Use of artificial intelligence in clinical laboratory testing could improve the diagnosis of cancer worldwide
In a proof of concept study, scientists at Shanghai Jiao Tong University in China have developed a clinical laboratory test that utilizes artificial intelligence (AI) to diagnose three types of cancer from a single drop of dried blood. The paper-based test was able to identify patients with colorectal, gastric, and pancreatic cancers and distinguish between patients with and without cancer.
The team’s goal was to develop a way to diagnose cancer while the disease is still in the earlier stages, especially in rural areas.
“Over a billion people across the world experience a high rate of missed disease diagnosis, an issue that highlights the need for diagnostic tools showing increased accuracy and affordability. In addition, such tools could be used in ecologically fragile and energy-limited regions, pointing to the need for developing solutions that can maximize health gains under limited resources for enhanced sustainability,” the researchers wrote in an article published in the journal Nature Sustainability titled, “A Sustainable Approach to Universal Metabolic Cancer Diagnosis.”
The researchers determined that by using less than 0.05 millimeters of dried blood, their test could accurately and quickly identify if a patient had cancer between 82% to 100% of the time.
According to Chaoyuan Kuang, MD, PhD (above), an oncologist at Montefiore Health System and assistant professor at the Albert Einstein College of Medicine, unlike liquid blood, dried serum can be “collected, stored, and transported at much lower cost and with much simpler equipment,” Live Science reported. “This could help democratize the availability of cancer early detection testing across the world,” he added. A paper-based clinical laboratory test that can detect and distinguish one cancer type from another would be a boon to cancer diagnosis worldwide. (Photo copyright: Albert Einstein College of Medicine.)
Improving Cancer Screening in Rural Areas
An earlier study conducted in China in 2022 examined results from 1,570 cancer survivors from both urban and rural areas of China. That study showed that 84.1% of the patients were diagnosed with cancer only after developing symptoms and that urban patients were more likely to be diagnosed in the early stages of cancer. In addition, rural patients also had less screening and treatment options available to them.
The researchers in this latest Chinese study tested their AI model on blood donors with and without cancer and compared the results to traditional liquid-blood biopsy tests.
“Based on modeling they performed, they reported the new tool could reduce the estimated proportion of undiagnosed cases of pancreatic, gastric, and colorectal cancers by about 20% to 50% if it was used for population-level cancer screening in rural China,” Live Science reported.
The scientists used dried serum spots (DSS) and machine learning to perform the research. According to their Nature Sustainability paper, DSS can be challenging in cancer research because sensitive biomarkers in the samples are often degraded or have inadequate amount of blood for proper analysis. To circumvent these issues, the researchers used nanoparticle-enhanced laser desorption/ionization mass spectrometry (NPELDI MS) to increase reliability and sensitivity. Inorganic nanoparticles were applied to the samples to strengthen selectivity and refine metabolic compounds from the samples.
However, the study authors noted that “the adaptation of NPELDI MS to dried spot analysis has not been validated,” Interesting Engineering reported.
A ‘Great Start’
The machine learning algorithm the Chinese scientists created demonstrates that DSS samples can be used to preserve important biological markers and could be beneficial in the diagnosis of cancer.
Their research indicated an overall reduction rate of undiagnosed cancers in the range of 20.35% to 55.10%. The researchers estimated the implementation of their AI tool could reduce the proportion of specific undiagnosed cancer cases in rural China by:
84.30% to 29.20% for colorectal cancer,
77.57% to 57.22% for gastric cancer, and
34.56% to 9.30% for pancreatic cancer.
It’s a “great start,” Chaoyuan Kuang, MD, PhD, an oncologist at Montefiore Health System and assistant professor at the Albert Einstein College of Medicine told Live Science. “This cancer test won’t enter use for a long time,” he said. Nevertheless, the potential of the tool is “immense,” he added, but that “we are still years away from being able to offer this test to patients.
“With further development, it could theoretically be used for the early detection of other types of cancer or for other diseases, or to monitor the progression of disease in patients who have already been diagnosed,” he noted.
Further research and clinical trials are needed before this AI tool can be used in a clinical diagnostic setting. This study is another example of researchers looking for cancer biomarkers in specimen types that are not tissue and further supports the hope that machine learning may one day detect cancer in earlier stages, increase survival rates, and save healthcare costs.
One factor motivating this type of research in China is the fact that the nation has more than 36,000 hospitals and approximately 20,000 anatomic pathologists. Of this total, only a minority of these pathologists have been trained to the standards of North America and Northern Europe.
