Piwi-interacting RNAs (piRNAs) as potential biomarkers and therapeutic targets for cardiovascular diseases

Abstract Background Gliomas account for the majority of fatal primary brain tumors, and there is much room for research in the underlying pathogenesis, the multistep progression of glioma, and how to improve survival. In our study, we aimed to identify potential biomarkers or therapeutic targets of glioma and study the mechanism underlying the tumor progression. Methods We downloaded the microarray datasets (GSE43378 and GSE7696) from the Gene Expression Omnibus (GEO) database. Then, we used weighted gene co-expression network analysis (WGCNA) to screen potential biomarkers or therapeutic targets related to the tumor progression. ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumors using Expression data) algorithm and TIMER (Tumor Immune Estimation Resource) database were used to analyze the correlation between the selected genes and the tumor microenvironment. Real-time reverse transcription polymerase chain reaction was used to measure the selected gene. Transwell and wound healing assays were used to measure the cell migration and invasion capacity. Western blotting was used to test the expression of epithelial-mesenchymal transition (EMT) related markers. Results We identified specific module genes that were positively correlated with the WHO grade but negatively correlated with OS of glioma. Importantly, we identified that 6 collagen genes (COL1A1, COL1A2, COL3A1, COL4A1, COL4A2, and COL5A2) could regulate the immunosuppressive microenvironment of glioma. Moreover, we found that these collagen genes were significantly involved in the EMT process of glioma. Finally, taking COL3A1 as a further research object, the results showed that knockdown of COL3A1 significantly inhibited the migration, invasion, and EMT process of SHG44 and A172 cells. Conclusions In summary, our study demonstrated that collagen genes play an important role in regulating the immunosuppressive microenvironment and EMT process of glioma and could serve as potential therapeutic targets for glioma management.

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Intestinal bacteria are potential biomarkers and therapeutic targets for gastric cancer

Microbial Pathogenesis ◽

10.1016/j.micpath.2021.104747 ◽

2021 ◽

Vol 151 ◽

pp. 104747

Author(s):

Shili Liu ◽

Jianjian Dai ◽

Xiang Lan ◽

Bingbing Fan ◽

Tianyi Dong ◽

...

Keyword(s):

Gastric Cancer ◽

Therapeutic Targets ◽

Intestinal Bacteria ◽

Potential Biomarkers

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Proteotranscriptomic Profiling of 231-BR Breast Cancer Cells: Identification of Potential Biomarkers and Therapeutic Targets for Brain Metastasis

Molecular & Cellular Proteomics ◽

10.1074/mcp.m114.046110 ◽

2015 ◽

Vol 14 (9) ◽

pp. 2316-2330 ◽

Cited By ~ 33

Author(s):

Matthew D. Dun ◽

Robert J. Chalkley ◽

Sam Faulkner ◽

Sheridan Keene ◽

Kelly A. Avery-Kiejda ◽

...

Keyword(s):

Breast Cancer ◽

Brain Metastasis ◽

Cancer Cells ◽

Breast Cancer Cells ◽

Therapeutic Targets ◽

Potential Biomarkers

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GPCRomics: GPCR Expression in Cancer Cells and Tumors Identifies New, Potential Biomarkers and Therapeutic Targets

Frontiers in Pharmacology ◽

10.3389/fphar.2018.00431 ◽

2018 ◽

Vol 9 ◽

Cited By ~ 45

Author(s):

Paul A. Insel ◽

Krishna Sriram ◽

Shu Z. Wiley ◽

Andrea Wilderman ◽

Trishna Katakia ◽

...

Keyword(s):

Cancer Cells ◽

Therapeutic Targets ◽

Potential Biomarkers

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Bioinformatic analysis identifies potential biomarkers and therapeutic targets of septic-shock-associated acute kidney injury

Hereditas ◽

10.1186/s41065-021-00176-y ◽

2021 ◽

Vol 158 (1) ◽

Author(s):

Yun Tang ◽

Xiaobo Yang ◽

Huaqing Shu ◽

Yuan Yu ◽

Shangwen Pan ◽

...

Keyword(s):

Gene Expression ◽

Septic Shock ◽

Acute Kidney Injury ◽

Molecular Mechanisms ◽

Therapeutic Targets ◽

Kidney Injury ◽

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Blood Samples ◽

Potential Biomarkers

Abstract Background Sepsis and septic shock are life-threatening diseases with high mortality rate in intensive care unit (ICU). Acute kidney injury (AKI) is a common complication of sepsis, and its occurrence is a poor prognostic sign to septic patients. We analyzed co-differentially expressed genes (co-DEGs) to explore relationships between septic shock and AKI and reveal potential biomarkers and therapeutic targets of septic-shock-associated AKI (SSAKI). Methods Two gene expression datasets (GSE30718 and GSE57065) were downloaded from the Gene Expression Omnibus (GEO). The GSE57065 dataset included 28 septic shock patients and 25 healthy volunteers and blood samples were collected within 0.5, 24 and 48 h after shock. Specimens of GSE30718 were collected from 26 patients with AKI and 11 control patents. AKI-DEGs and septic-shock-DEGs were identified using the two datasets. Subsequently, Gene Ontology (GO) functional analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed to elucidate molecular mechanisms of DEGs. We also evaluated co-DEGs and corresponding predicted miRNAs involved in septic shock and AKI. Results We identified 62 DEGs in AKI specimens and 888, 870, and 717 DEGs in septic shock blood samples within 0.5, 24 and 48 h, respectively. The hub genes of EGF and OLFM4 may be involved in AKI and QPCT, CKAP4, PRKCQ, PLAC8, PRC1, BCL9L, ATP11B, KLHL2, LDLRAP1, NDUFAF1, IFIT2, CSF1R, HGF, NRN1, GZMB, and STAT4 may be associated with septic shock. Besides, co-DEGs of VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 coupled with corresponding predicted miRNAs, especially miR-29b-3p, miR-152-3p, and miR-223-3p may be regarded as promising targets for the diagnosis and treatment of SSAKI in the future. Conclusions Septic shock and AKI are related and VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 genes are significantly associated with novel biomarkers involved in the occurrence and development of SSAKI.

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