Novel AI blood testing technology can ID lung cancers with high accuracy


Date:
August 20, 2021
Source:
Johns Hopkins Medicine
Summary:
A novel artificial intelligence blood testing technology was
found to detect over 90% of lung cancers in samples from nearly
800 individuals with and without cancer.



FULL STORY ==========================================================================
A novel artificial intelligence blood testing technology developed
by researchers at the Johns Hopkins Kimmel Cancer Center was found to
detect over 90% of lung cancers in samples from nearly 800 individuals
with and without cancer.


==========================================================================
The test approach, called DELFI (DNA evaluation of fragments for early interception), spots unique patterns in the fragmentation of DNA shed from cancer cells circulating in the bloodstream. Applying this technology
to blood samples taken from 796 individuals in Denmark, the Netherlands
and the U.S., investigators found that the DELFI approach accurately distinguished between patients with and without lung cancer.

Combining the test with analysis of clinical risk factors, a protein
biomarker, and followed by computed tomography imaging, DELFI helped
detect 94% of patients with cancer across stages and subtypes. This
included 91% of patients with earlier or less invasive stage I/II cancers
and 96% of patients with more advanced stage III/IV cancers. These
results will be published in the August 20 issue of the journal Nature Communications.

Lung cancer is the most common cause of cancer death, claiming almost 2
million lives worldwide each year. However, fewer than 6% of Americans at
risk for lung cancers undergo recommended low-dose computed tomography screening, despite projections that tens of thousands of deaths could
be avoided, and even fewer are screened worldwide, explains senior
study author Victor E. Velculescu, M.D., Ph.D., professor of oncology
and do-director of the Cancer Genetics and Epigenetics Program at
the Johns Hopkins Kimmel Cancer Center. This is due to a variety of
reasons, including concerns of potential harm from investigation of
false positive imaging results, radiation exposure or worries about complications from invasive procedures. "It is clear that there is an
urgent, unmet clinical need for development of alternative, noninvasive approaches to improve cancer screening for high-risk individuals and, ultimately, the general population," says lead author Dimitrios Mathios,
a postdoctoral fellow at the Johns Hopkins Kimmel Cancer Center. "We
believe that a blood test, or 'liquid biopsy,' for lung cancer could
be a good way to enhance screening efforts, because it would be easy
to do, broadly accessible and cost-effective." The DELFI technology
uses a blood test to indirectly 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 in a chaotic manner
into the bloodstream. DELFI helps identify the presence of cancer using
machine learning, a type of artificial intelligence, to examine millions
of cell-free DNA fragments for abnormal patterns, including the size and
amount of DNA in different genomic regions. This approach provides a view
of cell-free DNA referred to as the "fragmentome." The DELFI approach only requires low-coverage sequencing of the genome, enabling this technology
to be cost-effective in a screening setting, the researchers say.

For the study, investigators from Johns Hopkins, working with researchers
in Denmark and the Netherlands, first performed genome sequencing of
cell-free DNA in blood samples from 365 individuals participating in a seven-year Danish study called LUCAS. The majority of participants were
at high risk for lung cancer and had smoking-related symptoms such as
cough or difficulty breathing.

The DELFI approach found that patients who were later determined to
have cancer had widespread variation in their fragmentome profiles,
while patients found not to have cancer had consistent fragmentome
profiles. Subsequently, researchers validated the DELFI technology
using a different population of 385 individuals without cancer and
46 individuals with cancer. Overall, the approach detected over 90%
of patients with lung cancer, including those with early and advanced
stages, and with different subtypes. "DNA fragmentation patterns provide
a remarkable fingerprint for early detection of cancer that we believe
could be the basis of a widely available liquid biopsy test for patients
with lung cancer," says author Rob Scharpf, Ph.D., associate professor
of oncology at the Johns Hopkins Kimmel Cancer Center.

A first-of-a-kind national clinical trial called DELFI-L101, sponsored by
the Johns Hopkins University spin-out Delfi Diagnostics, is evaluating a
test based on the DELFI technology in 1,700 participants in the U.S.,
including healthy participants, individuals with lung cancers and
individuals with other cancers.

