Prognostic Indicator In Gastric Cancer Research Articles

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

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

Pyroptosis-related gene signature for predicting gastric cancer prognosis.

Gastric cancer (GC) is a prevalent form of malignancy characterized by significant heterogeneity. The development of a specific prediction model is of utmost importance to improve therapy alternatives. The presence of H. pylori can elicit pyroptosis, a notable carcinogenic process. Furthermore, the administration of chemotherapeutic drugs is often employed as a therapeutic approach to addressing this condition. In the present investigation, it was observed that there were variations in the production of 17 pyroptosis-regulating proteins between stomach tissue with tumor development and GC cells. The predictive relevance of each gene associated with pyroptosis was assessed using the cohort from the cancer genome atlas (TCGA). The least absolute shrinkage and selection operator (LASSO) was utilized to enhance the outcomes of the regression approach. Patients with gastric cancer GC in the cohort from the TCGA were categorized into low-risk or high-risk groups based on their gene expression profiles. Patients with a low risk of gastric cancer had a higher likelihood of survival compared to persons classified as high risk (P<0.0001). A subset of patients diagnosed with GC from a Genes Expression Omnibus (GEO) cohort was stratified according to their overall survival (OS) duration. The statistical analysis revealed a higher significance level (P=0.0063) regarding OS time among low-risk individuals. The study revealed that the GC risk score emerged as a significant independent prognostic factor for OS in patients diagnosed with GC. The results of Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) research revealed that genes associated with a high-risk group had significantly elevated levels of immune system-related activity. Furthermore, it was found that the state of immunity was diminished within this particular group. The relationship between the immune response to cancer and pyroptosis genes is highly interconnected, suggesting that these genes have the potential to serve as prognostic indicators for GC.

CC chemokine receptors are prognostic indicators of gastric cancer and are associated with immune infiltration

BackgroundCC chemokine receptors are responsible for regulating the tumor microenvironment (TME) and participating in carcinogenesis and tumor advancement. However, no functional study has investigated CC chemokine receptors in gastric cancer (GC) prognosis, risk, immunotherapy, or other treatments.MethodsWe conducted a bioinformatics analysis on GC data using online databases, including the Human Protein Atlas (HPA), Kaplan-Meier (KM) plotter, GeneMANIA, MethSurv, the University of ALabama at Birmingham CANcer (UALCAN) Data Analysis Portal, Gene Set Cancer Analysis (GSCA), cBioportal, and Tumor IMmune Estimation Resource (TIMER).ResultsWe noted that CC chemokine receptor expression correlated with survival in GC. CC chemokine receptor expression was also strongly linked to different tumor-infiltrating immune cells. Additionally, CC chemokine receptors were found to be broadly drug-resistant in GC.ConclusionOur study identifed CC chemokine receptor expression helped in predicting the prognosis of patients diagnosed with GC. The expression level of the CC chemokine receptors was also positively related to multiple tumor-infiltrating lymphocytes (TILs). These findings provide evidence to monitor patients with GC using CC chemokine receptors, which can be used as an effective biomarker for predicting the disease prognosis and be regarded as a therapeutic target for modulating the tumor immune microenvironment.

Expression of selected long non-coding RNAs in gastric cancer cells treated with coumarin: Possible mechanisms for anti-cancer activity

