In-silico study reveals immunological signaling pathways, their genes, and potential herbal drug targets in ovarian cancer

Krishnamoorthy, Praveen; Kamal, Mohammad Azhar; Warsi, Mohiuddin Khan; Alnajeebi, Afnan M.; Ali, Haytham A.; Helmi, Nawal; Izhari, Mohammad Asrar; Mustafa, Saad; Firoz, Ahmad; Mobashir, Mohammad

doi:10.1016/j.imu.2020.100422

Cited by 18 publications

(9 citation statements)

References 38 publications

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“…Li and Tang found that low levels of CDKN1B are associated with a poor prognosis in epithelial ovarian carcinoma [ 21 ]. GNAI3 is involved in the immune pathway in OC [ 22 ]. DNAJB1 and RHEB expressions have also been reported to be affected in OC [ 23 , 24 ].…”

Section: Discussionmentioning

confidence: 99%

Effects of Autophagy-Related Genes on the Prognosis and Immune Microenvironment of Ovarian Cancer

Zhang

2022

BioMed Research International

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Ovarian cancer (OC) is among the most malignant tumors of the female reproductive system. The role of autophagy in cancer is complex, and the functional relationship between autophagy-related genes and OC remains unclear. Here, the prognostic value of autophagy-related genes in OC and relationships between autophagy and immune function were evaluated. OC data from The Cancer Genome Atlas and the Human Autophagy Database were obtained to identify autophagy-related genes. Univariate and multivariate Cox analyses were used to construct a prognostic model based on autophagy-related genes. Relationships between risk scores and clinical traits were evaluated. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Cytoscape were used to analyze gene functions and their effects on the immune microenvironment. Relationships between autophagy genes and long noncoding RNAs (lncRNAs) were evaluated by Pearson’s correlation coefficients, and lncRNAs corresponding to the autophagy-related genes associated with OC prognosis were used to construct a model. Relationships between risk scores and survival and prognosis were evaluated. Finally, a gene set enrichment analysis was performed. Seven autophagy-related genes (CAPN1, CDKN1B, DNAJB1, GNAI3, MTMR14, RHEB, and SIRT2) were identified as independent predictors of prognosis. Three lncRNAs corresponding to autophagy genes independently influenced prognosis. Autophagy genes are closely related to immunity. Fifteen immune cell types showed different levels of infiltration between the high- and low-risk groups. Moreover, immune cell infiltration differed between the high- and low-risk groups based on the model. Our analysis of genes and lncRNAs related to prognosis clarifies the role of autophagy in OC and provides a theoretical basis for further research.

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Section: Discussionmentioning

confidence: 99%

Effects of Autophagy-Related Genes on the Prognosis and Immune Microenvironment of Ovarian Cancer

Zhang

2022

BioMed Research International

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“…We have described the fold change, and, by considering genes as DEGs, we have applied thresholds for FC >= +2.0 (upregulated genes) and FC <= -2.0 (downregulated genes); these DEGs have been considered for pathway enrichment analysis. But for heatmap and network presentations, the top 100 DEGs (50 up and 50 down) genes have been presented (76,77).…”

Section: Methodsmentioning

confidence: 99%

In-Silico Study of Immune System Associated Genes in Case of Type-2 Diabetes With Insulin Action and Resistance, and/or Obesity

