have enormous public health implications for cancer screening and personalized approaches for clinical management of patients with cancer, we outline the challenges and opportunities ahead.

Stomach cancer continues to be a major public health concern in China, with its incidence, prevalence, mortality, and overall burden showing notable changes over time. This study set out to analyze the long-term trends of stomach cancer from 1990 to 2021, figure out the effects of aging, epidemiological changes, and population growth, and also make projections for the future. To conduct the study, data from the Global Burden of Disease Study 2021 was used. This data allowed for the analysis of various aspects such as age-standardized incidence, prevalence, mortality rates, disability-adjusted life years (DALYs), years lived with disability (YLDs), and years of life lost (YLLs) related to stomach cancer in China. Joinpoint regression analysis was carried out to spot significant trends and turning points. Decomposition analysis was done to assess how much aging, epidemiological changes, and population growth contributed. Additionally, the Bayesian age-period-cohort (BAPC) model was employed to predict what the trends might be from 2021 to 2030. In 2021, there were 611,799 new cases of stomach cancer in China. The age-standardized incidence rate was 29.05 per 100,000 people, with males having a much higher rate of 44.48 compared to females at 15.23. The age-standardized prevalence and mortality rates were 57.22 and 21.51 per 100,000 respectively, and both were higher in males as well. There were also significant gender differences in DALYs, YLDs, and YLLs, with males shouldering a greater burden. From 1990 to 2021, the incidence and mortality rates went down, especially after 2004. Through decomposition analysis, it was found that aging led to a decrease in incidence but an increase in mortality, especially among males. Epidemiological changes caused both the incidence and mortality rates to drop, and the effect was more pronounced in males. The BAPC model forecasts that the incidence and mortality rates will continue to decline for both genders from 2021 to 2030, with a more rapid decrease in males. Overall, this study emphasizes the changing trends of the stomach cancer burden in China, the significant gender differences, and the impacts of aging, epidemiological changes, and population growth. It's crucial to keep monitoring and implement targeted public health strategies to further reduce the burden of stomach cancer.

Gastric cancer (GC) has a high prevalence in Asian countries, and there is an unmet need for non-invasive and efficient GC screening methods. This study evaluated the diagnostic efficacy of GASTROClear, a panel of blood serum miRNAs for the detection of GC, in a Japanese population.

We conducted a pilot cohort study, comprising 103 patients with GC and 122 healthy controls. Serum samples were prospectively collected from study participants at two Japanese hospitals using a predefined blood-processing protocol. The diagnostic performance of GASTROClear was analyzed using a receiver operating characteristic curve and cutoff. By applying a logistic regression algorithm, we evaluated the diagnostic efficacy of novel combinations of GC diagnostic biomarker panels, consisting of GASTROClear and alternative serum markers (anti-Helicobacter pylori [Hp] antibody and pepsinogen).

Most patients had Stage I (58%) GC and were asymptomatic (59%). The area under the curve (AUC) value for the detection of GC using GASTROClear was 0.80, with 70.9% sensitivity and 75.2% specificity. GASTROClear performed equally well within the subgroups based on age, sex, symptoms, Hp status, and tumor characteristics. We improved the diagnostic performance of GASTROClear by combining it with an anti-Hp antibody and pepsinogen. This yielded an AUC value of 0.88, with the highest specificity (86.9%) at a fixed sensitivity (70.9%).

GASTROClear demonstrated competent diagnostic efficacy for GC in the detection of GC in our Japanese cohort, even in the early stages of cancer and asymptomatic cases. Its combination with existing serum markers may contribute to efficient risk stratification to detect GC.

The existing gastric cancer (GC) risk prediction models based on biomarkers are limited. This study aims to identify new promising biomarkers for GC to develop a risk prediction model for effective assessment, screening, and early diagnosis. This study was conducted utilizing a large combined cohort for upper gastrointestinal cancer that was established in Hebei Province, China. General macro risk factors, Helicobacter pylori (H.pylori) infection status, and protein biomarkers were collected through questionnaire surveys and laboratory tests. Novel GC biomarkers were explored using data-independent acquisition (DIA) proteomics and enzyme-linked immunosorbent assay (ELISA). Multiple machine learning algorithms were used to identify key predictors for the GC risk prediction model, which was validated with an independent external cohort from multiple hospitals. A total of 530 participants aged 40 to 74 were analyzed, with 104 ultimately diagnosed with GC. Significant biomarkers in GC patients were identified by DIA combined ELISA, including elevated Keratin 7 (KRT7) and Mammary fibrostatin (SERPINB5) (P<0.001) and decreased Dickkopf-associated protein 3 (DKK3) (P<0.001). Factors such as sex, age, smoking status, alcohol consumption, family history of GC, H. pylori infection, DKK3 and SERPINB5 were used to create a multidimensional risk prediction model for GC. This model achieved an area under the curve (AUC) of 0.938 (95% confidence interval: 0.913-0.962). The risk prediction model developed in this study shows high accuracy and practical utility, serving as an effective preliminary screening tool for identifying high-risk individuals for GC.

Gastric cancer (GC) is a prevalent malignancy affecting the digestive system. We aimed to develop a risk prediction model based on endoscopic atrophy classification for GC.

We retrospectively collected the data from January 2020 to October 2021 in our hospital and randomly divided the patients into training and validation sets in an 8:2 ratio. We used multiple machine learning algorithms such as logistic regression (LR), Decision tree, Support Vector Machine, Random forest, and so on to establish the models. We employed the Least absolute shrinkage and selection operator (LASSO) to screen variables for the LR model. However, we chose all the variables to construct the models for other machine learning algorithms. All models were evaluated using the receiver operating characteristic curve (ROC), predictive histograms, and decision curve analysis (DCA).

A total of 1156 patients were selected for the analysis. Five variables, including age, sex, family history of GC, HP infection status, and Kimura-Takemoto Classification (KTC), were screened using LASSO analysis. The area under the curve (AUC) of all the machine learning models ranged from 0.762 to 0.974 in the training set and from 0.608 to 0.812 in the validation set. Among them, the LR model exhibited the highest AUC value (0.812, 95%CI: 0.737-0.887) in the validation set with good calibration and clinical applicability. Finally, we constructed a nomogram to demonstrate the LR model.

