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Quantitative biophysical metrics for rapid evaluation of ovarian cancer metastatic potential.

ABSTRACT: Ovarian cancer is routinely diagnosed long after the disease has metastasized through the fibrous submesothelium. Despite extensive research in the field linking ovarian cancer progression to increasingly poor prognosis, there are currently no validated cellular markers or hallmarks of ovarian cancer that can predict metastatic potential. To discern disease progression across a syngeneic mouse ovarian cancer progression model, here we fabricated extracellular matrix mimicking suspended fiber networks: cross-hatches of mismatch diameters for studying protrusion dynamics, aligned same diameter networks of varying interfiber spacing for studying migration, and aligned nanonets for measuring cell forces. We found that migration correlated with disease while a force-disease biphasic relationship exhibited F-actin stress fiber network dependence. However, unique to suspended fibers, coiling occurring at the tips of protrusions and not the length or breadth of protrusions displayed the strongest correlation with metastatic potential. To confirm that our findings were more broadly applicable beyond the mouse model, we repeated our studies in human ovarian cancer cell lines and found that the biophysical trends were consistent with our mouse model results. Altogether, we report complementary high throughput and high content biophysical metrics capable of identifying ovarian cancer metastatic potential on a timescale of hours.

SUBMITTER: Mukherjee A

PROVIDER: S-EPMC9265161 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Epithelial ovarian cancer (EOC) accounts for 4% of all cancers in women and is the leading cause of death from gynecologic malignancies. It is well established that cancer invasion and metastasis still represent the major causes of the failure of cancer treatment. Previously, we identified the mannose receptor LY75 (DEC205/CD205) gene as notably hypomethylated in high-grade (HG) serous epithelial ovarian tumors, compared to normal ovarian tissues. LY75 has been identified as a putative antigen-uptake receptor, which is expressed abundantly on dendritic cells, which are specialist antigen presenting cells to T lymphocytes for the initiation of an immune response. The implication of LY75 in EOC tumorigenesis is currently unknown. Here we show that LY75 is strongly overexpressed in HG serous EOC tumors as compared to normal ovarian tissue. Importantly, shRNA-mediated LY75 knockout in the mesenchymal EOC cells (SKOV3) led to mesenchymal to epithelial transition (MET), associated with overexpression of epithelial markers E-cadherin and EPCAM and loss of expression of mesenchymal markers Fibronectin, N-cadherin Snail1 and Twist1. In addition, LY75 suppression significantly inhibited EOC cell migration and invasion in vitro. However, LY75 knockdown led to enhanced tumor cell dissemination and significantly increased lethality in vivo, in xenograft model of advanced peritoneal EOC. Thus, our findings indicate that LY75 could play an essential role in the mesenchymal-to-epithelial transition (MET) of EOC cells and support the hypothesis that, while epithelial-to-mesenchymal transition (EMT) enables the invasiveness of tumor cells, a MET-associated epithelial phenotype could be essential for their metastatic colonization. To better understand the molecular mechanisms of LY75 gene action in epithelial ovarian cancer (EOC), we employed the Agilent Whole Human Genome microarrays, containing ~ 44,000 genes to identify global gene expression changes upon LY75 suppression in SKOV3 EOC cells. We compared the gene expression of the previously selected shRNA-mediated LY75-knockdown clones sh-S3 and sh-S6 against the corresponding control (ctrl) clone. The microarray experiments were performed in duplicates, as two hybridizations were carried out for each of the LY75-suppressing cell clone against the corresponding control, using a fluorescent dye reversal (dye-swap) technique.

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Quantitative biophysical metrics for rapid evaluation of ovarian cancer metastatic potential.

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