Biomarkers of gastric cancer: Current topics and future perspective

The current landscape of gastric cancer and gastroesophageal junction cancer diagnosis and treatment in China: a comprehensive nationwide cohort analysis

BACKGROUND

Gastric cancer is the fifth most common cancer globally and is associated with significant morbidity and mortality. Despite its alarming prevalence, limited comparative evidence exists on its treatment efficacy and prognosis across diverse China populations.

METHODS

To address this, our study used a large-scale dataset from the National Cancer Information Database, including data from 220,304 patients from 53 leading hospitals across 27 provinces in China.

RESULTS

From 2017 to 2023, early-stage (Stages I-II) gastric cancer diagnoses increased to 35.63% of all cancer cases. Our study evaluated the neoadjuvant treatment strategies, adjuvant post-operative therapy, first- and second-line management for progressive stages, alongside current gastric cancer treatment guidelines in China. Notably, immunotherapy accounted for 16.17% and 23.28% of first- and second-line treatments for late-stage gastric cancers, and 14.56% and 5.00% for neoadjuvant and adjuvant therapies, respectively. Analysis of survival rates revealed that the 1-, 2-, 3-, 4-, and 5-year survival rates were 74.07%, 54.89%, 44.21%, 37.97%, and 33.53%, respectively. The 5-year survival rates across stages I-IV were 85.07%, 49.34%, 35.56%, and 13.15%, respectively.

CONCLUSIONS

These findings offer critical insights into the current state of gastric cancer treatment in China and can inform future initiatives to improve therapeutic outcomes for patients with gastric cancer.

The combination of CA125, CA199, CEA, and AFP is an effective diagnostic biomarker for gastric cancer in elderly individuals

BACKGROUND

Serum tumour markers (TMs) such as alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA), carbohydrate antigen 199 (CA199) and CA125 have been established as prognostic indicators for gastric cancer (GC); however, the diagnostic value of these markers for GC in older adults has yet to be examined. Therefore, this study aimed to explore the diagnostic and prognostic significance of AFP, CEA, CA199 and CA125 for GC in elderly individuals.

METHODS

A total of 188 patients who visited The Sixth Affiliated Hospital, School of Medicine, South China University of Technology, from May 2021 to March 2024 were selected for this study. TMs, namely, CA199, CA125, CEA, and AFP, were examined in all patients. Comparisons of these TMs were conducted among the three groups, and TM levels were compared in patients with GC at various TNM stages. The diagnostic value of these TMs for GC was evaluated by calculating the area under the curve (AUC).

RESULTS

We selected 89 patients diagnosed with GC: 52 patients with benign gastric diseases and 47 healthy individuals for our study. The positivity rates of AFP, CA125, CEA and CA199 were significantly greater in the GC group (31.46%, 31.46%, 43.82% and 23.60%, respectively) than in the benign gastric disease group and healthy control group. The diagnostic sensitivities of CEA, CA125, CA199 and AFP for GC were 31.46%, 29.21%, 44.90% and 24.72%, respectively. The combination of these markers yielded a sensitivity of 65.17%, which was significantly greater than the sensitivity of each marker alone (P < 0.05). Additionally, patients with stage I-II disease had significantly lower serum levels of CEA, CA199, CA125, and AFP than did those with stage III-IV disease.

CONCLUSIONS

The levels of serum TMs, including CA12-5, CEA, CA199 and AFP, are elevated in elderly individuals with GC, indicating a higher TNM stage. The combination of CEA, CA12-5, CA199 and AFP has enhanced diagnostic value for GC, thereby offering significant clinical guidance. However, this study is limited by its retrospective design and lack of external validation, which should be addressed in future prospective trials.

Methylated Reprimo Cell-Free DNA as a Non-Invasive Biomarker for Gastric Cancer

Restrictions resulting from the COVID-19 pandemic abruptly reversed the slow decline of the diagnosis and mortality rates of gastric cancer (GC). This scenario highlights the importance of developing cost-effective methods for mass screening and evaluation of treatment response. In this study, we evaluated a non-invasive method based on the circulating methylated cell-free DNA (cfDNA) of Reprimo (RPRM), a tumor suppressor gene associated with the development of GC. Methylated RPRM cfDNA was analyzed in three de-identified cohorts: Cohort 1 comprised 81 participants with GC and 137 healthy donors (HDs); Cohort 2 comprised 27 participants with GC undergoing gastrectomy and/or chemotherapy analyzed at the beginning and after three months of treatment; and Cohort 3 comprised 1105 population-based participants in a secondary prevention program who underwent esophagogastroduodenal (EGD) endoscopy. This cohort includes 180 normal participants, 845 participants with premalignant conditions (692 with chronic atrophic gastritis [AG] and 153 with gastric intestinal metaplasia/low-grade dysplasia [GIM/LGD]), 21 with high-grade dysplasia/early GC [HGD/eGC], and 59 with advanced GC [aGC]). A nested case-control substudy was performed using a combination of methylated RPRM cfDNA and pepsinogens (PG)-I/II ratio. The dense CpG island of the promoter region of the RPRM gene was bisulfite sequenced and analyzed to develop a fluorescence-based real-time PCR assay (MethyLight). This assay allows the determination of the absolute number of copies of methylated RPRM cfDNA. A targeted sequence of PCR amplicon products confirmed the gastric origin of the plasma-isolated samples. In Cohort 1, the mean value of GCs (32,240.00 copies/mL) was higher than that of the HD controls (139.00 copies/mL) (p < 0.0001). After dividing this cohort into training-validation subcohorts, we identified an area under the curve of 0.764 (95% confidence interval (CI) = 0.683-0.845) in the training group. This resulted in a cut-off value of 87.37 copies/mL (sensitivity 70.0% and specificity 80.2%). The validation subcohort predicted a sensitivity of 66.67% and a specificity of 83.33%. In Cohort 2 (monitoring treatment response), RPRM levels significantly decreased in responders (p = 0.0042) compared to non-responders. In Cohort 3 (population-based participants), 18.9% %, 24.1%, 30.7%, 47.0%, and 71.2% of normal, AG, GIM/LGD, HGD/eGC, and aGC participants tested positive for methylated RPRM cfDNA, respectively. Overall sensitivity and specificity in distinguishing normal/premalignant conditions vs. GC were 65.0% (95% CI 53.52% to 75.33%) and 75.9% (95% CI 73.16% to 78.49%), respectively, with an accuracy of 75.11% (95% CI 72.45% to 77.64%). Logistic regression analyses revealed an OR of 1.85 (95% CI 1.11-3.07, p = 0.02) and an odds ratio (OR) of 3.9 (95% CI 1.53-9.93, p = 0.004) for the risk of developing GIM/LGD and HGD/eGC, respectively. The combined methylated RPRM cfDNA and PG-I/II ratio reached a sensitivity of 78.9% (95% CI 54.43% to 93.95%) and specificity of 63.04% (95% CI 52.34% to 72.88%) for detecting HGD/eGC vs. three to six age- and sex-matched participants with premalignant conditions. Our results demonstrate that methylated RPRM cfDNA should be considered a direct biomarker for the non-invasive detection of GC and a predictive biomarker for treatment response.

Advances and challenges in gastric cancer testing: the role of biomarkers

Advances in the identification of molecular biomarkers and the development of targeted therapies have enhanced the prognosis of patients with advanced gastric cancer. Several established biomarkers have been widely integrated into routine clinical diagnostics of gastric cancer to guide personalized treatment. Human epidermal growth factor receptor 2 (HER2) was the first molecular biomarker to be used in gastric cancer with trastuzumab being the first approved targeted therapy for HER2-positive gastric cancer. Programmed death-ligand 1 positivity and microsatellite instability can guide the use of immunotherapies, such as pembrolizumab and nivolumab. More recently, zolbetuximab has been approved for patients with claudin 18.2-positive diseases in some countries. More targeted therapies, including savolitinib for MET-positive patients, are currently under clinical investigation. However, the clinical application of these diagnostic approaches could be hampered by many existing challenges, including invasive and costly sampling methods, variability in immunohistochemistry interpretation, high costs and long turnaround times for next-generation sequencing, the absence of standardized and clinically validated diagnostic cut-off values for some biomarkers, and tumor heterogeneity. Novel testing and analysis techniques, such as artificial intelligence-assisted image analysis and multiplex immunohistochemistry, and emerging therapeutic strategies, including combination therapies that integrate immune checkpoint inhibitors with targeted therapies, offer potential solutions to some of these challenges. This article reviews recent progress in gastric cancer testing, outlines current challenges, and explores future directions for biomarker testing and targeted therapy for gastric cancer.

Helicobacter pylori-related serum indicators: Cutting-edge advances to enhance the efficacy of gastric cancer screening

Helicobacter pylori (H. pylori) infection induces pathological changes via chronic inflammation and virulence factors, thereby increasing the risk of gastric cancer development. Compared with invasive examination methods, H. pylori-related serum indicators are cost-effective and valuable for the early detection of gastric cancer (GC); however, large-scale clinical validation and sufficient understanding of the specific molecular mechanisms involved are lacking. Therefore, a comprehensive review and analysis of recent advances in this field is necessary. In this review, we systematically analyze the relationship between H. pylori and GC and discuss the application of new molecular biomarkers in GC screening. We also summarize the screening potential and application of anti-H. pylori immunoglobulin G and virulence factor-related serum antibodies for identifying GC risk. These indicators provide early warning of infection and enhance screening accuracy. Additionally, we discuss the potential combination of multiple screening indicators for the comprehensive analysis and development of emerging testing methods to improve the accuracy and efficiency of GC screening. Although this review may lack sufficient evidence due to limitations in existing studies, including small sample sizes, regional variations, and inconsistent testing methods, it contributes to advancing personalized precision medicine in high-risk populations and developing GC screening strategies.

m6A transferase KIAA1429 mediates the upregulation of LncRNA LINC00968 promoting the progression of gastric cancer cells

BACKGROUND

The screening and monitoring of gastric cancer is still a clinical challenge. Both N6-methyladenosine (m6A) and lncRNAs have been evidenced as critical regulators of gastric cancer, but their interaction and potential in modulating tumor progression remain unclear. This study aimed to evaluate the function of lncRNA LINC00968 in gastric cancer biological processes, and we discovered the role of KIAA1429, a typical m6A eraser, in mediating LINC00968 function.