Like other nations, China’s demand for subspecialist pathology services outstrips its supply of such pathologists. This is the reason why researchers in that country want to develop diagnostic assays for cancer and other diseases that are faster, cheaper, and comparable to a human pathologist in accuracy.
Study findings may lead to new clinical laboratory tests, as well as vaccines and immunotherapies for neurodegenerative diseases
Research into the human genome continues to produce useful new insights. This time, a study led by researchers at Stanford University identified a genetic variation that is believed to help “slow or even stall” progression of neurodegenerative diseases, including Alzheimer’s and Parkinson’s, according to a press release. Because these genetic variations are common, it is likely that diagnostic tests can be developed for use by clinical laboratories.
Researchers at Stanford Medicine led the study which discovered that approximately one in five individuals carry the gene variant, a protective allele identified as DR4 (aka, HLA-DR4). It’s one of a large number of alleles found in a gene known as DRB1.
DRB1 is part of a family of genes collectively known as the human lymphocyte antigen complex or HLA. The HLA-DRB1 gene plays a crucial role in the ability of the immune system to see a cell’s inner contents.
“In an earlier study, we’d found that carrying the DR4 allele seemed to protect against Parkinson’s disease,” said Emmanuel Mignot, MD, PhD (above), Director of the Stanford Center for Narcolepsy, in a Stanford press release. “Now, we’ve found a similar impact of DR4 on Alzheimer’s disease.” Clinical laboratories may soon have new vaccines for both neurodegenerative diseases. (Photo copyright: Stanford University.)
DR4 Found to Impact Both Parkinson’s and Alzheimer’s Diseases
To perform their research, the team examined a large collection of medical and genetic databases from 176,000 people who had either Alzheimer’s or Parkinson’s disease. The people involved in the study were from numerous countries located in East Asia, Europe, the Middle East and South America. Their genomes were then compared with people who did not have the diseases, focusing on the incidence and age of onset.
“In an earlier study we’d found that carrying the DR4 allele seemed to protect against Parkinson’s disease,” said Mignot in the Stanford press release. “Now, we’ve found a similar impact of DR4 on Alzheimer’s disease.”
The team found that about 20% to 30% of people carry DR4, and that they have around a 10% risk reduction for developing the two diseases.
“That this protective factor for Parkinson’s wound up having the same protective effect with respect to Alzheimer’s floored me,” said Emmanuel Mignot, MD, PhD, the Craig Reynolds Professor of Sleep Medicine in the Department of Psychiatry and Behavioral Sciences at Stanford University and the Director of the Stanford Center for Narcolepsy, in the Stanford Medicine press release. “The night after we found that out, I couldn’t sleep.”
The scientists also analyzed data from autopsied brains of more than 7,000 Alzheimer’s patients and discovered that individuals who carry DR4 had fewer neurofibrillary tangles and that those tangles are composed mainly of modified tau proteins, a common biomarker for Alzheimer’s.
The presence of these tangles corresponds with the severity of Alzheimer’s disease. They are not typically seen in Parkinson’s patients, but the Stanford team found that Parkinson’s patients who did carry DR4 experienced later onset of symptoms.
Mignot stated that tau, which is essential in Alzheimer’s, may also play a role in Parkinson’s, but that further research is required to prove its function.
Both diseases are characterized by the progressive loss of certain nerve cells or neurons in the brain and are linked to an accumulation of abnormal proteins. The Stanford researchers suggested that the DR4 gene variant may help protect individuals from Alzheimer’s and Parkinson’s by preventing the buildup of tau proteins.
“This is a very interesting study, providing additional evidence of the involvement of the immune system in the pathogenesis of Alzheimer’s and Parkinson’s,” neurologist Wassim Elyaman, PhD, Assistant Professor of Neurological Sciences in Neurology, the Taub Institute and the Institute for Genomic Medicine at Columbia University, told Live Science.
New Vaccines and Immunotherapies
According to the Alzheimer’s Association, more than six million Americans are currently living with Alzheimer’s disease and approximately one in three Americans die with Alzheimer’s or another dementia.
The Parkinson’s Foundation states that nearly one million Americans are currently living with Parkinson’s disease, and that number is expected to rise to 1.2 million by 2030. Parkinson’s is the second-most common neurodegenerative disease after Alzheimer’s disease.
Even though the genetic analysis of the Stanford research is strong, more immune cell and blood-based research is needed to definitively establish how tau is connected to the two diseases.
This research could have implications for clinical laboratories by giving them biomarkers for a useful new diagnostic test, particularly for diagnosing Alzheimer’s and Parkinson’s.
Further, Mignot suggested that an effective vaccine could delay the onset or slow the progression of both diseases. He hopes to test his hypothesis on genetically modified mice and eventually human subjects.