Modeling osteosarcoma progression by measuring the connectivity dynamics using an inference of multiple differential modules algorithm

Effect of PTGES3 on the Prognosis and Immune Regulation in Lung Adenocarcinoma

Background

PTGES3 is upregulated in multiple cancer types and promotes tumorigenesis and progression. However, the clinical outcome and immune regulation of PTGES3 in lung adenocarcinoma (LUAD) are not fully understood. This study aimed to explore the expression level and prognostic value of PTGES3 and its correlation with potential immunotherapy in LUAD.

Methods

All data were obtained from several databases, including the Cancer Genome Atlas database. Firstly, gene and protein expression of PTGES3 were analyzed using Tumor Immune Estimation Resource (TIMER), R software, Clinical Proteomic Tumor Analysis Consortium (CPTAC), and Human Protein Atlas (HPA). Thereafter, survival analysis was conducted using the R software, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and Kaplan-Meier Plotter. In addition, gene alteration and mutation analyses were conducted using the cBio Cancer Genomics Portal (cBioPortal) and Catalog of Somatic Mutations in Cancer (COSMIC) databases. The molecular mechanisms associated with PTGES3 were assessed via Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), GeneMANIA, GEPIA2, and R software. Lastly, the role of PTGES3 in immune regulation in LUAD was investigated using TIMER, Tumor-Immune System Interaction Database (TISIDB), and SangerBox.

Results

The gene and protein expression of PTGES3 were elevated in LUAD tissues and compared to the normal tissues, and the high expression of PTGES3 was correlated with cancer stage and tumor grade. Survival analysis revealed that overexpression of PTGES3 was associated with poor prognosis of LUAD patients. Moreover, gene alteration and mutation analysis revealed the occurrence of several types of PTGES3 gene alterations in LUAD. Moreover, co-expression analysis and cross-analysis revealed that three genes, including CACYBP, HNRNPC, and TCP1, were correlated and interacted with PTGES3. Functional analysis of these genes revealed that PTGES3 was primarily enriched in oocyte meiosis, progesterone-mediated oocyte maturation, and arachidonic acid metabolism pathways. Furthermore, we found that PTGES3 participated in a complex immune regulation network in LUAD.

Conclusion

The current study indicated the crucial role of PTGES3 in LUAD prognosis and immune regulation. Altogether, our results suggested that PTGES3 could serve as a promising therapeutic and prognosis biomarker for the LUAD.

Exploration of Flavonoids as Lead Compounds against Ewing Sarcoma through Molecular Docking, Pharmacogenomics Analysis, and Molecular Dynamics Simulations

Ewing sarcoma (ES) is a highly malignant carcinoma prevalent in children and most frequent in the second decade of life. It mostly occurs due to t(11;22) (q24;q12) translocation. This translocation encodes the oncogenic fusion protein EWS/FLI (Friend leukemia integration 1 transcription factor), which acts as an aberrant transcription factor to deregulate target genes essential for cancer. Traditionally, flavonoids from plants have been investigated against viral and cancerous diseases and have shown some promising results to combat these disorders. In the current study, representative flavonoid compounds from various subclasses are selected and used to disrupt the RNA-binding motif of EWS, which is required for EWS/FLI fusion. By blocking the RNA-binding motif of EWS, it might be possible to combat ES. Therefore, molecular docking experiments validated the binding interaction patterns and structural behaviors of screened flavonoid compounds within the active region of the Ewing sarcoma protein (EWS). Furthermore, pharmacogenomics analysis was used to investigate potential drug interactions with Ewing sarcoma-associated genes. Finally, molecular dynamics simulations were used to investigate the stability of the best selected docked complexes. Taken together, daidzein, kaempferol, and genistein exhibited a result comparable to ifosfamide in the proposed in silico study and can be further analyzed as possible candidate compounds in biological in vitro studies against ES.

High expression of PTGES3 is an independent predictive poor prognostic biomarker and correlates with immune infiltrates in lung adenocarcinoma

BACKGROUND

Immune-infiltration was positively relationship with overall survival in lung adenocarcinoma (LUAD). Nevertheless, the potential clinical value of PTGES3, especially in terms of prognosis and tumor immune-infiltration in LUAD had not been fully elucidated.

