Nature Biotechnology Cancer Diagnostic Milestone: Diagnosing Cancer with Unprecedented Accuracy

Blood tests are simple, non-invasive, and economically feasible and promise to be the next important milestone
in cancer diagnosis.
However, liquid biopsies are currently not reliable enough to be widely available
.
A new multiparametric approach developed at the Weizmann Institute for Science could lead to a blood test to diagnose cancer
with unprecedented accuracy.
The study was published in
the journal Nature Biotechnology.

Dr.
Efrat Shema of the Department of Immunology and Regenerative Biology at Weizmann, who led the research team, explains: "Many of the traditional methods of detecting and diagnosing cancer currently available clinically are invasive and unpleasant
.
" Obtaining a biopsy sample through a needle, endoscope, or surgery can be painful and sometimes risky, while imaging methods such as MRI or PET scans require expensive, bulky equipment, and are not universally available
.
An effective blood test can provide an attractive alternative to
cancer screening or diagnosis.

"Eliminating this discomfort means that people are less likely to avoid tests and are more likely to detect cancer earlier," said
Vadim Fedyuk, who led the study with graduate student Nir Erez.

The idea of using liquid biopsies to diagnose cancer stems from the fact that blood contains free DNA and proteins that come from dead blood cells in healthy people and from dead tumor cells
from cancer patients.
"Some of the byproducts of cellular destruction, including cancer DNA and proteins, are dumped into the bloodstream, and we know how to collect and analyze them," Shema said
.

Some blood tests for cancer are already at an advanced stage of development, but most are flawed and may limit their use
.
When such a test was first developed, they looked for genetic signs of cancer, known as mutations, but this can be difficult to identify because mutated fragments make up only a small fraction
of free-circulating DNA.
In addition, these mutations do not always cause cancer, and healthy people can also be present
.
Recently, liquid biopsy methods have begun to rely on epigenetics, or modifications to the cellular genome that do not involve DNA mutations — for example, chemical tags attached to DNA molecules that alter gene expression
.
These methods also run into problems, either because they require excess blood or because they only look for a single epigenetic change that doesn't produce sufficiently reliable results
.

In the new study, Shema set out to rethink this epigenetic analysis, aiming to develop an analysis that
relies on a small number of blood samples to assess multiple epigenetic parameters.
She developed a method
to image individual molecules during her postdoctoral research at Harvard Medical School and the Broad Institute.
This method makes it possible to achieve precise epigenetic localization
using only a very small amount of raw material using fluorescence microscopy.
For example, it can be used to look at epigenetic markers on nucleosomes, which are fragments
of DNA wrapped around a protein "spool.
" When cells are destroyed, these nucleosomes can flow into the bloodstream like floaters, so Shema reasoned that the millions of nucleosomes found in the blood could be analyzed to detect cancer
.

Using Shema's single-molecule imaging approach, Fedyuk and Erez and colleagues compared
nucleosomes in the blood of 30 healthy individuals with 60 patients with colorectal cancer at different stages.
They found that the nucleosomes of the two groups had significantly different patterns
of epigenetic markers.
The analysis covered six different epigenetic modifications associated with cancer, as well as a variety of other cancer indicators, including protein fragments from dead tumors that could not be detected by conventional techniques
.

Next, in collaboration with Professor Guy Ron of the Ragha Institute of Physics at the Hebrew University of Jerusalem, the scientists combined their revealed molecular biology of cancer with artificial intelligence algorithms to apply machine learning to large
datasets obtained from both groups.
The analysis looked not only at all of these cancer markers, but also at combinations and relationships
between them.
To make sure their findings weren't limited to colorectal cancer, the scientists also applied their technique to compare
blood nucleosomes from healthy volunteers with those of 10 pancreatic cancer patients.

"Our algorithm can distinguish between healthy and patient groups with record certainty in this type of study with 92 percent
accuracy," Shema said.
Scientists call this new technique EPINUC, an acronym
for "Epigenetics of Plasmapherization of Nucleosomes.
"

If supported by studies involving more patients, these findings could lead to the use of multiparametric blood tests of less than 1 milliliter of blood to detect and diagnose cancer
.
In the future, thanks to the level of detail revealed in the analysis, the results of this blood test may also advance personalized medicine
by recommending the best treatment for each patient.

Shema concludes: "We have successfully demonstrated the concept of our method, which now needs to be proven
in clinical trials.
In the future, our multiparametric approach can be used not only to diagnose various cancers, but also to diagnose other diseases that leave traces in the blood, such as autoimmune diseases or heart disease
.
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