Long non-coding RNAs (lncRNAs) can be utilized as prognostic indicators of gastric cancer since they can affect several cancer-related processes. Coumarin is a natural product with some useful anti-cancer properties. Here, we measured the expression of selected lncRNAs (RuPAR, SNHG6, CASC11, and their targets, miR-340–5p, p21, E-cadherin, and CDK1) in AGS gastric cancer cells treated with coumarin. MTT test has been utilized for assessing the AGS cells’ cell viability after exposure to coumarin. The expression of the lncRNAs (RuPAR, SNHG6, and CASC11) and miR-340–5p was evaluated via qRT-PCR. Western blot analysis has been utilized to determine changes in p21, E-cadherin, and CDK1 expression. Coumarin decreased AGS viability in a dose-dependent manner. The coumarin treated cells had lower levels of the mRNAs known to be targets of lncRNAs SNHG6 and CASC11 compared to control. Additionally, the coumarin group had increased levels of lncRNA RuPAR expression when compared with the control group. Some lncRNA targets, including p21, E-cadherin, and CDK1, showed lower expression in the coumarin group compared to the control by Western blotting. Coumarin could be a promising pharmacological candidate to be included in gastric cancer treatment regimens because it modulates lncRNAs and their targets.

Immune responses of six-transmembrane epithelial antigen of the prostate 4 functions as a novel biomarker in gastric cancer.

Immune cells play an important role in regulating the behavior of tumor cells. According to emerging evidence, six-transmembrane epithelial antigen of the prostate 4 (STEAP4) performs a crucial part in tumor microenvironmental immune response and tumorigenesis, and serves as the potential target for cellular and antibody immunotherapy. However, the immunotherapeutic role of STEAP4 in gastric cancer (GC) remains unclear. To investigate the expression of STEAP4 in GC and its relationship with immune infiltrating cells, and explore the potential value of STEAP4 as an immune prognostic indicator in GC. The expression level of STEAP4 was characterized by immunohistochemistry in tumors and adjacent non-cancerous samples in 96 GC patients. Tumor Immune Estimation Resource was used to study the correlation between STEAP4 and tumor immune infiltration level and immune infiltration gene signature. R package was used to analyze the relationship between STEAP4 expression and immune and stromal scores in GC (GSE62254) by the ESTIMATE algorithm, and Kaplan-Meier Plotter and Gene Expression Profiling Interactive Analysis were applied to analyze the effect of STEAP4 on clinical prognosis. Immunohistochemistry analysis showed that STEAP4 expression was higher in GC tissues than in adjacent tissues, and STEAP4 expression was positively correlated with the clinical stage of GC. In GC, the expression of STEAP4 was positively correlated with the infiltration levels of B cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells. The expression level of STEAP4 was strongly correlated with most of the immune markers. In addition, STEAP4 expression was inversely correlated with tumor purity, but correlated with stromal score (r = 0.43, P < 0.001), immune score (r = 0.29, P < 0.001) and estimate score (r = 0.39, P < 0.001). Moreover, stromal, immune, and estimate scores were higher in the STEAP4 high expression group, whereas tumor purity was higher in the STEAP4 Low expression group. The relationship between STEAP4 expression and prognosis of patients with GC was further investigated, and the results showed that high STEAP4 expression was associated with poor overall survival and disease-free survival. In addition, Kaplan-Meier Plotter showed that high expression of STEAP4 was significantly correlated with poor survival of patients with GC. The current findings suggest an oncogenic role for STEAP4 in GC, with significantly high levels being associated with poor prognosis. Investigation of the GC tumor microenvironment suggests the potential function of STEAP4 is connected with the infiltration of diverse immune cells, which may contribute to the regulation of the tumor microenvironment. In conclusion, STEAP4 may serve as a potential therapeutic target for GC to improve the immune infiltration, as well as serve as a prognostic biomarker for judging the prognosis and immune infiltration status of GC.

Feasibility evaluation of hsa_circ_0005480 as an auxiliary diagnostic and prognostic indicator for gastric cancer.

Aim: To explore the potential role of hsa_circ_0005480 as a marker for gastric cancer (GC). Methods: GSE83521, GSE93541 and GSE131414 were combined to screen the most potential circRNAs in GC. The expression of hsa_circ_0005480 was verified in clinical plasma samples and its diagnostic performance was evaluated by receiver operating characteristic (ROC)curve. Results: Hsa_circ_0005480 was upregulated in newly diagnosed GC patients, and performed well in distinguishing GC patients from healthy donors. Combination of hsa_circ_0005480 with traditional laboratory metrics showed increased sensitivityand accuracy than standalone application. In addition, hsa_circ_0005480 expression was low in GC patients treated with chemoradiotherapy or surgery, and decreased dynamically about 1 week postoperatively. Conclusion: Hsa_circ_0005480 may prove to be a marker for auxiliary diagnosis and prognostic evaluation of GC.

