Amino acid metabolism-related genes as potential biomarkers and the role of MATN3 in stomach adenocarcinoma: A bioinformatics, mendelian randomization and experimental validation study.

BACKGROUND: Stomach adenocarcinoma (STAD) is a major contributor to cancer-related mortality worldwide. Alterations in amino acid metabolism, which is integral to protein synthesis, have been observed across various tumor types. However, the prognostic significance of amino acid metabolism-related genes in STAD remains underexplored. METHODS: Transcriptomic gene expression and clinical data for STAD patients were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Amino acid metabolism-related gene sets were sourced from the Gene Set Enrichment Analysis (GSEA) database. A prognostic model was built using LASSO Cox regression based on the TCGA cohort and validated with GEO datasets (GSE84433, GSE84437, GSE84426). Kaplan-Meier analysis compared overall survival (OS) between high- and low-risk groups, and ROC curves assessed model accuracy. A nomogram predicted 1-, 3-, and 5-year survival. Copy number variations (CNVs) in model genes were visualized using data from the Xena platform, and mutation profiles were analyzed with "maftools" to create a waterfall plot. KEGG and GO enrichment analyses were performed to explore biological mechanisms. Immune infiltration and related functions were evaluated via ssGSEA, and Spearman correlation analyzed associations between risk scores and immune components. The TIDE database predicted immunotherapy efficacy, while FDA-approved drug sensitivity was assessed through CellMiner database. The role of MATN3 in STAD was further examined in vitro and in vivo, including amino acid-targeted metabolomic sequencing to assess its impact on metabolism. Finally, Mendelian randomization (MR) analysis evaluated the causal relationship between the model genes and gastric cancer. RESULTS: In this study, we developed a prognostic risk model for STAD based on three amino acid metabolism-related genes (SERPINE1, NRP1, MATN3) using LASSO regression analysis. CNV amplification was common in SERPINE1 and NRP1, while CNV deletion frequently occurred in MATN3. STAD patients were classified into high- and low-risk groups based on the median risk score, with the high-risk group showing worse prognosis. A nomogram incorporating the risk score and clinical factors was created to estimate 1-, 3-, and 5-year survival rates. Distinct mutation profiles were observed between risk groups, with KEGG pathway analysis showing immune-related pathways enriched in the high-risk group. High-risk scores were significantly associated with the C6 (TGF-ß dominant) subtype, while low-risk scores correlated with the C4 (lymphocyte-depleted) subtype. Higher risk scores also indicated increased immune infiltration, enhanced immune functions, lower tumor purity, and poorer immunotherapy response. Model genes were linked to anticancer drug sensitivity. Manipulating MATN3 expression showed that it promoted STAD cell proliferation and migration in vitro and tumor growth in vivo. Metabolomic sequencing revealed that MATN3 knockdown elevated levels of 30 amino acid metabolites, including alpha-aminobutyric acid, glycine, and aspartic acid, while reducing (S)-ß-Aminoisobutyric acid and argininosuccinic acid. MR analysis found a significant causal effect of NRP1 on gastric cancer, but no causal relationship for MATN3 or SERPINE1. CONCLUSION: In conclusion, the amino acid metabolism-related prognostic model shows promise as a valuable biomarker for predicting the clinical prognosis, selecting immunotherapy and drug treatment for STAD patients. Furthermore, our study has shed light on the potential value of the MATN3 as a promising strategy for combating the progression of STAD.

Machine learning based intratumor heterogeneity signature for predicting prognosis and immunotherapy benefit in stomach adenocarcinoma.

Stomach adenocarcinoma (STAD) is a prevalent malignancy that is highly aggressive and heterogeneous. Intratumor heterogeneity (ITH) showed strong link to tumor progression and metastasis. High ITH may promote tumor evolution. An ITH-related signature (IRS) was created using as integrative technique including 10 machine learning methods based on TCGA, GSE15459, GSE26253, GSE62254 and GSE84437 datasets. The relevance of IRS in predicting the advantages of immunotherapy was assessed using a number of prediction scores and three immunotherapy datasets (GSE78220, IMvigor210 and GSE91061). Vitro experiments were performed to verify the biological functions of AKR1B1. The RSF + Enet (alpha = 0.1) projected model was proposed as the ideal IRS because it had the highest average C-index. The IRS demonstrated a strong performance in serving as an independent risk factor for the clinical outcome of STAD patients. It performed exceptionally well in predicting the overall survival rate of STAD patients, as seen by the TCGA cohort's AUC of 1-, 3-, and 5-year ROC curves, which were 0.689, 0.683, and 0.669, respectively. A low IRS score demonstrated a superior response to immunotherapy, as seen by a lower TIDE score, lower immune escape score, greater TMB score, higher PD1&CTLA4 immunophenoscore, higher response rate, and improved prognosis. Common chemotherapeutic and targeted treatment regimens had lower IC50 values in the group with higher IRS scores. Vitro experiment showed that AKR1B1 was upregulated in STAD and knockdown of AKR1B1 obviously suppressed tumor cell proliferation and migration. The present investigation produced the best IRS for STAD, which may be applied to prognostication, risk stratification, and therapy planning for STAD patients.

