Prognosis Of Gastric Cancer Patients Research Articles

Identification of differentially expressed mRNAs as novel predictive biomarkers for gastric cancer diagnosis and prognosis

BACKGROUND Gastric cancer (GC) has a high mortality rate worldwide. Despite significant progress in GC diagnosis and treatment, the prognosis for affected patients still remains unfavorable. AIM To identify important candidate genes related to the development of GC and identify potential pathogenic mechanisms through comprehensive bioinformatics analysis. METHODS The Gene Expression Omnibus database was used to obtain the GSE183136 dataset, which includes a total of 135 GC samples. The limma package in R software was employed to identify differentially expressed genes (DEGs). Thereafter, enrichment analyses of Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed for the gene modules using the clusterProfile package in R software. The protein-protein interaction (PPI) networks of target genes were constructed using STRING and visualized by Cytoscape software. The common hub genes that emerged in the cohort of DEGs that was retrieved from the GEPIA database were then screened using a Venn Diagram. The expression levels of these overlapping genes in stomach adenocarcinoma samples and non-tumor samples and their association with prognosis in GC patients were also obtained from the GEPIA database and Kaplan-Meier curves. Moreover, real-time quantitative polymerase chain reaction (RT-qPCR) and western blotting were performed to determine the mRNA and protein levels of glutamic-pyruvic transaminase (GPT ) in GC and normal immortalized cell lines. In addition, cell viability, cell cycle distribution, migration and invasion were evaluated by cell counting kit-8, flow cytometry and transwell assays. Furthermore, we also conducted a retrospective analysis on 70 GC patients diagnosed and surgically treated in Wenzhou Central Hospital, Dingli Clinical College of Wenzhou Medical University, The Second Affiliated Hospital of Shanghai University between January 2017 to December 2020. The tumor and adjacent normal samples were collected from the patients to determine the potential association between the expression level of GPT and the clinical as well as pathological features of GC patients. RESULTS We selected 19214 genes from the GSE183136 dataset, among which there were 250 downregulated genes and 401 upregulated genes in the tumor samples of stage III-IV in comparison to those in tumor samples of stage I-II with a P -value < 0.05. In addition, GO and KEGG results revealed that the various upregulated DEGs were mainly enriched in plasma membrane and neuroactive ligand-receptor interaction, whereas the downregulated DEGs were primarily enriched in cytosol and pancreatic secretion, vascular smooth muscle contraction and biosynthesis of the different cofactors. Furthermore, PPI networks were constructed based on the various upregulated and downregulated genes, and there were a total 15 upregulated and 10 downregulated hub genes. After a comprehensive analysis, several hub genes, including runt-related transcription factor 2 (RUNX2 ), salmonella pathogenicity island 1 (SPI1 ), lysyl oxidase (LOX ), fibrillin 1 (FBN1 ) and GPT , displayed prognostic values. Interestingly, it was observed that GPT was downregulated in GC cells and its upregulation could suppress the malignant phenotypes of GC cells. Furthermore, the expression level of GPT was found to be associated with age, lymph node metastasis, pathological staging and distant metastasis (P < 0.05). CONCLUSION RUNX2 , SPI1 , LOX , FBN1 and GPT were identified key hub genes in GC by bioinformatics analysis. GPT was significantly associated with the prognosis of GC, and its upregulation can effectively inhibit the proliferative, migrative and invasive capabilities of GC cells.

METTL5 promotes gastric cancer progression via sphingomyelin metabolism

BACKGROUND The treatment of gastric cancer (GC) has caused an enormous social burden worldwide. Accumulating studies have reported that N6-methyladenosine (m6A) is closely related to tumor progression. METTL5 is a m6A methyltransferase that plays a pivotal role in maintaining the metabolic stability of cells. However, its aberrant regulation in GC has not been fully elucidated. AIM To excavate the role of METTL5 in the development of GC. METHODS METTL5 expression and clinicopathological characteristics were analyzed via The Cancer Genome Atlas dataset and further verified via immunohistochemistry, western blotting and real-time quantitative polymerase chain reaction in tissue microarrays and clinical samples. The tumor-promoting effect of METTL5 on HGC-27 and AGS cells was explored in vitro by Cell Counting Kit-8 assays, colony formation assays, scratch healing assays, transwell assays and flow cytometry. The tumor-promoting role of METTL5 in vivo was evaluated in a xenograft tumor model. The EpiQuik m6A RNA Methylation Quantification Kit was used for m6A quantification. Next, liquid chromatography-mass spectrometry was used to evaluate the association between METTL5 and sphingomyelin metabolism, which was confirmed by Enzyme-linked immunosorbent assay and rescue tests. In addition, we investigated whether METTL5 affects the sensitivity of GC cells to cisplatin via colony formation and transwell experiments. RESULTS Our research revealed substantial upregulation of METTL5, which suggested a poor prognosis of GC patients. Increased METTL5 expression indicated distant lymph node metastasis, advanced cancer stage and pathological grade. An increased level of METTL5 correlated with a high degree of m6A methylation. METTL5 markedly promotes the proliferation, migration, and invasion of GC cells in vitro . METTL5 also promotes the growth of GC in animal models. METTL5 knockdown resulted in significant changes in sphingomyelin metabolism, which implies that METTL5 may impact the development of GC via sphingomyelin metabolism. In addition, high METTL5 expression led to cisplatin resistance. CONCLUSION METTL5 was found to be an oncogenic driver of GC and may be a new target for therapy since it facilitates GC carcinogenesis through sphingomyelin metabolism and cisplatin resistance.