MATERIALS AND METHODS

The expression of LINC00968 was assessed using PCR and regulated by cell transfection. Cellular processes were evaluated by CCK8 and Transwell assays. The m6A modification and the interaction of LINC00968 with KIAA1429 were identified with Methylated RNA immunoprecipitation-qPCR. The regulatory effect of LINC00968 on miR-3202 and VIRMA was estimated by luciferase reporter assay.

RESULTS

Significantly increased LINC00968 was observed in gastric cancer cells. Silencing LINC00968 suppressed gastric cancer cell growth and motility. m6A-modified sites were predicted in LINC00968 and overexpressing KIAA1429 enhanced the enrichment and stability of LINC00968 in gastric cancer and reversed the knockdown of LINC00968. The overexpression of KIAA1429 could attenuate the inhibitory effect of LINC00968 knockdown on gastric cancer cellular processes. LINC00968 could negatively regulate the expression of miR-3202, which further regulate VIRMA, the coding gene of KIAA1429, in gastric cancer cells.

CONCLUSIONS

LINC00968 contributes to the enhanced cell growth and metastasis of gastric cancer, which was mediated by KIAA1429-mediating m6A modification and the miR-3202/VIRMA axis.

Transcriptional and microbial profile of gastric cancer patients infected with Epstein-Barr virus

Introduction

Gastric cancer (GC), which has low survival rates and high mortality, is a major concern, particularly in Asia and South America, with over one million annual cases. Epstein-Barr virus (EBV) is recognized as a carcinogen that may trigger gastric carcinogenesis by infecting the stomach epithelium via reactivated B cells, with growing evidence linking it to GC. This study investigates the transcriptional and microbial profiles of EBV-infected versus EBV-non-infected GC patients.

Methods

Using Illumina NextSeq, cDNA libraries were sequenced, and reads were aligned to the human genome and analyzed with DESeq2. Kegg and differential analyses revealed key genes and pathways. Gene sensitivity and specificity were assessed using ROC curves (p < 0.05, AUC > 0.8). Non-aligned reads were used for microbiome analysis with Kraken2 for bacterial identification. Microbial analysis included LDA score, Alpha and Beta diversity metrics, with significance set at p ≤ 0.05. Spearman's correlation between differentially expressed genes (DEGs) and bacteria were also examined.

Results

The data revealed a gene expression pattern in EBV-positive gastric cancer, highlighting immune response, inflammation, and cell proliferation genes (e.g., GBP4, ICAM1, IL32, TNFSF10). ROC analysis identified genes with high specificity and sensitivity for discriminating EBV+ gastric cancer, including GBP5, CMKLR1, GM2A and CXCL11 that play pivotal roles in immune response, inflammation, and cancer. Functional enrichment pointed to cytokine-cytokine receptor interactions, antigen processing, and Th17 immune response, emphasizing the role of the tumor microenvironment, shaped by inflammation and immunomodulation, in EBV-associated GC. Microbial analysis revealed changes in the gastric microbiota in EBV+ samples, with a significant reduction in bacterial taxa. The genera Choristoneura and Bartonella were more abundant in EBV+ GC, while more abundant bacteria in EBV- GC included Citrobacter, Acidithiobacillus and Biochmannia. Spearman's correlation showed a strong link between DE bacterial genera and DEGs involved in processes like cell differentiation, cytokine production, digestion, and cell death.

Conclusion

These findings suggest a complex interaction between the host (EBV+ GC) and the microbiota, possibly influencing cancer progression, and offering potential therapeutic targets such as microbiota modulation or gene regulation. Comparing with EBV- samples further highlights the specific impact of EBV and the microbiota on gastric cancer pathogenesis.

Role of ITGB2 protein structure and molecular mechanism in precancerous lesions of gastric cancer: Influencing the occurrence and development of cancer through the CXCL1-CXCR2 axis

Gastric cancer is a prevalent gastrointestinal tumor. In the classical cascade of gastric cancer development, the gradual progression from non-atrophic gastritis, atrophic gastritis, intestinal metaplasia, to intraepithelial neoplasia eventually leads to early gastric cancer. We investigated the proteomic characteristics of chronic gastritis (CG), low-grade intraepithelial neoplasia (low-grade LGIN), and early gastric cancer (EGC). Additionally, we utilized transcriptomic databases to explore the expression patterns of ITGB2 across different stages of gastric tissue and its correlation with the prognosis of gastric cancer. The expression of ITGB2 was confirmed in cytological experiments, revealing that ITGB2 can influence the onset and progression of gastric cancer via the CXCL1-CXCR2 axis. This finding suggests that ITGB2 represents a novel biomarker for gastric cancer, making it a potential target for accurate diagnosis and treatment.

Identification and Validation of Four Serum Biomarkers With Optimal Diagnostic and Prognostic Potential for Gastric Cancer Based on Machine Learning Algorithms

BACKGROUND

Gastric cancer (GC) is considered a highly heterogeneous disease, and currently, a comprehensive approach encompassing molecular data from various biological levels is lacking.

METHODS

This study conducted different analyses, including the identification of differentially expressed genes (DEGs), weighted correlation networks (WGCNA), single-cell RNA sequencing (scRNA-seq), mRNA expression-based stemness index (mRNAsi), and multiCox analysis, utilizing data from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Subsequently, the machine learning algorithms including least absolute shrinkage and selection operator (LASSO) regression and random forest (RF), combined with multiCox analysis were exploited to identify hub genes. These findings were then validated through the receiver operating characteristic (ROC) curve and Kaplan-Meier analysis, and were experimentally confirmed in GC samples by reverse transcription-polymerase chain reaction (RT-PCR) and enzyme-linked immunosorbent assay (ELISA).

RESULTS

Integrated analysis of TCGA and GEO databases, coupled with LASSO regression and RF algorithms, allowed us to identify 18 hub genes encoding differentially expressed secreted proteins in GC. The results of RT-PCR and bioinformatics analysis revealed four promising biomarkers with optimal diagnostic and prognostic potential. ROC analysis and Kaplan-Meier curves highlighted CHI3L1, FCGBP, VSIG2, and TFF2 as promising biomarkers for GC, offering superior modeling accuracy. These findings were further confirmed by RT-PCR and ELISA, affirming the clinical utility of these four biomarkers. Additionally, CIBERSORT analysis indicated a potential correlation between the four biomarkers and the infiltration of B memory cells and Treg cells.

CONCLUSION

This study unveiled four promising biomarkers present in the serum of patients with GC, which could serve as powerful indicators of GC and provide valuable insights for further research into GC pathogenesis.

Multivariate Cox regression analysis of prognostic genes and therapeutic mechanisms of gastric cancer

Gastric cancer (GC) is a common malignant tumor, which originated from the epithelial cells of the stomach. It has the characteristics of high incidence and poor prognosis. Therefore, it is urgent to find new prognostic markers for the diagnosis and treatment of GC. Download gene expression matrix and clinical data from TCGA database and GSE84437 dataset. Through independent prognostic analysis and clinical correlation analysis, 74 prognostic related genes (PRG) were screened out. A PPI network was established for PRG to identify four key genes (KG), namely LMOD1, CRYAB, VCL and MYL9. Survival analysis showed that patients with high expression of KG had poor prognosis. Multivariate Cox regression analysis showed that KG was an independent prognostic factor. TCGA database verifies the importance and significance of KG as a prognostic indicator. Functional enrichment analysis showed that KG was mainly involved in cell adhesion molecules, adhesion spots and PI3K/AKT signaling pathway. KG may be a potential therapeutic target for gastric cancer.

Serum metabolic profiling analysis of chronic gastritis and gastric cancer by untargeted metabolomics

Chronic gastritis (CG), particularly when associated with Helicobacter pylori (H. pylori) infection, is a significant precursor to gastric cancer (GC), a leading cause of cancer-related deaths worldwide. The persistent inflammation in CG, driven by factors such as H. pylori, induces oxidative stress and DNA damage in gastric epithelial cells, which can lead to malignant transformation. Atrophic gastritis, a form of CG, can be categorized into autoimmune and H. pylori-associated types, both of which increase the risk of GC development, particularly when compounded by external factors like smoking and dietary habits. This manuscript explores the pathophysiological mechanisms underlying CG and its progression to GC, highlighting the critical role of metabolomics in advancing our understanding of these processes. Metabolomics, the comprehensive study of metabolites, offers a novel approach to identifying biomarkers that could facilitate early detection and improve the accuracy of GC diagnosis and prognosis. The analysis of metabolic alterations, particularly in glucose, lipid, and amino acid metabolism, reveals distinct biochemical pathways associated with the progression from benign gastritis to malignancy. Integrating metabolomic profiling with traditional diagnostic methods can revolutionize GC management, enabling more personalized treatment strategies and improving clinical outcomes. However, significant challenges remain, including the need to validate biomarkers across diverse populations and standardize metabolomic techniques. Future research should address these challenges to fully realize the potential of metabolomics in early GC detection and treatment, ultimately aiming to reduce the global burden of this deadly disease.

Prognostic development and validation of a prediction model based on major histocompatibility complex-related differentially expressed genes in stomach adenocarcinoma

Background

Stomach adenocarcinoma (STAD) is a common malignant tumor with high morbidity and mortality. Major histocompatibility complex (MHC) is an important component of the immune system responsible for antigen presentation. However, no studies have yet reported on the relationship between major histocompatibility complex-related differentially expressed genes (MHCRDEGs) and the survival prognosis of STAD. The aim of this study is to explore the relationship between MHCRDEGs and survival prognosis in STAD patients.