Integrative analysis of multiple cell death model for precise prognosis and drug response prediction in gastric cancer.

BACKGROUND: Gastric cancer (GC) is a common upper gastrointestinal tumor. However, the evaluation of prognosis and treatment response in patients with gastric cancer remains a challenge. Programmed cell death (PCD) is one of the important terminal paths for the cells of metazoans, and is involved in a variety of biological events that include morphogenesis, maintenance of tissue homeostasis, and elimination of harmful cells. The objective of this project is to investigate the predictive significance of cell death pathways and create prognostic signatures associated to cell death, with the purpose of forecasting prognosis and providing guidance for the treatment of gastric cancer. METHODS: Gene transcription profiles and corresponding clinical data of gastric cancer patients were collected from The Cancer Genome Atlas (TCGA-STAD, n = 448) and the Gene Expression Comprehensive Database (GSE84437, n = 483). Thirteen types of cell death-related genes, including apoptosis, necroptosis, pyroptosis, ferroptosis, autophagy, cuprotosis, parthanatos, entotic cell death, netotic cell death, lysosome-dependent cell death, alkaliptosis, oxeiptosis, and disulfidptosis, were analysed. Cell death-related genes associated with prognosis were identified in the TCGA-STAD training cohort using Lasso-Cox regression to generate a risk score. Patients were categorized into high and low-risk groups based on the median risk score for survival difference analysis. Cell death-related genes associated with prognosis were identified in the TCGA-STAD training cohort using Lasso-Cox regression to generate a risk score. Additionally, the response to immunotherapy in the high-risk and low-risk groups was calculated using the oncoPredict algorithm. Futhermore, the model genes were validated in the GEO validation set. RESULTS: A total of 324 differential programmed cell death (PCD)-related genes were identified, and 65 were selected through single-factor Cox analysis. Six PCD-related genes were ultimately identified by Lasso regression to construct a prognostic risk score model. The log-rank test revealed that patients in the high-risk group had inferior survival time compared with those in the low-risk group. The area under the ROC curve (AUC) for the training group at years 1, 3, and 5 were 0.684, 0.713, 0.743, respectively, while the AUC for the validation cohort at years 1, 3, and 5 were 0.695, 0.704, and 0.707, respectively. Unsupervised clustering identified potential subtypes included in the model, and a survival difference was also observed between the two subgroups. Multifactor Cox results, combined with clinical information, demonstrated that the prognostic risk score can serve as an independent prognostic factor, irrespective of other clinical features. CONCLUSION: By comprehensively analyzing multiple cell death patterns, we have established a novel model that accurately forecasts the clinical prognosis and drug sensitivity of gastric cancer. It was found that all 12 representative drugs may not be suitable for patients in high-risk groups.

Unveiling the role of RARs in stomach adenocarcinoma: clinical implications and prognostic biomarkers.

Background: Retinoic acid receptors (RARs) family are known to play a significant role in the occurrence and development of tumors. However, the relationship between RARs and stomach adenocarcinoma (STAD) has not yet been clearly identified. The aim of this study is to evaluate the expression profile and clinical value of the RARs family in STAD. Methods: The expression level, clinical characteristics, prognostic value, immunity-related evaluations, genetic alteration and methylation site of RARs in STAD were explored using a series of online databases including gene expression profiling interactive analysis (GEPIA), tumor immune estimation resource (TIMER), University of Alabama at Birmingham cancer data (UALCAN), Human Protein Atlas (HPA), Kaplan-Meier plotter, gene set cancer analysis (GSCA), cBioPortal, MethSurv, GeneMANIA, LinkedOmics, Metascape, Search tool for the retrieval of interacting genes (STRING), tumor immune single-cell hub (TISCH) and cancer cell line encyclopedia (CCLE). Results: We discovered dramatically increased expression of RARA and decreased expression of RARB in STAD tissues, and many clinical variables were closely related to RARs. Notably, higher expressions of RARA and RARB as well as lower expression of RARG correlated with worse overall survival (OS) for STAD patients. The clinical value of prognostic model indicated that RARs were identified to be potential prognostic biomarkers for STAD patients. Moreover, RARB was closely related to immune cell infiltration, which had effect on the role of RARB in STAD prognosis. And the genetic alteration of RARB was significantly associated with the longer disease-free survival (DFS) of STAD patients. Additionally, some CpG sites of the RARs family were related with the prognosis of STAD patients. Functional enrichment analyses indicated that several pathways in STAD might be pivotal pathways regulated by RARs. At the single-cell level, there was some extent of infiltration of tumor microenvironment-related cells in the RARs expression in STAD. Conclusions: Our results evaluated the expression profile and clinical values of RARs in patients with STAD, which provided a basis for future in-depth exploration of the specific mechanisms of each member of RARs in STAD.

Association of COL4A2 indel polymorphism with the development of stomach adenocarcinoma in Chinese populations.