We established a nomogram based on endoscopic atrophy classification for GC, which might be valuable in predicting GC risk and assisting clinical decision-making.

Although chronic atrophic gastritis (CAG), intestinal metaplasia (IM), and dysplasia constitute gastric pre-neoplastic conditions of gastric cancer (GC), data on endoscopic correlation and the prevalence in many South American countries are scarce. The aims of this study were to establish prevalence and perform endoscopic-histological correlation of gastric pre-neoplastic conditions using high-definition white light endoscopy (WLE) and to determine interobserver agreement for endoscopic findings for CAG and IM.

A prospective, observational, descriptive, cross-sectional study was carried out at a Uruguayan hospital during a 6-month period. Risk was stratified according to Operative Link for Gastritis Assessment and Operative Link for Gastric Intestinal Metaplasia stage for CAG and IM, respectively. An independent and blinded second observer was included to determine interobserver endoscopic and histologic agreement.

A total of 102 patients (mean age 57 years ± 1.6 years, 68.6% woman) were included. Prevalence of histological CAG and IM were 38.2% and IM 31.4%, respectively. Endoscopic-histological correlation for CAG had kappa index 0.063, sensitivity 46%, and specificity 60%. For endoscopic IM, the kappa index was 0.216, sensitivity 22%, and specificity 96%. Interobserver variability was good for gastric fold flattening and very good in the presence of whitish-greyish plaques for CAG and IM, respectively.

The endoscopic-histological correlation of both CAG and IM was low, raising the need for biopsy for diagnosis in all cases, regardless of HD-WLE findings. Although prevalence of gastric pre-neoplastic conditions in this group of Uruguayan patients was comparable to those described in countries with a high incidence of GC, a low proportion of high-risk stages (III and IV) was identified.

Operative link on gastritis assessment (OLGA) and operative link on gastric intestinal metaplasia assessment (OLGIM) systems are histological staging systems of gastritis for gastric cancer (GC) risk estimation. Intermediate OLGA/OLGIM stages are of concern in a region with high incidence of GC. This study aimed to validate OLGA and OLGIM staging systems for early GC (EGC) in Chinese population.

This single-centre, case-control study included 196 patients with EGC and 196 age-matched and sex-matched health screening control subjects. OLGA and OLGIM systems, and other clinical parameters were evaluated using logistic regression analysis.

OLGA and OLGIM stages II/III/IV were more prevalent in patients with EGC than in the control subjects. Multivariable analysis revealed family history of GC, previous Helicobacter pylori (H. pylori) infection, OLGA stages II and III-IV, OLGIM stages II and III-IV as independent risk factors for EGC (ORs, 4.04, 1.87, 2.52, 6.79, 4.11 and 10.78, respectively). Area under the receiver operating characteristic curve on EGC risk estimation was improved for OLGIM compared with OLGA (0.78 vs 0.71, p<0.001). Autoantibody seropositivity of gastric mucosa was not associated with EGC risk stratified by H. pylori status.

Surveillance of intermediate-risk patients (OLGA/OLGIM II) should be emphasised in our region. The OLGIM may be preferred over the OLGA for EGC risk estimation.

Gastric cancer continues to be a leading global health concern, with current therapeutic approaches requiring significant improvement. While the disruption of iron metabolism in the advancement of gastric cancer has been well-documented, the underlying regulatory mechanisms remain largely unexplored. Additionally, the complement C5a-C5aR pathway has been identified as a crucial factor in gastric cancer development. The impact of the complement system on iron metabolism and its role in gastric cancer progression is an area warranting further investigation. Our research demonstrates that the C5a-C5aR pathway promotes gastric cancer progression by enhancing iron acquisition in tumor cells through two mechanisms. First, it drives macrophage polarization toward the M2 phenotype, which has a strong iron-release capability. Second, it increases the expression of LCN2, a high-affinity iron-binding protein critical for iron export from tumor-associated macrophages, by activating endoplasmic reticulum stress in these cells. Both mechanisms facilitate the transfer of iron from macrophages to cancer cells, thereby promoting tumor cell proliferation. This study aims to elucidate the connection between the complement C5a-C5aR pathway and iron metabolism within the tumor microenvironment. Our data suggest a pivotal role of the C5a-C5aR pathway in tumor iron management, indicating that targeting its regulatory mechanisms may pave the way for future iron-targeted therapeutic approaches in cancer treatment.

Advances in gastric cancer screening have enabled earlier detection, shifting the focus of treatment toward preserving patients' quality of life (QoL). Function-preserving gastrectomy (FPG), including pylorus-preserving gastrectomy, proximal gastrectomy, and sentinel node navigation surgery, represents a paradigm shift in the surgical management of early gastric cancer. These techniques aim to balance oncological safety with the preservation of gastric function, mitigating postgastrectomy syndromes such as dumping syndrome, bile reflux, and nutritional deficiencies. QoL assessment tools, including EORTC QLQ-STO22, KOQUSS-40, and PGSAS-45, have become integral for evaluating patient-reported outcomes, providing insights into physical, emotional, and functional recovery. Although current evidence underscores the benefits of FPG, most studies are limited to East Asia, highlighting the need for multinational trials to validate these findings globally. FPG has demonstrated comparable short- and long-term oncological outcomes to conventional gastrectomy. Enhanced nutritional recovery and reduced gastrointestinal sequelae make FPG increasingly attractive. However, its widespread adoption is challenged by technical complexity, resource intensity, and the need for adequate surgical experience. The integration of advanced technologies, such as robotic surgery and artificial intelligence, coupled with personalized approaches, is expected to further optimize FPG outcomes. This review underscores the critical role of standardized QoL assessments, collaborative research, and technological innovations in advancing FPG as a cornerstone of patient-centered gastric cancer care.

