Objective To screen specific antibodies to Helicobacter pylori(H.pylori)in serum,and establish antibody panels and discrimination models for different infection status,which are non-invasive and suitable for gastric cancer screening in Chinese population.Methods A total of 300 subjects with different H.pylori statuses were enrolled depending on an endoscopy screening cohort in a high-risk area of gastric cancer,including current,past,and negative infections.The recomLine Helicobacter IgG 2.0 immunoblotting assay was used to analyze and screen 10 H.pylori specific antibodies in serum samples.Results A total of nine antibody reactivity against CagA,VacA,GroEL,FliD,HpaA,gGT,HtrA,NapA,and CtkA showed significant differences among different H.pylori infection status groups(all P＜0.05).A panel comprising the nine antibodies distinguished exposure subjects to H.pylori(current and past infections)from negatives,with an area under the curve(AUC)of 0.935(95%CI:0.907-0.963).The combination of four antibodies(CagA,GroEL,FliD,and gGT)may help to discriminate current and past infection subjects,with an AUC of 0.927(95%CI:0.891-0.964).Conclusion The antibody panels and discriminant models for H.pylori infection status established in the present study may provide a potential and non-invasive screening method for the development of precise gastric cancer prevention strategies.

Objective:To identify proteins associated with the risk of gastric cancer (GC) and build a protein risk score for risk prediction of GC based on proteomic analysis.Methods:Gastric mucosal proteomics data were used to construct Dataset One, comprising 94 GC cases and 230 individuals with different stages of gastric mucosal lesions. The GC cases were recruited from the National Upper Gastrointestinal Cancer Early Detection (UGCED) Program in Linqu, Shandong Province, as well as clinical patients from the Fifth Medical Center, General Hospital of PLA, and Peking University Cancer Hospital. Non-cancer individuals were enrolled from the National UGCED Program in Linqu and community screening programs at the Dongfang Hospital. All participants were pathologically confirmed. Multivariate logistic regression analysis was employed to identify gastric mucosal proteins significantly associated with GC risk. Subsequently, plasma proteomics data from the UK Biobank Pharma Proteomics Project (UKB-PPP) were used to construct Dataset Two, including 40 baseline GC cases and 47 933 non-cancer individuals, and Dataset Three, comprising 138 incident GC cases and 47 933 non-cancer individuals during a prospective follow-up period. In Dataset Two, multivariate logistic regression analysis was conducted to assess associations between plasma protein levels and baseline GC risk. In Dataset Three, multivariate Cox regression analysis was used to examine associations with the risk of incident GC. A poly-protein risk score (PRS) was developed using a weighted summation method based on protein effect sizes from Dataset Two. Its associations with GC risk and the progression of gastric mucosal lesions were evaluated using linear regression trend tests.Results:A total of 324, 47 973 and 48 071 participants were included in Datasets One, Two, and Three, respectively. Across the three datasets, the proportions of males and individuals aged>60 years were higher in the GC group than in the non-GC group (all P values<0.05). The follow-up period in Dataset Three had a M ( P 25, P 75) of 14.47 (13.7, 15.2) years, with a median of 7.4 (4.6, 11.3) years for those who progressed to GC. Based on Dataset One, 2 524 tissue-differential proteins associated with GC risk were identified through multivariate logistic regression analysis adjusted for age and sex. Among these, seven proteins were consistently associated with GC risk across tissue and plasma levels in Datasets Two and Three, with consistent directions of association. Five proteins (MRC1, APOL1, BST2, PON2, and GGH) were positively associated with GC risk, while two (GSN and CLEC3B) were negatively associated. Analysis of the PRS based on these seven proteins showed that for each standard deviation increase in the tissue-derived PRS, the risk of GC increased by 6.26 times (95% CI: 4.02-9.75). In Dataset Two, each standard deviation increase in the plasma-derived PRS was associated with a 2.13-fold increase in GC risk (95% CI: 1.68-2.69). In the prospective cohort of Dataset Three, individuals in the high PRS group had a 2.27-fold higher risk of GC compared to the low PRS group (95% CI: 1.50-3.45). Moreover, each standard deviation increase in the plasma PRS was associated with a 57% higher risk of GC ( HR=1.57, 95% CI: 1.34-1.84). Additionally, the tissue-derived PRS showed an increasing trend with the progression of gastric mucosal lesions. Conclusion:The tissue and plasma proteomics identified seven individual proteins that may indicate the risk of developing gastric cancer, showing the potential as biomarkers for aiding in the screening of gastric cancer.

