Adenocarcinoma Of Stomach Research Articles

Identification of lncRNA dual targeting PD-L1 and PD-L2 as a novel prognostic predictor for gastric cancer

BackgroundAlthough breakthroughs have been achieved in gastric cancer (GC) therapy with immune checkpoint inhibitors (ICIs) targeting programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1), the acquisition of high response rate remains a huge challenge for clinicians. It is imperative to identify novel biomarkers for predicting response to immunotherapy and explore alternative therapeutic strategy for GC.MethodsThe transcriptomic profiles and clinical information of GC patients from The Cancer Genome Atlas (TCGA)-stomach adenocarcinoma (STAD) database was used to screen differentially expressed lncRNAs between the tumor specimens and the paracancerous tissues. The TargetScan, miRDB and miRcode database were then utilized to construct competing endogenous RNA (ceRNA) networks and identify pivotal lncRNAs. An independent dataset from GEO (GSE70880) and 23 pairs of GC specimens of our cohort were subsequently performed for external validity. The relationship between clinical variables and gene expression were evaluated by Kruskal–wallis test and Wilcoxon signed-rank. The prognostic value of the candidate genes was assessed using Kaplan-Meier analysis and Cox regression models. CIBERSORT and Gene set enrichment analysis (GSEA) were used to determine immune cell infiltration. Gastric adenocarcinoma AGS cells and human embryonic kidney 293T (HEK293T) cells with knockdown of LINC01094 were generated by siRNA transfection, followed by detecting the alteration of the target miRNA and PD-L1/PD-L2 by RT-qPCR. Besides, the interaction between lncRNA and the miRNA–PD-L1/PD-L2 axis were verified by dual luciferase reporter assay.ResultsTwenty-two intersecting lncRNAs were identified to be PD-L1/PD-L2-related lncRNAs and LINC01094–miR-17-5p–PD-L1/PD-L2 was constructed as a potential ceRNA network. LINC01094 was increased in tumor specimens than adjacent normal samples and was positively associated with advanced tumor stages and EBV and MSI status. Furthermore, LINC01094 expression was an independent risk factor for poor overall survival (OS) in GC patients. CD8+ T cell exhaustion-related genes were enriched in high-LINC01094 tissues and high-PD-L2 group. A strong positive association of LINC01094 expression was established with M2 macrophages, IL-10+ TAM, as well as PD-L1 and PD-L2 levels, therefore a LINC01094–miR-17-5p–IL-10 network was proposed in macrophages. Using the exoRBase database, LINC01094 was assumed in blood exosomes of GC patients The results of knockdown experiments and luciferase reporter assays revealed that LINC01094 interacted with miR-17-5p and served as a miRNA sponge to regulate the expression of PD-L1 and PD-L2.ConclusionLINC01094 dually regulates the expression of PD-L1 and PD-L2 and shapes the immunosuppressive tumor microenvironment via sponging miR-17-5p. LINC01094 may serve as a potential prognostic predictor and therapeutic target in GC.

Synchronous primary gastric diffuse large B-cell lymphoma and multiple lung primary adenocarcinoma with pulmonary cryptococosis: a case report and literature review

BackgroundThe coexistence of non-Hodgkin’s lymphoma of the stomach and multiple primary lung adenocarcinomas with pulmonary cryptococcosis has rarely been reported.Case presentationWe herein present a 75-year-old man who was admitted to our hospital due to hematemesis. Gastroscopy and imaging revealed extensive stomach wall thickening and multiple lung lesions, including nodules and cavernous lesion. The patient was diagnosed with primary diffuse large B-cell lymphoma via gastroscopy and bilateral lung primary adenocarcinoma with cryptococcal infection via percutaneous CT-guided puncture biopsy. He subsequently underwent six cycles of R-CHOP regimen for gastric lymphoma, along with CT-guided radiofrequency ablation for the upper lobe of the right lung primary adenocarcinoma and radioactive particle implantation was performed on the lower lobe of the left lung primary adenocarcinoma, supplemented with antifungal therapy. After a definite diagnosis and systemic treatment, the patient was followed up for twenty-seven months with no tumor recurrence, progression or metastasis.ConclusionTo the best of our knowledge, the complex combination of multiple primary malignancies and pulmonary cryptococcal infection is extremely rare. The diagnosis is been confusing and challenging. CT-guided needle biopsy can help achieve pathological diagnosis, elucidate the type and stage of the tumor, and even change the clinical treatment strategy, which is necessary and beneficial.