The early diagnosis and treatment of Gastric Intraepithelial Neoplasia (GIN) are pivotal for improving the survival rates of patients with gastric cancer (GC). Regrettably, reliable noninvasive biomarkers for GIN screening are currently lacking.

mRNA data from the GEO database, pan-cancer data from the TCGA database, and a gene list of exocrine proteins were subjected to integrated analysis to identify a noninvasive biomarker for GIN. The scRNA-seq data analysis, IHC and Elisa were employed to validate the expression of the biomarker in the serum and tissues of clinical patients across different pathological stages.

MUC17 has been identified as a non-invasive diagnostic marker for GIN. It is upregulated in GIN prior to the onset of gastric carcinogenesis and downregulated in other tumors, with high GC specificity. The area under the curve values of serum MUC17 for differentiating chronic gastritis (CG) from low-grade intraepithelial neoplasia (LGIN), high-grade intraepithelial neoplasia (HGIN), and early gastric cancer (EGC) were 0.8788, 0.8544, and 0.9513, respectively. Additionally, low plasma MUC17 levels were found to be significantly lower in gastric ulcer (GU), gastric neuroendocrine tumor (GNET), and gastrointestinal stromal tumor (GIST) compared to GIN. The AUC for differentiating between GIN and GU, GNET, or GIST was 0.7803, 0.9244 and 0.9796, respectively.

These findings suggest that plasma MUC17 levels hold substantial promise as a screening biomarker for individuals with GIN and EGC, effectively identifying high-risk groups that necessitate further gastroscopy.

Detection of gastric cancer (GC) at early stages is an effective strategy for decreasing mortality. This study aimed to construct a prediction nomogram based on a questionnaire to assess the risk of developing GC.

Our study comprised a total of 4379 participants (2326 participants from outpatient at Fengqing People's Hospital were considered for model development and internal validation, and 2053 participants from outpatients at the endoscopy center at the Seventh Affiliated Hospital of Sun Yat-Sen University were considered for independent external validation) and gastric mucosa status was determined by endoscopy and biopsies. The eligible participants in development cohort from Fengqing people's Hospital were randomly separated into a training cohort (n=1629, 70.0%) and an internal validation cohort (n=697, 30.0%). The relevant features were selected by a least absolute shrinkage and selection operator (LASSO), and the ensuing features were evaluated through multivariable logistic regression analysis. Subsequently, the variables were selected to construct a prediction nomogram. The discriminative ability and predictive accuracy of the nomogram were evaluated by the C-index and calibration plot, respectively. Decision curve analysis (DCA) curves were used for the assessment of clinical benefit of the model. This model was developed to estimate the risk of developing neoplastic lesions according to the "transparent reporting of a multivariable prediction model for individual prognosis or diagnosis" (TRIPOD) statement.

Six variables, including age, sex, alcohol consumption, cigarette smoking, education level, and Hp infection status, were independent risk factors for the development of neoplastic lesions. Thus, these variables were incorporated into the final nomogram. The AUC of the nomogram were 0.701, 0.657 and 0.699 in the training, internal validation, and external validation cohorts, respectively. The calibration curve showed that the nomogram was in good agreement with the observed outcomes. Compared to treatment of all patients or none, our nomogram showed a notably higher clinical benefit.

This nomogram proved to be a convenient, cost-effective tool to effectively predict an individual's risk of developing neoplastic lesions, and it can act as a prescreening tool before gastroscopy.

The progression of gastric cancer involves a complex multi-stage process, with gastroscopy and biopsy being the standard procedures for diagnosing gastric diseases. This study introduces an innovative non-invasive approach to differentiate gastric disease stage using gastric fluid samples through machine-learning-assisted surface-enhanced Raman spectroscopy (SERS). This method effectively identifies different stages of gastric lesions. The XGBoost algorithm demonstrates the highest accuracy of 96.88% and 91.67%, respectively, in distinguishing chronic non-atrophic gastritis from intestinal metaplasia and different subtypes of gastritis (mild, moderate, and severe). Through blinded testing validation, the model can achieve more than 80% accuracy. These findings offer new possibilities for rapid, cost-effective, and minimally invasive diagnosis of gastric diseases.

A Raman-active boronate modified surface-enhanced Raman scattering (SERS) microporous array chip based on the enzymatic reaction was constructed for reliable, sensitive, and quantitative monitoring of D-Proline (D-Pro) and D-Alanine (D-Ala) in saliva. Initially, 3-mercaptophenylboronic acid (3-MPBA) was bonded to Au-coated Si nanocrown arrays (Au/SiNCA) via Au-S bonding. Following this, H2O2 obtained from D-amino acid oxidase (DAAO)-specific catalyzed D-amino acids (D-AAs) further reduced 3-MPBA to 3-hydroxythiophenol (3-HTP) with a new Raman peak at 882 cm-1. Meanwhile, the original characteristic peak at 998 cm-1 remained unchanged. Therefore, the I882/I998 ratio increased with increasing content of D-AAs in the sample to be tested, allowing D-AAs to be quantitatively detected. The Au/SiNCA with large-area periodic crown structure prepared provided numerous, uniform "hot spots," and the microporous array chip with 16 detection units was employed as the platform for SERS analysis, realizing high-throughput, high sensitivity, high specificity and high-reliability quantitative detection of D-AAs (D-Pro and D-Ala). The limits of detection (LOD) were down to 10.1 µM and 13.7 µM throughout the linear range of 20-500 µM. The good results of the saliva detection suggested that this SERS sensor could rapidly differentiate between early-stage gastric cancer patients and healthy individuals.

Clinical opportunistic screening is a cost-effective cancer screening modality. This study aimed to establish an easy-to-use diagnostic model serving as a risk stratification tool for identification of individuals with malignant gastric lesions for opportunistic screening.

We developed a questionnaire-based diagnostic model using a joint dataset including two clinical cohorts from northern and southern China. The cohorts consisted of 17,360 outpatients who had undergone upper gastrointestinal endoscopic examination in endoscopic clinics. The final model was derived based on unconditional logistic regression, and predictors were selected according to the Akaike information criterion. External validation was carried out with 32,614 participants from a community-based randomized controlled trial.

