OBJECTIVES: To develop a risk prediction model for the transformation of chronic atrophic gastritis to high-grade intraepithelial neoplasia (HGIN) based on traditional Chinese medicine (TCM) syndrome patterns. METHODS: Clinical data of 201 chronic atrophic gastritis patients who visited the Second People's Hospital Affiliated to Fujian University of Traditional Chinese Medicine and Dong'erhuan Branch between January 2022 and March 2023 were retrospectively analyzed, including 32 patients with HGIN (HGIN group) and 169 patients with moderate and severe chronic atrophic gastritis (non-HGIN group). The information of demographic characteristics, dietary habits, lifestyle factors, social and psychosocial factors, family history of tumors, medical history and comorbidities, long-term medication, endoscopic findings, histopathological examination results, as well as TCM syndrome types were collected. Potential HGIN risk factors were screened using LASSO regression, and the significant risk factors for establishing an HGIN risk prediction model were identified using logistic regression analysis. The final model was visually presented using a nomogram, and its diagnostic performance was evaluated through receiver operating characteristic curve analysis. RESULTS: Spleen-stomach Qi deficiency was the most common TCM syndrome in both HGIN and non-HGIN groups. LASSO-logistic regression model analysis showed that heavy alcohol consumption (X1), syndrome of static blood in stomach collaterals (X2), low-grade intraepithelial neoplasia (X3), high-salt diet (X4), and age (X5) were independent risk factors related to the occurrence of HGIN, and the predictive model was ln［P/(1－P)］=2.159X1+2.230X2+1.664X3+2.070X4+0.122X5- 11.096. The model demonstrated good discriminative ability, calibration, and goodness-of-fit, with area under the curve values of 0.940 and 0.891 in the training and validation sets, respectively. CONCLUSIONS The TCM syndrome of static blood in stomach collaterals shows correlation with the transformation from chronic atrophic gastritis to HGIN. The HGIN prediction model based on TCM syndrome patterns developed in the study demonstrates potential value in clinical application.
Humans ; Gastritis, Atrophic/diagnosis* ; Medicine, Chinese Traditional ; Retrospective Studies ; Female ; Male ; Middle Aged ; Stomach Neoplasms/diagnosis* ; Adult ; Risk Factors ; Carcinoma in Situ/diagnosis* ; Aged ; Nomograms ; Chronic Disease ; Logistic Models

Humans ; Biomarkers, Tumor/metabolism* ; Claudins/analysis* ; Consensus ; Immunohistochemistry/methods* ; Stomach Neoplasms/diagnosis*

OBJECTIVES: To investigate the role of SF3B3 in gastric cancer (GC) progression and prognosis and its possible mechanisms. METHODS: SF3B3 expression levels in pan-cancer and GC were analyzed using TIMER2.0, GEPIA, and UALCAN databases and validated using immunohistochemistry in GC tissues. Survival curves of GC patients were established using Kaplan-Meier Plotter and the data of a patient cohort our hospital. The independent risk factors for 5-year postoperative survival were identified using Cox regression, and their predictive values were evaluated using ROC analysis. SF3B3-associated biological processes were predicted by bioinformatics enrichment analyses. In GC HGC-27 cells, the effects of lentivirus-mediated SF3B3 knockdown and overexpression on cell proliferation and migration were investigated, and the changes in the key glycolytic proteins and extracellular acidification rate (ECAR) were detected. The influence of SF3B3 expression level on tumorigenesis and glycolytic protein expression in vivo were evaluated in a nude mouse xenograft model. RESULTS: High expression of SF3B3 in GC was associated with poor patient prognosis (P<0.05). The factors affecting 5-year survival outcomes following gastric oncological resection included high SF3B3 expression, a CEA level ≥5μg/L, a CA19-9 level ≥37 kU/L, tumor stage T3-4, and lymph node metastasis stage N2-3 (P<0.05). Bioinformatics analysis showed significant enrichment of SF3B3 in glycolysis. In HGC-27 cells, SF3B3 knockdown significantly inhibited while SF3B3 overexpression enhanced cell proliferation, migration, and invasion. SF3B3 knockdown obviously decreased the expressions of HK2, PKM2 and LDHA proteins and ECAR in HGC-27 cells, whereas SF3B3 overexpression produced the opposite effect. In nude mouse xenograft models, SF3B3 knockdown significantly reduced tumor mass and downregulated expression of HK2, PKM2 and LDHA proteins, and SF3B3 overexpression induced the opposite changes. CONCLUSIONS SF3B3 overexpression is associated with poor prognosis of GC patients and promotes GC cell proliferation, migration and invasion possibly by enhancing glycolysis.
Stomach Neoplasms/diagnosis* ; Humans ; Cell Proliferation ; Prognosis ; Animals ; Mice, Nude ; Cell Line, Tumor ; Mice ; Cell Movement ; Male ; Female