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.

Efficacy and Safety of First-Line Palliative Chemotherapy with Fluorouracil Plus Leucovorin, Oxaliplatin, and Docetaxel (FLOT) in HER2-Negative Metastatic Gastric or Gastroesophageal Junction Adenocarcinoma: A Single-Institutional Real-World Experience from Eastern India

Background Fluorouracil plus leucovorin, oxaliplatin, and docetaxel (FLOT) is one of the preferred perioperative chemotherapy regimens in locally advanced resectable gastric cancer (GC). Till date, there are very few published data from India, regarding the outcomes of this relatively well-tolerated biweekly triplet regimen as first-line palliative chemotherapy in metastatic gastric or gastroesophageal junction (GEJ) adenocarcinoma. Materials and Methods In the present retrospective study, we evaluated the efficacy and safety of first-line FLOT regimen in Indian patients with HER2-negative metastatic adenocarcinoma of stomach or GEJ. The primary endpoint was overall survival (OS). Progression-free survival (PFS), overall response rate (ORR), and toxicity profile were taken as secondary endpoints. Results Between January 2021 and June 2024, 88 patients were treated with FLOT. The median age was 52 years (range, 23–68); 69.3% were males and 37.5% of the patients had ≥ 3 metastatic disease sites involvement at baseline. Dose reductions due to toxicity were required in 25% of the patients. The ORR was 68.2%; median PFS and OS were 6.3 months (95% confidence interval [CI]: 5.3–7.4) and 12.5 months (95% CI: 11.3–14.2), respectively. The most frequent grade 3 to 4 adverse events were diarrhea (15.9%), fatigue (13.6%), and neutropenia (12.5%). Younger patients (aged < 55 years) had much less ≥ grade 3 diarrhea (7.5%, n = 4), compared with patients aged ≥ 55 years (28.6%, n = 10). There was one toxicity-related death. Conclusion In the present study, biweekly FLOT regimen with primary prophylactic granulocyte colony-stimulating factor demonstrated encouraging efficacy with a favorable nongastrointestinal toxicity profile in Indian patients with HER2-negative metastatic gastric or GEJ adenocarcinoma. Clearly, this well-tolerated triplet regimen should be explored further through large prospective randomized trials in Asian patients.

Construction of store-operated calcium entry-related gene signature for predicting prognosis and indicates immune microenvironment infiltration in stomach adenocarcinomas