This questionnaire-based diagnostic model for malignant gastric lesions had eight predictors, including advanced age, male gender, family history of gastric cancer, low body mass index, unexplained weight loss, consumption of leftover food, consumption of preserved food, and epigastric pain. This model showed high discriminative power in the development set with an area under the receiver operating characteristic curve (AUC) of 0.791 (95% confidence interval [CI]: 0.750-0.831). External validation of the model in the general population generated an AUC of 0.696 (95% CI: 0.570-0.822). This model showed an ideal ability for enriching prevalent malignant gastric lesions when applied to various scenarios.

This easy-to-use questionnaire-based model for diagnosis of prevalent malignant gastric lesions may serve as an effective prescreening tool in clinical opportunistic screening for gastric cancer.

Gastric cancer is a major cause of cancer-related death worldwide, despite the reduction in its incidence. The disease is still burdened with a poor prognosis, particularly in Western countries. The main risk factor is the infection by Helicobacter pylori, classified as a class I carcinogen by the IARC, and It is well-known that primary prevention of gastric cancer can be achieved with the eradication of the infection. Moreover, non-invasive measurement of pepsinogens (PGI and PGI/PGII ratio) allows the identification of patients that should undergo upper gastrointestinal (GI) endoscopy. Gastric non-cardia adenocarcinoma is indeed preceded by a well-defined precancerous process that involves consecutive stages, described for the first time by Correa et al. more than 40 years ago, and patients with advance stages of gastric atrophy/intestinal metaplasia and with dysplastic changes should be followed-up periodically with upper GI endoscopies. Despite these effective screening and surveillance methods, national-level screening campaigns have been adopted only in few countries in eastern Asia (Japan and South Korea). In this review, we describe primary and secondary preventive measures for gastric cancer, discussing the need to introduce screening also in Western countries. Moreover, we propose a simple algorithm for screening that could be easily applied in clinical practice.

Gastric cancer predominantly adenocarcinoma, accounts for over 85% of gastric cancer diagnoses. Current therapeutic options are limited, necessitating the discovery of novel drug targets and effective treatments. The Affymetrix gene expression microarray dataset (GSE64951) was retrieved from NCBI-GEO data normalization and DEGs identification was done by using R-Bioconductor package. Gene Ontology (GO) analysis of DEGs was performed using DAVID. The protein-protein interaction network was constructed by STRING database plugin in Cytoscape. Subclusters/modules of important interacting genes in main network were extracted by using MCODE. The hub genes from in the network were identified by using Cytohubba. The miRNet tool built a hub gene/mRNA-miRNA network and Kaplan-Meier-Plotter conducted survival analysis. AutoDock Vina and GROMACS MD simulations were used for docking and stability analysis of marine compounds against the 5CNN protein. Total 734 DEGs (507 up-regulated and 228 down-regulated) were identified. Differentially expressed genes (DEGs) were enriched in processes like cell-cell adhesion and ATP binding. Eight hub genes (EGFR, HSPA90AA1, MAPK1, HSPA4, PPP2CA, CDKN2A, CDC20, and ATM) were selected for further analysis. A total of 23 miRNAs associated with hub genes were identified, with 12 of them targeting PPP2CA. EGFR displayed the highest expression and hazard rate in survival analyses. The kinase domain of EGFR (PDBID: 5CNN) was chosen as the drug target. Adociaquinone A from Petrosia alfiani, docked with 5CNN, showed the lowest binding energy with stable interactions across a 50 ns MD simulation, highlighting its potential as a lead molecule against EGFR. This study has identified crucial DEGs and hub genes in gastric cancer, proposing novel therapeutic targets. Specifically, Adociaquinone A demonstrates promising potential as a bioactive drug against EGFR in gastric cancer, warranting further investigation. The predicted miRNA against the hub gene/proteins can also be used as potential therapeutic targets.

Cancer screening aims to detect and treat malignant lesions at an early stage and to prolong patients' lifetime. There is still a lack of effective cancer screening programs in China. We initiated a screening project in 2018 and this study presented the cancer screening status in China.

We conducted a cross-sectional study in one cancer-care medical center of China. The screening program included routine blood tests, plasma tumor markers, gastric endoscopy, colonoscopy, ultrasound, and computed tomography (CT) scans. Screening results were presented as sensitivity, specificity and positive predictive values (PPVs).

Twenty-three (1.46%) out of 1,576 participants were eventually diagnosed with malignant tumors or high-grade intraepithelial neoplasia (HGIN). A family history of malignancy (78.26% in diagnosed cancer and HGIN vs. 46.36% in the others) was the only statistically significant parameter associated with cancer detection (p = 0.002). None of the common tumor markers were associated with the cancers screened. Except for colonoscopy (50.00%) and ultrasound for renal cancer (66.67%), the sensitivities of most screening methods were 100%. The specificities of all the screening means were above 96%. Most PPVs ranged from 30-60%.

We emphasized risk stratification for early cancer screening, such as a family history of cancer. The survey illustrated that gastric endoscopy, colonoscopy, ultrasound, and lung CT for early cancer screening had high specificity, reasonable sensitivity, and PPV. We anticipated this report would motivate larger-sample studies to estimate the risk-to-benefit ratio of cancer screening and urge the establishment of a native Chinese screening project and even guidelines.

Workplace cancer screening programs are determined as part of an employee's benefits package and health checkups are perceived positively. However, the current status of workplace cancer screening programs in Japan is unavailable. This study aimed to assess the adherence to national guidelines for colorectal, breast, and cervical cancer screenings in the workplace among Japanese enterprises and identify factors associated with excessive or inadequate screenings.

A cross-sectional study design was employed. Data were obtained from a survey conducted by the "Corporate Action to Promote Cancer Control" between November and December 2022 among registered partner enterprises in Japan. The survey included questions on background characteristics, cancer screening practices, and intervention approaches. The analysis included 432 enterprises that provided complete responses regarding colorectal, breast, and cervical cancer screenings.

