Survival Of Gastric Cancer Patients Research Articles

A comprehensive analysis of the expression, immune infiltration, prognosis and partial experimental validation of CHST family genes in gastric cancer

Previous studies have demonstrated that carbohydrate sulfotransferase family proteins (CHSTs) play a crucial role in the extracellular matrix structural constituent and cancer progression, however, the effect of CHSTs on gastric cancer is still superficial. To investigate these, our study seeks to provide a comprehensive understanding of CHSTs' expression, immune infiltration, and prognostic implications in gastric cancer, utilizing data from the TCGA, GEO and GTEx databases. Furthermore, we conducted experimental validation to elucidate the role of CHST14 specifically in gastric cancer. Our findings suggest that most CHSTs were highly expressed in gastric cancer. Gene copy number variations further indicated prevalent CHSTs amplification in gastric cancer, pointing to its potential relevance in disease progression. Intriguingly, we noted strong positive correlations between most CHSTs and immune cell infiltration. Importantly, most members of CHSTs were related to OS and PFI with gastric cancer, with particular emphasis on CHST14 and CHST9. Multifactorial regression analysis indicates that CHST14 is an independent prognostic factor influencing the overall survival of gastric cancer patients. In further experimental validation, our results demonstrate elevated expression of CHST14 in gastric cancer, and knocking down CHST14 inhibits gastric cancer cell proliferation, invasion, migration and EMT. Additionally, CHST14 may exert its function through the regulation of the Wnt pathway. In summary, our study comprehensively analyzes the hitherto undescribed role of CHSTs in gastric cancer through the analysis of multi-omics data. Importantly, we identify CHST14 as a pivotal promoter in the malignant progression of gastric cancer, offering potential targets for gastric cancer therapy.

Intensifying supportive care is associated with improved survival in gastric cancer patients with malignant ascites.

Gastric cancer patients with malignant ascites often have poor functional status and malnutrition that preclude receipt of systemic therapies. Thus, these patients have a very poor prognosis. Beginning in 2019, our multidisciplinary gastric cancer disease-oriented team implemented a more aggressive supportive care plan for gastric cancer patients with malignant ascites. The initiative included measures such as supplemental enteral nutrition, ascites drainage, and initiation of chemotherapy on an inpatient basis. We compared outcomes for gastric cancer patients who presented with synchronous malignant ascites treated before and after the implementation of the care plan. We performed a retrospective review of our institutional database to identify patients diagnosed with gastric adenocarcinoma and synchronous malignant ascites between 2010 and 2022. We compared overall survival (OS) between patients diagnosed from 2010 to 2018, which will be referred to as the historical control era and patients diagnosed from 2019 to 2022, which will be called the aggressive supportive care era. Fifty-four patients were included in our analysis; 31 patients were treated in the historical control time frame, and 23 patients were treated during the aggressive supportive care era. Demographic, clinical, and pathologic characteristics were similar between groups. 3% of historical controls received supplemental tube feeds at diagnosis as compared to 30% of the aggressive supportive care cohort (p < 0.01). 3% of historical controls received their first cycle of chemotherapy in the inpatient setting versus 39% of patients treated during the aggressive supportive care era (p < 0.01). The median number of chemotherapy cycles received was 5 among historical controls and 9.5 among aggressive supportive care era patients (p = 0.02). There was no difference in the number of days spent as an inpatient between the two groups. The median OS for historical control patients was 5.4 months as compared with 10.4 months for patients treated during aggressive supportive care era (p = 0.04). Gastric cancer patients with synchronous malignant ascites treated during a timeframe when our multidisciplinary team implemented more aggressive supportive care measures had improved OS as compared with historic controls. Our results suggest that aggressive supportive measures for these patients with highly challenging clinical issues and poor prognosis can prolong survival. Specifically, initiation of chemotherapy in the inpatient setting and supplemental nutrition should be considered for patients at high risk for treatment intolerance.

Prognostic Implications of LRP1B and Its Relationship with the Tumor-Infiltrating Immune Cells in Gastric Cancer.