Gastric adenocarcinoma (STAD) is the most prevalent malignancy of the human digestive system and the fourth leading cause of cancer-related death. Calcium pools, especially Ca2+ entry (SOCE) for storage operations, play a crucial role in maintaining intracellular and extracellular calcium balance, influencing cell activity, and facilitating tumor progression. Nevertheless, the prognostic and immunological value of SOCE in STAD has not been systematically studied. The objective of this study was to develop a risk model for SOCE signature and to explore its correlation with clinical characteristics, prognosis, tumor microenvironment (TME), as well as response to immunotherapy, chemotherapy, and targeted drugs. We used the TCGA, GEO (GSE84437 and GSE159929), cBioPortal and TIMER databases to acquire mRNA expression data for STAD, along with patient clinical indicators, single-cell sequencing data, genomic variation information, and correlations of immune cell infiltration. An analysis of SOCE genes based on tumor vs. normal tissue comparisons, pan-cancer dimension, single-cell sequencing, DNA mutation, and copy number variation revealed that SOCE genes significantly impact the survival of STAD patients and are differentially involved in the immune response. SOCE co-expressed genes were identified by Pearson analysis, and subsequently protein-protein interaction (PPI) and gene function enrichment analysis indicated that coexpressed genes were associated with multicellular pathways. Based on TCGA and GSE84437 datasets, a multifactor Cox proportional hazard regression analysis was conducted to identify SOCE co-expressed genes associated with overall survival in STAD patients. Several mRNA prognostic genes, including PTPRJ, GPR146, LTBP3, FBLN1, EFEMP2, ADAMTS7 and LBH, were identified, which could be used as effective prognostic predictors for STAD patients. In both training and test datasets, receiver operating characteristic (ROC) curves were utilized to evaluate and illustrate the predictive capability of this characteristic in forecasting overall survival of STAD patients. The qPCR and human protein atlas (HPA) were employed to assess mRNA expression and protein levels. Furthermore, the ESTIMATE, TIMER, CIBERSORT, QUANTISEQ, MCPCOUNTER, xCell and EPIC algorithms were utilized to perform immune score and analyze immune cell infiltration. It effectively revealed the difference in prognosis and immune cell infiltration in TME between high-risk and low-risk groups based on the risk signature associated with SOCE. Notably, significant differences in tumor immune dysfunction and rejection (TIDE) scores between the two groups, suggesting that patients in the low-risk group may exhibit a more favorable response to ICIS treatment. The GDSC database and R packages for predictive analysis were utilized to analyze responses to chemotherapy and targeted drugs in high-risk and low-risk groups. In summary, the 7-gene signature associated with SOCE serves as a significant biomarker for evaluating the TME and predicting the prognosis of STAD patients. In addition, it may provide valuable insights for developing effective immunotherapy and chemotherapy regiments for patients with STAD.

Claudin-9 (CLDN9) promotes gastric cancer progression by enhancing the glycolysis pathway and facilitating PD-L1 lactylation to suppress CD8+ T cell anti-tumor immunity

BackgroundGastric cancer (GC) is a common malignancy characterized by the absence of reliable prognostic indicators and effective therapeutic targets. Claudin-9 (CLDN9) has been demonstrated to be upregulated in various cancers. However, its prognostic value, biological function, and regulatory mechanisms in GC remain unclear. Therefore, this study aimed to elucidate the role of CLDN9 in GC progression and its underlying mechanisms. MethodsWe utilized consensus cluster, random survival forest, and multivariate Cox regression analyses to identify CLDN9 in GC. Subsequently, we evaluated the mRNA and protein levels of CLDN9 in GC using quantitative real-time polymerase chain reaction (PCR) (qRT-PCR), western blotting (WB), and immunohistochemistry (IHC). Furthermore, the role of CLDN9 in GC progression was investigated using a series of functional in vivo and in vitro experiments. Finally, we elucidated the molecular mechanisms of CLDN9 using bioinformatics, molecular biology, animal models, and patient tissue specimens. ResultsTwo GC subtypes with survival and functional differences were identified based on glycolytic metabolic genes in the Cancer Genome Atlas (TCGA)- Stomach adenocarcinoma (STAD) dataset. A prognostic risk score was calculated using seven genes to assess the overall survival (OS) in GC. Using random survival forest and multivariate Cox analyses, we identified CLDN9 as the key gene linked to the glycolytic subtype and prognosis of GC. CLDN9 expression was significantly upregulated in patients with GC as well as in GC cells. CLDN9 knockdown inhibited tumor proliferation, invasion, and metastasis both in vivo and in vitro. Mechanistically, CLDN9 was found to regulate lactate dehydrogenase A (LDHA) expression and promote glycolytic metabolism by activating the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/hypoxia-inducible factor 1-alpha (HIF1α) signaling pathway. Additionally, lactate, a glycolytic metabolite, enhanced programmed cell death ligand 1 (PD-L1) lactylation and stability, which suppressed anti-tumor immunity in CD8+ T cells, thereby contributing to GC progression. ConclusionsCLDN9 expression is associated with GC development and progression. Mechanistically, CLDN9 enhances the glycolysis pathway and facilitates PD-L1 lactylation through the PI3K/AKT/HIF1α signaling pathway, thereby suppressing anti-tumor immunity in CD8+ T cells. CLDN9 has the potential to serve as a novel prognostic marker and therapeutic target for GC.

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.