The guideline-adherence rates for colorectal, breast, and cervical cancer screenings in the workplace were 12.7%, 3.0%, and 8.8%, respectively. Enterprises had lower adherence to screening guidelines than local governments. Colorectal (70.8%) and breast (67.1%) cancer screenings were predominantly categorized as "overscreening" and cervical (60.6%) cancer screening, as "underscreening." Factors such as enterprise scale, health insurance associations, and the number of interventional approaches were significantly associated with increased "overscreening" (101-1000: β = 0.13, p = 0.01; ≥ 1000: β = 0.17, p < 0.01; health insurance association: β = 0.23, p < 0.01; and approaches: β = 0.42, p < 0.01) and reduced "underscreening" (101-1000: β = -0.13, p = 0.01; ≥ 1000: β = -0.17, p < 0.01; health insurance association: β = -0.18, p < 0.01; and approaches: β = -0.48, p < 0.01).

Adherence to national guidelines for colorectal, breast, and cervical cancer screenings in the workplace was suboptimal among Japanese enterprises. Therefore, appropriate cancer screening measures and interventions to ensure guideline adherence and optimization of screening benefits while minimizing potential harms should be expeditiously implemented.

Efforts have been made to develop an endoscopic screening system incorporating serologic gastric cancer (GC) risk stratification (ABC classification) alongside annual population-based GC screening using barium. We conducted a randomized controlled trial (RCT) to compare GC detection rates between the Ba-Endo group, which underwent annual barium tests for primary screening followed by detailed endoscopic examinations, and the ABC-Endo group, where endoscopy intervals were determined based on individual gastric cancer risk in the ABC classification.

In total, 1206 individuals from Yurihonjo and Nikaho City, Akita Prefecture, were randomized through the minimization method using sex and age as allocation factors. The intervention study was conducted for both groups over 5 years. The Ba-Endo group received annual barium tests, and the ABC-Endo group underwent EGD at different intervals: group A, EGD only at entry; group B, EGD once every 3 years; group C, EGD once every 2 years; and group D, EGD every year.

There were 24 detected GC lesions, with a GC detection rate of 1.9%. GC detection rates in the Ba-Endo and ABC-Endo groups were 2.0% and 1.8%, respectively, with no significant differences between groups (P = 1.0). However, the rate of GC cured by endoscopic resection alone was 41.6% in the Ba-Endo group and was significantly higher at 90.9% in the ABC-Endo group (P = .02).

There were no differences between the Ba-Endo and ABC-Endo groups in GC detection rates. However, the rate of detected GCs that could be cured by endoscopic resection alone was significantly higher in the ABC-Endo group. (Clinical trial registration number: UMIN000005962.).

5-Hydroxymethylcytosine-enriched gene profiles and regions show tissue-specific and tumor specific. There is a potential value to explore cell-free DNA 5-hydroxymethylcytosine feature biomarkers for early gastric cancer detection.

A matched case‒control study design with 50 gastric cancer patients and 50 controls was performed to sequence the different 5-hydroxymethylcytosine modification features of cell free DNA. Significantly differential 5-hydroxymethylcytosine modification genes were identified to construct a gastric cancer diagnostic model. Data set from GEO was used as an external testing set to test the robustness of the diagnostic model.

Accounting for more than 90% of 5-hydroxymethylcytosine peaks were distributed in the gene body in both the gastric cancer and control groups. The diagnostic model was developed based on five different 5-hydroxymethylcytosine modification genes, FBXL7, PDE3A, TPO, SNTG2 and STXBP5. The model could effectively distinguish gastric cancer patients from controls in the training (AUC = 0.95, sensitivity = 88.6%, specificity = 94.3%), validation (AUC = 0.87, sensitivity = 73.3%, specificity = 93.3%) and testing (AUC = 0.90, sensitivity = 81.9%, specificity = 90.2%) sets. The risk scores of the controls from the model were significantly lower than those of gastric cancer patients in both our own data (P < 0.001) and GEO external testing data (P < 0.001), and no significant difference between different TNM stage patients (P = 0.09 and 0.66). Furthermore, there was no significant difference between the healthy control and benign gastric disease patients in the testing set from GEO (P = 0.10).

The characteristics of 5-hydroxymethylcytosine in cell free DNA are specific to gastric cancer patients, and the diagnostic model constructed by five genes' 5-hydroxymethylcytosine features could effectively identify gastric cancer patients.

Intestinal metaplasia (IM) is classified into complete intestinal metaplasia (CIM) and incomplete intestinal metaplasia (IIM). Patients diagnosed with IIM face an elevated susceptibility to the development of gastric cancer, underscoring the critical need for early screening measures. In addition to the complexities associated with diagnosis, the exact mechanisms driving the progression of gastric cancer in IIM patients remain poorly understood. OLFM4 is overexpressed in several types of tumors, including colorectal, gastric, pancreatic, and ovarian cancers, and its expression has been associated with tumor progression.

In this study, we used pathological sections from two clinical centers, biopsies of IM tissues, precancerous lesions of gastric cancer (PLGC) cell models, animal models, and organoids to explore the role of OLFM4 in IIM.

Our results show that OLFM4 expression is highly increased in IIM, with superior diagnostic accuracy of IIM when compared to CDX2 and MUC2. OLFM4, along with MYH9, was overexpressed in IM organoids and PLGC animal models. Furthermore, OLFM4, in combination with Myosin heavy chain 9 (MYH9), accelerated the ubiquitination of GSK3β and resulted in increased β-catenin levels through the Wnt signaling pathway, promoting the proliferation and invasion abilities of PLGC cells.

OLFM4 represents a novel biomarker for IIM and could be utilized as an important auxiliary means to delimit the key population for early gastric cancer screening. Finally, our study identifies cell signaling pathways involved in the progression of IM.

