Genes In Gastric Cancer Research Articles

Large-scale analysis of CDH1 mutations defines a distinctive molecular subset with treatment implications in gastric cancer.

Although histological and molecular classifications have been extensively studied for gastric cancer (GC), targeted therapies for GC remain limited. CDH1 mutations (MT) are characteristic of genomically stable GC and are associated with poor prognosis, but lack effective or targeted therapies. Here, we showed the overall mutation frequency of CDH1 was 9.7% (155 of 1596). CDH1-MT GC showed significantly lower rates of PD-L1 positivity (CPS score ≥1) than CDH1-wildtype (WT) GC (56.7% vs. 73.3%, p < 0.05). Compared to CDH1-WT GC, mutations of ARID1A, WRN, POT1, CDK12, and FANCC were significantly higher, while TP53 and APC were significantly lower in CDH1-MT GC (p < 0.05); The rates of KRAS and HER2 amplifications were significantly lower, while CRKL and IGF1R amplifications were significantly higher in CDH1-MT GC, compared to CDH1-WT GC (p < 0.05). Frequently altered genes in CDH1-MT GC were especially enriched in DNA damage repair and cell cycle checkpoint pathways. Inhibition of E-cadherin sensitized GC cell lines to PARP and Wee1 inhibitors by disrupting DNA damage repair pathway and cell cycle checkpoint. This is the largest study to investigate the distinct genomic landscape of CDH1-MT GC. Our data indicated GC patients with CDH1 mutations could potentially benefit from agents targeting PARP and Wee1.

A novel m6A/m5C/m1A/m7G-related classification and risk signature predicts prognosis and reveals immunotherapy inclination in gastric cancer.

Gastric cancer (GC) is characterized by high morbidity and mortality rates, and the prognosis is not optimistic. Therefore, the search for new biomarkers is crucial. Methylation modifications in RNA modifications play a crucial role in tumors. However, the role of methylation modification of integrated m6A/m5C/m1A/m7G, in GC and its related analysis have not been reported. It still needs to be studied in depth. Our study aims to deepen our understanding of m6A/m5C/m1A/m7G methylation and potentially provide new strategies for GC treatment. We used TCGA-STAD (The Cancer Genome Atlas-Stomach Adenocarcinoma) as a training set and GSE84433 as a validation set to analyze and determine potential associations between m6A/m5C/m1A/m7G-related genes and clinical risk of GC. In addition, we explored the prognostic value and potential biological mechanisms of m6A/m5C/m1A/m7G-related genes in GC through consistent clustering, differential expression gene identification, enrichment analysis, and immune infiltration analysis. Finally, we constructed m6A/m5C/m1A/m7G-related risk signature (MRRS) to evaluate the correlation between risk grade and survival prognosis, drug sensitivity, and immune infiltration, and validated the validity by immunohistochemical staining. We identified subgroups of C1, C2, and C3 patients by consensus clustering using data from 45 m6A/m5C/m1A/m7G-related genes. The three groups showed significant differences in survival, immune scores, and immune cell infiltration. We then constructed MRRS using least absolute shrinkage and selection operator (LASSO) regression analysis, including SLC5A6, FKBP10, GPC3, and GGH, which could accurately differentiate between high-/low-risk populations. Its accuracy was further validated in the validation set and immunohistochemical staining. These results suggest that m6A/m5C/m1A/m7G are closely related to the GC tumor immune microenvironment, and MRRS has good performance in predicting the survival of GC patients. In this study, we highlighted the association of m6A/m5C/m1A/m7G subtypes with changes in the GC immunotumor microenvironment. We constructed and validated MRRS, which is valuable in predicting survival, immune infiltration and drug sensitivity in GC patients. This helps to deepen our understanding of m6A/m5C/m1A/m7G methylation and potentially provides new strategies for GC treatment.

Bioinformatics analysis of the association between obesity and gastric cancer.