Investigating MATN3 and ASPN as novel drivers of gastric cancer progression via EMT pathways

Abstract Gastric cancer (GC) is a leading cause of cancer-related deaths globally, necessitating the identification of novel therapeutic targets. This study investigates the roles of MATN3 and ASPN in GC progression via the epithelial-mesenchymal transition (EMT) pathway. Analysis of the Cancer Genome Atlas—Stomach Adenocarcinoma (TCGA-STAD) dataset revealed that both MATN3 and ASPN are significantly upregulated in GC tissues and correlate with poor patient survival. Protein–protein interaction and co-expression analyses confirmed a direct interaction between MATN3 and ASPN, suggesting their synergistic role in EMT activation. Functional assays demonstrated that MATN3 promotes GC cell proliferation, migration, and invasion, while its knockdown inhibits these malignant behaviors and induces apoptosis. ASPN overexpression further amplified these oncogenic effects. In vivo, studies in a mouse model corroborated that co-overexpression of MATN3 and ASPN enhances tumor growth and metastasis. These findings highlight the MATN3-ASPN axis as a potential therapeutic target in GC, offering new insights into the molecular mechanisms driving GC progression.

Machine learning-based identification of an immunotherapy-related signature to enhance outcomes and immunotherapy responses in melanoma.

Immunotherapy has revolutionized skin cutaneous melanoma treatment, but response variability due to tumor heterogeneity necessitates robust biomarkers for predicting immunotherapy response. We used weighted gene co-expression network analysis (WGCNA), consensus clustering, and 10 machine learning algorithms to develop the immunotherapy-related gene model (ITRGM) signature. Multi-omics analyses included bulk and single-cell RNA sequencing of melanoma patients, mouse bulk RNA sequencing, and pathology sections of melanoma patients. We identified 66 consensus immunotherapy prognostic genes (CITPGs) using WGCNA and differentially expressed genes (DEGs) from two melanoma cohorts. The CITPG-high group showed better prognosis and enriched immune activities. DEGs between CITPG-high and CITPG-low groups in the TCGA-SKCM cohort were analyzed in three additional melanoma cohorts using univariate Cox regression, resulting in 44 consensus genes. Using 101 machine learning algorithm combinations, we constructed the ITRGM signature based on seven model genes. The ITRGM outperformed 37 published signatures in predicting immunotherapy prognosis across the training cohort, three testing cohorts, and a meta-cohort. It effectively stratified patients into high-risk or low-risk groups for immunotherapy response. The low-risk group, with high levels of model genes, correlated with increased immune characteristics such as tumor mutation burden and immune cell infiltration, indicating immune-hot tumors with a better prognosis. The ITRGM's relationship with the tumor immune microenvironment was further validated in our experiments using pathology sections with GBP5, an important model gene, and CD8 IHC analysis. The ITRGM also predicted better immunotherapy response in eight cohorts, including urothelial carcinoma and stomach adenocarcinoma, indicating broad applicability. The ITRGM signature is a stable and robust predictor for stratifying melanoma patients into 'immune-hot' and 'immune-cold' tumors, enhancing prognosis and response to immunotherapy.

Assessment of Helicobacter pylori Infection and Associated Risk Factors in Asymptomatic Patients Attending Muhoza Health Center

Background: H. pylori, is a bacterial pathogen that colonizes the gastric mucous lining and the epithelial tissue of the stomach. Helicobacter pylori strains infections can lead to several diseases such as duodenal ulcers, gastric ulcers, adenocarcinoma of the distal stomach, mucosa-associated lymphoid tissue (MALT) lymphoma, diabetes mellitus, cardiovascular disease and autoimmune diseases. The objectives of this study were to assess the prevalence of H. pylori infection and risk factors associated with H. pylori in asymptomatic participants attending Muhoza health center Methodology: A cross-sectional study was conducted from 13th September to 13th October. Stool samples from 60 eligible participants were collected in sterile containers and they were immunoserologicaly analysed. Rapid tests were used to detect H. pylori antigens. A liquid in the testing kit was mixed with a small portion of the stool. The mixture was poured to the sample hole on the rapid test which displayed results. Data regarding risk factors were collected using questionnaires and were analyzed statistically using SPSS 20. Results: The prevalence of H. pylori infection was 37%. Females were more affected than males, with 25% and 12% respectively. Age, education, source of water and household population were significantly associated with Helicobacter pylori with p-values < 0.05. The study was limited since it was one health center based, hence not having large representative population. Conclusion: Education of the population about prevention of the infection, supply clean, treated water for home usage and drinking, are recommended to the local government authorities in Musanze. Screening for H. pylori infection, good adherence on antibiotics against H. pylori, hand washing, and proper household settings to reduce crowding issue are recommended. Further researches are recommended for more conclusive results. Keywords: H. pylori infection, risk factors, stomach, asymptomatic.

