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.