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Discovery-Ovarian Cancer Breakthrough Discovery: New Biomarkers for Early Detection of Ovarian Cancer
Monday, 10 Jul 2023 21:00 pm
JAC24

JAC24

A team of Japanese researchers from Nagoya University has made a significant breakthrough in the early detection of ovarian cancer. Ovarian cancer is notoriously difficult to detect in its initial stages when treatment is most effective. However, the team has identified new biomarkers that can improve the detection process.

The researchers focused on identifying membrane proteins in ovarian cancer cells using a unique technology involving nanowires coated with polyketone. This approach allowed them to pinpoint three previously unknown membrane proteins associated with ovarian cancer.

One common method for cancer detection is the analysis of extracellular vesicles (EVs), particularly exosomes, which are small proteins released by tumors. These proteins can be isolated from body fluids like blood, urine, and saliva, as they are found outside cancer cells. However, the lack of reliable biomarkers for ovarian cancer detection has hindered progress in this area.

To address this challenge, the team extracted both small and medium/large EVs from high-grade serous carcinoma (HGSC), the most prevalent type of ovarian cancer. They then conducted protein analysis using liquid chromatography-mass spectrometry.

According to Akira Yokoi, a researcher from Nagoya University Graduate School of Medicine, the identification and validation process for the proteins were arduous. Multiple antibodies were tested before finding the right targets. Ultimately, they discovered that small EVs were more suitable biomarkers than the medium and large types. The team identified three membrane proteins, namely FRalpha, Claudin-3, and TACSTD2, associated with HGSC in small EVs.

Once the proteins were identified, the researchers aimed to develop a method to capture EVs that could indicate the presence of ovarian cancer. Scientist utilized the polyketone chain-coated nanowires (pNWs), this technology designed specifically for separating exosomes molicule from blood samples of human body.

The creation of pNWs was a challenging process, involving the experimentation of various coatings on the nanowires. However, the team found that polyketones were an excellent fit for the purpose.

Yokoi stated, "Our findings demonstrated the usefulness of each of the three identified proteins as biomarkers for HGSCs." This breakthrough could have significant implications, as these diagnostic biomarkers could serve as predictive markers for specific therapies.

By optimizing therapeutic strategies based on these biomarkers, doctors can potentially personalize treatments for ovarian cancer patients. This research contributes to the advancement of personalized medicine in the field of ovarian cancer.

 

 

In conclusion, the team of Japanese researchers from Nagoya University has achieved a significant breakthrough in the early detection of ovarian cancer. By identifying new biomarkers associated with high-grade serous carcinoma (HGSC), the most prevalent type of ovarian cancer, they have addressed the challenge of reliable detection methods for this disease. Through their innovative approach using nanowires coated with polyketone and the analysis of extracellular vesicles (EVs), they successfully pinpointed three previously unknown membrane proteins, namely FRalpha, Claudin-3, and TACSTD2, as biomarkers for HGSC.
The discovery of these biomarkers opens up new possibilities for early detection and personalized treatment of ovarian cancer. By developing a method to capture EVs that indicate the presence of ovarian cancer, doctors can potentially use these biomarkers as predictive markers for specific therapies. This breakthrough has significant implications for the field of ovarian cancer and contributes to the advancement of personalized medicine. With improved detection and personalized treatment strategies, the researchers' findings have the potential to positively impact the outcomes and prognosis of ovarian cancer patients.

 

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