T-cells infiltration mediates the association between neutrophil/lymphocyte ratio and survival in gastric cancer.

Neutrophil/lymphocyte ratio (NLR) is a vital index for systemic inflammation and a prognostic indicator for gastric cancer (GC). Despite the abundant literature on NLR's prognostic value for GC, the underlying factors mediating its impact on survival remain unclear. The objective of this study was to analyze the role of NLR in different prognostic models and subgroups, and investigate the mediating effects of immune infiltrates between NLR and survival. A total of 924 patients who underwent D2 lymph node resection were enrolled in this study. According to the level of NLR, patients were divided into two groups, the high and low NLR groups. Clinical parameters, indexes related to immune infiltrates, and survival were compared between the two groups. Prognostic models, interaction analysis, and mediating effects analysis were performed to investigate the clinical association of NLR, immune infiltrates, and survival. The infiltration of CD3+ and CD8+ T cells was significantly different in the two NLR groups. The level of NLR was an independent prognostic predictor of GC. In addition, an interaction effect exists between NLR and MMR status on the prognosis of GC (p-interaction <0.01). Lastly, the mediating effect analysis revealed that the infiltration level of CD3+ T cells was the mediating factor between NLR and survival (p < 0.001). The level of NLR is an independent prognostic predictor of GC. The effect of NLR on prognosis is partly mediated by CD3+ T-cell infiltration.

Integrated bioinformatics analysis for exploring hub genes and related mechanisms affecting the progression of gastric cancer

ABSTRACT Objective Gastric cancer (GC) is a high-risk tumor disease worldwide. The goal of the current study was to explore new diagnostic and prognostic indicators for gastric cancer. Methods Database GSE19826 and GSE103236 were gained from the Gene Expression Omnibus (GEO) to screen for differentially expressed genes (DEGs), which were then grouped together as co-DEGs. GO and KEGG pathway analysis were used to investigate the function of these genes. The protein-protein interaction (PPI) network of DEGs was constructed by STRING. Results GSE19826 selected 493 DEGs in GC and gastric normal tissues, including 139 up-regulated genes and 354 down-regulated genes. A total of 478 DEGs were selected by GSE103236, including 276 up-regulated genes and 202 downregulated genes. 32 co-DEGs were overlapped from two databasesand involved in digestion, regulation of response to wounding, wound healing, potassium ion imports across plasma membrane, regulation of wound healing, anatomical structure homeostasis, and tissue homeostasis. KEGG analysis revealed that co-DEGs were mainly involved in ECM-receptor interaction, tight junction, protein digestion and absorption, gastric acid secretion and cell adhesion molecules. Twelve hub genes were screened by Cytoscape, including cholecystokinin B receptor (CCKBR), Collagen type I alpha 1 (COL1A1), COL1A2, COL2A1, COL6A3, COL11A1, matrix metallopeptidase 1 (MMP1), MMP3, MMP7, MMP10, tissue inhibitor of matrix metalloprotease 1 (TIMP1) and secreted phosphoprotein 1 (SPP1). Conclusions Twelve key genes affecting the progression of gastric cancer were obtained by bioinformatics, which may be potential biomarkers for the diagnosis and prognosis of GC.

