Diagnosis to dissection: AI's role in early detection and surgical intervention for gastric cancer.

Gastric cancer remains a formidable health challenge worldwide; early detection and effective surgical intervention are critical for improving patient outcomes. This comprehensive review explores the evolving landscape of gastric cancer management, emphasizing the significant contributions of artificial intelligence (AI) in revolutionizing both diagnostic and therapeutic approaches. Despite advancements in the medical field, the subtle nature of early gastric cancer symptoms often leads to late-stage diagnoses, where survival rates are notably decreased. Historically, the treatment of gastric cancer has transitioned from palliative care to surgical resection, evolving further with the introduction of minimally invasive surgical (MIS) techniques. In the current era, AI has emerged as a transformative force, enhancing the precision of early gastric cancer detection through sophisticated image analysis, and supporting surgical decision-making with predictive modeling and real-time preop-, intraop-, and postoperative guidance. However, the deployment of AI in healthcare raises significant ethical, legal, and practical challenges, including the necessity for ongoing professional education and the development of standardized protocols to ensure patient safety and the effective use of AI technologies. Future directions point toward a synergistic integration of AI with clinical best practices, promising a new era of personalized, efficient, and safer gastric cancer management.

Gastric Metastasis Mimicking Early Gastric Cancer from Invasive Ductal Carcinoma of the Breast: Case Report and Literature Review.

Backgound and Objectives: Gastric metastasis from invasive ductal breast cancer (BC) is rare. It mainly occurs in patients with lobular BC. The occurrence of multiple metastases is typically observed several years after the primary diagnosis. Endoscopic findings of gastric metastasis of the BC were usually the linitis plastic type. Case presentation: A 72-year-old women who underwent right modified radical mastectomy (MRM) 10 month ago was referred after being diagnosed with early gastric cancer (EGC) during systemic chemotherapy. EGC type I was found at gastric fundus, and pathologic finding showed poorly differentiated adenocarcinoma. Metachronous double primary tumor EGC was considered. Management and Outcome: A laparoscopic total gastrectomy was performed, and postoperative pathology revealed submucosa invasion and two lymph node metastases. A pathologic review that focused on immunohistochemical studies of selected antibodies such as GATA binding protein 3 (GATA3), gross cystic disease fluid protein-15 (GCDFP-15), cytokeratin 7 (CK7) was performed again, comparing previous results. As a result, gastric metastasis from BC was diagnosed. After totally laparoscopic total gastrectomy, palliative first-line chemotherapy with paclitaxel/CDDP was performed. Two months after gastrectomy, she was diagnosed with para-aortic lymph node metastasis and multiple bone metastases. She expired six months after gastrectomy. Conclusions: Gastric metastasis from invasive ductal carcinoma of the breast, which is clinically manifested as EGC, is a very rare condition. If there is a history of BC, careful pathological review will be required.

Optimal number of images and 2-year interval affect cancer detection in screening esophagogastroduodenoscopy: An observational study.

We aimed to identify quality indicator for esophagogastroduodenoscopy for detecting upper gastrointestinal (UGI) cancer. Data from 43,526 consecutive health checkups from August 2012 to January 2022 were retrospectively collected. The study ultimately analyzed 42,387 examinations by 12 endoscopists who performed more than 1000 examinations, including all cancers detected. These endoscopists were classified either into fast/slow group based on their mean examination time for a normal finding of esophagogastroduodenoscopy during their first year of the examination, or small/large group based on number of endoscopic images, respectively. The association between UGI cancer detection rate and examination time or the number of images was analyzed, using 5 minutes or 50 images as cutoff values. The detection rate of overall (8 pharyngeal, 39 esophageal, 69 gastric) cancers in the fast, slow, small, and large groups were 0.17%, 0.32%, 0.21%, and 0.31%, respectively. On multivariable analysis, endoscopists in the fast group or the small group were less likely to detect overall UGI cancer (OR: 0.596, 95% CI: 0.373-0.952, P = .030; OR: 0.652, 95% CI: 0.434-0.979, P = .039). Additionally, repeated endoscopy within 2 years had a higher overall cancer detection rate, compared with repeated screening after 2 years. In a sub-analysis, a significant negative relationship was found between the detection rate of gastric cancer and the number of gastric images < 35 (OR: 0.305, 95% CI: 0.189-0.492, P = .000). There was also a negative correlation trend between the detection rate of pharyngeal and esophageal cancers and the number of esophageal images < 11 (OR: 0.395, 95% CI: 0.156-1.001, P = .050). The optimal number of images and screening 2-year interval are considered useful quality indicators for detecting UGI cancer. This study also suggests that a total of 50 images, or 35 images of the stomach are suitable for detecting UGI cancer, or gastric cancer, during screening endoscopy.

