Outcomes Of Gastric Cancer Patients Research Articles

SLITRK2 as a prognostic and immunological biomarker in gastric cancer.

SLIT and NTRK-like protein 2 (SLITRK2) encodes a transmembrane protein that regulates neurite outgrowth. Some studies have demonstrated that SLITRK2 overexpressed in glioma. But the expression pattern, prognostic value and immunologic function of SLITRK2 in tumors remains unknown. The expression pattern of SLITRK2 among pan-cancers was examined through the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). We analyzed the association between SLITRK2 expression level and tumor stage among pan-cancers. Kaplan-Meier survival analysis was utilized to investigate the prognostic relevance of SLITRK2 across 33 different types of cancers. Moreover, the correlations among SLITRK2 expression, immune cell infiltration, immunomodulatory related genes, tumor mutation burden (TMB), microsatellite instability (MSI) were evaluated. The relationship between SLITRK2 expression and crucial genes mutations was also illustrated. By using tissue microarray (TMA), the expression of SLITRK2 in 89 paired gastric cancer (GC) tissues was investigated. Our study indicated that SLITRK2 expression varied across cancers. Elevated SLITRK2 expression was positively related to advanced tumor stage, poor overall survival (OS) and reduced disease-free survival (DFS). Bioinformatic analyses underscore SLITRK2's role in immune response, with its expression significantly tied to immune cell infiltration and marker expression. Based on TMA data, SLITRK2 expression level was positively associated with differentiation, lymph node metastasis, AJCC stage, TNM stage, and poor survival outcome in GC patients. Our findings provided that SLITRK2 may function as a biomarker by regulating immune cell infiltration. In addition, we verified that high SLITRK2 expression was correlated with poor prognosis in GC.

Survival and Treatment Outcomes in Gastric Cancer Patients with Brain Metastases: A Systematic Review and Meta-Analysis

Background: Brain metastases (BM) from gastric cancer (GC) are rare but associated with poor prognosis, significantly impacting patient survival and quality of life. The objective of this systematic review and meta-analysis is to consolidate existing research on BM from GC, evaluate the incidence and clinical outcomes, and explore the effectiveness of treatment options. Methods: A systematic search was conducted across the Medline, Web of Science, and Scopus databases, following PRISMA guidelines. Eighteen high-quality studies, as per the Newcastle–Ottawa Quality Assessment Scale, were included, encompassing 70,237 GC patients, of whom 621 developed BM. Data on progression-free survival (PFS), overall survival (OS), neurological symptoms, and HER2 status were analyzed using a random-effects model. Results: The incidence of BM in GC patients was found to be 2.29% (95% CI: 1.06–3.53%), with the range extending from 0.47% to 7.79% across studies. HER2-positive status was significantly associated with a higher likelihood of developing BM, with an odds ratio of 43.24 (95% CI: 2.05–913.39; p = 0.02), although this finding was based on limited data. The surgical resection of BM was linked to significantly improved survival outcomes, with a mean difference in OS of 12.39 months (95% CI: 2.03–22.75; p = 0.02) compared to non-surgical approaches. Conclusions: The surgical resection of brain metastases in GC patients significantly enhances overall survival, while HER2-positive patients may show a higher risk for developing BM. These findings underscore the importance of tailored therapeutic approaches for GC patients with BM.