Recent studies have shown that low-density lipoprotein receptor-related protein 1b (LRP1B), as a potential tumor suppressor, is implicated in the response to immunotherapy. The frequency of LRP1B mutation gene is high in many cancers, but its role in gastric cancer (GC) has not been determined. The prognostic value of LRP1B mutation in a cohort containing 100 patients having received radical gastrectomy for stage II-III GC was explored. By analyzing the data of LRP1B mRNA, the risk score of differentially expressed genes (DEGs) between LRP1B mutation-type and wild-type was constructed based on the TCGA-STAD cohort. The infiltration of tumor immune cells was evaluated by the CYBERSORT algorithm and verified by immunohistochemistry. LRP1B gene mutation was an independent risk factor for disease-free survival (DFS) in GC patients (HR = 2.57, 95% CI: 1.28-5.14, p = 0.008). The Kaplan-Meier curve demonstrated a shorter survival time in high-risk patients stratified according to risk score (p < 0.0001). CYBERSORT analysis showed that the DEGs were mainly concentrated in CD4+ T cells and macrophages. TIMER analysis suggested that LRP1B expression was associated with the infiltration of CD4+ T cells and macrophages. Immunohistochemistry demonstrated that LRP1B was expressed in the tumor cells (TCs) and immune cells in 16/89 and 26/89 of the cohort, respectively. LRP1B-positive TCs were associated with higher levels of CD4+ T cells, CD8+ T cells, and CD86/CD163 (p < 0.05). Multivariate analysis showed that LRP1B-positive TCs represented an independent protective factor of DFS in GC patients (HR = 0.43, 95% CI: 0.10-0.93, p = 0.042). LRP1B has a high prognostic value in GC. LRP1B may stimulate tumor immune cell infiltration to provide GC patients with survival benefits.

A weighted distance-based dynamic ensemble regression framework for gastric cancer survival time prediction

Accurate prediction of gastric cancer patient survival time is essential for clinical decision-making. However, unified static models lack specificity and flexibility in predictions owing to the varying survival outcomes among gastric cancer patients. We address these problems by using an ensemble learning approach and adaptively assigning greater weights to similar patients to make more targeted predictions when predicting an individual’s survival time. We treat these problems as regression problems and introduce a weighted dynamic ensemble regression framework. To better identify similar patients, we devise a method to measure patient similarity, considering the diverse impacts of features. Subsequently, we use this measure to design both a weighted K-means clustering method and a fuzzy K-means sampling technique to group patients and train corresponding base regressors. To achieve more targeted predictions, we calculate the weight of each base regressor based on the similarity between the patient to be predicted and the patient clusters, culminating in the integration of the results. The model is validated on a dataset of 7791 patients, outperforming other models in terms of three evaluation metrics, namely, the root mean square error, mean absolute error, and the coefficient of determination. The weighted dynamic ensemble regression strategy can improve the baseline model by 1.75%, 2.12%, and 13.45% in terms of the three respective metrics while also mitigating the imbalanced survival time distribution issue. This enhanced performance has been statistically validated, even when tested on six public datasets with different sizes. By considering feature variations, patients with distinct survival profiles can be effectively differentiated, and the model predictive performance can be enhanced. The results generated by our proposed model can be invaluable in guiding decisions related to treatment plans and resource allocation. Furthermore, the model has the potential for broader applications in prognosis for other types of cancers or similar regression problems in various domains.

Diagnostic accuracy of radiomics-based machine learning for neoadjuvant chemotherapy response and survival prediction in gastric cancer patients: A systematic review and meta-analysis

BackgroundIn recent years, researchers have explored the use of radiomics to predict neoadjuvant chemotherapy outcomes in gastric cancer (GC). Yet, a lingering debate persists regarding the accuracy of these predictions. Against this backdrop, this study was conducted to examine the accuracy of radiomics in predicting the response to neoadjuvant chemotherapy in GC patients. MethodsAn exhaustive search of relevant studies was conducted in PubMed, Cochrane, Embase, and Web of Science databases up to February 21, 2023. The radiomics quality scoring (RQS) tool was employed to assess study quality. Tumor response to neoadjuvant chemotherapy and survival outcomes were examined as outcome measures. ResultsFourteen studies involving 3,373 GC patients who had received neoadjuvant chemotherapy were incorporated in our meta-analysis. The mean RQS score across all studies was 36.3%, ranging between 0 and 63.9%. On the validation cohort, when the modeling variables were restricted to radiomic features alone, the predictive performance was characterized by a c-index of 0.750 (95% CI: 0.710–0.790), with a sensitivity of 0.67 (95% CI: 0.58–0.75) and a specificity of 0.77 (95% CI: 0.69–0.84) for the prediction of neoadjuvant chemotherapy response. When clinical data was integrated with radiomic features as modeling variables, the predictive performance improved, yielding a c-index of 0.814 (95% CI: 0.780–0.847), a sensitivity of 0.78 [95% CI: 0.70–0.84], and a specificity of 0.73 [95% CI: 0.67–0.79]. ConclusionsRadiomics holds promise to noninvasively predict neoadjuvant chemotherapy response and survival outcomes among patients with locally advanced GC. Additionally, we underscore the need for future multicenter studies and the development of imaging-sourced tools for risk stratification in this patient population.