Obesity and gastric cancer (GC) are prevalent diseases worldwide. In particular, the number of patients with obesity is increasing annually, while the incidence and mortality rates of GC are ranked high. Consequently, these conditions seriously affect the quality of life of individuals. While evidence suggests a strong association between these two conditions, the underlying mechanisms of this comorbidity remain unclear. We obtained the gene expression profiles of GSE94752 and GSE54129 from the Gene Expression Omnibus database. To investigate the associated biological processes, pathway enrichment analyses were conducted using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes for the shared differentially expressed genes in obesity and GC. A protein-protein interaction (PPI) network was subsequently established based on the Search Tool for the Retrieval of Interacting Genes (STRING) database, followed by the screening of the core modules and central genes in this network using Cytoscape plug-in MCODE. Furthermore, we scrutinized the co-expression network and the interplay network of transcription factors (TFs), miRNAs, and mRNAs linked to these central genes. Finally, we conducted further analyses using different datasets to validate the significance of the hub genes. A total of 246 shared differentially expressed genes (209 upregulated and 37 downregulated) were selected for ensuing analyses. Functional analysis emphasized the pivotal role of inflammation and immune-associated pathways in these two diseases. Using the Cytoscape plug-in CytoHubba, nine hub genes were identified, namely, CXCR4, CXCL8, CXCL10, IL6, TNF, CCL4, CXCL2, CD4, and CCL2. IL6 and CCL4 were confirmed as the final hub genes through validation using different datasets. The TF-miRNA-mRNA regulatory network showed that the TFs primarily associated with the hub genes included RELA and NFKB1, while the predominantly associated miRNAs included has-miR-195-5p and has-miR-106a-5p. Using bioinformatics methods, we identified two hub genes from the Gene Expression Omnibus datasets for obesity and GC. In addition, we constructed a network of hub genes, TFs, and miRNAs, and identified the major related TFs and miRNAs. These factors may be involved in the common molecular mechanisms of obesity and GC.

Identification and validation of Cystatin A as a novel promising therapeutic target for gastric cancer.

The effect of pharmacological treatment of gastric cancer (GC) is limited, thus, it holds significant scientific importance to thoroughly investigate the molecular mechanisms underlying GC development and identify novel molecules capable of substantially extending patients' survival. This study utilized bioinformatics techniques to identify 11 genes associated with recurrence-free survival (RFS) in GC patients and investigated the potential biological functions of these genes through single-cell transcriptomic analysis. Subsequently, a single gene Cystatin A (CSTA) was selected for further analysis to explore its impact on signaling pathways and treatment. Differentially expressed genes (DEGs) were identified and overlapped in the analysis of RFS to identify potential prognostic genes for GC patients, based on data from the Cancer Genome Atlas-stomach adenocarcinoma (TCGA-STAD) and GSE54129. Subsequently, a prognostic model based on RFS in GC patients was established. Single-cell sequencing data were employed to explore the potential functions of these model genes. CSTA, one of the RFS-related genes, was further investigated using immunohistochemistry (IHC), Cell Counting Kit 8 (CCK-8), transwell, scratch, colony formation assays, flow cytometry, and Western blotting methods. Through bioinformatics analysis, we identified 23 RFS-related genes in GC. Using the least absolute shrinkage and selection operator (LASSO)-Cox method, an RFS prognostic model was developed which pinpointed 11 GC prognosis-related (GPR) genes as significant factors influencing RFS in GC patients. The single-cell analysis revealed their potential role in affecting differentiation and maturation of pre-fibroblasts thereby impacting RFS in GC patients. CSTA exhibited low expression levels in GC tissues. Overexpression of CSTA promoted apoptosis in GC cells through the caspase-dependent apoptotic pathway and enhanced their response to cisplatin via this same pathway. The 11 GPR genes are primarily enriched within a specific type of stromal cell exhibiting heightened communication, metabolism, and differentiation levels. The gene signature of these stromal cells has implications for patient prognosis. Additionally, CSTA, a gene related to prognosis, has been shown to influence apoptosis levels in GC cells.

Impact of pathogenic germline variants in HRR genes on gastroesophageal cancer in a large real-world Chinese population: A comprehensive study.

