UNASSIGNED: Increasing evidence reveals the involvement of mitochondria and macrophage polarisation in tumourigenesis and progression. This study aimed to establish mitochondria and macrophage polarisation-associated molecular signatures to predict prognosis in gastric cancer (GC) by single-cell and transcriptional data.
UNASSIGNED: Initially, candidate genes associated with mitochondria and macrophage polarisation were identified by differential expression analysis and weighted gene co-expression network analysis. Subsequently, candidate genes were incorporated in univariateCox analysis and LASSO to acquire prognostic genes in GC, and risk model was created. Furthermore, independent prognostic indicators were screened by combining risk score with clinical characteristics, and a nomogram was created to forecast survival in GC patients. Further, in single-cell data analysis, cell clusters and cell subpopulations were yielded, followed by the completion of pseudo-time analysis. Furthermore, a more comprehensive immunological analysis was executed to uncover the relationship between GC and immunological characteristics. Ultimately, expression level of prognostic genes was validated through public datasets and qRT-PCR.
UNASSIGNED: A risk model including six prognostic genes (GPX3, GJA1, VCAN, RGS2, LOX, and CTHRC1) associated with mitochondria and macrophage polarisation was developed, which was efficient in forecasting the survival of GC patients. The GC patients were categorized into high-/low-risk subgroups in accordance with median risk score, with the high-risk subgroup having lower survival rates. Afterwards, a nomogram incorporating risk score and age was generated, and it had significant predictive value for predicting GC survival with higher predictive accuracy than risk model. Immunological analyses revealed showed higher levels of M2 macrophage infiltration in high-risk subgroup and the strongest positive correlation between risk score and M2 macrophages. Besides, further analyses demonstrated a better outcome for immunotherapy in low-risk patients. In single-cell and pseudo-time analyses, stromal cells were identified as key cells, and a relatively complete developmental trajectory existed for stromal C1 in three subclasses. Ultimately, expression analysis revealed that the expression trend of RGS2, GJA1, GPX3, and VCAN was consistent with the results of the TCGA-GC dataset.
UNASSIGNED: Our findings demonstrated that a novel prognostic model constructed in accordance with six prognostic genes might facilitate the improvement of personalised prognosis and treatment of GC patients.

Background: The short-term and long-term outcomes of laparoscopic-assisted distal gastrectomy (LADG) and totally laparoscopic distal gastrectomy (TLDG) have been subject to controversy with various reconstruction techniques of Billroth-I, Billroth-II, Roux-en-Y, and Uncut. This study aims to compare the short-term and long-term outcomes of LADG and TLDG as well as the outcomes of different anastomoses. Methods: This study enrolled patients with gastric cancer at the First Affiliated Hospital of Nanjing Medical University (NMUH) between 2017 and 2021. Postoperative complications were classified according to the Clavien-Dindo grade. Exclusion criteria included metachronous and synchronous malignancy and palliative surgery. The Kaplan-Meier analysis was applied to assess 5-year prognosis between two groups. Results: This study included 1221 cases with an overall complication rate of 17.37% for LADG, which was significantly higher than TLDG\'s 10.72%. The incidence of anastomosis-related complications was 4.79% for LADG and 1.13% lower for TLDG. LADG and TLDG did not show significant difference for Grade III-V complications and resected lymph nodes. The postoperative stay was shorter for TLDG than LADG, and R-Y had a longer postoperative stay than B-II and Uncut after combining LADG and TLDG. The operation time was shorter in TLDG cases than that in LADG cases. The 5-year OS of the TLDG group was not significantly better than that of the LADG group. Conclusion: TLDG is superior in overall complication rate, anastomosis-related complication rate, postoperative stay and operation time to LADG. No difference of OS was observed between LADG and TLDG. Four anastomoses had no convincing evidence of being superior in complications rates, post-op stay, and harvested lymph nodes to each other.

