Surveillance of premalignant gastric cardia lesions: A population-based prospective cohort study in China

Proteomic and serological markers for diagnosing cardia gastric cancer and precursor lesions in a Chinese population

Cardia gastric cancer (CGC) is prevalent in East Asia, and noninvasive, cost-effective screening methods are needed. This study investigated the diagnostic value of serum pepsinogen (PG), gastrin-17 (G-17), Helicobacter pylori (H. pylori) antibodies, and proteomic profiling for CGC and precancerous lesions. We conducted a case-control study involving biopsy-confirmed patients with CGC (n = 60), low-grade intraepithelial neoplasia (CLGD, n = 60), high-grade intraepithelial neoplasia (CHGD, n = 64), and healthy controls (n = 120) matched for age and sex from high-incidence areas in China. Serological markers including PGI, PGII, G-17, and H. pylori were measured using ELISA and Western blot, while plasma protein markers were assessed using Olink® technology. The VSOLassoBag algorithm and nine machine learning (ML) algorithms were employed to identify crucial features and construct predictive models. Various evaluation metrics, including the area under the receiver-operating-characteristic curve (AUC), were utilized to compare predictive performance. Elevated PGII levels, decreased PGR, and H. pylori infection were significantly associated with an increased risk of CGC and precancerous lesions (P for trend < 0.05). The eXtreme Gradient Boosting (XGBoost) model performed best in discriminative ability among the 9 ML models. Following feature reduction based on predictive performance, a final explainable XGBoost model was developed, incorporating five protein biomarkers (CDHR2, ICAM4, PTPRM, CDC27, and FLT1). This model exhibited excellent performance in distinguishing individuals with CGC and precancerous lesions from healthy controls (AUC = 0.931 for CGC, 0.867 for CHGD, and 0.763 for CLGD), surpassing the traditional serological marker-based model. This study underscores the diagnostic potential of serological markers and proteomic profiling in the detection of CGC. Further validation and exploration of combined biomarker approaches are warranted to enhance early diagnosis and improve outcomes in high-risk populations.

Can patients with mild non-neoplastic lesions diagnosed at baseline screening be safely exempt from surveillance: evidence from multicenter community-based cohorts

Surveillance recommendations for gastric cancer (GC) in current guidelines focused on advanced precancerous lesions and were based on precise diagnosis of severity/extent of baseline lesions. We aimed to develop a less endoscopy-related equipment-dependent risk-stratification tool, and assessed whether mild-precursor-lesion patients can be safely exempt from surveillance. In the multicenter community-based cohort, 75,051 participants receiving baseline endoscopy were enrolled during 2015-2017 and followed-up until 2021. Cumulative incidence rates (CIRs) of GC for precancerous-conditions were calculated by Kaplan-Meier method and compared by Log-rank tests. Mixed-effects Cox regression models were used to detect potential factors for progression towards GC. A risk score was calculated as counts of selected factors. An independent cohort, including 26,586 participants was used for external validation. During a median follow-up of 6.25 years, CIRs of GC were 0.302%, 0.436%, and 4.756% for normal group, non-neoplastic (atrophic gastritis/intestinal metaplasia) and neoplastic lesions (low-grade/high-grade dysplasia), respectively (Ptrend<0.001). Four predictors, including male, ⩾60 years, smoking, and limited vegetable consumption, were selected for risk-stratification. High-risk patients (⩾3 risk factors) with non-neoplastic lesions showed higher GC risks (adjusted HR=7.73, 95%CI: 4.29-13.92), and their four-year CIR reached the one-year CIR of neoplastic lesions. Further categorizing non-neoplastic lesions by histological grade, both patients with moderate-to-severe lesions (aHR=3.07, 95%CI: 1.67-5.64) and high-risk patients with mild lesions (aHR=7.29, 95%CI: 3.58-14.86) showed higher risks. Consistent trends were observed in validation cohort. High-risk mild-precursor-lesion patients should receive surveillance within 3-5 years after baseline screening. Our study provides evidence on supplementing current guideline recommendations.

