About OneTest for Cancer

The foundation of OneTest is the measurement of a panel of protein biomarkers. OneTest is not a genetic test that predicts your lifetime risk of cancer. Instead, it measures a group of tumor-associated proteins secreted by tumors as they grow. These biomarkers have been widely used for cancer screening outside of the U.S., especially in the Far East (Japan, South Korea, China) for over two decades. In that region, tens of millions of individuals receive what are often day-long health check-ups that include blood tests that measure the levels of the same biomarkers that are part of OneTestTM.

A unique feature of OneTest is the incorporation of machine learning algorithms to improve the performance of biomarker testing alone. Machine Learning is a form of artificial intelligence (AI) in which a computer system has the ability to continually process and incorporate new data and thus fine tune its output over time. Because the algorithm used to combine biomarker levels with relevant clinical factor data is derived from machine learning, this algorithm is amenable to periodic review and redefinition.. By leveraging additional data from the US population and expanding the number of clinical factor predictors, we expect to improve the accuracy of the OneTest algorithm over time.

OneTest customers who permit us to use their biomarker levels, clinical inputs, and cancer / non-cancer outcomes for further algorithm development will eventually help improve the health outcomes of those who subsequently take the test.

What is Unique and Advantageous about OneTest?

It can help with early detection of lung, liver, pancreas, and other cancers that are not widely screened for in the United States.
Although screening for all the major cancer types has been widespread in the Far East for decades, most Americans are routinely tested only for colon cancer, plus breast and cervical cancer for women, and prostate cancer for men. OneTest is one of the first blood tests available in the USA that simultaneously screens for different types of cancers, including those of the lungs, liver, pancreas, ovaries, kidneys and others.

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We measure tumor proteins (not genes) which help detect early cancer today, not in the future.
Many popular DNA testing companies today offer not only ancestry analysis, but also tests for inherited genetic abnormalities that pre-dispose the consumer to various diseases. Such tests have very limited value for early cancer detection since recent studies have confirmed that fewer than 5% of the genetic mutations that cause cancer are inherited. Instead, most cancer-causing mutations result from random DNA copying errors over time.

Beyond inherited genetic mutations, research is underway by many to study whether circulating tumor DNA in the blood (“ctDNA”) may be useful for early cancer detection. It will likely be several years before it can be determined whether ctDNA biomarkers are complementary or even superior to protein biomarkers. 20/20 and its research collaborators will be looking at the future potential of circulating tumor DNA and plan to collect and save excess blood samples from as many of our customers as possible for this very purpose.

Our algorithms already provide better accuracy that is expected to continually improve over time.
We use machine learning to compare biomarker levels and other characteristics such as age and gender with a vast database of 28,000 subjects tested over the past 12 years. This approach has been demonstrated to help detect nearly twice as many cancers as biomarker testing alone. (See Accuracy, Reliability & Scientific Support for more details.) While the current algorithm is fixed on the basis of rigorous studies performed to date, 20/20 GeneSystems, Inc. is committed to the performance of regular review of the algorithm as the existing patient dataset grows.As with some popular traffic & navigation apps where a community of drivers share real time road info to alert other drivers to traffic & road conditions, OneTest users who permit us to incorporate their biomarker levels, clinical inputs, and cancer / non-cancer outcomes help improve the health outcomes of those who subsequently take the test.

OneTest is powered and validated by real-world data from asymptomatic individuals.
Most biomarker-based cancer tests are developed and validated using stored laboratory blood samples from cancer patients. The purported accuracy of these tests usually drops considerably when they are later used in a real-world screening setting (i.e. individuals without signs or symptoms of cancer).

OneTest was developed and validated based on one-year outcome data from about 28,000 individuals screened over 12 years at a leading research hospital in Taiwan. This data set will grow and integrate results from our American consumers.

Fire Departments Who Rely on OneTest

Fire Departments Across the Nation Choose to Screen for Cancer with OneTest

Why Fire Departments Choose OneTest?

“As Chief, this was the easiest decision ever. We just bought these for our department. All 411 members have the option to participate if they would like. If your people are your greatest asset, why would you not protect it?”
Chief Landry Merkison
“I just did my test today. It was easy. Just went to my doctor with the kit I got from Onetest. My doctor did some research on the test before I got there and she told me it was a great test for the money.”
Captain Justin Ulrich
“Adding the OneTest into our annual physical assessments has helped to provide not only early warning for some of the common types of cancer plaguing our industry but also a sense of relief and security.”
Mansfield Fire Department
Texas

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OneTest was developed by the company that invented and manufactures the patented BioCheck Suspicious Powder Screening Kits used by hundreds of Fire Departments worldwide

2020 GeneSystems’ CEO Jonathan Cohen and other staff are current or former volunteer firefighters.

View Academic Support for OneTest

“Improving Multi-Tumor Biomarker Health Check-up Tests with Machine Learning Algorithms”

“Machine Learning Algorithms Significantly Improve the Accuracy of Multi Tumor Biomarker Panel for the
Early Detection of Multiple Cancers”