A high-magnification micrograph of an ovarian clear cell carcinoma. The images show, focally, the characteristic clear cells with prominent nucleoli and the typical hyaline globules. A high-magnification micrograph of an ovarian clear cell carcinoma. The images show, focally, the characteristic clear cells with prominent nucleoli and the typical hyaline globules. [Image from Nephron/CC BY-SA 3.0]
A synthetic biomarker, which is a nanoparticle that works with tumor proteins to release fragments into the urine for detection, helps the MIT-developed test create a much clearer signal that natural biomarkers in the bloodstream don’t offer.
“What we did in this paper is engineer our sensor to be about 15 times better than a previous version, and then compared it against a blood biomarker in a mouse model of ovarian cancer to show that we could beat it,” said Sangeeta Bhatia, senior author on the study, said in a press release.
Bhatia, who is also a member of MIT’s Koch Institute for Integrative Cancer Research and Institute for Medical Engineering and Science, proposed the idea of using synthetic biomarkers to diagnose cancer in 2012. The activity of protein-cutting enzymes called endoproteases can be measured with synthetic biomarkers because they are created by tumors to help recruit blood vessels. They invade surrounding tissues and allow cancer to spread.
Researchers had to design nanoparticles that were coated with small protein fragments to detect endoproteases.
The particles passively collected at the tumor site after being injected into a mouse. MMPs split the peptides to release tiny reporter fragments that can be filtered by the kidney and concentrated in urine. The fragments can then be detected from a variety of different methods.
To detect particles that are smaller than 5 mm in diameter, the researchers had to increase the sensitivity of the synthetic biomarker detector system. They used 2 new strategies to boost the sensitivity. First, they optimized the length of the polymer that attaches to peptides to nanoparticles. Then, they added a tumor-penetrating peptide to the nanoparticles to cause them to gather at the tumor in greater numbers. The number of split peptides that end up in the urine increases as a result.
Combining these 2 strategies allowed researchers to make the system sensitive enough to detect small tumors that are 2 mm in diameter in mice.
“This is important work to validate novel strategies for the earlier detection of cancer that are not dependent on biomarkers made by cancer cells. [The method] instead forces the generation of artificial biomarkers at the tumor site, if any tumor indeed exists within the body,” said Sanjiv Sam Gambhir, chair of the department of radiology at Stanford University School of Medicine. “Such approaches should eventually hep change the way in which we detect cancer.”
About 22,440 women will be diagnosed with ovarian cancer in 2017 with another 14,080 women dying from it, according to the American Cancer Society. It is ranked as the 5th cancer death among women and the likelihood of a woman developing ovarian cancer in her lifetime is about 1 in 75.
Ovarian cancer is diagnosed in several ways. Women can be diagnosed from a physical exam based on whether they exhibit symptoms. They can also receive imaging tests like computed tomography scans, magnetic resonance imaging scans and ultrasound scans to determine if there is a pelvic mass present. Laparoscopies, colonoscopies and biopsies are also used to detect ovarian cancer.
Ovarian cancer is cancer that affects the ovaries. There are 3 types of cells that make up the ovaries and can develop tumors. Epithelial tumors are on the outer surface of the ovary. Germ cell tumors start from the cells that produce eggs. Stromal tumors occur from structural tissue cells that help keep the ovary together and produce estrogen and progesterone.
The MIT researchers also showed that they were able to detect proteases in microarrays of many tumor cells from different cancer patients. They could detect colorectal tumors that metastasized to the liver using this method.
“Every patient’s tumor is different, and not every tumor will be amenable to targeting with the same molecule,” said Bhatia. “This is a tool that will help us to exploit the modularity of the technology and personalize formulations.”
The research was funded by the Koch Institute’s Marble Center for Cancer Nanomedicine, the Ludwig center for Molecular Oncology, the Koch Institute Support Grant from the National Cancer Institute, the Core Center Grant from the National Institute of Environmental Health Science, a Ruth L. Kirschstein National Research Service Award, the Howard Hughes Medical Institute and a National Science Foundation Graduate Research Fellowship. It was published online in the Nature Biomedical Engineering journal.
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