Expression analysis of apolipoprotein E and its associated genes in gastric cancer

Integrated bioinformatics reveals genetic links between visceral obesity and uterine tumors

Visceral obesity (VO), characterized by excess fat around internal organs, is a recognized risk factor for gynecological tumors, including benign uterine leiomyoma (ULM) and malignant uterine leiomyosarcoma (ULS). Despite this association, the shared molecular mechanisms remain underexplored. This study utilizes an integrated bioinformatics approach to elucidate common molecular pathways and identify potential therapeutic targets linking VO, ULM, and ULS. We analyzed gene expression datasets from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs) in each condition. We found 101, 145, and 18 DEGs in VO, ULM, and ULS, respectively, with 37 genes overlapping across all three conditions. Functional enrichment analysis revealed that these overlapping DEGs were significantly enriched in pathways related to cell proliferation, immune response, and transcriptional regulation, suggesting shared biological processes. Protein-protein interaction network analysis identified 14 hub genes, of which TOP2A, APOE, and TYMS showed significant differential expression across all three conditions. Drug-gene interaction analysis identified 26 FDA-approved drugs targeting these hub genes, highlighting potential therapeutic opportunities. In conclusion, this study uncovers shared molecular pathways and actionable drug targets across VO, ULM, and ULS. These findings deepen our understanding of disease etiology and offer promising avenues for drug repurposing. Experimental validation is needed to translate these insights into clinical applications and innovative treatments.

Apolipoproteins: New players in cancers

Apolipoproteins (APOs), the primary protein moiety of lipoproteins, are known for their crucial role in lipid traffic and metabolism. Despite extensive exploration of APOs in cardiovascular diseases, their roles in cancers did not attract enough attention. Recently, research focusing on the roles of APOs in cancers has flourished. Multiple studies demonstrate the interaction of APOs with classical pathways of tumorigenesis. Besides, the dysregulation of APOs may indicate cancer occurrence and progression, thus serving as potential biomarkers for cancer patients. Herein, we summarize the mechanisms of APOs involved in the development of various cancers, their applications as cancer biomarkers and their genetic polymorphism associated with cancer risk. Additionally, we also discuss the potential anti-cancer therapies by virtue of APOs. The comprehensive review of APOs in cancers may advance the understanding of the roles of APOs in cancers and their potential mechanisms. We hope that it will provide novel clues and new therapeutic strategies for cancers.

Research progress on exosomal proteins as diagnostic markers of gastric cancer (review article)

Gastric cancer (GC) is one of the most common types of tumors and the most common cause of cancer mortality worldwide. The diagnosis of GC is critical to its prevention and treatment. Available tumor markers are the crucial step for GC diagnosis. Recent studies have shown that proteins in exosomes are potential diagnostic and prognostic markers for GC. Exosomes, secreted by cells, are cup-shaped with a diameter of 30–150 nm under the electron microscope. They are also surrounded by lipid bilayers and are widely found in various body fluids. Exosomes contain proteins, lipids and nucleic acid. The examination of exosomal proteins has the advantages of quickness, easy sampling, and low pain and cost, as compared with the routine inspection method of GC, which may lead to marked developments in GC diagnosis. This article summarized the exosomal proteins with a diagnostic and prognostic potential in GC, as well as exosomal proteins involved in GC progression.

Analysis of Gastric Cancer Transcriptome Allows the Identification of Histotype Specific Molecular Signatures With Prognostic Potential

Gastric cancer is the fifth most common malignancy but the third leading cause of cancer-associated mortality worldwide. Therapy for gastric cancer remain largely suboptimal making the identification of novel therapeutic targets an urgent medical need. In the present study we have carried out a high-throughput sequencing of transcriptome expression in patients with gastric cancers. Twenty-four patients, among a series of 53, who underwent an attempt of curative surgery for gastric cancers in a single center, were enrolled. Patients were sub-grouped according to their histopathology into diffuse and intestinal types, and the transcriptome of the two subgroups assessed by RNAseq analysis and compared to the normal gastric mucosa. The results of this investigation demonstrated that the two histopathology phenotypes express two different patterns of gene expression. A total of 2,064 transcripts were differentially expressed between neoplastic and non-neoplastic tissues: 772 were specific for the intestinal type and 407 for the diffuse type. Only 885 transcripts were simultaneously differentially expressed by both tumors. The per pathway analysis demonstrated an enrichment of extracellular matrix and immune dysfunction in the intestinal type including CXCR2, CXCR1, FPR2, CARD14, EFNA2, AQ9, TRIP13, KLK11 and GHRL. At the univariate analysis reduced levels AQP9 was found to be a negative predictor of 4 years survival. In the diffuse type low levels CXCR2 and high levels of CARD14 mRNA were negative predictors of 4 years survival. In summary, we have identified a group of genes differentially regulated in the intestinal and diffuse histotypes of gastric cancers with AQP9, CARD14 and CXCR2 impacting on patients' prognosis, although CXCR2 is the only factor independently impacting overall survival.

