<meta charset="utf8"></head><body>La expresión de TMOD3 y su papel en la progresión del cáncer de ovario

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
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			<td>cBioportal</td>
			<td>Memorial Sloan Kettering Cancer Center</td>
			<td></td>
			<td>Correlation analysis of&#160; TMOD3 with targeted miRNAs (https://www.cbioportal.org)</td>
		</tr>
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			<td>CTD database</td>
			<td>North Carolina State University</td>
			<td></td>
			<td>To analyze the relationships between chemistry, genes, phenotype, disease, and environment (https://ctdbase.org/)</td>
		</tr>
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			<td>Cytoscape</td>
			<td>National Institute of General Medical Sciences of the National Institutes of Health</td>
			<td></td>
			<td>Network Data Integration, Analysis, and Visualization (www.cytoscape.org/)</td>
		</tr>
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			<td>DAVID</td>
			<td>Frederick National Laboratory for Cancer Research</td>
			<td></td>
			<td>A comprehensive set of functional annotation tools for investigators to understand the biological meaning behind large lists of genes(https://david.ncifcrf.gov/)</td>
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			<td>GEO</td>
			<td>NCBI</td>
			<td></td>
			<td>Gene expression analysis (https://www.ncbi.nlm.nih.gov/geo/ )</td>
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			<td>HPA</td>
			<td>Knut &#38; Alice Wallenberg foundation</td>
			<td></td>
			<td>The Human Protein Atlas (HPA) database helped analyze the distribution of TMOD3 in various immune cells (https://www.proteinatlas.org/)</td>
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			<td>KM-plotter</td>
			<td>&#160;Department of Bioinformatics of the Semmelweis University</td>
			<td></td>
			<td>Prognostic Analysis (https://kmplot.com/analysis/)</td>
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			<td>LinkedOmics</td>
			<td>Baylor College of Medicine</td>
			<td></td>
			<td>A platform for biologists and clinicians to access, analyze and compare cancer multi-omics data within and across tumor types (http://www.linkedomics.org/)</td>
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			<td>PubChem database</td>
			<td>U.S. National Library of Medicine</td>
			<td></td>
			<td>To determine the definitive molecular structure of the drug</td>
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			<td>ROC Plotter</td>
			<td>&#160;Department of Bioinformatics of the Semmelweis University</td>
			<td></td>
			<td>Validation of the interest gene as a predictive marker (http://www.rocplot.org/)</td>
		</tr>
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			<td>STRING</td>
			<td>Swiss Institute of Bioinformatics</td>
			<td></td>
			<td>Coexpression networks analysis(https://string-db.org)</td>
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			<td>TargetScan</td>
			<td>Whitehead Institute for Biomedical Research</td>
			<td></td>
			<td>Prediction of miRNA targets (www.targetscan.org/)</td>
		</tr>
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			<td>TIMER</td>
			<td>Harvard University</td>
			<td></td>
			<td>Systematical analysis of immune infiltrates across diverse cancer types (https://cistrome.shinyapps.io/timer/)</td>
		</tr>
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			<td>TISIDB</td>
			<td>The University of Hong Kong</td>
			<td></td>
			<td>A web portal for tumor and immune system interaction(http://cis.hku.hk/TISIDB/)</td>
		</tr>
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			<td>TNMplot</td>
			<td>Department of Bioinformatics of the Semmelweis University</td>
			<td></td>
			<td>Gene expression analysis (https://www.tnmplot.com/ )</td>
		</tr>
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			<td>UALCAN</td>
			<td>The University of ALabama at Birmingham&#160;</td>
			<td></td>
			<td>Gene expression analysis (http://ualcan.path.uab.edu)</td>
		</tr>
	</tbody>
</table>

tropomodulin 3 overexpression as a marker for platinum resistance and immune infiltration in ovarian cancer