DDX24 promotes tumor progression by mediating hexokinase-1 induced glycolysis in gastric cancer

Metabolic reprogramming allows tumor cells to meet high demand of biogenesis and increased energy for rapid proliferation. Gastric cancer (GC) ranks among the most prevalent malignancies globally. Exploring the underlying mechanisms of glycolytic reprogramming in GC could provide new therapeutic target for GC treatment. Here, we showed that DEAD-box helicase 24 (DDX24) played a critical role in hexokinase-1 (HK1) induced glycolysis. DDX24 expression was significantly elevated in GC tissues and was closely associated with worse survival in GC patients. In addition, DDX24 promoted glucose uptake and lactate production in GC cells. Mechanistically, DDX24 could bind the HK1 mRNA and positively regulated HK1 level at the transcriptional level. Moreover, DDX24 promoted the proliferation, migration, and invasion ability of GC cells by upregulating HK1. Collectively, these results suggested that DDX24 was a critical player in the regulation of glycolytic reprogramming and also implicated DDX24 as a valuable therapeutic target for GC.

Discovery of a novel lipid metabolism-related gene signature to predict outcomes and the tumor immune microenvironment in gastric cancer by integrated analysis of single-cell and bulk RNA sequencing

Gastric cancer (GC) is a pressing global clinical issue, with few treatment options and a poor prognosis. The onset and spread of stomach cancer are significantly influenced by changes in lipid metabolism-related pathways. This study aimed to discover a predictive signature for GC using lipid metabolism-related genes (LMRGs) and examine its correlation with the tumor immune microenvironment (TIME). Transcriptome data and clinical information from patients with GC were collected from the TCGA and GEO databases. Data from GC samples were analyzed using both bulk RNA-seq and single-cell sequencing of RNA (scRNA-seq). To identify survival-related differentially expressed LMRGs (DE-LMRGs), differential expression and prognosis studies were carried out. We built a predictive signature using LASSO regression and tested it on the TCGA and GSE84437 datasets. In addition, the correlation of the prognostic signature with the TIME was comprehensively analyzed. In this study, we identified 258 DE-LMRGs in GC and further screened seven survival-related DE-LMRGs. The results of scRNA-seq identified 688 differentially expressed genes (DEGs) between the three branches. Two critical genes (GPX3 and NNMT) were identified using the above two gene groups. In addition, a predictive risk score that relies on GPX3 and NNMT was developed. Survival studies in both the TCGA and GEO datasets revealed that patients categorized to be at low danger had a significantly greater prognosis than those identified to be at high danger. Additionally, by employing calibration plots based on TCGA data, the study demonstrated the substantial predictive capacity of a prognostic nomogram, which incorporated a risk score along with various clinical factors. Within the high-risk group, there was a noticeable abundance of active natural killer (NK) cells, quiescent monocytes, macrophages, mast cells, and activated CD4 + T cells. In summary, a two-gene signature and a predictive nomogram have been developed, offering accurate prognostic predictions for general survival in GC patients. These findings have the potential to assist healthcare professionals in making informed medical decisions and providing personalized treatment approaches.

A novel prognostic and therapeutic target biomarker based on complement-related gene signature in gastric cancer.

