(RxWiki News) With high-tech biomedical probes, the future of ovarian cancer detection may be greatly simplified. A recent study tested whether a special probe could detect ovarian cancer cells based on tissue samples.
This method showed promise for detecting the presence of ovarian cancer based on how firm the cells were.
Simply put, they used a high-tech probe to see whether the cells were hard or soft—squeezably soft even.
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Todd Sulchek, PhD, assistant professor, and Wenwei Xu, PhD student, at the George W. Woodruff School of Mechanical Engineering at the Georgia Institute of Technology, have proposed an ovarian cancer diagnostic technique.
Metastatic (cancer spreading) cells and benign (non-cancerous) cells can both be found in ovarian tumors.
Researchers used advanced technology called, atomic force microscopy (AFM), to help doctors determine whether ovarian tumor cells are cancerous or not.
AFM uses a probe to “bounce” signals off a surface to learn what an object is made of. It looked at things like density.
Dr. Sulchek said, “In order to spread, metastatic cells must push themselves into the bloodstream. As a result, they must be highly deformable and softer.”
This team of engineers tested AFM on ovarian tumor cells to see if the technology could detect metastatic cells vs. benign cells.
AFM was done on cultured ovarian samples, not from existing patient samples. Authors recommend further studies test in the technology on patient-derived cells.
Dr. Sulchek's team found the benign cells were harder and the cancerous cells were softer.
Authors said, “Collectively, our results indicate that mechanical stiffness may be a useful biomarker in the development of accurate, non-invasive clinical methods to evaluate the relative metastatic potential of ovarian and perhaps other types of cancer cells.”
“Our results indicate that cell stiffness may be a useful biomarker to evaluate the relative metastatic potential of ovarian and perhaps other types of cancer cells.”
This test has not yet been used in a clinical setting on patients with ovarian cancer as a diagnostic tool.
This study was published in October in PLOS ONE.
Funding for this study was supported by grants from the National Science Foundation, President’s Undergraduate Research Award, and Petit Scholars Program at Georgia Tech.
No conflicts of interest were reported.