A systems biology approach to pathogenesis of gastric cancer: gene network modeling and pathway analysis

Investigation of guanidino acetic acid and rumen-protected methionine induced improvements in longissimus lumborum muscle quality in beef cattle

This study examined the impact of dietary guanidino acetic acid (GAA) and rumen-protected methionine (RPM) on beef quality in Simmental bulls. For 140 days, forty-five bulls (453.43 ± 29.05 kg) were randomly divided into control (CON), 0.1% GAA (GAA), and 0.1% GAA + 0.1% RPM (GAM) groups with 15 bulls in each group and containing 3 pen with 5 bulls in each pen. Significant improvements in eye muscle area, pH48h, redness (a*) value, and crude protein (CP) content of longissimus lumborum (LL) muscles were observed in the GAA and GAM groups (P < 0.05). Conversely, the lightness (L*) value, drip loss, cooking loss, and moisture contents decreased (P < 0.05). Additionally, glutathione (GSH) and glutathione peroxidase (GSH-PX) concentrations of LL muscles in GAM were higher (P < 0.05), while malondialdehyde (MDA) content of LL muscles in GAA and GAM groups were lower (P < 0.05). Polyunsaturated fatty acids (PUFA) profiles were enriched in beef from GAM group (P < 0.05). The addition of GAA and RPM affected the expression of genes in LL muscle, such as HMOX1, EIF4E, SCD5, and NOS2, which are related to hypoxia metabolism, protein synthesis, and unsaturated fatty acid synthesis-related signaling pathways. In addition, GAA and RPM also affected the content of a series of metabolites such as L-tyrosine, L-tryptophan, and PC (O-16:0/0:0) involved in amino acid and lipid metabolism-related signaling pathways. In summary, GAA and RPM can improve the beef quality and its nutritional composition. These changes may be related to changes in gene expression and metabolic pathways related to protein metabolism and lipid metabolism in beef.

Identification ATP5F1D as a Biomarker Linked to Diagnosis, Prognosis, and Immune Infiltration in Endometrial Cancer Based on Data-Independent Acquisition (DIA) Analysis

In developed countries, endometrial cancer (EC) is the most prevalent gynecological cancer. ATP5F1D is a subunit of ATP synthase, as well as an important component of the mitochondrial electron transport chain (ETC). ETC plays a compelling role in carcinogenesis. To date, little is known about the role of ATP5F1D in EC. We undertook data-independent acquisition mass spectrometry (DIA-MS) of 20 EC patients, comprising 10 high-grade and 10 low-grade cancer tissues. Biological functions of differentially expressed genes (DEGs) were analyzed by GO and KEGG. The expression level, clinicopathological features, diagnostic potency, prognostic value, RNA modifications, immune characteristics, and therapy response of ATP5F1D were investigated. In total, 77 DEGs were acquired by DIA analysis, which were closely related to regulating immune response and metabolic pathways. Among the five genes (NDUFB8, SLC26A2, RAF1, ATP5F1D, and GSTM5) involving in reactive oxygen species pathway, ATP5F1D showed the most significant differential expression (2.903-fold change). We found ATP5F1D had a high diagnostic value and was associated with a favorable prognosis in EC patients. After analyzing the RNA modifications of ATP5F1D, revealing a negative regulation between them. Additionally, ATP5F1D was closely related to tumor immune infiltration. Our results suggested T-cell dysfunction and TAM-M2 polarization might be the important mechanisms of ATP5F1D to facilitate tumor immune escape. Noticeably, EC patients with ATP5F1D-high expression had better immune treatment responses and were more sensitive to chemotherapy drugs. ATP5F1D can be used as a biomarker for diagnosis, prognosis, and immune infiltration of EC, and offers a crucial reference for personalized treatment of EC patients.