Predictive model using four ferroptosis-related genes accurately predicts gastric cancer prognosis

BACKGROUND Gastric cancer (GC) is a common malignancy of the digestive system. According to global 2018 cancer data, GC has the fifth-highest incidence and the third-highest fatality rate among malignant tumors. More than 60% of GC are linked to infection with Helicobacter pylori (H. pylori) , a gram-negative, active, microaerophilic, and helical bacterium. This parasite induces GC by producing toxic factors, such as cytotoxin-related gene A, vacuolar cytotoxin A, and outer membrane proteins. Ferroptosis, or iron-dependent programmed cell death, has been linked to GC, although there has been little research on the link between H. pylori infection-related GC and ferroptosis. AIM To identify coregulated differentially expressed genes among ferroptosis-related genes (FRGs) in GC patients and develop a ferroptosis-related prognostic model with discrimination ability. METHODS Gene expression profiles of GC patients and those with H. pylori -associated GC were obtained from The Cancer Genome Atlas and Gene Expression Omnibus (GEO) databases. The FRGs were acquired from the FerrDb database. A ferroptosis-related gene prognostic index (FRGPI) was created using least absolute shrinkage and selection operator–Cox regression. The predictive ability of the FRGPI was validated in the GEO cohort. Finally, we verified the expression of the hub genes and the activity of the ferroptosis inducer FIN56 in GC cell lines and tissues. RESULTS Four hub genes were identified (NOX4, MTCH1, GABARAPL2, and SLC2A3 ) and shown to accurately predict GC and H. pylori -associated GC. The FRGPI based on the hub genes could independently predict GC patient survival; GC patients in the high-risk group had considerably worse overall survival than did those in the low-risk group. The FRGPI was a significant predictor of GC prognosis and was strongly correlated with disease progression. Moreover, the gene expression levels of common immune checkpoint proteins dramatically increased in the high-risk subgroup of the FRGPI cohort. The hub genes were also confirmed to be highly overexpressed in GC cell lines and tissues and were found to be primarily localized at the cell membrane. The ferroptosis inducer FIN56 inhibited GC cell proliferation in a dose-dependent manner. CONCLUSION In this study, we developed a predictive model based on four FRGs that can accurately predict the prognosis of GC patients and the efficacy of immunotherapy in this population.

Characterization of alternative splicing events and prognostic signatures in gastric cancer

BackgroundAccumulating evidences indicate that the specific alternative splicing (AS) events are linked to the occurrence and prognosis of gastric cancer (GC). Nevertheless, the impact of AS is still unclear and needed to further elucidation.MethodsThe expression profile of GC and normal samples were downloaded from TCGA. AS events were achieved from SpliceSeq database. Cox regression together with LASSO analysis were employed to identify survival-associated AS events (SASEs) and calculate risk scores. PPI and pathway enrichment analysis were implemented to determine the function and pathways of these genes. Kaplan-Meier (K-M) analysis and Receiver Operating Characteristic Curves were used to evaluate the clinical significance of genes of SASEs. Q-PCR were applied to validate the hub genes on the survival prognosis in 47 GC samples. Drug sensitivity and immune cell infiltration analysis were conducted.ResultsIn total, 48 140 AS events in 10 610 genes from 361 GC and 31 normal samples were analyzed. Through univariate Cox regression, 855 SASEs in 763 genes were screened out. Further, these SASEs were analyzed by PPI and 17 hub genes were identified. Meanwhile, using Lasso and multivariate Cox regression analysis, 135 SASEs in 132 genes related to 7 AS forms were further screened and a GC prognostic model was constructed. K-M curves indicates that high-risk group has poorer prognosis. And the nomogram analysis on the basis of the multivariate Cox analysis was disclosed the interrelationships between 7 AS forms and clinical parameters in the model. Five key genes were then screened out by PPI analysis and Differential Expression Gene analysis based on TCGA and Combined-dataset, namely STAT3, RAD51B, SOCS2, POLE2 and TSR1. The expression levels of AS in STAT3, RAD51B, SOCS2, POLE2 and TSR1 were all significantly correlated with survival by qPCR verification. Nineteen drugs were sensitized to high-risk patients and eight immune cells showed significantly different infiltration between the STAD and normal groups.ConclusionsIn this research, the prognostic model constructed by SASEs can be applied to predict the prognosis of GC patients and the selected key genes are expected to become new biomarkers and therapeutical targets for GC treatment.

