Prognostic biomarker HAMP and associates with immune infiltration in gastric cancer

GCBRGCN: Integration of ceRNA and RGCN to Identify Gastric Cancer Biomarkers

Gastric cancer (GC) is a prevalent malignancy, and the discovery of biomarkers plays a crucial role in the diagnosis and prognosis of GC. However, current strategies for identifying GC biomarkers often focus on a single ribonucleic acid (RNA) class, neglecting the potential for multiple RNA types to collectively serve as biomarkers with improved predictive capabilities. To bridge this gap, our study introduces the GC biomarker relation graph convolution neural network (GCBRGCN) model which integrates the competing endogenous RNA (ceRNA) network with GC clinical informations and whole transcriptomics data, leveraging the relational graph convolutional network (RGCN) to predict GC biomarkers. It demonstrates exceptional performance, surpassing traditional machine learning and graph neural network algorithms with an area under the curve (AUC) of 0.8172 in the task of predicting GC biomarkers. Our study identified three unreported potential novel GC biomarkers: CCNG1, CYP1B1, and CITED2. Moreover, FOXC1 and LINC00324 were characterized as biomarkers with significance in both prognosis and diagnosis. Our work offers a novel framework for GC biomarker identification, highlighting the critical role of multiple types RNA interaction in oncological research.

Ferroptosis: opening up potential targets for gastric cancer treatment

The fifth most frequent cancer in the world is gastric cancer. It ranks as the fourth most common reason for cancer-related deaths. Even though surgery is the only curative treatment for stomach cancer, adding adjuvant radiotherapy and chemotherapy is preferable than only surgery. The majority of patients, however, are discovered to be extremely tardy the first time and have a terrible prognosis. Therefore, it is necessary to create more viable therapy modalities. A growing number of studies in recent years have shown that ferroptosis and many cancer types are related. This gives our treatment a fresh viewpoint. We investigated the relationship between different signal pathways and non-coding RNA on ferroptosis in gastric cancer cells. Also discussed the targets cause ferroptosis resistance increased or reduced to the influence of the chemoresistance,proliferation and metastasis.

Iron and cancer: overview of the evidence from population-based studies

Iron is an essential nutrient required for various physiological processes in the body. However, iron imbalance can potentially contribute to initiating and promoting cancer development. Epidemiological studies have investigated the relationship between dietary iron intake and the risk of different types of cancer, yet, not all studies have consistently shown a significant association between dietary iron and cancer risk. Also, studies have shown different effects of dietary heme and non-heme iron intake on cancer risk. While some epidemiological studies suggest a possible link between high dietary iron (mainly heme-iron) intake and increased cancer risk, the evidence remains inconsistent. Moreover, multiple iron biomarkers, which can mirror physiological iron status, have demonstrated varied correlations with the risk of cancer, contingent upon the specific biomarker analyzed and the type of cancer being investigated. Here, we have investigated the current evidence on the potential relationship between dietary iron intake on one hand, and iron biomarkers on the other hand, with the risk of developing different types of cancer, including breast, prostate, lung, pancreatic, colon, colorectal, and liver cancers. Further research is warranted to better understand the complex relationship between dietary iron, physiological iron and cancer development. Future research should account for factors that affect and interact with dietary iron and physiological iron levels, such as genetic susceptibility, overall diet quality, and lifestyle habits.

Prediction and verification of the prognostic biomarker SLC2A2 and its association with immune infiltration in gastric cancer

