Identification of Potential Core Genes Associated With the Progression of Stomach Adenocarcinoma Using Bioinformatic Analysis

Physical Exercise-Induced DNA Methylation in Disease-Related Genes in Healthy Adults-A Systematic Review With Bioinformatic Analysis

ABSTRACT

Vasileva, F, Hristovski, R, Font-Lladó, R, Georgiev, G, Sacot, A, López-Ros, V, Calleja-González, J, Barretina-Ginesta, J, López-Bermejo, A, and Prats-Puig, A. Physical exercise-induced DNA methylation in disease-related genes in healthy adults-A systematic review with bioinformatic analysis. J Strength Cond Res 38(2): 384-393, 2024-This study aimed to systematically review the existing literature regarding physical exercise (PE) and DNA methylation (DNAm) in healthy adults. Specific goals were to (a) identify differently methylated genes (DMGs) after PE intervention, their imprinting status, chromosome and genomic location, function, and related diseases; and (b) to screen for core genes and identify methylation changes of the core genes that can be modified by PE intervention. Our search identified 2,869 articles from which 8 were finally included. We identified 1851 DMGs ( p < 0.05) after PE intervention, although 45 of them were imprinted. Aerobic exercise (AE) seems to induce more DNA hypermethylation rather than hypomethylation, whereas anaerobic exercise (AN) seems to induce more DNA hypomethylation rather than hypermethylation. Aerobic exercise induced highest % of methylation changes on chromosome 6, whereas AN and mixed type (MT) on chromosome 1. Mixed type induced higher % of methylation changes close to transcription start site in comparison to AE and AN. After PE intervention, DMGs were mainly involved in fat metabolism, cell growth, and neuronal differentiation, whereas diseases regulated by those genes were mainly chronic diseases (metabolic, cardiovascular, neurodegenerative). Finally, 19 core genes were identified among DMGs, all related to protein metabolism. In conclusion, our findings may shed some light on the mechanisms explaining PE-induced health benefits such as the potential role that PE-induced DNAm may have in disease prevention and disease treatment.

Jian Yun Qing Hua Decoction inhibits malignant behaviors of gastric carcinoma cells via COL12A1 mediated ferroptosis signal pathway

BACKGROUND

Jian Yun Qing Hua Decoction (JYQHD), a traditional Chinese medicine decoction, which has been applied in the treatment of gastric cancer (GC). We attempt to confirm the anti-gastric cancer effect of JYQHD and explore the mechanism of JYQHD.

METHODS

Acute toxicity test was used to understand the toxicity of JYQHD. We studied the expression and prognostic outcome of COL12A1 within GC tissues through the network databases. Using several web-based databases, we analyzed the major components and targets of JYQHD, as well as known therapeutic targets in gastric cancer. The Venn diagram was utilized to obtain the overlapped genes. Lentiviral vector, shRNAs and plasmids, were used to transfect GC cells. Cell counting kit-8 (CCK8), sphere formation, malondialdehyde (MDA), glutathione (GSH), reactive oxygen species (ROS), Fe2+, transmission electron microscopy (TEM), quantitative Real-Time Polymerase Chain Reaction (qRT-PCR), Western-Blot (WB), and immunohistochemical (IHC) assays were employed to investigate the role and mechanism of COL12A1 and JYQHD in GC.

RESULTS

The results showed that JYQHD was non-toxic and safe. JYQHD inhibited growth and sphere formation ability through inducing the ferroptosis of GC cells, and suppressed the GC cells induced subcutaneous xenograft tumor growth. COL12A1 was highly expressed in gastric cancer tissues, indicating poor prognosis. COL12A1 specifically enhanced GC cell progression and stemness via suppressing ferroptosis. JYQHD down-regulated COL12A1 in order to suppress the stemness of GC cells via inducing ferroptosis.

CONCLUSION

COL12A1 inhibited ferroptosis and enhanced stemness in GC cells. JYQHD inhibited the development of GC cells by inhibiting cancer cell stemness via the ferroptosis pathway mediated by COL12A1.