UNASSIGNED: The combination of neoadjuvant immunotherapy and chemotherapy (NICT) has become a common treatment regimen for locally advanced gastric cancer (LAGC). However, the safety and efficacy of radical gastrectomy following NICT (NICT-G) remain controversial. This study aimed to analyze the risk factors influencing postoperative complications (POCs) after NICT-G. Additionally, it aimed to construct a nomogram to provide a clinical reference for predicting POCs.
UNASSIGNED: This study included 177 patients who received NICT-G at the Chinese PLA General Hospital First Medical Center from January 2020 to January 2024. Univariable and multivariable logistic regression models were used to evaluate the risk factors influencing POCs, and a nomogram model was constructed. To evaluate the discrimination and accuracy of the nomogram model, the area under the receiver operating characteristic curve (AUC) and the calibration curve were measured.
UNASSIGNED: In 177 patients who received NICT-G, the pathological complete response and major pathological response rates were 15.8% and 45.2%, respectively, whereas the rates of the overall and severe treatment-related adverse events were 71.8% and 15.8%, respectively. In addition, 43 (24.3%) patients developed overall POCs (Clavien-Dindo classification ≥ II). Univariable and multivariable logistic analyses showed that age ≥70 years, greater estimated blood loss, platelet/lymphocyte ratio (PLR) ≤196, neutrophil/lymphocyte ratio (NLR) >1.33, non-R0 resection, and body mass index (BMI) < 18.5 kg/m2 were independent risk factors for overall POCs (p < 0.05). The nomogram model developed using the abovementioned variables showed that the AUC (95% confidence interval [CI]) was 0.808 (95% CI): 0.731-0.885 in predicting the POC risk. The calibration curves showed that the prediction curve of the nomogram was a good fit for the actual POCs (Hosmer-Lemeshow test: χ2 = 5.76, P = 0.451).
UNASSIGNED: The independent risk factors for overall POCs in the NICT-G were age ≥ 70 years, greater estimated blood loss, PLR ≤ 196, NLR > 1.33, non-R0 resection, and BMI < 18.5 kg/m2. The nomogram model developed based on the abovementioned indicators showed better accuracy in predicting the POC risk.

OBJECTIVE: In gastric cancer cells, the influence of CAR T cells can be produced in the process of inhibiting the progression of gastric cancer, and the role of tyrosine phosphatase SHP2 can be explored in this study, along with its molecular mechanisms.
METHODS: The research utilized subcutaneous tumor models in nude mice to assess gastric cancer progression. Protein expression was detected using Western blotting, while Q-PCR examined the expression levels of lncRNA SNHG18 and miR-211-5p in MGC-803 cells. The relationship between miR-211-5p and lncRNA SNHG18 can be analyzed by dual luciferase reporter genes. The migratory ability of MGC-803 cells was determined through wound healing and transwell experiments, and cell proliferation was evaluated using a CCK-8 assay.
RESULTS: SHP2 was found to inhibit the cytotoxic effects of CAR-T cells on MGC-803 cells, and it suppressed the expression of proteins related to the ROS/JNK/NFAT4 signaling pathway in MGC-803 cells and the miR-211-5p/BRD4 axis in CAR-T cells. In addition, the proliferation, invasion and migration of MGC-803 cells were promoted, and the expression of miR-211-5p could be inhibited specifically by ncRNA SNHG18, as shown below:SHP2 in gastric cancer cells mediates the ROS/JNK/NFAT4 signaling pathway and induces lncRNA SNHG18, which, through the miR-211-5p/BRD4 axis in CAR-T cells, promotes gastric cancer growth and metastasis.