Presentation and outcome of Gastric Cancer at a Tertiary Care Center

Introduction: Gastric cancer is the fifth most common cancer globally and the fourth leading cause of cancer-related deaths. Early-stage disease can be managed with endoscopic therapy or surgery, while advanced gastric cancer requires a multimodal treatment approach, including extensive lymphadenectomy. This study aims to evaluate the clinicodemographic profile and treatment outcomes of gastric cancer patients and to establish an effective therapeutic strategy. Methods: This retrospective descriptive cross-sectional study was conducted in the Department of Surgery at Shree Birendra Hospital. It included patients with gastric malignancies who had complete medical records. Data on patient history, AJCC staging, operative details, and postoperative findings were analyzed. Surgical choices were based on the clinical indication in each case. Clinicopathological characteristics and surgical outcomes were compared across tumor stages. Data were analyzed using Statistical Package for Social Sciences (SPSS) version 24. Results: The study included 90 patients (62 males, 28 females) aged between 23 and 82 years. The most common clinical presentations were abdominal pain (58%), gastric outlet obstruction (18%), lump (5%), anemia (5%), and peritonitis (4%). Adenocarcinoma was the predominant histological type (87.78%). Curative surgery was performed on 73 patients (81.11%), while 17 patients (18.89%) underwent palliative procedures. Morbidity occurred in 16 patients (17.7%), primarily due to chest complications and sepsis, and mortality was recorded in 5 patients (5.5%). Conclusion: This study highlights the predominance of locally advanced gastric cancer in males, with distal gastric cancer and well-differentiated adenocarcinoma being the most common. Chest complications and sepsis were the leading causes of morbidity and mortality. No patients received perioperative chemotherapy, underscoring the need for updated treatment protocols to improve outcomes.

Body Composition Decrease and Impact on Clinical Outcome in Gastric Cancer Patients Undergoing Radical Gastrectomy After Neoadjuvant Treatment

This study investigates the impact of neoadjuvant therapy (NT) on body composition and its correlation with long-term survival and other clinical outcomes in patients with advanced gastric cancer. We utilized Computed Tomography (CT) scans to measure body composition before and after NT, including Subcutaneous Adipose Tissue Index (SATI), Visceral Adipose Tissue Index (VATI), Skeletal Muscle Index (SMI), and Muscle Density (MA). We then analyzed the decrease in body composition in relation to tumor regression, inflammatory markers, nutritional scores, and long-term survival. Our findings reveal a negative correlation between the decrease in SATI and VATI after NT, and both tumor regression and nutritional score. Notably, patients who experienced a significant loss in SATI or VATI post-NT had shorter Recurrence-Free Survival (RFS) and Overall Survival (OS). Additionally, significant loss in SATI and VATI emerged as an independent risk factor for both RFS and OS. In conclusion, our study convincingly demonstrates that in patients with advanced gastric cancer, SATI and VATI decreases after NT and is negatively associated with tumor regression and nutritional score. A significant loss in SATI and VATI is a risk factor for shorter RFS and OS, thereby underscoring the importance of maintaining body composition during NT.

Construction and interpretation of machine learning-based prognostic models for survival prediction among intestinal-type and diffuse-type gastric cancer patients

BackgroundGastric cancer is one of the most common malignant tumors worldwide, with high incidence and mortality rates, and it has a complex etiology and complex pathological features. Depending on the tumor type, gastric cancer can be classified as intestinal-type and diffuse-type gastric cancer, each with distinct pathogenic mechanisms and clinical presentations. In recent years, machine learning techniques have been widely applied in the medical field, offering new perspectives for the diagnosis, treatment, and prognosis of gastric cancer patients.MethodsThis study recruited 2158 gastric cancer patients and constructed prognostic prediction models for both intestinal-type and diffuse-type gastric cancer. Clinical pathological data were collected from patients, and machine learning algorithms were used for feature selection and model construction. The performance of the models was validated with training and testing datasets. The Shapley additive explanations (SHAP) values were used to interpret the model predictions and identify the main factors that influence patient survival.ResultsIn the prognostic model for intestinal-type gastric cancer, the gradient boosting decision tree (GBDT) model demonstrated the best performance, with key features including pTNM, CA125, tumor size, CA199, and PALB. Similarly, in the prognostic model for diffuse-type gastric cancer, the GBDT model was utilized, with key features comprising pTNM, Borrmann type IV disease, lymphocyte (LYM), lactate dehydrogenase (LDH), potassium (K), perineural invasion (PNI), tumor size, and whole stomach location. Risk stratification analysis revealed that the prognosis of high-risk patients was significantly worse than that of low-risk patients.ConclusionMachine learning shows great potential in predicting survival outcomes of gastric cancer patients, providing strong support for the development of personalized treatment plans.