Lymphocyte subset is more suitable than systemic inflammatory response biomarker and immunoglobulin in constructing prognostic nomogram model for advanced gastric cancer

The serum factors of inflammation are known to be useful prognostic indicators of gastric cancer (GC). However, few studies have made comparisons to screen out more suitable biomarkers for the construction of Nomogram models. In this study, 566 patients who underwent radical gastrectomy were randomly selected. We evaluated the prognostic value of markers of systemic inflammation, including WBC, NLR, PLR, circulating total T cells, CD4+T cells, CD8+T cells and CD19+B cells, serum IgA, IgM, IgE and IgG, and compared them with traditional tumor markers (CEA, CA19-9, CA72-4 and CA125). Kaplan‒Meier analysis was used to analyze the correlation between biomarkers and overall survival (OS). We used time-dependent ROC analysis to investigate the prognostic accuracy of each biomarker. The risk of death was evaluated by the Cox regression model, and the Nomogram model was constructed by R software. We found that circulating total T cells, CD8+T cells, CEA, and CA125 had statistical significance in predicting advanced GC prognosis. Circulating CD8+T cells and CA125 were continuously superior to circulating total T cells and CEA in the prediction of 5-year OS. Cox regression found that CA125, circulating CD8+T cells, sex, and lymph node metastasis rate were independent risk factors for advanced GC. Furthermore, we combined all these predictors to construct a nomogram, which can supplement the AJCC 8th system. According to the comparison with commonly used serum immune biomarkers, circulating CD8+T cells is more sensitive to advanced GC. The prediction function of the Nomogram will supplement the traditional AJCC system, which contributes to individual survival prediction.

Prognostic value of hyaluronidase-1 and CD44 immunohistological expression in gastric cancer

Abstract Introduction Although many studies have investigated molecular markers for gastric cancer, the mechanisms of carcinogenesis remain obscure. CD44 serves as the principal transmembrane hyaluronate receptor. HAS1 has been identified as a key contributor to oncogenesis and disease progression in both hematological and solid cancers HAS1 has been shown to be prognostic factor in a variety of other cancers. Aim Our aim was to evaluate the expression of the CD44 and HAS1 as prognostic indicators for gastric cancer. Methodology Seventy five cases of gastritis and gastric cancer, obtained from the archives of Pathology Departments of Theodor Bilharz Research Institute (TBRI) – Giza, Egypt, including eleven case with gastritis and sixty four cases of gastric cancer. Detailed histopathological assessment was done as well as immunohistochemical staining for CD44 and HAS1. Results Our results showed increased expression of both HAS1 &amp;CD44 with increasing grades and stages as well lymph node metastasis of gastric carcinoma. No significant difference was noticed in their expression between H.pylori associated and non-associated gastritis. Conclusion We concluded that modulation of HAS1/ CD44 expression is of significant prognostic value in gastric cancer and could be a major target for the anticancer and chemo-preventive agents.

LncRNA SNHG22 promotes gastric cancer progression by regulating the miR-101-3p/e2f2 axis

ABSTRACT Gastric cancer (GC) still poses a significant threat to human life. Hence, there is an urgent need to understand the mechanism of GC progression and develop novel therapeutics approach to treating GC. This study was conducted to evaluate the role of the lncRNA SNHG22 in the progression of GC. First, GC data from TCGA were analyzed using GEPIA. After the starbase database was used to predict SNHG22 target miRNA and miR-101-3p target mRNA. The predictions were validated using a dual-luciferase reporter assay, biotinylated RNA pull-down assay, and RIP-qRT-PCR. The relative expression of SNHG22, miR-101-3p, and E2F2 was measured by qRT-PCR and western blot (WB) analysis, while the mechanism of GC cell proliferation was elucidated through the colony formation and CCK-8 assay. Our result showed that SNHG22 was upregulated significantly in GC tissue samples from TCGA database, GC cell lines, and clinical tissue samples, and its expression was related to low survival rate of gastric cancer patients. Bioinformatics prediction predicted miR-101-3p as the potential target of SNHG22 and E2F2 genes as miR-101-3p target mRNA. We found that E2F2 expression was negatively associated with overall survival of GC patients. Functional study showed that silencing SNHG22 markedly inhibited the proliferation, migration, and invasion of GC cells as well as in vivo tumor growth. This was reversed after inhibiting miR-101-3p or overexpressing E2F2. The lncRNA SNHG22 promotes the proliferation, migration, and invasion of GC cells via the miR-101-3p/E2F2 axis. SNHG22 might be a potential prognostic indicator in gastric cancer.

