A novel artificial intelligence blood testing technology has been used to successfully detect lung cancer in a 2021 study has now detected more than 80% of liver cancers in a new study of 724 people.
From: Johns Hopkins Medicine
November 18, 2022 -- The
blood test, called DELFI (DNA evaluation of fragments for early interception)
detects fragmentation changes among DNA from cancer cells shed into the
bloodstream, known as cell-free DNA (cfDNA). In the most recent study,
investigators used the DELFI technology on blood plasma samples obtained from
724 individuals in the U.S., the European Union (E.U.) and Hong Kong to detect
hepatocellular cancer (HCC), a type of liver cancer.
The researchers believe
this is the first genome-wide fragmentation analysis independently validated in
two high-risk populations and across different racial and ethnic groups with
different causes associated with their liver cancers.
Their findings were
reported Nov. 18 in Cancer Discovery and at the American
Association for Cancer Research Special Conference: Precision Prevention, Early
Detection, and Interception of Cancer.
It is estimated that
400 million people worldwide are at higher risk of developing HCC because of
cirrhosis from chronic liver diseases including chronic viral hepatitis or
non-alcoholic fatty liver disease, according to a worldwide analysis of the
burden of liver disease (J. Hepatology, 2019).
"Increased early
detection of liver cancer could save lives, but currently available screening
tests are underutilized and miss many cancers," says Victor Velculescu,
M.D., Ph.D., professor of oncology and co-director of the Cancer Genetics and
Epigenetics Program at the Johns Hopkins Kimmel Cancer Center, who co-led the
study with Zachariah Foda, M.D., Ph.D., gastroenterology fellow, Akshaya
Annapragada, M.D./Ph.D. student, and Amy Kim, M.D., assistant professor of
medicine at the Johns Hopkins University School of Medicine.
Of the 724 plasma
samples studied, 501 were collected in the U.S. and E.U. and included samples
from 75 people with HCC to train and validate the machine learning model, a
type of artificial intelligence that uses data and algorithms to improve
accuracy, explains Foda. For validation, an additional 223 plasma samples were
analyzed from individuals in Hong Kong and included samples from 90 people with
HCC, 66 with hepatitis B virus (HBV), 35 with HBV-related liver cirrhosis and
32 people with no underlying risk factors.
The DELFI technology
uses a blood test to measure the way DNA is packaged inside the nucleus of a
cell by studying the size and amount of cell-free DNA present in the
circulation from different regions across the genome. Healthy cells package DNA
like a well-organized suitcase, in which different regions of the genome are
placed carefully in various compartments. The nuclei of cancer cells, by contrast,
are like more disorganized suitcases, with items from across the genome thrown
in haphazardly. When cancer cells die, they release DNA fragments in a chaotic
manner into the bloodstream.
DELFI identifies the
presence of cancer by examining millions of cfDNA fragments for abnormal
patterns, including the size and amount of DNA in different genomic regions.
The DELFI approach only requires low-coverage sequencing, enabling this
technology to be cost-effective in a screening setting, the researchers say.
In the latest study,
researchers performed the test -- which was previously shown to accurately
classify lung cancer -- on cfDNA fragments isolated from the plasma samples.
They analyzed the patterns of fragmentation across each sample to develop a DELFI
score.
Scores were low for
cancer-free individuals with viral hepatitis or cirrhosis (median DELFI score
was 0.078 and 0.080, respectively), but, on average, 5 to 10 times higher for
the 75 HCC patients in the U.S./E.U. samples, with high scores observed across
all cancer stages, including early-stage disease (DELFI scores for Stage 0 =
0.46, Stage A = 0.61, Stage B = 0.83, and Stage C = 0.92). In addition, the
test detected fragmentation changes in the content and packaging of liver
cancer genomes, including from genome regions associated with liver-specific
activity.
The DELFI technology
detected liver cancers at their earliest stages, with an overall sensitivity --
or ability to accurately detect a cancer -- of 88% and a specificity of 98%,
which means it almost never incorrectly provided a false positive result, among
people at average risk. In samples collected from those at high risk of HCC,
the test had 85% sensitivity and 80% specificity.
"Currently, less
than 20% of the high-risk population get screened for liver cancer due to
accessibility and suboptimal test performance. This new blood test can double
the number of liver cancer cases detected, compared to the standard blood test
available, and increase early cancer detection," says Kim, co-senior
author on the study.
The researchers say
next steps include validating this approach in larger studies for clinical use.
More than 800,000
people are diagnosed with liver cancer worldwide each year, and it is a leading
cause of cancer deaths worldwide, according to the American Cancer Society.
In addition to
Velculescu, Foda, Annapragada and Kim, other researchers were Kavya Boyapati,
Daniel Bruhm, Nicholas Vulpescu, Jamie Medina, Dimitrios Mathios, Stephen
Cristiano, Noushin Niknafs, Harry Luu, Michael Goggins, Robert Anders, Jing
Sun, Shruti Meta, David Thomas, Gregory Kirk, Vilmos Adleff, Jillian Phallen
and Robert Scharpf.
The research was
supported by the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation,
Stand Up to Cancer-Dutch Cancer Society International Translational Cancer
Research Dream Team Grant (SU2C-AACR-DT1415), the Gray Foundation, the
Commonwealth Foundation, SU2C INTIME Lung Cancer Interception Dream Team Grant,
the Mark Foundation for Cancer Research, a research grant from Delfi
Diagnostics, the National Institutes of Health grants CA121113, CA006973,
CA233259, GM136577, CA237624 and CA062924, and Department of Defense CDMRP
Award W81XWH-20-1-0605. Stand Up to Cancer is a program of the Entertainment
Industry Foundation administered by the American Association for Cancer
Research.
The researchers
disclose the following competing interests: Velculescu is a founder of Delfi
Diagnostics, serves on the board of directors and as a consultant for this
organization, and owns Delfi Diagnostics stock, which is subject to certain
restrictions under Johns Hopkins University policy. Additionally, The Johns
Hopkins University owns equity in Delfi Diagnostics. Velculescu divested his
equity in Personal Genome Diagnostics (PGDx) to LabCorp in February 2022. He is
an inventor on patent applications submitted by The Johns Hopkins University
related to cancer genomic analyses and cell-free DNA for cancer detection that
have been licensed to one or more entities, including Delfi Diagnostics,
LabCorp, Qiagen, Sysmex, Agios, Genzyme, Esoterix, Ventana and ManaT Bio. Under
the terms of these license agreements, the university and inventors are
entitled to fees and royalty distributions. Velculescu is an adviser to
Danaher, Takeda Pharmaceuticals and Viron Therapeutics. Scharpf is a founder
and consultant of Delfi Diagnostics and owns Delfi Diagnostics stock subject to
certain restrictions under university policy. These arrangements have been
reviewed and approved by The Johns Hopkins University in accordance with its
conflict-of-interest policies.
https://www.sciencedaily.com/releases/2022/11/221118114845.htm
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