UNASSIGNED: Gastric cancer (GC) is a typical malignant tumor and the main cause of cancer-related deaths. Its pathogenesis involves multiple steps, including pyroptosis, although these steps are still uncertain. Pyroptosis, also known as gasdermin-mediated programmed necrosis, participates in various pathological processes in tumors, including GC. ELANE, which encodes neutrophil elastase, is closely associated with GC. Additionally, ELANE has been implicated in GC cell pyroptosis, but this has not been confirmed. Therefore, investigating the link between ELANE and pyroptosis in GC is warranted. This research uses bioinformatics and experiments to examine the relationship between ELANE, pyroptosis, and GC prognosis.
UNASSIGNED: The GEO and TCGA databases, along with pyroptosis-related genes, were applied to identify pyroptosis-related differentially expressed genes (DEGs). ELANE was selected via primary screening. Using the median expression level of ELANE as the threshold, pyroptosis-related DEGs were divided into low- and high-ELANE groups. Based on the DEGs in these two groups, GO, KEGG and GSEA analyses were conducted to elucidate the mechanisms of ELANE in GC. Furthermore, we plotted ROC and Kaplan-Meier curves to analyze the clinical and pathological features of ELANE expression. The Nomograms tool was applied to calculate the predictive value of ELANE for the clinical outcomes of GC cases. Immunohistochemical analysis was performed to detect the level of ELANE in GC tissues and to validate whether ELANE was involved in pyroptosis in GC cells through cell experiments. Finally, the immune infiltration of ELANE was investigated, and interaction networks (proteins-ELANE, microRNA-ELANE, and small-molecule drug-ELANE) were constructed.
UNASSIGNED: We aimed to investigate the expression of the ELANE gene in GC and study the relationship among ELANE, pyroptosis, and the prognosis of patients with GC. Differential expression analysis of gene-expression datasets from TCGA-STAD and GSE49051 revealed that the expression of the ELANE gene was significantly up-regulated in GC. Using STRING network analysis, we identified multiple proteins involved in the occurrence and development of GC, including interactions between ELANE and GSDMC, a member of the gasdermin protein family. Survival analysis showed that ELANE expression levels significantly affected overall survival (OS), disease-free survival (DFS), and progression-free survival (PFS) in patients with GC. Additionally, ROC analysis demonstrated that ELANE was effective in distinguishing GC patients from normal controls (AUC = 0.812). Immunohistochemical analysis showed that ELANE was highly expressed in gastric cancer tissues and was closely related to age, tumor grade, and stage. The cell experiments further confirmed that the high expression of ELANE in gastric cancer cells was associated with pyroptosis. Comprehensive analysis indicated that ELANE could be used as a potential prognostic marker for GC and plays an important role in pyroptosis.
UNASSIGNED: High ELANE expression is related to poor survival and prognosis of patients with GC. It participates in pyroptosis and immune infiltration in GC. Therefore, ELANE is a promising prognostic biomarker for pyroptosis in GC.

The rising incidence of colorectal cancer (CRC) and gastric cancer (GC) worldwide, coupled with the limited effectiveness of current chemotherapeutic agents, has prioritized the search for new therapeutic options. Natural substances, which often exhibit cytostatic properties, hold significant promise in this area. This review evaluates the anticancer properties of three natural alkaloids-berberine, sanguinarine, and chelerythrine-against CRC and GC. In vivo and in vitro studies have demonstrated that these substances can reduce tumor volume and inhibit the epithelial-mesenchymal transition (EMT) of tumors. At the molecular level, these alkaloids disrupt key signaling pathways in cancer cells, including mTOR, MAPK, EGFR, PI3K/AKT, and NF-κB. Additionally, they exhibit immunomodulatory effects, leading to the induction of programmed cell death through both apoptosis and autophagy. Notably, these substances have shown synergistic effects when combined with classical cytostatic agents such as cyclophosphamide, 5-fluorouracil, cetuximab, and erlotinib. Furthermore, berberine has demonstrated the ability to restore sensitivity in individuals originally resistant to cisplatin GC. Given these findings, natural compounds emerge as a promising option in the chemotherapy of malignant gastrointestinal tumors, particularly in cases with limited treatment options. However, more research is necessary to fully understand their therapeutic potential.

The potential role of the transient receptor potential Vanilloid 1 (TRPV1) non-selective cation channel in gastric carcinogenesis remains unclear. The main objective of this study was to evaluate TRPV1 expression in gastric cancer (GC) and precursor lesions compared with controls. Patient inclusion was based on a retrospective review of pathology records. Patients were subdivided into five groups: Helicobacter pylori (H. pylori)-associated gastritis with gastric intestinal metaplasia (GIM) (n = 12), chronic atrophic gastritis (CAG) with GIM (n = 13), H. pylori-associated gastritis without GIM (n = 19), GC (n = 6) and controls (n = 5). TRPV1 expression was determined with immunohistochemistry and was significantly higher in patients with H. pylori-associated gastritis compared with controls (p = 0.002). TRPV1 expression was even higher in the presence of GIM compared with patients without GIM and controls (p < 0.001). There was a complete loss of TRPV1 expression in patients with GC. TRPV1 expression seems to contribute to gastric-mucosal inflammation and precursors of GC, which significantly increases in cancer precursor lesions but is completely lost in GC. These findings suggest TRPV1 expression to be a potential marker for precancerous conditions and a target for individualized treatment. Longitudinal studies are necessary to further address the role of TRPV1 in gastric carcinogenesis.

