We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us

Download Mobile App




New High-Throughput Microscopy and Machine Learning Systems Identify and Classify DNA Repair Factors

By LabMedica International staff writers
Posted on 04 Feb 2022

A team of researchers has developed high-throughput microscopy and machine learning systems that can identify and classify DNA repair factors. More...

The highly sensitive method for visualizing DNA repair mechanisms at work was developed by researchers at Massachusetts General Hospital (Boston, MA, USA) who also used the technique to identify nine new proteins that are involved in DNA repair. The finding can help researchers develop new cancer drugs, as well as methods for improving the effectiveness of existing therapies.

The DNA that lies tightly coiled in nearly every human cell is subjected to thousands of insults and injuries from within and without daily, which is why the human body has evolved multiple highly effective mechanisms for repairing DNA damage. DNA damage repair is a double-edged sword: When it goes awry, it can lead to diseases such as cancer and degenerative motor disorders, but it can also be exploited to treat many forms of cancer using drugs that interfere with DNA’s ability to fix itself, thereby causing cancerous cells to stop replicating and die. Previous studies of DNA repair mechanisms were performed using systems developed by biochemists to purify proteins, but these systems have relatively low yields or “throughput.

The new technique is a combination of high-throughput microscopy and machine learning. The investigators first developed a high-throughput microscopy test to analyze how proteins are attracted to or excluded from double-strand DNA breaks. With this system they generated a library of 384 mostly unknown factors and were able to identify which of these proteins are called into action when DNA damage occurs. They then performed a proof-of-principle study, following one specific factor labeled PHF20 that is kept away from the site of DNA damage, and discovered that PHF20 is excluded because it can interfere with recruitment of another critical DNA repair factor labeled 53BP1. The systems developed by the researchers could help improve the treatment of breast and ovarian cancers caused by mutations in the cancer susceptibility genes BRCA1 and BRCA2. These cancers are treated with a class of drugs known as PARP inhibitors that work by inhibiting a particular DNA repair factor.

“We have in place exquisite mechanisms to repair DNA breaks, and when those fail, we end up with disease. We accumulate genomic instability, we accumulate mutations, and many diseases happen because of the inability of cells to repair DNA,” said Raul Mostoslavsky, MD, PhD, scientific co-director of the MGH Cancer Center and the Laurel Schwartz Professor of Oncology (Medicine) at Harvard Medical School.

Related Links:
Massachusetts General Hospital 


Gold Member
Blood Gas Analyzer
Stat Profile pHOx
POC Helicobacter Pylori Test Kit
Hepy Urease Test
Laboratory Software
ArtelWare
Autoimmune Liver Diseases Assay
Microblot-Array Liver Profile Kit
Read the full article by registering today, it's FREE! It's Free!
Register now for FREE to LabMedica.com and get access to news and events that shape the world of Clinical Laboratory Medicine.
  • Free digital version edition of LabMedica International sent by email on regular basis
  • Free print version of LabMedica International magazine (available only outside USA and Canada).
  • Free and unlimited access to back issues of LabMedica International in digital format
  • Free LabMedica International Newsletter sent every week containing the latest news
  • Free breaking news sent via email
  • Free access to Events Calendar
  • Free access to LinkXpress new product services
  • REGISTRATION IS FREE AND EASY!
Click here to Register








Channels

Hematology

view channel
Image: Residual leukemia cells may predict long-term survival in acute myeloid leukemia (Photo courtesy of Shutterstock)

MRD Tests Could Predict Survival in Leukemia Patients

Acute myeloid leukemia is an aggressive blood cancer that disrupts normal blood cell production and often relapses even after intensive treatment. Clinicians currently lack early, reliable markers to predict... Read more
Copyright © 2000-2026 Globetech Media. All rights reserved.