Diagnostic Usefulness of p53 Immunostaining in Gastric Cancer and Dysplasia: A Real-world Clinical Experience.

BACKGROUND/AIM: Gastric cancer and its precancerous lesions represent a significant public health concern. A subset of gastric cancers exhibits mutations in the TP53 gene, often accompanying distinctive morphologic alterations. This study aimed to assess the diagnostic efficacy of p53 immunostaining in real-world clinical settings. PATIENTS AND METHODS: A retrospective analysis was conducted on 50 cases of gastric tumors and tumor-like lesions, wherein p53 immunostaining played a pivotal diagnostic role. The staining pattern of p53 was examined in conjunction with clinicopathologic parameters. RESULTS: Mutant p53 staining pattern demonstrated a significant association with high-grade nuclear atypia (p<0.001), high-grade dysplasia, and tubular adenocarcinoma (p<0.001), as well as microsatellite instability status (p=0.034). Furthermore, the diagnostic utility of p53 immunostaining was evident in scenarios where: 1) biopsy specimens contained few tumor cells, 2) pathologic evaluation of resection margins was limited by cauterization artifacts, and 3) distinction between low-grade and high-grade gastric dysplasia was challenging. CONCLUSION: P53 immunostaining can be helpful for the diagnosis of gastric tumor and tumor-like lesions, and accurate pathologic margin evaluation, particularly in lesions demonstrating intestinal-type differentiation and some degree of nuclear atypia.

Development and validation of an inflammatory biomarkers model to predict gastric cancer prognosis: a multi-center cohort study in China.

BACKGROUND: Inflammatory factors have increasingly become a more cost-effective prognostic indicator for gastric cancer (GC). The goal of this study was to develop a prognostic score system for gastric cancer patients based on inflammatory indicators. METHODS: Patients' baseline characteristics and anthropometric measures were used as predictors, and independently screened by multiple machine learning(ML) algorithms. We constructed risk scores to predict overall survival in the training cohort and tested risk scores in the validation. The predictors selected by the model were used in multivariate Cox regression analysis and developed a nomogram to predict the individual survival of GC patients. RESULTS: A 13-variable adaptive boost machine (ADA) model mainly comprising tumor stage and inflammation indices was selected in a wide variety of machine learning models. The ADA model performed well in predicting survival in the validation set (AUC = 0.751; 95% CI: 0.698, 0.803). Patients in the study were split into two sets - "high-risk" and "low-risk" based on 0.42, the cut-off value of the risk score. We plotted the survival curves using Kaplan-Meier analysis. CONCLUSION: The proposed model performed well in predicting the prognosis of GC patients and could help clinicians apply management strategies for better prognostic outcomes for patients.

[Surgical management of gastrointestinal stromal tumors of gastric origin]. / Prise en charge chirurgicale des tumeurs stromales gastro-intestinales d'origine gastrique.

Gastrointestinal Stromal Tumors (GISTs) account for 1 to 2% of gastrointestinal malignant tumors. They are characterized by overexpression of the tyrosine kinase (KIT). 60% of GISTs originate in the stomach. Managing them remains complex and varies depending on several factors such as location, size, molecular biology, type of clinical presentation, and the risks/benefits of surgical treatment. Surgery remains the only curative treatment, while tyrosine kinase inhibitors have demonstrated their efficacy as systemic treatment in the perioperative context. Risk stratification for recurrence guides the choice of adjuvant treatment, with a recommended duration of 3 years for high-risk patients.

