May 16, 2019
The University of Illinois at Chicago College of Dentistry’s Dr. Guy Adami and Dr. Joel Schwartz are harnessing the power of big data to change the landscape of oral cancer prevention. To do this, they are combining the latest advances in machine learning with one of the oldest functional food products in the world: green tea.
With a team of oral science experts and computer scientists, Adami and Schwartz, professors in the Department of Oral Medicine and Diagnostic Sciences, aim to gain insight into how different people respond to the polyphenols found in green tea through the genomic analysis of molecules called RNAs. These polyphenols, also present in many other common foods and drinks, have been shown in animal studies to reduce the risk of cancer development and progression.
“If we knew which people show the greatest response to drinking green tea and could apply it to cancer prevention, we could develop more effective treatments, or even personalized medicines," said Adami.
Using samples from the mouth, team members knew they were on to something because of noticeable changes in the kinds of bacteria found in the tea drinkers’ mouths. From these samples taken using a tool similar to a toothbrush, they analyzed RNA changes in cells from the tongue and gums.
“With standard analysis methods, we couldn’t be sure the tea was doing anything to the cells because the variability in the data made it inconclusive,” said Adami.
To solve this, Adami brought in a computational genomics expert, Dr. Saurabh Sinha, co-director of the Knowledge Engine for Genomics (KnowEnG) Center at the University of Illinois Urbana-Champaign and associate professor in the Department of Computer Science.
“What our KnowEnG center and platform does is turn big data into knowledge using a combination of data science and machine learning to enhance the analysis of genomics studies,” Sinha explained.
Using the new cloud-based platform, the team was able to perform a much deeper analysis into how the polyphenols were interacting with human cells. They further enhanced those insights using the power of machine learning by integrating their small sample data with a much larger knowledge base about gene relationships and other bioinformatics developed over decades from a vast genomics research community.
“After running the data through the KnowEng platform, it was like a light bulb turned on,” said Adami. “We could clearly see the effects of green tea on the cells lining the mouth.”.
Polyphenols are a category of chemicals that naturally occur in many vegetables and fruits. They offer several health benefits, including their role as antioxidants, which can combat cell damage, as well as their effects on reducing inflammation and helping to fight cancer. Green tea is rich in polyphenols and offers a number of other health benefits. However, its association with fighting cancer is yet to be well understood.
Adami and Schwartz’s team analyzed the effects of green tea polyphenols on cells in the mouth and the genes they express for a better understanding of how they might prevent oral cancer. The study included 11 subjects and analyzed 360 microRNAs. Specifically, they wanted to know whether there were any microRNA differences between one group that had been drinking green tea for four weeks and another that did not.
MicroRNAs often are selected for analysis in modern cancer research as potential diagnostic biomarkers and therapeutic targets. They influence multiple processes that are relevant to cancer, such as cell proliferation, metabolism, differentiation, and migration.
With traditional analysis methods, it was unclear if the green tea was doing anything to the cells because of data variability. Through a deeper level of genomics analysis, the team was able to clearly see how RNAs change in sync after drinking green tea, and how some people’s cells were more sensitive to green tea polyphenols than others.
“The biggest ‘a-ha’ moment was when we saw the changes in the bacteria in the tea drinkers after just four weeks,” said Adami. “The deep genomics analysis let us detect changes in the RNA, while also ensuring we weren't just seeing things that happened by chance.”
The cloud-based KnowEnG is an analytical platform that takes advantage of algorithms used successfully in other data mining endeavors, including Google’s search functions, but have not been previously applied to interpretation of genomic data. By placing their new results into the context of the Knowledge Network, biomedical researchers can produce a high-powered analysis of new genomic and transcriptomic datasets.
“These studies were a great match for our computational genomics capabilities because our deep analysis methods could help answer questions that have eluded researchers for some time, and those answers may one day lead to improvements in how cancers, particularly cancers of the head and neck, are diagnosed and treated,“ said Sinha, who leads the KnowEnG platform.
KnowEnG’s Knowledge Network combines a vast volume of prior data from multiple high quality public genomic information sources and integrates the information with new research data. This helps researchers better understand and identify the connection between genes and cells, how RNAs and miRNAs regulate cell activity, and disease progression in the context of a genomic study.
The team is planning further research to better understand the significance of the RNA changes. “While the computational biological methods led us to identify changes in human oral cell RNA with green tea consumption, we do not know what these changes mean yet,” Adami said.
There is certainly a need for such research that holds the promise of one day saving millions from a cancer diagnosis.
In the United States, over 43,000 people will be diagnosed this year and over 9,000 will die from head and neck cancers. The disease is the sixth most common cancer type worldwide and remains a major cause of death and disability.
Researchers at UIC continue to work on discoveries that may one day move humanity closer to cures and effective preventative measures. From tailored chemotherapy treatments to improved screening and preventative diets, there is significant promise for unlocking unprecedented medical precision.
“In our center (KnowEnG) we are using similar genomics analysis to determine the right drug treatment for particular types of cancer, where there isn’t a clear answer as to which drug or dosage is best,” said Sinha.
One day a quick mouth swab during a routine physical check-up may be able to generate a genetic data sample that could quickly lead to diagnosis and preventive treatment. From tailored chemotherapy treatments to improved screening and preventative diets, big data holds significant promise for unlocking unprecedented medical precision.
“Every person is different, and we hope to one day use those differences to help the ones who are suffering from cancers and other oral diseases,” said Adami.
The Oral Medicine and Facial Pain Clinic at the College provides a broad range of diagnosis and non-surgical treatment for the treatment of oral mucosal diseases, including oral complications of medical therapy including cancer treatment (i.e. chemotherapy and radiation therapy); oral changes associated with systemic diseases; salivary gland dysfunction and dry mouth; inflammatory conditions including mucosal auto-immune diseases; viral, bacterial and fungal infections; benign growths; diagnosis of oral cancer and pre-cancerous lesions; canker sores; bad breath; taste changes; ad oral manifestations of HIV. The clinic uses a multidisciplinary approach to expertly diagnose and treat these oral mucosal diseases. Call (312) 355-1222 or email firstname.lastname@example.org.