Objective:To identify proteins associated with the risk of gastric cancer (GC) and build a protein risk score for risk prediction of GC based on proteomic analysis.Methods:Gastric mucosal proteomics data were used to construct Dataset One, comprising 94 GC cases and 230 individuals with different stages of gastric mucosal lesions. The GC cases were recruited from the National Upper Gastrointestinal Cancer Early Detection (UGCED) Program in Linqu, Shandong Province, as well as clinical patients from the Fifth Medical Center, General Hospital of PLA, and Peking University Cancer Hospital. Non-cancer individuals were enrolled from the National UGCED Program in Linqu and community screening programs at the Dongfang Hospital. All participants were pathologically confirmed. Multivariate logistic regression analysis was employed to identify gastric mucosal proteins significantly associated with GC risk. Subsequently, plasma proteomics data from the UK Biobank Pharma Proteomics Project (UKB-PPP) were used to construct Dataset Two, including 40 baseline GC cases and 47 933 non-cancer individuals, and Dataset Three, comprising 138 incident GC cases and 47 933 non-cancer individuals during a prospective follow-up period. In Dataset Two, multivariate logistic regression analysis was conducted to assess associations between plasma protein levels and baseline GC risk. In Dataset Three, multivariate Cox regression analysis was used to examine associations with the risk of incident GC. A poly-protein risk score (PRS) was developed using a weighted summation method based on protein effect sizes from Dataset Two. Its associations with GC risk and the progression of gastric mucosal lesions were evaluated using linear regression trend tests.Results:A total of 324, 47 973 and 48 071 participants were included in Datasets One, Two, and Three, respectively. Across the three datasets, the proportions of males and individuals aged>60 years were higher in the GC group than in the non-GC group (all P values<0.05). The follow-up period in Dataset Three had a M ( P 25, P 75) of 14.47 (13.7, 15.2) years, with a median of 7.4 (4.6, 11.3) years for those who progressed to GC. Based on Dataset One, 2 524 tissue-differential proteins associated with GC risk were identified through multivariate logistic regression analysis adjusted for age and sex. Among these, seven proteins were consistently associated with GC risk across tissue and plasma levels in Datasets Two and Three, with consistent directions of association. Five proteins (MRC1, APOL1, BST2, PON2, and GGH) were positively associated with GC risk, while two (GSN and CLEC3B) were negatively associated. Analysis of the PRS based on these seven proteins showed that for each standard deviation increase in the tissue-derived PRS, the risk of GC increased by 6.26 times (95% CI: 4.02-9.75). In Dataset Two, each standard deviation increase in the plasma-derived PRS was associated with a 2.13-fold increase in GC risk (95% CI: 1.68-2.69). In the prospective cohort of Dataset Three, individuals in the high PRS group had a 2.27-fold higher risk of GC compared to the low PRS group (95% CI: 1.50-3.45). Moreover, each standard deviation increase in the plasma PRS was associated with a 57% higher risk of GC ( HR=1.57, 95% CI: 1.34-1.84). Additionally, the tissue-derived PRS showed an increasing trend with the progression of gastric mucosal lesions. Conclusion:The tissue and plasma proteomics identified seven individual proteins that may indicate the risk of developing gastric cancer, showing the potential as biomarkers for aiding in the screening of gastric cancer.

Objective To screen specific antibodies to Helicobacter pylori(H.pylori)in serum,and establish antibody panels and discrimination models for different infection status,which are non-invasive and suitable for gastric cancer screening in Chinese population.Methods A total of 300 subjects with different H.pylori statuses were enrolled depending on an endoscopy screening cohort in a high-risk area of gastric cancer,including current,past,and negative infections.The recomLine Helicobacter IgG 2.0 immunoblotting assay was used to analyze and screen 10 H.pylori specific antibodies in serum samples.Results A total of nine antibody reactivity against CagA,VacA,GroEL,FliD,HpaA,gGT,HtrA,NapA,and CtkA showed significant differences among different H.pylori infection status groups(all P＜0.05).A panel comprising the nine antibodies distinguished exposure subjects to H.pylori(current and past infections)from negatives,with an area under the curve(AUC)of 0.935(95%CI:0.907-0.963).The combination of four antibodies(CagA,GroEL,FliD,and gGT)may help to discriminate current and past infection subjects,with an AUC of 0.927(95%CI:0.891-0.964).Conclusion The antibody panels and discriminant models for H.pylori infection status established in the present study may provide a potential and non-invasive screening method for the development of precise gastric cancer prevention strategies.