SNHG15-mediated feedback loop interplays with HNRNPA1/SLC7A11/GPX4 pathway to promote gastric cancer progression.

Dysregulation of long noncoding RNA (lncRNA) expression plays a pivotal role in the initiation and progression of gastric cancer (GC). However, the regulation of lncRNA SNHG15 in GC has not been well studied. Mechanisms for ferroptosis by SNHG15 have not been revealed. Here, we aimed to explore SNHG15-mediated biological functions and underlying molecular mechanisms in GC. The novel SNHG15 was identified by analyzing RNA-sequencing (RNA-seq) data of GC tissues from our cohort and TCGA dataset, and further validated by qRT-PCR in GC cells and tissues. Gain- and loss-of-function assays were performed to examine the role of SNHG15 on GC both invitro and invivo. SNHG15 was highly expressed in GC. The enhanced SNHG15 was positively correlated with malignant stage and poor prognosis in GC patients. Gain- and loss-of-function studies showed that SNHG15 was required to affect GC cell growth, migration and invasion both invitro and invivo. Mechanistically, the oncogenic transcription factors E2F1 and MYC could bind to the SNHG15 promoter and enhance its expression. Meanwhile, SNHG15 increased E2F1 and MYC mRNA expression by sponging miR-24-3p. Notably, SNHG15 could also enhance the stability of SLC7A11 in the cytoplasm by competitively binding HNRNPA1. In addition, SNHG15 inhibited ferroptosis through an HNRNPA1-dependent regulation of SLC7A11/GPX4 axis. Our results support a novel model in which E2F1- and MYC-activated SNHG15 regulates ferroptosis via an HNRNPA1-dependent modulation of the SLC7A11/GPX4 axis, which serves as the critical effectors in GC progression, and provides a new therapeutic direction in the treatment of GC.

TM-Score predicts immunotherapy efficacy and improves the performance of the machine learning prognostic model in gastric cancer

Immunotherapy is becoming increasingly important, but the overall response rate is relatively low in the treatment of gastric cancer (GC). The application of tumor mutational burden (TMB) in predicting immunotherapy efficacy in GC patients is limited and controversial, emphasizing the importance of optimizing TMB-based patient selection. By combining TMB and major histocompatibility complex (MHC) related hub genes, we established a novel TM-Score. This score showed superior performance for immunotherapeutic selection (AUC = 0.808) compared to TMB, MSI status, and EBV status. Additionally, it predicted the prognosis of GC patients. Subsequently, a machine learning model adjusted by the TM-Score further improved the accuracy of survival prediction (AUC > 0.8). Meanwhile, we found that GC patients with low TM-Score had a higher mutation frequency, higher expression of HLA genes and immune checkpoint genes, and higher infiltration of CD8+ T cells, CD4+ helper T cells, and M1 macrophages. This suggests that TM-Score is significantly associated with tumor immunogenicity and tumor immune environment. Notably, based on the RNA-seq and scRNA-seq, it was found that AKAP5, a key component gene of TM-Score, is involved in anti-tumor immunity by promoting the infiltration of CD4+ T cells, NK cells, and myeloid cells. Additionally, siAKAP5 significantly reduced MHC-II mRNA expression in the GC cell line. In addition, our immunohistochemistry assays confirmed a positive correlation between AKAP5 and human leukocyte antigen (HLA) expression. Furthermore, AKAP5 levels were higher in patients with longer survival and those who responded to immunotherapy in GC, indicating its potential value in predicting prognosis and immunotherapy outcomes. In conclusion, TM-Score, as an optimization of TMB, is a more precise biomarker for predicting the immunotherapy efficacy of the GC population. Additionally, AKAP5 shows promise as a therapeutic target for GC.