Methods

Using The Cancer Genome Atlas (TCGA) database, we screened for differentially expressed MHCRDEGs, and a survival prognosis model was constructed based on these genes. We generated training and validation samples from the TCGA and Gene Expression Omnibus (GEO) datasets to enhance the robustness of our findings. The predictive effects of the model were assessed using Kaplan-Meier (KM) survival curve analysis, receiver operating characteristic (ROC) curve analysis, calibration analysis and decision curve analysis (DCA), with statistical significance reported as P values. The differences in the expression of key MHCRDEGs between different subgroups of TCGA and GEO databases were analyzed. Finally, a multifactorial survival prognostic model was constructed by combining MHC score (MHCs), and quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to verify the expression of key genes.

Results

We identified five key MHCRDEGs: MKI67, MYB, SERPINE1, TRIM31, and HAVCR1. In the first prognostic model, the KM curves demonstrated a highly statistically significant difference in predicting overall survival (OS) in patients (P<0.001). The ROC curves indicated that the model showed relatively low accuracy in predicting 1-year [area under curve (AUC) =0.616], 3-year (AUC =0.644), and 5-year (AUC =0.619) occurrence. Furthermore, calibration analysis and DCA suggested that the model's predictions of OS were consistent with the actual patient survival, with the 5-year prognostic model exhibiting the best clinical utility. In the TCGA and GEO datasets, most of the key genes showed significant expression differences between the STAD/GEO and normal groups (P<0.001). Finally, the predictive model constructed by combining MHCs with clinicopathological staging demonstrated good predictive accuracy with optimal clinical utility at 5 years, with specific accuracy metrics provided as part of our results, and validated their expression via qRT-PCR in cell lines (MKI67: P=0.01, MYB: P=0.02, SERPINE1: P=0.02, TRIM31: P=0.02, HAVCR1: P<0.0001).

Conclusions

In this study, the expression and distribution of MHCRDEGs in STAD were analyzed by various methods, and a clinical prediction model of STAD was constructed using MHCRDEGs. The validity of this model confirms the feasibility of MHCRDEGs as prognostic markers for STAD, elucidating their potential clinical implications in guiding treatment strategies for this disease.

The molecular mechanisms of Caulophyllum robustum Maxim extract inhibition by regulating FAK/PI3K signaling pathway in gastric cancer HGC-27 cells

ETHNOPHARMACOLOGICAL RELEVANCE

Caulophyllumrobustum Maxim extract (CRME), as recorded in traditional Chinese medicine, has the function of dispelling Feng, regulating Qi and dredging collaterals, promoting blood circulation and regulating menstruation, gingering up and relieving pain, clearing heat simultaneously detoxifying, lowering blood pressure and hemostasis. CRME is often used as Chinese materia medica preparation for rheumatoid arthritis, traumatic injury, irregular menstruation, abdominal pain, and hypertension treatment. Since gastric cancer (GC) existed as a health problem of human over the years, we are committed to the development of potential components of Chinese herbal medicine curing cancer, and we found CRME is expected to be one of the effective anti-tumor traditional Chinese medicine preparations.

AIMS OF THE STUDY

To investigate the molecular mechanisms of CRME anticancer effects and the potential links between CRME and FAK.

MATERIALS AND METHODS

Caulophyllumrobustum Maxim was extracted to obtain CRME, high-performance liquid chromatography (HPLC) was used for qualitative analysis. Information about CRME was collected from traditional Chinese medicine records and local surveys unpublished internationally. Series of cellular function experiments were applied to detect cell proliferation, migration, apoptosis, autophagy, cell cycle, angiogenesis. The xenograft model is employed in vivo.

RESULTS

CRME can significantly inhibit HGC-27 cells on proliferation, migration and angiogenic capacity. Xenograft model indicated CRME inhibited cell proliferation in vivo. Annexin V-FITC/PI double staining assay and PI single staining assay depicted that CRME induces cell apoptosis, and arrests cell cycle at G0/G1 phase. AO (acridine orange) staining assay showed that CRME promoted autophagosome formation and inhibited autophagic flow. HPLC indicated Cauloside A and Cauloside C are components of CRME. Western blot indicated that FAK/PI3K signaling pathway is critical in the inhibition of CRME on HGC-27 cells.

CONCLUSIONS

The anti-tumor components of CRME, Cauloside A and Cauloside C, inhibited tumor progression in HGC-27 cells. This inhibition is achieved by decreasing the phosphorylation levels of FAK, thereby modulating PI3K/AKT signaling pathway.

Electrochemical immunoassay for gastric cancer biomarker pepsinogen I detection based on PdAgPt/MoS2

This study presents a novel electrochemical immunosensor for the detection of pepsinogen I, a potential biomarker for gastric cancer, based on a unique PdAgPt/MoS2nanocomposite. The key innovation lies in the synergistic combination of trimetallic PdAgPt nanoparticles with MoS2nanoflowers, which has not been previously reported for pepsinogen I detection. This hybrid material demonstrates exceptional electron transfer properties and a significantly larger electroactive surface area compared to conventional materials. The optimized immunosensor exhibits superior performance metrics: a wide linear range of 0.5-200 ng ml-1and an unprecedented low detection limit of 0.173 ng ml-1, surpassing existing detection methods. The sensor shows remarkable selectivity with interfering substances exhibiting relative responses below 5%, excellent reproducibility (RSD 3.8%), and outstanding stability (95.6% retention after 30 d). Analysis of spiked serum samples resulted in recoveries ranging from 96.8% to 104.5%, demonstrating the sensor's practical applicability for early gastric cancer screening. This work represents a significant advancement in developing rapid, sensitive, and cost-effective diagnostic tools for gastric cancer surveillance.

Brasiliensic acid: in vitro cytotoxic and genotoxic, in vivo acute toxicity and in silico pharmacological prediction of a new promising molecule

Brasiliensic acid (Bras) is a chromanone isolated from Calophyllum brasiliense Cambèss. bark extracts with confirmed potential activity on gastric ulcer and Helicobacter pylori infection. This study aimed to investigate the in vitro and in vivo toxicity of Bras and molecular docking studies on its interactions with the H. pylori virulence factors and selected gastric cancer-related proteins. Cytotoxicity was evaluated by alamarBlue© assay, genotoxicity by micronucleus and comet assays, and on cell cycle by flow cytometry, using Chinese hamster epithelial ovary cells. Bras was not cytotoxic to CHO-K1 cells, and caused no chromosomal aberrations, nor altered DNA integrity. Furthermore, Bras inhibited damages to DNA by H2O2 at 1.16 µM. No cell cycle arrest was observed, but apoptosis accounted for 31.2% of the cell death observed in the CHO-K1 at 24 h incubation of the IC50. Oral acute toxicity by Hippocratic screening test in mice showed no relevant behavioral change/mortality seen up to 1,000 mg/kg. The molecular docking approach indicated potential interactions between Bras and the various targets for peptic ulcer and gastric cancer, notably CagA virulence factor of H. pylori and VEGFR-2. In conclusion, Bras is apparently safe and an optimization for Bras can be considered for gastric ulcer and cancer.Communicated by Ramaswamy H. Sarma.

Integration of Gastric Cancer RNA-Seq Datasets Along With PPI Network Suggests That Nonhub Nodes Have the Potential to Become Biomarkers

BACKGROUND

The breakthrough discovery of novel biomarkers with prognostic and diagnostic value enables timely medical intervention for the survival of patients diagnosed with gastric cancer (GC). Typically, in studies focused on biomarker analysis, highly connected nodes (hubs) within the protein-protein interaction network (PPIN) are proposed as potential biomarkers. However, this study revealed an unexpected finding following the clustering of network nodes. Consequently, it is essential not to overlook weakly connected nodes (nonhubs) when determining suitable biomarkers from PPIN.

METHODS AND RESULTS

In this study, several potential biomarkers for GC were proposed based on the findings from RNA-sequencing (RNA-Seq) datasets, along with differential gene expression (DGE) analysis, PPINs, and weighted gene co-expression network analysis (WGCNA). Considering the overall survival (OS) analysis and the evaluation of expression levels alongside statistical parameters of the PPIN cluster nodes, it is plausible to suggest that THY1, CDH17, TGIF1, and AEBP1, categorized as nonhub nodes, along with ITGA5, COL1A1, FN1, and MMP2, identified as hub nodes, possess characteristics that render them applicable as biomarkers for the GC. Additionally, insulin-like growth factor (IGF)-binding protein-2 (IGFBP2), classified as a nonhub node, demonstrates a significant negative correlation with both groups within the same cluster. This observation underscores the conflicting findings regarding IGFBP2 in various cancer studies and enhances the potential of this gene to serve as a biomarker.

CONCLUSION

The findings of the current study not only identified the hubs and nonhubs that may serve as potential biomarkers for GC but also revealed a PPIN cluster that includes both hubs and nonhubs in conjunction with IGFBP2, thereby enhancing the understanding of the complex behavior associated with IGFBP2.

Dysregulated transfer RNA-derived small RNAs as potential gastric cancer biomarkers

Gastric cancer (GC) is the kind of carcinoma that has the highest rates of morbidity and death worldwide. In the early stages of GC, there is currently an absence of sensitive and specific biomarkers. The newly-discovered class of non-coding RNAs (ncRNAs) known as transfer RNA-derived small RNAs (tsRNAs) is highly expressed in bodily fluids and neoplastic cells. High-throughput sequencing was initially employed to identify differentially expressed tsRNAs in early GC patients, followed by validation in patient serum, GC tissues, and cell lines by quantitative real-time polymerase chain reaction (qRT-PCR). We identified dysregulated tsRNAs (the up-regulated tsRNAs included tRF-31-PNR8YP9LON4VD, tRF-30-MIF91SS2P4FI, and tRF-30-IK9NJ4S2I7L7, whereas the down-regulated tsRNAs included tRF-38-W6RM7KYUPRENRHD2, tRF-37-LBRY73W0K5KKOV2, tRF-36-JB59V3WD8YQ84VD, tRF-25-MBQ4NKKQBR, and tRF-36-0KFMNKYUHRF867D) in GC, and we verified that the serum of patients, GC cells and tissues both consistently expressed these tsRNAs. Additionally, GC patients' serum had considerably greater expression levels of the three up-regulated tsRNAs than did healthy controls. Receiver operating characteristic (ROC) curve analysis demonstrated that the sensitivity and specificity of the three up-regulated tsRNAs were superior to those of CEA, CA199, and CA724 in the process of diagnosing GC, particularly in its early stages. This suggests that tsRNAs have great diagnostic efficacy and potential as new "liquid biopsy" biomarkers for the diagnosis of GC. Using bioinformatics software, we predicted that dysregulation of tsRNAs may be a potential regulatory mechanism for the development of GC.