Gastric cancer (GC) is one of the most prevalent cancer types that reduce human life expectancy. The current tumor-node-metastasis (TNM) staging system is inadequate in identifying higher or lower risk of GC patients because of tumor heterogeneity. Research shows that complement plays a dual role in the tumor development and progression of GC. We downloaded GC data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). A complement-related risk signature was constructed through bioinformatics analysis. Subsequently, the predictive ability of this signature was validated with GSE84437 dataset, and a nomogram integrating risk score and common clinical factors was established. Besides, we evaluated the association of risk score with the immune and stromal cell infiltration in TCGA. Furthermore, immunotherapy response prediction and drug susceptibility analysis were conducted to access the ability of the risk signature in predicting the therapeutic effect. A complement-related gene (CRG) signature, based on six genes (SPLG, C9, ITIH1, ZFPM2, CD36, and SERPINE1), was established. In both the training and validation sets, the overall survival of GC patients in the high-risk group was lower than that of the low-risk group, and the nomogram to predict the 1-, 2-, and 3-year survival rates of GC patients was developed. In addition, CIBERSORT algorithm showed the high-risk patients had higher levels of immune cell infiltration than low-risk patients, and the ESTIMATE results implied that the high-risk group had more stromal component in tumor microenvironment. Besides, compared to the low-risk group, there were higher expressions of most immune checkpoint genes and HLA genes in the high-risk group, and the high-risk patients showed higher sensitivity to the chemotherapy and targeted drugs (axitinib, dasatinib, pazopanib, saracatinib, sunitinib and temsirolimus). The novel CRG signature may act as a reliable, efficient tool for prognostic prediction and treatment guidance in future clinical practice.

Establishment and validation of a prognostic model for gastric cancer patients of Hebei Province in China.

Hebei Province is a high-risk area for gastric cancer in China, and there is currently no survival prediction model for gastric cancer patients in Hebei Province. This study aimed to build the best survival prediction model for gastric cancer patients in Hebei Province. The development dataset included 1,993 hospitalized gastric cancer patients from the Hebei Cancer Registration Project during 2016 and 2017. Three tree-based machine learning methods [survival trees (ST), random survival forests (RSF), and gradient boosting machines (GBM)] and Cox, were used to develop the models by ten-fold cross validation with 200 iterations. California Chinese hospitalized gastric cancer patients were used as external test models. In addition, we compared the multivariable group with the Tumor Node Metastasis (TNM) group. The 3- and 5-year cancer-specific survival (CSS) rates of the development dataset were 57.07% and 44.48%, respectively. For predicting the 3-year CSS rates of gastric cancer patients of multivariable group, the C-indexes in train datasets were 0.75, 0.72, 0.79 and 0.76 for Cox, ST, RSF and GBM. Multivariable group performed better than TNM group. The predictive ability of Cox and RSF were superior to ST and GBM. A nomogram was established to predict the 3- and 5-year CSS rates of gastric cancer patients. The nomogram was useful for facilitating clinicians to predict the survival of gastric cancer patients, and identifying high-risk patients so as to adopt more reasonable treatment plans.

Clinicopathologic features and prognosis of 71 patients with gastric cancer and disseminated intravascular coagulation.

Gastric cancer consists of solid tumors with a tendency for disseminated intravascular coagulation (DIC). DIC is rare in patients with stomach cancer, and there have been few studies on this condition. We aimed to perform comprehensive analyses of the prognosis and clinicopathologic characteristics of stomach cancer patients with DIC. Between June 2006 and March 2020, 14,016 patients at Fujian Cancer Hospital were diagnosed with stomach cancer. We reviewed their medical records and found that 105 of these patients were diagnosed with DIC. After excluding patients who were lost to follow-up, 71 patients with DIC remained. The clinical data were retrospectively analyzed to observe clinical characteristics and prognostic factors, and the Kaplan-Meier survival analysis was performed. Prognostic variables were investigated by the Cox proportional hazards method. The median age was 54 (range, 21-83) years, and 38 patients (53.5%) were male. The histological category was poorly differentiated gastric cancer in 58 patients (81.7%). Eleven patients (15.5%) developed DIC after curative gastric resection. Sixty patients (84.5%) had DIC at the initial presentation of gastric cancer or developed DIC when the tumor progressed during treatment. Fifty-one patients (71.8%) had bleeding symptoms, and 43 (60.6%) patients had comorbidities at the time of DIC diagnosis. Among the 71 patients, 42 (59.2%) had multiple metastatic patterns. Twenty-one (29.6%) patients received chemotherapy. The median overall survival (OS) was 57.0 days (95% confidence interval [CI] [33.1-80.9] days). Tumor status (P = 0.000) and treatment (P = 0.003) were found to be significant variables associated with OS by univariate analysis. Multivariate analysis showed that tumor status (P = 0.000) and treatment (P = 0.000) had independent effects on OS. Gastrointestinal bleeding, multiple metastatic patterns and comorbidities at diagnosis with DIC are common in patients with gastric cancer complicated with DIC. Patients with poorly differentiated gastric cancer are more likely to develop DIC. Treatment and tumor status are separate risk variables for the survival of gastric cancer patients with DIC.DIC patients without tumors have a good prognosis and can be cured by appropriate etiological correction and symptomatic treatment. Chemotherapy can improve the prognosis of DIC patients with tumors.

