Bioinformatics analysis of differentially expressed proteins in prostate cancer based on proteomics data

Abstract

We mined the literature for proteomics data to examine the occurrence and metastasis of prostate cancer (PCa) through a bioinformatics analysis. We divided the differentially expressed proteins (DEPs) into two groups: the group consisting of PCa and benign tissues (P&b) and the group presenting both high and low PCa metastatic tendencies (H&L). In the P&b group, we found 320 DEPs, 20 of which were reported more than three times, and DES was the most commonly reported. Among these DEPs, the expression levels of FGG, GSN, SERPINC1, TPM1, and TUBB4B have not yet been correlated with PCa. In the H&L group, we identified 353 DEPs, 13 of which were reported more than three times. Among these DEPs, MDH2 and MYH9 have not yet been correlated with PCa metastasis. We further confirmed that DES was differentially expressed between 30 cancer and 30 benign tissues. In addition, DEPs associated with protein transport, regulation of actin cytoskeleton, and the extracellular matrix (ECM)–receptor interaction pathway were prevalent in the H&L group and have not yet been studied in detail in this context. Proteins related to homeostasis, the wound-healing response, focal adhesions, and the complement and coagulation pathways were overrepresented in both groups. Our findings suggest that the repeatedly reported DEPs in the two groups may function as potential biomarkers for detecting PCa and predicting its aggressiveness. Furthermore, the implicated biological processes and signaling pathways may help elucidate the molecular mechanisms of PCa carcinogenesis and metastasis and provide new targets for clinical treatment.

Identification of Novel Prognosis and Prediction Markers in Advanced Prostate Cancer Tissues Based on Quantitative Proteomics

“…Another group of proteins decreased in the PCa tissues was related to blood microparticles, which influence the complement and coagulation cascades and platelet degranulation. These bioinformatic results are very similar to previous proteomics studies conducted in PCa (31)(32)(33). In fact, these three protein groups, including the mitochondrial proteins, extracellularrelated proteins, and blood microparticle proteins, are known to be highly related to the occurrence of cancer.…”

Distinct roles for the RNA-binding protein Staufen1 in prostate cancer

“…org) also identifies Staufen1 as a prognostic factor in human prostate cancer where survival rates decrease in patients with high Staufen1 expression (N = 99) compared to those with low Staufen1 expression (N = 395) (Protein Atlas; Stau1). 1 These findings are in agreement with the cell line data presented above and indicate that Staufen1 is also increased in human PC tumours.…”

“…Prostate cancer (PC) is one of the most common malignant cancers with the second highest rate of mortality in men worldwide [1][2][3][4]. Despite improved scientific knowledge surrounding the underlying molecular mechanisms and risk factors associated with PC, prognosis remains poor for advanced PC [5].…”

Glycopatterns and Glycoproteins Changes in MCN and SCN: A Prospective Cohort Study

“…In the cystic fluid of PCLs, Fibrinogen Alpha chain (FGA), fibrinogen beta chain (FGB), and fibrinogen gamma chain (FGG) were markedly elevated in MCN. They have been reported to elevate in prostate cancer, lung cancer, hepatocellular carcinoma, pancreatic cancer, infectious diseases, and myocardial infarction [37, 38]. Ghezzi reported that plasma fibrinogen level might be a potential index to predict prognosis, improving the early diagnosis of endometrial cancer and optimize the treatment schedule [39].…”