Identification of key genes and pathways involved in T-DM1-resistance in OE-19 esophageal cancer cells through bioinformatics analysis

Introduction

Esophageal Cancer (EC) ranks among the most common malignancies worldwide. Most EC patients acquire drug resistance to chemotherapy either intrinsically or acquired after T-DM1 treatment, which shows that increasing or decreasing the expression of particular genes might influence chemotherapeutic sensitivity or resistance. Therefore, gaining a deeper understanding of the altered expression of genes involved in EC drug resistance and developing new therapeutic methods are essential targets for continued advancement in EC therapy.

Methods

The present study aimed to find critical regulatory genes/pathways in the progression of T-DM1 resistance in OE-19 EC cells. Expression datasets were extracted from GEO omnibus. Gene interactions were analyzed, and the protein-protein interaction network was drawn. Then, enrichment analysis of the hub genes and network cluster analysis of the hub genes was performed. Finally, the genes were screened in the DrugBank database as therapeutic targets and molecular docking analysis was done on the selected targets.

Results

In the current study, nine hub genes were identified in TDM-1-resistant EC cells (CTGF, CDH17, THBS1, CXCL8, NRP1, ITGB5, EDN1, FAT1, and PTGS2). The KEGG analysis highlighted the IL-17 signaling pathway and ECM-receptor interaction pathway as the most critical pathways; cluster analysis also showed the significance of these pathways. Therefore, the genes involved in these two pathways, including CXCL8, FSCN1, PTGS2, SERPINE2, LEF1, THBS1, CCN2, TAGLN, CDH11, and ITGA6, were searched in DrugBank as therapeutic targets. The DrugBank analysis suggests a potential role for Nonsteroidal Anti-Inflammatory Drugs (NSAIDs) in reducing T-DM1 drug resistance in EC. The docking results revealed that NSAIDs, including Diclofenac, Mefenamic acid, Celecoxib, Naproxen, and Etoricoxib, significantly suppress resistant cancer cells.

Conclusion

This comprehensive bioinformatics analysis deeply explains the molecular mechanisms governing TDM-1 resistance in EC. The identified hub genes and their associated pathways offer potential targets for therapeutic interventions. Moreover, the possible role of NSAIDs in mitigating T-DM1 resistance presents an intriguing avenue for further investigation. This research contributes significantly to the field and establishes a basis for further research to enhance treatment efficacy for EC patients.

Raman fiber-optic probe for rapid diagnosis of gastric and esophageal tumors with machine learning analysis or similarity assessments: a comparative study

Gastric and esophageal cancers, the predominant forms of upper gastrointestinal malignancies, contribute significantly to global cancer mortality. Routine detection methods, including medical imaging, endoscopic examination, and pathological biopsy, often suffer from drawbacks such as low sensitivity and laborious and complex procedures. Raman spectroscopy is a non-invasive and label-free optical technique that provides highly sensitive biomolecular information to facilitate effective tumor identification. In this work, we report the use of fiber-optic Raman spectroscopy for the accurate and rapid diagnosis of gastric and esophageal cancers. Using a database of 14,000 spectra from 140 ex vivo tissue pieces of both tumor and normal tissue samples, we compare the random forest (RF) and our established Euclidean distance Raman spectroscopy (EDRS) model. The RF analysis achieves a sensitivity of 85.23% and an accuracy of 83.05% in diagnosing gastric tumors. The EDRS algorithm with improved diagnostic transparency further increases the sensitivity to 92.86% and accuracy to 89.29%. When these diagnostic protocols are extended to esophageal tumors, the RF and EDRS models achieve accuracies of 71.27% and 93.18%, respectively. Finally, we demonstrate that fewer than 20 spectra are sufficient to achieve good Raman diagnostic accuracy for both tumor tissues. This optimizes the balance between acquisition time and diagnostic performance. Our work, although conducted on ex vivo tissue models, offers valuable insights for in vivo in situ endoscopic Raman diagnosis of gastric and esophageal cancer lesions in the future. Our study provides a robust, rapid, and convenient method as a new paradigm in in vivo endoscopic medical diagnostics that integrates spectroscopic techniques and a Raman probe for detecting upper gastrointestinal malignancies.