CircVAPA-rich small extracellular vesicles derived from gastric cancer promote neural invasion by inhibiting SLIT2 expression in neuronal cells

Gastric cancer (GC) is one of the most common cancer worldwide. Neural invasion (NI) is considered as the symbiotic interaction between nerves and cancers, which strongly affects the prognosis of GC patients. Small extracellular vesicles (sEVs) play a key role in intercellular communication. However, whether sEVs mediate GC-NI remains unexplored. In this study, sEVs release inhibitor reduces the NI potential of GC cells. Muscarinic receptor M3 on GC-derived sEVs regulates their absorption by neuronal cells. The enrichment of sEV-circVAPA in NI-positive patients’ serum is validated by serum high throughput sEV-circRNA sequencing and clinical samples. sEV-circVAPA promotes GC-NI in vitro and in vivo. Mechanistically, sEV-circVAPA decreases SLIT2 transcription by miR-548p/TGIF2 and inhibits SLIT2 translation via binding to eIF4G1, thereby downregulates SLIT2 expression in neuronal cells and finally induces GC-NI. Together, this work identifies the preferential absorption mechanism of GC-derived sEVs by neuronal cells and demonstrates a previously undefined role of GC-derived sEV-circRNA in GC-NI, which provides new insight into sEV-circRNA based diagnostic and therapeutic strategies for NI-positive GC patients.

Exosomal miR-493 suppresses MAD2L1 and induces chemoresistance to intraperitoneal paclitaxel therapy in gastric cancer patients with peritoneal metastasis

Intraperitoneal (IP) chemotherapy with paclitaxel (PTX) for gastric cancer (GC) with peritoneal metastasis (PM) is considered a promising treatment approach, however, there are no useful biomarkers to predict the efficacy of IP therapy. We examined the association between intra-peritoneal exosomes, particularly exosomal micro-RNAs (exo-miRNAs), and IP-chemo sensitivity. MKN45 cells that were cultured with intra-peritoneal exosomes from patients who did not respond to IP therapy with PTX (IPnon-respond group) exhibited resistance to PTX compared with exosomes from responding patients (IPrespond group) (p = 0.002). A comprehensive search for exo-miRNAs indicated that miR-493 was significantly up-regulated in exosomes from the IPnon-respond group compared with those collected from the IPrespond group. The expression of miR-493 in PTX-resistant MKN45 cells (MKN45PTX-res) was higher compared with that in MKN45. In addition, MKN45PTX-res cells exhibited lower MAD2L1 gene and protein expression compared with MKN45. Finally, miR-493 enhancement by transfection of miR-493 mimics significantly down-regulated MAD2L1 expression in MKN45 cells and reduced PTX sensitivity. Our results suggest that intra-peritoneal exo-miR-493 is involved in chemoresistance to PTX by downregulating MAD2L1 in GC with PM. Exo-miR-493 may be a biomarker for chemoresistance and prognosis of GC patients with PM and may also be a promising therapeutic target.

Geriatric nutritional risk index predicts the prognosis of gastric cancer patients treated with immune checkpoint inhibitors.

The nutritional status is closely linked to the immune function of patients. Previous studies have demonstrated the utility of the Geriatric Nutritional Risk Index (GNRI) in assessing nutritional status. The aim of this study is to investigate the prognostic significance of GNRI in patients with gastric cancer who received immune checkpoint inhibitor (ICI) therapy. The study enrolled 89 gastric cancer patients who received different types of immune checkpoint inhibitors (ICIs) between August 2016 and December 2020, along with 57 patients who underwent chemotherapy during the same period as a control group. The GNRI cutoff point was established based on prior research. Differences in clinical and pathological features were analyzed using the Chi-square test or independent samples t-test. Univariate and multivariate analyses were used to identify prognostic factors for both progression-free survival (PFS) and overall survival (OS). Furthermore, nomograms were created to predict the likelihood of patient survival. There were 31 cases (21.2%) with GNRI < 92.00 and 115 cases (78.8%) with GNRI ≥ 92.00. Patients with low GNRI had significantly shorter PFS (21.33 months vs 28.37 months, P = .001) and OS (33.06 months vs 41.63 months, P = .001) than those with high GNRI, among all patients. Similar results were also found in patients treated with ICIs. Additionally, GNRI was identified as an independent prognostic factor. The C-index and 95% CI of the nomograms for predicting survival probabilities were 0.667 (0.600-0.735) and 0.685 (0.622-0.749), respectively. GNRI was significantly associated with survival time in patients with gastric cancer who received ICIs, patients with low GNRI had shorter PFS and OS. GNRI might be able to identify patients who might benefit from ICIs.