Identification of miR-143-3p as a diagnostic biomarker in gastric cancer

BACKGROUND

Gastric cancer (GC) is among the most common types of gastrointestinal cancers and has a high incidence and mortality around the world. To suppress the progression of GC, it is essential to develop diagnostic markers. MicroRNAs regulate GC development, but a clearer insight into their role is needed before they can be applied as a molecular markers and targets.

METHODS

In this study, we assessed the diagnostic value of differentially expressed microRNAs as potential diagnostic biomarkers for GC using data for 389 tissue samples from the Cancer Genome Atlas (TCGA) and 21 plasma samples from GC patients.

RESULTS

The expression of hsa-miR-143-3p (also known as hsa-miR-143) was significantly downregulated in GC according to the TCGA data and plasma samples. The 228 potential target genes of hsa-miR-143-3p were analyzed using a bioinformatics tool for miRNA target prediction. The target genes correlated with extracellular matrix organization, the cytoplasm, and identical protein binding. Furthermore, the pathway enrichment analysis of target genes showed that they were involved in pathways in cancer, the phosphoinositide 3-kinase (PI3K)-protein kinase B (Akt) signaling pathway, and proteoglycans in cancer. The hub genes in the protein-protein interaction (PPI) network, were matrix metallopeptidase 2 (MMP2), CD44 molecule (CD44), and SMAD family member 3 (SMAD3).

CONCLUSIONS

This study suggests that hsa-miR-143-3p may be used as a diagnostic marker for GC, contributing via the pathways involved in the development of GC.

C-Biomarker.net: A Cytoscape app for the identification of cancer biomarker genes from cores of large biomolecular networks

Although there have been many studies revealing that biomarker genes for early cancer detection can be found in biomolecular networks, no proper tool exists to discover the cancer biomarker genes from various biomolecular networks. Accordingly, we developed a novel Cytoscape app called C-Biomarker.net, which can identify cancer biomarker genes from cores of various biomolecular networks. Derived from recent research, we designed and implemented the software based on parallel algorithms proposed in this study for working on high-performance computing devices. We tested our software on various network sizes and found the suitable size for each running mode on CPU or GPU. Interestingly, using the software for 17 cancer signaling pathways, we found that on average 70.59% of the top three nodes residing at the innermost core of each pathway are biomarker genes of the cancer respectively to the pathway. Similarly, by the software, we also found 100% of the top ten nodes at both cores of Human Gene Regulatory (HGR) network and Human Protein-Protein Interaction (HPPI) network are multi-cancer biomarkers. These case studies are reliable evidence for performance of cancer biomarker prediction function in the software. Through the case studies, we also suggest that true cores of directed complex networks should be identified by the algorithm of R-core rather than K-core as usual. Finally, we compared the prediction result of our software with those of other researchers and confirmed that our prediction method outperforms the other methods. Taken together, C-Biomarker.net is a reliable tool that efficiently detects biomarker nodes from cores of various large biomolecular networks. The software is available at https://github.com/trantd/C-Biomarker.net.

Landscape of Druggable Molecular Pathways Downstream of Genomic CDH1/Cadherin-1 Alterations in Gastric Cancer

Loss of CDH1/Cadherin-1 is a common step towards the acquisition of an abnormal epithelial phenotype. In gastric cancer (GC), mutation and/or downregulation of CDH1/Cadherin-1 is recurrent in sporadic and hereditary diffuse GC type. To approach the molecular events downstream of CDH1/Cadherin-1 alterations and their relevance in gastric carcinogenesis, we queried public databases for genetic and DNA methylation data in search of molecular signatures with a still-uncertain role in the pathological mechanism of GC. In all GC subtypes, modulated genes correlating with CDH1/Cadherin-1 aberrations are associated with stem cell and epithelial-to-mesenchymal transition pathways. A higher level of genes upregulated in CDH1-mutated GC cases is associated with reduced overall survival. In the diffuse GC (DGC) subtype, genes downregulated in CDH1-mutated compared to cases with wild type CDH1/Cadherin-1 resulted in being strongly intertwined with the DREAM complex. The inverse correlation between hypermethylated CpGs and CDH1/Cadherin-1 transcription in diverse subtypes implies a common epigenetic program. We identified nonredundant protein-encoding isoforms of 22 genes among those differentially expressed in GC compared to normal stomach. These unique proteins represent potential agents involved in cell transformation and candidate therapeutic targets. Meanwhile, drug-induced and CDH1/Cadherin-1 mutation-related gene expression comparison predicts FIT, GR-127935 hydrochloride, amiodarone hydrochloride in GC and BRD-K55722623, BRD-K13169950, and AY 9944 in DGC as the most effective treatments, providing cues for the design of combined pharmacological treatments. By integrating genetic and epigenetic aspects with their expected functional outcome, we unveiled promising targets for combinatorial pharmacological treatments of GC.

