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Salivary Protein Database Could Benefit Precision Medicine

The database is the first public platform that catalogs and curates information on salivary proteins, which could improve the development of precision medicine.

A new database could help researchers explore the complex nature of saliva, potentially advancing precision medicine, according to a study published in the Journal of Dental Research.

The Human Salivary Proteome Wiki, funded by the National Institute of Dental and Craniofacial Research (NIDCR), provides researchers and clinicians with unbiased evidence from multiple independent studies to better understand saliva, and includes analytical tools to search for data by tissue type, disease, and more.

"This community-based data and knowledge base will pave the way to harness the full potential of the salivary proteome for diagnosis, risk prediction, and therapy for oral and systemic diseases, and increase preparedness for future emerging diseases and pandemics," said Stefan Ruhl, DDS, PhD, lead investigator of the study, curator of the Human Salivary Proteome Wiki, and professor of oral biology in the University at Buffalo School of Dental Medicine.

Saliva facilitates digestion, taste, swallowing, and speech, and serves as the first line of defense against pathogens in the mouth, protecting the body from harmful microbes. Saliva plays an important role in immune responses and it can be easily collected as a fluid sample, making it a desirable tool in precision medicine and noninvasive diagnostics.

During the COVID-19 pandemic, it was widely used to detect the virus and track the body’s immune response.

"Saliva has become an attractive body fluid for on-site, remote and real-time monitoring of oral and systemic health. The scientific community needs a saliva-centered information platform that keeps pace with the rapid accumulation of new data and knowledge," said William Lau, PhD, of the National Institutes of Health (NIH) and first author of the study.

However, researchers noted that saliva is challenging to study because of the high variability in the thousands of salivary proteins. Therefore, normal ranges for the compensation of saliva need to be established to define the status of health.

Developed in collaboration with the NIH Center for Information Technology, the Human Salivary Proteome Wiki was released in 2019 as a user-friendly public database to provide rich analytical, curation, and annotation tools for the biomedical research community.

The database compiles information and research on the salivary proteome, genome, transcriptome (types and levels of mRNA expressed in salivary gland tissue), and glycome (array of sugars attached to salivary glycoproteins).

Users may submit proposals to add, remove, or modify data to an interdisciplinary team of curators who ensure information is accurate and supported by sound scientific evidence. Annotations are also credited to the researchers and clinicians who submit them to the wiki, helping drive references to critical research.

"The Human Salivary Proteome Wiki will improve salivary sciences, saliva-based diagnostics, precision medicine and dentistry, and ultimately facilitate personalized treatment for both oral and systemic diseases," said Preethi Chander, PhD, program director of the NIDCR Salivary Biology and Immunology Program.

Other researchers are leveraging large volumes of information to advance precision medicine treatments. A team from The Ohio State University Comprehensive Cancer Center - Arthur G. James Cancer Hospital and Richard J. Solove Research Institute (OSUCCC - James) conducted a study of genomic data in patients with advanced small cell lung cancer.

Researchers found new insights into the patterns of treatment resistance, which could pave the way for precision medicine treatments.

"Advanced SCLC often does not respond as well to immune therapies that are effective in other types of lung cancer, and the reasons for this are poorly understood," said principal investigator Sameek Roychowdhury, MD, PhD, a medical oncologist and member of the OSUCCC - James Translational Therapeutics Research Program. 

"Our findings suggest that the causes of treatment resistances in advanced small cell lung cancer may be subtype-specific. They also highlight the importance of tumor genomic studies to identify the most effective therapies for these patients and to support development of new therapies for this often-fatal disease."

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