Effects of tumor marker regression load score on long-term prognosis of gastric cancer patients undergoing radical surgery after neoadjuvant chemotherapy

BackgroundThe effects of the dynamics of serum tumor markers (CA72-4, CEA, CA19-9, CA125 and AFP) before and after neoadjuvant chemotherapy (NACT) on the prognosis of gastric cancer(GC) patients remain unclear. MethodsThe training set contained 334 GC patients from Fujian Medical University Union Hospital (FJMUUH) and 113 GC patients in Qinghai University Affiliated Hospital (QhUAH) were used as an external validation set. Tumor marker regression load (ΔTMRL) indicator, including ΔCA72-4, ΔCEA, ΔCA19-9, ΔCA125, and ΔAFP, is defined as [(postNACT marker– preNACT marker)/preNACT marker]. Tumor marker regression load score (TMRLS) consists of ΔCA72-4, ΔCEA and ΔCA125. The predictive performance of the nomogram-TMRLS was evaluated using the area under the receiver operating characteristic(ROC) curve(AUC), decision curve analysis(DCA), and C-index. ResultsPatients from FJMUUH were divided into two groups, TMRLS-low and TMRLS-high, determined by R package maxstat. Survival analysis revealed a higher 3-year overall survival(OS) in the TMRLS-low than in the TMRLS-high group. The TMRLS-high group who received postoperative adjuvant chemotherapy(AC) showed a significantly higher 3-year OS rate than those who did not. Multivariate COX regression analysis indicated that TMRLS was an independent prognostic factor for OS. A nomogram for predicting OS based on TMRLS showed a significantly higher C-index and AUC than the ypTNM stage. The above results were also found in the QhUAH external validation cohort. ConclusionTMRLS is a novel independent prognostic factor for GC who underwent NACT and a radical gastrectomy. Furthermore, the TMRLS-high group, who received postoperative AC, may achieve better survival outcomes. Notably, the predictive performance of the nomogram-TMRLS significantly outperformed that of the ypTNM stage.

Identification of Key lncRNAs Associated with Immune Infiltration and Prognosis in Gastric Cancer.

Long non-coding RNAs (lncRNAs), as promising novel biomarkers for cancer treatment and prognosis, can function as tumor suppressors and oncogenes in the occurrence and development of many types of cancer, including gastric cancer (GC). However, little is known about the complex regulatory system of lncRNAs in GC. In this study, we systematically analyzed lncRNA and miRNA transcriptomic profiles of GC based on bioinformatics methods and experimental validation. An lncRNA-miRNA interaction network related to GC was constructed, and the nine crucial lncRNAs were identified. These 9 lncRNAs were found to be associated with the prognosis of GC patients by Cox proportional hazards regression analysis. Among them, the expression of lncRNA SNHG14 can affect the survival of GC patients as a potential prognostic marker. Moreover, it was shown that SNHG14 was involved in immune-related pathways and significantly correlated with immune cell infiltration in GC. Meanwhile, we found that SNHG14 affected immune function in many cancers, such as breast cancer and esophageal carcinoma. Such information revealed that SNHG14 may serve as a potential target for cancer immunotherapy. As well, our study could provide practical and theoretical guiding significance for clinical application of non-coding RNAs.

Establishment of a prognostic model for gastric cancer patients who underwent radical gastrectomy using machine learning: a two-center study.

Gastric cancer is a prevalent gastrointestinal malignancy worldwide. In this study, a prognostic model was developed for gastric cancer patients who underwent radical gastrectomy using machine learning, employing advanced computational techniques to investigate postoperative mortality risk factors in such patients. Data of 295 patients with gastric cancer who underwent radical gastrectomy at the Department of General Surgery of Affiliated Hospital of Xuzhou Medical University (Xuzhou, China) between March 2016 and November 2019 were retrospectively analyzed as the training group. Additionally, 109 patients who underwent radical gastrectomy at the Department of General Surgery Affiliated to Jining First People's Hospital (Jining, China) were included for external validation. Four machine learning models, including logistic regression (LR), decision tree (DT), random forest (RF), and gradient boosting machine (GBM), were utilized. Model performance was assessed by comparing the area under the curve (AUC) for each model. An LR-based nomogram model was constructed to assess patients' clinical prognosis. Lasso regression identified eight associated factors: age, sex, maximum tumor diameter, nerve or vascular invasion, TNM stage, gastrectomy type, lymphocyte count, and carcinoembryonic antigen (CEA) level. The performance of these models was evaluated using the AUC. In the training group, the AUC values were 0.795, 0.759, 0.873, and 0.853 for LR, DT, RF, and GBM, respectively. In the validation group, the AUC values were 0.734, 0.708, 0.746, and 0.707 for LR, DT, RF, and GBM, respectively. The nomogram model, constructed based on LR, demonstrated excellent clinical prognostic evaluation capabilities. Machine learning algorithms are robust performance assessment tools for evaluating the prognosis of gastric cancer patients who have undergone radical gastrectomy. The LR-based nomogram model can aid clinicians in making more reliable clinical decisions.