Effectiveness of nutritional support for clinical outcomes in gastric cancer patients: A meta-analysis of randomized controlled trials.

Gastric cancer (GC) is a leading cause of cancer-related morbidity and mortality globally. This meta-analysis was conducted to assess the impact of nutritional interventions on clinical outcomes in GC patients. Comprehensive search was conducted across four medical databases to identify randomized controlled trials (RCTs) that examined nutritional interventions in GC patients. The outcomes assessed included hospitalization duration, nutritional status, immune function, and complications. A total of 11 studies were included. Enteral nutrition (EN) significantly reduce hospital stay duration compared to no nutritional intervention (SMD = -1.22, 95% CI [-1.72, -0.73], P < 0.001) and parenteral nutrition (PN) (SMD = -1.30, 95% CI [-1.78, -0.82], P < 0.001), but showed no significant difference compared to immunonutrition (IN). EN also improved nutritional status, indicated by higher albumin prealbumin levels, and improved immune function by elevating CD4+ levels (SMD = 1.09, 95% CI [0.61, 1.57], P < 0.001). However, IN showed superior effects on immunoglobulin levels (IgG and IgM). No significant differences were observed in complication rates among EN, IN, and PN interventions. Nutritional support, particularly EN and IN, can significantly improve hospitalization outcomes, nutritional status, and immune function. Customizing interventions according to patient requirements can optimize therapeutic outcomes, highlighting the need for further research in this area.

Integrating machine learning and multi-omics analysis to develop an immune-derived multiple programmed cell death signature for predicting clinical outcomes in gastric cancer

Abstract Objectives Metastasis of tumor cells is the leading reason for mortality among patients diagnosed with gastric cancer (GC). Emerging evidence indicated a strong correlation between programmed cell death (PCD) and the invasion and metastasis of tumor cells. Therefore, we aimed to develop a programmed cell death signature to assess the prognosis and therapeutic efficacy in GC patients. Methods Here, we collected 1911 PCD-related genes from 19 different PCD patterns, and developed an immune-derived multiple programmed cell death index (MPCDI) using the integrating machine learning and multi-omics analysis, and systematically dissected heterogeneity in GC patients. Subsequently, we divided GC patients into two categories, namely high-MPCDI group and low-MPCDI group, using the median MPCDI as the threshold. We performed a comprehensive analysis of the clinical characteristics, somatic mutations, immune infiltration, drug sensitivity, and immunotherapeutic efficacy of the two groups. Results Survival and immunotherapy response analyses indicated that the high-MPCDI patients experienced a poorer overall survival (p=0.018) and were more resistant to commonly used chemotherapeutic drugs but benefited from immunotherapy compared to the low-MPCDI patients. In addition, MPCDI was confirmed as a standalone risk factor for overall survival, and nomograms can provide a precise tool for the clinical diagnosis of GC patients. Conclusions Taken together, the MPCDI can serve as a robust clinical diagnostic classifier to guide medication administration and improve outcomes in GC patients.

Circ_0008315 promotes tumorigenesis and cisplatin resistance and acts as a nanotherapeutic target in gastric cancer