OBJECTIVE: The objective of the study was to assess the potential association between the indel polymorphism (rs34802628) located within the intron of the collagen type ⅳ alpha 2 gene (COL4A2) and the susceptibility to stomach adenocarcinoma (STAD) within a Chinese population. METHODS: Peripheral venous blood samples were collected from a total of 497 STAD patients and 804 healthy control individuals to extract genomic DNA. The genotyping of the COL4A2 rs34802628 polymorphism was carried out using a polymerase chain reaction assay. Additionally, statistical analyses were conducted on the expression levels of COL4A2 mRNA using the GEPIA database. Meanwhile, the expression of COL4A2 mRNA was also validated by Real-time PCR using STAD tissue samples. Then, based on an analysis of patient tumor RNA seq data available from the Cancer Genome Atlas (TCGA), we assessed the prognostic value of mRNA expression of the COL4A2 gene in STAD patients using K-M plotter. RESULTS: The study presented compelling evidence supporting an association between the rs34802628 polymorphism in the COL4A2 gene and susceptibility to STAD. Logistic regression analysis revealed that both the heterozygote and homozygote 4-bp del/del genotypes were significantly associated with a decreased risk of STAD, even after controlling for other variables (adjusted odds ratio [OR] = 0.663, 95% confidence interval [CI] 0.519-0.848, p = 0.037; OR = 0.422, 95% CI 0.290-0.614, p = 0.000005, respectively). Importantly, individuals carrying the 4-bp deletion allele demonstrated a notably lower risk of developing the disease (OR = 0.696, 95% CI 0.591-0.820, p = 0.000014). Furthermore, Genotype-phenotype correlation studies in human STAD tissue samples demonstrated that the higher mRNA expression levels of COL4A2 were associated with the ins allele of rs34802628. Bioinformatics analysis revealed that higher expression of the COL4A2 gene was significant with development and poor prognosis of STAD. CONCLUSION: The results of our study provide strong evidence indicating a potential involvement of genetic variants in the COL4A2 gene in the development of STAD. Nonetheless, to validate and consolidate these findings, additional investigations incorporating larger sample sizes and functional experiments are necessary.

Development and validation of a risk prognostic model based on the H. pylori infection phenotype for stomach adenocarcinoma.

Background: Stomach adenocarcinoma (STAD) is one of the most common malignancies. Infection of helicobacter pylori (H. pylori) is a major risk factor that leads to the development of STAD. This study constructed a risk model based on the H. pylori-related macrophages for predicting STAD prognosis. Methods: The single-cell RNA sequencing (scRNA-seq) dataset and the clinic information and RNA-seq datasets of STAD patients were collected for establishing a prognostic model and for validation. The "Seurat" and "harmony" packages were used to process the scRNA-seq data. Key gene modules were sectioned using the "limma" package and the "WGCNA" package. Kaplan-Meier (KM) and Receiver Operating Characteristic Curve (ROC) analyses were performed with "survminer" package. The "GSVA" package was employed for single sample gene set enrichment analysis (ssGSEA). Cell migration and invasion were measured by carrying out wound healing and trans-well assays. Results: A total of 17397 were screened and classified into 8 cell type clusters, among which the macrophage cluster was closely associated with the H. pylori infection. Macrophages were further categorized into four subtypes (including C1, C2, C3, and C4), and highly variable genes of macrophage subtype C4 could serve as an indicator of the prognosis of STAD. Subsequently, we developed a RiskScore model based on six H. pylori -associated genes (TNFRSF1B, CTLA4, ABCA1, IKBIP, AKAP5, and NPC2) and observed that the high-risk patients exhibited poor prognosis, higher suppressive immune infiltration, and were closely associated with cancer activation-related pathways. Furthermore, a nomogram combining the RiskScore was developed to accurately predict the survival of STAD patients. AB CA 1 in the RiskScore model significantly affected the migration and invasion of tumor cells. Conclusion: The gene expression profile served as an indicator of the survival for patients with STAD and addressed the clinical significance of using H. pylori-associated genes to treat STAD. The current findings provided novel understandings for the clinical evaluation and management of STAD.

UBR1 is a prognostic biomarker and therapeutic target associated with immune cell infiltration in gastric cancer.