Potential Probes for Targeted Intraoperative Fluorescence Imaging in Gastric Cancer

Gastric cancer (GC) is a malignant tumor of the gastrointestinal tract associated with high mortality rates and accounting for approximately 1 million new cases diagnosed annually. Surgery, particularly radical gastrectomy, remains the primary treatment; however, there are currently no specific approaches to better distinguish malignant from healthy tissue or to differentiate between metastatic and non-metastatic lymph nodes. As a result, surgeons have to remove all lymph nodes indiscriminately, increasing intraoperative risks for patients and prolonging hospital stay. Near-infrared fluorescence imaging with indocyanine green (ICG) can provide real-time visualization of the surgical field using both conventional laparoscopy and robotic mini-invasive precision surgery platforms. However, its application shows some limits, as ICG is a non-targeted contrast agent. Several studies are now investigating the potential efficacy of fluorescent targeted agents that could selectively bind to the tumor tissue, offering a valuable tool for metastatic mapping during robotic gastrectomy. This review aims to summarize the key fluorescent agents that have been developed to recognize GC markers, as well as those targeting the tumor microenvironment (TME) and metabolic features. These agents hold great potential as valuable tools for enhancing precision surgery in robotic gastrectomy procedures improving the clinical recovery of GC patients.

Identification of gastric cancer biomarkers through in-silico analysis of microarray based datasets

Gastric cancer is among the most prevalent cancers worldwide including in Pakistan. Late diagnosis of gastric cancer leads to reduced survival. The present study aimed to investigate biomarkers for early diagnosis and prognosis of gastric cancer. For this purpose, the ten microarray-based gene expression datasets (GSE54129, GSE79973, GSE161533, GSE103236, GSE33651, GSE19826, GSE118916, GSE112369, GSE13911, and GSE81948) were retrieved from GEO database and analyzed by GEO2R to identify differentially expressed genes. Datasets were arranged in subsets of different dataset combinations to identify common DEGs. The gene ontology and functional pathway enrichment analysis of common DEGs was performed by DAVID tool. Pan-cancer analysis was conducted by UALCAN database. Survival analysis of common DEGs was done by Kaplan-Meier plotter. A total of 71 common DEGs were identified in different combinations of datasets. Among them, only 5 DEGs namely ATP4B, ATP4A, CCKBR, KCNJ15, and KCNJ16 were detected to be common in all the datasets. The GO and pathway analysis represented that the identified DEGs are involved in gastric acid secretion and collecting duct acid secretion pathways. Further expression validation of these five genes using three additional datasets (GSE31811, GSE26899, and GSE26272) confirmed their differential expression in gastric cancer samples. The pan-cancer analysis also revealed aberrant expression of DEGs in various cancers. The survival analysis showed the association of these 5 DEGs with poor survival of gastric cancer patients. To conclude, this study revealed a panel of 5 genes, which can be employed as diagnostic and prognostic biomarkers of gastric cancer patients.

The potential of circular RNAs as biomarkers and therapeutic targets for gastric cancer: A comprehensive review

BACKGROUND

Gastric cancer (GC) is a global health concern, contributing significantly to cancer-related mortality rates. Early detection is vital for improving patient outcomes. Recently, circular RNAs (circRNAs) have emerged as crucial players in the development and progression of various cancers, including GC.

AIM

This comprehensive review underscores the promising potential of circRNAs as innovative biomarkers for the early diagnosis of GC, as well as their possible utility as therapeutic targets for this life-threatening disease. Specifically, the review focuses on recent findings, mechanistic insights, and clinical applications of circRNAs in GC.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Dysregulation of circRNAs has been consistently observed in GC tissues, offering potential diagnostic value due to their stability in bodily fluids such as blood and urine. For instance, circPTPN22 and hsa_circ_000200. Furthermore, the expression levels of circRNAs such as circCUL2, hsa_circ_0000705 and circSHKBP1 have shown strong associations with critical clinical features of GC, including diagnosis, prognosis, tumor size, lymph node metastasis, tumor-node-metastasis (TNM) stage, and treatment response. Additionally, circRNAs such as circBGN, circLMO7, and circMAP7D1 have shown interactions with specific microRNAs (miRNAs), proteins, and other molecules that play key roles in development and progression of GC. This further highlighting their potential as therapeutic targets. Despite their potential, several challenges need to be addressed to effectively apply circRNAs as GC biomarkers. These include standardizing detection methods, establishing cutoff values for diagnostic accuracy, and validating findings in larger patient cohorts. Moreover, the functional mechanisms by which circRNAs contribute to GC pathogenesis and therapeutic resistance warrant further investigation. Advances in circRNAs research could provide valuable insights into the early detection and targeted treatment of GC, ultimately improving patient outcomes.

Establishment and validation of a nomogram model for early diagnosis of gastric cancer: a large-scale cohort study

Purpose

Identifying high-risk populations and diagnosing gastric cancer (GC) early remains challenging. This study aimed to establish and verify a nomogram model for the early diagnosis of GC based on conventional laboratory indicators.

Methods

We performed a retrospective analysis of the clinical data of 2,770 individuals with first diagnosis of GC and 1,513 patients with benign gastric disease from January 2018 to December 2022. The cases were divided into the training set and validation set randomly, with a ratio of 7:3. Variable screening was performed by least absolute shrinkage and selection operator (LASSO) and logistic regression analysis. A nomogram was constructed in the training set to assist in the early diagnosis of GC.

Results

There were 4283 patients included in the study, with 2998 patients assigned in the training set and 1285 patients in the validation set. Through LASSO regression and logistic regression analysis, independent variables associated with GC were identified, including CEA, CA199, LYM, HGB, MCH, MCHC, PLT, ALB, TG, HDL, and AFR. The nomogram model was constructed using the above 11 independent indicators. The AUC was 0.803 for the training set and 0.797 for the validation set, indicating that the model showed high clinical diagnostic efficacy. The calibration curves and decision curve analysis (DCA) of the nomogram presented good calibration and clinical application ability.

Conclusion

Based on the analysis of large sample size, we constructed a nomogram model with 11 routine laboratory indicators, which showed good discrimination ability and calibration.

The regulatory role of tRNA-derived small RNAs in the prognosis of gastric cancer

In recent years, tRNA-derived small RNAs (tsRNAs) including tRNA-derived stress-induced RNAs (tiRNAs) and tRNA-derived fragments (tRFs), with specific structure and enriched in body fluids, have been found to have specific biological functions. In this paper, the biogenesis, classification, subcellular localization, and biological functions of tsRNAs were summarized. It has been proved that tsRNAs affected tumor cells in proliferation, apoptosis, migration and invasion, and played roles in regulating the occurrence and development of various tumors. In gastric cancer (GC), the imbalance of tsRNAs, such as tRF-33-P4R8YP9LON4VDP, tRF-17-WS7K092, tRF-23-Q99P9P9NDD and others, was closely related to the clinicopathological characteristics of GC patients. Some tsRNAs, such as tRF-23-Q99P9P9NDD, tRF-31-U5YKFN8DYDZDD, and tRF-27-FDXXE6XRK45 promoted the proliferation, migration and invasion of GC cells. Other tsRNAs, such as tRF-41-YDLBRY73W0K5KKOVD, tRF-18-79MP9PO4, and tRF-Glu-TTC-027 inhibited the proliferation, migration and invasion of GC cells. The tsRNAs played roles in the occurrence of GC were through several signaling pathways, such as phosphoinositide 3-kinase (PI3K)-AKT serine/threonine kinase (AKT), Wnt-β-Catenin, and mitogen-activated protein kinase (MAPK) pathways. These findings may provide new strategies for the diagnosis and treatment of GC.

Best-Practice Biomarker Testing of Oesophago-Gastric Cancer in the UK: Expert Consensus Recommendations Developed Using a Modified Delphi

AIMS

Oesophago-gastric cancers (OGCs) are amongst the most commonly diagnosed malignancies worldwide and are associated with high disease-related mortality. Predictive biomarkers are molecules that can be objectively measured and used to indicate a likely response to therapeutic intervention, thus facilitating individualised cancer therapy. However, there remains variation in uptake and implementation of biomarker testing across the UK.

MATERIALS AND METHODS

We conducted a modified Delphi study to formulate consensus recommendations for best-practice biomarker testing of OGC in the UK. We employed two rounds of online questionnaires followed by a virtual consensus meeting. Biomarkers for discussion included HER2, MSI/MMR, and PD-L1. Topics comprised the overall biomarker pathway, pre-analytical, analytical, and post-analytical considerations, including challenges in current practice.

RESULTS

Twenty-six and eighteen participants completed the first and second round Delphi questionnaire, respectively, with an even split of pathologists and oncologists from across the UK. There was consensus (>80% agreement) across several topics, including the requirements for standardisation of the pathway, which must include coordination throughout the tissue journey, requirements for a quality-assured process to ensure accuracy and validity of testing, plus the need for clear, detailed information on the pathology report to support treatment decisions. There was consensus amongst oncologists regarding reflex testing of all biomarkers depending on histology; however, concerns over capacity in relation to workload and availability of pathologists were evident among the pathologists. Overall, participants were in the opinion that reflex testing improves the speed of treatment decisions and improves patient care.

