Researchers develop new method for identifying oral #cancer


In a new study, researchers in Brazil have identified a correlation between oral cancer progression and the abundance of specific proteins present in tumor tissue and saliva. (Photograph: pongwit sanongboon/Shutterstock)

SÃO PAULO, Brazil: In a discovery that may help the early identification of oral squamous cell carcinoma (OSCC), researchers in Brazil have found a correlation between the cancer’s progression and the abundance of specific proteins present in tumor tissue and saliva. The discovery offers parameters for predicting the progression of the disease and may help in overcoming the limitations of clinical and imaging exams.

“We worked on the study for five years until we achieved this breakthrough,” said contributing author Adriana Franco Paes Leme, a researcher at the Brazilian National Bioscience Laboratory—part of National Energy and Materials Research Center (CNPEM) in São Paulo.

During the first phase of the study, researchers used laser microdissection and proteomics to map the proteins in mouth cancer tissue and correlate them with the clinical characteristics of the patients. This analysis enabled the identification of several proteins, such as CSTB, NDRG1, LTA4H, PGK1, COL6A1, ITGAV and MB—with differing levels of abundance depending on the tumor area—and link them to key clinical outcomes.

After identifying and quantifying proteins in about 120 tumor tissue samples, the second phase of the study saw researchers deploy two protein verification strategies. “One strategy consisted of gauging the abundance of the selected proteins in independent tissue samples using immunohistochemistry with antibodies. The other consisted of monitoring the same preselected targets in patients’ saliva,” explained Paes Leme.

“Saliva is a promising source of markers, as well as being a fluid obtained by noninvasive collection,” she explained. “We verified the proteins in saliva from 40 patients. Technical triplicates were analyzed to achieve the highest possible confidence level for the results in this phase of the study.”

After analyzing the saliva samples, researchers used bio-informatics and machine learning techniques to obtain prognostic signatures. From here, they were able to verify which of the proteins or peptides were selected during the first phase and could thereby distinguish between patients who had or did not have cervical lymph node metastasis.

According to the study’s results, it was possible to identify three specific peptides—LTA4H, COL6A1 and CSTB —that can be used as a signature to classify patients with and without cervical lymph node metastasis. Researchers believe that this could potentially help doctors overcome the limitations of clinical exams and guide personalized treatment strategies.

“The data led to robust results that are highly promising as guides to defining the severity of the disease. We suggested potential markers of the disease in the first phase of the study and verified these markers in the second phase, enhancing the reliability of the findings and showing that these markers are effective in classifying patients with cervical lymph node metastasis,” said Paes Leme.

Scientists are now working on a new study designed to use translational techniques to build affordable biosensors that are capable of detecting prognostic signatures in patients’ saliva.

The study, titled “Combining discovery and targeted proteomics reveals a prognostic signature in oral cancer”, was published on September 5 in Nature Communications.

Partners of the study included the São Paulo State Cancer Institute, the University of Campinas’s Piracicaba Dental School and Institute of Computing, the University of São Paulo’s Mathematics and Computer Science Institute in São Carlos, the Dental School of the West Paraná University, as well as other institutions in and outside of Brazil. It was funded by the São Paulo Research Foundation, with the research conducted at the National Energy and Materials Research Center.