Honeycomb-like Structured Film, a Novel Therapeutic Device, Suppresses Tumor Growth in an In Vivo Ovarian Cancer Model.
Tsuyoshi OhtaMasaru TanakaSeitaro TakiHiroyuki NakagawaSatoru NagasePublished in: Cancers (2022)
Ovarian cancer cell dissemination can lead to the mortality of patients with advanced ovarian cancer. Complete surgery for no gross residual disease contributes to a more favorable prognosis than that of patients with residual disease. HCFs have highly regular porous structures and their 3D porous structures act as scaffolds for cell adhesion. HCFs are fabricated from biodegradable polymers and have been widely used in tissue engineering. This study aimed to show that HCFs suppress tumor growth in an in vivo ovarian cancer model. The HCF pore sizes had a significant influence on tumor growth inhibition, and HCFs induced morphological changes that rounded out ovarian cancer cells. Furthermore, we identified gene ontology (GO) terms and clusters of genes downregulated by HCFs. qPCR analysis demonstrated that a honeycomb structure downregulated the expression of CXCL2, FOXC1, MMP14, and SNAI2, which are involved in cell proliferation, migration, invasion, angiogenesis, focal adhesion, extracellular matrix (ECM), and epithelial-mesenchymal transition (EMT). Collectively, HCFs induced abnormal focal adhesion and cell morphological changes, subsequently inhibiting the differentiation, proliferation and motility of ovarian cancer cells. Our data suggest that HCFs could be a novel device for inhibiting residual tumor growth after surgery, and could reduce surgical invasiveness and improve the prognosis for patients with advanced ovarian cancer.
Keyphrases
- tissue engineering
- extracellular matrix
- epithelial mesenchymal transition
- signaling pathway
- cell adhesion
- cell migration
- cell proliferation
- high glucose
- diabetic rats
- biofilm formation
- genome wide
- endothelial cells
- transforming growth factor
- drug delivery
- stem cells
- oxidative stress
- genome wide identification
- pseudomonas aeruginosa
- single cell
- electronic health record
- cardiovascular events
- type diabetes
- mesenchymal stem cells
- vascular endothelial growth factor
- binding protein
- coronary artery bypass
- cystic fibrosis
- escherichia coli
- big data
- artificial intelligence
- transcription factor
- highly efficient
- cell cycle
- ionic liquid
- long non coding rna
- surgical site infection