BACKGROUND: Ubiquitination is a targeted protein modification process mediated by intracellular molecules. UBR1 encodes a protein that binds to unstable N-terminal residues of substrate proteins and contributes to the formation of substrate-linked polyubiquitin chains. However, the function and cellular pathways of UBR1 in tumors have received inadequate attention. This study aimed to investigate the potential of UBR1 as a prognostic biomarker and immunotherapy target for stomach adenocarcinoma (STAD) as well as its biological function and molecular mechanism in relation to the disease. METHODS: Differential expression and pan-cancer gene set enrichment analysis (GSEA) were conducted using The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Genotype-Tissue Expression (GTEx) datasets. The Human Protein Atlas (HPA) database was utilized to identify UBR1-enriched pathways in AGS cells and to compare immunohistochemical differences between cancerous and adjacent non-cancerous tissues in gastric cancer. Quantitative Polymerase Chain Reaction (QPCR) and Western blot (WB) analyses were employed to validate these findings in both cancerous and adjacent non-cancerous tissues of gastric cancer. UBR1 expression in GES-1 and four gastric cancer cell lines was assessed using QPCR and WB. Kaplan-Meier curves, univariate and multivariate Cox regression analyses, and receiver operating characteristic (ROC) curve analyses were performed to evaluate the prognostic and diagnostic roles of UBR1. Additionally, the correlation between UBR1 expression and clinical parameters was analyzed using TCGA and GEO databases. UBR1 mutation data were obtained from the cBioPortal database. The mutation landscape, mutation-associated genes, protein structure, tumor mutation burden (TMB), and microsatellite instability (MSI) correlations were analyzed and illustrated. The biological functions of UBR1 were investigated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The correlation between UBR1 and immune infiltration was assessed using TIMER and EPIC computational methods. Protein expression levels of UBR1 in gastric cancer cell lines were determined by immunohistochemistry (IHC) and WB analysis. Quantitative real-time PCR (qRT-PCR) was employed to analyze mRNA expression. Immunoprecipitation (IP) assays were conducted to detect protein-protein interactions between UBR1 and PDL1, while cellular immunofluorescence was used to observe the co-localization of these proteins. Cell proliferation was evaluated using CCK8 and colony formation assays. Cell migration was assessed using Transwell and wound healing assays. Finally, apoptosis was analyzed using flow cytometry, and WB was used to detect changes in apoptotic proteins and NF-κB P65 pathway proteins. RESULTS: UBR1 was upregulated in 28 cancer types, including STAD, and its overexpression was validated in gastric cancer cell lines and tissues. UBR1 expression was associated with advanced pathological characteristics. High UBR1 expression was linked to poor prognostic outcomes, including overall survival (OS), progression-free interval (PFI), disease-specific survival (DSS), as well as responses to surgery, chemotherapy, and HER2 expression. UBR1 expression showed significant correlations with clinical parameters such as age, gender, TNM stage, pathological stage, tumor resection, and anti-reflux therapy. Amplifications and deletions were the most frequent genetic alterations associated with UBR1. According to KEGG and GSEA analyses, UBR1 was significantly associated with several cancer pathways, oxidative phosphorylation, and the TNF-NFκB pathway. UBR1 also exhibited a significant correlation with immune cell infiltration and immunotherapy, including a direct interaction with PDL1. Knockdown of UBR1 inhibited the proliferation, migration, and invasion of STAD cells and promoted apoptosis. CONCLUSIONS: UBR1 is overexpressed in STAD, promoting its progression and positively correlating with immune cell infiltration and immunotherapeutic responses. Therefore, UBR1 could be a promising biomarker for the prognosis and immunotherapy of STAD.

Integrated analysis of disulfidoptosis-related genes identifies NRP1 as a novel biomarker promoting proliferation of gastric cancer via glutamine mediated energy metabolism.

The incidence and mortality of gastric cancer rank fifth and fourth worldwide among all malignancies, respectively. Additionally, disulfidoptosis, a recently identified form of cellular demise, is closely linked to the initiation and advancement of malignancies. This study aims to create a novel signature of disulfidptosis-related genes (DRGs) and to further explore its association with the tumor immune microenvironment. Based on our comprehensive study, a prognostic signature consisting of 31 DRGs in stomach adenocarcinoma (STAD) was identified and characterized. Through the integrative analyses involving gene expression profiling, machine learning algorithms, and Cox regression models, the prognostic significance of these DRGs was demonstrated. Our findings highlight their strong predictive power in assessing overall survival across diverse patient datasets, and their better performance than traditional clinicopathological factors. Moreover, the DRGs signature showed association with the characteristics of the tumor microenvironment, which has implications for the immune modulation and therapeutic strategies in STAD. Specifically, NRP1 emerged as a key DRG with elevated expression in STAD, showing correlation with the advanced stages of diseases and poorer outcomes. Functional studies further revealed the role of NRP1 in promoting STAD cell proliferation through the modulation of glutamine metabolism. Overall, our study underscores the clinical relevance of DRGs as biomarker and potential therapeutic targets in STAD management, providing insights into disease biology and personalized treatments.

Construction of a prognostic model via WGCNA combined with the LASSO algorithm for stomach adenocarcinoma patients.

Objective: This study aimed to identify prognostic signatures to predict the prognosis of patients with stomach adenocarcinoma (STAD), which is necessary to improve poor prognosis and offer possible treatment strategies for STAD patients. Methods: The overlapping genes between the key model genes that were screened by the weighted gene co-expression network analysis (WGCNA) and differentially expressed genes (DEGs) whose expression was different with significance between normal and tumor tissues were extracted to serve as co-expression genes. Then, enrichment analysis was performed on these genes. Furthermore, the least absolute shrinkage and selection operator (LASSO) regression was performed to screen the hub genes among overlapping genes. Finally, we constructed a model to explore the influence of polygenic risk scores on the survival probability of patients with STAD, and interaction effect and mediating analyses were also performed. Results: DEGs included 2,899 upregulated genes and 2,896 downregulated genes. After crossing the DEGs and light-yellow module genes that were obtained by WGCNA, a total of 39 overlapping genes were extracted. The gene enrichment analysis revealed that these genes were enriched in the prion diseases, biosynthesis of unsaturated fatty acids, RNA metabolic process, hydrolase activity, etc. PIP5K1P1, PTTG3P, and SNORD15B were determined by LASSO-Cox. The prognostic prediction of the three-gene model was established. The Cox regression analysis showed that the comprehensive risk score for three genes was an independent prognosis factor. Conclusion: PIP5K1P1, PTTG3P, and SNORD15B are related to the prognosis and overall survival of patients. The three-gene risk model constructed has independent prognosis predictive ability for STAD.