The group would like to further study DELFI in other types of cancers.

Other scientists who contributed to the work include Stephen Cristiano,
Jamie E. Medina, Jillian Phallen, Daniel Bruhm, Noushin Niknafs, Leonardo Ferreira, Vilmos Adleff, Jia Yuee Ciao, Alessandro Leal, Michael Noe,
James White, Adith S. Arun, Carolyn Hruban, Akshaya V. Annapragada,
Patrick M. Forde, Valsamo Anagnostou and Julie R. Brahmer of Johns
Hopkins. Additional authors were from Herlev and Gentofte Hospital and Bispebjerg Hospital in Copenhagen; Aarhus University Hospital in Aarhus, Denmark; Herning Regional Hospital in Herning, Denmark; the Netherlands
Cancer Institute in Amsterdam; Delfi Diagnostics; and Hvidovre Hospital
in Hvidovre, Denmark.

The work was supported in part by the Dr. Miriam and Sheldon G. Adelson
Medical Research Foundation; a Stand Up to Cancer /INTIME Lung
Cancer Interception Dream Team grant; Stand Up to Cancer-Dutch Cancer
Society International Translational Cancer Research Dream Team Grant (SU2C-AACR-DT1415); the Gray Foundation; the Commonwealth Foundation;
the Mark Foundation for Cancer Research; the Lundbeck Foundation;
an unrestricted grant from Roche Denmark; a research grant from Delfi Diagnostics; and National Institutes of Health grants CA121113, CA006973, CA233259 and 1T32GM136577.

Mathios, Cristiano, Phallen, Leal, Adleff, Scharpf and Velculescu are
inventors on patent applications submitted by Johns Hopkins University
related to cell- free DNA for cancer detection. Cristiano, Phallen,
Leal, Adleff and Scharpf are founders of Delfi Diagnostics, and Adleff
and Scharpf are consultants for this organization. Velculescu is a
founder of Delfi Diagnostics and of Personal Genome Diagnostics, serves
on the board of directors and as a consultant for both organizations,
and owns Delfi Diagnostics and Personal Genome Diagnostics stock, which
are subject to certain restrictions under university policy. The Johns
Hopkins University owns equity in Delfi Diagnostics and Personal Genome Diagnostics. Additionally, Velculescu is an adviser to Bristol-Myers
Squibb, Genentech, and Takeda Pharmaceuticals. The terms of these
arrangements are managed by The Johns Hopkins University in accordance
with its conflict of interest policies.

========================================================================== Story Source: Materials provided by Johns_Hopkins_Medicine. Note:
Content may be edited for style and length.


========================================================================== Journal Reference:
1. Dimitrios Mathios, Jakob Sidenius Johansen, Stephen Cristiano,
Jamie E.

Medina, Jillian Phallen, Klaus R. Larsen, Daniel C. Bruhm,
Noushin Niknafs, Leonardo Ferreira, Vilmos Adleff, Jia Yuee Chiao,
Alessandro Leal, Michael Noe, James R. White, Adith S. Arun,
Carolyn Hruban, Akshaya V. Annapragada, Sarah O/strup Jensen,
Mai-Britt Worm O/rntoft, Anders Husted Madsen, Beatriz Carvalho,
Meike de Wit, Jacob Carey, Nicholas C.

Dracopoli, Tara Maddala, Kenneth C. Fang, Anne-Renee Hartman,
Patrick M.

Forde, Valsamo Anagnostou, Julie R. Brahmer, Remond J. A. Fijneman,
Hans Jo/rgen Nielsen, Gerrit A. Meijer, Claus Lindbjerg Andersen,
Anders Mellemgaard, Stig E. Bojesen, Robert B. Scharpf, Victor
E. Velculescu.

Detection and characterization of lung cancer using cell-free
DNA fragmentomes. Nature Communications, 2021; 12 (1) DOI:
10.1038/s41467- 021-24994-w ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2021/08/210820093400.htm

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