The hardening of the liver can lead to cancer later on. A new blood test in development could assist physicians in identifying it.
A new blood test is being developed to detect circulating bits of DNA that have been associated with liver scarring.(Image credit: Bloomberg Creative via Getty Images)Subscribe to our newsletter
A novel blood test can identify a precursor to liver ailments, which can subsequently serve as an omen of cancer. The aspiration is that this test might help avert liver cancer before its onset.
The test employs a machine learning algorithm to examine free-floating genetic material present in the bloodstream. In the recent investigation, scientists utilized it to detect fragments of DNA indicative of early-stage liver scarring, also known as fibrosis. This initial scarring, if unaddressed, can progress to severe liver hardening, termed cirrhosis, and ultimately result in cancer.
“The most effective approach to intervene in liver cancer is not to detect the cancer itself at an early stage, but rather to identify early liver disease,” Velculescu informed Live Science.
Once identified, fibrosis can be reversed through antifibrotic medications, adjustments in lifestyle, and other therapeutic interventions, he elaborated. In contrast, cirrhosis is largely irreversible.
Indications of illness evident in the blood
Millions of individuals in the United States have liver fibrosis without their knowledge. Factors contributing to the development of this scarring include liver inflammation (hepatitis), diabetes, elevated blood pressure, and obesity. When diagnosed promptly, liver fibrosis is reversible.
However, current conventional clinical assessments, such as the fibrosis-4 (FIB-4) blood test which utilizes age, liver enzymes, and platelet counts to estimate the extent of liver scarring, are inadequate in detecting early-stage liver disease, stated Velculescu.
We aim to detect alterations that might be occurring within the disease process across the entire genome.
Akshaya Annapragada, MD/PhD student at Johns Hopkins Kimmel Cancer Center.
In the recent study, published on March 4 in the journal Science Translational Medicine, Velculescu and his team initially examined blood samples from 423 participants, both with and without liver disease. By analyzing millions of cell-free DNA fragments in the blood, they identified markers capable of differentiating patients with early liver scarring from those without any degree of liver disease.
Cell-free DNA, also referred to as circulating DNA, consists of minute portions of genetic material released into the blood as cells regenerate and undergo apoptosis. Rather than searching for specific mutations or changes in DNA sequences, the team employed a computational model to identify broader, genome-wide patterns within all the free-floating DNA shed by cells.
“Our objective is to identify changes that may be present in the disease across the entire genome,” Akshaya Annapragada, the study’s first author and an MD/PhD student in Velculescu’s laboratory, communicated to Live Science. “This provides us with a greater number of opportunities to discover something significant.”
They pinpointed several factors collectively associated with early liver disease. These included the length of the DNA fragments and the frequency with which cells shed repetitive DNA sequences. They also detected crucial epigenetic modifications, which are alterations on the genome that influence gene activity without altering the fundamental DNA sequence.
Equipped with these insights, they devised a test to detect these patterns in the blood.
To evaluate the efficacy of the blood test, the team assessed it on an additional 221 participants: 30 with early liver disease, 85 with advanced liver disease, and 106 with no liver disease. The test successfully identified 50% of early liver disease cases and approximately 78% of advanced cases.
It accurately classified disease-free individuals in 83% of instances, indicating a false positive rate of 17% for liver disease detection.
The utilization of machine learning to discern patterns across the entire genome allows the team to analyze billions of fragments simultaneously, explained Alain Thierry, a professor and research director at INSERM, the French National Institute of Health and Medical Research, who was not involved in the study.
This represents an advancement compared to prior blood tests that focused on specific mutations or disease markers, necessitating thousands of genome sequencing runs to gather sufficient DNA for interpretation, according to Annapragada. In contrast, “this test requires only one to two genome sequencing runs, making it considerably more economical and efficient.”
The subsequent phase involves larger clinical trials to confirm the predictive capabilities of the machine learning models for detecting liver fibrosis, stated Velculescu.
The researchers expressed their hope that tests similar to theirs will eventually facilitate the development of non-invasive methods for screening a variety of diseases through a single blood test, thereby enabling earlier diagnosis and treatment before conditions become chronic and irreversible.