MEF2D facilitates liver metastasis of gastric cancer cells through directly inducing H1X under IL-13 stimulation

Liver metastasis is the most common occurrence in gastric cancer patients, although the precise mechanism behind it remains unclear. Through a combination of proteomics and quantitative RT-PCR, our study has revealed a significant correlation between the upregulation of myocyte enhancer factor-2D (MEF2D) and both distant metastasis and poor prognosis in gastric cancer patients. In mouse models, we observed that overexpressing or knocking down MEF2D in gastric cancer cells respectively promoted or inhibited liver metastasis. Furthermore, our research has demonstrated that MEF2D regulates the transcriptional activation of H1X by binding to the H1X promoter. This regulation leads to the upregulation of H1X, which, in turn, promotes the in vivo metastasis of gastric cancer cells along with the upregulation of the downstream gene β-CATENIN. Additionally, we found that the expression of MEF2D and H1X at both mRNA and protein levels can be induced by the inflammatory factor IL-13, and this induction exhibits a time gradient dependence. In human gastric cancer tissues, the expression of IL13RA1, the receptor for IL-13, positively correlates with the expression of MEF2D and H1X. IL13RA1 has been identified as an intermediate receptor through which IL-13 regulates MEF2D. In conclusion, our findings suggest that MEF2D plays a crucial role in promoting liver metastasis of gastric cancer by upregulating H1X and downstream target β-CATENIN in response to IL-13 stimulation. Targeting MEF2D could therefore be a promising therapeutic strategy for the clinical management of gastric cancer. Statement of SignificanceMEF2D promotes its transcriptional activation in gastric cancer cells by binding to the H1X promoter and is upregulated by IL-13-IL13RA1, thereby promoting distant metastasis of gastric cancer.

Integrated Analysis Construct a Tumor-Associated Macrophage Novel Signature with Promising Implications in Predicting the Prognosis and Immunotherapeutic Response of Gastric Cancer Patients.

Gastric cancer (GC) remains one of the most prevalent malignant tumors worldwide. At present, tumor-associated macrophages (TAMs) are essential in the progression, metastasis, and drug resistance of tumors. Therefore, TAMs can be a crucial target for tumor treatment. We intended to investigate the TAM characteristics in GC and develop a risk signature based on TAM to predict the prognosis of GC patients. The single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data were acquired from a publicly available database. We utilized the Seurat pipeline to process the scRNA-seq data and determine TAM cell types using marker genes. Univariate Cox regression analysis was utilized to examine TAM-related prognostic genes, and then we employed Lasso-Cox regression analysis, and Multivariate Cox regression analysis established a novel risk profile to forecast the clinical value of the model with a new nomogram combining risk profiles and clinicopathological characteristics. The current study employed scRNA-seq data to identify five TAM clusters in GC, among which four were significantly associated with GC prognosis. Accordingly, we further developed a TAM-related risk signature utilizing nine genes. After evaluation, our model accurately predicted the prognosis of gastric cancer. Generally, GC patients with low TAMS scores exhibited a more favorable prognosis, greater benefits from immunotherapy, and higher levels of immune cell infiltration. The prognosis of GC can be effectively predicted by TAM-based risk signatures, and the signature may provide a new perspective for comprehensively guiding clinical diagnosis, prediction, and immunotherapy for gastric cancer.

FAM120A deficiency improves resistance to cisplatin in gastric cancer by promoting ferroptosis

The occurrence of chemoresistance is an inescapable obstacle affecting the clinical efficacy of cisplatin in gastric cancer (GC). Exploring the regulatory mechanism of cisplatin resistance will help to provide potential effective targets for improving the prognosis of gastric cancer patients. Here, we find that FAM120A is upregulated in GC tissues and higher in cisplatin-resistant GC tissues, and its high expression is positively correlated with the poor outcome of GC patients. Functional studies indicate that FAM120A confers chemoresistance to GC cells by inhibiting ferroptosis. Mechanically, METTL3-induced m6A modification and YTHDC1-induced stability of FAM120A mRNA enhance FAM120A expression. FAM120A inhibits ferroptosis by binding SLC7A11 mRNA and enhancing its stability. FAM120A deficiency enhances cisplatin sensitivity by promoting ferroptosis in vivo. These results reveal the function of FAM120A in chemotherapy tolerance and targeting FAM120A is an effective strategy to alleviate cisplatin resistance in GC.