Gastric tumors are neoplastic lesions that occur in the stomach, posing a great threat to human health. Gastric cancer represents the malignant form of gastric tumors, and early detection and treatment are crucial for patient recovery. Endoscopic examination is the primary method for diagnosing gastric tumors. Deep learning techniques can automatically extract features from endoscopic images and analyze them, significantly improving the detection rate of gastric cancer and serving as an important tool for auxiliary diagnosis. This paper reviews relevant literature in recent years, presenting the application of deep learning methods in the classification, object detection, and segmentation of gastric tumor endoscopic images. In addition, this paper also summarizes several computer-aided diagnosis (CAD) systems and multimodal algorithms related to gastric tumors, highlights the issues with current deep learning methods, and provides an outlook on future research directions, aiming to promote the clinical application of deep learning methods in the endoscopic diagnosis of gastric tumors.
Humans ; Stomach Neoplasms/diagnostic imaging* ; Deep Learning ; Diagnosis, Computer-Assisted/methods* ; Gastroscopy/methods* ; Algorithms

OBJECTIVE: To investigate the clinicopathological features of Helicobacter pylori (Hp)-negative early gastric cancer. METHODS: The clinicopathological data of 30 cases of Hp-negative early gastric cancer were collected retrospectively at Pingdingshan Medical District, 989 Hospital of PLA Joint Logistics Support Force, and Beijing Chaoyang Hospital, Capital Medical University, from 2009 to 2021, and the histomorphological characteristics and immunophenotype were observed, and combined with the literature to explore. RESULTS: The median age of 30 patients was 58.5 years (range: 21-80 years), including 13 males and 17 females. The upper part of the stomach was 13 cases, the middle part of the sto-mach was 9 cases, and the lower part of the stomach was 8 cases. The median diameter of the tumor was 11 mm (range: 1-30 mm). According to the Paris classification, 9 cases were 0-Ⅱa, 7 cases were 0-Ⅱb, and 14 cases were 0-Ⅱc. Endoscopic examination showed that 18 cases of lesions were red, 12 cases of lesions were faded or white, and microvascular structures and microsurface structures were abnormal. In all the cases, collecting venules were regularly arranged in the gastric body and corner mucosa. There were 18 cases of well differentiated adenocarcinoma in the mucosa. The tumor presented glandular tubular-like and papillary structure, with dense glands and disordered arrangement; the cells were cuboidal or columnar, with increased nuclear chromatin and loss of nuclear polarity, and most of them expressed gastric mucin. Signet-ring cell carcinoma was found in 7 cases, all the cancer tissues were composed of signet-ring cells, and the cancer cells were mainly distributed in the middle layer to the surface layer of mucosa. Gastric oxyntic gland adenoma (gastric adenocarcinoma of the fundic gland type confined to mucosa) in 2 cases, gastric adenocarcinoma of the fundic gland type in 2 cases, and gastric adenocarcinoma of fundic gland mucosa type in 1 case. The tumor tissue was composed of branching tubular glands, except 1 case of mucosal surface epithelium was partially neoplastic, the other 4 cases of mucosal surface epi-thelium were all non-neoplastic; the cells were arranged in a single layer, and the nucleus was close to the basal side, and the nucleus was only slightly atypical. Pepsinogen I and H⁺/K⁺ ATPase were positive in 5 cases of gastric fundus gland type tumors, and 1 case of foveolar-type tumor cells at the surface and depth of mucosa showed MUC5AC positive. The gastric mucosa adjacent to cancer was generally normal in all cases, without atrophy, intestinal metaplasia and Hp. CONCLUSION Hp-negative early gastric cancer is a heterogeneous disease group with various histological types, and tubular adenocarcinoma and signet-ring cell carcinoma are common. Tubular adenocarcinoma mostly occurs in the elderly and the upper to middle part of the stomach, while signet-ring cell carcinoma mostly occurs in young and middle-aged people and the lower part of the stomach. Gastric neoplasm of the fundic gland type is relatively rare.
Male ; Aged ; Middle Aged ; Female ; Humans ; Young Adult ; Adult ; Aged, 80 and over ; Stomach Neoplasms/pathology* ; Helicobacter pylori ; Retrospective Studies ; Helicobacter Infections/diagnosis* ; Adenocarcinoma/pathology* ; Carcinoma, Signet Ring Cell/pathology*