Bioinformatic Analysis of IKK Complex Genes Expression in Selected Gastrointestinal Cancers.

Gastrointestinal cancers account for over a quarter of all cancer cases and are associated with poor prognosis and high mortality rates. The IKK complex (the canonical I kappa B kinase), comprising the CHUK, IKBKB, and IKBKG genes, plays a crucial role in activating the NF-kB signaling pathway. This study aimed to analyze publicly available bioinformatics data to elucidate the oncogenic role of IKK genes in selected gastrointestinal cancers. Our findings reveal that IKBKB and IKBKG are significantly upregulated in all examined cancers, while CHUK is upregulated in esophageal carcinoma and stomach adenocarcinoma. Additionally, the expression of IKK genes varies with histological grade and nodal metastases. For instance, in stomach adenocarcinoma, CHUK and IKBKB are upregulated in higher histological grades and greater lymph node infiltration. Lower expression levels of CHUK, IKBKB, and IKBKG in stomach adenocarcinoma and IKBKB in esophageal squamous cell carcinoma correlate with shorter overall survival. Conversely, in esophageal adenocarcinoma, reduced IKBKG expression is linked to longer overall survival, while higher IKBKB expression in colon adenocarcinoma is associated with longer overall survival. Given the significant role of IKK genes in the development and progression of selected gastrointestinal cancers, they hold potential as prognostic markers and therapeutic targets, offering valuable insights for clinical practice.

System analysis based on T-cell exhaustion-related genes identifies PTPRT as a promising diagnostic and prognostic biomarker for gastric cancer

Multiple investigations have demonstrated the crucial involvement of T-cell exhaustion (TEX) in anti-tumor immune response and their strong correlation with prognosis. This study aimed at creating a strong signature using TEX for gastric cancer through bioinformatics analysis and experimental validation. We utilized data from The Cancer Genome Atlas (TCGA) databases to retrieve RNA-seq data from patients with stomach adenocarcinoma (STAD). Genes related to TEX were discovered using gene set variance analysis (GSVA) and weighted gene correlation network analysis (WGCNA). Subsequently, prognostic signature based on TEX was developed using LASSO-Cox analysis. Relationship between key genes and immune cells were examined. Finally, biological function of a key TEX-related gene PTPRT in gastric cancer was verified by in vivo experiment. A total of 29 TEX-related biomarkers were screened by WGCNA and random forest. Among them, five core signatures (PTPRT, CAV2, PPIH, PRDM2, and FGF1), further identified by LASSO-Cox, were considered as strong predictors of prognosis for gastric cancer and associated with immune infiltration. PTPRT gene had the largest number of SNPs, with the most mutation types. In vivo experiments revealed that PTPRT overexpression significantly inhibited tumor malignant progression and accelerated apoptosis through stimulating the secretion of killer cytokines such as TNF-α and IFN-γ. In addition, flow cytometry revealed that PTPRT overexpression alleviated TEX by increasing the abundance of CD8+ T cells, with inhibition of cell surface PD-1 and Tim-3. The predictive prognostic value of TEX gene expression levels was evaluated in patients with gastric cancer, providing a new perspective for precision immuno-oncology studies.