The distribution and maturation of tertiary lymphoid structures can predict clinical outcomes of patients with gastric adenocarcinoma.

Introduction: Tertiary lymphoid structures (TLSs) are analogues of secondary lymphoid organs that contain various immune cells. The spatial distribution, maturation and composition of TLSs have differential effects on prognosis, and the roles of TLSs in gastric adenocarcinoma (GA) have not been revealed. Methods: Thus, we evaluated the prognostic value of TLSs in GA through analysis of bulk RNA sequencing(RNA-seq) data from public databases and validated our findings in tumour samples from the Fudan University Shanghai Cancer Center (FUSCC) cohort. The spatial distribution,maturation, and composition of TLSs in GA were analysed by reviewing H&E-stained sections and by multiplex immunofluorescence (mIF) staining. Results: We found that TLSs, especially TLSs with germinal centres (GCs) and TLSs located in the invasive margin (IM), were correlated with prolonged overall survival (OS). Second, analysis of public RNA-seq data showed that high dendritic cell (DC) scores were a favourable prognostic factor in GA patients with high scores for both TLSs and GCs. In the FUSCC cohort, DC-LAMP+ DCs weresignificantly enriched in IM-TLSs with GCs, suggesting a potential correlation between the tumour immune activation milieu and the DC abundance. Third, compared to that in TLSs without GCs, the proportion of FOXP3+CD8+ Treg cells was significantly decreased in IM-TLSs with GCs, and the percentage of PD1+CD20+ B cells was significantly increased in TLSs with GCs. Discussion: Our results demonstrate that the spatial arrangement and maturation of TLSs significantly affect prognosis and indicate that TLSs could be a new additional factor for histopathological evaluation.

Comprehensive analysis of CPNE1 predicts prognosis and drug resistance in gastric adenocarcinoma.

BACKGROUND: Recent studies have confirmed that Copines-1 (CPNE1) is associated with many malignancies. However, the role of CPNE1 in stomach adenocarcinoma (STAD) is currently unclear. METHODS: TIMER2.0, TCGA, UALCAN databases were used to investigate the expression of CPNE1 in STAD and normal tissues. KM-plotter database was used to explore the relationship between CPNE1 expression and prognosis in STAD. Immunohistochemistry (IHC) was used to assess the protein levels of CPNE1 in both normal and cancer tissues, as well as to confirm the prognostic significance of CPNE1. In order to assess the viability of CPNE1 as a divider, the Recipient Operating Characteristics (ROC) curve was employed and the assessment based on the AUC score (below the curve). To investigate the potential function of CPNE1, correlation analysis and enrichment analysis were performed with the clusterProfiler package in R software. The CPNE1 binding protein network was constructed by STRING and GeneMANIA. The relationship between methylation and prognosis was explored by Methsurv database. The Genomics of Drug Sensitivity in Cancer (GDSC) was employed to predict drug responsiveness in STAD. Ultimately, CCK-8 assays and RT-qPCR were performed to confirm the correlation between CPNE1 expression and the IC50 of Axitinib in the AGS cell line. RESULT: CPNE1 is highly expressed in various cancers, including STAD. High expression of CPNE1 indicated poor overall survival (OS) of STAD (P < 0.05). The ROC curve suggested that CPNE1 was a potential diagnostic biomarker (AUC = 0.925). The functions of CPNE1 were enriched in DNA-acting catalytic activity, sulfur transferase activity, Ran GTPase binding, DNA helicase activity, helicase activity and eukaryotic ribosome biosynthesis. Hyper-methylated CPNE1 predicts better prognosis in STAD (P < 0.05). Additionally, STAD patients with high-expression CPNE1 seemed to be more resistant to the chemotherapeutic agents, including A-770041, WH-4-023, AZD-2281, AG-014699, AP-24534, Axitinib, AZD6244, RDEA119, AZD8055, Temsirolimus, Pazopanib and Roscovitine. In vitro experiments demonstrated the involvement of CPNE1 in Axitinib chemoresistance. CONCLUSION: CPNE1 could be a predictive biomarker and a potential target for biological therapy in STAD.

FDX1 as a novel biomarker and treatment target for stomach adenocarcinoma.