10588 Background: Genetic testing in gastroesophageal cancer has been limited to those with hereditary cancer syndromes, restricting understanding of the impact of germline variants in sporadic cancers. Our study expands this by exploring germline and somatic characteristics in a broad Chinese cohort, enhancing risk assessment and guiding treatment strategies in a wider population. Methods: From October 2017 to April 2023, we retrospectively analyzed 2596 Chinese gastroesophageal cancer (GEC) patients, including 2003 with gastric cancer (GC), 196 with gastroesophageal junction cancer (GEJC), and 397 with esophageal cancer (EC). A 520-gene panel including 62 genes associated with cancer predisposition, was employed for genomic profiling of paired tumor and white blood cell samples. The pathogenicity of germline variants was determined according to ACMG guidelines. Results: In this retrospective cohort, the proportion of patients carrying pathogenic/likely pathogenic (P/LP) germline variants was 5.3% in GC, 5.6% in GEJC, and 5.0% in EC, respectively. Notably, genes associated with HRR exhibited the highest rates of P/LP germline mutations in GEC (94, 3.7%), with the majority occurring in non-BRCA HRR genes (77, 3.0%). The top five genes with the highest mutation rates were ATM, PALB2, FANCA, CHEK2, and RAD54L. Compared to the East Asian population without cancer in the genomAD database, a higher proportion of P/LP germline mutations were found in the CDH1(Inf [6.46-Inf], p &lt; 0.001), PALB2 (5.60 [1.61-13.09], p = 0.002), SDHA (8.99 [1.29-99.42], p = 0.012), ATM (2.15 [1.08-4.09], p = 0.02), and CHEK2 (3.83 [1.06-13.32], p = 0.02) genes in GC. Similarly, significant increases in PALB2 (10.36 [2.32-37.28], p = 0.002) and ATM (4.42 [0.86-14.33], p = 0.036) were also observed in EC and GEJC. The HRR P/LP variant group exhibited a higher incidence of biallelic inactivation (loss of wildtype allele) compared to the B/LB variant group (24.7% vs 6.6%, p&lt;0.001). Moreover, the similar trend was observed for the moderately/uncertainly penetrant gene ATM and FANCA (38.5% vs 0.6%, p &lt; 0.001; 42.9% vs 9.8%, p = 0.025), which suggests that ATM and FANCA may be associated with a high risk. The HRR genes ATM(56 vs 61, p = 0.052), CDH1(33 vs 61, p = 0.003), and FANCI(48 vs 61, p = 0.041) with P/LP variants were associated with a younger age of onset. Carriers of HRR P/LP variants had less prevalent somatic TP53 variants in GC and GEC and higher HRD score compared to non-carriers (p=0.005). Conclusions: Our research delineates the germline P/LP variant landscape in Chinese GEC, revealing the significant role of HRR P/LP variants. The presence of P/LP variants in HRR genes in GEC is linked to distinct disease characteristics and progression, underscoring their importance in guiding personalized treatment approaches and risk evaluation.

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

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

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

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. To identify important candidate genes related to the development of GC and identify potential pathogenic mechanisms through comprehensive bioinformatics analysis. 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. 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). 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.

F2RL3 Regulates Epithelial-Mesenchymal Transition and Angiogenesis in Gastric Cancer through the Rap1/MAPK Signaling Pathway.

Gastric cancer (GC) is frequently diagnosed at advanced stages, when cancer cells have already metastasized. Therefore, patients with GC have a low survival rate and poor prognosis even after treatment. We downloaded GC-related RNA sequencing (RNA-Seq) data, copy number variation (CNV) data, and clinical data for bioinformatics analysis to screen prognostic genes of GC. Single-sample gene set enrichment analysis and survival analyses were performed on the RNA-Seq data, and differential and correlation analyses were conducted on the CNV data to obtain CNV-driven differentially expressed genes (DEGs). Prognostic genes were identified through univariate Cox analyses of the CNV-driven DEGs, combined with the clinical data. F2R like thrombin or trypsin receptor 3 (F2RL3) was finally selected for verification after functional and survival analyses of the prognostic genes. F2RL3 expression was lower in paracancer tissue than in GC tissue, and lower in GES-1 gastric epithelial cells than in GC cells. The cell culture supernatants from F2RL3-knockdown GC cells were collected and used to culture human umbilical vein endothelial cells (HUVECs). It was observed that F2RL3 enhanced the activity, metastasis, invasion, and angiogenesis of GC cells; promoted the epithelial-mesenchymal transition (EMT) of GC cells; and impacted the Ras-associated protein 1 (Rap1)/mitogen-activated protein kinase (MAPK) pathway. To further explore the involvement of the Rap1/MAPK pathway in GC development, a pathway activator was added to GC cells with knockdown of F2RL3 expression. This pathway activator not only enhanced the activity, invasion, and migration of GC cells but also promoted the EMT and blood vessel formation. F2RL3 regulates the angiogenesis and EMT of GC cells through the Rap1/MAPK pathway, thus influencing the onset and progression of GC.

