AnnexinA5 Might Suppress the Phenotype of Human Gastric Cancer Cells via ERK Pathway

Integrative analysis of single-cell and bulk RNA sequencing reveals the oncogenic role of ANXA5 in gastric cancer and its association with drug resistance

Background

Gastric cancer (GC) remains a leading cause of cancer-related mortality, with over one million new cases and 769,000 deaths reported in 2020. Despite advancements in chemotherapy, surgery, and targeted therapies, delayed diagnosis due to overlooked early symptoms leads to poor prognosis.

Methods

We integrated bulk RNA sequencing and single-cell RNA sequencing datasets from TCGA, GEO, and OMIX001073, employing normalization, batch effect correction, and dimensionality reduction methods to identify key cell populations associated with GC invasion and epithelial-mesenchymal transition (EMT), as well as analyze the tumor immune microenvironment.

Results

Our analysis identified the MUC5AC+ malignant epithelial cell cluster as a significant player in GC invasion and EMT. Cluster 1, representing this cell population, exhibited higher invasion and EMT scores compared to other clusters. Survival analysis showed that high abundance in cluster 0 correlated with improved survival rates (P=0.012), whereas cluster 1 was associated with poorer outcomes (P=0.045). A prognostic model highlighted ANXA5 and GABARAPL2 as two critical genes upregulated in GC tumors. High-risk patients demonstrated increased immune cell infiltration and worse prognosic. Analysis of tumor mutation burden (TMB) indicated that patients with low TMB in the high-risk group had the worst prognosis. Wet-lab validation experiments confirmed the oncogenic role of ANXA5, showing its facilitation of cell proliferation, invasion, and migration while suppressing apoptosis.

Conclusion

This study offers novel insights into the subpopulations of malignant epithelial cells in GC and their roles in tumor progression. It provides a prognostic model and potential therapeutic targets to combat GC, contributing crucial understanding to the fundamental mechanisms of drug resistance in gastrointestinal cancers.

Mechanism of Progesterone in Treatment of Traumatic Brain Injury Based on Network Pharmacology and Molecular Docking Technology

BACKGROUND Previous studies have confirmed that progesterone has a protective effect on traumatic brain injury (TBI). In this paper, network pharmacology and molecular docking technology were used to further explore the potential mechanism of progesterone in the treatment of TBI. MATERIAL AND METHODS Based on network pharmacology, potential targets of progesterone for TBI were obtained. The network diagram of interactions between target proteins was established to screen the key targets of progesterone for TBI. The DAVID database was used to analyze its biological function and enrichment pathway, and to explore and determine the biological pathway of progesterone in treating TBI. Molecular docking technology was used to simulate the interaction between progesterone and key target proteins. RESULTS Progesterone can treat TBI by anti-inflammatory action, repairing damaged cell membranes, stabilizing the structure of the blood-brain barrier, alleviating brain edema, reducing neuronal apoptosis, and improving neurological function. The molecular mechanism involves the PI3K/Akt signaling pathway, MAPK signaling pathway, and Ras signaling pathway. CONCLUSIONS Progesterone is a potential clinical treatment for TBI. Exploring the potential targets and pathways of TBI therapy through network pharmacology can provide a direction for subsequent research.

Pathobiological functions and clinical implications of annexin dysregulation in human cancers

Annexins are an extensive superfamily of structurally related calcium- and phospholipid-binding proteins, largely conserved and widely distributed among species. Twelve human annexins have been identified, referred to as Annexin A1-13 (A12 remains as of yet unassigned), whose genes are spread throughout the genome on eight different chromosomes. According to their distinct tissue distribution and subcellular localization, annexins have been functionally implicated in a variety of biological processes relevant to both physiological and pathological conditions. Dysregulation of annexin expression patterns and functions has been revealed as a common feature in multiple cancers, thereby emerging as potential biomarkers and molecular targets for clinical application. Nevertheless, translation of this knowledge to the clinic requires in-depth functional and mechanistic characterization of dysregulated annexins for each individual cancer type, since each protein exhibits varying expression levels and phenotypic specificity depending on the tumor types. This review specifically and thoroughly examines the current knowledge on annexin dysfunctions in carcinogenesis. Hence, available data on expression levels, mechanism of action and pathophysiological effects of Annexin A1-13 among different cancers will be dissected, also further discussing future perspectives for potential applications as biomarkers for early diagnosis, prognosis and molecular-targeted therapies. Special attention is devoted to head and neck cancers (HNC), a complex and heterogeneous group of aggressive malignancies, often lately diagnosed, with high mortality, and scarce therapeutic options.

