Cell-free DNA promises to transform how we find diseases

Scientists have been aware of cfDNA since 1948, but only in the last two decades have they figured out what to do with it.

Updated - July 31, 2023 10:31 am IST

Published - July 30, 2023 10:30 am IST

Representative illustration.

Representative illustration. | Photo Credit: Ashraful Islam/Unsplash

In the human body, most of the DNA in a genome is neatly packed inside cells with the help of specific proteins, protecting it from being degraded. However, in a variety of scenarios, some fragments of DNA are ‘released’ from their containers and are present outside the cell, in body fluids. These small fragments of nucleic acids are widely known as cell-free DNA (cfDNA).

Scientists have been aware of such degraded fragments of nucleic acids in body fluids since 1948. But only in the last two decades or so, since genome sequencing technologies started to become more accessible, have they really figured out what to do with that knowledge.

A useful tool

cfDNA can be generated and released from a cell in a number of possible situations, including when a cell is dying and the nucleic acids become degraded. Since an array of processes modulates the degradation, the amount, size, and source of the cfDNA can vary across a range as well.

In addition, the release of cfDNA could occur together with a variety of processes, including those required for normal development, those related to the development of certain cancers, and those associated with several other diseases. One of the initial reports of the levels of cfDNA in diseases came from studies that were taking a closer look at an autoimmune disease: systemic lupus erythematosus – where the body’s own immune system attacks specific cells.

So it is not surprising that researchers around the world are increasingly finding cfDNA to be a useful tool to understand human diseases and to use the knowledge to improve diagnosis, monitoring, and prognosis.

Checking the baby

By far, one of the most widely used applications of cfDNA has been in screening foetuses for specific chromosomal abnormalities, an application known as non-invasive prenatal testing. The application stems from one of the first reports of cfDNA in pregnancies, published in The Lancet in August 1997. The availability of affordable genome-sequencing approaches will allow clinicians to sequence cfDNA fragments that correspond to foetal DNA. They can then use it to understand specific chromosomal abnormalities that involve changes in the chromosomal copy number. Such changes can lead to conditions like Down’s syndrome, which is due to a change in chromosome 21 (there are three copies of chromosome 21 in place of two, so it is also called trisomy 21).

As a result, thanks to a cfDNA-based technique, clinicians can now screen mothers from a few millilitres of blood, obtained after nine or ten weeks of pregnancy, to ensure the developing foetus is devoid of such chromosomal abnormalities. The test is almost 99% accurate for trisomy 21 or Down’s syndrome and a bit less so for other common trisomies (of chromosomes 13 and 18).

Screening for such abnormalities before the genome-sequencing era would have entailed inserting a fine needle into the body to retrieve the amniotic fluid and cells covering the developing foetus, and analysing them in the lab. This method carries risks to both the foetus and the mother. It is therefore not surprising that the cfDNA-based approach has now become the mainstay for screening high-risk pregnancies.

This said, the test is not without its limitations – which means a positive test result on a cfDNA test should always be followed up with a confirmation test.

Catching a cancer

Another emerging application of cfDNA is in the early detection, diagnosis, and treatment of cancers.

Last month, researchers at the Johns Hopkins Kimmel Cancer Centre, Maryland, reported developing a new test they have dubbed ‘Genome-wide Mutational Incidence for Non-Invasive detection of cancer’, or ‘GEMINI’. They adopted a whole-genome-sequencing approach to cfDNA extracted from patients.

Specifically, the researchers examined a type of genetic mutation that, when combined with machine-learning approaches, could provide a way to detect cancer early. Using a particular machine-learning model, some genomic data, and data from a computed tomography (CT) scan, the researchers could successfully detect lung cancer – including those with early stage disease – in more than the 90% of the 89 people they studied.

The team also found that it could replicate the findings using cfDNA derived from a prospective observational cohort of over 300 individuals who were at high risk of developing lung cancer. They found that combining the new approach with the existing approaches could significantly enhance their ability to detect cancers early.

The researchers also identified seven individuals who did not have cancer but had a high chance of developing it – and subsequently did so 231 to 1,868 days after the initial test.

The team’s findings were published in the journal Nature Genetics.

Almost infinite applications

There are a number of emerging applications of cfDNA, including in understanding why a body is rejecting a transplanted organ. Here, some cfDNA obtained from the donor who is donating the organ – called donor-derived cfDNA, dd-cfDNA – could provide an early yet accurate estimate of how well the organ is being taken up. This is an attractive proposition because changes in the levels of cfDNA in the blood would precede any biochemical or molecular markers that researchers currently use as a proxy for organ acceptance. That is, the cfDNA could send a signal earlier than other markers if something is going to go wrong.

Indeed, cfDNA seems to have an almost infinite number of applications, especially as nucleic-acid sequencing becomes rapidly democratised and finds more applications of its own in clinical settings. There have already been some reports suggesting that cfDNA could be used as a biomarker for neurological disorders like Alzheimer’s disease, neuronal tumours, stroke, traumatic brain injury, and even metabolic disorders like type-2 diabetes and non-alcoholic fatty liver disease.

In a true sense, cfDNA genomics promises to set us on the path of more effective disease-screening and early diagnosis, and on course for a healthy world.

The authors are scientists at the CSIR Institute of Genomics and Integrative Biology. All opinions expressed here are personal.

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