Abstract P28: Comprehensive Molecular Phenotyping of ARID1A-deficient Gastric Cancer Reveals Pervasive Epigenomic Reprogramming and Therapeutic Opportunities

Abstract Objective Gastric cancer (GC) is a leading cause of cancer mortality, with ARID1A being the second most frequently mutated driver gene in GC. We sought to decipher ARID1A-specific GC regulatory networks and examine therapeutic vulnerabilities arising from ARID1A loss. Design Genomic profiling of GC patients including a Singapore cohort (&amp;gt;200 patients) was performed to derive mutational signatures of ARID1A inactivation across molecular subtypes. Single-cell transcriptomic profiles of ARID1A-mutated GCs were analyzed to examine tumor microenvironmental changes arising from ARID1A loss. Genome-wide ARID1A binding and chromatin profiles (H3K27ac, H3K4me3, H3K4me1, ATAC-seq) of gastric cell lines were generated to identify gastric-specific epigenetic landscapes regulated by ARID1A. Distinct cancer hallmarks of ARID1A-mutated GCs were converged at the genomic, single-cell, and epigenomic level, and targeted by pharmacological inhibition. Results We observed prevalent ARID1A inactivation across GC molecular subtypes, with distinct mutational signatures and linked to a NFKB-driven pro-inflammatory tumour microenvironment. ARID1A-depletion caused loss of H3K27ac activation signals at ARID1A-occupied distal enhancers, but unexpectedly gain of H3K27ac at ARID1A-occupied promoters in genes such as NFKB1 and NFKB2. Promoter activation in ARID1A-mutated GCs was associated with enhanced gene expression, increased BRD4 binding, and reduced HDAC1 and CTCF occupancy. Combined targeting of promoter activation and tumour inflammation via bromodomain and NFKB inhibitors confirmed therapeutic synergy specific to ARID1A-genomic status. Conclusion Our results suggest a therapeutic strategy for ARID1A-mutated GCs targeting both tumour-intrinsic (BRD4-assocatiated promoter activation) and extrinsic (NFKB immunomodulation) cancer phenotypes. Citation Format: Chang Xu, Kie Kyon Huang, Jia Hao Law, Joy Shijia Chua, Taotao Sheng, Natasha M. Flores, Melissa Pool Pizzi, Atsushi Okabe, Angie Lay Keng Tan, Feng Zhu, Vikrant Kumar, Xiaoyin Lu, Ana Morales Benitez, Benedict Shi Xiang Lian, Haoran Ma, Shamaine Wei Ting Ho, Kalpana Ramnarayanan, Chukwuemeka George Anene-Nzelu, Milad Razavi-Mohseni, Siti Aishah Binte Abdul Ghani, Su Ting Tay, Xuewen Ong, Ming Hui Lee, Yu Amanda Guo, Hassan Ashktorab, Duane Smoot, Shang Li, Anders Jacobsen Skanderup, Michael A. Beer, Roger Sik Yin Foo, Joel Shi Hao Wong, Kaushal Sanghvi, Wei Peng Yong, Raghav Sundar, Atsushi Kaneda, Shyam Prabhakar, Pawel Karol Mazur, Jaffer A. Ajani, Khay Guan Yeoh, Jimmy Bok-Yan So, Patrick Tan, Singapore Gastric Cancer Consortium. Comprehensive Molecular Phenotyping of ARID1A-deficient Gastric Cancer Reveals Pervasive Epigenomic Reprogramming and Therapeutic Opportunities [abstract]. In: Proceedings of Frontiers in Cancer Science; 2023 Nov 6-8; Singapore. Philadelphia (PA): AACR; Cancer Res 2024;84(8_Suppl):Abstract nr P28.

Clinical features and molecular landscape of cuproptosis signature-related molecular subtype in gastric cancer.