IntroductionCisplatin-based chemotherapy is one of the fundamental therapeutic modalities for gastric cancer (GC). Chemoresistance to cisplatin is a great clinical challenge, and its underlying mechanisms remain poorly understood. Circular RNAs (circRNAs) are involved in the pathophysiology of multiple human malignancies.MethodsHigh-throughput sequencing was performed to determine the differentially expressed profile of circRNA in GC tissues and cisplatin-resistant GC cells. Quantitative real-time polymerase chain reaction and Fluorescence in situ hybridization was utilized to confirm the dysregulation of circ_0008315 in GC tissues. To evaluate the prognostic significance of circ_0008315 in GC, we used Kaplan-Meier plot. The self-renewal ability of drug-resistant GC cell was verified through tumor sphere formation assay. GC organoids were constructed to simulate the tumor microenvironment and verified the function of circ_0008315 in cisplatin resistance of gastric cancer. In vivo evaluation was conducted using patient-derived xenograft models. Dual-luciferase reporter gene, RNA immunoprecipitation and miRNA pull-down assays were employed to investigate the molecular mechanisms of circ_0008315 in GC.ResultsWe revealed that a novel circRNA hsa_circ_0008315 was upregulated in GC and cisplatin-resistant GC cells. Elevated circ_0008315 was also observed in cisplatin-resistant GC organoid model. High circ_0008315 expression predicted unfavorable survival outcome in GC patients. Downregulation of circ_0008315 expression inhibited proliferation, mobility, and epithelial-mesenchymal transition of GC cells in vitro and in vivo. Reducing circ_0008315 expression in cisplatin-resistant GC organoid model reversed cisplatin resistance. Mechanistically, circ_0008315 modulated the stem cell properties of GC through the miR-3666/CPEB4 signaling pathway, thereby promoting cisplatin resistance and GC malignant progression. Furthermore, we developed PLGA-PEG nanoparticles targeting circ_0008315, and the nanoparticles could effectively inhibit GC proliferation and cisplatin resistance.ConclusionCirc_0008315 exacerbates GC progression and cisplatin resistance, and can be used as a prognostic predictor. Circ_0008315 may function as a promising nanotherapeutic target for GC treatment.Graphical

Evaluating the efficacy of immunotherapy in gastric cancer: Insights from immune checkpoint inhibitors.

The emergence of immunotherapy, particularly immune checkpoint inhibitors (ICIs), represents a groundbreaking approach to treating gastric cancer (GC). However, the prognosis of GC patients receiving ICI treatment is influenced by various factors. This manuscript identified sarcopenia and myosteatosis as inde-pendent prognostic factors impacting the outcomes of GC patients treated with ICIs. Additionally, this study introduced a visual predictive model to estimate the prognosis of GC patients. If confirmed by further studies, this observation could provide valuable insights to propel the advancement of personalized clinical medicine and the integration of precision medicine practices.

LOXL3 Silencing Hampers the Metastasis and Angiogenesis of Gastric Cancer Cells Dependent on Ferroptosis Activation.

Gastric cancer (GC) remains a major unmet clinical problem accountable for considerable incidence and fatality rate. Lysyl oxidase-like 3 (LOXL3) has been recognized to be overexpressed in GC. Our work was meant to disclose the significance of LOXL3 in the advancement of GC and the likely action mechanism. LOXL3 expression in GC tissues and its correlation with the outcome of GC patients were investigated through bioinformatics tools. RT-qPCR and western blotting inspected LOXL3 expression in GC cells. CCK-8 method, EDU, as well as colony formation assays assayed cell proliferation. The capacities of cells to migrate and invade were appraised by wound healing and transwell assays, severally. Tube formation assay and ELISA measured angiogenesis. TBARS, C11 BODIPY staining, and FerroOrange estimated ferroptosis. Western blotting examined the expression of proteins implicated in metastasis and ferroptosis. The up-regulation of LOXL3 expression was noticed in GC tissues and cells, which was also associated with the poor outcome of GC patients. When LOXL3 was underexpressed, the proliferation, migration, invasion, epithelial-mesenchymal transition, and angiogenesis of GC cells were all halted. In addition, LOXL3 deletion resulted in the activation of ferroptosis in GC cells, and ferrostatin-1 (Fer-1), the specific ferroptosis inhibitor, compensated the suppressive role of LOXL3 down-regulation in the proliferation, metastasis, and angiogenesis of GC cells in vitro. All in all, knockdown of LOXL3 may serve an activator of ferroptosis to obstruct the aggressive process of GC.

Integrated single-cell and bulk RNA sequencing analyses identify an immunotherapy nonresponse-related fibroblast signature in gastric cancer.