BACKGROUND: Stomach adenocarcinoma (STAD) is one of the main reasons for cancer-related deaths worldwide. This investigation aimed to define the connection between STAD and Cuproptosis-related genes (CRGs). Cuproptosis is a newly identified form of mitochondrial cell death triggered by copper. AIM: To explore the identification of potential biomarkers for STAD disease based on cuproptosis. METHODS: A predictive model using Gene Ontology (GO), Least Absolute Shrinkage and Selection Operator (LASSO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Variation Analysis (GSVA), and Gene Set Enrichment Analysis analyzed gene interconnections, focusing on 3 copper-related genes and their expression in The Cancer Genome Atlas-STAD. Networks for mRNA-miRNA and mRNA-transcription factor interactions were constructed. The prognostic significance of CRG scores was evaluated using time-receiver operating characteristic, Kaplan-Meier curves, and COX regression analysis. Validation was conducted with datasets GSE26942, GSE54129, and GSE66229. Expression of copper-related differentially expressed genes was also analyzed in various human tissues and gastric cancer subpopulations using the human protein atlas. RESULTS: Three significant genes (FDX1, LIAS, MTF1) were identified and selected via LASSO analysis to predict and classify individuals with STAD into high and low CRG score subgroups. These genes were down-regulated in both risk categories. GO and KEGG analyses highlighted their involvement mainly in the electron transport chain. After validating their differential expression, FDX1 emerged as the most accurate diagnostic marker for gastric cancer. Additionally, the RCircos package localized FDX1 on chromosome 11. CONCLUSION: Our study revealed that FDX1 could be a potential biomarker and treatment target for gastric malignancy, providing new ideas for further scientific research.

Establishment and validation of a prognostic scoring model based on disulfidptosis-related long non-coding RNAs in stomach adenocarcinoma.

Background: Stomach adenocarcinoma (STAD), a frequently occurring gastrointestinal tumour, is often detected late and has a poor prognosis. Long non-coding RNAs (lncRNAs) significantly affect tumour development. Recent studies have identified disulfidptosis as a previously unexplained form of cell death. Herein, we aimed to examine the predictive value of disulfidptosis-related lncRNA models for the clinical prognosis and immunotherapy of STAD. Methods: STAD-related transcriptomic data were obtained from The Cancer Genome Atlas (TCGA), whereas genes associated with disulfidptosis were identified from previously published papers. A risk prediction model for disulfidptosis-related lncRNAs was developed using the Cox regression and least absolute shrinkage selection algorithm methods. The accuracy of the model was confirmed using calibration curves, and the biological functions were analysed using Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA). Finally, the tumour mutation burden (TMB) and tumour immune dysfunction and exclusion (TIDE) algorithms were used to screen drugs that are sensitive to STAD. Results: The risk prediction models were constructed using seven disulfidptosis-related lncRNAs. The validated results were consistent with the predicted ones, with significant survival differences. When combined with clinical data, the risk scores were used as independent prognostic markers. Based on the tumour mutation load, the high-risk patient group had a poorer survival rate as compared with the low-risk patient group. Further studies were conducted to understand the different groups' inconsistent responses to immune status; subsequently, relatively sensitive drugs were identified. Conclusions: Overall, seven markers of disulfidptosis-related lncRNAs associated with STAD were found to facilitate prognostic prediction, suggesting new ideas for immunotherapy and clinical applications.

FASTKD1 as a diagnostic and prognostic biomarker for STAD: Insights into m6A modification and immune infiltration.

Fas-activated serine/threonine kinase domain 1 (FASTKD1), a known modulator of mitochondrial-mediated cell death and survival processes, has garnered attention for its potential role in various biological contexts. However, its involvement in gastric cancer remains unclear. Thus, the present study aimed to investigate the relationship between FASTKD1 expression and key factors, including clinicopathological characteristics, immune infiltration and m6A modification in stomach adenocarcinoma (STAD). The expression of FASTKD1 was analyzed in STAD and normal adjacent tissues to assess its association with clinicopathological characteristics and survival prognosis. Data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used in this study. Additionally, the findings were validated through immunohistochemical staining. Co-expression analysis of FASTKD1 was performed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (GO/KEGG) enrichment analysis, Gene Set Enrichment Analysis (GSEA) and LinkedOmics database analysis. An in-depth analysis was conducted using databases, such as Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), GEO and TCGA to explore the potential correlation between FASTKD1 expression and immune infiltration and m6A modification in STAD. The results revealed that FASTKD1 was significantly upregulated across different tumor types, including STAD. Notably, FASTKD1 was able to distinguish between tumor and normal tissue samples with accuracy. Furthermore, the expression levels of FASTKD1 were significantly associated with clinical stage and survival. Through GO/KEGG enrichment analysis and GSEA, it was revealed that the genes co-expressed with FASTKD1 were active in a variety of biological processes. Within the TIMER, GEPIA and TCGA databases, a notable inverse correlation was observed between FASTKD1 expression and the abundance of immune cell subsets. Notably, significant correlations were established between FASTKD1 and m6A modification genes, YTHDF1 and LRPPRC, in both TCGA and GEO datasets. In conclusion, FASTKD1 may serve a significant role in m6A modification and immune infiltration processes, making it a potentially valuable diagnostic and prognostic biomarker in STAD.

Comprehensive analysis of the expression, prognostic, and immune infiltration for COL4s in stomach adenocarcinoma.