Flavokawain C exhibits anti-tumor effects on in vivo HCT 116 xenograft and identification of its apoptosis-linked serum biomarkers via proteomic analysis

Chalcones and their derivatives belong to the flavonoid family. They have been extensively studied for their anticancer properties and some have been approved for clinical use. In this study, the in vivo anti-tumor activity of flavokawain C (FKC), a naturally occurring chalcone found in Kava (Piper methysticum Forst) was evaluated in HCT 116 cells (colon carcinoma). We also attempted to identify potential biomarkers and/or molecular targets in serum with applicability in predicting treatment outcome. The anti-tumor effects and toxicity of FKC were assessed using the xenograft nude mice model. Cisplatin was used as positive control. The anti-proliferative and apoptotic activities were then evaluated in tumor tissues treated with FKC. Furthermore, two-dimensional electrophoresis (2-DE) followed by protein identification using MALDI-TOF/TOF-MS/MS was performed to compare the serum proteome profiles between healthy nude mice and nude mice bearing HCT 116 tumor treated with vehicle solution and FKC, respectively. Our results showed that FKC treatment significantly inhibited HCT 116 tumor growth. In vivo toxicity studies showed that administration of FKC did not cause damage to major organs and had no significant effect on body weight. FKC was found to induce apoptosis in tumor, and this was associated with increased expression of cleaved caspase-3 and decreased expression of Ki67 in tumor tissues. Our proteomic analysis identified five proteins that changed in abundance - Ig mu chain C region (secreted form), GRP78, hemopexin, kininogen-1 and apolipoprotein E. Overall, our findings demonstrated the potential of FKC as an anti-cancer agent for the treatment of colon carcinoma.

Association between the methylation of the STAT1 and SOCS3 in peripheral blood and gastric cancer

BACKGROUND AND AIM

DNA methylation is an important epigenetic modification that can promote the development of various cancers. The STAT1 and SOCS3 have been observed to be hypermethylated in tumor tissues and peripheral blood. This study aimed to explore the relationship between the methylation status of the STAT1 and SOCS3 in peripheral blood and gastric cancer (GC).

METHODS

This hospital-based case-control study involved 372 patients with GC and 379 controls. The methylation status of the STAT1 and SOCS3 was semiquantitatively determined using the methylation-sensitive high-resolution melting method. Logistic regression analysis was used to analyze the relationship between the STAT1 and SOCS3 methylation status and GC susceptibility. Moreover, propensity scores were used to control confounding factors.

RESULTS

Compared with negative methylation, the positive methylation of SOCS3 significantly increased the risk of GC (OR_a  = 1.820, 95% CI: 1.247-2.658, P = 0.002). This trend was also found via stratified analysis, and methylation positivity of the SOCS3 significantly increased the risk of GC in the < 60 years group, in the ≥ 60 years group, and in the positive Helicobacter pylori infection group (OR_a  = 1.654, 95% CI: 1.029-2.660, P = 0.038; OR_a  = 1.957, 95% CI: 1.136-3.376, P = 0.016; OR_a  = 2.084, 95% CI: 1.270-3.422, P = 0.004, respectively). Additionally, no significant association was found between STAT1 methylation and GC risk (OR_a  = 0.646, 95% CI: 0.363-1.147, P = 0.135). This study found that the interaction between the methylation status of STAT1 and SOCS3 and environmental factors did not have an impact on GC risk.

CONCLUSION

SOCS3 methylation may serve as a new potential biomarker for GC susceptibility.

Serum Apolipoprotein E and Other Inflammatory Markers Can Identify Non-Responding Patients to a Dendritic Cell Vaccine

BACKGROUND

Despite the majority of patients do not gain any benefit from dendritic cells (DC) vaccines, this approach has occasionally given rise to dramatic responses in melanoma. Biomarkers are crucial to identify which patients are more likely to respond. We looked for correlations between pre- or post- vaccination biomarkers and clinical outcomes to DC therapy in a cohort of patients with stage IV melanoma receiving a vaccine with autologous ex-vivo expanded DCs pulsed with allogeneic tumor cell lysate.

METHODS

Serial serum samples were collected at baseline, week 4 and 12 and they were analyzed for a panel of different inflammatory markers using cytometric bead array technology and ELISA.

