A novel, non-invasive method for detecting precancerous oral lesions early could lead to more effective oral cancer treatments, as well as improved survival rates.
Oral cancer is the 18th most common cancer worldwide, with some 354 864 new cases and 177 384 deaths reported in 2018. Major risk factors include smoking, alcohol consumption and exposure to the human papillomavirus (HPV).
“Premalignant oral lesions such as leukoplakia (white patch) and erythroplakia (red patch) can also increase the risk of cancer,” explains RAMAN-Dx project coordinator Fiona Lyng, manager of the Radiation and Environmental Science Centre (RESC) at Technological University Dublin, Ireland. “Different degrees of precancer can be defined as mild, moderate and severe dysplasia, depending on the degree of cellular and tissue change.” Despite improvements in treatment, there has been no significant improvement in the 5-year survival rate of oral cancer patients, which remains at around 50 %. A key issue is the fact that diagnosing oral precancer depends in the first instance on visual examination and can therefore be subjective. “There is a clear need for new objective techniques to detect premalignant lesions,” says Lyng. The good news is that optical spectroscopic techniques have shown promise in characterising tissues, cells and biofluids. In particular, Raman spectroscopy, which is often used to identify specific molecules, could have potential for diagnosing oral cancers.
Accurate tissue analysis
The RAMAN-Dx project, which was undertaken with the support of the Marie Skłodowska-Curie Actions programme, sought to build on this, by developing two new methods based on time-gated Raman spectroscopy and surface-enhanced Raman spectroscopy (SERS), for detecting premalignant oral lesions. To begin with, a library of saliva and exfoliated cell samples was collected from both healthy donors and patients with mild, moderate and severe dysplasia and cancer from Dublin Dental Hospital. Time-gated Raman measurements of the oral exfoliated cells and SERS measurements of the saliva were then carried out. The team was able to develop a comprehensive Raman spectral database of healthy donor and mild, moderate and severe dysplasia samples. “Our classification model achieved excellent sensitivity and specificity,” notes Lyng. “This enabled us to identify dysplasia cases based on the spectral dataset obtained from the exfoliated cells and saliva.” The Marie Skłodowska-Curie fellow, Amuthachelvi Daniel, was able to carry out this work at both Technological University Dublin and VTT in Finland. “This enabled Daniel to work in a non-academic environment, which has been very beneficial for her career development,” says Lyng. “At the end of the secondment, Amutha was offered a permanent position as a senior application specialist at Timegate Instruments, a spin-off company of VTT.”
Effective, early diagnoses
The methods pioneered in the RAMAN-Dx project have the potential to be further developed into effective tests for oral cancer diagnosis. “The results we obtained have shown how Raman spectroscopy can be used on non-invasive samples, to discriminate between healthy patients and those with oral dysplasia,” adds Lyng. “Using exfoliated cells or saliva to screen and monitor for oral lesions also means that the need for invasive tissue biopsies could be greatly reduced. Such tests could also help to direct clinicians to the most appropriate biopsy site, in the case of extensive oral lesions.” For patients, the key benefit is the potential for earlier detection of precancerous lesions. The bottom line is that this could result in better treatment outcomes and ultimately better quality of life. The next step is for these pioneering methods to be turned into novel, cost-effective solutions that can be used to screen for oral cancer and suspicious oral lesions.
RAMAN-Dx was funded by Horizon 2020 and this article was originally published by Community Research and Development Information Service (CORDIS). CORDIS is the European Commission's primary source of results from the projects funded by the EU's framework programmes for research and innovation (FP1 to Horizon 2020).