CONCLUSION

The recommendations reflect best-practices and should be implemented to support rapid multidisciplinary team decision-making within oesophago-gastric cancer. Results reflect the need for standardisation and demonstrate the challenges faced in clinical practice by those requesting and testing biomarkers for oesophago-gastric cancer, suggesting significant concerns relating to pathologist capacity.

The implicated role of GDF15 in gastrointestinal cancer

BACKGROUND

Growth differentiation factor 15 (GDF15), a stress-responsive cytokine from transforming growth factor superfamily, is highly expressed in mammalian tissues, including pancreas, stomach and intestine under pathological conditions. In particular, elevated levels of GDF15 might play an important role in the development and progression of various gastrointestinal cancers (GCs), suggesting its potential as a promising target for disease prediction and treatment.

METHODS

In this review, systematic reviews addressing the role of GDF15 in GCs were updated, along with the latest clinical trials focussing on the GDF15-associated digestive malignancies.

RESULTS

The multiple cellular pathways through which GDF15 is involved in the regulation of physiological and pathological conditions were first summarized. Then, GDF15 was also established as a valuable clinical index, functioning as a predictive marker in diverse GCs. Notably, latest clinical treatments targeting GDF15 were also highlighted, demonstrating its promising potential in mitigating and curing digestive malignancies.

CONCLUSIONS

This review unveils the pivotal roles of GDF15 and its potential as a promising target in the pathogenesis of GCs, which may provide insightful directions for future investigations.

Clinicopathological and prognostic significance of TIMP1 expression in gastric cancer: a systematic review and meta-analysis

BACKGROUND

The research on the associations between tissue inhibitors of metalloproteinase-1 (TIMP1) expression and the clinicopathological characteristics and prognosis of patients with gastric cancer (GC) have resulted in contradictory findings. Exploring the associations between TIMP1 and clinicopathological parameters and the prognosis of GC patients is essential.

METHODS

We searched the literature in the databases according to the inclusion and exclusion criteria. Hazard ratios (HRs), odds ratios (ORs) and 95% confidence intervals (95% CIs) were used to evaluate the relationships between TIMP1 expression and the clinicopathological parameters and prognosis of GC patients.

RESULTS

Nine studies with 1,200 GC patients were included. Our results indicated that TIMP1 expression was not related to sex, age, TNM stage, depth of invasion, lymph node metastasis, or tumor size in GC patients. However, TIMP1 expression was associated with the differentiation of GC. Furthermore, TIMP1 expression was associated with poor prognosis in GC patients.

CONCLUSION

TIMP1 expression was related to tumor differentiation and poor prognosis but not sex, age, TNM stage, depth of invasion, lymph node metastasis or tumor size.

Identification and validation of a novel innate lymphoid cell-based signature to predict prognosis and immune response in liver cancer by integrated single-cell RNA analysis and bulk RNA sequencing

Background

Innate lymphoid cells (ILCs) exert tumor suppressive and tumor promoting effects. However, the prognostic significance of ILC-associated genes remains unclear in hepatocellular carcinoma (HCC). Hence, the aim of this research was to develop an innovative predictive risk classification system using bioinformatics examination.

Methods

We explored the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases to gather data pertaining to HCC and its clinical details. Significantly different ILC-associated genes were investigated by Seurat analysis. The number of signaling interactions of ILCs with other cells was discovered by CellPhoneDB analysis. ClusterProfiler and Metascape were utilized to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses on ILC genes. In order to identify potential ILC predictors, we utilized univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses, subsequently validating these predictors in TCGA and GEO groups. The multi-omics ILC signature model's clinical predictive capabilities, along with drug sensitivity and immune factor relations, were assessed using Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) and pRRophetic. We investigated the possible molecular pathways in our predictive ILC signature through the utilization of gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). Five key genes were screened out by constructing a competing endogenous RNA (ceRNA) network using Cytoscape and their values in clinical indexes were demonstrated. Immunohistochemistry (IHC) in HCC cases confirmed the expression of these genes.

Results

ILC cell subsets were identified, and cell-cell communication analysis revealed that the signaling pathways involving ILC cell subsets were mostly abundant in the HCC microenvironment. Subsequently, 270 marker genes of the ILC clusters were subjected to GO and KEGG enrichment analysis. Furthermore, a total of 58 prognostically relevant genes were screened as features for prognostic prediction models. Next, the models were validated and clinically evaluated (P values of Kaplan-Meier survival curves below 0.05). Five key genes (C2, STK4, CALM1, IL7R, and RORA) were further screened by multi omics analysis of immune cell and factor and drug sensitivity and correlation analysis of tumor regulatory genes in liver cancer. Furthermore, the potential clinical value of the 5 key genes was confirmed in HCC patients. Finally, the IHC results confirmed the expression of C2, STK4, CALM1, IL7R, and RORA in HCC. Our experimental results provided preliminary evidence supporting the oncogenic roles of STK4 and CALM1, as well as the tumor-suppressive roles of C2, RORA, and IL7R in HCC.

Conclusions

A novel prognostic feature of ILC potentially involved in HCC was discovered. It showed high values in predicting patient overall survival (OS) as well as good differences in immunity and drug sensitivity. Therefore, targeting these ILC signatures may be a potential effective approach in HCC treatment.

Nomogram for predicting 10-year postoperative recurrence of stage I gastric cancer

Background

With the advancement of various auxiliary examination techniques, the detection rate of stage I gastric cancer has gradually increased, and its clinical first-choice treatment is surgery. Although patients with stage I gastric cancer generally have a good postoperative survival rate, there is still a certain probability of recurrence. Given the large number of gastric cancer cases, there is a vast population of patients with stage I disease. We are aiming to identify the risk factors for postoperative recurrence of stage I gastric cancer and to establish a reliable predictive model to assess the risk of recurrence in the population for clinical practice.

Methods

In this retrospective cohort study, we utilized the Surveillance, Epidemiology, and End Results (SEER) database to investigate predictive factors for recurrence among stage I gastric cancer patients who underwent curative gastrectomy between 2000 and 2018. The cohort was divided into training and validation sets for the development and validation of a nomogram. Prognostic factors were evaluated through univariate and multivariate Cox regression analyses. Significant variables identified by the concordance index (C-index) and calibration plots were used to construct nomograms predicting the probability of 5- and 10-year recurrence.

Results

Risk factors for recurrence included sex, age, race, histology, tumor size, American Joint Committee on Cancer Tumor (AJCC T) and primary site, which were used to construct the nomogram. The C-index for both the training and validation cohorts indicated that the nomogram possessed good calibration and discrimination abilities in predicting the probability of 5- and 10-year recurrence after curative surgery for stage I gastric cancer.

Conclusions

This study established a reliable predictive model for recurrence following curative gastrectomy in stage I gastric cancer based on a population cohort. The findings of this study have the potential to significantly impact clinical practice by providing clinicians with tools for personalized risk assessment and for making informed treatment decisions.

Identifying the signature of NAD+ metabolism-related genes for immunotherapy of gastric cancer

NAD (Nicotinamide Adenine Dinucleotide) -related metabolic reprogramming in tumor cells involves multiple vital cellular processes. However, the role of NAD metabolism in immunity and the prognosis of gastric cancer (GC) remains not elucidated. Here we identified and clustered 33 NAD + metabolism-related genes (NMRGs) based on 808 GC samples from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Survival analysis between different groups found a poor prognosis in the GC patients with high NMRGs expression. Gene SGCE, APOD, and PPP1R14A were identified and performed high expression in GC samples, while the qRT-PCR results further confirmed that their expression levels in GC cell lines were significantly higher than those from normal human gastric mucosa epithelial cells. Based on the single-cell analysis, Gene SGCE, APOD, and PPP1R14A can potentially be novel biomarkers of tumor-associated fibroblasts (CAFs). In parallel, the proliferation and migration of GC cells were significantly hampered following the knockdown of SGCE, APOD, and PPP1R14A, particularly APOD, we confirmed that APOD knockdown can inhibit β-catenin and N-cadherin expression, while promote E-cadherin expression. This study unveils a novel NMRGs-related gene signature, highlighting APOD as a prognostic biomarker linked to the tumor microenvironment. APOD drives GC cell proliferation and metastasis through the Wnt/β-catenin/EMT signaling pathway, establishing it as a promising therapeutic target for GC patients.

The role of cuproptosis in gastric cancer

As a biologically essential transition metal, copper is widely involved in various enzymatic reactions and crucial biological processes in the body. It plays an increasingly important role in maintaining normal cellular metabolism and supporting the growth and development of the human body. As a trace element, copper maintains the dynamic balance of its concentration in body fluids through active homeostatic mechanisms. Both excess and deficiency of copper ions can impair cell function, ultimately leading to cell damage and death. Cuproptosis is a novel form of cell death where copper ions cause cell death by directly binding to the lipoylated components of the citric acid cycle (CAC) in mitochondrial respiration and interfering with the levels of iron-sulfur cluster (Fe-S cluster) proteins, ultimately causing protein toxic stress. Its primary characteristics are Cu2+ concentration dependence and high expression in mitochondrial respiratory cells. Recent research has revealed that, compared to other forms of programmed cell death such as apoptosis, necrosis, and autophagy, cuproptosis has unique morphological and biochemical features. Cuproptosis is associated with the occurrence and development of various diseases, including cancer, neurodegenerative diseases, and cardiovascular diseases. This article focuses on a review of the relevance of cuproptosis in gastric cancer (GC).