Factors that determine nonresponse to immune checkpoint inhibitor (ICI) remain unclear. The protumor activities of cancer-associated fibroblasts (CAFs) suggest that they are potential therapeutic targets for cancer treatment. There is, however, a lack of CAF-related signature in predicting response to immunotherapy in gastric cancer (GC). Single-cell RNA sequencing (scRNA-seq) and RNA sequencing (RNA-seq) data of GC immunotherapy were downloaded from the Gene Expression Omnibus database. Bulk RNA-seq data were obtained from The Cancer Genome Atlas. The R package 'Seurat' was used for scRNA-seq data processing. Cellular infiltration, receptor-ligand interactions, and evolutionary trajectory analysis were further explored. Differentially expressed genes affecting overall survival were obtained using the limma package. Weighted Gene Correlation Network Analysis was used to identify key modules of immunotherapy nonresponder. Prognostic model was constructed by univariate Cox and least absolute contraction and selection operator analysis using the intersection of activated fibroblast genes (AFGs) with key module genes. The differences in clinicopathological features, immune microenvironment, immunotherapy prediction, and sensitivity to small molecule agents between the high- and low-risk groups were further investigated. Based on scRNA-seq, we finally identified 20 AFGs associations with the prognosis of GC patients. AFGs' high expression levels were correlated with both poor prognosis and tumor progression. Three genes (FRZB, SPARC, and FKBP10) were identified as immunotherapy nonresponse-related fibroblast genes and used to construct the prognostic signature. This signature is an independent significant risk factor affecting the clinical outcomes of GC patients. Remarkably, there were more CD4 memory T cells, resting mast cells, and M2 macrophages infiltrating in the high-risk group, which was characterized by higher tumor immune exclusion. Moreover, patients with higher risk scores were more prone to not respond to immunotherapy but were more sensitive to various small molecule agents, such as memantine. In conclusion, this study constructed a fibroblast-associated ICI nonresponse gene signature, which could predict the response to immunotherapy. This study potentially revealed a novel way to overcome immune resistance in GC.

Association of miR-338-3p with survival outcomes in gastric cancer patients who received peri-operative blood transfusion.

Perioperative blood transfusion (BT) is frequent in the treatment of gastric cancer (GC), but its effects on the prognosis of GC remains controversial. In this study, we aimed to further confirm the relationship of perioperative BT with GC overall survival and to evaluate the predictive value of microRNA-338-3p (miR-338-3p) for the prognosis of GC patients who received perioperative BT. Clinical data and serum samples were collected and analyzed from 246 patients with GC. Five-year follow-up survival information was assessed by Kaplan-Meier survival analysis. miR-338-3p relative expression was assessed by RT-qPCR, and its relationship with the prognosis of GC patients, who received perioperative BT, was evaluated using Kaplan-Meier curves and Cox regression analysis. GC patients received perioperative BT had poor 5year survival than those without BT. In patients received BT, miR-338-3p expression was higher in survival cases than died population and high miR-338-3p was independently associated with better overall survival prognosis. Perioperative BT is related with poor prognosis in GC patients and miR-338-3p may be a prognostic biomarker for GC patients received perioperative BT. BT in perioperative GC patients should be cautious, especially for those with low levels of miR-338-3p.

The impact of CLDN18.2 expression on effector cells mediating antibody-dependent cellular cytotoxicity in gastric cancer

Activating antibody-dependent cellular cytotoxicity (ADCC) by targeting claudin-18 isoform 2 (CLDN18.2) using zolbetuximab, a monoclonal antibody against CLDN18.2, has been considered a promising novel therapeutic strategy for gastric cancer (GC). However, the impact of CLDN18.2 expression on natural killer (NK) cells and monocytes/macrophages—crucial effector cells of ADCC—in GC has not been fully investigated. In the present study, we assessed the impact of CLDN18.2 expression on clinical outcomes, molecular features, and the frequencies of tumor-infiltrating NK cells and macrophages, as well as peripheral blood NK cells and monocytes, in GC by analyzing our own GC cohorts. The expression of CLDN18.2 did not significantly impact clinical outcomes of GC patients, while it was significantly and positively associated with Epstein–Barr virus (EBV) status and PD-L1 expression. The frequencies of tumor-infiltrating NK cells and macrophages, as well as peripheral blood NK cells and monocytes, were comparable between CLDN18.2-positive and CLDN18.2-negative GCs. Importantly, both CLDN18.2 expression and the number of tumor-infiltrating NK cells were significantly higher in EBV-associated GC compared to other molecular subtypes. Our findings support the effectiveness of zolbetuximab in CLDN18.2-positive GC, and offer a novel insight into the treatment of this cancer type, highlighting its potential effectiveness for CLDN18.2-positive/EBV-associated GC.