Deciphering the multidimensional impact of IGFBP1 expression on cancer prognosis, genetic alterations, and cellular functionality: A comprehensive Pan-cancer analysis

ObjectivesIGF-binding protein 1 (IGFBP1) is a key regulator of insulin-like growth factors, impacting biological processes, including cancer progression and prognosis. Materials and methodsThis study investigates genetic alterations affecting IGFBP1 expression in tumors using data from The Cancer Genome Atlas (TCGA) PanCancer Atlas via cBioPortal. We analyzed samples from 32 cancer types for mutation sites, including deep deletions, amplifications, and mutations. RNA-seq data were normalized using log2(value + 1). Statistical analyses, including survival outcomes, were conducted using R packages like ggplot2, stats, and car. Kaplan-Meier survival curves and log-rank tests assessed overall survival (OS) and progression-free survival (PFS). Univariate Cox regression was used to develop nomogram models for OS. Functional consequences of IGFBP1 mutations were explored through protein structure, stability, and IGF interaction analyses. Protein-protein interaction networks and functional enrichment were analyzed using GEPIA2, STRING, and Cytoscape. Gene Ontology (GO), KEGG, and Gene Set Enrichment Analysis (GSEA) provided insights into affected biological pathways. ResultsPan-cancer analysis revealed diverse expression patterns, including significant upregulation in cutaneous melanoma (SKCM) and downregulation in lung adenocarcinoma (LUAD) and stomach adenocarcinoma (STAD). Specifically, elevated IGFBP1 expression in SKCM patients led to a 25 % improvement in 5-year survival. In contrast, higher IGFBP1 levels in LUAD and OV patients resulted in a 30 % and 20 % decrease in survival, respectively. Elevated IGFBP1 levels are significantly linked to advanced tumor stage and grade in OV and LUAD, affecting prognostic outcomes. Nomogram models for OV, SKCM, LUAD, and STAD showed IGFBP1's predictive strength with AUC values ranging from 0.70 to 0.85, indicating its diagnostic potential. Genetic analyses revealed mutations in IGFBP1 in 12 % of STAD cases and 10 % of UCEC cases, indicating significant genetic variation. Immune analysis showed that high IGFBP1 expression significantly influenced immune cell infiltration, particularly macrophages and CD8+ T cells, thereby affecting survival in LUAD and OV. Functional enrichment and gene set enrichment analysis identified IGFBP1 involvement in crucial pathways, such as cell cycle regulation, immune response, and PD-1 signaling, highlighting its biological impact. Additionally, IGFBP1 expression delineates distinct molecular and immune subtypes, correlating with specific cancer behaviors and immune patterns. ConclusionsThese findings highlight IGFBP1's potential as a biomarker and therapeutic target, particularly for immunoregulation and cancer subtype stratification.

A novel prognostic model based on telomere-related lncRNAs in gastric cancer.

Telomeres are specialized structures at the ends of chromosomes that are important for their protection. Over time, long non-coding RNAs (lncRNAs) have gradually come into the spotlight as essential biomarkers of proliferation, migration, and invasion of human malignant tumors. Nevertheless, the impact of telomere-related lncRNAs (TRLs) in gastric cancer is currently unknown. In the present study, we screen the TRLs and identify a prognostic TRLs signature in gastric cancer. First, telomere-related genes (TRGs) were retrieved from the website, and RNA sequencing (RNA-seq) data and clinical data of stomach adenocarcinoma (STAD) patients were gathered from The Cancer Genome Atlas (TCGA) database. Gastric cancer patients' lncRNAs and overall survival (OS) were found to be related using univariate Cox regression analysis. Next, least absolute shrinkage and selection operator (LASSO) regression analysis and multifactorial Cox regression analysis were used to further screen telomere-related differentially expressed lncRNAs (TRDELs), and finally six lncRNAs were obtained, including LINC01537, CFAP61-AS1, DIRC1, RABGAP1L-IT1, DBH-AS1, and REPIN1-AS1. According to these six TRDELs, a prognostic model for gastric cancer was constructed. The samples were divided into the training group and the testing group at random, and the reliability of prognostic model was validated in both groups and overall samples. In addition, we performed Kaplan-Meier (K-M) survival curve analysis, independent prognostic analysis, and functional enrichment analysis to validate the predictive value and independence of the model, as well as immune cell correlation analysis, clustering analysis, and principal component analysis (PCA) to further explore the relationship between this model and the tumor cells. Finally, we performed the drug sensitivity analysis to identify a few small molecules that may have a therapeutic effect on gastric cancer. Finally, we constructed a prognostic model for gastric cancer consisting of six TRDELs. According to the K-M curve, the prognosis of the low-risk group was noticeably superior than that of the high-risk group. Multivariate Cox regression analysis suggested that risk score was an independent prognostic element. Receiver operating characteristic (ROC) curves, nomogram, and calibration curve indicated that the prognostic model had good predictive ability. Functional enrichment analysis demonstrated major pathways with high- and low-risk groups. Next, both tumor microenvironment (TME) and immune correlation analysis showed discrepancy in the high- and low-risk groups. Through drug sensitivity analysis, we screened four small molecules that might be beneficial for gastric cancer treatment. A prognostic model consisting of these six TRDELs was capable to predict the prognosis of gastric cancer patients.