In Silico Insights Reveal Fibronectin 1 as a Theranostic Marker in Gastric Cancer

Gastric cancer (GC) is a complex and highly variable disease, ranking among the top five cancers diagnosed globally, and a leading cause of cancer-related deaths. Emerging from stomach lining cells amid chronic inflammation, it often advances to preneoplastic stages. Late-stage diagnoses and treatment challenges highlight the critical need for early detection and innovative biomarkers, motivating this study's focus on identifying theranostic markers through gene ontology analysis. By exploring deregulated biological processes, this study aims to uncover insights into cancer progression and associated markers, potentially identifying novel theranostic candidates in GC. Using public data from The Human Protein Atlas, this study pinpointed 299 prognostic genes, delineating 171 with unfavorable prognosis and 128 with favorable prognosis. Functional enrichment and protein-protein interaction analyses, supported by RNAseq results and conducted via Metascape and Cytoscape, highlighted five genes (vWF, FN1, THBS1, PCDH7, and F5) with promising theranostic potential. Notably, FN1 and THBS1 exhibited significant promise, with FN1 showing a 370% expression increase in cancerous tissue, and it is possible that FN1 can also indicate the stratification status in GC. While further validation is essential, these findings provide new insights into molecular alterations in GC and potential avenues for clinical application of theranostic markers.

Emerging methods and techniques for cancer biomarker discovery

Modern cancer research depends heavily on the identification and validation of biomarkers because they provide important information about the diagnosis, prognosis, and response to treatment of the cancer. This review will provide a comprehensive overview of cancer biomarkers, including their development phases and recent breakthroughs in transcriptomics and computational techniques for detecting these biomarkers. Blood-based biomarkers have great potential for non-invasive tumor dynamics and treatment response monitoring. These include circulating tumor DNA, exosomes, and microRNAs. Comprehensive molecular profiles are provided by multi-omic technologies, which combine proteomics, metabolomics, and genomes to support the identification of biomarkers and the targeting of therapeutic interventions. Genetic changes are detected by next-generation sequencing, and patterns of protein expression are found by protein arrays and mass spectrometry. Tumor heterogeneity and clonal evolution can be understood using metabolic profiling and single-cell studies. It is projected that the use of several biomarkers-genetic, protein, mRNA, microRNA, and DNA profiles, among others-will rise, enabling multi-biomarker analysis and improving individualised treatment plans. Biomarker identification and patient outcome prediction are further improved by developments in AI algorithms and imaging techniques. Robust biomarker validation and reproducibility require cooperation between industry, academia, and doctors. Biomarkers can provide individualized care, meet unmet clinical needs, and enhance patient outcomes despite some obstacles. Precision medicine will continue to take shape as scientific research advances and the integration of biomarkers with cutting-edge technologies continues to offer a more promising future for personalized cancer care.

Platelet-to-neutrophil ratio predicts hemorrhagic transformation and unfavorable outcomes in acute ischemic stroke with intravenous thrombolysis

BACKGROUND

Acute ischemic stroke (AIS) retains a notable stance in global disease burden, with thrombolysis via recombinant tissue plasminogen activator (rtPA) serving as a viable management approach, albeit with variable outcomes and the potential for complications like hemorrhagic transformation (HT). The platelet-to-neutrophil ratio (P/NR) has been considered for its potential prognostic value in AIS, yet its capacity to predict outcomes following rtPA administration demands further exploration.

AIM

To elucidate the prognostic utility of P/NR in predicting HT and clinical outcomes following intravenous rtPA administration in AIS patients.

METHODS

Data from 418 AIS patients treated with intravenous rtPA at Thammasat University Hospital from January 2018 to June 2021 were retrospectively analyzed. The relationship between P/NR and clinical outcomes [early neurological deterioration (E-ND), HT, delayed ND (D-ND), and 3-mo outcomes] was scrutinized.

RESULTS

Notable variables, such as age, diabetes, and stroke history, exhibited statistical disparities when comparing patients with and without E-ND, HT, D-ND, and 3-mo outcomes. P/NR prognostication revealed an optimal cutoff of 43.4 with a 60.3% sensitivity and a 52.5% specificity for 90-d outcomes. P/NR prognostic accuracy was statistically significant for 90-d outcomes [area under the curve (AUC) = 0.562], D-ND (AUC = 0.584), and HT (AUC = 0.607).

CONCLUSION

P/NR demonstrated an association with adverse 3-mo clinical outcomes, HT, and D-ND in AIS patients post-rtPA administration, indicating its potential as a predictive tool for complications and prognoses. This infers that a diminished P/NR may serve as a novel prognostic indicator, assisting clinicians in identifying AIS patients at elevated risk for unfavorable outcomes following rtPA therapy.

Integrated gene-metabolite association network analysis reveals key metabolic pathways in gastric adenocarcinoma

Gastric adenocarcinoma is one of the most death cause cancers worldwide. Metabolomics is an effective approach for investigating the occurrence and progression of cancer and detecting prognostic biomarkers by studying the profiles of small bioactive molecules. To fully decipher the functional roles of the disrupted metabolites that modulate the cellular mechanism of gastric cancer, integrated gene-metabolite association network methods are critical to map the associations between metabolites and genes. In this study, we constructed a knowledge-based gene-metabolite association network of gastric cancer using the dysregulated metabolites and genes between gastric cancer patients and control group. The topological pathway analysis and gene-protein-metabolite-disease association analysis revealed four key gene-metabolite pathways which include eleven metabolites associated with modulated genes. The integrated gene-metabolite association network enables mechanistic investigation and provides a comprehensive overview regarding the investigation of molecular mechanisms of gastric cancer, which facilitates the in-depth understanding of metabolic biomarker roles in gastric cancer.

Unveiling molecular clues: Exploring IFNγ, IL-10, and MMP7 blood levels in gastric carcinoma patients

Objectives

Gastric carcinoma is a leading cause of morbidity and mortality worldwide. Early detection can help reduce mortality rates. Biomarkers are being investigated globally for their potential in disease screening, monitoring, and follow-up in various cancers. However, currently, there is insufficient data on the role of biomarkers in gastric carcinoma.

Material and Methods

This single center case control study was conducted from June 2018 to March 2021 from South India. Blood samples were collected from 85 patients diagnosed with gastric carcinoma and 85 apparently healthy individuals serving as the control group. The samples were collected in a fasting state. The serum levels of biomarkers interferon gamma (IFNγ), interleukin 10 (IL-10), and matrix metalloproteinase 7 (MMP7) were measured using enzyme-linked immunosorbent assay (ELISA) and compared between the two groups. Additionally, the levels of biomarkers were compared within the gastric cancer group based on disease location, stage, and histotype.

Results

The serum levels of IFNγ and IL-10 were found to be significantly elevated in gastric carcinoma patients compared to the healthy control group. Both biomarkers exhibited high sensitivity and specificity in detecting carcinoma of the stomach. However, there was no significant difference in the serum level of MMP7 between gastric cancer patients and control group.

Conclusion

IFNγ and IL-10 show promise as potential molecular biomarkers for the detection of gastric carcinoma. Further, well designed studies, involving larger and more diverse populations matched for stage and histological types, are necessary to establish the screening and monitoring utility of these biomarkers in gastric carcinoma.

Genetic Markers of Susceptibility in Gastric Cancer: A Comprehensive Systematic Review

This systematic review synthesizes findings from various studies that examine genetic markers associated with susceptibility to gastric cancer. By conducting a comprehensive search across multiple databases, we analyzed studies on the relationship between specific genetic polymorphisms and the risk of developing gastric cancer. Our review highlights significant genetic markers, including mucin 1 (MUC1), prostate stem cell antigen (PSCA), tumor necrosis factor-alpha (TNF-α), DNA methyltransferases (DNMTs), matrix metalloproteinase-7 (MMP-7), and interleukin-8 (IL-8), emphasizing their roles across different ethnic and demographic contexts. The findings demonstrate a robust association between these markers and gastric cancer susceptibility, particularly noting variations in risk among diverse populations. Such variations could inform personalized treatment and screening strategies. The review also underscores the need for further research to explore how these polymorphisms influence cancer development and to confirm their potential clinical applications. We discuss the implications of these genetic markers for global health strategies and personalized medicine, highlighting the importance of integrating genetic testing into current gastric cancer management protocols.

Fructose-1, 6-Bisphosphate Aldolase B Suppresses Glycolysis and Tumor Progression of Gastric Cancer

OBJECTIVE

Gastric cancer (GC) is believed to be one of the most common digestive tract malignant tumors. However, mounting evidence indicates a link between the glycolysis and tumorigenesis, including gastric cancer.

METHODS

Our research identified 5508 differently expressed mRNAs in gastric cancer. Then, the genes highly associated with tumorigenesis were identified through weighted correlation network analysis (WGCNA). Bioinformatics analysis observed that these hub genes were significantly linked to the regulation of cell cycle, drug metabolism, and glycolysis. Among these hub genes, there is a critical gene involved in glycolysis regulation, namely fructose-bisphosphate B (ALDOB).

RESULTS

Analysis based on The Cancer Genome Atlas (TCGA) and three Gene Expression Omnibus (GEO) datasets revealed that ALDOB was significantly downregulated in GC compared with normal tissues. In addition, cell viability assay confirmed that ALDOB acted as a tumor suppressor. Finally, drug sensitivity analysis revealed that ALDOB increased the sensitivity of gastric cancer cells to most antitumor drugs, especially talazoparib, XAV939, and FTI-277. Our results showed that the expression of ALDOB was significantly lower in GC tissues than in normal tissues. And ALDOB significantly inhibited proliferation and migration, delayed glycolysis in GC cells. Consequently, our study suggests that ALDOB may be a potential target for the clinical treatment of gastric cancer.