Conversion Therapy for Gastric Cancer with Peritoneal Metastasis

Peritoneal metastasis in gastric cancer has a poor prognosis and is increasing in prevalence. Neoadjuvant chemotherapy is used for advanced tumors; however, surgery is generally not considered for metastatic and unresectable diseases. Recently, conversion surgery, a treatment which aims for an R0 resection following chemotherapy, has become a novel therapeutic option with better survival rates. In addition to surgery, hyperthermic intraperitoneal chemotherapy (HIPEC) leads to significant tumor reduction, but it is limited by its morbidity. Pressurized intraperitoneal aerosol chemotherapy (PIPAC) delivers high concentrations of chemotherapy, but does not remove the tumor, making it useful mostly in palliative settings. Intraperitoneal (IP) therapy, known for its minimally invasive nature and repeatability, shows promise but requires further research. Ultimately, an integrated approach involving systemic chemotherapy, radical gastrectomy, HIPEC, PIPAC and IP chemotherapy can be used to optimize treatment outcomes of gastric cancer patients with peritoneal metastasis.

The Prediction of DLL4 as a Prognostic Biomarker in Patients with Gastric Cancer Using Anti-DLL4 Nanobody.

Angiogenesis and cancer metastasis depend on the DLL4/Notch signaling pathway. A new approach to treating angiogenesis could inhibit or block this pathway. In the present study, we investigated DLL4 expression as a biomarker capable of predicting survival outcomes in gastric cancer patients using a novel anti-DLL4 Nanobody. By using a recently developed anti-DLL4 Nanobody, the expression of DLL4 was evaluated in tissue samples from 135 gastric cancer patients. It was evaluated whether DLL4 expression is related to clinicopathological factors, overall survival (OS), and recurrence-free survival (RFS). Sixty-five (48%) gastric cancer patients had a positive expression of DLL4 within the tumor tissue. Based on both the univariate and multivariate regression analyses, the expression of DLL4 was strongly associated with RFS (HR, 1.94; p = 0.008) and OS (HR, 2.06; p = 0.004). Moreover, the survival analysis demonstrated that DLL4 expression was a significant independent factor of unfavorable OS (HR, 2.7; p = 0.01) and RFS (HR, 2.3; p = 0.02) in gastric cancer patients. DLL4 expression in gastric cancer patients may predict poor prognosis and survival. Furthermore, the current data demonstrate the potential of Nanobody for detecting DLL4, and it may lead to develop novel therapies and diagnostics for tumors.

IL-4/IL-4R axis signaling drives resistance to immunotherapy by inducing the upregulation of Fcγ receptor IIB in M2 macrophages

In recent years, immunotherapy, particularly PD-1 antibodies, have significantly enhanced the outcome of gastric cancer patients. Despite these advances, some patients do not respond well to treatment, highlighting the need to understand resistance mechanisms and develop predictive markers of treatment effectiveness. This study retrospectively analyzed data from 106 patients with stage IV gastric cancer who were treated with first-line immunotherapy in combination with chemotherapy. By comparing plasma cytokine levels between patients resistant and sensitive to PD-1 antibody therapy, the researchers identified elevated IL-4 expression in the resistant patients. Mechanical investigations revealed that IL-4 induces metabolic changes in macrophages that activate the PI3K/AKT/mTOR pathway. This alteration promotes ATP production, enhances glycolysis, increases lactic acid production, and upregulates FcγRIIB expression in macrophages. Ultimately, these changes lead to CD8+ T cell dysfunction and resistance to PD-1 antibody therapy in gastric cancer. These findings highlight the role of IL-4-induced macrophage polarization and metabolic reprogramming in immune resistance and verify IL-4 as potential targets for improving treatment outcomes in gastric cancer patients.