Objective: To investigate the clinicopathological characteristics of reactive epithelial hyperplasia and dysplasia in the stomach, as well as the clinical value of mucin special staining and proliferating cell nuclear antigen (Ki-67) in distinguishing the two gastric lesions. Methods: The clinical pathological data of 63 patients with gastric reactive epithelial hyperplasia, 54 patients with low-grade dysplasia, and 63 patients with high-grade dysplasia diagnosed from May 2018 to May 2021 in Beijing Chaoyang Hospital, Capital Medical University, Beijing, China were analyzed. Alcian blue periodic acid Schiff (AB-PAS) and Ki-67 staining were performed to examine the mucin staining pattern, number of Ki-67 positive cells, Ki-67 staining patterns in the three groups of lesions, and histopathologic characteristics. Results: The positive rates of AB-PAS in the reactive epithelial hyperplasia and gastric dysplasia groups were 87.3%(55/63) and 10.3%(12/117), respectively. The expression of AB-PAS in the reactive epithelial hyperplasia was gradually increased from the base to the surface of the epithelium. In low-grade dysplasia and high-grade dysplasia, there was no mucin present in the dysplasia epithelium. The difference between the two groups was statistically significant (P<0.01). The positive rate of Ki-67 in the epithelial reactive hyperplasia (>10%) was 81.0% (51/63), and the positive cells were mainly located in the neck and middle parts of the mucosal glands (58/63, 92.1%). In the low-grade dysplasia group, the positive rate of Ki-67 (>10%) was 90.7%(49/54); the positive cells were mainly located in the upper mucosa (33/54, 61.1%), showing a banded distribution pattern; in the high-grade dysplasia group, the positive rate (>10%) was 95.2%(60/63), and the positive cells were mainly located in the whole mucosa (49/63, 77.8%), showing a diffuse/diffuse scattered distribution pattern. The three groups had statistically different rates and distribution patterns of Ki-67 expression (P<0.01). Conclusion: The gastric epithelial reactive hyperplasia and dysplasia can be differentiated using clinicopathological features, AB-PAS staining and Ki-67 expression pattern.
Alcian Blue ; Humans ; Hyperplasia ; Ki-67 Antigen/metabolism* ; Periodic Acid ; Staining and Labeling ; Stomach Neoplasms/diagnosis*

Gastric cancer with positive peritoneal cytology is a hotspot in the study of gastric cancer, and its prognosis is poor. Intraperitoneal free cancer cells may be associated with cancer cells migration, invasion and metastasis. Tumor T stage, peritoneal metastasis, lymph node metastasis, low histological differentiation, linitis plastica, adenocarcinoma of esophagogastric junction, and operation are the clinicopathological risk factors of gastric cancer with positive peritoneal cytology. Currently, the acquisition of free cancer cells is mainly through diagnostic laparoscopy combined with peritoneal lavage, and cytopathological examination is gold standard for diagnosis. Its treatment strategies are not in consensus, including preoperative chemotherapy combined with radical resection, postoperative chemotherapy and peritoneal local treatment, which can prolong the survival of patients. At present, postoperative chemotherapy is often used in China, and the best treatment strategies remain to be further studied.
China ; Gastrectomy ; Humans ; Neoplasm Staging ; Peritoneal Lavage ; Peritoneal Neoplasms/diagnosis* ; Prognosis ; Retrospective Studies ; Stomach Neoplasms/surgery*

Due to the lack of typical symptoms and imaging findings, gastric gastrointestinal stromal tumor (GIST) is easy to be misdiagnosed as other gastric tumors clinically. In clinical practice, clinicians should adopt the multidisciplinary team model, fully understand the characteristics of gastric GIST, grasp the key points of its differential diagnosis from other gastric tumors to achieve precise diagnosis and treatment. This paper analyzes the causes of misdiagnosis and elucidates the differential diagnosis of gastric GIST, aiming to improve the accuracy of preoperative diagnosis, reduce the misdiagnosis, and improve treatment outcomes.
Diagnosis, Differential ; Diagnostic Errors ; Gastrointestinal Stromal Tumors/diagnosis* ; Humans ; Stomach Neoplasms/diagnosis* ; Treatment Outcome