Delineating protein biomarkers for gastric cancers: A catalogue of mass spectrometry-based markers and assessment of their suitability for targeted proteomics applications

Gastric cancer (GC) is a global health concern. To facilitate improved management of GCs, protein biomarkers have been identified through mass spectrometry-based proteomics platforms. In order to exhibit clinical utility of such data, we congregated over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the mass spectrometry platforms, association of the protein with infectious agents, protein identifiers, sample size and clinical characters of samples used with details on validation. Development of targeted proteomics methods is the cornerstone for pursuing these markers into clinical utility. Therefore, we developed Protein Biomarker Matrix for Gastric Cancer (PBMGC), a simple catalogue of robustness of each protein. This analysis yielded the identification of robust tissue, serum, and urine diagnostic and prognostic protein biomarker panels which can be further tested for their clinical utility. We also ascertained proteotypic tryptic peptides of 5631 proteins suitable for developing multiple reaction monitoring (MRM) assays. Extensive characterization of these peptides was carried out to record peptide ions, mass/charge and enhanced specific peptide features. With the vision of catering to proteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). Users can browse and download the data and improve GCPDB by submitting recently published data. SIGNIFICANCE: Mass spectrometry-based proteomics platforms have accumulated substantial data on proteins differentially regulated in gastric cancer (GC) clinical samples. The utility of such data in clinical applications is limited by search for suitable biomarker panels for assessment of GCs. We assembled over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the corresponding details including mass spectrometry platforms, status on the association of the protein with infectious agents, protein identifiers from different databases, sample size and clinical characters of samples used in test and control conditions along with details on their validation. Towards the vision of utilizing these markers in clinical assays, Protein Biomarker Matrix for Gastric Cancer (PBMGC) was developed and clinically relevant multi-protein panels were identified. We also demonstrated identification and characterization of tryptic proteotypic tryptic peptides of 5631 proteins biomarkers of GCs which are suitable for development of MRM assays in a SCIEX QTRAP instrument. Aimed to caterproteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). The users can browse and download details on different markers and improve GCPDB by submitting recently published data. Such an analysis could lay a cornerstone for building more such resources or conduct such analysis in different clinical conditions to uptake and develop targeted proteomics as the method of choice for clinical applications.

Protein Biomarkers of Gastric Preneoplasia and Cancer Lesions in Blood: A Comprehensive Review

Gastric cancer (GC) is a major cause of cancer-related mortality worldwide. It is often associated with a bad prognosis because of its asymptomatic phenotype until advanced stages, highlighting the need for its prevention and early detection. GC development is preceded by the emergence of gastric preneoplasia lesions (GPNLs), namely atrophic gastritis (AG), intestinal metaplasia (IM), and dysplasia (DYS). GC is currently diagnosed by endoscopy, which is invasive and costly and has limited effectiveness for the detection of GPNLs. Therefore, the discovery of non-invasive biomarkers in liquid biopsies, such as blood samples, in order to identify the presence of gastric preneoplasia and/or cancer lesions at asymptomatic stages is of paramount interest. This comprehensive review provides an overview of recently identified plasma/serum proteins and their diagnostic performance for the prediction of GPNLs and early cancer lesions. Autoantibodies appear to be promising biomarkers for AG, IM and early gastric cancer detection, along with inflammation and immunity-related proteins and antibodies against H. pylori virulence factors. There is a lack of specific protein biomarkers with which to detect DYS. Despite the need for further investigation and validation, some emerging candidates could pave the way for the development of reliable, non-invasive diagnostic tests for the detection and prevention of GC.

BRD4 expression and its regulatory interaction with miR-26a-3p, DLG5-AS1, and JMJD1C-AS1 lncRNAs in gastric cancer progression

Gastric cancer remains a significant health challenge despite advancements in diagnosis and treatment. Early detection is critical to reducing mortality, necessitating the investigation of molecular mechanisms underlying gastric cancer progression. This study focuses on BRD4 expression and its correlation with miR-26a-3p, DLG5-AS1, and JMJD1C-AS1 lncRNAs in gastric cancer. Analysis of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets revealed significant upregulation of BRD4 in gastric cancer tissues compared to normal tissues, correlating negatively with miR-26a-3p and positively with DLG5-AS1 and JMJD1C-AS1 lncRNAs. Quantitative RT-PCR confirmed these findings in 25 gastric cancer tissue samples and 25 normal samples. BRD4's overexpression was associated with reduced survival rates and older patient age. MiR-26a-3p, a known tumor suppressor, showed decreased expression in gastric cancer tissues, with ROC analysis suggesting it, alongside BRD4, as a potential diagnostic biomarker. Additionally, bioinformatics predicted miR-26a-3p's interaction with BRD4 mRNA. Upregulated lncRNAs DLG5-AS1 and JMJD1C-AS1 likely act as competing endogenous RNAs, sponging miR-26a-3p, thus promoting BRD4 dysregulation. These lncRNAs have not been previously studied in gastric cancer. The findings propose a novel BRD4/lncRNA/miRNA regulatory axis in gastric cancer, highlighting the potential of BRD4, DLG5-AS1, and JMJD1C-AS1 as biomarkers for early diagnosis. Further studies with larger sample sizes and in vivo and in vitro experiments are needed to elucidate this regulatory mechanism's role in gastric cancer progression.

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

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

Hypoxia exacerbates the malignant transformation of gastric epithelial cells induced by long-term H. pylori infection

Helicobacter pylori is a microaerophilic Gram-negative bacterium that resides in the human stomach and is classified as a class I carcinogen for gastric cancer. Numerous studies have demonstrated that H. pylori infection plays a role in regulating the function of host cells, thereby contributing to the malignant transformation of these cells. However, H. pylori infection is a chronic process, and short-term cellular experiments may not provide a comprehensive understanding of the in vivo situation, especially when considering the lower oxygen levels in the human stomach. In this study, we aimed to investigate the mechanisms underlying gastric cell dysfunction after prolonged exposure to H. pylori under hypoxic conditions. We conducted a co-culture experiment using the gastric cell line GES-1 and H. pylori for 30 generations under intermittent hypoxic conditions. By closely monitoring cell proliferation, migration, invasion, autophagy, and apoptosis, we revealed that sustained H. pylori stimulation under hypoxic conditions significantly influences the function of GES-1 cells. This stimulation induces epithelial-mesenchymal transition and contributes to the propensity for malignant transformation of gastric cells. To confirm the in vitro results, we conducted an experiment involving Mongolian gerbils infected with H. pylori for 85 weeks. All the results strongly suggest that the Nod1 receptor signaling pathway plays a crucial role in H. pylori-related apoptosis and autophagy. In summary, continuous stimulation by H. pylori affects the functioning of gastric cells through the Nod1 receptor signaling pathway, increasing the likelihood of cell carcinogenesis. The presence of hypoxic conditions further exacerbates this process.IMPORTANCEDeciphering the collaborative effects of Helicobacter pylori infection on gastric epithelial cell function is key to unraveling the development mechanisms of gastric cancer. Prior research has solely examined the outcomes of short-term H. pylori stimulation on gastric epithelial cells under aerobic conditions, neglecting the bacterium's nature as a microaerophilic organism that leads to cancer following prolonged stomach colonization. This study mimics a more genuine in vivo infection scenario by repeatedly exposing gastric epithelial cells to H. pylori under hypoxic conditions for up to 30 generations. The results show that chronic exposure to H. pylori in hypoxia substantially increases cell migration, invasion, and epithelial-mesenchymal transition, while suppressing autophagy and apoptosis. This highlights the significance of hypoxic conditions in intensifying the carcinogenic impact of H. pylori infection. By accurately replicating the in vivo gastric environment, this study enhances our comprehension of H. pylori's pathogenic mechanisms in gastric cancer.

The functions of cuproptosis in gastric cancer: therapy, diagnosis, prognosis

Gastric cancer (GC) is the fifth most prevalent type of cancer in the whole world. Cuproptosis is discovered as a programmed cell death pathway and connected to cells' growth and death, as well as tumorigenesis. The relationship between cuproptosis and GC is still elusive. Two aspects of this study will elaborate the relationship between cuproptosis and immunotherapy as well as biomarkers in GC. Notably, the herein review is intended to highlight what has been accomplished regarding the cuproptosis for the diagnosis, immunotherapy, and prognosis in GC. The aim of this study is to offer a potential directions and the strategies for future research regarding cuproptosis inside the GC.

KPNA2 promotes the progression of gastric cancer by regulating the alternative splicing of related genes

RNA-binding proteins (RBPs) play critical roles in genome regulation. In this study, we explored the latent function of KPNA2, which is an essential member of the RBP family, in the regulation of alternative splicing (AS) in gastric cancer (GC). We analyzed the role of KPNA2 in regulating differential expression and AS via RNA sequencing (RNA-seq) and improved RNA immunoprecipitation sequencing (iRIP-seq). Clinical specimens were used to analyze the associations between KPNA2 expression and clinicopathological characteristics. CCK8 assays, transwell assays and wound healing assays were performed to explore the effect of KPNA2/WDR62 on GC cell progression. KPNA2 was shown to be highly expressed in GC cells and tissues and associated with lymph node metastases. KPNA2 promoted the proliferation, migration and invasion of GC cells and primarily regulated exon skipping, alternative 3's splice sites (A3SSs), alternative 5' splice sites (A5SSs), and cassette exons. We further revealed that KPNA2 participated in biological processes related to cell proliferation, and the immune response in GC via the regulation of transcription. In addition, KPNA2 preferentially bound to intron regions. Notably, KPNA2 regulated the A3SS AS mode of WDR62, and upregulation of WDR62 reversed the KPNA2 downregulation-induced inhibition of GC cell proliferation, migration and invasion. Finally, we discovered that the AS of immune-related molecules could be regulated by KPNA2. Overall, our results demonstrated for the first time that KPNA2 functions as an oncogenic splicing factor in GC that regulated the AS and differential expression of GC-related genes, and KPNA2 may be a potential target for GC treatment.

The Role and Function of TRPM8 in the Digestive System

Transient receptor potential (TRP) melastatin member 8 (TRPM8) is a non-selective cation channel that can be activated by low temperatures (8-26 °C), cooling agents (including menthol analogs such as menthol, icilin, and WS-12), voltage, and extracellular osmotic pressure changes. TRPM8 expression has been identified in the digestive system by several research teams, demonstrating its significant involvement in tissue function and pathologies of the digestive system. Specifically, studies have implicated TRPM8 in various physiological and pathological processes of the esophagus, stomach, colorectal region, liver, and pancreas. This paper aims to comprehensively outline the distinct role of TRPM8 in different organs of the digestive system, offering insights for future mechanistic investigations of TRPM8. Additionally, it presents potential therapeutic targets for treating conditions such as digestive tract inflammation, tumors, sensory and functional disorders, and other related diseases. Furthermore, this paper addresses the limitations of existing studies and highlights the research prospects associated with TRPM8.