Characterization of tumor endothelial cells (TEC) in gastric cancer and development of a TEC-based risk signature using single-cell RNA-seq and bulk RNA-seq data.

Tumor endothelial cells (TECs) are essential participants in tumorigenesis. This study is focused on elucidating the TEC traits in gastric cancer (GC) and constructing a prognostic risk model to predict the clinical outcome of GC patients. Single-cell RNA sequencing (scRNA-seq) data were obtained from the GEO database. Using specific markers, the Seurat R package aided in processing scRNA-seq data and identifying TEC clusters. Based on TEC cluster-associated genes identified by Pearson correlation analysis, TEC-related prognostic genes were screened by lasso-Cox regression analysis, thereby constructing a risk signature. A nomogram was created by combining the risk signature with clinicopathological features. Based on the scRNA-seq data, 5 TEC clusters were discovered in GC, with 3 of them showing prognostic associations in GC. A total of 163 genes were pinpointed among 3302 DEGs as significantly linked to TEC clusters, leading to the formulation of a risk signature comprising 8 genes. Furthermore, there was a notable correlation between the risk signature and the immune cell infiltration. Multivariate analysis findings indicated that the risk signature served as an independent prognostic factor for GC. Moreover, its efficacy in forecasting immune response was validated. TEC-based risk model is highly effective in predicting the survival outcomes of GC patients and can forecast the immune response. Targeting TECs may significantly inhibit tumor progression and enhance the efficacy of immunotherapy.

Survival outcomes in patients with stage IV gastric cancer with Krukenberg tumors: A systematic review and meta-analysis.

e16020 Background: Stage IV gastric cancer patients with Krukenberg tumors tend to have poor survival outcomes, usually less than 2 years. The management of such tumor groups remains unstandardized, and whether oophorectomy improves survival is unknown. In this study, we systematically analyze the survival outcomes in gastric cancer patients with ovarian metastases who received either standard chemotherapy, surgical resection of ovarian metastases, or combined chemotherapy and surgery. Methods: We synthesized randomized controlled trials and observational studies, which were retrieved by systematically searching MEDLINE (PubMed), Embase, and the Cochrane Library through January 25, 2024, using the Boolean logic. Participants included individuals with pathologically and radiologically confirmed ovarian metastasis or clinically symptomatic cases with imaging evidence. Statistical analyses were conducted using R (v.4.3.2., Vienna) (PROSPERO ID-CRD42023488373). Results: A total of 1502 patients from 17 retrospective studies were pooled for differential overall survival (OS) outcomes ( Table). The OS in the standard chemotherapy cohort using the random effects model was 6.708 months (95% CI: 3.867 to 9.548). Heterogeneity was non-significant (P = 0.3854) with I2 of 5.5%. In the surgical resection cohort, OS was 12.786 months (95% CI: 6.9 to 18.671). I2 was 0%, and heterogeneity was low (P = 0.6013). In the combined chemotherapy and surgical resection cohort, OS was 16.228 months (95% CI: 12.254 to 20.202). I2 was 0%, and heterogeneity was insignificant (P = 0.9632). Conclusions: This meta-analysis provides novel insights into survival outcomes associated with distinct therapeutic modalities in gastric cancer with krukenberg metastases, contributing valuable evidence for clinical decision-making and future research directions. While the combined approach of chemotherapy and surgery demonstrates the highest effect size for OS, judicious consideration of patient-centric approaches is imperative in the oncological care landscape. [Table: see text]

Understanding the relationship between obesity and in-hospital outcomes in gastric cancer patients : A nationwide analysis.