BACKGROUND: Collagen (COL) genes, play a key role in tumor invasion and metastasis, are involved in tumor extracellular matrix (ECM)-receptor interactions and focal adhesion pathways. However, studies focusing on the diagnostic value of the COL4 family in stomach adenocarcinoma (STAD) are currently lacking. METHODS: The TCGA database was employed to retrieve the clinical features and RNA sequencing expression profiles of patients with STAD. We conducted an investigation to examine the expression disparities between STAD and adjacent normal tissues. Kaplan-Meier survival analysis was utilized to assess their prognostic significance, while Spearman correlation analysis was employed to determine their association with immune checkpoint genes and immunomodulatory molecules. Furthermore, GO and KEGG analyses were performed on the COL4s-related genes, revealing potential biological pathways through gene set enrichment analysis (GSEA). Subsequently, we explored the extent of immune infiltration of the COL4 family in STAD using the TIMER database. Lastly, the expression levels of the COL4 family in STAD were further validated through quantitative PCR (qPCR) and western blot techniques. RESULTS: The expression levels of COL4A1/2 were significantly upregulated, while COL4A5/6 were conspicuously downregulated in STAD. The survival analysis revealed that the upregulated COL4s indicated poorer overall survival, first progression and post-progression survival outcomes. Additionally, our findings demonstrated a positive correlation between the expressions of COL4A1/2/3/4 and the infiltration of immune cells, including CD8 + T cells, dendritic cells, macrophages, neutrophils and CD4 + T cells. Further correlation analysis uncovered a favorable association between the expression of COL4A1/2/3/4 and various crucial immunomodulatory molecules, immunological checkpoint molecules, and chemokines. Quantitative PCR analysis confirmed that the expression patterns of COL4A1/3/4/6 genes aligned with the finding from the TCGA database. However, gastric cancer cells exhibited downregulation of COL4A2. Consistently, the protein level of COL4A1 was elevated, whereas the protein level of COL4A2 was reduced in the gastric cancer cell lines. CONCLUSION: COL4s could potentially serve as biomarkers for diagnosing and predicting the prognosis of STAD.

Identification and Validation of a Cancer-Testis Antigen-Related Signature to Predict the Prognosis in Stomach Adenocarcinoma.

Background: Stomach adenocarcinoma (STAD) is the fifth most common cancer and the third leading cause of cancer-related deaths worldwide. Cancer-testis antigens (CTAs) participate in the pathogenesis and development of multiple cancers and are aberrantly overexpressed in various types of cancer. This study aimed to develop a CTA-related gene signature (CTARSig) to predict prognosis in STAD patients and explore its underlying mechanisms. Methods: We performed differential and prognostic analyses of CTA-related genes and constructed a CTA-related signature (CTARSig) along with a novel nomogram to predict the prognosis of patients with STAD based on the Cox and The Least Absolute Shrinkage and Selection Operator. CTARSig was further validated in an external cohort (GSE84437). Additionally, univariate and multivariate Cox regression, as well as receiver operating characteristic (ROC) analyses, were performed to assess the CTARSig systematically. Single-sample gene set enrichment analysis and ESTIMATE were used to characterise the Tumor Immune Microenvironment (TIME) in patients with STAD. Furthermore, Gene Set Variation Analysis, Kyoto Encyclopedia of Genes and Genomes, and Gene Ontology analyses revealed the biological functions and signalling pathways associated with CTARSig. Finally, the human gastric cancer cell lines, HCG-27 and AGS, were used for in vitro and in vivo experiments, respectively, to further validate the role of ELOVL4. Results: Eleven CTA-related genes were identified to construct the CTARSig. Kaplan-Meier curves, independent prognostic analysis, and ROC curves revealed that CTARSig could better predict survival in patients with STAD. Moreover, in our study, we demonstrated that ELOVL4 is upregulated in gastric cancer tissues and that its high expression is associated with poor survival. Additionally, in vitro and in vivo experiments demonstrated that ELOVL4 promotes the metastatic and invasive potential of STAD cells, suggesting it may be a potential therapeutic target for STAD. Conclusion: In this study, a novel signature associated with CTAs was constructed for STAD, which may be a good predictor of patient prognosis. Thus, ELOVL4 may be a potential therapeutic target for gastric cancer. This study provides new insights into the potential roles of CTAs in gastric cancer.

Integrative analysis indicates the potential values of ANKRD53 in stomach adenocarcinoma.

BACKGROUND: Ankyrin repeat domain 53 (ANKRD53) plays an important role in maintaining chromosome integrity and stability, and chromosome instability is associated with cancer. Through integrative analysis, this study investigates the potential value of ANKRD53 in stomach adenocarcinoma (STAD). METHODS: RNA-seq and scRNA-seq data were used for integrative analysis based on online databases. Expression of ANKRD53 was confirmed by RT-PCR after bioinformatic analysis. Kaplan-Meier and Cox regression analyses were performed to evaluate the prognostic value of ANKRD53 in STAD. Gene set enrichment analysis (GSEA) was performed to evaluate ANKRD53-related signaling pathways. In addition, the interaction of ANKRD53 with immunity was also investigated. RESULTS: RT-PCR in STAD cell lines confirmed that ANKRD53 was downregulated in STAD samples compared to normal samples in the online databases. As an independent predictive biomarker, ANKRD53 was combined with other clinicopathological parameters to create a prognostic nomogram. Using GSEA, ANKRD53 was found to be involved in five pathways, including the TGF-ß signaling pathway. Further investigation revealed that ANKRD53 was associated with immune checkpoint molecules, immunological pathways, and immunotherapy, in addition to MSI, TMB and neoantigens. In addition, scRNA-seq data revealed that ANKRD53 is mainly expressed in CD8+ T and dendritic cells. CONCLUSIONS: ANKRD53 is an important biomarker for STAD that deserves further attention.