Metabolic and immune-related gene signatures: Predictive stratification and prognostic implications in gastric cancer.

Gastric cancer, marked by its heterogeneous nature, showcases various molecular subtypes and clinical trajectories. This research delves into the significance of metabolic and immune-driven pathways in gastric cancer, constructing a prognostic signature derived from differentially expressed metabolic and immune-correlated genes (DE-MIGs). Metabolic and immune-associated gene were sourced from the GeneCards database. Differential expression analysis on the TCGA-STAD dataset was executed using the limma package, unveiling 51 DE-MIGs that underwent functional enrichment scrutiny. The LASSO Cox regression methodology guided the creation of the prognostic signature, and individual patient risk scores were determined. Assessment tools like CIBERSORT, ESTIMATE and ssGSEA were deployed to study the immune microenvironment, while mutation profiles, genomic stability, resistance to chemotherapy and immunotherapy responsiveness were scrutinized across distinct signature categorizations. Among the identified DE-MIGs, 26 were significantly tied to the overall survival of gastric cancer patients. The developed prognostic signature proficiently differentiated patients into high-risk and low-risk cohorts, with the latter showing markedly better outcomes. The study underscored the centrality of the immune microenvironment in influencing gastric cancer outcomes. Key pathways such as TGF-Beta, TP53 and NRF2 dominated the high-risk group, whereas the LRTK-RAS and WNT pathways characterized the low-risk group. Interestingly, the low-risk segment also manifested a heightened tumor mutation burden and enhanced susceptibility to immunotherapy. Our findings introduce a pivotal prognostic signature, rooted in DE-MIGs, that effectively segregates gastric cancer patients into distinct risk-based segments. Insights into the influential role of the immune microenvironment in gastric cancer progression pave the way for more refined therapeutic interventions.

Increased expression of LINC00323 correlates with tumor progression and poor prognosis of gastric cancer.

LINC00323 is a novel lncRNA which has reported to play an important role in the development and recurrence in several cancers. However, the expression and predictive value of LINC00323 in gastric cancer (GC) remain mysterious. LINC00323 expression in GC tissues and adjacent normal tissues was evaluated by quantitative reverse-transcription PCR (qRT-PCR). The relationship between LINC00323 expression and clinicopathological features and patients' survival were analyzed. Univariate and multivariate survival analyses were performed. LINC00323 expression were found to be significantly increased in GC tissues. High expression of LINC00323 exerted a pro-tumor effect in the late stage of GC development. Kaplan-Meier analysis showed that patients with high LINC00323 were associated with poor overall survival (OS) and progression-free survival (PFS). Moreover, the combination of TNM stage and drinking status better identified GC patient outcome than those of TNM stage alone. Our data showed that LINC00323 overexpression might serve as a novel independent prognostic factor for survival of GC patients, suggesting LINC00323 was a potential biomarker and therapeutic target for GC.

Prognostic significance of a five-factor modified frailty index in patients with gastric cancer undergoing curative-intent resection: A cohort study.

The 5-factor modified frailty index (mFI-5) evaluates frailty based on variables including functional status, diabetes, chronic obstructive pulmonary disease, congestive heart failure, and hypertension requiring medication. Despite its effectiveness in predicting surgical risk, the potential of mFI-5 as a predictor of long-term survival in patients with gastric cancer (GC) has not been investigated. This study aims to assess the prognostic significance of mFI-5 in patients with GC who have undergone curative-intent gastric resection. Among the 494 patients diagnosed with stage I to III GC, multivariate analysis revealed that age, tumor-node-metastasis (TNM) stage, geriatric nutritional risk index, mFI-5, and the type of gastrectomy were significant predictors for both overall survival (OS) and disease-free survival (DFS). We assessed 3 models: Baseline model (BM, TNM stage only), interim model (IM, all significant variables except mFI-5), and full model (FM, all significant variables including mFI-5). FM outperformed BM for OS (C-index 0.818 vs 0.683; P < .001) and DFS (C-index 0.805 vs 0.687; P < .001). Similarly, IM outperformed BM for OS (C-index 0.811 vs 0.683; P < .001) and DFS (C-index 0.797 vs 0.687; P < .001). Multiple metrics consistently supported the improved discriminative capacity of FM and IM compared to BM. However, while FM exhibits enhanced predictive capacity over IM, this improvement lacks statistical significance across key metrics. In conclusion, our study highlights the clinical significance of the mFI-5, along with age, TNM stage, geriatric nutritional risk index, and type of gastrectomy, as valuable predictors of long-term survival in GC patients. The FM consistently demonstrates enhanced predictive accuracy compared to the BM. However, it is important to note that while the FM improves predictive power over the IM, this enhancement does not achieve statistical significance across multiple metrics. These findings collectively emphasize the potential clinical value of the FM as a robust tool for surgeons in predicting long-term survival outcomes before surgery in patients with GC.