Ovarian cancer is the second-highest in the mortality rate of gynecologic tumors worldwide1. It can be classified into three types based on histopathology: germ cell, gonadal mesenchymal, and epithelial tumors, of which 90% of patients are epithelial ovarian cancer. Risk factors associated with ovarian cancer include persistent ovulation, increased gonadotropin exposure, and inflammatory cytokines2. More than 75% of ovarian cancer cases are not detected until advanced stages, resulting in their lack of effective treatment. Patients with advanced ovarian cancer have a poor prognosis, with less than 20% of the 5-year survival rate despite new chemotherapy regimens, such as intraperitoneal administration and targeted therapy. The standard treatment for ovarian cancer mainly consists of tumor resection surgery followed by chemotherapy with drugs such as platinum and paclitaxel. However, tumor recurrence occurs in about 70% of cases1. Cisplatin exerts its therapeutic effects by interfering with DNA replication and transcription and is currently the first-line agent in ovarian cancer chemotherapy. However, a significant proportion of ovarian cancer patients are platinum-resistant3. Multiple cellular processes, such as drug efflux, cellular detoxification, DNA repair, apoptosis, and autophagy, are critical in platinum resistance in ovarian cancer cells4,5,6.
The alteration in the cytoskeleton is an important mechanism affecting platinum resistance in ovarian cancer. It has been recently reported that cytoskeleton-related genes are usually aberrantly expressed, and the actin cytoskeleton is significantly modified in the presence of cisplatin-triggered apoptosis7. Many studies have shown that cisplatin modulates the nanomechanics of ovarian cancer cells. The cell stiffness of sensitive cells increases with platinum dose-dependently, mainly contributed by&#160;the disruption of&#160;actin polymerization. In contrast, cisplatin-resistant cells showed no significant change in cell stiffness after cisplatin treatment8. Furthermore, the Young&#39;s moduli of cisplatin-sensitive ovarian cancer cells were lower, as revealed by atomic force microscopy. In contrast, cisplatin-resistant ovarian cancer cells exhibit a cytoskeleton characterized by long actin stress fibers. Inhibiting Rho GTPase decreases stiffness and enhances cisplatin sensitivity in these resistant cells. Conversely, activating Rho GTPase in cisplatin-sensitive cells increases cell stiffness and reduces their sensitivity to cisplatin9.The RNA-binding protein with multiple splicing (RBPMS), a tumor suppressor gene, reduces cisplatin resistance in ovarian cancer cells by regulating the protein expression of the cytoskeletal network and maintaining cell integrity10. Actin stress fibers are more pronounced in A2780/CP cells compared to A2780 cells. The development of drug resistance in ovarian cancer cells induces extensive reorganization of the actin cytoskeleton, thereby affecting cellular mechanical properties, motility, and intracellular drug transport11.
TMOD3 is a cytoskeleton-regulatory protein that prevents the depolymerization of actin by capping the slow-growing (pointed) ends of actin filaments12.TMOD3 plays different roles in different cell types by regulating actin dynamics and participates in various processes, such as promoting cell shape, cell migration, and muscle contraction. It was shown that TMOD3 deletion in mice leads to embryonic death at E14.5-E18.5, suggesting that TMOD3 may be a critical factor in embryonic development13. Based on its biological functions in stem and progenitor cells, TMOD3 may play an essential role in tumor progression. In hepatocellular carcinoma, TMOD3 promotes the growth, invasion, and migration of hepatocellular carcinoma cells by activating the MAPK/ERK signaling pathway14 and promotes distant metastasis by activating the PI3K-AKT pathway through interaction with the epidermal growth factor receptor15. MiRNA-490-3p inhibits hepatocellular carcinoma cell proliferation and invasion by targeting TMOD316. MiR-145 improves the radiosensitivity of radiation-resistant non-small cell lung cancer by inhibiting TMOD317. In vitro experiments revealed that TMOD3 mediated the invasion of esophageal cancer cells by regulating the cytoskeleton through interaction with lysyl oxidase homolog 2 (LOXL2)18. In addition, proteomic analysis revealed that high expression of TMOD3 could potentially mediate etoposide chemoresistance in lung cancer through the apoptotic pathway19. Although TMOD3 has been increasingly studied in tumors in recent years, there are still no reports on the role of TMOD3 in ovarian cancer and chemotherapy.
This study found that TMOD3 is upregulated in ovarian cancer. Notably, the upregulation of TMOD3 was associated with platinum resistance. This study also evaluated the prognostic value of TMOD3 in ovarian cancer and its correlation with tumor immune infiltration. This study suggests that overexpression of TMOD3 in ovarian cancer is associated with platinum resistance.

