Correspondence
Prof. Dr. Kevin Pagel, Freie Universität Berlin, Institute of Chemistry
and Biochemistry, Altensteinstraße 23A, 14195 Berlin, Germany, Email:
kevin.pagel@fu-berlin.de
This Research Highlight showcases the Research Paper entitled, Big
cohort metabolomic profiling of serum for oral squamous cell carcinoma
screening and diagnosis , https://doi.org/10.1002/ntls.20210071
Cancer is the plague of our time. It is the leading cause of death
worldwide, accounting for nearly one in six deaths.11ReferencesFerlay J, Ervik M, Lam F, Colombet M, Mery L, Piñeros M, Znaor A,
Soerjomataram I, Bray F (2020). Global Cancer Observatory: Cancer
Today. Lyon, France: International Agency for Research on Cancer.
Available from: https://gco.iarc.fr/today, accessed [30 April
2022] The mortality of cancer is reduced significantly when
diagnosed and treated early enough, ideally before or immediately after
the first symptoms occur. The current gold standard in cancer
diagnostics are biopsies from suspect tissue, which are examined using
histology. However, the excision of specimen is often a very unpleasant
and painful experience for the patient and potentially suffers from
sampling inaccuracy due to tissue inhomogeneity. An alternative strategy
are so-called liquid biopsies: the sampling of circulating or excreted
body fluids such as blood or saliva, which are subsequently screened for
specific DNA or protein-based tumor markers using immune recognition or
sequencing techniques. A limiting factor of this approach is that each
molecular probe is sensitive to only one particular feature, which may
not be sufficient to come to a reliable conclusion. Multiplexing the
detection of multiple DNA and protein-based features is generally
possible, but causes further problems such as cross-reactivity and
exploding costs.
Especially with the advent of easy-to-use chromatography and mass
spectrometry instrumentation, another class of molecules got in focus
for cancer detection: metabolites. As the name implies, metabolites are
small molecular substrates or products of metabolism – a diverse
potpourri ranging from amino acids, lipids, and sugars to hormones and
reaction intermediates. Each individual has a characteristic metabolic
profile that can be traced back in body fluids. This metabolic
fingerprint varies depending on the state and condition of the organism
and therefore provides a snapshot of the underlying cellular
processes22Johnson C, Ivanisevic J, Siuzdak G. Metabolomics:
beyond biomarkers and towards mechanisms. Nat Rev Mol Cell Biol2016; 31: 451–459. and their activity.33Rinschen
MM, Ivanisevic J, Giera M, Siuzdak G. Identification of bioactive
metabolites using activity metabolomics. Nat Rev Mol Cell Biol2019; 20: 353–367. Cancer cells generally grow much faster
than normal cells and consume vast amounts of nutrients. Not
surprisingly, this leads to drastic changes in their metabolic profile
– an effect that is often referred to as “metabolic
reprogramming”.44Hsu PP, Sabatini DM. Cancer Cell Metabolism:
Warburg and Beyond. Cell 2008; 135: 703–707. While
the details of metabolic reprogramming are still not fully understood,
it was shown for various examples that the resulting changes in the
metabolic profile can be successfully used for the mechanistic
elucidation55Jain M, Nilsson R, Sharma S, Madhusudhan N, Kitami
T, Souza AL, Kafri R, Kirschner MW, Clish CB, Mootha VK.Science 2012; 336: 1040-1044. and detection of cancer
and other diseases.66Nagana Gowda GA, Zhang S, Gu H, Asiago V,
Shanaiah N, Raftery D. Metabolomics-based methods for early disease
diagnostics, Expert Rev Mol Diagn 2008, 8: 617-633.,77Sinclair
E, Trivedi DK, Sarkar D, Walton-Doyle C, Milne J, Kunath T, Rijs AM,
de Bie RMA, Goodacre R, Silverdale M, Barran P. Metabolomics of sebum
reveals lipid dysregulation in Parkinson’s disease. Nat Commun2021; 12: 1592.