GLUL stabilizes N-Cadherin by antagonizing β-Catenin to inhibit the progresses of gastric cancer

Glutamate-ammonia ligase (GLUL, also known as glutamine synthetase) is a crucial enzyme that catalyzes ammonium and glutamate into glutamine in the ATP-dependent condensation. Although GLUL plays a critical role in multiple cancers, the expression and function of GLUL in gastric cancer remain unclear. In the present study, we have found that the expression level of GLUL was significantly lower in gastric cancer tissues compared with adjacent normal tissues, and correlated with N stage and TNM stage, and low GLUL expression predicted poor survival for gastric cancer patients. Knockdown of GLUL promoted the growth, migration, invasion and metastasis of gastric cancer cells in vitro and in vivo, and vice versa, which was independent of its enzyme activity. Mechanistically, GLUL competed with β-Catenin to bind to N-Cadherin, increased the stability of N-Cadherin and decreased the stability of β-Catenin by alerting their ubiquitination. Furthermore, there were lower N-Cadherin and higher β-Catenin expression levels in gastric cancer tissues compared with adjacent normal tissues. GLUL protein expression was correlated with that of N-Cadherin, and could be the independent prognostic factor in gastric cancer. Our findings reveal that GLUL stabilizes N-Cadherin by antagonizing β-Catenin to inhibit the progress of gastric cancer.

Microsatellite instability in gastric cancer: An institutional case series analysis in patients treated with neoadjuvant therapy

IntroductionPast studies documented that microsatellite instability (MSI) is associated with improved survival in gastric cancer (GC). The aim of this study was to evaluate MSI status in a series of GCs treated with neoadjuvant therapy in relation to the tumors' characteristics and oncological outcomes. MethodsPatients with GCs treated between 2017 and 2022 ​at a single Italian high-volume Institution undergoing pre-operative treatment followed by resection were included if studied for their microsatellite status. Clinicopathological data were analyzed for the association with MSI. The same features were analyzing pooling the series with a subset of patients from another European trial.Secondary outcomes included the overall (OS), and disease-free (DFS) survivals comparing MSI vs microsatellite stable (MSS) GCs, and GCs presenting complete-major response (TRG1-2) vs partial response (TRG3-4) and absence of response (TRG5). ResultsAmong 73 patients selected, 12.3% were MSI. In the single institutional analysis, we documented a difference in the distribution of ypT stages with a prevalence of ypT0 patients in MSI vs MSS patients (ypT0 respectively 11.1% vs 1.6%, p ​< ​0.0001). However, this difference was not of statistical value when pooling patients with those from the European trial (overall 108 patients, 9.2% MSI; ypT0 respectively 10.0% vs 2.0%, p 0.144). In the pooled analysis, a prevalence of female patients was reported in the MSI group comparing MSS (respectively, 70.0% vs 27.6%, p 0.01). At a mean follow-up of 27.7 months, OS and DFS survivals were reported similar comparing MSS and MSI (log-rank test respectively p 0.18 and p 0.96), however TRG1-2 ​GCs had improved OS and DFS comparing other sub-groups (TRG1-2 vs TRG3-4 vs TRG5, OS and DFS log-rank test respectively p 0.017 and p 0.0029). ConclusionThis study could not demonstrate a correlation between microsatellite status and survival in gastric cancer patients who underwent pre-operative treatment. A complete/major response was the only variable correlated with mid-term survival.