High SERPINH1 expression predicts poor prognosis in lung adenocarcinoma

Background

Serpine Protease Inhibitorclade H1 (SERPINH1) is abnormally expressed in a variety of tumor tissues and is linked to the biological processes of tumorigenesis, migration, invasion, and metastasis. SERPINH1 expression and prognosis in malignant tumors, such as gastric, colorectal, and breast cancers, have previously been studied, but the gene has not yet been investigated in lung adenocarcinoma (LUAD) in terms of prognosis and the potential mechanisms of action.

Methods

SERPINH1 was identified as an independent prognostic factor for LUAD in The Cancer Genome Atlas (TCGA) cohort and Affiliated Hospital of Nantong University (NTU) cohort (the LUAD data set) by univariate and multivariate Cox regression analyses. Additionally, we performed immunohistochemical staining to analyze the expression of SERPINH1 in LUAD and normal lung tissue. Based on the TCGA database, we analyzed the correlation of this gene with the tumor mutation burden (TMB), tumor microenvironment, immune infiltration, immune checkpoints, and anti-tumor drugs using the R language-related R package.

Results

SERPINH1 was highly expressed in LUAD tissue. Kaplan-Meier survival curves in both the TCGA cohort and the NTU cohort showed that the SERPINH1 low-expression group had a higher survival rate than the high-expression group. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of the SERPINH1 co-expressed genes revealed that the gene was associated with the extracellular matrix and cell proliferation and migration. The analysis of SERPINH1 and the TMB revealed a superior survival advantage for patients with high TMB and high SERPINH1 expression, and worse survival for those with low TMB and high SERPINH1 expression. The analysis of the tumor microenvironment (TME) and immune infiltration revealed that the high and low expression of SERPINH1 was associated with different immune infiltration characteristics. The analysis of the immune checkpoints and anti-tumor drugs showed that immunotherapy and anti-neoplastic treatment were more efficacious in the high SERPINH1 expression group than the low SERPINH1 expression group.

Conclusions

Using LUAD tissues and clinical samples, we showed that SERPINH1 can be used as a prognostic biomarker for LUAD. Our findings provide a new approach and strategy for the clinical treatment of LUAD patients.

SERPINH1 is a Potential Prognostic Biomarker and Correlated With Immune Infiltration: A Pan-Cancer Analysis

Background: Serpin peptidase inhibitor clade H, member 1 (SERPINH1) is a gene encoding a member of the serpin superfamily of serine proteinase inhibitors. The upregulated of SERPINH1 was associated with poor prognosis in breast cancer, stomach adenocarcinoma, and esophageal carcinoma. However, the role of SERPINH1 in pan-cancer is largely unexplored.

Methods: SERPINH1 expression and the correlation with prognosis in human pan-cancer were analyzed by the Cancer Genome Atlas and the Genotype-Tissue Expression dataset. Pearson correlation analysis was applied to evaluate the role of SERPINH1 expression in tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), DNA methyltransferase, and common immunoregulators. Spearman’s correlation test was used to analysis SERPINH1 expression in tumor immune infiltration and infiltrating immune cells via the Tumor Immune Evaluation Resource database. Furtherly, immunohistochemistry staining of SERPINH1 was acquired from the Human Protein Atlas database for validation.

Results: SERPINH1 was abnormally expressed in fourteen cancers. The high expression of SERPINH1 significantly reduced the overall survival (OS), disease-specific survival, and progression free interval in eleven cancers. Moreover, SERPINH1 expression was correlated with MMR, MSI, TMB, and DNA methylation in multiple types of cancer. Also, SERPINH1 expression showed strong association with immunoregulators and immune checkpoint markers in testicular germ cell tumors, brain lower grade glioma (LGG), pheochromocytoma and paraganglioma. In addition, SERPINH1 expression was related to immune cell infiltration in multiple cancers, particularly in breast invasive carcinoma, LGG, and liver hepatocellular carcinoma. The result of immunohistochemistry verification shown that SERPINH1 staining was higher in tumor samples than in normal tissue in colon adenocarcinoma, head and neck squamous cell carcinoma, kidney renal papillary cell carcinoma and cervical squamous cell carcinoma, which was consistent with the result of OS.

