Positive peritoneal lavage fluid cytology based on isolation by size of epithelial tumor cells indicates a high risk of peritoneal metastasis.

Background: Peritoneal metastasis (PM) is the most prevalent type of metastasis in patients with gastric cancer (GC) and has an extremely poor prognosis. The detection of free cancer cells (FCCs) in the peritoneal cavity has been demonstrated to be one of the worst prognostic factors for GC. However, there is a lack of sensitive detection methods for FCCs in the peritoneal cavity. This study aimed to use a new peritoneal lavage fluid cytology examination to detect FCCs in patients with GC, and to explore its clinical significance on diagnosing of occult peritoneal metastasis (OPM) and prognosis. Methods: Peritoneal lavage fluid from 50 patients with GC was obtained and processed via the isolation by size of epithelial tumor cells (ISET) method. Immunofluorescence and fluorescence in situ hybridization (FISH) were used to identify FCCs expressing chromosome 8 (CEP8), chromosome 17 (CEP17), and epithelial cell adhesion molecule (EpCAM). Results: Using a combination of the ISET platform and immunofluorescence-FISH, the detection of FCCs was higher than that by light microscopy (24.0% vs. 2.0%). Samples were categorized into positive and negative groups, based on the expressions of CEP8, CEP17, and EpCAM. Statistically significant relationships were demonstrated between age (P = 0.029), sex (P = 0.002), lymphatic invasion (P = 0.001), pTNM stage (P = 0.001), and positivity for FCCs. After adjusting for covariates, patients with positive FCCs had lower progression-free survival than patients with negative FCCs. Conclusion: The ISET platform highly enriched nucleated cells from peritoneal lavage fluid, and indicators comprising EpCAM, CEP8, and CEP17 confirmed the diagnosis of FCCs. As a potential detection method, it offers an opportunity for early intervention of OPM and an extension of patient survival.

IMPROVEMENT OF THE MODEL OF PREVENTION OF MALIGNANT NEOPLASM OF THE GASTRIC.

The fight against malignant neoplasms is one of the most important problems of health care in Ukraine; its relevance is due to the continuous growth of oncological morbidity in the population, the complexity of timely diagnosis and treatment, high cost, as well as quite high levels of disability and mortality of such patients. Gastric cancer, which remains one of the most common and deadly neoplasms in the world, occupies one of the leading positions among cancer. Aim - scientifically substantiate and develop a model for improving the organization of prevention of malignant neoplasms of the gastric. A study of performance indicators of oncology health care facilities and a survey of respondents was conducted: 180 respondents of patients with gastric cancer and precancerous diseases of the stomach using medical-statistical, sociological methods and questionnaires. A functional and organizational model for improving the prevention of malignant neoplasms of the stomach has been scientifically substantiated and developed. The features of the proposed model were the inclusion in it, in addition to the previously existing, innovative elements (an algorithm for early diagnosis and prevention of negative consequences of malignant neoplasms of the stomach at the level of primary medical care, reminders for primary medical care doctors regarding monitoring of risk factors and predictors of malignancy of precancerous stomach diseases, the allocation of a dynamic monitoring group due to the increased risk of precancerous gastric diseases becoming oncological), as well as previously existing, but functionally changed components (optimization of the functions of the primary care physician in relation to the information provision of the patient and his relatives; monitoring of risk factors for precancerous and cancerous stomach diseases, control and accounting for the implementation of the recommendations of specialist doctors and rehabilitation specialists), the interaction between which provided the model with a qualitatively new focus on achieving its strategic goal - preventing the occurrence and progression of the development of malignant neoplasms of the gastric. The proposed functional and organizational model will lead to a positive medical and social effect for the improvement of the organization of the prevention of gastric cancer in the main areas: systematicity, comprehensiveness and preventive direction. Its implementation will lead to an increase in early detection, coverage of dynamic monitoring of patients, as well as a projected economic effect due to a decrease in the specific weight of neglected forms of gastric cancer, improvement in survival and reduction in mortality.

Metabolomic profiling of upper GI malignancies in blood and tissue: a systematic review and meta-analysis.