Les tumeurs stromales gastro-intestinales (GIST) constituent entre 1 et 2 % des tumeurs malignes gastro-intestinales. Elles se caractérisent par une surexpression de la tyrosine kinase (KIT). 60 % des GIST sont d'origine gastrique. Leur prise en charge reste complexe et varie selon plusieurs facteurs tels que la localisation, la taille, la biologie moléculaire, le type de manifestation clinique et les risques/bénéfices du traitement chirurgical. La chirurgie demeure le seul traitement curatif, tandis que les inhibiteurs de tyrosine kinase ont démontré leur efficacité comme traitement systémique dans le contexte périopératoire. La stratification du risque de récidive guide le choix du traitement adjuvant, avec une durée recommandée de 3 ans pour les patients à haut risque.

Bioinformatics Analysis and Validation of Potential Markers Associated with Prediction and Prognosis of Gastric Cancer.

Gastric cancer (GC) is one of the most common cancers worldwide. Most patients are diagnosed at the progressive stage of the disease, and current anticancer drug advancements are still lacking. Therefore, it is crucial to find relevant biomarkers with the accurate prediction of prognoses and good predictive accuracy to select appropriate patients with GC. Recent advances in molecular profiling technologies, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, have enabled the approach of GC biology at multiple levels of omics interaction networks. Systemic biological analyses, such as computational inference of "big data" and advanced bioinformatic approaches, are emerging to identify the key molecular biomarkers of GC, which would benefit targeted therapies. This review summarizes the current status of how bioinformatics analysis contributes to biomarker discovery for prognosis and prediction of therapeutic efficacy in GC based on a search of the medical literature. We highlight emerging individual multi-omics datasets, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics, for validating putative markers. Finally, we discuss the current challenges and future perspectives to integrate multi-omics analysis for improving biomarker implementation. The practical integration of bioinformatics analysis and multi-omics datasets under complementary computational analysis is having a great impact on the search for predictive and prognostic biomarkers and may lead to an important revolution in treatment.

Multi-dimensional cell-free DNA-based liquid biopsy for sensitive early detection of gastric cancer.

BACKGROUND: Gastric cancer is the fifth most common cancer type. Most patients are diagnosed at advanced stages with poor prognosis. A non-invasive assay for the detection of early-stage gastric cancer is highly desirable for reducing associated mortality. METHODS: We collected a prospective study cohort of 110 stage I-II gastric cancer patients and 139 non-cancer individuals. We performed whole-genome sequencing with plasma samples and profiled four types of cell-free DNA (cfDNA) characteristics, fragment size pattern, copy number variation, nucleosome coverage pattern, and single nucleotide substitution. With these differential profiles, we developed an ensemble model to detect gastric cancer signals. Further, we validated the assay in an in-house first validation cohort of 73 gastric cancer patients and 94 non-cancer individuals and an independent second validation cohort of 47 gastric cancer patients and 49 non-cancer individuals. Additionally, we evaluated the assay in a hypothetical 100,000 screening population by Monte Carlo simulation. RESULTS: Our cfDNA-based assay could distinguish early-stage gastric cancer from non-cancer at an AUROC of 0.962 (95% CI: 0.942-0.982) in the study cohort, 0.972 (95% CI: 0.953-0.992) in the first validation cohort and 0.937 (95% CI: 0.890-0.983) in the second validation cohort. The model reached a specificity of 92.1% (128/139) and a sensitivity of 88.2% (97/110) in the study cohort. In the first validation cohort, 91.5% (86/94) of non-cancer individuals and 91.8% (67/73) of gastric cancer patients were correctly identified. In the second validation cohort, 89.8% (44/49) of non-cancer individuals and 87.2% (41/47) of gastric cancer patients were accurately classified. CONCLUSIONS: We introduced a liquid biopsy assay using multiple dimensions of cfDNA characteristics that could accurately identify early-stage gastric cancer from non-cancerous conditions. As a cost-effective non-invasive approach, it may provide population-wide benefits for the early detection of gastric cancer. TRIAL REGISTRATION: This study was registered on ClinicalTrials.gov under the identifier NCT05269056 on March 7, 2022.

PPIH acts as a potential predictive biomarker for patients with common solid tumors.