CircNRD1 elevates THAP domain containing 11 through sequestering microRNA-421 to inhibit gastric cancer growth and tumorigenesis.

We explored the role and mechanism of circular RNAcircNRD1 in gastric cancer (GC) progression, aiming to identify new bio-markers for the treatment and prognosis of GC patients. The RNA expression was examined by reverse transcription-quantitative polymerase chain reaction. Cell proliferation, migration and invasion were analyzed by 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, 5-ethynyl-2'-deoxyuridine (EdU) incorporation assay, scratch assay and transwell assay. Western blot assay was conducted for protein expression measurement. Dual-luciferase reporter, RNA immunoprecipitation, and RNA pull-down assays were conducted to verify the interaction between microRNA-421 (miR-421) and circNRD1 or THAP domain containing 11 (THAP11). Xenograft tumor model was established to perform in vivo experiments. CircNRD1 was notably downregulated in GC tissues and cell lines. Additionally, decreased circNRD1 level was closely associated with advanced tumor stage and dismal prognosis in GC patients. CircNRD1 overexpression suppressed the proliferation and metastasis of GC cells. CircNRD1 acted as a molecular sponge for miR-421 in GC cells, and the antitumor impacts of circNRD1 overexpression in GC cells could be alleviated by miR-421 overexpression. miR-421 directly targeted THAP11, and circNRD1 could up-regulate THAP11 expression in GC cells through sponging miR-421. THAP11 knockdown reversed circNRD1 overexpression-induced tumor suppressing effects in GC cells. CircNRD1 overexpression significantly blocked tumor growth in vivo. CircNRD1 suppressed the proliferation and metastasis of GC cells in vitro and blocked tumor growth in vivo via modulating miR-421/THAP11 axis.

A Clinical Study of Intraoperative Perfusion Chemotherapy in Gastric Cancer: A Prospective Cohort Study.

Gastric cancer (GC) is the third largest cause of cancer-related death worldwide, with major geographic disparities in incidence and outcomes. Sociodemographic indicators, food habits, and genetic predispositions all add to the load. Despite advances in systemic treatments, peritoneal metastasis remains a concern, with intraperitoneal chemotherapy (IPC) emerging as a promising treatment option. A prospective cohort research was done, with 30 GC patients receiving cytoreductive surgery (CRS) followed by lobaplatin-based intraoperative chemotherapy. The study evaluated postoperative complications, survival rates, and disease recurrence using Statistical Package for the Social Sciences (SPSS) version 25.0(IBM SPSS Statistics, Armonk, NY) for data analysis. The purpose of this study is to assess the effectiveness, safety, and dependability of lobaplatin as an intraoperative chemotherapeutic agent in patients having gastric cancer surgery, with a particular emphasis on those patients who do not have distant metastases. The study population had a balanced gender distribution, with an average age of 44.83 years. Most patients had advanced-stage cancer (T3 and T4), and lobaplatin treatment resulted in a low frequency of serious postoperative sequelae. Preliminary studies suggest that lobaplatin is a safe and potentially effective IPC drug for GC, with few side effects and adequate survival rates. Lobaplatin shows promise as an intraoperative chemotherapeutic treatment for gastric cancer, necessitating more research in bigger, randomized controlled studiesto determine its efficacy and safety profile. The study emphasizes the need for novel treatment strategies to enhance the prognosis of GC patients, particularly those with peritoneal involvement.

LncRNA SNHG26 promotes gastric cancer progression and metastasis by inducing c-Myc protein translation and an energy metabolism positive feedback loop

Metastasis is a bottleneck in cancer treatment. Studies have shown the pivotal roles of long noncoding RNAs (lncRNAs) in regulating cancer metastasis; however, our understanding of lncRNAs in gastric cancer (GC) remains limited. RNA-seq was performed on metastasis-inclined GC tissues to uncover metastasis-associated lncRNAs, revealing upregulated small nucleolar RNA host gene 26 (SNHG26) expression, which predicted poor GC patient prognosis. Functional experiments revealed that SNHG26 promoted cellular epithelial–mesenchymal transition and proliferation in vitro and in vivo. Mechanistically, SNHG26 was found to interact with nucleolin (NCL), thereby modulating c-Myc expression by increasing its translation, and in turn promoting energy metabolism via hexokinase 2 (HK2), which facilitates GC malignancy. The increase in energy metabolism supplies sufficient energy to promote c-Myc translation and expression, forming a positive feedback loop. In addition, metabolic and translation inhibitors can block this loop, thus inhibiting cell proliferation and mobility, indicating potential therapeutic prospects in GC.