Recent studies have highlighted the biological significance of cuproptosis in disease occurrence and development. However, it remains unclear whether cuproptosis signaling also has potential impacts on tumor initiation and prognosis of gastric cancer (GC). In this study, 16 cuproptosis-related genes (CRGs) transcriptional profiles were harnessed to perform the regularized latent variable model-based clustering in GC. A cuproptosis signature risk scoring (CSRS) scheme, based on a weighted sum of principle components of the CRGs, was used to evaluate the prognosis and risk of individual tumors of GC. Four distinct cuproptosis signature-based clusters, characterized by differential expression patterns of CRGs, were identified among 1136 GC samples across three independent databases. The four clusters were also associated with different clinical outcomes and tumor immune contexture. Based on the CSRS, GC patients can be divided into CSRS-High and CSRS-Low subtypes. We found that DBT, MTF1, and ATP7A were significantly elevated in the CSRS-High subtype, while SLC31A1, GCSH, LIAS, DLAT, FDX1, DLD, and PDHA1 were increased in the CSRS-Low subtype. Patients with CSRS-Low score were characterized by prolonged survival time. Further analysis indicated that CSRS-Low score also correlated with greater tumor mutation burden (TMB) and higher mutation rates of significantly mutated genes (SMG) in GC. In addition, the CSRS-High subtype harbored more significantly amplified focal regions related to tumorigenesis (3q27.1, 12p12.1, 11q13.3, etc.) than the CSRS-Low tumors. Drug sensitivity analyses revealed the potential compounds for the treatment of gastric cancer with CSRS-High score, which were experimentally validated using GC cells. This study highlights that cuproptosis signature-based subtyping is significantly associated with different clinical features and molecular landscape of GC. Quantitative evaluation of the CSRS of individual tumors will strengthen our understanding of the occurrence and development of cuproptosis and the treatment progress of GC.

Identification of Novel PI3Kα Inhibitor Against Gastric Cancer: QSAR-, Molecular Docking-, and Molecular Dynamics Simulation-Based Analysis.

Gastriccancer (GC) is a malignant tumor with global incidence and death ranking fifth and fourth, respectively. GC patients nevertheless have a poor prognosis despite the effectiveness of more advanced chemotherapy and surgical treatment options. The second most frequently mutated gene in GC is PI3Kalpha, a confirmed oncogene that results in abnormal PI3K/AKT/mTOR signaling, causing enhanced translation, proliferation, and survival, and is mutated in 7-25% of GC patients. The protein PI3Kalpha was targeted in the present study by utilizing machine learning (ML), molecular docking, and simulation. A total of 9214 molecules from the DrugBank database were chosen for the first screening. A training set for 6770 compounds tested against PI3Kalpha was assessed to create a quantitative structure-activity relationship-based machine learning model using five different classification algorithms: random forest, random tree, J48 pruned tree, decision stump, and REPTree. Furthermore, consideration was given to the random forest classifier for screening based on its performance index (Kappa statistics, ROC, and MCC). Overall, 1539 of the 9214 drug bank compounds were predicted to be active. Thereafter, three pharmacological filters, Lipinski's rule, Ghose filter, and Veber rule, were applied to test the drug-like properties of the screened compounds. Twenty-six of 1593 compounds showed excellent drug-like properties and were further considered for molecular docking. Thereafter, two compounds were screened as hits because they possessed the molecular docked position with the lowest binding energy and an excellent bonding profile. The binding stability of the selected compounds was further assessed through molecular dynamics simulations for up to 100 ns. Furthermore, compound 1-(3-(2,4-dimethylthiazol-5-YL)-4-oxo-2,4-dihydroindeno[1,2-C]pyrazol-5-YL)-3-(4-methylpiperazin-1-YL) urea was selected as a potential hit in the final screening by analyzing a number of parameters, including the Rg, RMSD, RMSF, H bonding, and SASA profile. Therefore, we conclude that compound 1-(3-(2, 4-dimethylthiazol-5-YL)-4-oxo-2,4-dihydroindeno[1,2-C]pyrazol-5-YL)-3-(4-methylpiperazin-1-YL) urea has efficient inhibitory potential against PI3Kalpha protein and could be utilized for the development of effective drugs against GC.

Association of tumour mutation burden with prognosis and its clinical significance in stage III gastric cancer

Background: To explore the correlation between the tumour mutation burden (TMB) and prognosis and its clinical significance among patients with stage III gastric cancer (GC). Methods: Patients with stage III GC were divided into a high TMB and low TMB group in both a study cohort of 38 patients and the Cancer Genome Atlas (TCGA) cohort of 173 patients. In the study cohort, next-generation sequencing was used to detect mutated GC genes and obtain TMB data. In the TCGA cohort, gene set enrichment analysis was performed, and the relationship between TMB, prognosis and clinicopathologic factors was analysed. Western blot and quantitative real-time polymerase chain reaction were used to detect the expression levels of both proteins and genes. Cell viability was measured using methyl thiazolyl tetrazolium and transwell cell assays. Results: Patients in the high TMB group had better overall survival (OS) rates than patients in the low TMB group for both cohorts and TMB was associated with age, mutation signature 1 and mutation signature 17. The Cox regression analysis revealed that age, not TMB, was an independent prognosis factor. Furthermore, genes with high-frequency mutations were significantly enriched in the Notch and RTK-RAS signalling pathways. The activation of these pathways was lower in the high TMB compared with the low TMB group, and the proliferation and migration abilities of GC cells showed a similar pattern in both TMB groups. Conclusion: Patients in the high TMB group had better OS rates than patients in the low TMB group. Genes with high-frequency mutations were significantly enriched in the RTK-RAS and Notch pathways. Hence, TMB could serve as a prognosis biomarker with potential clinical significance.

