New Findings in Ovarian Cancer

Discovering new vulnerable area and biomarker in ovarian cancers can help to identify best candidates for new ovarian cancer treatments.

Newly discovered molecular mechanisms and biomarkers in ovarian cancer will help to identify best candidates for possible new treatments.

This finding published in the journal Cell using a research tool invented in a UT Southwestern lab in the Cecil H. and Ida Green Center for Reproductive Biology Sciences.

Ovarian Cancer | Cancer in the Ovaries - Causes, Symptoms, Treatment & Prevention
Ovarian cancer affects both the ovaries and is referred to as the 'silent killer' as the symptoms go unnoticed until the disease advances.

‘New important molecular mechanisms and biomarkers in ovarian cancer are discovered.’

Many researchers are trying to explore mechanisms that support cancer growth such as gene amplification, increased protein level, or upregulation of critical cellular pathway.

These changes give cancer a selective advantage, at the same time they can become a weak area if the alteration is blocked that will kill the cancer or stop its growth.

This new study discovered that ovarian cancers massively amplify an enzyme, NMNAT-2, that makes NAD+. NAD+ is the substrate for a family of enzymes called PARPs, which chemically modify proteins with ADP-ribose from NAD+.

What Women Should Know About Gynecologic Cancer
Cancers arising from the organs of the female reproductive tract (uterine, ovarian, cervical, vulval and vaginal cancers) are termed gynecologic cancers.

As it is difficult to identify single ADP-ribose group attached to a protein, they developed a synthetic detection reagent made up of natural protein domains fused together to detect ADP-ribosylated proteins in cells and patient samples.

“We were able to show that when ribosomes are mono(ADP-ribosyl)ated in ovarian cancer cells, the modification changes the way they translate mRNAs into proteins,” Dr. Kraus said.

Artificial Intelligence Can Now Predict Survival of Ovarian Cancer Patients
Artificial intelligence (AI) can now predict how ovarian cancer patients will respond to treatment, the likely outcome, and the chances of survival. This will help in planning alternative treatments for the patient beforehand.

This study identified mono (ADP-ribose) and NMNAT-2 as potential biomarkers for ovarian cancers, which allowed clinicians to identify ovarian cancer patients who may respond well to treatment.

This finding is not only a great advance in basic science but also a real promise for clinician investigators and cancer care practitioners because it shows a biomarker and a pathway for future drug target.

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Source-Medindia