Endoscopic Surveillance of Intestinal Metaplasia of the Esophagogastric Junction: A Decision Modeling Analysis

INTRODUCTION

The incidence of esophagogastric junction adenocarcinoma (EGJAC) has been rising. Intestinal metaplasia of the esophagogastric junction (EGJIM) is a common finding in gastroesophageal reflux (irregular Z-line) and may represent an early step in the development of EGJAC in the West. Worldwide, EGJIM may represent progression along the Correa cascade triggered by Helicobacter pylori . We sought to evaluate the cost-effectiveness of endoscopic surveillance of EGJIM.

METHODS

We developed a decision analytic model to compare endoscopic surveillance strategies for 50-year-old patients after diagnosis of non-dysplastic EGJIM: (i) no surveillance (standard of care), (ii) endoscopy every 3 years, (iii) endoscopy every 5 years, or (iv) 1-time endoscopy at 3 years. We modeled 4 progression scenarios to reflect uncertainty: A (0.01% annual cancer incidence), B (0.05%), C (0.12%), and D (0.22%).

RESULTS

Cost-effectiveness of endoscopic surveillance depended on the progression rate of EGJIM to cancer. At the lowest progression rate (scenario A, 0.01%), no surveillance strategies were cost-effective. In moderate progression scenarios, 1-time surveillance at 3 years was cost-effective, at $30,989 and $16,526 per quality-adjusted life year for scenarios B (0.05%) and C (0.12%), respectively. For scenario D (0.22%), surveillance every 5 years was cost-effective at $77,695 per quality-adjusted life year.

DISCUSSION

Endoscopic surveillance is costly and can cause harm; however, low-intensity longitudinal surveillance (every 5 years) is cost-effective in populations with higher EGJAC incidence. No surveillance or 1-time endoscopic surveillance of patients with EGJIM was cost-effective in low-incidence populations. Future studies to better understand the natural history of EGJIM, identify risk factors of progression, and inform appropriate surveillance strategies are required.

Novel metabolic biomarker for early detection and diagnosis to the patients with gastric cardia adenocarcinoma

BACKGROUND

Gastric cardia adenocarcinoma (GCA) is classified as Siewert type II adenocarcinoma at the esophagogastric junction in Western countries. The majority of GCA patients do not exhibit early warning symptoms, leading to over 90% of diagnoses at an advanced stage, resulting in a grim prognosis, with less than a 20% 5-year survival rate.

METHOD

Metabolic features of 276 GCA and 588 healthy controls were characterized through a widely-targeted metabolomics by UPLC-MS/MS analysis. This study encompasses a joint pathway analysis utilizing identified metabolites, survival analysis in both early and advanced stages, as well as high and negative and low expression of HER2 immunohistochemistry staining. Machine learning techniques and Cox regression models were employed to construct a diagnostic panel.

RESULTS

A total of 25 differential metabolites were consistently identified in both discovery and validation sets based on criteria of p < 0.05, (VIP) ≥ 1, and FC ≥ 2 or FC ≤ 0.5. Early-stage GCA patients exhibited a more favorable prognosis compared to those in advanced stages. HER2 overexpression was associated with a more positive outcome compared to the negative and low expression groups. Metabolite panel demonstrated a robust diagnostic performance with AUC of 0.869 in discovery set and 0.900 in validation set.

CONCLUSIONS

A total of 25 common and stable differential metabolites may hold promise as liquid non-invasive indicators for GCA diagnosis. HER2 may function as a tumor suppressor gene in GCA, as its overexpression is associated with improved survival. The downregulation of bile acid metabolism in GCA may offer valuable theoretical insights and innovative approaches for precision-targeted treatments in GCA patients.

DNA methylation drives a new path in gastric cancer early detection: Current impact and prospects

Gastric cancer (GC) is one of the most common and deadly cancers worldwide. Early detection offers the best chance for curative treatment and reducing its mortality. However, the optimal population-based early screening for GC remains unmet. Aberrant DNA methylation occurs in the early stage of GC, exhibiting cancer-specific genetic and epigenetic changes, and can be detected in the media such as blood, gastric juice, and feces, constituting a valuable biomarker for cancer early detection. Furthermore, DNA methylation is a stable epigenetic alteration, and many innovative methods have been developed to quantify it rapidly and accurately. Nonetheless, large-scale clinical validation of DNA methylation serving as tumor biomarkers is still lacking, precluding their implementation in clinical practice. In conclusion, after a critical analysis of the recent existing literature, we summarized the evolving roles of DNA methylation during GC occurrence, expounded the newly discovered noninvasive DNA methylation biomarkers for early detection of GC, and discussed its challenges and prospects in clinical applications.