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

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. 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). 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. 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.

Potential molecular metabolic mechanisms underlying the effects of cimifugin in gastric cancer through single-cell and bulk RNA sequencing combined with network pharmacology.

Gastric cancer (GC) is a leading cause of cancer-related mortality worldwide, posing a significant clinical challenge due to its complex tumor microenvironment (TME) and metabolic heterogeneity. Despite continuous improvements in treatment strategies including surgery, chemotherapy, and targeted therapies, the metabolic reprogramming in GC continues to impede treatment efficacy, highlighting an urgent need for the development of novel therapeutic strategies. This persistent issue underscores the urgent need for novel therapeutic approaches that can effectively address the diverse and dynamic characteristics of GC. Cimifugin, a traditional Chinese medicine (TCM), has garnered attention for its potential role in alleviating inflammation, neurological disorders, pain, and metabolic disorders. Its multi-targeting properties and minimal side effects suggest a broad potential for cancer management, which is currently being explored. This study aims to delineate the molecular mechanisms that cimifugin may impact within the TME and metabolic pathways of GC, with the expectation of contributing to a deeper understanding of GC and the development of innovative treatment strategies. We identified the GC-related TME cell types and metabolic profiles and pathways by using relevant data from the single-cell RNA sequencing (scRNA-seq) database GSE134520 and the stomach adenocarcinoma (STAD) data set from The Cancer Genome Atlas (TCGA). We also assessed the effects of cimifugin on MKN28 cell proliferation, invasion, and migration. By using six public platforms, we comprehensively predicted the potential biological targets of cimifugin. Clinical prognosis and immunohistochemistry (IHC), molecular docking, and dynamics simulations were used to confirm the clinical relevance and stability of the aforementioned targets. Cimifugin inhibited MKN28 cell proliferation, migration, and invasion. Cimifugin may potentially act on various metabolic pathways in GC, including folate biosynthesis, xenobiotic metabolism via cytochrome P450 (CYP), glutathione metabolism, steroid hormone biosynthesis, and tryptophan metabolism. Cimifugin was noted to stably bind to three significant core targets associated with metabolic reprogramming in GC: AKR1C2, MAOB, and PDE2A; all three targets were strongly expressed in endocrince cells, pit mucous cells (PMCs), and common myeloid progenitors (CMPs). We verified the pharmacological effects of cimifugin on GC cell proliferation, invasion, and migration. AKR1C2, MAOB, and PDE2A were identified as the key targets of cimifugin in GC-related metabolic reprogramming and pathogenesis. Our research provides preliminary insights into the potential therapeutic effects of cimifugin, which could be considered for future exploration in the context of GC treatment.