TOB1 modulates neutrophil phenotypes to influence gastric cancer progression and immunotherapy efficacy.

The ErbB-2.1(TOB1) signaling transducer protein is a tumor-suppressive protein that actively suppresses the malignant phenotype of gastric cancer cells. Yet, TOB1 negatively regulates the activation and growth of different immune cells. Understanding the expression and role of TOB1 in the gastric cancer immune environment is crucial to maximize its potential in targeted immunotherapy. This study employed multiplex immunofluorescence analysis to precisely delineate and quantify the expression of TOB1 in immune cells within gastric cancer tissue microarrays. Univariate and multivariate Cox analyses were performed to assess the influence of clinical-pathological parameters, immune cells, TOB1, and double-positive cells on the prognosis of gastric cancer patients. Subsequent experiments included co-culture assays of si-TOB1-transfected neutrophils with AGS or HGC-27 cells, along with EdU, invasion, migration assays, and bioinformatics analyses, aimed at elucidating the mechanisms through which TOB1 in neutrophils impacts the prognosis of gastric cancer patients. We remarkably revealed that TOB1 exhibits varying expression levels in both the nucleus (nTOB1) and cytoplasm (cTOB1) of diverse immune cell populations, including CD8+ T cells, CD66b+ neutrophils, FOXP3+ Tregs, CD20+ B cells, CD4+ T cells, and CD68+ macrophages within gastric cancer and paracancerous tissues. Significantly, TOB1 was notably concentrated in CD66b+ neutrophils. Survival analysis showed that a higher density of cTOB1/nTOB1+CD66b+ neutrophils was linked to a better prognosis. Subsequent experiments revealed that, following stimulation with the supernatant of tumor tissue culture, the levels of TOB1 protein and mRNA in neutrophils decreased, accompanied by enhanced apoptosis. HL-60 cells were successfully induced to neutrophil-like cells by DMSO. Neutrophils-like cells with attenuated TOB1 gene expression by si-TOB1 demonstrated heightened apoptosis, consequently fostering a malignant phenotype in AGS and HCG-27 cells upon co-cultivation. The subsequent analysis of the datasets from TCGA and TIMER2 revealed that patients with high levels of TOB1 combined neutrophils showed better immunotherapy response. This study significantly advances our comprehension of TOB1's role within the immune microenvironment of gastric cancer, offering promising therapeutic targets for immunotherapy in this context.

Prognostic value and potential function of a novel heme-related LncRNAs signature in gastric cancer

Heme is a coordination complex formed by the binding of iron ions and porphyrin rings. Its metabolic processes are associated with various cancers, including gastric cancer (GC). In recent years, long non-coding RNAs (LncRNAs) have been identified as key regulatory factors in GC. However, the role of LncRNAs associated with heme metabolism in GC and their relationship with prognosis have not been reported. In this study, we constructed a novel LncRNAs signature related to heme metabolism (HMlncSig) and validated its prognostic value for predicting the survival of GC patients through training, test, and entire cohorts. Kaplan-Meier analysis demonstrated that patients in the high-risk group had shorter survival times. Univariate and multivariate Cox regression analysis showed that HMlncSig was an independent prognostic indicator for GC patients, regardless of other clinical pathological features. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis and gene set variation analysis pathways showed that the activation of these markers may be involved in tumor progression, influencing the survival of GC patients. The nomogram, based on HMlncSig score and clinical features, demonstrated the strong predictive ability of this signature. Additionally, significant differences were observed between the high-risk and low-risk groups in terms of immune cell subtypes, expression of immune checkpoint genes, and response to chemotherapy and immunotherapy. Through clinical validation, we found that the risk score and heme levels of GC patients were both significantly elevated and correlated with the degree of malignancy. Furthermore, we found that AP000692.1, a key gene in this signature, promoted the proliferation, migration, and invasion of GC cells. In conclusion, our HMlncSig model has significant predictive value for the prognosis of GC patients and can provide clinical guidance for personalized immunotherapy.