Schlafen family is a prognostic biomarker and corresponds with immune infiltration in gastric cancer.

The Schlafen (SLFN) gene family plays an important role in immune cell differentiation and immune regulation. Previous studies have found that the increased SLFN5 expression in patients with intestinal metaplasia correlates with gastric cancer (GC) progression. However, no investigation has been conducted on the SLFN family in GC. Therefore, we systematically explore the expression and prognostic value of SLFN family members in patients with GC, elucidating their possible biological function and its correlation with tumor immune cells infiltration. TCGA database results indicated that the SLFN5, SLFN11, SLFN12, SLFN12L, and SLFN13 expression was significantly higher in GC. The UALCAN and KM plotter databases indicated that enhanced the SLFN family expression was associated with lymph node metastasis, tumor stage, and tumor grade and predicted an adverse prognosis. cBioportal database revealed that the SLFN family had a high frequency of genetic alterations in GC (about 12%), including mutations and amplification. The GeneMANIA and STRING databases identified 20 interacting genes and 16 interacting proteins that act as potential targets of the SLFN family. SLFN5, SLFN11, SLFN12, SLFN12L, and SLFN14 may be implicated in the immunological response, according to Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Additionally, Timer and TISIDB databases indicate that SLFN5, SLFN11, SLFN12, SLFN12L, and SLFN14 are involved in the immune response. Furthermore, Timer, TCGA, and TISIDB databases suggested that the SLFN5, SLFN11, SLFN12, SLFN12L, and SLFN14 expression in GC is highly linked with immune cell infiltration levels, immune checkpoint, and the many immune cell marker sets expression. We isolated three samples of peripheral blood mononuclear cell (PBMC) and activated T cells; the results showed the expression of SLFN family members decreased significantly when T cell active. In conclusion, the SLFN family of proteins may act as a prognostic indicator of GC and is associated with immune cell infiltration and immune checkpoint expression in GC. Additionally, it may be involved in tumor immune evasion by regulating T cell activation.

MiR-548 predicts clinical prognosis and functions as a tumor promoter in gastric cancer.

Numerous pieces of evidence have demonstrated the functional role of miR-548 in various cancers. The expression and function of miR-548 in gastric cancer were investigated in the present study. A total of 123 gastric cancer patients were included and provided paired gastric cancer tissues and matched normal tissues. RT-qPCR was used to detect the expression of miR-548. CCK8 assay was used to evaluate cell proliferation, and Transwell assay was applied to assess cell migration and invasion. The clinical significance of miR-548 was estimated by a series of statistical analyses. miR-548 was found to be upregulated in gastric cancer, which was associated with the lymph node metastasis and TNM stage of patients. Patients with relatively high miR-548 expression possessed bad survival. miR-548 was identified as a prognostic indicator of gastric cancer. miR-548 was also found to promote the proliferation, migration, and invasion of gastric cancer. Upregulated miR-548 was involved in the progression of gastric cancer and predicted the prognosis of patients. Inhibition of miR-548 might be a novel therapeutic strategy for gastric cancer.

FSIP1 Is Associated with Poor Prognosis and Can Be Used to Construct a Prognostic Model in Gastric Cancer.