SIVA-1 interaction with PCBP1 serves as a predictive biomarker for cisplatin sensitivity in gastric cancer and its inhibitory effect on tumor growth in vivo

Background: SIVA-1 has been reported to play a key role in cell apoptosis and gastric cancer (GC) chemoresistance in vitro. Nevertheless, the clinical significance of SIVA-1 in GC chemotherapy remains unclear. Methods and results: Immunohistochemistry and histoculture drug response assays were used to determine SIVA-1 expression and the inhibition rate (IR) of agents to GC and to further analyze the relationship between these two phenomena. Additionally, cisplatin (DDP)-resistant GC cells were used to elucidate the role and mechanism of SIVA-1 in vivo. The results demonstrated that SIVA-1 expression was positively correlated with the IR of DDP to GC but not with those of 5-fluorouracil (5-FU) or adriamycin (ADM). Furthermore, SIVA-1 overexpression with DDP treatment synergistically inhibited tumor growth in vivo by increasing PCBP1 and decreasing Bcl-2 and Bcl-xL expression. Conclusions: Our study demonstrated that SIVA-1 may serve as an indicator of the GC sensitivity to DDP, and the mechanism of SIVA-1 in GC resistance to DDP was preliminarily revealed.

Integrated analysis of the role of PR/SET domain 14 in gastric cancer

BACKGROUND

Gastric cancer is one of the most common tumors worldwide, and most patients are deprived of treatment options when diagnosed at advanced stages. PRDM14 has carcinogenic potential in breast and non-small cell lung cancer. however, its role in gastric cancer has not been elucidated.

METHODS

We aimed to elucidate the expression of PRDM14 using pan-cancer analysis. We monitored the expression of PRDM14 in cells and patients using quantitative polymerase chain reaction, western blotting, and immunohistochemistry. We observed that cell phenotypes and regulatory genes were influenced by PRDM14 by silencing PRDM14. We evaluated and validated the value of the PRDM14-derived prognostic model. Finally, we predicted the relationship between PRDM14 and small-molecule drug responses using the Connectivity Map and The Genomics of Drug Sensitivity in Cancer databases.

RESULTS

PRDM14 was significantly overexpressed in gastric cancer, which identified in cell lines and patients' tissues. Silencing the expression of PRDM14 resulted in apoptosis promotion, cell cycle arrest, and inhibition of the growth and migration of GC cells. Functional analysis revealed that PRDM14 acts in epigenetic regulation and modulates multiple DNA methyltransferases or transcription factors. The PRDM14-derived differentially expressed gene prognostic model was validated to reliably predict the patient prognosis. Nomograms (age, sex, and PRDM14-risk score) were used to quantify the probability of survival. PRDM14 was positively correlated with sensitivity to small-molecule drugs such as TPCA-1, PF-56,227, mirin, and linsitinib.

CONCLUSIONS

Collectively, our findings suggest that PRDM14 is a positive regulator of gastric cancer progression. Therefore, it may be a potential therapeutic target for gastric cancer.

KAT2A Promotes the Succinylation of PKM2 to Inhibit its Activity and Accelerate Glycolysis of Gastric Cancer

Gastric cancer (GC) is one of the main causes of cancer-related death. Lysine acetyltransferases 2 A (KAT2A) is a succinyltransferase that plays an essential role in cancer development. The pyruvate kinase M2 (PKM2) is a glycolysis rate-limiting enzyme that mediates the glycolysis of cancers. This study aimed to explore the effects and mechanism of KAT2A in GC progression. The effects of biological behaviors of GC cells were evaluated by MTT, colony formation and seahorse assays. The succinylation modification was assessed by immunoprecipitation (IP). The interaction between proteins were detected by Co-IP and immunofluorescence. A pyruvate kinase activity detection kit was used to evaluate the activity of PKM2. Western blot was performed to detect the expression and oligomerization of protein. Herein, we confirmed that KAT2A was highly expressed in GC tissues and was associated with a poor prognosis. Function studies showed that knockdown of KAT2A inhibited cell proliferation and glycolytic metabolism of GC. Mechanistically, KAT2A could directly interacted with PKM2 and KAT2A silencing inhibited the succinylation of PKM2 at K475 site. In addition, the succinylation of PKM2 altered its activity rather than its protein levels. Rescue experiments showed that KAT2A promoted GC cell growth, glycolysis, and tumor growth by promoting PKM2 K475 succinylation. Taken together, KAT2A promotes the succinylation of PKM2 at K475 to inhibit PKM2 activity, thus promotes the progression of GC. Therefore, targeting KATA2 and PKM2 may provide novel strategies for the treatment of GC.

APOA1 mRNA and serum APOA1 protein as diagnostic and prognostic biomarkers in gastric cancer

Background

Gastric cancer (GC) remains a formidable challenge in oncology, ranking as a leading cause of cancer mortality globally. This underscores an urgent need for innovative prognostic markers that can revolutionize patient management and outcomes. Recent insights into cancer biology have spotlighted the profound influence of lipid metabolism alterations on tumorigenesis, tumor progression, and the tumor microenvironment. These alterations not only fuel cancer cell growth and proliferation but also play a strategic role in evading immune surveillance and promoting metastasis. The intricate web of lipid metabolism in cancer cells, characterized by deregulated uptake, synthesis, and oxidation of fatty acids (FAs), opens new avenues for targeted therapeutic interventions and prognostic evaluations. Specifically, this study zeroes in on apolipoprotein A-I (APOA1), a key player in lipid metabolism, to unearth its prognostic value in GC. By delving into the role of lipid metabolism-related genes, particularly APOA1, we aim to unveil their potential as groundbreaking biomarkers for GC prognosis. This endeavor not only aims to enhance our understanding of the molecular underpinnings of GC but also to spearhead the development of lipid metabolism-based strategies for improved diagnostic, prognostic, and therapeutic outcomes.

Methods

Transcriptomic and clinical data from GC patients and healthy individuals were sourced from The Cancer Genome Atlas (TCGA) database, a comprehensive project that molecularly characterizes over 20,000 primary cancer and matched normal samples across 33 cancer types. Significantly differentially expressed lipid metabolism-related genes were identified using the "limma" package in R. Prognostic genes were selected via univariate Cox regression analysis. Differential gene enrichment analysis was performed using Metascape (http://www.metascape.org). The Human Protein Atlas (HPA, https://www.proteinatlas.org) provided information on APOA1 protein expression in GC and healthy tissues. Immune cell infiltration was analyzed using the CIBERSORT algorithm (http://cibersort.stanford.edu).

Results

Significant differences in lipid metabolism-related gene expression were observed between GC and normal tissues, closely linked to FA metabolism, oxidoreductase activity, and sphingolipid metabolism. APOA1 emerged as a potential prognostic biomarker by intersecting prognostic and differentially expressed lipid metabolism genes. Immunohistochemical analysis confirmed APOA1 downregulation in GC. The receiver operating characteristic (ROC) analysis demonstrated its predictive value, with the area under the curve (AUC) being 0.64 [95% confidence interval (CI): 0.52-0.76]. APOA1 expression correlated with immune cell infiltrations. Clinical serum APOA1 results revealed lower levels in GC patients (1.38 vs. 1.26; P<0.05), associated with poor prognosis (hazard ratio =1.50; P<0.001) and clinical characteristics. ROC analysis of serum APOA1 demonstrated good diagnostic ability (AUC: 0.63, 95% CI: 0.61-0.65). Serum APOA1 levels significantly increased after treatment.

Conclusions

This study highlights lipid metabolism reprogramming in GC and identifies APOA1 as a potential diagnostic and prognostic biomarker, suggesting its clinical utility in managing GC.

EGFR and PI3K Signalling Pathways as Promising Targets on Circulating Tumour Cells from Patients with Metastatic Gastric Adenocarcinoma

The prognosis for metastatic gastric adenocarcinoma (mGAC) remains poor. Gene alterations in receptor tyrosine kinases (RTKs) such as epidermal growth factor receptor (EGFR) and their downstream effectors including catalytic subunit alpha of the phosphatidylinositol 3-kinase (PIK3CA) are common in mGAC. Targeted RTK and phosphatidylinositol-3-kinase (PI3K) treatments have demonstrated clinical benefits in other solid tumours and are key potential targets for clinical development against mGAC given the presence of recurrent alterations in these pathways. Furthermore, combination RTK/PI3K treatments may overcome compensatory mechanisms that arise using monotherapies, leading to improved patient outcomes. Herein, we investigated RTK/PI3K single and combination drug responses against our unique human mGAC-derived PIK3CA gain-of-function mutant, human epidermal growth factor receptor 2 (HER2)-negative, EGFR-expressing circulating tumour cell line, UWG02CTC, under two- and three-dimensional culture conditions to model different stages of metastasis. UWG02CTCs were highly responsive to the PI3K p110α-subunit targeted drugs PIK-75 (IC50 = 37.0 ± 11.1 nM) or alpelisib (7.05 ± 3.7 µM). Drug sensitivities were significantly increased in 3D conditions. Compensatory MAPK/ERK pathway upregulation by PI3K/Akt suppression was overcome by combination treatment with the EGFR inhibitor gefitinib, which was strongly synergistic. PIK-75 plus gefitinib significantly impaired UWG02CTC invasion in an organotypic assay. In conclusion, UWG02CTCs are a powerful ex vivo mGAC drug responsiveness model revealing EGFR/PI3K-targeted drugs as a promising combination treatment option for HER2-negative, RAS wild-type mGAC patients.