Laparoscopic radical gastrectomy for gastric cancer: Long-term outcome in a teaching center

BackgroundLaparoscopic gastrectomy for gastric cancer (GC) are increasing, yet the evidence of the relationship between the learning curve and long-term outcomes is limited. AimsTo analyze the relationship between the learning curve and survival in GC patients over a 10-year period. MethodsThis retrospective cohort study studied 3674 patients who underwent laparoscopic radical gastrectomy for gastric cancer. Cusum and Cox regression analysis were used to assess the association between the surgeon's experience and the 3 years overall survival (OS). ResultsThe 3-year OS of all patients was 71.8 %. This increase of 3-year OS was associated with laparoscopic cases (r = 0.638, p = 0.047). Analysis of the CUSUM curve showed a significant change in the 3-year OS of 1400 cases. Further propensity score matching (PSM) of patients during and after the learning curve (<1400 and ≥ 1400 cases) showed a significant difference in the 3-year OS between the two groups (68.5 % vs. 72.3 %, p = 0.045). Cox regression analysis verified that in ≥1400 cases, prior laparoscopic surgery (p = 0.045), textbook outcome (TO) and the number of retrieved lymph nodes (LNs) were independent protective factors. The LN non-compliance rate was an independent risk factor. In contrast, the rate of TO and the median number of retrieved LNs were significantly higher after the learning curve (≥1400 cases). Furthermore, the rates of LN non-compliance were significantly lower (p < 0.05). ConclusionsIncreasing laparoscopic surgical experience is associated with surgical quality and prognostic improvement in patients with gastric cancer. But improvements in outcomes accrued slowly over a long period.

Comparison of Clinicopathological Features and Prognosis of Mucinous Gastric Carcinoma and other Gastric Cancers: A Retrospective Study of 4,417 Patients

BackgroundMucinous gastric carcinoma (MGC) is a distinct histologic subtype of gastric cancer (GC) that is often diagnosed at an advanced stage. The clinicopathological characteristics and prognosis of MGC, when compared to adenocarcinoma and signet-ring cell carcinoma (SRCC), are currently subjects of debate and require further investigation. MethodsIn this study, we conducted an investigation on 4,417 patients who were hospitalized with GC at Zhejiang Cancer Hospital between April 2008 and December 2019. The objective was to compare the prognosis and clinicopathological characteristics of MGC with other types of GC. ResultsIn comparison to adenocarcinoma, MGC patients exhibited more advanced tumor infiltration (p < 0.001), lower tumor differentiation (p < 0.001), and higher rates of preoperative tumor marker positivity (except for AFP and CA125) (all p < 0.05). However, after propensity score matching (PSM) to eliminate confounding factors, MGC patients surprisingly exhibited a better prognosis than adenocarcinoma patients (p = 0.008), and the results in multifactorial COX regression were similar (HR = 0.792, 95% CI 0.629–0.997, p = 0.047). Among patients with MGC, age, pN stage, as well as preoperative levels of CA125 and CA724 (all p < 0.05), emerged as independent prognostic markers. While overall survival did not significantly differ between MGC and SRCC (p = 0.196), significant survival disparities emerged in advanced-stage patients (p = 0.009), with MGC showing better survival rates. Furthermore, a nomogram was developed to predict 1-, 3-, and 5-year survival in gastric cancer patients based on various factors, achieving a C-index of 0.772 (95% CI: 0.745–0.799). ConclusionsWhile the poorer prognosis associated with MGC may be linked to its advanced stage and lower degree of differentiation, its biological behavior could contribute to improved survival.

Impact of anastomotic leakage on survival after surgery for gastric carcinoma: A PRISMA systematic review and meta-analysis.