BACKGROUND: Our previous studies have indicated that mRNA and protein levels of PPIH are significantly upregulated in Hepatocellular Carcinoma (LIHC) and could act as predictive biomarkers for patients with LIHC. Nonetheless, the expression and implications of PPIH in the etiology and progression of common solid tumors have yet to be explored, including its potential as a serum tumor marker. METHODS: We employed bioinformatics analyses, augmented with clinical sample evaluations, to investigate the mRNA and protein expression and gene regulation networks of PPIH in various solid tumors. We also assessed the association between PPIH expression and overall survival (OS) in cancer patients using Kaplan-Meier analysis with TCGA database information. Furthermore, we evaluated the feasibility and diagnostic efficacy of PPIH as a serum marker by integrating serological studies with established clinical tumor markers. RESULTS: Through pan-cancer analysis, we found that the expression levels of PPIH mRNA in multiple tumors were significantly different from those in normal tissues. This study is the first to report that PPIH mRNA and protein levels are markedly elevated in LIHC, Colon adenocarcinoma (COAD), and Breast cancer (BC), and are associated with a worse prognosis in these cancer patients. Conversely, serum PPIH levels are decreased in patients with these tumors (LIHC, COAD, BC, gastric cancer), and when combined with traditional tumor markers, offer enhanced sensitivity and specificity for diagnosis. CONCLUSION: Our findings propose that PPIH may serve as a valuable predictive biomarker in tumor patients, and its secreted protein could be a potential serum marker, providing insights into the role of PPIH in cancer development and progression.

Gastroenteropancreatic neuroendocrine neoplasms: current development, challenges, and clinical perspectives.

Neuroendocrine neoplasms (NENs) are highly heterogeneous and potentially malignant tumors arising from secretory cells of the neuroendocrine system. Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are the most common subtype of NENs. Historically, GEP-NENs have been regarded as infrequent and slow-growing malignancies; however, recent data have demonstrated that the worldwide prevalence and incidence of GEP-NENs have increased exponentially over the last three decades. In addition, an increasing number of studies have proven that GEP-NENs result in a limited life expectancy. These findings suggested that the natural biology of GEP-NENs is more aggressive than commonly assumed. Therefore, there is an urgent need for advanced researches focusing on the diagnosis and management of patients with GEP-NENs. In this review, we have summarized the limitations and recent advancements in our comprehension of the epidemiology, clinical presentations, pathology, molecular biology, diagnosis, and treatment of GEP-NETs to identify factors contributing to delays in diagnosis and timely treatment of these patients.

Machine learning-driven SERS analysis platform for rapid and accurate detection of precancerous lesions of gastric cancer.

A novel approach is proposed leveraging surface-enhanced Raman spectroscopy (SERS) combined with machine learning (ML) techniques, principal component analysis (PCA)-centroid displacement-based nearest neighbor (CDNN). This label-free approach can identify slight abnormalities between SERS spectra of gastric lesions at different stages, offering a promising avenue for detection and prevention of precancerous lesion of gastric cancer (PLGC). The agaric-shaped nanoarray substrate was prepared using gas-liquid interface self-assembly and reactive ion etching (RIE) technology to measure SERS spectra of serum from mice model with gastric lesions at different stages, and then a SERS spectral recognition model was trained and constructed using the PCA-CDNN algorithm. The results showed that the agaric-shaped nanoarray substrate has good uniformity, stability, cleanliness, and SERS enhancement effect. The trained PCA-CDNN model not only found the most important features of PLGC, but also achieved satisfactory classification results with accuracy, area under curve (AUC), sensitivity, and specificity up to 100%. This demonstrated the enormous potential of this analysis platform in the diagnosis of PLGC.

Determination of Matrix Metalloproteinase 2 in Biological Samples Using a 3D Stochastic Microsensor Based on Graphene Oxide/AuNanoparticles/(Z)-N-(pyridin-4-yl-methyl) Octadec-9-enamide.

The levels of the MMPs in the biological samples of confirmed patients with gastric cancer are significantly elevated compared to those found in healthy people. Therefore, a novel 3D stochastic microsensor based on graphene oxide, modified with gold nanoparticles and (Z)-N-(pyridin-4-yl-methyl) octadec-9-enamide (namely N2-AuNP/GO), was designed for the determination of MMP-2 in biological samples, and validated for the screening tests of biological samples in order to be used for the early diagnosis of gastric cancer. The proposed sensor presents a low limit of quantification (1.00 × 10-22 g mL-1), high sensitivity (1.84 × 107 s-1 g-1 mL), and a wide working concentration range (1.00 × 10-22-1.00 × 10-7 g mL-1). Recovery values higher than 99.15% were recorded for the assay of MMP-2 in whole blood, gastric tissue tumors, saliva, and urine samples.