OBJECTIVE: To conduct a systematic review and meta-analysis of case-control and cohort human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on esophageal cancer (EC), cancer of the gastroesophageal junction (GEJ), and gastric cancer (GC) in blood and tissue. BACKGROUND: Upper gastrointestinal cancers (UGC), predominantly EC, GEJ, and GC, are malignant tumour types with high morbidity and mortality rates. Numerous studies have focused on metabolomic profiling of UGC in recent years. In this systematic review and meta-analysis, we have provided a collective summary of previous findings on metabolites and metabolomic profiling associated with EC, GEJ and GC. METHODS: Following the PRISMA procedure, a systematic search of four databases (Embase, PubMed, MEDLINE, and Web of Science) for molecular epidemiologic studies on the metabolomic profiles of EC, GEJ and GC was conducted and registered at PROSPERO (CRD42023486631). The Newcastle-Ottawa Scale (NOS) was used to benchmark the risk of bias for case-controlled and cohort studies. QUADOMICS, an adaptation of the QUADAS-2 (Quality Assessment of Diagnostic Accuracy) tool, was used to rate diagnostic accuracy studies. Original articles comparing metabolite patterns between patients with and without UGC were included. Two investigators independently completed title and abstract screening, data extraction, and quality evaluation. Meta-analysis was conducted whenever possible. We used a random effects model to investigate the association between metabolite levels and UGC. RESULTS: A total of 66 original studies involving 7267 patients that met the required criteria were included for review. 169 metabolites were differentially distributed in patients with UGC compared to healthy patients among 44 GC, 9 GEJ, and 25 EC studies including metabolites involved in glycolysis, anaerobic respiration, tricarboxylic acid cycle, and lipid metabolism. Phosphatidylcholines, eicosanoids, and adenosine triphosphate were among the most frequently reported lipids and metabolites of cellular respiration, while BCAA, lysine, and asparagine were among the most commonly reported amino acids. Previously identified lipid metabolites included saturated and unsaturated free fatty acids and ketones. However, the key findings across studies have been inconsistent, possibly due to limited sample sizes and the majority being hospital-based case-control analyses lacking an independent replication group. CONCLUSION: Thus far, metabolomic studies have provided new opportunities for screening, etiological factors, and biomarkers for UGC, supporting the potential of applying metabolomic profiling in early cancer diagnosis. According to the results of our meta-analysis especially BCAA and TMAO as well as certain phosphatidylcholines should be implicated into the diagnostic procedure of patients with UGC. We envision that metabolomics will significantly enhance our understanding of the carcinogenesis and progression process of UGC and may eventually facilitate precise oncological and patient-tailored management of UGC.

Real-World Application of Artificial Intelligence for Detecting Pathologic Gastric Atypia and Neoplastic Lesions.

PURPOSE: Results of initial endoscopic biopsy of gastric lesions often differ from those of the final pathological diagnosis. We evaluated whether an artificial intelligence-based gastric lesion detection and diagnostic system, ENdoscopy as AI-powered Device Computer Aided Diagnosis for Gastroscopy (ENAD CAD-G), could reduce this discrepancy. MATERIALS AND METHODS: We retrospectively collected 24,948 endoscopic images of early gastric cancers (EGCs), dysplasia, and benign lesions from 9,892 patients who underwent esophagogastroduodenoscopy between 2011 and 2021. The diagnostic performance of ENAD CAD-G was evaluated using the following real-world datasets: patients referred from community clinics with initial biopsy results of atypia (n=154), participants who underwent endoscopic resection for neoplasms (Internal video set, n=140), and participants who underwent endoscopy for screening or suspicion of gastric neoplasm referred from community clinics (External video set, n=296). RESULTS: ENAD CAD-G classified the referred gastric lesions of atypia into EGC (accuracy, 82.47%; 95% confidence interval [CI], 76.46%-88.47%), dysplasia (88.31%; 83.24%-93.39%), and benign lesions (83.12%; 77.20%-89.03%). In the Internal video set, ENAD CAD-G identified dysplasia and EGC with diagnostic accuracies of 88.57% (95% CI, 83.30%-93.84%) and 91.43% (86.79%-96.07%), respectively, compared with an accuracy of 60.71% (52.62%-68.80%) for the initial biopsy results (P<0.001). In the External video set, ENAD CAD-G classified EGC, dysplasia, and benign lesions with diagnostic accuracies of 87.50% (83.73%-91.27%), 90.54% (87.21%-93.87%), and 88.85% (85.27%-92.44%), respectively. CONCLUSIONS: ENAD CAD-G is superior to initial biopsy for the detection and diagnosis of gastric lesions that require endoscopic resection. ENAD CAD-G can assist community endoscopists in identifying gastric lesions that require endoscopic resection.

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.

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.

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.

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.

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.

[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.

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.

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.

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.

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.

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.

Circulating miRNA and circulating tumor DNA application as liquid biopsy markers in gastric cancer.

Liquid biopsy has been investigated as a novel method to overcome the numerous challenges in gastric cancer (GC) management. This non-invasive, feasible, and easy-to-repeat method has been shown to be cost-effective and capable of increasing diagnostic sensitivity and prognostic assessment. Additionally, it is potentially accurate to aid decision-making and personalized treatment planning. MicroRNA (miRNA) and circulating tumor DNA (ctDNA) markers can enhance GC management in various aspects, including diagnosis (mainly earlier diagnosis and the ability to perform population-based screening), prognosis (more precise stratification of prognosis), and treatment (including more accurate prediction of treatment response and earlier detection of resistance to the treatment). Concerning the treatment-related application, miRNAs' mimics and antagonists (by using two main strategies of restoring tumor suppressor miRNAs and inhibiting oncogene miRNAs) have been shown to be effective therapeutic agents. However, these need to be further validated in clinical trials. Furthermore, novel delivery systems, such as lipid-based vectors, polymeric-based vectors, and exosome-based delivery, have been developed to enhance the performance of these agents. Moreover, this paper explores the current detection and measuring methods for these markers. These approaches are categorized into direct methods (e.g., Chem-NAT, HTG EdgeSeq, and Multiplex Circulating Fireplex) and indirect methods (e.g., Reverse transcription-quantitative polymerase chain reaction (RT-qPCR), qPCR, microarray, and NGS) for miRNA detection. For ctDNA measurement, main core technologies like NGS, digital PCR, real-time PCR, and mass spectrometry are suggested.

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.