RESULTS

Twenty-one patients were evaluable for response. Patients were separated into responders and non-responders based on clinical benefit. Responders were defined as patients who achieved a complete response, partial response or stable disease the latter lasting for at least 6 months. Responders (N = 9) showed a significantly longer Progression-free Survival (PFS; HR 0.23; 95% CI 0.08-062; P < .001) and Overall Survival (OS; HR 0.22; 95% CI 0.08-0.59; P < .001). The clinical non-responder phenotype correlated with an elevated pre-vaccination level of cytokines associated with inflammation compared to clinical responders (Apolipoprotein C111; IL-12 p40; MiP1α; Stem Cell Factor and TNFα). Apolipoprotein E (ApoE) was also significantly elevated in the pre-vaccine sera of the clinically non-responding group and in addition it was found to correlate with outcomes. Patients with increased levels of ApoE had a significantly shorter PFS (HR 3.02; 95% CI 1.09-8.35; P = .015) and OS (HR 2.40; 95% CI 0.9-6.3; P = .034).

CONCLUSION

Our findings support the notion that treating the inflammatory background may have an impact on clinical outcome for patients receiving immunotherapy. A larger study is needed to confirm the significance of ApoE as a predictive biomarker for response to DC vaccines.

Analysis of cancer gene attributes using electrical sensor

Prediction of cancer gene attributes by their primary structure (long amino acid sequence) is instrumental in large-scale genomics projects, especially in the field of genomics. Various methods are proposed to predict gene characteristics from its primary structure, but accurate prediction of it is still very challenging task. Here we introduce an electrical network based sensor or detector to discriminate cancer and non-cancer cells based on two features i.e. amino acid sequence length, and hydrophilic/hydrophobic property. The electrical circuit consists of resistors, capacitors and inductors, is used for modeling individual amino acid and cascaded to form gene system. Corresponding electrical responses are judged using Bode and Nyquist analyzers and achieve 89.55% accuracy with 87.06% True Positive rate and 95.42% True Negative rate, demonstrate that proposed electrical sensor model is very promising for predicting the cancer gene attributes as well as non-cancer gene in the field of large-scale genomics study.

Apolipoprotein E is a pancreatic extracellular factor that maintains mature β-cell gene expression

The in vivo microenvironment of tissues provides myriad unique signals to cells. Thus, following isolation, many cell types change in culture, often preserving some but not all of their in vivo characteristics in culture. At least some of the in vivo microenvironment may be mimicked by providing specific cues to cultured cells. Here, we show that after isolation and during maintenance in culture, adherent rat islets reduce expression of key β-cell transcription factors necessary for β-cell function and that soluble pancreatic decellularized matrix (DCM) can enhance β-cell gene expression. Following chromatographic fractionation of pancreatic DCM, we performed proteomics to identify soluble factors that can maintain β-cell stability and function. We identified Apolipoprotein E (ApoE) as an extracellular protein that significantly increased the expression of key β-cell genes. The ApoE effect on beta cells was mediated at least in part through the JAK/STAT signaling pathway. Together, these results reveal a role for ApoE as an extracellular factor that can maintain the mature β-cell gene expression profile.

Identification of key genes and pathways in uterine leiomyosarcoma through bioinformatics analysis

Uterine leiomyosarcoma (uLMS) is a rare but malignant gynaecological tumour with a poor survival outcome. The present study was aimed at identifying the key genes and pathways in the development of uLMS through bioinformatics analysis. To minimize the frequency of false-positive results of the bioinformatics analysis, 3 microarrays including GSE764, GSE64763 and GSE68312 were downloaded from Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were screened out using the online tool GEO2R. Then, Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery. Finally, a protein-protein interaction (PPI) network of the DEGs was constructed using Cytoscape, and module analysis was conducted using the plug-in MCODE. A total of 95 DEGs including 21 upregulated genes and 74 downregulated genes were identified. The upregulated DEGs were annotated with 'DNA metabolic process', 'nucleobase-containing compound biosynthetic process' and 'cellular macromolecule biosynthetic process', while the downregulated DEGs were annotated with 'cellular response to chemical stimulus', 'movement of cell or subcellular component' and 'response to inorganic substances'. The results of the PPI network analysis demonstrated that matrix metallopeptidase 9, apolipoprotein E, cyclin E1 and syndecan 1 were the predominant upregulated genes in uLMS. Additionally, the genes in the main module were enriched in 'proteoglycans in cancer', 'p53 signalling pathway' and 'extracellular matrix-receptor interaction'. The key genes and pathways identified in the present study may provide valuable clues for clarifying the molecular mechanism underlying the development of uLMS and demonstrate promise for use as diagnostic markers and therapeutic targets.