We investigated whether radiomics of computed tomography (CT) image data enables the differentiation of bone metastases not visible on CT from unaffected bone, using pathologically confirmed bone metastasis as the reference standard, in patients with gastric cancer. In this retrospective study, 96 patients (mean age, 58.4 ± 13.3 years; range, 28-85 years) with pathologically confirmed bone metastasis in iliac bones were included. The dataset was categorized into three feature sets: (1) mean and standard deviation values of attenuation in the region of interest (ROI), (2) radiomic features extracted from the same ROI, and (3) combined features of (1) and (2). Five machine learning models were developed and evaluated using these feature sets, and their predictive performance was assessed. The predictive performance of the best-performing model in the test set (based on the area under the curve [AUC] value) was validated in the external validation group. A Random Forest classifier applied to the combined radiomics and attenuation dataset achieved the highest performance in predicting bone marrow metastasis in patients with gastric cancer (AUC, 0.96), outperforming models using only radiomics or attenuation datasets. Even in the pathology-positive CT-negative group, the model demonstrated the best performance (AUC, 0.93). The model\'s performance was validated both internally and with an external validation cohort, consistently demonstrating excellent predictive accuracy. Radiomic features derived from CT images can serve as effective imaging biomarkers for predicting bone marrow metastasis in patients with gastric cancer. These findings indicate promising potential for their clinical utility in diagnosing and predicting bone marrow metastasis through routine evaluation of abdominopelvic CT images during follow-up.

Gastric cancer (GC) is a leading cause of death, and this pathology often receives a diagnosis in an advanced stage. The development of a less invasive and cost-effective test for detection is essential for decreasing the mortality rate and increasing the life expectancy of GC patients. We evaluated the potential targeting of CD54/ICAM1, a marker of gastric cancer stem cells, with miRNAs to detect GC in blood samples. The analyses included 79 blood samples, 38 from GC patients and 41 from healthy donors, who attended INCan, México City. The total RNA was obtained from the blood plasma, and RT-PCR and qPCR were performed to obtain the relative expression of each miRNA. Hsa-miR-335-5p was detected in the plasma of GC patients and healthy donors at the same levels. The ROC curve analyses indicated that this miRNA was not a candidate for the molecular diagnosis of GC. We did not observe a correlation between the expression of hsa-miR-335-5p and clinical variables; however, the Kaplan-Meier analyses indicated that, in patients who survived more than 12 months, a lower expression of hsa-miR-335-5p was correlated with a better prognosis. It would be convenient to evaluate a larger panel of miRNAs, including miRNAs expressed in a limited number of cell types or with a low number targets, to obtain more specific candidates for developing a robust test for the diagnosis/prognosis of GC.

BACKGROUND: Oesophageal, gastroesophageal, and gastric malignancies are often diagnosed at locally advanced stage and multimodal therapy is recommended to increase the chances of survival. However, given the significant variation in treatment response, there is a clear imperative to refine patient stratification. The aim of this narrative review was to explore the existing evidence and the potential of radiomics to improve staging and prediction of treatment response of oesogastric cancers.
METHODS: The references for this review article were identified via MEDLINE (PubMed) and Scopus searches with the terms \"radiomics\", \"texture analysis\", \"oesophageal cancer\", \"gastroesophageal junction cancer\", \"oesophagogastric junction cancer\", \"gastric cancer\", \"stomach cancer\", \"staging\", and \"treatment response\" until May 2024.
RESULTS: Radiomics proved to be effective in improving disease staging and prediction of treatment response for both oesophageal and gastric cancer with all imaging modalities (TC, MRI, and 18F-FDG PET/CT). The literature data on the application of radiomics to gastroesophageal junction cancer are very scarce. Radiomics models perform better when integrating different imaging modalities compared to a single radiology method and when combining clinical to radiomics features compared to only a radiomics signature.
CONCLUSIONS: Radiomics shows potential in noninvasive staging and predicting response to preoperative therapy among patients with locally advanced oesogastric cancer. As a future perspective, the incorporation of molecular subgroup analysis to clinical and radiomic features may even increase the effectiveness of these predictive and prognostic models.