An Unexpected Lymphoma: A Rare Case of Primary Gastric Burkitt's Lymphoma.

Primary gastric Burkitt's lymphoma is an aggressive non-Hodgkin's lymphoma that has been rarely reported in the literature. The majority of primary gastric lymphomas are diffuse large B-cell lymphomas and mucosa-associated lymphoid tissue (MALT) lymphomas. Patients with primary gastric Burkitt's lymphoma can present with abdominal pain, hematemesis, melena, perforation, and obstruction. Diagnosis is made with a combination of clinical, radiological, and pathological findings. Treatment data are limited due to the limited cases reported. We present a case of a 47-year-old female who presented with diffuse abdominal pain, melena, and coffee-ground emesis that was diagnosed with primary gastric Burkitt's lymphoma following biopsies taken from a gastric ulcerated mass found on upper endoscopy.

Homocystein, Vitamin B12 and Folic Acid as Screening Biomarkers in Early Diagnosis and Gastric Cancer Monitoring.

Gastric cancer has been demonstrating a reduction in the number of cases over the past decades, largely attributed to advancements in public health practices and increased accessibility to educational initiatives for the general population. Nevertheless, it persists as the third leading cause of mortality globally among both men and women. These fatalities are typically associated with delayed disease detection. The current study assessed the levels of homocysteine, vitamin B12, and folic acid as a means of establishing a screening biomarker profile that could be integrated into routine testing protocols to facilitate swift diagnosis of the illness. A total of 207 control subjects and 207 individuals with gastric cancer were scrutinized, with biochemical measurements conducted using chemiluminescence for homocysteine, folic acid, and vitamin B12. The two groups were matched based on age, tumor location, subtype, tumor classification, presence of Epstein-Barr Virus infection (EBV), and Helicobacter pylori (H. pylori). Significant statistical variances were identified in the mean levels of the triad of substances among cancer patients when compared to the control group for all corresponding variables. In conclusion, our study indicated that analyzing the triad of homocysteine, vitamin B12, and folic acid holds diagnostic value for gastric cancer and could potentially serve as an effective screening marker for this type of cancer in the future.

Advances in Diagnostic, Staging, and Restaging Evaluation of Esophageal and Gastric Cancer.

The initial endoscopic and staging evaluation of esophagogastric cancers must be accurate and comprehensive in order to select the optimal therapeutic plan for the patient. Esophageal and gastric cancers (and treatment paradigms) are delineated by their proximity to the cardia (within 2 cm). The most frequent and important symptom that informs the initial staging evaluation is dysphagia, which is associated with at least cT3 or locally advanced disease. Endoscopic ultrasound is often needed if earlier stage disease is suspected, preferably in combination with endoscopic mucosal or submucosal resection or fine-needle aspiration of suspicious lymph nodes to enhance staging accuracy.

Machine learning models to predict submucosal invasion in early gastric cancer based on endoscopy features and standardized color metrics.

Conventional endoscopy is widely used in the diagnosis of early gastric cancers (EGCs), but the graphical features were loosely defined and dependent on endoscopists' experience. We aim to establish a more accurate predictive model for infiltration depth of early gastric cancer including a standardized colorimetric system, which demonstrates promising clinical implication. A retrospective study of 718 EGC cases was performed. Clinical and pathological characteristics were included, and Commission Internationale de l'Eclariage (CIE) standard colorimetric system was used to evaluate the chromaticity of lesions. The predicting models were established in the derivation set using multivariate backward stepwise logistic regression, decision tree model, and random forest model. Logistic regression shows location, macroscopic type, length, marked margin elevation, WLI color difference and histological type are factors significantly independently associated with infiltration depth. In the decision tree model, margin elevation, lesion located in the lower 1/3 part, WLI a*color value, b*color value, and abnormal thickness in enhanced CT were selected, which achieved an AUROC of 0.810. A random forest model was established presenting the importance of each feature with an accuracy of 0.80, and an AUROC of 0.844. Quantified color metrics can improve the diagnostic precision in the invasion depth of EGC. We have developed a nomogram model using logistic regression and machine learning algorithms were also explored, which turned out to be helpful in decision-making progress.