Gastric cancer (GC) is the fifth most common cause of cancer-associated deaths; however, its treatment options are limited. Despite clinical improvements, chemotherapy resistance and metastasis are major challenges in improving the prognosis and quality of life of patients with GC. Therefore, effective prognostic biomarkers and targets associated with immunological interventions need to be identified. Solute carrier family 2 member 2 (SLC2A2) may serve a role in tumor development and invasion. The present study aimed to evaluate SLC2A2 as a prospective prognostic marker and chemotherapeutic target for GC. SLC2A2 expression in several types of cancer and GC was analyzed using online databases, and the effects of SLC2A2 expression on survival prognosis in GC were investigated. Clinicopathological parameters were examined to explore the association between SLC2A2 expression and overall survival (OS). Associations between SLC2A2 expression and immune infiltration, immune checkpoints and IC50 were estimated using quantification of the tumor immune contexture from human RNA-seq data, the Tumor Immune Estimation Resource 2.0 database and the Genomics of Drug Sensitivity in Cancer database. Differential SLC2A2 expression and the predictive value were validated using the Human Protein Atlas, Gene Expression Omnibus, immunohistochemistry and reverse transcription-quantitative PCR. SLC2A2 expression was downregulated in most types of tumor but upregulated in GC. Functional enrichment analysis revealed an association between SLC2A2 expression and lipid metabolism and the tumor immune microenvironment. According to Gene Ontology term functional enrichment analysis, SLC2A2-related differentially expressed genes were enriched predominantly in 'chylomicron assembly', 'plasma lipoprotein particle assembly', 'high-density lipoprotein particle', 'chylomicron', 'triglyceride-rich plasma lipoprotein particle', 'very-low-density lipoprotein particle'. 'intermembrane lipid transfer activity', 'lipoprotein particle receptor binding', 'cholesterol transporter activity' and 'intermembrane cholesterol transfer activity'. In addition, 'cholesterol metabolism', and 'fat digestion and absorption' were significantly enriched in the Kyoto Encyclopedia of Genes and Genomes pathway analysis. Patients with GC with high SLC2A2 expression had higher levels of neutrophil and M2 macrophage infiltration and a significant inverse correlation was observed between SLC2A2 expression and MYC targets, tumor mutation burden, microsatellite instability and immune checkpoints. Furthermore, patients with high SLC2A2 expression had worse prognosis, including OS, disease-specific survival and progression-free interval. Multivariate regression analysis demonstrated that SLC2A2 could independently prognosticate GC and the nomogram model showed favorable performance for survival prediction. SLC2A2 may be a prospective prognostic marker for GC. The prediction model may improve the prognosis of patients with GC in clinical practice, and SLC2A2 may serve as a novel therapeutic target to provide immunotherapy plans for GC.

Risk scoring based on DNA methylation-driven related DEGs for colorectal cancer prognosis with systematic insights

Colorectal cancer is a common malignant tumor of the digestive tract. Despite advances in diagnostic techniques and medications. Its prognosis remains challenging. DNA methylation-driven related circulating tumor cells have attracted enormous interest in diagnosing owing to their non-invasive nature and early recognition properties. However, the mechanism through which risk biomarkers act remains elusive. Here, we designed a risk model based on differentially expressed genes, DNA methylation, robust, and survival-related factors in the framework of Cox regression. The model has satisfactory performance and is independently verified by an external and isolated dataset in terms of C-index value, ROC, and tROC. The model was applied to Colorectal cancer patients who were subsequently divided into high- and low-risk groups. Functional annotations, genomic alterations, tumor immune environment, and drug sensitivity were analyzed. We observed that up-regulated genes are associated with epithelial cell differentiation and MAPK signaling pathways. The down-regulated genes are related to IL-7 signaling and apoptosis-induced DNA fragmentation. Interestingly, the immune system was inhibited in high-risk groups. High-frequency mutation genes tend to co-occur. High-risk score patients are related to copy number amplification events. To address the challenges, we suggested eleven and twenty-one drugs that are sensitive to low- and high-risk patients. Finally, an artificial neural network was provided to evaluate the immunotherapeutic efficiency. Taken together, the findings demonstrated that our risk score model is robust and reliable for evaluating the prognosis with novel diagnostic and treatment targets. It also yields benefits for the treatment and provides unique insights into developing therapeutic strategies.

Hepcidin is upregulated and is a potential therapeutic target associated with immunity in glioma

Background

Glioma is the most common primary malignant brain tumor with high mortality and poor prognosis. Hepcidin is a fascinating iron metabolism regulator. However, the prognostic value of hepcidin HAMP in gliomas and its correlation with immune cell infiltration remain unclear. Here, we comprehensively elucidate the prognostic value and potential role of hepcidin in gliomas.

Methods

Hepcidin gene expression and clinical characteristics in glioma were analyzed using the CGGA, TCGA, Rembrandt and Gravendeel glioma databases. A survival analysis was conducted using Kaplan-Meier and Cox regression analyses. A gene set enrichment analysis (GSEA) was conducted to select the pathways significantly enriched for hepcidin associations. The correlations between hepcidin and immune cell infiltration and immunotherapy were analyzed using network platforms such as CIBERSORT and TIMER.

Results

In glioma tissues, the expression of hepcidin was significantly increased. High hepcidin expression is related to grade, age, PRS type, IDH mutation, chemotherapy status and 1p19q codeletion status, which significantly indicates the poor prognosis of glioma patients. Hepcidin can be used as an independent prognostic factor for glioma through the multivariate COX regression analysis. The results of Gene Ontology (GO), Kyoto Encyclopedia of Gene and Genome (KEGG) and gene set enrichment analysis (GSEA) indicated that hepcidin was involved in the immune response. In addition, hepcidin expression was positively correlated with the degree of immune cell infiltration, the expression of various immune cell markers and the efficacy of immunotherapy.

Conclusion

Our results indicate that hepcidin can be used as a candidate biomarker to judge the prognosis and immune cell invasion of gliomas.