<meta charset="utf8"></head><body>Autor destacado: Desvelando el papel de TMOD3 en la resistencia al platino y la infiltración inmunitaria en el cáncer de ovario

Sobreexpresión de tropomodulina 3 como marcador de resistencia al platino e infiltración inmunitaria en el cáncer de ovario

The cytoskeleton plays an important role in platinum resistance in ovarian cancer. Tropomodulin 3 (TMOD3) is critical in the development of many tumors, ...

tropomodulin-3-overexpression-as-marker-for-platinum-resistance

Research

JoVE Journal

Cancer Research

Tropomodulin 3 Overexpression as a Marker for Platinum Resistance and Immune Infiltration in Ovarian Cancer

1.8K vistas.  Yangzhou Polytechnic College. Nuestra investigación se centra en la resistencia a los fármacos en el cáncer de ovario. En nuestro artículo, intentamos descubrir el papel de TMOD3 en el cáncer de ovario y la quimioterapia. Se ha demostrado que muchas proteínas del calendario del citos desempeñan un papel importante en el cáncer de ovario y la resistencia a los medicamentos, pero aún no hay informes sobre el papel de TMOD3, el cáncer de ovario y la terapia sim.Nuestro estud...

Video: Autor destacado: Desvelando el papel de TMOD3 en la resistencia al platino y la infiltración inmunitaria en el cáncer de ovario

The cytoskeleton plays an important role in platinum resistance in ovarian cancer. Tropomodulin 3 (TMOD3) is critical in the development of many tumors, but its role in the drug resistance of ovarian cancer remains unexplored. By analyzing data from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases, this study compared TMOD3 expression in ovarian cancer and normal tissues, and examined the expression of TMOD3 after platinum treatment in platinum-sensitive and platinum-resistant ovarian cancers. The Kaplan-Meier method was used to assess the effect of TMOD3 on overall survival (OS) and progression-free survival (PFS) in ovarian cancer patients. microRNAs (miRNAs) targeting TMOD3 were predicted using TargetScan and analyzed using the TCGA database. Tumor Immune Estimation Resource (TIMER) and an integrated repository portal for tumor-immune system interactions (TISIDB) were used to determine the relationship between TMOD3 expression and immune infiltration. TMOD3 coexpression networks in ovarian cancer were explored using LinkedOmics, the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and The Database for Annotation, Visualization, and Integrated Discovery (DAVID) Bioinformatics. The results showed that TMOD3 was highly expressed in ovarian cancer and was associated with the grading, staging, and metastasis of ovarian cancer. TMOD3 expression was significantly reduced in platinum-treated ovarian cancer cells and patients. However, TMOD3 expression was higher in platinum-resistant ovarian cancer cells and tissues compared to platinum-sensitive ones. Higher TMOD3 expression was significantly associated with lower OS and PFS in ovarian cancer patients treated with platinum-based chemotherapy. miRNA-mediated post-transcriptional regulation is likely responsible for high TMOD3 expression in ovarian cancer and platinum-resistant ovarian tissues. The expression of TMOD3 mRNA was associated with immune infiltration in ovarian cancer. These findings indicate that TMOD3 is highly expressed in ovarian cancer and is closely associated with platinum resistance and immune infiltration.

Tropomodulin 3 (TMOD3) has been increasingly studied in tumors in recent years. This study is the first to report that TMOD3 is highly expressed in ovarian cancer and is closely associated with platinum resistance and immune infiltration. These results could help improve the therapeutic outcomes for ovarian cancer.