The immunological landscape and silico analysis of key paraptosis regulator LPAR1 in gastric cancer patients

This study aims to identify key regulators of paraptosis in gastric cancer (GC) and explore their potential in guiding therapeutic strategies, especially in stomach adenocarcinoma (STAD). Genes associated with paraptosis were identified from the references and subjected to Cox regression analysis in the TCGA-STAD cohort. Using machine learning models, LPAR1 consistently ranked highest in feature importance. Multiple sequencing data showed that LPAR1 was significantly overexpressed in cancer-associated fibroblasts (CAFs). LPAR1 expression was significantly higher in normal tissues, and ROC analysis demonstrated its discriminative ability. Copy number alterations and microsatellite instability were significantly associated with LPAR1 expression. High LPAR1 expression correlated with advanced tumor grades and specific cancer immune subtypes, and multivariate analysis confirmed LPAR1 as an independent predictor of poor prognosis. LPAR1 expression was associated with different immune response metrics, including immune effector activation and upregulated chemokine secretion. High LPAR1 expression also correlated with increased sensitivity to compounds, such as BET bromodomain inhibitors I-BET151 and RITA, suggesting LPAR1 as a biomarker for predicting drug activity. FOXP2 showed a strong positive correlation with LPAR1 transcriptional regulation, while increased methylation of LPAR1 promoter regions was negatively correlated with gene expression. Knockdown of LPAR1 affected cell growth in most tumor cell lines, and in vitro experiments demonstrated that LPAR1 influenced extracellular matrix (ECM) contraction and cell viability in the paraptosis of CAFs. These findings suggest that LPAR1 is a critical regulator of paraptosis in GC and a potential biomarker for drug sensitivity and immunotherapy response. This underscores the role of CAFs in mediating tumorigenic effects and suggests that targeting LPAR1 could be a promising strategy for precision medicine in GC.

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

BackgroundStomach 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. MethodsThe 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. ResultsA 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. ABCA1 in the RiskScore model significantly affected the migration and invasion of tumor cells. ConclusionThe 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.

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. 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. 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. 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.

Elucidating the pan-oncologic landscape of S100A9: prognostic and therapeutic corollaries from an integrative bioinformatics and Mendelian randomization analysis

The calcium-binding protein S100A9 has emerged as a pivotal biomolecular actor in oncology, implicated in numerous malignancies. This comprehensive bioinformatics study transcends traditional boundaries, investigating the prognostic and therapeutic potential of S100A9 across diverse neoplastic entities. Leveraging a wide array of bioinformatics tools and publicly available cancer genomics databases, such as TCGA, we systematically examined the S100A9 gene. Our approach included differential expression analysis, mutational burden assessment, protein interaction networks, and survival analysis. This robust computational framework provided a high-resolution view of S100A9’s role in cancer biology. The study meticulously explored S100A9’s oncogenic facets, incorporating comprehensive analyses of its relationship with prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), DNA methylation, and immune cell infiltration across various tumor types. This study presents a panoramic view of S100A9 expression across a spectrum of human cancers, revealing a heterogeneous expression landscape. Elevated S100A9 expression was detected in malignancies such as BLCA (Bladder Urothelial Carcinoma), CESC (Cervical squamous cell carcinoma and endocervical adenocarcinoma), COAD (Colon adenocarcinoma), ESCA (Esophageal carcinoma), and GBM (Glioblastoma multiforme), while reduced expression was noted in BRCA (Breast invasive carcinoma), HNSC (Head and Neck squamous cell carcinoma), and KICH (Kidney Chromophobe). This disparate expression pattern suggests that S100A9’s role in cancer biology is multifaceted and context-dependent. Prognostically, S100A9 expression correlates variably with patient outcomes across different cancer types. Furthermore, its expression is intricately associated with TMB and MSI in nine cancer types. Detailed examination of six selected tumors—BRCA, CESC, KIRC (Kidney renal clear cell carcinoma), LUSC (Lung squamous cell carcinoma), SKCM (Skin Cutaneous Melanoma); STAD (Stomach adenocarcinoma)—revealed a negative correlation of S100A9 expression with the infiltration of most immune cells, but a positive correlation with neutrophils, M1 macrophages, and activated NK cells, highlighting the complex interplay between S100A9 and the tumor immune environment. This bioinformatics synthesis posits S100A9 as a significant player in cancer progression, offering valuable prognostic insights. The data underscore the utility of S100A9 as a prognostic biomarker and its potential as a therapeutic target. The therapeutic implications are profound, suggesting that modulation of S100A9 activity could significantly impact cancer management strategies.