Due to its exceptional sensitivity, speed, and the ability to obtain
quantitative information, mass-spectrometry is a perfectly suited tool
to determine metabolic fingerprints comprising hundreds of different
components.88Alseekh S, Aharoni A, Brotman Y et al. Mass
spectrometry-based metabolomics: a guide for annotation,
quantification and best reporting practices. Nat Methods 2021;18: 747–756. However, the human metabolome database (HMDB)
currently contains more than 200,000 entries.99Wishart DS, Guo
AC, Oler E et al. HMDB 5.0: the Human Metabolome Database for 2022.Nucleic Acids Res 2022, 50: D622–D631. Reliably
monitoring only a fraction of these to identify diagnostic cancer
biomarkers represents a formidable challenge, not only for the MS-based
measurement itself but also for the underlying data analysis. In a
Research Article recently published in Natural Sciences1010Yang,
X, Song, X, Yang, X, et al. Big cohort metabolomic profiling of serum
for oral squamous cell carcinoma screening and diagnosis. Nat
Sci 2022; 2:e20210071. as well as a related study1111Song X,
Yang X, Narayanan R, Shankar V, Ethiraj S, Wang X, Duan N, Ni Y-H, Hu
Q, Zare RN Oral squamous cell carcinoma diagnosed from saliva
metabolic profiling. Proc Natl Acad Sci USA 2020; 117:16167-16173., Richard N. Zare, Qingang Hu and co-workers present an
elegant way to drastically simplify the measurement as well as the
analysis of metabolites for the detection of oral squamous cell
carcinoma (OSCC).
The special beauty of the presented approach lies in the combination of
multiple innovative techniques. First, instead of using off-line
capillaries or a chromatography-based infusion system, the authors use
the much simpler conductive polymer spray ionization. This technique
utilizes small triangles of a conductive polymeric substrate1212Song
X, Chen H, Zare RN. Conductive Polymer Spray Ionization Mass
Spectrometry for Biofluid Analysis. Anal Chem 2018;90: 12878–12885. containing a solvent reservoir to which a
few microliters of blood, serum or saliva are applied. Using a
non-porous polymer rather than the often-employed paper1313Wang H,
Liu J, Cooks R, Ouyang Z. Paper Spray for Direct Analysis of Complex
Mixtures Using Mass Spectrometry. Angew Chem Int Ed 2010;49: 877-880. prevents unintended binding of apolar compounds
such as lipids and significantly reduces the amount of background
signal. Application of a high voltage to the emitter generates molecular
ions by a mechanism similar to that of electrospray ionization
(ESI),1414Yamashita M, Fenn JB. Electrospray ion source. Another
variation on the free-jet theme. J Phys Chem. 1984;88: 4451–4459. which can subsequently be analyzed using the
vast portfolio of available mass spectrometry and tandem mass
spectrometry techniques. However, in contrast to ESI, virtually no
sample work-up and no time-consuming purification steps are required as the
sample is directly applied to the polymeric support. This prevents
sample loss, makes the approach exceptionally fast and, most importantly
for clinical applications, cheap. Zare, Hu and co-workers were able to
measure an impressive 819 serum samples in 12 hours, which highlights
the potential of conductive polymer spray ionization for high-throughput
clinical applications. Second, the authors used a machine learning
algorithm to identify diagnostic molecular markers that can be used to
distinguish cancer from non-cancer cases. Usually, mass-spectrometry
based metabolomics yields highly complex data, which are difficult to
disentangle without applying a human bias. The presented machine
learning approach circumvents this step and identifies markers purely
based on a mathematical algorithm. This not only impedes human error but
also helps to pinpoint markers and the correlations between markers that
would otherwise remain hidden. In total, 65 diagnostic metabolites, most
of them lipids, were found to be significantly up- or downregulated in
cancer cases. Monitoring these markers by mass spectrometry of serum can
be used to quickly distinguish OSCC from healthy metabolites and even
predict the stage of cancer, an aspect that is often crucial for the
correct choice of treatment. Finally, the authors elegantly validate
their findings by cross-correlating their measurements with analyses on
other body fluids such as saliva and molecular imaging of cancerous
tissue using desorption electrospray ionization. The imaging data nicely
illustrate the spatial distribution of the identified markers in excised
tumor tissue.
The present study is a perfect showcase for how mass spectrometry-based
metabolomics workflows can be simplified to make them usable in clinical
applications. Using body fluids in conjunction with conductive polymer
spray ionization drastically reduces the discomfort for patients and
significantly lowers the cost and time expenditure of the analysis.
Recently, a comparable approach has been successfully employed for the
metabolomics-based diagnosis of Parkinson’s disease from sebum
samples,1515Sarkar D, Sinclair E, Lim SH, et al. Paper Spray
Ionisation Ion Mobility Mass Spectrometry of Sebum Classifies
Biomarker Classes for the Diagnosis of Parkinson’s Disease.ChemRxiv. Cambridge: Cambridge Open Engage; 2021;
doi:10.26434/chemrxiv-2021-vsjwj-v2; This content is a preprint and
has not been peer-reviewed. which further highlights its universal
utility. Likewise, artificial intelligence has demonstrated its
exceptional potential in aiding the identification of diagnostic markers
in various other applications. The present paper therefore persuasively
demonstrates the current transformation of mass spectrometry from an
expensive research-only technique into a diagnostic tool that can be
used in hospitals.