Prognostic value and therapeutic potential of NEK family in stomach adenocarcinoma.

Never in mitosis gene A-related kinase (NEK) is an 11-membered family of serine/threonine kinases (NEK1-NEK11), which are known to play important roles in the formation and development of cancer. However, few studies have examined the roles of these kinases in the development of stomach adenocarcinoma (STAD). In this study, we conducted a comprehensive analysis of the relationships between the NEKs family members and STAD. The differential expression of the NEK genes in STAD was validated using The Cancer Genome Atlas (TCGA) and Tumor Immune Estimation Resource (TIMER) databases, and their prognostic and diagnostic values of NEKs in STAD were assessed using the Kaplan-Meier plotter and TCGA data. The effect of NEK expression on immune cell infiltration in STAD was analysed using the TIMER and TISIDB databases. The expression levels of the majority of the NEK family members were consistently upregulated in STAD, whereas that of NEK10 was downregulated. The upregulation of NEK2/3/4/5/6/8 was closely associated with clinicopathological parameters of patients, and the overexpressed levels of these proteins had good diagnostic value for the disease. NEK1/8/9/10/11 expression correlated with poor overall survival and post-progressive survival, whereas a higher NEK1/6/9/11 level implied worse first progressive survival. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that the NEKs may be related to immunological responses. Additionally, our study confirmed that these kinases correlated with immune cell infiltration and different immune infiltration subtypes in STAD. Our results suggest that NEK9 in particular has the potential to be used as a diagnostic and prognostic biomarker of STAD development and progression and an immune target for treatment of the disease. These findings expand our understanding of the biological functions of the NEK family members in STAD.

Construction of a disulfidptosis-related glycolysis gene risk model to predict the prognosis and immune infiltration analysis of gastric adenocarcinoma.

BACKGROUND: The pattern of cell death known as disulfidptosis was recently discovered. Disulfidptosis, which may affect the growth of tumor cells, represents a potential new approach to treating tumors. Glycolysis affects tumor proliferation, invasion, chemotherapy resistance, the tumor microenvironment (TME), and immune evasion. However, the efficacy and therapeutic significance of disulfidptosis-related glycolysis genes (DRGGs) in stomach adenocarcinoma (STAD) remain uncertain. METHODS: STAD clinical data and RNA sequencing data were downloaded from the TCGA database. DRGGs were screened using Cox regression and Lasso regression analysis to construct a prognostic risk model. The accuracy of the model was verified using survival studies, receiver operating characteristic (ROC) curves, column plots, and calibration curves. Additionally, our study investigated the relationships between the risk scores and immune cell infiltration, tumor mutational burden (TMB), and anticancer drug sensitivity. RESULTS: We have successfully developed a prognosis risk model with 4 DRGGs (NT5E, ALG1, ANKZF1, and VCAN). The model showed excellent performance in predicting the overall survival of STAD patients. The DRGGs prognostic model significantly correlated with the TME, immune infiltrating cells, and treatment sensitivity. CONCLUSIONS: The risk model developed in this work has significant clinical value in predicting the impact of immunotherapy in STAD patients and assisting in the choice of chemotherapeutic medicines. It can correctly estimate the prognosis of STAD patients.

TEAD4 Activates PCSK9 to Promote Stomach Adenocarcinoma Cell Stemness through Fatty Acid Metabolism.

INTRODUCTION: This study attempted to investigate how proprotein convertase subtilisin/kexin type 9 (PCSK9) influences the stemness of stomach adenocarcinoma (STAD) cells. METHODS: CCK-8 and sphere-formation assays were used to detect cell viability and stemness. qRT-PCR and Western blot were used to detect PCSK9 and TEAD4 expression. The binding relationship was verified by dual-luciferase and chromatin immunoprecipitation assays. The effect of TEAD4 activating PCSK9 on the stemness of STAD cells was detected by bioinformatics, BODIPY 493/503, Oil red O, Western blot, and kits. In vivo experiments verified the role of the TEAD4/PCSK9 axis in tumor formation in nude mice. RESULTS: PCSK9 and TEAD4 were highly expressed in STAD. PCSK9 was enriched in the fatty acid metabolism (FAM) pathway. PCSK9 activated the fatty acid metabolism and promoted the proliferation and stemness of STAD cells. TEAD4 as a transcription factor upstream of PCSK9, cell experiments revealed that knockdown of PCSK9 inhibited STAD cell stemness, whereas further addition of fatty acid inhibitors could attenuate the promoting effect on STAD cell stemness brought by STAD overexpression. Rescue experiments showed overexpressed PCSK9 exerted an inhibitory effect on the stemness of STAD cells brought by TEAD4 knockdown. The hypothesis that TEAD4/PCSK9 axis can promote STAD cell growth was confirmed by in vivo experiments. CONCLUSION: Transcription factor TEAD4 could activate PCSK9 to promote the stemness of STAD cells through FAM. These results added weight to the assumption that TEAD4/PCSK9 axis has the potential to be the therapeutic target that inhibits cancer stem cell in STAD.