Gastric cancer (GC) is one of the most common upper gastrointestinal malignant tumors, and the incidence of the GC shows an increasing trend in the past years. Finding more sensitive markers will help to reveal the mechanism of GC progression and clinic diagnoses. This study first analyzed the mRNA expression level of FSIP1 in TCGA GC samples and the significance in predicting the prognosis. KEGG and GO analyses were used to explore the molecular mechanism of FSIP1 in GC progression. This study further retrospectively analyzed 166 clinical samples of GC from Harbin Medical University Cancer Hospital and evaluated the expression level of FSIP1 by immunohistochemistry. Kaplan-Meier and Cox multivariate analysis was used to investigate the prognostic value of FSIP1 expression in GC patients. We also identified correlations between FSIP1 and clinicopathological characteristics. This study found that the mRNA level of FSIP1 was significantly upregulated in GC compared with nontumor specimens and correlated with poor prognosis. Immunohistochemistry confirmed the results of bioinformatics analysis of the TCGA GC database. FSIP1 was associated with pTNM pathological stage, tumor location, and neural invasion. In addition, multivariate Cox regression analysis showed that FSIP1, T classification, and N classification were independent posterior factors of patients and could be combined with pathological features to construct a nomogram prognostic model. Overall, our results suggest that FSIP1 is expected to be an independent prognostic indicator of GC.

LINC00922 promotes deterioration of gastric cancer.

Several studies have demonstrated the association of lncRNAs with a variety of cancers. Here, we explored the role of LINC00922 in gastric cancer (GC) using bioinformatics approaches and in vitro experiments. We examined the expression of LINC00922 and the prognosis of GC patients based on data from The Cancer Genome Atlas (TCGA) and Gene Expression Profiling Interactive Analysis (GEPIA). LINC00922-related genes were identified by the Multi Experiment Matrix (MEM) database and The Atlas of Noncoding RNAs in Cancer (TANRIC), followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction analysis. The significance of LINC00922 in cell proliferation, apoptosis, invasion and migration was assessed by MTT assay, flow cytometry, Transwell assay and wound-healing assay. The expression of LINC00922 was increased in GC tissues compared with adjacent non-tumor tissues, and increased LINC00922 expression was correlated with poor overall survival and disease-free survival. In addition, 336 overlapping genes were identified by the MEM database and TANRIC and found to be involved in GC-related biological processes, such as cell adhesion and migration, as well as TGF-β signaling. In the protein-protein interaction network, hub genes, such as FSTL3 and LAMC1, were identified. LINC00922 overexpression significantly promoted cell proliferation and invasion in vitro, whereas LINC00922 knockdown exerted opposite effects. In summary, our findings indicate that LINC00922 is overexpressed in GC tissues, suggesting that it might play a role in the development and progression of GC, and thus, it might serve as a prognostic indicator of GC.

Radiomics in Gastric Cancer: First Clinical Investigation to Predict Lymph Vascular Invasion and Survival Outcome Using 18F-FDG PET/CT Images.