METHODS

Original data available from TCGA and GEO databases and integrated via R3.6.3. Kaplan-Meier and Cox regression methods were used to examine the effect of PTGES3 expression in overall survival, and nomogram was performed to illustrate the correlation between the PTGES3 expression and the risk of LUAD. The associate between PTGES3 and cancer immune characteristics were analyzed via the TISIDB databases. Western blot and RT-qPCR were used to analyze PTGES3 expression in the clinical lung adenocarcinoma tissue samples or non-small cell lung cancer cell lines.

RESULTS

PTGES3 mRNA and protein expression were significantly elevated in LUAD compared with normal lung tissues. Up-regulated PTGES3 was significantly associated with pathologic stage and TM stage. Kaplan-Meier survival analysis and subgroup analysis showed that up-regulated PTGES3 was associated with a worse overall survival of LUAD (HR = 1.71 (1.27-2.31), p < 0.001). Multivariate Cox analysis showed that high PTGES3 expression was an independent factor affecting overall survival (HR = 1.64 (1.14-2.37), p < 0.001). GO and KEGG analysis revealed that the cell cycle, regulation of DNA replication, and regulation of innate immune response were enriched. A positive correlation between PTGES3 expression and immune infiltrating levels of Th2 cells was found.

CONCLUSION

PTGES3 may play an important role in the cell cycle and as an independent predictive prognostic biomarker correlates with immune infiltrates in lung adenocarcinoma.

Botanical Drug Puerarin Ameliorates Liposaccharide-Induced Depressive Behaviors in Mice via Inhibiting RagA/mTOR/p70S6K Pathways

BACKGROUND

The depressive symptom hallmarks the progression of the neurodegenerative diseases, especially Alzheimer's disease. Bacterial infection is related to inflammation and depression. The present project thereby examined whether botanical drug puerarin could attenuate liposaccharide- (LPS-) induced depressive behaviors in mice.

METHODS

Adult male C57BL/6N mice were sequentially treated with LPS and puerarin and evaluated for the depressive behaviors by tail suspension test and forced swim test. The brain tissues were profiled for the molecular targets of puerarin by next-generation RNA sequencing technique. Candidate targets were further verified in LPS-treated mice, neural stem cells, and highly differentiated PC12 cell line.

RESULTS

Puerarin ameliorated LPS-induced depression in the mice. RNA sequencing profiles revealed that puerarin altered the expression of 16 genes while markedly downregulated Ras-related GTP-binding protein A (RagA) in LPS-treated mice. The effect of puerarin on RagA expression was confirmed by immunostaining, Western blot, and quantitative real-time PCR (qRT-PCR). Biochemical studies showed that puerarin inhibited RagA/mTOR/p70S6K pathway, attenuated the accumulation of mTORC1 in close proximity to lysosome, and reduced the production of proinflammatory cytokines.

CONCLUSIONS

Botanical drug puerarin attenuated inflammation and depressive behaviors in LPS-challenged mice by inhibiting RagA/mTOR/p70S6K pathways. Puerarin may be a lead compound for the new antidepressant drugs.

Differential Co-Expression Analyses Allow the Identification of Critical Signalling Pathways Altered during Tumour Transformation and Progression

Biological systems respond to perturbations through the rewiring of molecular interactions, organised in gene regulatory networks (GRNs). Among these, the increasingly high availability of transcriptomic data makes gene co-expression networks the most exploited ones. Differential co-expression networks are useful tools to identify changes in response to an external perturbation, such as mutations predisposing to cancer development, and leading to changes in the activity of gene expression regulators or signalling. They can help explain the robustness of cancer cells to perturbations and identify promising candidates for targeted therapy, moreover providing higher specificity with respect to standard co-expression methods. Here, we comprehensively review the literature about the methods developed to assess differential co-expression and their applications to cancer biology. Via the comparison of normal and diseased conditions and of different tumour stages, studies based on these methods led to the definition of pathways involved in gene network reorganisation upon oncogenes' mutations and tumour progression, often converging on immune system signalling. A relevant implementation still lagging behind is the integration of different data types, which would greatly improve network interpretability. Most importantly, performance and predictivity evaluation of the large variety of mathematical models proposed would urgently require experimental validations and systematic comparisons. We believe that future work on differential gene co-expression networks, complemented with additional omics data and experimentally tested, will considerably improve our insights into the biology of tumours.