Objective:To provide evidence for optimizing the screening strategy for gastric cancer (GC), we evaluated the risk of incident GC for individuals with different precancerous gastric lesions in a prospective cohort study.Methods:Based on the National Upper Gastrointestinal Cancer Early Detection Program launched in Linqu, Shandong, a high-risk area of gastric cancer in China, we included a total of 14 087 subjects diagnosed with different gastric lesions stages by endoscopic screening from 2012 to 2018. Study subjects were prospectively followed up until December 31, 2019. The incidence of GC during the follow-up was ascertained by repeated endoscopic examinations, cancer, death registry reports, and active follow-up of study subjects and was confirmed by reviewing medical records extracted from the hospital information management system. The Poisson regression model was applied to calculate the relative risk ( RR) and 95% CI for GC occurrence among subjects with different gastric lesions. Results:Among 14 087 subjects with different gastric lesions as determined by their first endoscopic examination in 2012-2018, 7 608 (54.00%) had a global diagnosis of superficial gastritis (SG), 2 848 (20.22%) had chronic atrophic gastritis (CAG), 3 103 (22.03%) had intestinal metaplasia (IM), and 520 (3.69%) had low-grade intestinal neoplasia (LGIN). During the follow-up, 109 subjects were diagnosed with GC, including 63 with high-grade intestinal neoplasia (HGIN) and 46 with invasive GC. Compared to subjects having normal gastric mucosa or SG, those with CAG ( RR=3.85, 95% CI: 2.04-7.28), IM ( RR=5.18, 95% CI: 2.79-9.60), and LGIN ( RR=19.08, 95% CI: 9.97-36.53) had significantly increased risk of progression to GC. Individuals with these gastric lesions had an elevated risk of developing HGIN and invasive GC. For subjects with LGIN, the RR was 22.96 (95% CI: 9.71-54.27) for developing HGIN and 14.64 (95% CI: 5.37-39.93) for developing invasive GC. Subgroup analyses found that all age group subjects with LGIN diagnosed during the initial endoscopic examination had a significantly increased risk of developing the GC. Conclusions:Our large-scale prospective study on a high-risk area of GC showed that most residents aged 40-69 years had gastric lesions of different stages. Subjects with more advanced gastric lesions had a significantly increased risk of progression to GC.

Traditional survival methods have a wide application in the field of biomedical research. However, applying traditional survival methods requires data to meet a set of special assumptions while the Random Survival Forest model can overcome this inconvenience. Herein, we used the clinical data of Primary Biliary Cholangitis (PBC) from Mayo Clinic to introduce and demonstrate Random Survival Forest model from mathematical principles, model building, practical example and attentions, aiming to provide a novel method for doing survival analysis.

The liquid chromatography tandem mass spectrometry was used to detect the urinary proteomics of 223 residents aged 40-69 years old who participated in the National Upper Gastrointestinal Cancer Early Detection Program in Linqu County, Shandong Province from November 22 to December 7, 2018, and analyze the alcohol consumption related proteomic profiles and individual urinary protein. There were significant differences in urinary protein profiles between alcohol consumption group and non-alcohol consumption group. The expression of 26 urinary proteins was up-regulated and 20 urinary proteins were down-regulated in alcohol consumption group ( P<0.05). The differentially expressed proteins had enzyme inhibitor activity and phospholipid binding function, and mainly enriched in pathways involving proximal tubule bicarbonate regeneration, complement and coagulation cascade, and cholesterol metabolism. The protein expressions of complement factor I (CFI), angiotensin converting enzyme 2 (ACE2) and protein C inhibitor (SERPINA5) were positively correlated with daily alcohol consumption.

Traditional survival methods have a wide application in the field of biomedical research. However, applying traditional survival methods requires data to meet a set of special assumptions while the Random Survival Forest model can overcome this inconvenience. Herein, we used the clinical data of Primary Biliary Cholangitis (PBC) from Mayo Clinic to introduce and demonstrate Random Survival Forest model from mathematical principles, model building, practical example and attentions, aiming to provide a novel method for doing survival analysis.

The liquid chromatography tandem mass spectrometry was used to detect the urinary proteomics of 223 residents aged 40-69 years old who participated in the National Upper Gastrointestinal Cancer Early Detection Program in Linqu County, Shandong Province from November 22 to December 7, 2018, and analyze the alcohol consumption related proteomic profiles and individual urinary protein. There were significant differences in urinary protein profiles between alcohol consumption group and non-alcohol consumption group. The expression of 26 urinary proteins was up-regulated and 20 urinary proteins were down-regulated in alcohol consumption group ( P<0.05). The differentially expressed proteins had enzyme inhibitor activity and phospholipid binding function, and mainly enriched in pathways involving proximal tubule bicarbonate regeneration, complement and coagulation cascade, and cholesterol metabolism. The protein expressions of complement factor I (CFI), angiotensin converting enzyme 2 (ACE2) and protein C inhibitor (SERPINA5) were positively correlated with daily alcohol consumption.

Gastric cancer is a malignant tumor characterized by high morbidity and mortality. With the development of molecular biol-ogy technology and the emergence of various new omics detection techniques in recent years, molecular epidemiologists of gastric cancer have conducted extensive studies on the genetic and host factors, as well as gene-environment interactions associated with ex-posure to environmental factors in gastric cancer. In addition, epidemiologists have studied the evolution of precancerous gastric le-sions, the development of gastric cancer, and explored relevant biomarkers to provide major evidence for the prevention and control of gastric cancer. This review summarizes the latest advances in the molecular epidemiology of gastric cancer, including existing evi-dence in studies for candidate-approach-based serum/plasma biomarkers, genome-wide association, whole-exome sequencing, tissue microarrays, as well as studies on metabolomics and microbiomes. We expect to provide insights into the future of molecular epidemi-ology studies in gastric cancer, promoting etiologic research, and the precise prevention and control of gastric cancer.