Conclusion: Overall, these results indicate that SERPINH1 may serve as an important prognostic biomarker and correlate with tumor immunity in human pan-cancer.

Identification and Validation of Biglycan as Prognosis and Therapy Markers for Patients with Stomach Adenocarcinoma

OBJECTIVE

Previous studies have confirmed the biglycan (BGN) as a core gene in stomach adenocarcinoma (STAD). Present study aimed at conducting further investigations to reveal the potential function of BGN in STAD.

METHODS

The mRNA and protein expressions of BGN in STAD were firstly evaluated, followed by immune infiltration analyses. The influence of BGN expression on the overall survival of STAD patients was subsequently analyzed, and a restrict survival analysis was performed as well. The protein-protein interaction (PPI) network analysis on the co-expressed genes with BGN was finally adopted to obtain the most important module in the whole network, and significant Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway associated with hub genes within the main module was further predicted.

RESULTS

(1) We verified the mRNA high expression of BGN in STAD (all P<0.05), and higher expression was observed in patients with stage 4 (P<0.001) and grade 3 (P<0.001). The BGN protein was mainly localized to the golgi apparatus, and protein expression displayed an individual difference. (2) Immune infiltration analysis showed the strongest correlation between BGN expression and abundance of natural killer cell (P<0.001), Transforming Growth Factor beta 1 (TGFB1) (P<0.001), TNF Receptor Superfamily Member 4 (TNFRSF4) (P<0.001) and C-X-C Motif Chemokine Ligand 12 (CXCL12) (P<0.001) in STAD. BGN expression was also correlated to immune subtypes (P=0.0347) and molecular subtypes (P=0.0263) in STAD. (3) High expression of BGN shortened the overall survival time of STAD patients (all P<0.01). The influence of BGN expression on the prognosis was statistically affected by several clinical phenotypes and cohorts of patients. Cox regression showed that BGN can be considered as a prognostic predictor of STAD (P<0.05). (4) Pathway analysis indicated that BGN possibly participated in ECM-receptor interaction, focal adhesion, human papillomavirus infection and PI3K-Akt signaling pathway (all P<0.001).

CONCLUSION

BGN was highly expressed in STAD, implying a poor prognosis of patients. Relevant signal pathways associated with BGN were distinguished as well. BGN could be used as a potential therapeutic biomarker for STAD.

Upregulation of HOXC9 generates interferon-gamma resistance in gastric cancer by inhibiting the DAPK1/RIG1/STAT1 axis

Clinical reports indicate that gastric cancer (GC) has a high mortality rate, but its pathological mechanism remains poorly understood. This work integrated bioinformatics analysis with experimental verification to explore novel biomarkers of gastric cancer. First, weighted gene coexpression network analysis was applied to screen significant genes correlated with GC development. Gene set enrichment analysis was also used to unearth the most relevant biological functions of significant genes. As a result, we discovered homeobox C9 (HOXC9) as a novel oncogene in GC, primarily through negatively regulating immune response. High expression of HOXC9 predicted a poor prognosis in GC patients, and knocking down HOXC9 efficiently enhanced the interferon‐gamma (IFNγ)‐dependent apoptosis in two GC cell lines as well as organoids from patients. Furthermore, cleaved caspase‐3/7 and phosphorylated signal transducer and activator of transcription 1 (p‐STAT1) were also significantly enhanced in HOXC9 knockdown cells and organoids treated with IFNγ. Mechanistically, we found that HOXC9 inhibited the death‐associated protein kinase 1 (DAPK1) and its downstream retinoic acid‐inducible gene‐I (RIG1) to generate GC IFNγ resistance. In summary, we identified and confirmed that HOXC9 generates IFNγ resistance in GC by inhibiting the DAPK1/RIG1/p‐STAT1 axis.