The long-term survival of postoperative anastomotic leakage (AL) following gastric cancer (GC) surgery is still debating. Our aim was to investigate the association between AL and survival of the patients following GC. We searched articles in databases from inception to July 2023 to retrieve literature related to postoperative AL and survival of GC patients. We evaluated the association of postoperative AL and survival of GC patients using the software STAT10.0. Seven articles with 6209 GC patients were included. Our results showed that the postoperative AL were associated with pooled 1-year patient overall survival (OS) result in an odds ratio (OR) of 0.504 (95% confidence interval (CI): 0.372-0.682; I2 = 84.1%; P = .000), pooled 3-year patient OS (OR = 0.467, 95% CI: 0.356-0.614; I2 = 85.3%; P = .000) and pooled 5-year patient OS (OR = 0.370, 95% CI: 0.171-0.805; I2 = 82.5%; P = .012). The P value of Egger test were 0.759, 0.187, 0.175. The postoperative AL were associated with pooled 1-year patient disease-free survival (DFS) result in an OR of 0.538 (95% CI: 0.171-1.691; I2 = 89.0%; P = .289), the pooled 3-year patient DFS (OR = 0.143, 95% CI: 0.119-1.431; I2 = 91.7%; P = .163), and the pooled 5-year patient DFS (OR = 0.344, 95% CI: 0.088-1.338; I2 = 91.0%; P = .124), and the P value of Egger test of pooled 1-, 3-, and 5-year DFS were 0.759, 0.247, 0.07. Postoperative AL was correlated with a worse OS in GC patients, but not correlated with DFS in GC patients, but more studies are required to confirm this conclusion.

RETRACTED: Hierarchical clustering identifies oxidative stress-related subgroups for the prediction of prognosis and immune microenvironment in gastric cancer

BackgroundGastric cancer (GC) is a prevalent malignancy of the digestive tract globally, demonstrating a substantial occurrence of relapse and metastasis, alongside the absence of efficacious treatment. Tumor progression and the development of cancer are linked to oxidative stress. Our objective was twofold: first, to determine distinct subcategories based on oxidative stress in GC patients, and second, to establish oxidative stress-related genes that would aid in stratifying the risk for GC patients. MethodsTCGA-STAD and GSE84437 datasets were utilized to obtain the mRNA expression profiles and corresponding clinical information of GC patients. Through consensus clustering analysis, distinct subgroups related to oxidative stress were identified. To uncover the underlying mechanisms, GSEA and GSVA were performed. xCell, CIBERSORT, MCPCounter, and TIMER algorithms were employed to evaluate the immune microenvironment and immune status of the different GC subtypes. A prognostic risk model was developed using the TCGA-STAD dataset and substantiated using the GSE84437 dataset. Furthermore, qRT-PCR was employed to validate the expression of genes associated with prognosis. ResultsTwo distinct subtypes of oxidative stress were discovered, with markedly different survival rates. The C1 subtype demonstrated an activated immune signal pathway, a significant presence of immune cell infiltration, high immune score, and a high microenvironment score, indicating a poor prognosis. Moreover, a prognostic signature related to oxidative stress (IMPACT and PXDN) was able to accurately estimate the likelihood of survival for patients with gastric cancer. A nomogram incorporating the patients' gender, age, and risk score was able to predict survival in gastric cancer patients. Additionally, the expression of IMPACT and PXDN showed a strong correlation with overall survival and the infiltration of immune cells. ConclusionBased on signatures related to oxidative stress, we developed an innovative system for categorizing patients with GC. This stratification enables accurate prognostication of individuals with GC.

Bacterial lipopolysaccharide related genes signature as potential biomarker for prognosis and immune treatment in gastric cancer

The composition of microbial microenvironment is an important factor affecting the development of tumor diseases. However, due to the limitations of current technological levels, we are still unable to fully study and elucidate the depth and breadth of the impact of microorganisms on tumors, especially whether microorganisms have an impact on cancer. Therefore, the purpose of this study is to conduct in-depth research on the role and mechanism of prostate microbiome in gastric cancer (GC) based on the related genes of bacterial lipopolysaccharide (LPS) by using bioinformatics methods. Through comparison in the Toxin Genomics Database (CTD), we can find and screen out the bacterial LPS related genes. In the study, Venn plots and lasso analysis were used to obtain differentially expressed LPS related hub genes (LRHG). Afterwards, in order to establish a prognostic risk score model and column chart in LRHG features, we used univariate and multivariate Cox regression analysis for modeling and composition. In addition, we also conducted in-depth research on the clinical role of immunotherapy with TMB, MSI, KRAS mutants, and TIDE scores. We screened 9 LRHGs in the database. We constructed a prognostic risk score and column chart based on LRHG, indicating that low risk scores have a protective effect on patients. We particularly found that low risk scores are beneficial for immunotherapy through TIDE score evaluation. Based on LPS related hub genes, we established a LRHG signature, which can help predict immunotherapy and prognosis for GC patients. Bacterial lipopolysaccharide related genes can also be biomarkers to predict progression free survival in GC patients.