Epigenetic modulation of cytokine expression in gastric cancer: influence on angiogenesis, metastasis and chemoresistance.

Cytokines are proteins that act in the immune response and inflammation and have been associated with the development of some types of cancer, such as gastric cancer (GC). GC is a malignant neoplasm that ranks fifth in incidence and third in cancer-related mortality worldwide, making it a major public health issue. Recent studies have focused on the role these cytokines may play in GC associated with angiogenesis, metastasis, and chemoresistance, which are key factors that can affect carcinogenesis and tumor progression, quality, and patient survival. These inflammatory mediators can be regulated by epigenetic modifications such as DNA methylation, histone protein modification, and non-coding RNA, which results in the silencing or overexpression of key genes in GC, presenting different targets of action, either direct or mediated by modifications in key genes of cytokine-related signaling pathways. This review seeks insight into the relationship between cytokine-associated epigenetic regulation and its potential effects on the different stages of development and chemoresistance in GC.

Homeobox Protein BarH-like 1 Promotes Gastric Cancer Progression by Activating Coiled-Coil Domain-Containing Protein 178.

Coiled-coil domain-containing protein 178 (CCDC178) has been revealed to exert metastasis-promoting properties in hepatocellular carcinoma, whereas its function in gastric cancer (GC) has not been fully understood. We evaluated its role in GC and the molecular mechanism. The differentially expressed genes in datasets related to GC metastasis were intersected with survival-related genes in GC, followed by prognostic significance prediction. Loss- and gain-of-function assays were conducted to examine the involvement of CCDC178, Homeobox protein BarH-like 1 (BARX1), and the extracellular signal-regulated kinase (ERK) pathway in GC cell malignant phenotype and the polarization of tumor-associated macrophages (TAM). The corresponding functions were verified in the in vivo animal experiment. High CCDC178 expression predicted a poor prognosis for GC patients, and CCDC178 correlated significantly with macrophage infiltration in GC tissues. CCDC178 activated the ERK pathway in GC. Silencing of CCDC178 reduced the colony formation, migratory and invasive potential of GC cells, and the M2-like polarization of TAM, which was reversed by TBHQ (an ERK activator). BARX1 bound to the promoter region of CCDC178, thus inducing its transcriptional level. Silencing of BARX1 suppressed the M2-type polarization of TAM in vitro and in vivo, and CCDC178 mitigated the repressing role of BARX1 knockdown. BARX1 activates the transcription of CCDC178 to induce the ERK pathway, thereby supporting macrophage recruitment and M2-like polarization in GC.

The macrophage-associated prognostic gene ANXA5 promotes immunotherapy resistance in gastric cancer through angiogenesis

Gastric cancer (GC) remains a predominant form of malignant tumor globally, necessitating innovative non-surgical therapeutic approaches. This investigation aimed to delineate the expression landscape of macrophage-associated genes in GC and to evaluate their prognostic significance and influence on immunotherapeutic responsiveness. Utilizing the CellMarker2.0 database, we identified 69 immune cell markers with prognostic relevance in GC, including 12 macrophage-specific genes. A Weighted Gene Co-Expression Network Analysis (WGCNA) isolated 3,181 genes correlated with these macrophage markers. The Cancer Genome Atlas (TCGA-STAD) dataset was employed as the training set, while data from the GSE62254 served as the validation cohort. 13 genes were shortlisted through LASSO-Cox regression to formulate a prognostic model. Multivariable Cox regression substantiated that the calculated risk score serves as an imperative independent predictor of overall survival (OS). Distinct macrophage infiltration profiles, pathway associations, treatment susceptibilities, and drug sensitivities were observed between high- and low-risk groups. The preliminary validation of ANXA5 in predicting the survival rates of GC patients at 1 year, 3 years, and 5 years, as well as its expression levels were higher and role in promoting tumor angiogenesis in GC through immunohistochemistry and angiogenesis experiments. In summary, macrophage-related genes were potentially a novel crosstalk mechanism between macrophages and endothelial cells in the tumor microenvironment, and the interplay between inflammation and angiogenesis might have also offered new therapeutic targets, providing a new avenue for personalized treatment interventions.