Hsa_Circ_0002762 may be a New Marker for the Gastric Cancer Diagnosis and Prognosis.

BACKGROUND: The global incidence and mortality rate of gastric carcinoma (GC) persists at elevated levels, often manifesting no overt symptoms in its early stages. Hsa_circ_0002762 has been identified as an important modulator in cervical cancer. This study aims to explore its role in the context of GC. METHODS: A quantitative real-time polymerase chain reaction (qPCR) was implemented to assess the expression level of hsa_circ_0002762. The over-expression was confirmed through an examination of 28 cases of gastric cancer and their corresponding adjacent tissues. In addition, plasma samples from 78 healthy individuals, from 45 benign gastritis patients, and from 106 gastric cancer patients were collected, and the diagnostic efficacy was assessed by analyzing the receiver operating characteristic (ROC) curve. Simultaneously, postoperative specimens from 36 GC cases were collected, and a Kaplan-Meier survival analysis curve was used to evaluate the prognosis of GC. RESULTS: The study revealed an up-regulation in the expression of hsa_circ_0002762 in gastric cancer plasma and tissues. The area under the receiver operating characteristic (ROC) curve for serum hsa_circ_0002762 was 0.784 (95% CI: 0.719 - 0.851), indicating a higher diagnostic efficiency compared to CEA (0.687, 95% CI: 0.611 - 0.763) and CA199 (0.699, 95% CI: 0.625 - 0.744). Combining these three biomarkers demonstrated an increased sensitivity in the diagnostic effectiveness. Finally, postoperative dynamic monitoring revealed a practical utility in predicting the clinical prognosis using serum has_circ_0002762. CONCLUSIONS: The findings from our study suggest that hsa_circ_0002762 holds promise as a novel diagnostic and prognostic marker for individuals with GC.

Hyponutrition among newly diagnosed gastric cancer.

OBJECTIVES: This study aims to determine the malnutrition status among Vietnamese patients newly diagnosed with gastric cancer (GC). BACKGROUND: GC remains the top rank of common and deadly diseases. With limited clinical manifestation, most GC patients were diagnosed at late stages when tumor is not radically resected. Malnutrition was associated with poor prognosis of GC, such as prolonged hospitalization, limited treatment efficacy and low survival rate. METHODS: The cross-sectional descriptive study recruited 77 patients newly diagnosed with GC and 90 healthy individuals (HC). The data used for this study were approved by the local Ethical Committee. The data were analysed on STATA 14.0 and GraphPad Prism 8.0. RESULTS: We observed the male dominant distribution in GC cohort and over 65% of GC were firstly diagnosed at advanced stages (III and IV). Anemia was detected in about 50% of GC patients. Hyponutrition was prevalent in newly diagnosed GC. We found the decreased tendency of anemia related indexes from HC to early stages (I and II) and advanced stages (III and IV) of GC patients. CONCLUSION: Anemia and hypoproteinemia occurred frequently among Vietnamese newly diagnosed GC. The nutrition therapy would benefit GC patients (Tab. 4, Fig. 4, Ref. 20).

Clinical value of serum polyunsaturated fatty acids in patients with gastric polyps.

Polyunsaturated fatty acids (PUFAs) are vital nutrients in human physiology and are implicated in various chronic diseases. However, the relationship between PUFAs and gastric polyps remains unclear. This study employed liquid chromatography-tandem mass spectrometry (LC-MS/MS) to assess PUFA levels in the serum of 350 patients, along with analyzing the ω-6 to ω-3 ratio. The results revealed significant differences in the levels of C16:1, C18:1, C18:2, α-C18:3, γ-C18:3, C20:1, C20:4, C20:5, ω-3-C22:5, ω-6-C22:5, and C22:6, as well as ω-6 to ω-3 ratio between the control and gasteic polyp groups. Moreover, setting the threshold for ω-6: ω-3 at 10 revealed a close correlation between polyp occurrence and this ratio. These findings suggest that PUFAs and the ω-6 to ω-3 ratio hold promise as potential early screening markers for gastric polyps. However, further research is imperative to elucidate the underlying mechanisms and therapeutic potential of PUFAs in managing gastric polyps.