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.