Bioinformatics analysis and verification of molecular targets in ovarian cancer stem-like cells

Behera, Abhijeet; Ashraf, Rahail; Srivastava, Amit Kumar; Kumar, Sanjay

doi:10.1016/j.heliyon.2020.e04820

Cited by 9 publications

(5 citation statements)

References 75 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Protein families with ankyrin-repeat proteins ANK (logFC >0.3) and zinc finger proteins associated with cancer progression ( Scurr et al, 2008 ; Jen and Wang, 2016 ) were upregulated in EP2. EP3 showed a unique signature of interferon-stimulated genes IFIT1-3 (logFC >2.5), IFITM1-3 (logFC >0.6), and ISG15 (logFC = 2.5), previously characterized as markers of cancer stem cells (CSC) ( Behera et al, 2020 ). Detailed marker information is provided in Supplementary Table S1A .…”

Section: Resultsmentioning

confidence: 99%

Exploring the tumor micro-environment in primary and metastatic tumors of different ovarian cancer histotypes

Xie,

Olalekan,

Back

et al. 2024

Front. Cell Dev. Biol.

View full text Add to dashboard Cite

Ovarian cancer is a highly heterogeneous disease consisting of at least five different histological subtypes with varying clinical features, cells of origin, molecular composition, risk factors, and treatments. While most single-cell studies have focused on High grade serous ovarian cancer, a comprehensive landscape of the constituent cell types and their interactions within the tumor microenvironment are yet to be established in the different ovarian cancer histotypes. Further characterization of tumor progression, metastasis, and various histotypes are also needed to connect molecular signatures to pathological grading for personalized diagnosis and tailored treatment. In this study, we leveraged high-resolution single-cell RNA sequencing technology to elucidate the cellular compositions on 21 solid tumor samples collected from 12 patients with six ovarian cancer histotypes and both primary (ovaries) and metastatic (omentum, rectum) sites. The diverse collection allowed us to deconstruct the histotypes and tumor site-specific expression patterns of cells in the tumor, and identify key marker genes and ligand-receptor pairs that are active in the ovarian tumor microenvironment. Our findings can be used in improving precision disease stratification and optimizing treatment options.

show abstract

Section: Resultsmentioning

confidence: 99%

Exploring the tumor micro-environment in primary and metastatic tumors of different ovarian cancer histotypes

Xie,

Olalekan,

Back

et al. 2024

Front. Cell Dev. Biol.

View full text Add to dashboard Cite

show abstract

“…Protein families with ankyrin-repeat proteins and zinc finger proteins associated with cancer progression 19,20 were upregulated in EP2. EP3 showed a unique signature of interferon-stimulated genes IFIT1-3 (logFC > 2.5), IFITM1-3 (logFC > 0.6), and ISG15 (logFC = 2.5), previously characterized as markers of cancer stem cells (CSC) 21 . Detailed marker information is provided in Table S1A .…”

Section: Resultsmentioning

confidence: 99%

Exploring the tumor micro-environment in ovarian cancer histotypes and tumor sites

Xie,

Olalekan,

Back

et al. 2023

Preprint

View full text Add to dashboard Cite

Ovarian cancer is a highly heterogeneous disease consisting of at least five different histological subtypes with varying clinical features, cells of origin, molecular composition, risk factors, and treatments. While most single-cell studies have focused on High grade serous ovarian cancer, a comprehensive landscape of the constituent cell types and their interactions within the tumor microenvironment are yet to be established in the different ovarian cancer histotypes. Further characterization of tumor progression, metastasis, and various histotypes are also needed to connect molecular signatures to pathological grading for personalized diagnosis and tailored treatment. In this study, we leveraged high-resolution single-cell RNA sequencing technology to elucidate the cellular compositions on 21 solid tumor samples collected from 12 patients with six ovarian cancer histotypes and both primary (ovaries) and metastatic (omentum, rectum) sites. The diverse collection allowed us to deconstruct the histotypes and tumor site-specific expression patterns of cells in the tumor and identify key marker genes and ligand-receptor pairs that are active in the ovarian tumor microenvironment. Our findings can be used in improving precision disease stratification and optimizing treatment options.

show abstract

“…IFIT2 is significantly overexpressed in ovarian cancer stem cells, indicating its potential role in drug resistance in ovarian cancer. 75 Nonetheless, elevated IFIT3 expression correlates with poor survival and increased resistance to various chemotherapeutic drugs, including cisplatin in OSCC patients. 74 IFIT proteins regulate multiple complex cellular processes based on cell and tissue types.…”

Section: Discussionmentioning

confidence: 99%

“…Studies demonstrated a correlation between IFIT2 down‐regulation and EMT induction, metastasis and multi‐drug resistance in patients with oral squamous cell carcinoma (OSCC). IFIT2 is significantly overexpressed in ovarian cancer stem cells, indicating its potential role in drug resistance in ovarian cancer 75 . Nonetheless, elevated IFIT3 expression correlates with poor survival and increased resistance to various chemotherapeutic drugs, including cisplatin in OSCC patients 74 .…”

Section: Discussionmentioning

confidence: 99%

Construction of miRNA‐lncRNA‐mRNA co‐expression network affecting EMT‐mediated cisplatin resistance in ovarian cancer

Naghsh-Nilchi

Ghahnavieh

Dehghanian

2022

J Cellular Molecular Medi

View full text Add to dashboard Cite

Platinum resistance is one of the major concerns in ovarian cancer treatment. Recent evidence shows the critical role of epithelial–mesenchymal transition (EMT) in this resistance. Epithelial‐like ovarian cancer cells show decreased sensitivity to cisplatin after cisplatin treatment. Our study prospected the association between epithelial phenotype and response to cisplatin in ovarian cancer. Microarray dataset GSE47856 was acquired from the GEO database. After identifying differentially expressed genes (DEGs) between epithelial‐like and mesenchymal‐like cells, the module identification analysis was performed using weighted gene co‐expression network analysis (WGCNA). The gene ontology (GO) and pathway analyses of the most considerable modules were performed. The protein–protein interaction network was also constructed. The hub genes were specified using Cytoscape plugins MCODE and cytoHubba, followed by the survival analysis and data validation. Finally, the co‐expression of miRNA‐lncRNA‐TF with the hub genes was reconstructed. The co‐expression network analysis suggests 20 modules relating to the Epithelial phenotype. The antiquewhite4, brown and darkmagenta modules are the most significant non‐preserved modules in the Epithelial phenotype and contain the most differentially expressed genes. GO, and KEGG pathway enrichment analyses on these modules divulge that these genes were primarily enriched in the focal adhesion, DNA replication pathways and stress response processes. ROC curve and overall survival rate analysis show that the co‐expression pattern of the brown module's hub genes could be a potential prognostic biomarker for ovarian cancer cisplatin resistance.

show abstract

Bioinformatics analysis and verification of molecular targets in ovarian cancer stem-like cells

Cited by 9 publications

References 75 publications

Exploring the tumor micro-environment in primary and metastatic tumors of different ovarian cancer histotypes

Exploring the tumor micro-environment in primary and metastatic tumors of different ovarian cancer histotypes

Exploring the tumor micro-environment in ovarian cancer histotypes and tumor sites

Construction of miRNA‐lncRNA‐mRNA co‐expression network affecting EMT‐mediated cisplatin resistance in ovarian cancer

Contact Info

Product

Resources

About