Gastric cancer (GC), an acknowledged malignant neoplasm, threatens life and digestive system functionality if not detected and addressed promptly in its nascent stages. The indispensability of early detection for GC to augment treatment efficacy and survival prospects forms the crux of this investigation. Our study introduces an innovative wrapper-based feature selection methodology, referred to as bCIFMVO-FKNN-FS, which integrates a crossover-information feedback multi-verse optimizer (CIFMVO) with the fuzzy k-nearest neighbors (FKNN) classifier. The primary goal of this initiative is to develop an advanced screening model designed to accelerate the identification of patients with early-stage GC. Initially, the capability of CIFMVO is validated through its application to the IEEE CEC benchmark functions, during which its optimization efficiency is measured against eleven cutting-edge algorithms across various dimensionalities-10, 30, 50, and 100. Subsequent application of the bCIFMVO-FKNN-FS model to the clinical data of 1632 individuals from Wenzhou Central Hospital-diagnosed with either early-stage GC or chronic gastritis-demonstrates the model's formidable predictive accuracy (83.395%) and sensitivity (87.538%). Concurrently, this investigation delineates age, gender, serum gastrin-17, serum pepsinogen I, and the serum pepsinogen I to serum pepsinogen II ratio as parameters significantly associated with early-stage GC. These insights not only validate the efficacy of our proposed model in the early screening of GC but also contribute substantively to the corpus of knowledge facilitating early diagnosis.

Population-based screening for gastric cancer (GC) in low prevalence nations is not recommended. The objective of this study was to develop a risk-prediction model to identify high-risk patients who could potentially benefit from targeted screening in a racial/ethnically diverse regional US population.

We performed a retrospective cohort study from Kaiser Permanente Southern California from January 2008-June 2018 among individuals age ≥50 years. Patients with prior GC or follow-up <30 days were excluded. Censoring occurred at GC, death, age 85 years, disenrollment, end of 5-year follow-up, or study conclusion. Cross-validated LASSO regression models were developed to identify the strongest of 20 candidate predictors (clinical, demographic, and laboratory parameters). Records from 12 of the medical service areas were used for training/initial validation while records from a separate medical service area were used for testing.

1,844,643 individuals formed the study cohort (1,555,392 training and validation, 289,251 testing). Mean age was 61.9 years with 53.3% female. GC incidence was 2.1 (95% CI 2.0-2.2) cases per 10,000 person-years (pyr). Higher incidence was seen with family history: 4.8/10,000 pyr, history of gastric ulcer: 5.3/10,000 pyr, H. pylori: 3.6/10,000 pyr and anemia: 5.3/10,000 pyr. The final model included age, gender, race/ethnicity, smoking, proton-pump inhibitor, family history of gastric cancer, history of gastric ulcer, H. pylori infection, and baseline hemoglobin. The means and standard deviations (SD) of c-index in validation and testing datasets were 0.75 (SD 0.03) and 0.76 (SD 0.02), respectively.

This prediction model may serve as an aid for pre-endoscopic assessment of GC risk for identification of a high-risk population that could benefit from targeted screening.

The lack of specific symptoms of gastric cancer (GC) causes great challenges in its early diagnosis. Thus it is essential to identify the risk factors for early diagnosis and treatment of GC and to improve the survival rates.

To assist physicians in identifying changes in the output of publications and research hotspots related to risk factors for GC, constructing a list of key risk factors, and providing a reference for early identification of patients at high risk for GC.

Research articles on risk factors for GC were searched in the Web of Science core collection, and relevant information was extracted after screening. The literature was analyzed using Microsoft Excel 2019, CiteSpace V, and VOSviewer 1.6.18.

A total of 2514 papers from 72 countries and 2507 research institutions were retrieved. China (n = 1061), National Cancer Center (n = 138), and Shoichiro Tsugane (n = 36) were the most productive country, institution, or author, respectively. The research hotspots in the study of risk factors for GC are summarized in four areas, namely: Helicobacter pylori (H. pylori) infection, single nucleotide polymorphism, bio-diagnostic markers, and GC risk prediction models.

In this study, we found that H. pylori infection is the most significant risk factor for GC; single-nucleotide polymorphism (SNP) is the most dominant genetic factor for GC; bio-diagnostic markers are the most promising diagnostic modality for GC. GC risk prediction models are the latest current research hotspot. We conclude that the most important risk factors for the development of GC are H. pylori infection, SNP, smoking, diet, and alcohol.

Colorectal, and gastric cancers have the second, and fourth mortality rates worldwide, respectively. Endoscopic screening is a crucial diagnostic tool for colorectal, and gastric cancers. Effective interventions can improve adherence to endoscopic screening in high-risk populations, which is important for cancer prevention and mortality reduction. This study aimed to identify interventions that could improve adherence to endoscopic screening for cancer in high-risk populations.

Combination keywords including colorectal cancer, gastric cancer, screening adherence, and interventions were used to search for articles in PubMed, Web of Science, Cochrane Library, and MEDLINE Complete. The review methodology was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-SCR).

A total of 12 articles were included in this review: 9 randomized controlled trials(RCT) and 3 quasi-experimental studies(QEDs). Among the extracted studies, 11 were about colorectal cancer, and 1 was about gastric cancer. Most studies used lecture-based or Information Technology-based health education interventions. Narrative interventions have proven to be novel and effective approaches for promoting adherence to endoscopic screening. Health education interventions included cancer epidemiology, cancer risk factors, warning symptoms, and screening methods.

All interventions involved were effective in increasing individual knowledge of cancer-related endoscopic screening, willingness to undergo screening, and screening behaviors. These findings provide a reference for designing endoscopy-related cancer screening interventions.

X-ray gastric cancer (GC) screening has been shown to decrease mortality. Population-based X-ray GC screening has been performed in Hiroshima Prefecture, Japan, since 1983 but time trends and the efficacy of the method over 39 years have not been assessed.

To evaluate time trends and efficacy of population-based X-ray GC screening and identify challenges and suggested solutions for the future.

This was a population-based retrospective study. The data were derived from aggregated data of the Hiroshima Regional Health Medical Promotion Organization, including the number and rate of participants and those requiring esophagogastroduodenoscopies (EGDs), the number and rate of participants diagnosed as having GC, and the positive predictive value of the abnormal findings detected by X-ray and confirmed by EGDs. The number and rate of esophageal cancers were also collected. Further, the cost of detecting one GC was evaluated.

