PCa has a higher and higher incidence among all tumors in men, especially those over 70. BPH is another common encountered disease and affects nearly seventy percent of men older than 70[22]. Therefore, both PCa and BPH are threats to the health of older men. In recent decades, because of changes in the global population structure and aging, elderly males have increased in number[23, 24]. Thus, the incidence of PCa and BPH will become more common. Understanding the relationship between PCa and BPH may help better predict the occurrence of PCa and may relieve pressure on the medical system. Although PCa primarily arises in the epithelial cells in the peripheral zone, and BPH arises in the transition zone, PCa and BPH have important factors in common, such as growth depend on hormone and responsiveness to antiandrogen therapy[25]. Moreover, inflammation could be an underlying cause of both BPH and PCa. In a study of 180 men with suspected PCa who were biopsied at baseline and after 5 years of follow-up, the 5-year PCa incidence was 20% for men with biopsy specimens showing inflammation at baseline compared with 6% for men with no evidence of inflammation in baseline biopsies[26]. The Reduction by Dutasteride of Prostate Cancer Events (REDUCE) trial found that patients with BPH all have chronic inflammatory infiltration[27]. These studies all provide evidence of a relationship between BPH and PCa. Sommers first reported the coexistence of BPH and PCa in 1957[2]. They found that BPH was identified in 80% of cadavers with PCa, and 45% without PCa, respectively. In 1974, Armenian et al. found that patients with BPH had a 4 to 5 times increased risk of PCa. A study by Chokkalingam et al. investigated about 87,000 men, and found that patients with BPH had a 1.2 to 1.7 folds increased risk of PCa incidence and mortality[20]. The largest study was carried out on the Danish male population (about 3,000,000 men) from 1980 to 2007; this study indicated that patients with BPH had a 2 to 3 times increased risk of PCa and a 2 to 8 folds risk of cancer-related mortality[6].
Over recent decades, bioinformatics on microarray data have focused broadly on the PCa occurrence depend on bioinformatic analysis and have revealed some of the mechanisms that may lead to PCa. However, until now, there has been no research concentrated on the molecular mechanisms underlying the development from BPH to PCa. We first adopted an integrated bioinformatics approach to directly compare the differences in gene expression between BPH and PCa. Three datasets, GSE5377, GSE104749, and GSE30994, were analyzed and normalized by R language. A total of 60 DEGs were found, 15 that were up-regulated and 45 that were down-regulated. Then, GO and KEGG pathways were utilized to show how the DEGs’ expression affected the biological pathways underlying the conversion of BPH to PCa. DEGs were mainly enriched in pathways related to the regulation of tight junctions, leukocyte transendothelial migration, and vascular smooth muscle contraction. Previous studies have proven that tight junctions can affect the metastasis of PCa cell lines DU145 and PC-3[28]. Leukocyte transendothelial migration can impact the migration of PCa cells[29]. Vascular smooth muscle contraction can also affect PCa development[30].
Hub genes, MYC, CXCR4, CSRP1, SNAI2, MYL9, ACTG2, and MYH11, were found by analyzing the PPIs of the DEGs. This result indicates that mutations in these genes may play significant roles in the development of PCa from BPH. MYC (MYC proto-oncogene) affects PCa progression due to a high-fat diet and plays a positive role in regulating the androgen receptor and androgen-receptor splice variants in PCa[31, 32]. In addition to PCa, MYC is also correlated with the occurrence of multiple tumors. Furthermore, MYC activation can promote bladder cancer proliferation and invasion[33]. The higher expression of MYC was found in colorectal cancer patients, and it may promote tumorigenesis in colorectal cancer through regulation of the Wnt-and Ras-dependent signal transduction pathway[34, 35]. MYC regulated by BRD4 can promote gastric cancer progression[36]. CXCR4 (C-X-C motif chemokine receptor 4) may promote PCa metastasis through regulation of phosphatidylinositol 4-kinase IIIα (PI4KIIIα) and SAC1 phosphatase[37]. In addition, CXCL12/CXCR4 can increase the malignancy of breast cancer and cervical cancer[38, 39]. SNAI2 (snail family transcriptional repressor 2) can regulate prostate tumor progress, angiogenesis, and metastasis potentially by modulating the GSK-3β/β-catenin signaling pathway[30]. Moreover, research has shown that SNAI2 can promote the invasion and migration of clear cell renal cell carcinoma. Du et al. found that transactivation of SNAI2 and c-MET could promote colorectal cancer metastasis[40]. SNAI2 also participates in regulation of the initiation and metastasis of breast cancer cells[41]. MYL9 (myosin light chain 9) can predict malignant progression and poor biochemical recurrence-free survival of PCa[42]. MYL9 is also associated with the recurrence of colorectal cancer[43]. ACTG2 (actin gamma 2, smooth muscle) and MYH11 (myosin heavy chain 11) have an affection in the development of PCa[44, 45]. ACTG2 can also affect hepatocellular carcinoma cell migration and tumor metastasis, and MYH11 may play a pivotal function in the progression of lung cancer and bladder cancer[46, 47].
When analyzing hub gene expression, 2 up-regulated hub genes, MYC and CXCR4, were not expressed differently between normal prostate samples and PCa samples in the GEPIA database. These results may due to that the normal sequence from GEPIA includes data from both TCGA and GTEx database. Therefore, an additional analysis was conducted; we analyzed hub genes’ expression in tumor and normal samples in UALCAN which include the sequence data only from TCGA database. We found that CXCR4 was not expressed differently in normal and PCa samples in UALCAN. We analyzed the value of hub genes in diagnosing PCa and tumor staging. According to the results, we found that all the hub genes, except CXCR4, could be used as diagnostic markers for PCa progression. In addition, some hub gene can also change when PCa progress. That means these hub genes can be indicators to predict disease progression. In addition, the hub genes were expressed differently in BPH and PCa samples, indicating these genes are potential predictors of PCa development from BPH. Some studies have reported that patients who develop PCa from BPH would have higher cancer-related mortalities. Therefore, at the same time, we also carried out a survival analysis to determine whether the expression of these hub genes affect patients’ survival times. We found that the hub genes do not impact overall survival time, but they can affect progression-free survival time.
In addition, we constructed regression model to value the mutation risk of hub genes in leading to PCa. In the model, we found that all the hub genes may be risk factors in causing PCa except CXCR4. In nomogram, we found that the mutation of CSRP1 is the highest risk factor in leading to PCa among all 7 hub genes. Furthermore, the hub genes function in tumor progression also be analyzed. Some hub genes such as CSRP1, MYL9 and SNAI2 will change when PCa progressed. These results reflect that the expression level change of these hub genes can be potential signal of disease progression.
Finally, we utilized our clinical specimens and C4-2 PCa cells to validate the hub genes’ functions in promoting PCa development. We chose MYC, MYL9 and SNAI2. The same results were found in this experiment. The expression of MYC, MYL9 and SNAI2 were obviously changed at the mRNA and protein levels. IHC analysis verified this result. Experiments from C4-2 prostate cancer cell reflects that the 3 hub genes can also affect cell invasion and proliferation ability.
However, our study had some limitations. First, although we included 3 datasets in the study, the number of samples was still small; there were only 10 BPH samples and 24 PCa samples. A too-small sample size may have led to a less representative study. Second, although we validated the hub genes’ expression with TCGA database and experiments, our results may be biased. Thus, our results require further validation. However, our study is the first one to address genes differentially expressed in BPH and PCa by bioinformatic analysis.