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Circulatory system proteins play a central role in human physiology; therefore, profiling plasma proteins has been explored widely as a robust and dynamic tool in studying diseases. Here, we investigated the proteomic profile of plasma in 1,118 pan-cancer patients. The integrative analysis uncovered diverse molecular characteristics of different cancer types and bridged the plausible connection with the clinical features, including tumor stages. The findings demonstrate that the balance between lipid and glucose metabolisms is important in regulating immune infiltration. The pre- and post-surgery comparison of the plasma proteome indicated that tumor-induced angiogenesis is overexpressed in the tumor, and the differences between the proteome patterns could monitor post-surgery therapeutic effects. Finally, we developed a panel of tumor-type-specific proteins to classify tumor types with >95% sensitivity/specificity. Collectively, this study portrayed the plasma proteome landscape of human cancers and screened reliable biomarkers that could assist in diagnostic and drug discovery efforts.

Glioblastoma (GBM) is the most malignant of all known intracranial tumors, meanwhile most patients have a poor prognosis. In order to improve the poor prognosis of GBM patients as much as possible, it is specifically significant to identify biomarkers related to the gene diagnosis and gene therapy. Herein, a total of 343 GBM specimens and 259 non-tumor specimens were collected from four Gene Expression Omnibus (GEO) datasets and TCGA database, and then analyzed the differentially expressed genes (DEGs) from the above data. Through Venn diagram analysis, 54 common upregulated DEGs and 22 common downregulated DEGs were triumphantly recognized. On account of the degree of formation communication in Protein-protein interaction network (PPIN), the 10 upregulated central genes had been ranked, incorporating LOX, IGFBP3, CD44, TIMP1, FN1, VEGFA, POSTN, COL1A1, COL1A2 and COL3A1. By combining the expression levels and the clinical features of GBM, four hub genes (TIMP1, FN1, POSTN and LOX) were significantly up-regulated and related to poor prognosis. Meanwhile, univariate and multivariate Cox regression analysis results suggested that TIMP1 could be one of the independent prognostic factors for GBM patients. Subsequently, TIMP1 was particularly correlated with the immune marker of macrophage M1, macrophage M2, Neutrophils, tumor associated macrophage and Tregs. In conclusion, these findings investigated that TIMP1 might be a new biomarker to determine prognosis and immune infiltration of GBM patients.