Esophageal adenocarcinoma (EAC) is a cancer that affects the mucus-secreting glands of the lower esophagus; the tube that connects the throat to the stomach. It is the most common form of esophageal cancer and is often preceded by Barrett’s metaplasia (BE), a damaging change in cells lining the esophagus.
While the cause of EAC remains unclear, cell mutations have been linked, perhaps caused by risk factors such as tobacco or alcohol use or chronic damage caused by gastroesophageal reflux disease, or GERD. But the cause of these mutations has proven confusing, in part because the incidence of EAC is disproportionate: African Americans are about four to five times less likely to develop EAC than whites. They are also less likely to experience BE.
In a new study, published Sept. 22, 2022 in the journal JCI InsightResearchers at the University of California’s San Diego School of Medicine, with colleagues in Brazil, used artificial intelligence-led tools to locate both a specific type of immune cell and the disease-causing agent, as well as a specific genetic variation known as an SNP (single nucleotide polymorphism) that acts as a protective factor in African Americans.
SNPs represent a difference in a single DNA building block, called a nucleotide. They normally appear in a person’s DNA. Most have no effect on health or development, but some are associated with disease when the variations are shared by many individuals who are also predisposed to that disease.
The team, led by co-corresponding authors Pradipta Ghosh, MD, professor in the departments of Medicine and Cellular and Molecular Medicine at UC San Diego School of Medicine, and Debashis Sahoo, PhD, associate professor in the departments of Pediatrics at UC San Diego School of Medicine and Computer Science at UC San Diego Jacobs School of Engineering, used artificial intelligence and machine learning to identify progression from BE to EAC in different cell types and tissues, and confirmed their findings using organoids, patient-derived biopsies, and a cross-sectional study of 113 subjects with BE and EAC.
The work confirmed that all EACs originate from BE and pointed to the role of the release of neutrophil, a white blood cell that acts as the immune system’s first line of defense, as the driver of cellular transformation in both EACs and adenocarcinoma of the gastroesophageal region. menopause, a rare esophageal cancer that occurs at the junction between the esophagus and stomach.
Both cancers have poor prognosis, with an overall 5-year survival rate of less than 20 percent.
“This neutrophil booster was prominent in Caucasians, but notably absent in African Americans,” Sahoo said. Conversely, SNPs associated with ethnic changes in absolute neutrophil counts, such as benign ethnic neutropenia characterized by lower neutrophil counts but no increased risk of infection, are common in individuals of African descent and may act as a deterrent to prevent BE from becoming EAC.”
The authors said the findings are important because they trace the cellular continuum from a precancerous state (BE) to cancer, clarifying the role of neutrophils and genetic variation by ethnicity.
A central challenge in genetics is to understand how changes in DNA result in observable changes in an organism. In this case, we found that an SNP that reduces the total number of circulating neutrophils in African Americans also protects them against EACs, a cancer whose progression is driven by neutrophils.”
Pradipta Ghosh, MD, professor, departments of medicine and cellular and molecular medicine, UC San Diego School of Medicine
Ghosh and colleagues are cautiously optimistic that neutrophil-targeted therapies could pose as potential immunotherapies in EACs. She said researchers will continue to explore these possibilities.
The study was conducted by an international team of gastroenterologists, bioinformaticians, experts in pre-cancer biology and cancer genetics, gathered under the umbrella of the Institute for Network Medicine at UC San Diego School of Medicine. The institute promotes several transdisciplinary programs that use biological networks created with AI tools from the Center for Precision Computational Systems Network to map unknown areas of disease.