PIEZO2 expression is an independent biomarker prognostic for gastric cancer and represents a potential therapeutic target

Gastric cancer (GC) is one of the most prevalent malignant tumors of the gastrointestinal system in the globe. The effect of PIEZO2 on the immune function and pathological features of gastric cancer remains to be explored. The Online database of cancer genes and GSE54129 have been used to analyze the clinical characteristics of PIEZO2 expression. We looked at the relationship between PIEZO2 and the immune systems of GC patients. The TIDE algorithm was used to explore the value of PIEZO2 in immunotherapy. Investigated the enrichment of PIEZO2 gene ontology and associated signal pathways using Online gene databases. The results show that overexpression of PIEZO2 was identified as an independent risk factor for patients with GC who had poor overall survival. Individuals may have a better prognosis if they had poorly differentiated GC and increased PIEZO2 expression (P < 0.05). We demonstrated a strong correlation between PIEZO2 and immune cells. The majority of immune checkpoint and immunological-related genes were associated with PIEZO2 expression. And PIEZO2 might be used as an immunotherapy target. Finally, the differential PIEZO2 genes in GC were mostly implicated in the processes of inflammation, immunological response, and tumor metastasis, according to functional analysis. PIEZO2 has a negative correlation with cell stemness and mutation levels in patients with GC and a positive correlation with immune cell infiltration and gene expression in the tumor microenvironment. These findings point to PIEZO2 as a potential new immunotherapy target of GC.

Clinical Significance of Disulfidptosis-related Genes and Functional Analysis in Gastric Cancer.

Background: Worldwide, gastric cancer (GC) remains intractable due to its poor prognosis and high morbidity and mortality. Disulfidptosis is a novel kind of cell death mediated by abnormal accumulation of intracellular disulphides. The correlation between disulfidptosis and GC is still unknown. Therefore, it is necessary to elucidate the pathogenesis and mechanism of disulfidptosis and GC for clinical diagnosis and intervention. Methods: RNA-sequencing data from several public data portals and clinical samples were collected. We compared the expression levels of four key genes of disulfidptosis, including SLC7A11, SLC3A2, RPN1, and NCKAP1, in GC and selected prognostic genes to build a novel GC prognosis-related nomogram model. The biological functions and immune landscape of the identified prognostic genes were explored. Results: Overexpressed NCKAP1 and SLC7A11 were prognostic disulfidptosis-related genes in GC. We combined these genes and several clinicopathological factors to build a prognostic nomogram model for GC. Meanwhile, the ROC curves showed that NCKAP1 and SLC7A11 were promising biomarkers for GC screening. The biological and cellular functions were focused on actin activities, GTPase and immunoreaction. The tumour immune microenvironment and immune therapy targets were identified. Competing endogenous RNA network was built to explore the downstream regulatory mechanisms. Finally, the elevated NCKAP1 and SLC7A11 expression in GC was validated via qRT-PCR in a cell line and tissue line. Conclusion: In conclusion, NCKAP1 and SLC7A11 are promising prognostic and diagnostic biomarkers for GC that correlate with the activities of actin, energy metabolism of GTPase, immune infiltration and immunotherapy.

Gastric Cancer Immune Subtypes and Prognostic Modeling: Insights from Aging-Related Gene Analysis.

Gastric cancer (GC) is highly heterogeneous and influenced by aging-related factors. This study aimed to improve individualized prognostic assessment of GC by identifying aging-related genes and subtypes. Immune scores of GC samples from GEO and TCGA databases were calculated using ESTIMATE and scored as high immune (IS_high) and low immune (IS_low). ssGSEA was used to analyze immune cell infiltration. Univariate Cox regression was employed to identify prognosis-related genes. LASSO regression analysis was used to construct a prognostic model. GSVA enrichment analysis was applied to determine pathways. CCK-8, wound healing, and Transwell assays tested the proliferation, migration, and invasion of the GC cell line (AGS). Cell cycle and aging were examined using flow cytometry, β-galactosidase staining, and Western blotting. Two aging-related GC subtypes were identified. Subtype 2 was characterized as lower survival probability and higher risk, along with a more immune-responsive tumor microenvironment. Three genes (IGFBP5, BCL11B, and AKR1B1) screened from aging-related genes were used to establish a prognosis model. The AUC values of the model were greater than 0.669, exhibiting strong prognostic value. In vitro, IGFBP5 overexpression in AGS cells was found to decrease viability, migration, and invasion, alter the cell cycle, and increase aging biomarkers (SA-β-galactosidase, p53, and p21). This analysis uncovered the immune characteristics of two subtypes and aging-related prognosis genes in GC. The prognostic model established for three aging-related genes (IGFBP5, BCL11B, and AKR1B1) demonstrated good prognosis performance, providing a foundation for personalized treatment strategies aimed at GC.