e16050 Background: Gastric cancer is the fifth most common form of cancer and the third leading cause of cancer-related deaths worldwide. Obesity has been identified as a significant risk factor for gastric cancer, associated with increased incidence and heightened complications in hospitalized patients. Our analysis comprehensively evaluates obesity's impact on hospital-admitted gastric cancer patients. Methods: Using the National Inpatient Sample (NIS) 2020, we identified gastric cancer patients with regional and advanced metastatic disease, and they were stratified into patients with and without obesity. The primary outcome was mortality, and secondary outcomes included length of stay, the total cost of hospitalization, and other in-hospital adverse outcomes. Multivariate logistic regression analysis was used to calculate the outcomes after adjusting for confounding variables. Results: A total of 17560 patients were hospitalized with gastric cancer, among which 1720(9.8%) had the concurrent diagnosis of Obesity. The mean age of patients with and without Obesity was 63 (+/- 13.88) and 66 (+/- 12.93),p&lt;0.001 respectively. The obese category had the greater percentage of male patients as compared to females (58.14% vs 44.85% respectively, p&lt;0.001). After adjusting for confounding variables, Obesity was not considered as an independent predictor of mortality in patients with gastric cancer (OR=1.06(0.59-1.92); p=0.90). However, patients with Obesity had prolonged length of stay (+ 1.52 days(1.49-2.26); p=0.004) and total cost of hospitalization (+ $30977(12320-49633); p=0.001). Similarly, obese patients had an increased likelihood of Acute kidney injury (OR=1.47(1.09-1.96); p=0.01), ICU admission (OR=2.01(1.30-3.09); p=0.002), invasive (OR=2.14(1.29-3.54); p=0.003) Noninvasive mechanical ventilation (OR=5.36(2.17-13.14); p&lt;0.001) and Heart failure (OR=1.68(1.09-2.57); p=0.02). No difference was noted in the risk of cardiac arrest (OR=1.26(0.28-5.68); p=0.76), and sepsis(OR=1.76(0.99-3.13); p=0.05). Conclusions: Obesity in patients with gastric cancer is not an independent predictor of mortality but is associated with increased length of stay, the total cost of hospitalization, increased risk of mechanical ventilation, and ICU admissions. Management of obesity can prove crucial in averting a wide range of potential health complications and significantly enhancing the overall quality of life in gastric cancer patients. [Table: see text]

A disulfidptosis-related classification and risk signature identifies immunotherapy biomarkers and predicts prognosis in gastric cancer: An observational study.

Gastric cancer (GC) is one of the most prevalent types of cancer globally, often detected at advanced stages. However, its prognosis remains poor, necessitating the exploration of new biomarkers. Disulfidptosis, a recently identified form of programmed cell death, has not yet been investigated in relation to GC and its associated mechanisms. We analyzed and identified potential associations between disulfidptosis genes and GC clinical risk using TCGA (The Cancer Genome Atlas)-STAD (stomach adenocarcinoma) as the training set and GSE84433 as the validation set. In addition, we explored the prognostic value and potential biological mechanisms of disulfide genes in GC by consensus clustering, enrichment analysis, mutation histology analysis and immune infiltration analysis. Finally, we constructed a disulfidptosis-related risk signature (DRRS) to assess the association between risk class, survival prognosis, and immune infiltration. By utilizing data from 19 disulfidptosis-related genes, we successfully identified subgroups of C1 and C2 patients through consensus clustering. Notably, the 2 groups exhibited significant variations in terms of survival rates, immune scores, and immune cell infiltration. Subsequently, we developed a DRRS via LASSO (least absolute shrinkage and selection operator) regression analysis, incorporating PRICKLE1, NRP1, APOD, MISP3, and SERPINE1. This scoring system effectively distinguished individuals with high and low risks, as verified with a validation set. These findings strongly indicate a close association between disulfidptosis and the immune microenvironment of GC tumors. Moreover, the DRRS demonstrated commendable predictive capabilities for the survival outcomes of GC patients. In this study, we have identified the association between different subtypes of disulfidptosis and alterations in the GC immunotumour microenvironment. Furthermore, we have developed and verified the accuracy of the DRRS, a valuable tool for predicting survival, biological function, and immune infiltration in patients with GC. These findings contribute to a better comprehension of disulfidptosis and offer potential opportunities for innovative approaches in GC treatment.