BackgroundLymph vascular invasion (LVI) is an unfavorable prognostic indicator in gastric cancer (GC). However, there are no reliable clinical techniques for preoperative predictions of LVI. The aim of this study was to develop and validate PET/CT-based radiomics signatures for predicting LVI of GC preoperatively. Radiomics nomograms were also established to predict patient survival outcomes.MethodsThis retrospective study registered 148 GC patients with histopathological confirmation for LVI status, who underwent pre-operative PET/CT scans (Discovery VCT 64 PET/CT system) from December 2014 to June 2019. Clinic-pathological factors (age, gender, and tumor grade, etc.) and metabolic PET data (maximum and mean standardized uptake value, total lesion glycolysis and metabolic tumor volume) were analyzed to identify independent LVI predictors. The dataset was randomly assigned to either the training set or test set in a 7:3 ratios. Three-dimensional (3D) radiomics features were extracted from each PET- and CT-volume of interests (VOI) singularly, and then a radiomics signature (RS) associated with LVI status is built by feature selection. Four models with different modalities (PET-RS: only PET radiomics features; CT-RS: only CT radiomics features; PET/CT-RS: both PET and CT radiomics features; PET/CT-RS plus clinical data) were developed to predict LVI. Patients were postoperatively followed up with PET/CT every 6-12 months for the first two years and then annually up to five years after surgery. The PET/CT radiomics score (Rad-scores) was calculated to assess survival outcome, and corresponding nomograms with radiomics (NWR) or without radiomics (NWOR) were established.ResultsTumor grade and maximum standardized uptake value (SUVmax) were the independent LVI predictor. 1037 CT and PET 3D radiomics features were extracted separately and reduced to 4 and 5 features to build CT-RS and PET-RS, respectively. PET/CT-RS and PET/CT-RS plus clinical data (tumor grade and SUVmax) were also developed. The ROC analysis demonstrated clinical usefulness of PET/CT-RS plus clinical data (AUC values for training and validation, respectively 0.936 and 0.914) and PET/CT-RS (AUC values for training and validation, respectively 0.881 and 0.854), which both are superior to CT-RS (0.838 and 0.824) and PET-RS (0.821 and 0.812). SUVmax and LVI were independent prognostic indicators of both OS and PFS. Decision curve analysis (DCA) demonstrated NWR outperformed NWOR and was established to assess survival outcomes. For estimation of OS and PFS, the C-indexes of the NWR were 0. 88 and 0.88 in the training set, respectively, while the C-indexes of the NWOR were 0. 82 and 0.85 in the training set, respectively.ConclusionsThe PET/CT-based radiomics analysis might serve as a non-invasive approach to predict LVI status in GC patients and provide effective predictors of patient survival outcomes.

Peripheral Cytokine Levels as a Prognostic Indicator in Gastric Cancer: A Review of Existing Literature.

Although strong connections exist between the carcinogenesis of gastric cancer and chronic inflammation, gastric cancer is unique in that the chronic gastritis which frequently precedes carcinogenesis is strongly associated with H. pylori infection. The interplay between H. pylori virulence factors and host immune cells is complex but culminates in the activation of inflammatory pathways and transcription factors such as NF-κB, STAT3, and AP-1, all of which upregulate cytokine production. Due to the key role of cytokines in modulating the immune response against tumour cells as well as possibly stimulating tumour growth and proliferation, different patterns of cytokine secretion may be associated with varying patient outcomes. In relation to gastric cancer, interleukin-6, 8, 10, 17A, TNF, and IFN-γ may have pro-tumour properties, although interleukin-10, TNF, and IFN-γ may have anti-tumour effects. However, due to the lack of studies investigating patient outcomes, only a link between higher interleukin-6 levels and poorer prognosis has been demonstrated. Further investigations which link peripheral cytokine levels to patient prognosis may elucidate important pathological mechanisms in gastric cancer which adversely impact patient survival and allow treatments targeting these processes to be developed.

Bioinformatic Analysis Identified Potentially Prognostic Long Noncoding RNAs and MicroRNAs for Gastric Cancer.

Gastric cancer (GC) is the fifth most common malignant tumor in the world. The present study was performed to discover the potential diagnostic and therapeutic long noncoding RNAs (lncRNAs) and microRNAs (miRNAs) of GC. Data used in this study to identify differentially expressed lncRNAs (DElncRNAs) and miRNAs (DEmiRNAs) were obtained from 187 GC tissues and 32 adjacent nontumor tissues. The total clinical data on GC included 187 cases. The above data were from the TCGA database. RStudio/Bioconductor software was used to conduct univariate analysis, the least absolute shrinkage and selection operator (LASSO) Cox, and multivariate Cox proportional risk regression for the DElncRNAs and DEmiRNAs. Clinical information was analyzed through univariate and multivariate Cox analysis. Results: five lncRNAs (AC007785.3, AC079385.3, LINC00392, LINC01729, and U95743.1) and two miRNAs (hsa-miR-3174, hsa-miR-605) were proven to be independent prognostic indicators of GC. Results of the Kaplan-Meier survival analysis showed that AC007785.3, AC079385.3, LINC01729, miR-3174, and miR-605 were significantly correlated with OS of GC. The target genes of AC079385.3, miR-3174, and miR-605 were obtained and clustered mainly on MAPK and cGMP-PKG signaling pathways. The clinical data showed that age and clinicopathologic stage were correlated with the prognosis of GC. Furthermore, AC007785.3 was associated with metastasis of GC, and miR-3174 was associated with the primary tumor condition of GC. We identified three lncRNAs (AC007785.3, AC079385.3, LINC01729), two miRNAs (miR-3174, miR-605), and clinical factors related to the pathogenesis and prognosis of GC. Our predicted results provide a possible entry point for the study of prognostic markers for GC.