Identification of plasma proteomic signatures associated with the progression of cardia gastric cancer and precancerous lesions

Objective

Considering that there are no effective biomarkers for the screening of cardia gastric cancer (CGC), we developed a noninvasive diagnostic approach, employing data-independent acquisition (DIA) proteomics to identify candidate protein markers.

Methods

Plasma samples were obtained from 40 subjects, 10 each for CGC, cardia high-grade dysplasia (CHGD), cardia low-grade dysplasia (CLGD), and healthy controls. Proteomic profiles were obtained through liquid chromatography-mass spectrometry (LC-MS/MS-based DIA proteomics. Candidate plasma proteins were identified by weighted gene co-expression network analysis (WGCNA) combined with machine learning and further validated by the Human Protein Atlas (HPA) database. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of the biomarker panel.

Results

There was a clear distinction in proteomic features among CGC, CHGD, CLGD, and the healthy controls. According to the WGCNA, we found 42 positively associated and 164 inversely associated proteins related to CGC progression and demonstrated several canonical cancer-associated pathways. Combined with the results from random forests, LASSO regression, and immunohistochemical results from the HPA database, we identified three candidate proteins (GSTP1, CSRP1, and LY6G6F) that could together distinguish CLGD (AUC = 0.91), CHGD (AUC = 0.99) and CGC (AUC = 0.98) from healthy controls with excellent accuracy.

Conclusions

The panel of protein biomarkers showed promising diagnostic potential for CGC and precancerous lesions. Further validation and a larger-scale study are warranted to assess its potential clinical applications, suggesting a potential avenue for CGC prevention in the future.

Neural network-based prognostic predictive tool for gastric cardiac cancer: the worldwide retrospective study

BACKGROUNDS

The incidence of gastric cardiac cancer (GCC) has obviously increased recently with poor prognosis. It's necessary to compare GCC prognosis with other gastric sites carcinoma and set up an effective prognostic model based on a neural network to predict the survival of GCC patients.

METHODS

In the population-based cohort study, we first enrolled the clinical features from the Surveillance, Epidemiology and End Results (SEER) data (n = 31,397) as well as the public Chinese data from different hospitals (n = 1049). Then according to the diagnostic time, the SEER data were then divided into two cohorts, the train cohort (patients were diagnosed as GCC in 2010-2014, n = 4414) and the test cohort (diagnosed in 2015, n = 957). Age, sex, pathology, tumor, node, and metastasis (TNM) stage, tumor size, surgery or not, radiotherapy or not, chemotherapy or not and history of malignancy were chosen as the predictive clinical features. The train cohort was utilized to conduct the neural network-based prognostic predictive model which validated by itself and the test cohort. Area under the receiver operating characteristics curve (AUC) was used to evaluate model performance.

RESULTS

The prognosis of GCC patients in SEER database was worse than that of non GCC (NGCC) patients, while it was not worse in the Chinese data. The total of 5371 patients were used to conduct the model, following inclusion and exclusion criteria. Neural network-based prognostic predictive model had a satisfactory performance for GCC overall survival (OS) prediction, which owned 0.7431 AUC in the train cohort (95% confidence intervals, CI, 0.7423-0.7439) and 0.7419 in the test cohort (95% CI, 0.7411-0.7428).

CONCLUSIONS

GCC patients indeed have different survival time compared with non GCC patients. And the neural network-based prognostic predictive tool developed in this study is a novel and promising software for the clinical outcome analysis of GCC patients.

A systematic review and meta-analysis on the relative and attributable risk of Helicobacter pylori infection and cardia and non-cardia gastric cancer

INTRODUCTION

This study aimed to update the association between Helicobacter pylori (H. pylori) infection and gastric cancer (GC).

METHODS

We searched PubMed, Embase, and Cochrane Library from 1990 to December 2021 to identify prospective studies. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were summarized to validate the relationship between H. pylori infection and GC.