The number of participants has decreased during the last four decades, from 39925 in 1983 to 12923 in 2021. The rate of those requiring EGDs decreased significantly in recent years (P < 0.001). The number of participants diagnosed as having GC has also declined, from 76 to 10 cases. However, the rate of cases diagnosed as GC among the participants remained around 0.1%. The positive predictive value increased significantly in recent years except during 1983-1991. The number and rate of accidentally detected esophageal cancers have risen recently, from 0% in 2008 to 0.02% in 2021, one-fifth of the diagnosis rate of GC. One GC diagnosis costs approximately 4200000 Japanese Yen (30000 United States Dollars) for the X-ray screenings and EGDs.

X-ray GC screening in Hiroshima has been efficient, but one challenge is the cost. Esophageal cancers may also need to be considered because they have gradually increased in recent years.

The incidence of gastric cancer remains high, and it is the sixth most common cancer and the fourth leading cause of cancer deaths worldwide. Oral contrast-enhanced ultrasonography is a simple, non-invasive, and painless method for the diagnosis of gastric tumors.

To explore the diagnostic value of oral contrast-enhanced ultrasonography for the detection of gastric tumors.

The screening results based on oral contrast-enhanced ultrasonography and electronic gastroscopy were compared with those of the postoperative pathological examination.

Among 42 patients with gastric tumors enrolled in the study, the diagnostic accordance rate was 95.2% for oral contrast-enhanced ultrasonography (n = 40) and 90.5% for electronic gastroscopy (n = 38) compared with postoperative pathological examination. The Kappa value of consistency test with pathological findings was 0.812 for oral contrast-enhanced ultrasonography and 0.718 for electronic gastroscopy, and there was no significant difference between them (P = 0.397). For the TNM staging of gastric tumors, the accuracy rate of oral contrast-enhanced ultrasonography was 81.9% for the overall T staging and 50%, 77.8%, 100%, and 100% for T1, T2, T3, and T4 staging, respectively. The sensitivity and specificity were both 100% for stages T3 and T4. The diagnostic accuracy rate of oral contrast-enhanced ultrasonography was 93.8%, 80%, 100%, and 100% for stages N0, N1-N3, M0, and M1, respectively.

The accordance rate of qualitative diagnosis by oral contrast-enhanced ultrasonography is comparable to that of gastroscopy, and it could be used as the preferred method for the early screening of gastric tumors.

To optimize gastric cancer screening score and reduce screening costs using machine learning models.

This study included 228,634 patients from the Taizhou Gastric Cancer Screening Program. We used three machine learning models to optimize Li's gastric cancer screening score: Gradient Boosting Machine (GBM), Distributed Random Forest (DRF), and Deep Learning (DL). The performance of the binary classification models was evaluated using the area under the curve (AUC) and area under the precision-recall curve (AUCPR).

In the binary classification model used to distinguish low-risk and moderate- to high-risk patients, the AUC in the GBM, DRF, and DL full models were 0.9994, 0.9982, and 0.9974, respectively, and the AUCPR was 0.9982, 0.9949, and 0.9918, respectively. Excluding Helicobacter pylori IgG antibody, pepsinogen I, and pepsinogen II, the AUC in the GBM, DRF, and DL models were 0.9932, 0.9879, and 0.9900, respectively, and the AUCPR was 0.9835, 0.9716, and 0.9752, respectively. Remodel after removing variables IgG, PGI, PGII, and G-17, the AUC in GBM, DRF, and DL was 0.8524, 0.8482, 0.8477, and AUCPR was 0.6068, 0.6008, and 0.5890, respectively. When constructing a tri-classification model, we discovered that none of the three machine learning models could effectively distinguish between patients at intermediate and high risk for gastric cancer (F1 scores in the GBM model for the low, medium and high risk: 0.9750, 0.9193, 0.5334, respectively; F1 scores in the DRF model for low, medium, and high risks: 0.9888, 0.9479, 0.6694, respectively; F1 scores in the DL model for low, medium, and high risks: 0.9812, 0.9216, 0.6394, respectively).

We concluded that gastric cancer screening indicators could be optimized when distinguishing low-risk and moderate to high-risk populations, and detecting gastrin-17 alone can achieve a good discriminative effect, thus saving huge expenditures.

Intestinal metaplasia (IM) is a pre-malignant condition of the gastric mucosa associated with increased gastric cancer (GC) risk. Analyzing 1,256 gastric samples (1,152 IMs) across 692 subjects from a prospective 10-year study, we identify 26 IM driver genes in diverse pathways including chromatin regulation (ARID1A) and intestinal homeostasis (SOX9). Single-cell and spatial profiles highlight changes in tissue ecology and IM lineage heterogeneity, including an intestinal stem-cell dominant cellular compartment linked to early malignancy. Expanded transcriptome profiling reveals expression-based molecular subtypes of IM associated with incomplete histology, antral/intestinal cell types, ARID1A mutations, inflammation, and microbial communities normally associated with the healthy oral tract. We demonstrate that combined clinical-genomic models outperform clinical-only models in predicting IMs likely to transform to GC. By highlighting strategies for accurately identifying IM patients at high GC risk and a role for microbial dysbiosis in IM progression, our results raise opportunities for GC precision prevention and interception.

The purpose of the current study was to compare the outcomes of patients with gastric cancer (GC) between the type 2 diabetes mellitus (T2DM) group and the non-T2DM group. The PubMed, Embase and Cochrane Library databases were searched from inception to March 8, 2022, to identify propensity score matching (PSM) studies that analyzed the effect of T2DM on the outcomes of patients with GC. Total complications, overall survival (OS), disease-free survival (DFS) and cancer-specific survival (CSS) were compared between the T2DM group and the non-T2DM group. A total of four PSM studies with 834 patients were included in the current study. There were 311 and 523 patients in the T2DM group and the non-T2DM group, respectively. Baseline characteristics of the two groups were adjusted with PSM in all the four studies, however, no significant difference was found in baseline characteristics (P>0.05). DFS was significantly worse in the T2DM group compared with that in the non-T2DM group [hazard ratio (HR), 1.45; 95% confidence interval (CI), 1.10-1.90; P=0.007)]. However, after pooling up the data, there was no significant difference between the T2DM group and the non-T2DM group in terms of OS (HR, 1.41; 95% CI, 0.92-2.16; P=0.11), CSS (HR, 1.29; 95% CI, 0.92-1.81; P=0.14) and total complications (odds ratio, 1.01; 95% CI, 0.64-1.60; P=0.95). Patients with GC and T2DM are associated with poor DFS. However, there were no significant differences between the T2DM group and the non-T2DM group in terms of OS, CSS and total complications.