Essential cancer protein identification using graph-based random walk with restart

Protein-protein interaction (PPI) network analysis holds significant promise for cancer diagnosis and drug target identification. This paper introduces a novel random walk-based method called essential cancer protein identification using graph-based random walk with restart (EPI-GBRWR) to address this gap. This proposed method incorporates local and global topological features of proteins, enhancing the accuracy of essential protein identification in PPI networks. Starting with meticulous preprocessing of cancer gene datasets from NCBI, including breast, lung, colorectal, and ovarian cancers, and identifying a core set of common genes. The proposed method constructs PPI networks to capture complex protein interactions from these common cancer genes. Topological analysis, including a centrality measures matrix, is generated to perform the analysis to identify essential nodes. The study revealed that 40 essential proteins among breast, colorectal, lung and ovarian cancer showcase the potency of integrative methodologies in unravelling cancer complexity, signalling a transformative era in cancer research and treatment. The strength of the findings from the study has direct clinical relevance in cancer diseases. It contributes to the field of precision medicine to guide personalized treatment strategies.

Mitochondria: a new intervention target for tumor invasion and metastasis

Mitochondria, responsible for cellular energy synthesis and signal transduction, intricately regulate diverse metabolic processes, mediating fundamental biological phenomena such as cell growth, aging, and apoptosis. Tumor invasion and metastasis, key characteristics of malignancies, significantly impact patient prognosis. Tumor cells frequently exhibit metabolic abnormalities in mitochondria, including alterations in metabolic dynamics and changes in the expression of relevant metabolic genes and associated signal transduction pathways. Recent investigations unveil further insights into mitochondrial metabolic abnormalities, revealing their active involvement in tumor cell proliferation, resistance to chemotherapy, and a crucial role in tumor cell invasion and metastasis. This paper comprehensively outlines the latest research advancements in mitochondrial structure and metabolic function. Emphasis is placed on summarizing the role of mitochondrial metabolic abnormalities in tumor invasion and metastasis, including alterations in the mitochondrial genome (mutations), activation of mitochondrial-to-nuclear signaling, and dynamics within the mitochondria, all intricately linked to the processes of tumor invasion and metastasis. In conclusion, the paper discusses unresolved scientific questions in this field, aiming to provide a theoretical foundation and novel perspectives for developing innovative strategies targeting tumor invasion and metastasis based on mitochondrial biology.

CTGF, FN1, IL-6, THBS1, and WISP1 genes and PI3K-Akt signaling pathway as prognostic and therapeutic targets in gastric cancer identified by gene network modeling

OBJECTIVE

Gastric cancer (GC) is one of the most common malignancies worldwide and it is considered the fourth most common cause of cancer death. This study aimed to find critical genes/pathways in GC pathogenesis to be used as biomarkers or therapeutic targets.

METHODS

Differentially expressed genes were explored between human gastric cancerous and noncancerous tissues, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes signaling pathway enrichment analyses were done. Hub genes were identified based on the protein-protein interaction network constructed in the STRING database with Cytoscape software. The hub genes were selected for further investigation using GEPIA2 and DrugBank databases.

RESULTS

Ten overexpressed hub genes in GC were identified in the current study, including FN1, TP53, IL-6, CXCL5, ELN, ADAMTS2, WISP1, MMP2, CTGF, and THBS1. The study demonstrated the PI3K-Akt pathway's central involvement in GC, with pronounced alterations in essential components. Survival analysis revealed significant correlations between CTGF, FN1, IL-6, THBS1, and WISP1 overexpression and reduced overall survival times in GC patients.

CONCLUSION

A mutual interplay emerged, where PI3K-Akt signaling could upregulate certain genes, forming feedback loops and intensifying cancer phenotypes. The interconnected overexpression of genes and the PI3K-Akt pathway fosters gastric tumorigenesis, suggesting therapeutic potential. DrugBank analysis identified limited FDA-approved drugs, advocating for further exploration while targeting these hub genes could reshape GC treatment. The identified genes could be novel diagnostic/prognostic biomarkers or potential therapeutic targets for GC, but further clinical validation is required.