Introduction
Oral cancer is one of the most common cancers in the head and neck region. There are around 377 713 new cases and 177 757 cases of death estimated worldwide in 2020 due to oral cancer.1 Oral squamous cell carcinoma (OSCC) contributes around 90 % of oral cancers. Tobacco use (smoked or chewed), alcohol consumption, and human papillomavirus infection are regarded as high-risk factors for OSCC development.2The diagnosis of OSCC includes a physical examination, radiography, computed tomography, magnetic resonance imaging, and histopathological examination of tissue biopsies.3, 4 However, changes in molecular distribution at the primary carcinoma site are difficult to track at early stages before the histological lesion can be detected.5 In addition, there are still many cases not diagnosed until the advanced stage when distant metastases have happened, thereby missing the best opportunity for treatment. If a necessary intervention before tumorigenesis could be conducted, the current 60% 5-year survival rate is expected to be majorly improved.4
Currently, tissue-based biopsy remains the gold standard in cancer diagnosis. It requires harvesting biospecimens by invasive procedures such as biopsies or needle aspirations. These procedures have common issues such as patient discomfort and sampling inaccuracy caused by tissue heterogeneity. By contrast, liquid biopsy has been increasingly considered as an alternative option for cancer detection because it can provide cancer-associated molecular information in a minimally invasive manner. Liquid biopsy is conducted by detecting tumor-associated markers in the circulating or excreted biological fluids such as saliva, urine, and serum. Currently, the detecting markers were primarily focused on exosome, circulating tumor cells (CTCs), and circulating cell-free tumor DNA (cfDNA) which are shed into the bloodstream by cancer cells undergoing apoptosis or necrosis. Several DNA and mRNA species were reported to be associated with OSCC progressions, such as Gal-1, Gal-3, Transgelin, miR-24, miR-181, miR-196a, miR-10b, miR-18, lincRNA-p21, GAS5, and HOTAIR.6-13
Gene- or protein-based clinical diagnosis mainly relies on the use of several immunoassays that introduce a hybrid probe or an antibody as a specific recognition element. This immune recognition-based multiplex detection is inevitably restricted by cross-reaction and spectral overlap in the readout. The analytical period and economic cost also increased with the introduction of more biorecognition probes.
In contrast to gene and protein molecular detection, metabolomics-basedin vitro diagnosis also has a considerable promise because it provides the metabolic phenotype information that can not only precisely characterize the oncometabolite distribution at different stages but also help to guide the necessary therapy.14 Therefore, a highly sensitive and specific metabolomics-based approach is in urgent demand for preclinical screening among the high-risk population.
In recent years, ambient ionization mass spectrometry has gradually gained interest in the field of clinical diagnosis owing to its advantages in free from laborious pretreatment, wide coverage of metabolite species, and high-throughput metabolome information monitoring among various biological samples. Combined with machine learning for high-dimension data interpretation, it can be performed with comparable accuracy at way less cost. 15-20
In previous work we have reported the practical value of conductive polymer spray ionization mass spectrometry combined with machine learning (CPSI-MS/ML) in the discrimination of OSCC with premalignant lesion (PML) and healthy contrast (HC).21 CPSI-MS/ML has shown its advantage in directly collecting hundreds of metabolites abundance information from a trace dried biofluid spot within a few seconds under atmospheric conditions,22 and in identifying key salivary metabolites and pathways involved in the progression from the PML to OSCC stage. The characteristic metabolites previously discovered in saliva were mainly narrowed to small molecules whose molecular weight is less than 500 Da.
Compared to saliva-based diagnosis, serum samples have advantages of a tightly controlled homeostatic environment and less external interference. Serum is a more clinically available biofluid that not only contains small metabolites but is also rich in lipid information. The minimally invasive nature of blood-based samples, the sensitive feature of metabolites, and evidence of changes in metabolites during OSCC initiation and progression, make blood-based metabolites attractive biomarker candidates.23, 24 Currently, dozens of metabolites have been reported to be dysregulated with OSCC malignant progression, including ketones, malonate, glutamine, propionate, valine, tyrosine, serine, methionine, and choline. 25-30
Given the hypothesis that the serum probably contains more OSCC-associated metabolic phenotype information, there were two concerns that needed to be investigated in this study: (1) whether the previously discovered salivary metabolites can still be significantly different among HC and OSCC in the serum to serve for preclinical screening; and (2) whether the significantly different metabolites in the serum can be not only used for discriminating OSCC from HC but also for discerning OSCC at different stages (T1, T2, T3, T4). Therefore, the aim of this study was to develop panels of serum metabolite markers for OSCC screening. The potential of serum metabolic profiling for staging was also preliminarily investigated. With the aid of the CPSI-MS/ML approach, we believe that a low-invasive serum diagnosis can be realized to provide a quick, accurate, cost-effective diagnosis of OSCC.Scheme 1 describes the general workflow that is followed.