RESULTS

Including 27 studies, findings indicated a strong link between H. pylori and non-cardia gastric cancer (NCGC) in both Europe/North America (OR=5.37, 95%CI:4.39-6.57) and Asia (OR = 2.50, 95%CI:1.89-3.32), and a positive association with cardia gastric cancer (CGC) in Asia (OR = 1.74, 95%CI:1.38-2.19), but an inverse association in European/American populations (OR = 0.64, 95%CI: 0.51 to 0.79). Furthermore, the strength of association was greater in studies that detected H. pylori by immunoblotting versus ELISA, and also in studies testing for H. pylori detection further back in time prior to cancer diagnosis (Ptrend<0.05). Approximately 79% of NCGC in Asia and 87% in Europe/North America, along with 62% of CGC in Asia, could be attributable to H. pylori infection.

CONCLUSIONS

The meta-analysis supports the significant attributable risk of H. pylori infection for GC and underscores the potential impact of targeting H. pylori in GC prevention programs.

PROSPERO REGISTRATION

CRD42021274120.

Linked color imaging-based endoscopic grading of gastric intestinal metaplasia and histological gastritis staging in the assessment of gastric cancer risk

OBJECTIVE

To evaluate the value and compare the effectiveness of linked color imaging-based endoscopic grading of gastric intestinal metaplasia (LCI-EGGIM) and operative link on gastric intestinal metaplasia (OLGIM) in risk stratification of early gastric cancer (EGC).

METHODS

Eighty-one patients with EGC who underwent endoscopic submucosal dissection were included. The general data and EGC-related risk factors of all participants were recorded. LCI-EGGIM and OLGIM were used for both groups.

RESULTS

The number of patients with LCI-EGGIM score ≥ 5 was significantly higher in the EGC group than in the control group (58.02% vs. 12.35%, p < .001). Furthermore, the number of patients with OLGIM stage III/IV in the EGC group was significantly higher than that in the control group (56.79% vs. 7.41%, p < .001). Multivariate analysis showed that OLGIM stage III/IV (adjusted odds ratio [AOR]: 29.74, 95% CI: 7.49-117.94) and LCI-EGGIM score ≥ 5 (AOR: 12.33, 95% CI: 3.71-41.02) were significantly associated with EGC. There was no significant difference in the area under the receiver operating characteristic curve between LCI-EGGIM and OLGIM in predicting the risk of EGC (0.74 vs. 0.77, p = .1116).

CONCLUSION

OLGIM and LCI-EGGIM can be used and have the same value for predicting the risk stratification of EGC in patients with gastric intestinal metaplasia.

Association Between Serum Midkine Level and Gastric Precancerous Lesion in Patients with Gastritis

Background

Gastric cancer is the fifth most common malignancy and the third highest cancer-related mortality worldwide after lung and colorectal cancers. The gastric carcinogenesis is started with precancerous lesion. Prompt diagnosis and management of gastric precancerous lesion may prevent disease progression. Midkine is a growth factor associated with various cancers and proposed as a marker for detecting gastric precancerous lesion.

Objective

The aim of the study is to determine the association between serum midkine level and gastric precancerous lesion in patients with gastritis.

Methods

A cross sectional study was conducted at Haji Adam Malik general hospital. Subjects were obtained by consecutive sampling. Inclusion criteria were patients aged 18 years or older, diagnosed with gastritis from gastroscopy and histopathology results, and willing to cooperate in the study. Each subjects underwent interview and endoscopic examination. Serum midkine level was determined using enzyme-linked immunosorbent assay (ELISA) method. Chi square, receiver operating characteristic (ROC) curve, and logistic regression tests were applied.

Results

A total of 160 subjects were enrolled with 29.4% had gastric precancerous lesion. Serum midkine level was associated with gastric premalignant lesion. Cut off point for serum midkine level was 252 pg/mL with area under the curve of 0.816 (p<0.001). It's sensitivity, specificity, and accuracy in diagnosing gastric precancerous lesion were 74.5%, 71.7%, and 72.5%, respectively. Helicobacter pylori infection, high serum midkine level, heavy alcohol drinker, and family history of gastric cancer were risk factors for gastric precancerous lesion.

Conclusion

Serum midkine level is associated with gastric premalignant lesion in patients with gastritis and has good diagnostic values.