Objective: Contrast-enhanced CT is an important method of preoperative diagnosis and evaluation for the malignant potential of gastric submucosal tumor (SMT). It has a high diagnostic accuracy rate in differentiating gastric gastrointestinal stromal tumor (GIST) with a diameter greater than 5 cm from gastric benign SMT. This study aimed to use deep learning algorithms to establish a diagnosis model (GISTNet) based on contrast-enhanced CT and evaluate its diagnostic value in distinguishing gastric GIST with a diameter ≤ 5 cm and other gastric SMT before surgery. Methods: A diagnostic test study was carried out. Clinicopathological data of 181 patients undergoing resection with postoperative pathological diagnosis of gastric SMT with a diameter ≤ 5 cm at Department of Gastrointestinal Surgery of Renji Hospital from September 2016 to April 2021 were retrospectively collected. After excluding 13 patients without preoperative CT or with poor CT imaging quality, a total of 168 patients were enrolled in this study, of whom, 107 were GIST while 61 were benign SMT (non-GIST), including 27 leiomyomas, 24 schwannomas, 6 heterotopic pancreas and 4 lipomas. Inclusion criteria were as follows: (1) gastric SMT was diagnosed by contrast-enhanced CT before surgery; (2) preoperative gastroscopic examination and biopsy showed no abnormal cells; (3) complete clinical and pathological data. Exclusion criteria were as follows: (1) patients received anti-tumor therapy before surgery; (2) without preoperative CT or with poor CT imaging quality due to any reason; (3) except GIST, other gastric malignant tumors were pathologically diagnosed after surgery. Based on the hold-out method, 148 patients were randomly selected as the training set and 20 patients as the test set of the GISTNet diagnosis model. After the GISTNet model was established, 5 indicators were used for evaluation in the test set, including sensitivity, specificity, positive predictive value, negative predictive value and the area under the receiver operating curve (AUC). Then GISTNet diagnosis model was compared with the GIST-risk scoring model based on traditional CT features. Besides, in order to compare the accuracy of the GISTNet diagnosis model and the imaging doctors in the diagnosis of gastric SMT imaging, 3 radiologists with 3, 9 and 19 years of work experience, respectively, blinded to clinical and pathological information, tested and judged the samples. The accuracy rate between the three doctors and the GISTNet model was compared. Results: The GISTNet model yielded an AUC of 0.900 (95% CI: 0.827-0.973) in the test set. When the threshold value was 0.345, the sensitivity specificity, positive and negative predictive values of the GISTNet diagnosis model was 100%, 67%, 75% and 100%, respectively. The accuracy rate of the GISTNet diagnosis model was better than that of the GIST-risk model and the manual readings from two radiologists with 3 years and 9 years of work experience (83% vs. 75%, 60%, 65%), and was close to the manual reading of the radiologist with 19 years of work experience (83% vs. 80%). Conclusion: The deep learning algorithm based on contrast-enhanced CT has favorable and reliable diagnostic accuracy in distinguishing gastric GIST with a diameter ≤ 5 cm and other gastric SMT before operation.
Deep Learning ; Diagnosis, Differential ; Gastrointestinal Stromal Tumors/diagnostic imaging* ; Humans ; Retrospective Studies ; Stomach Neoplasms/diagnostic imaging* ; Tomography, X-Ray Computed

BACKGROUND: Endoscopic biopsy can underestimate gastric malignancies as low-grade intraepithelial neoplasia (LGIN). Definitively diagnosed LGIN would progress. This study aimed to evaluate predictive factors to identify malignancies misdiagnosed as LGIN by biopsy and LGIN at high risk of progression. METHODS: The clinical records of patients diagnosed with gastric LGIN by endoscopic biopsy who underwent at least two endoscopies during the first year of follow-up between 2007 and 2017 were retrospectively collected. Three endoscopists reviewed photographs of the initial endoscopy, described lesion characteristics, and made endoscopic diagnoses. Logistic regression was used to analyze predictors to identify malignancies underestimated as LGIN. A receiver operating characteristic curve was used to evaluate the diagnostic accuracy of these predictors. Patient clinical outcomes of follow-up >1 year were collected. Kaplan-Meier estimates with log-rank tests and Cox proportional hazards regression were used to analyze predictors of progression. RESULTS: Overall, 48 of 182 (26.4%) patients were proven to have malignancies. A single lesion, a large lesion size, and marked intestinal metaplasia (IM) were independent predictors of initially misdiagnosed malignancies. The area under the curve of these predictors was 0.871, with a sensitivity of 68.7% and specificity of 92.5%. Twelve of 98 patients (12.2%) progressed during the 33-month median follow-up period. A whitish appearance, irregular margins, marked IM, and histological diagnosis of LGIN more than twice within the first year were predictors for progression. CONCLUSIONS Lesions diagnosed as LGIN by biopsy with marked IM and other predictors above should be prudently treated for high potential to be malignancies or progress. Endoscopic follow-up with repeated biopsies within the first year is recommended.
Biopsy ; Carcinoma in Situ ; Endoscopy ; Humans ; Prognosis ; Retrospective Studies ; Stomach Neoplasms/diagnosis*