Construction and validation of prognostic signatures related to mitochondria and macrophage polarization in gastric cancer.

Increasing evidence reveals the involvement of mitochondria and macrophage polarisation in tumourigenesis and progression. This study aimed to establish mitochondria and macrophage polarisation-associated molecular signatures to predict prognosis in gastric cancer (GC) by single-cell and transcriptional data. Initially, candidate genes associated with mitochondria and macrophage polarisation were identified by differential expression analysis and weighted gene co-expression network analysis. Subsequently, candidate genes were incorporated in univariateCox analysis and LASSO to acquire prognostic genes in GC, and risk model was created. Furthermore, independent prognostic indicators were screened by combining risk score with clinical characteristics, and a nomogram was created to forecast survival in GC patients. Further, in single-cell data analysis, cell clusters and cell subpopulations were yielded, followed by the completion of pseudo-time analysis. Furthermore, a more comprehensive immunological analysis was executed to uncover the relationship between GC and immunological characteristics. Ultimately, expression level of prognostic genes was validated through public datasets and qRT-PCR. A risk model including six prognostic genes (GPX3, GJA1, VCAN, RGS2, LOX, and CTHRC1) associated with mitochondria and macrophage polarisation was developed, which was efficient in forecasting the survival of GC patients. The GC patients were categorized into high-/low-risk subgroups in accordance with median risk score, with the high-risk subgroup having lower survival rates. Afterwards, a nomogram incorporating risk score and age was generated, and it had significant predictive value for predicting GC survival with higher predictive accuracy than risk model. Immunological analyses revealed showed higher levels of M2 macrophage infiltration in high-risk subgroup and the strongest positive correlation between risk score and M2 macrophages. Besides, further analyses demonstrated a better outcome for immunotherapy in low-risk patients. In single-cell and pseudo-time analyses, stromal cells were identified as key cells, and a relatively complete developmental trajectory existed for stromal C1 in three subclasses. Ultimately, expression analysis revealed that the expression trend of RGS2, GJA1, GPX3, and VCAN was consistent with the results of the TCGA-GC dataset. Our findings demonstrated that a novel prognostic model constructed in accordance with six prognostic genes might facilitate the improvement of personalised prognosis and treatment of GC patients.

Cross-talk of Three Molecular Subtypes of Telomere Maintenance Defines Clinical Characteristics and Tumor Microenvironment in Gastric Cancer.

Background: Telomere maintenance takes part in the regulation of gastric cancer (GC) pathogenesis and is essential for patients' clinical features. Though the correlation between a single telomere maintenance-related gene and GC has previously been published, comprehensive exploration and systematic analysis remain to be studied. Our study is aimed at determining telomere maintenance-related molecular subtypes and examining their role in GC. Methods: By analyzing the transcriptome data, we identified three telomere maintenance-associated clusters (TMCs) with heterogeneity in clinical features and tumor microenvironment (TME). Then, we screened five prognostic telomere maintenance-related genes and established corresponding TM scores. Additionally, the expression level and biological function of tubulin beta 6 class V (TUBB6) were validated in GC tissues and cells. Results: TMC1 was correlated with EMT and TGF-beta pathway and predicted low tumor mutation burden (TMB) as well as bad prognostic outcomes. TMC3 was associated with cell cycle and DNA repair. In terms of TMB and overall survival, TMC3 exhibited opposite results against TMC1. Significant heterogeneity was observed between TMCs. TUBB6 was upregulated and could promote GC proliferation, migration, and invasion. Conclusion: Altogether, combining bioinformatics and functional experiments, we identified three molecular subtypes based on telomere maintenance-associated genes in GC, which could bring new ideas and novel biomarkers to the clinic.