4 DISCUSSION
BrMs
and gliomas, representing two distinct types of brain malignancies, are
mostly fatal tumors and are accompanied by poor prognosis. In addition,
clinical and biological variability is thought to exist within each type
and each grade of tumor, suggesting that the identification of molecular
factors that contribute to this variation is invaluable for the
development of targeted therapies.
To
reveal the common denominators of brain colonization by widely different
types of BrMs, we summed up three clusters with distinct protein
patterns by unsupervised clustering.
Proteins
related to tumor proliferation and immune response
were
recognized as commonalities for metastatic cells to colonize the brain.
Among
them, the L1 cell adhesion
molecule (L1CAM)
interaction
process was enriched by
Reactome
pathways in both cluster 1 and 2, but the enrichment was more
significant
in cluster 1 (Figure 3B).
L1CAM
is
a
member of the immunoglobulin-like cell-adhesion molecule family, which
has been reported to promote
motility
and invasion in many tumor
vasculatures,
including BrMs
[31,
32].
Additionally,
collagen
proteins (e.g., COL18A1, COL4A1, and COL6A1) in
extracellular matrix (ECM), which
have been recognized as diagnostic tumor markers, were also in cluster 1
( Figure S2C and D).
The
accumulation of collagens can establish tumorigenesis and metastasis
[33-35].
Moreover, the
VEGFA-VEGFR2
signaling pathway was present in all clusters,
especially
in cluster 2.
Vascular
endothelial growth factor (VEGF)-related pathways stimulate
angiogenesis
for tumor colonization, and they have been observed in many tumors,
including BrMs [15, 36,
37].
In cluster 3, a series of
eukaryotic
initiation factors (eIFs) that cooperate with ribosomes for mRNA
translation was identified (Figure 3D).
Because
mis-regulated mRNA expression is a common feature of tumor growth,
eIFs
are
aberrantly
expressed in many human cancers and serve as potential drug targets in
cancer therapy [38]. In addition, subunits of
chaperonin-containing tailless
complex polypeptide 1 (CCT or TRiC)
in
cluster 3 play a key role in mediating protein folding and
cytoskeleton
assembly, which may influence tumor division, migration, and
invasion
[39].
Among
gliomas, when comparing IV-Mut subgroups to II/III-Mut subgroups,
nesprin-1
(SYNE1, 4.18 times lower in IV-Mut vs. II/III-Mut) has previously been
identified as a frequently high-mutated gene in GBM patients and
associated with poor survival
[40-42].
Similarly, low glycine
decarboxylase (GLDC, 13.48 times lower in IV-Mut vs. II/III-Mut)
expression in IV-Mut increases the toxic production of
aminoacetone
and methylglyoxal, resulting in short survival [43,
44].
Another downregulated protein in IV-Mut, namely,
serum deprivation response
protein (SDPR or CAVIN2, 10.22 times lower in IV-Mut vs. II/III-Mut),
has
also
been reported to be correlated with poor survival in patients [45].
Conversely,
CD14
(4.25 times higher in IV-Mut vs. II/III-Mut) is widely expressed in
gliomas, as detected by immunohistochemistry, and the number of
CD14+ cells increases as
gliomas
progress [46,
47].
TFc
fragment of IgG binding protein (FCGBP, 68.19 times higher in IV-Mut vs.
II/III-Mut) has been demonstrated to participate in tumor immunity and
is expressed in different grades of gliomas, especially in high-grade
gliomas
[48].
Similarly, the expression of
mitogen-activated protein kinase
(MEK1 or
MAP2K1,
2.18 times higher in IV-Mut vs. II/III-Mut) is positively correlated
with the grade of glioma
as
MEK1
activates downstream RAS/MAPK signaling pathway for tumor proliferation
and invasion, thereby supporting the current use of MEK inhibitors for
glioma therapy [49,
50].
In addition, there were several significantly changed proteins (e.g.,
PPIF,
PRSS1, PTRHD1, and
PDLIM2;
Figure S3D)
that
have not been reported in glioma research but are regarded as drug
targets for other
diseases.
For instance, PDZ and LIM domain
protein 2 (PDLIM2) regulates transcriptional factors in multiple
cancers, such as B.C, L.C, and kidney cancer
[51]
and it has been explored as a therapeutic target for cancer
treatment.
Thus,
PDLIM2 may be used as a novel diagnostic marker to
differentiate
high-grade gliomas from low-grade
formations,
and it may even a drug target for gliomas. In addition, comparison of
the
DEPs
in
the low-grade versus high-grade group (IV-Mut vs. II/III-Mut) and
in the IDH1 mutant versus
wild-type
group (IV-Mut vs. IV-WT) resulted in
a
low overlap between the two cohorts
(cure
S3F). Therefore, these results suggested that the proteomics results are
reliable and applicable for discriminating different types of gliomas.
The present study utilized BrMs and gliomas to comprehensively analyze
primary and secondary brain tumors. Proteomic analysis revealed
distinct
pathway-level differences between
the two types of brain malignancies,
in
which BrMs focused on tumor development and gliomas progressed to
invasiveness.
Notably,
microenvironment analysis has shown that BrM samples have a
more
pronounced accumulation of
lymphocytes
and neutrophils compared to gliomas, whereas gliomas
are
dominated by microglia [17]. Furthermore, the proteomic differences
of BrM (L.C) and glioma (IV) were utilized for precise disease
classification. By attempting machine learning, five proteins (KRT8,
KRT19, KRT7, TACSTD2, and CDH1) were furtherly selected to classify
these two tumors with an accuracy of 90%. In particular, three of these
proteins, namely, KRT8, KRT19, and KRT7, belong to the keratin family.
Keratins, including KRT7, KRT8, and KRT19,
are
extensively
used acs diagnostic tumor
markers
as
malignancies
largely maintain the specific keratin patterns associated with their
respective
cells of origin [52].
Tumor-associated calcium signal
transducer 2
(TACSTD2
or TROP2) is a
transmembrane
glycoprotein that is highly expressed in various cancer types
[53].
In the present study, TACSTD2 was overexpressed in BrM (L.C) compared to
glioma
(IV),
suggesting
that it may be a candidate marker
to
differentiate the two cancer types. Another transmembrane glycoprotein,
cadherin 1 (CDH1 or
E-cadherin),
has also been demonstrated to be upregulated in secondary metastases
[54]. In summary, these five biomarkers have been
validated
to be dysregulated in other cancers, and the present study revealed
their potential capacity for distinguishing glioma (IV) and BrM
(L.C).
Here,
we
built
a comprehensive
and
comparative proteomic analysis for both BrMs and gliomas for the first
time,
which
uncover the different proteome patterns of these two typical malignant
tumors in the brain, indicating potential application in cancer-specific
therapy.
Further
efforts can focus on biomarker validation with more clinical samples.