Identifying Diagnostic and Prognostic Biomarkers and Candidate Therapeutic Drugs of Gastric Cancer Based on Transcriptomics and Single-Cell Sequencing.

Background and Objective: Gastric cancer (GC) is an important health burden and the prognosis of GC is poor. We aimed to explore new diagnostic and prognostic indicators as well as potential therapeutic targets for GC in the current study. Methods: We screened the overlapped differentially expressed genes (DEGs) from GSE54129 and TCGA STAD datasets. Protein-protein interaction network analysis recognized the hub genes among the DEGs. The roles of these genes in diagnosis, prognosis, and their relationship with immune infiltrates and drug sensitivity of GC were analyzed using R studio. Finally, the clinically significant hub genes were verified using single-cell RNA sequencing (scRNA-seq) data. Results: A total of 222 overlapping genes were screened, which were enriched in extracellular matrix-related pathways. Further, 17 hub genes were identified, and our findings demonstrated that BGN, COMP, COL5A2, and SPARC might be important diagnostic and prognostic indicators of GC, which were also correlated with immune cell infiltration, tumor mutation burden (TMB), microsatellite instability (MSI), and sensitivity of therapeutic drugs. The scRNA-seq results further confirmed that all four hub genes were highly expressed in GC. Conclusion: Based on transcriptomics and single-cell sequencing, we identified four diagnostic and prognostic biomarkers of GC, including BGN, COMP, COL5A2, and SPARC, which can help predict drug sensitivity for GC as well.

Significance of a preoperative systemic immune-inflammation index as a predictor of postoperative survival outcomes in gastric cancer

BackgroundSince inflammation and the immune system contribute to the development and progression of malignancies, parameters that reflect a host’s immune-inflammatory status may be useful prognostic indicators of gastric cancer (GC). The present study examined the clinical significance of a preoperative systemic immune-inflammation index (SII) for predicting postoperative survival outcomes in GC.MethodsA total of 447 patients who underwent curative gastrectomy for GC were included in the present study. SII was calculated as platelet count × neutrophil count/lymphocyte count. The prognostic impact of preoperative SII was examined using univariate and multivariate analyses.ResultsPreoperative SII ranged between 105 and 4455 (median 474), and the optimal cutoff value for predicting overall survival (OS) was 395 based on a receiver operating characteristic curve. The 5-year OS rate of the SII ≥ 395 group was 80.0%, which was significantly worse than that (92.7%) of the SII < 395 group (p < 0.001). The multivariate analysis identified SII ≥ 395 (hazard ratio [HR] 2.95; 95% confidence interval [CI] 1.49–6.39; p = 0.001), heart disease (HR 2.14, 95% CI 1.07–4.07), C-reactive protein ≥ 0.5 (HR 2.45, 95% CI 1.15–4.94), pT4 (HR 4.46, 95% CI 2.44–8.14), and pN+ (HR 4.02, 95% CI 2.10–7.93) as independent predictors of worse OS. Peritoneal recurrence was more frequent in the high SII group than in the low SII group (p = 0.028).ConclusionPreoperative SII may be a useful predictor of postoperative survival outcomes in GC. The meticulous surveillance of GC relapse, particularly peritoneal dissemination, is necessary for patients with SII ≥ 395 even after curative gastrectomy.