Cancer screening has the potential to decrease mortality from several common cancer types. The first cancer screening programme in China was initiated in 1958 and the Cancer High Incidence Fields established in the 1970s have provided an extensive source of information for national cancer screening programmes. From 2012 onwards, four ongoing national cancer screening programmes have targeted eight cancer types: cervical, breast, colorectal, lung, oesophageal, stomach, liver, and nasopharyngeal cancers. By synthesising evidence from pilot screening programmes and population-based studies for various screening tests, China has developed a series of cancer screening guidelines. Nevertheless, challenges remain for the implementation of a fully successful population-based programme. The aim of this Review is to highlight the key milestones and the current status of cancer screening in China, describe what has been achieved to date, and identify the barriers in transitioning from evidence to implementation. We also make a set of implementation recommendations on the basis of the Chinese experience, which might be useful in the establishment of cancer screening programmes in other countries.

Intestinal metaplasia plays a crucial role in the risk stratification of gastric cancer development. The objective of the study was to develop a prediction model for Operative Link on Gastric Intestinal Metaplasia (OLGIM) Stage III-IV.

We analyzed 7945 high-risk gastric cancer individuals from 115 hospitals who underwent questionnaires and gastroscope. The participants were assigned to either the development or validation cohort randomly. Demographics and clinical characteristics were obtained. The outcome measurement was OLGIM III-IV. Univariate logistic regression was used for feature selection and multivariate logistic analysis was performed to develop the nomogram. Area under the curves, calibration plots, decision curve and clinical impact analysis were used to assess the performance of the nomogram.

4600 individuals and 3345 individuals were included in the development and validation cohort, of which 124 and 86 individuals were diagnosed with OLGIM III-IV, respectively. Parameters in the training validation cohort matched well and there was no significant difference between two cohorts. A nomogram model for predicting OLGIM Stage III-IV consisted of 4 significantly associated variables, including age, gender, PG I and G-17 (AUC 0.723 and 0.700 for the 2 cohorts). The nomogram demonstrated excellent performance in the calibration curve. Decision curve and clinical impact analysis suggested clinical benefit of the prediction model.

This reliable individualized nomogram might contribute to more accurate management for patients with OLGIM III-IV. Therefore, we suggest that this study be used as an incentive to promote the application.

This study aimed to evaluate the socioeconomic inequality in gastric cancer (GC) screening in Korea. Socioeconomic inequality was assessed using both organized and opportunistic screening according to income and educational level.

GC screening data were obtained from the 2009-2022 Korean National Cancer Screening Survey. The final analysis included 47,163 cancer-free men and women. The weighted cancer screening rate was estimated using joinpoint regression. The inequality indices were measured in terms of both the absolute slope index of inequality (SII) and the relative index of inequality (RII) using the Poisson regression model.

The organized screening rate for GC increased from 38.2% in 2009 to 70.8% in 2022, whereas the opportunistic screening rate decreased from 18.8 to 4.5%. Regarding educational inequality, a negative SII value was observed [-3.5, 95% confidence interval (CI), -7.63-0.83%] in organized screening, while a positive SII (9.30%; 95% CI, 6.69-11.91%) and RII (1.98%; 95% CI, 1.59-2.46) were observed in opportunistic screening. Furthermore, income inequality was not found in organized GC screening; however, overall SII and RII for opportunistic screening were 7.72% (95% CI, 5.39-10.5) and 1.61 (95% CI, 1.42-1.81), respectively.

Organized screening rates have grown gradually over time and account for the majority of GC screenings in South Korea. While no socioeconomic inequalities were found in organized screening, significant socioeconomic inequalities were found in opportunistic screening.

Gastric cancer is one of the leading causes of death worldwide, and resections are performed to cure the disease. We have previously reported the changes in the gastric microbiota after gastric cancer resection, which may be associated with the oral microbiota; however, the changes in the oral microbiota remain uncharacterized. This study aimed to characterize the changes in the salivary microbiota caused by gastric cancer resection and to evaluate their association with the gastric fluid microbiota. Saliva and gastric fluid samples were collected from 63 patients who underwent gastrectomy before and after surgery, and a 16S rRNA metagenomic analysis was performed to compare the microbiota composition. The number of bacterial species in the salivary microbiota decreased, and the bacterial composition changed after the resection of gastric cancer. In addition, we identified several bacterial genera that varied significantly in the salivary microbiota, some of which also showed similar changes in the gastric fluid microbiota. These findings indicate that changes in the gastric environment affect the oral microbiota, emphasizing the close association between the oral and gastric fluid microbiota. Our study signifies the importance of focusing on the oral microbiota in the perioperative period of gastrectomy in patients with gastric cancer.

There is a need for serum diagnostic biomarkers to improve the prognosis of solid malignant tumors. Here, we conducted a single-institutional study to evaluate the diagnostic performance of serum stromal cell-derived factor 4 (SDF4) levels in cancer patients. Serum samples were collected from a total of 582 patients with solid cancers including gastric cancer (GC) and 80 healthy volunteers. SDF4 protein levels in sera, and conditioned media or lysates of human GC cell lines were measured by enzyme-linked immunosorbent assay, and those in GC tissue by immunohistochemistry. Serum SDF4 levels were higher in patients with cancer than the healthy control in all cancer type. Regarding GC, serum SDF4 levels distinguished healthy controls from GC patients with the area under the curve value of 0.973, sensitivity of 89%, and specificity of 99%. Serum SDF4 levels were significantly elevated in patient with early stage GC. In immunohistochemistry, the frequency of SDF4-positive GC tumors did not vary significantly between GC stages. The ability of human GC cell lines to both produce and secrete SDF4 was confirmed in vitro. In conclusion, serum SDF4 levels could be a promising candidate for a novel diagnostic biomarker for GC and other malignancies.