The discovery could lead to new biomarkers that clinical laboratories can use to identify cancer and monitor treatment in patients.
As DNA “dark matter” (the DNA sequences between genes) is studied more, researchers are finding that so-called “junk DNA” (non-functional DNA) may influence a variety of health conditions and diseases, including cancer. This is of interest to pathologists and clinical laboratories involved in cancer diagnosis, and could lead to new non-invasive liquid biopsy methods to identify cancer in blood samples.
Researchers at the Johns Hopkins Kimmel Cancer Center in Baltimore, Maryland, have developed a technique to identify changes in repetitive elements of the genetic code in cancer tissue and in free DNA (cf-DNA) shed into the blood, according to a news release from Johns Hopkins University.
Hopkins researchers published their machine learning approach, called ARTEMIS (Analysis of Repetitive Elements in Disease), in the journal Neuroscience. Science Translational Medicine The paper is titled “Genome-wide repetitive sequences in cancer and free DNA.”
ARTEMIS “demonstrates the potential to predict early-stage cases of lung and liver cancer in humans by detecting repetitive genetic sequences.” Genetic Engineering and Biotechnology News (general) report.
This technology has the potential to enable non-invasive monitoring of cancer treatment and cancer diagnosis. Technology Network I got it.
“Our study shows that ARTEMIS can reveal genome-wide repetitive landscapes that reflect the dramatic underlying changes in human cancer,” said the study co-leader. Akshaya Annapragada “By uncovering the so-called 'dark genome,' this study provides unique insights into the cancer genome and provides proof-of-concept for the utility of genome-wide repeat sequences as tissue- and blood-based biomarkers for cancer detection, characterization and monitoring,” said Dr. Levine (above), an MD-PhD student at the Johns Hopkins School of Medicine and associate professor at the Johns Hopkins School of Medicine, in a news release. Clinical laboratories may soon have a new biomarker for cancer detection. (Photo Credit: Johns Hopkins University)
Early detection of lung and liver cancer
Artemis means “goddess of the hunt” in Greek. For researchers at Johns Hopkins University, ARTEMIS is a technology that “analyzes junk DNA found in tumors” and floating around in the bloodstream. Financial Times explained.
“This is like a big reveal behind the curtain,” geneticist Victor Berculescu, MD, PhD, professor of oncology and co-director of the Cancer Genetics and Epigenetics Program at the Johns Hopkins Kimmel Cancer Center, said in a news release.
“Until ARTEMIS, this dark matter in the genome was basically ignored, but now we know that these repeats don't occur randomly,” he added. “We found that they cluster around genes that are altered in different ways in cancer, and for the first time we're seeing that these sequences may be key to tumour development.”
ARTEMIS “has the potential to lead to new treatments, new diagnostics and new screening methods for cancer,” Berculescu noted.
Repeated DNA sequences are difficult to study
For some time, technical limitations have prevented scientists from analyzing repetitive genomic sequences.
“Genetic alterations in repetitive sequences are a hallmark of cancer and other diseases, but they have been difficult to characterize using standard sequencing methods,” the study authors wrote in their paper. Science Translational Medicine paper.
“We are a new hair“To identify repetitive elements in the whole-genome sequence, we employed a base-by-base (short sequences of DNA) finding approach called ARTEMIS,” the researchers wrote.
Scientists tested ARTEMIS in the laboratory.
The first analysis looked at 1,280 repetitive genetic elements in both normal and tumor tissue from 525 cancer patients who participated in the PCAWG. Technology Networkreported the following findings:
- An average of 807 altered elements were found in each tumor.
- Nearly two-thirds (820) were alterations not previously found in human cancers.
The researchers secondly investigated “alterations in repetitive elements across the genome that are predictive of cancer,” using machine learning to give each sample an ARTEMIS score, according to a Johns Hopkins news release.
According to a statement from Johns Hopkins University, the scoring “performed highly, detecting tumors from healthy tissues in 525 PCAWG participants across all cancer types analyzed, with an overall area under the curve (AUC) score of 0.96 (out of a possible 1.0).”
Introducing liquid biopsy
The scientists then used liquid biopsies to determine whether ARTEMIS was capable of diagnosing cancer non-invasively. The researchers used blood samples from:
According to Johns Hopkins University, the results are as follows:
- ARTEMIS classified patients as having lung cancer with an AUC of 0.82.
- ARTEMIS detected patients with liver cancer compared with patients with cirrhosis and viral hepatitis with an AUC score of 0.87.
Finally, scientists used the ARTEMIS blood test to determine the origin of tumors in cancer patients. They reported that the technology had a 78% accuracy rate in finding the origin of tumor tissue across 12 tumor types.
“These analyses reveal widespread variations in the recurrent landscape of human cancer and offer detection and characterization approaches that may aid in early detection and disease monitoring in cancer patients,” the researchers wrote. Science Translational Medicine.
Planning a large-scale clinical trial
Berculescu said further studies, including larger clinical trials, are planned.
“Although still in its early stages, this research demonstrates that some cancers could be diagnosed earlier by detecting tumour-specific changes in cells from blood samples,” said Dr Hattie Brooks, Research Information Manager at Cancer Research UK (CRUK). Financial Times.
If ARTEMIS proves viable as a non-invasive blood test for cancer, it could provide pathologists and clinical laboratories with new biomarkers and the opportunity to work with oncologists to rapidly diagnose cancer and monitor patients' responses to treatment.
—Donna Marie Pocius
Related information:
No more 'junk DNA': Johns Hopkins researchers develop method to identify cancer from repetitive elements in genetic code
Genome-wide repeat landscape in cancer and free DNA
AI detects cancer through DNA repeats in liquid biopsies
Genetic 'dark matter' could help monitor cancer
AI explores 'dark genomes' to shed light on cancer growth