et al. 2021

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Type-2 diabetes and obesity are among the leading human diseases and highly complex in terms of diagnostic and therapeutic approaches and are among the most frequent and highly complex and heterogeneous in nature. Based on epidemiological evidence, it is known that the patients suffering from obesity are considered to be at a significantly higher risk of type-2 diabetes. There are several pieces of evidence that support the hypothesis that these diseases interlinked and obesity may aggravate the risk(s) of type-2 diabetes. Multi-level unwanted alterations such as (epi-) genetic alterations, changes at the transcriptional level, and altered signaling pathways (receptor, cytoplasmic, and nuclear level) are the major sources that promote several complex diseases, and such a heterogeneous level of complexity is considered as a major barrier in the development of therapeutics. With so many known challenges, it is critical to understand the relationships and the shared causes between type-2 diabetes and obesity, and these are difficult to unravel and understand. For this purpose, we have selected publicly available datasets of gene expression for obesity and type-2 diabetes, have unraveled the genes and the pathways associated with the immune system, and have also focused on the T-cell signaling pathway and its components. We have applied a simplified computational approach to understanding differential gene expression and patterns and the enriched pathways for obesity and type-2 diabetes. Furthermore, we have also analyzed genes by using network-level understanding. In the analysis, we observe that there are fewer genes that are commonly differentially expressed while a comparatively higher number of pathways are shared between them. There are only 4 pathways that are associated with the immune system in case of obesity and 10 immune-associated pathways in case of type-2 diabetes, and, among them, only 2 pathways are commonly altered. Furthermore, we have presented SPNS1, PTPN6, CD247, FOS, and PIK3R5 as the overexpressed genes, which are the direct components of TCR signaling.

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“…The principle of enriched pathways remains similar to DAVID database where we have a list of background and target genes. The complete approach for this study has been presented in Figure 1A which was also applied for the previous study (Kamal et al, 2020;Kumar et al, 2020;Warsi et al 2020;Eldakhakhny et al, 2021).…”

Section: Methodsmentioning

confidence: 99%

Gene Expression Profiling of Early Acute Febrile Stage of Dengue Infection and Its Comparative Analysis With Streptococcus pneumoniae Infection

Bajrai

Sohrab

Alandijany

et al. 2021

Front. Cell. Infect. Microbiol.

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Infectious diseases are the disorders caused by organisms such as bacteria, viruses, fungi, or parasites. Although many of them are permentantly hazardous, a number of them live in and on our bodies and they are normally harmless or even helpful. Under certain circumstances, some organisms may cause diseases and these infectious diseases may be passed directly from person to person or via intermediate vectors including insects and other animals. Dengue virus and Streptococcus pneumoniae are the critical and common sources of infectious diseases. So, it is critical to understand the gene expression profiling and their inferred functions in comparison to the normal and virus infected conditions. Here, we have analyzed the gene expression profiling for dengue hemorrhagic fever, dengue fever, and normal human dataset. Similar to it, streptococcus pneumoniae infectious data were analyzed and both the outcomes were compared. Our study leads to the conclusion that the dengue hemorrhagic fever arises in result to potential change in the gene expression pattern, and the inferred functions obviously belong to the immune system, but also there are some additional potential pathways which are critical signaling pathways. In the case of pneumoniae infection, 19 pathways were enriched, almost all these pathways are associated with the immune system and 17 of the enriched pathways were common with dengue infection except platelet activation and antigen processing and presentation. In terms of the comparative study between dengue virus and Streptococcus pneumoniae infection, we conclude that cell adhesion molecules (CAMs), MAPK signaling pathway, natural killer cell mediated cytotoxicity, regulation of actin cytoskeleton, and cytokine-cytokine receptor interaction are commonly enriched in all the three cases of dengue infection and Streptococcus pneumoniae infection, focal adhesion was enriched between classical dengue fever — dengue hemorrhagic fever, dengue hemorrhagic fever—normal samples, and SP, and antigen processing and presentation and Leukocyte transendothelial migration were enriched in classical dengue fever —normal samples, dengue hemorrhagic fever—normal samples, and Streptococcus pneumoniae infection.

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In-silico study reveals immunological signaling pathways, their genes, and potential herbal drug targets in ovarian cancer

Cited by 18 publications

References 38 publications

Effects of Autophagy-Related Genes on the Prognosis and Immune Microenvironment of Ovarian Cancer

Effects of Autophagy-Related Genes on the Prognosis and Immune Microenvironment of Ovarian Cancer

In-Silico Study of Immune System Associated Genes in Case of Type-2 Diabetes With Insulin Action and Resistance, and/or Obesity

Gene Expression Profiling of Early Acute Febrile Stage of Dengue Infection and Its Comparative Analysis With Streptococcus pneumoniae Infection

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