Construction and validation of a novel coagulation-related 7-gene prognostic signature for gastric cancer

Background: Gastric cancer (GC) is the most common malignant tumor. Due to the lack of practical molecular markers, the prognosis of patients with advanced gastric cancer is still poor. A number of studies have confirmed that the coagulation system is closely related to tumor progression. Therefore, the purpose of this study was to construct a coagulation-related gene signature and prognostic model for GC by bioinformatics methods.

Methods: We downloaded the gene expression and clinical data of GC patients from the TCGA and GEO databases. In total, 216 coagulation-related genes (CRGs) were obtained from AmiGO 2. Weighted gene co-expression network analysis (WGCNA) was used to identify coagulation-related genes associated with the clinical features of GC. Last absolute shrinkage and selection operator (LASSO) Cox regression was utilized to shrink the relevant predictors of the coagulation system, and a Coag-Score prognostic model was constructed based on the coefficients. According to this risk model, GC patients were divided into high-risk and low-risk groups, and overall survival (OS) curves and receiver operating characteristic (ROC) curves were drawn in the training and validation sets, respectively. We also constructed nomograms for predicting 1-, 2-, and 3-year survival in GC patients. Single-sample gene set enrichment analysis (ssGSEA) was exploited to explore immune cells’ underlying mechanisms and correlations. The expression levels of coagulation-related genes were verified by real-time quantitative polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC).

Results: We identified seven CRGs employed to construct a Coag-Score risk model using WGCNA combined with LASSO regression. In both training and validation sets, GC patients in the high-risk group had worse OS than those in the low-risk group, and Coag-Score was identified as an independent predictor of OS, and the nomogram provided a quantitative method to predict the 1-, 2-, and 3-year survival rates of GC patients. Functional analysis showed that Coag-Score was mainly related to the MAPK signaling pathway, complement and coagulation cascades, angiogenesis, epithelial–mesenchymal transition (EMT), and KRAS signaling pathway. In addition, the high-risk group had a significantly higher infiltration enrichment score and was positively associated with immune checkpoint gene expression. Conclusion: Coagulation-related gene models provide new insights and targets for the diagnosis, prognosis prediction, and treatment management of GC patients.

Increased ANXA5 expression in stomach adenocarcinoma infers a poor prognosis and high level of immune infiltration

BACKGROUND: The prognostic role of annexin A5 (ANXA5) in stomach adenocarcinoma (STAD) has not been studied, and its relationship with immune infiltration is still unclear. OBJECTIVE: This investigation aimed at exploring the role of ANXA5 in STAD using an integrated bioinformatics analysis. METHODS: The expression of ANXA5 in STAD and the correlations between the effect of ANXA5 and survival of STAD patients were investigated using database. The clusterProfiler package in R software was used to perform enrichment analysis on the top 100 co-expressed genes of ANXA5 from the COXPRESdb online database. Correlations between ANXA5 and immune cell infiltrates were analyzed using the TIMER database. RESULTS: In STAD, ANXA5 expression was significantly upregulated and increased ANXA5 expression was significantly correlated with poor overall survival (P< 0.05). In multivariate analysis, upregulated ANXA5 expression was an independent predictive factors of poor prognosis (P< 0.05). The co-expressed genes were involved in extracellular matrix (ECM)-related processes. In STAD, ANXA5 expression was significantly correlated with various infiltrating immune cells (P< 0.05). CONCLUSIONS: Together with our findings, ANXA5 could serve as a potential biomarker to assess prognosis and immune infiltration level in STAD.