As the second most prevalent malignancy in men worldwide, prostate cancer (PC) ranks as the fifth leading cause of male cancer deaths. According to the reports of the International Agency for Research on Cancer (IARC), there were estimated to be 1.276 million new cases of PC and approximately 359,000 deaths from PC worldwide in 2018. The age-standardized incidence rate by world standard population (ASIRW) and age-standardized mortality rate by world standard population (ASMRW) were 29.3 per 100,000 and 7.6 per 100,000, respectively (Bray et al., 2018). Treatment options for early-stage PC can be divided into non-radical treatments such as watchful waiting and hormone therapy and radical treatments such as radical prostatectomy, radiation therapy, and cryotherapy. The current first-line treatment option for patients with advanced metastatic PC still remains endocrine therapy, but after a median duration of 18–24 months of endocrine therapy, almost all patients will progress to castration-resistant PC (CRPC). Once patients enter this stage, the prognosis is poor. Due to the heterogeneous nature of PC, it remains difficult for urologists to develop individualized clinical treatment plans for their patients (Knight, 2014). Although drugs such as docetaxel, abiraterone, and apatamide have been developed for the treatment of CRPC, which can extend life expectancy to some extent, the low survival rate of mCRPC suggests it remains urgent for us to carry out further research into the mechanisms related to the development of PC, especially CRPC, and to develop novel targeted therapies.

Phagocytosis regulatory factors, as with common cytokines, are expressed in almost all cancers and promote six characteristics of cancer cells, thus promoting the occurrence of tumors. The tumor microenvironment provides the necessary immunosuppressive and hypermetabolic environment for tumor growth and progression. Tumor-associated macrophages (TAMs) play an important role in inhibiting tumor immunity, while PRFs play an important role in regulating the activity of induced tumor immune cells such as macrophages and T cells. Current studies have shown, in many cancers (liver, gastric, esophageal, colon, and bladder), that immune-infiltrating cells in a tumor microenvironment can promote tumor growth by promoting angiogenesis, cause DNA damage, and alter the microenvironment thus evading immune responses. Inflammatory cells can not only directly promote tumorigenesis, growth, and metastasis by remodeling the extracellular matrix (ECM) and mediating epithelial–mesenchymal trans differentiation (EMT) but also release cytokines further causing the promotion of tumor growth (Khan et al., 2016). Macrophages are innate immune cells and represent the main cell type of tumor-infiltrating immune cells. TAMs are a source of several inflammatory cytokines, and these cells can be divided into two types: tumor-suppressive M1 and tumorigenic M2 (Lanciotti et al., 2014). Current studies have focused on M2 cells, which contribute to tissue repair and vascular regeneration. Phagocytosis plays a critical role in the neutralization and termination of pathogens (Lim et al., 2017) but can also contribute to a diverse range of developmental, homeostatic, and non-infectious disease processes, including apoptotic cell clearance, senescent erythrocyte turnover, tumor surveillance, elimination of cellular debris after injury, and synaptic pruning (Arandjelovic and Ravichandran, 2015; Gordon, 2016; Hong et al., 2016; Chen et al., 2017). Dysregulation of phagocytosis by professional or non-professional phagocytes (Chung et al., 2013; Juncadella et al., 2013) can lead to autoimmunity, developmental deficits, and buildup of toxic protein aggregates (Gordon, 2016; Hong et al., 2016). Much of our current understanding of the molecular basis of phagocytosis is derived from forward genetic screens in model organisms. Numerous PRFs in cultured Drosophila S2 cells have been identified by RNAi screens (Kocks et al., 2005; Philips et al., 2005), although a systematic screen for PRFs in mammalian cells has not been reported.

Monoclonal antibody therapies targeting tumor antigens have been described as “magic bullets” for cancer therapy, which drive cancer cell elimination in part by triggering a macrophage-derived phagocytosis of cancer cells (Scott et al., 2012; Maleki et al., 2013; Sliwkowski and Mellman, 2013; Weiskopf and Weissman, 2015; Tsao et al., 2019). However, a low phagocytic activity of macrophages in the tumor microenvironment and the expression of anti-phagocytic factors by cancer cells, remain key obstacles before the promise of a monoclonal antibody therapy for diverse cancers can be realized (Ruffell and Coussens, 2015; Cunha et al., 2018; Su et al., 2018; Pathria et al., 2019). Furthermore, the mechanisms by which cancer cells evade phagocytosis are not fully understood. In a study published in Nature, researchers used intercellular CRISPR screening to identify PRFs in cancer cells, and using genome-wide reverse screening in macrophages, they found that the G-protein-coupled receptor GPR84 mediates enhanced phagocytosis in APMAP-deficient cancer cells. This work revealed an intrinsic cancer regulator that was sensitive to antibody-driven phagocytosis, expanding our understanding of the mechanisms by which cancers are resistant to the phagocytosis of macrophages (Roarke et al., 2021).

In PC, numerous controlled clinical trials and meta-analyses have confirmed that inflammatory cells and related factors can promote the growth of PC cells (Mishina et al., 1985). Lanciotti et al. (2014) found that in pathological sections from PC patients treated with androgen deprivation therapy (ADT), the group with lower TAM counts (<22) had a significantly better prognosis than the group with higher counts (>22) (Nonomura et al., 2011), suggesting that TAMs may be a good predictive marker for PC. In addition, if the replenishment of macrophages in the prostate is blocked, the incidence of PC can be reduced to some extent and the development of mCRPC can be delayed, suggesting that the use of NSAIDs can reduce the risk of PC (Mantovani et al., 2006). However, the specific role of other subtypes of macrophages and associated PRFs are yet to be resolved, except for M2, which requires further study. As with macrophages, cytokines such as PRFs may play an important role in the occurrence and development of tumors. However, thus far, the mechanistic role of PRFs in PC has not been reported. Therefore, further studies on the relevance of immune-infiltrating inflammatory cells, especially macrophages and related PRFs, and the tumor microenvironment are of obvious importance for the further treatment of PC.

In this study, we aimed to comprehensively characterize PRFs in PRAD, and to screen and determine key PRFs, and construct tumor prognostic and therapeutic signatures based on the relevant genes. First, we systematically described the expression of PRFs in prostate PRAD, and evaluated their expression patterns and their relationship with patient outcome. We then analyzed potential prognostic PRFs by using the Cox and Lasso analysis and constructed a phagocytic factor-mediated risk core. We then divided the samples into two groups with significant differences in OS prognosis based on the risk core. Finally, a correlation analysis was conducted between the risk score and clinical features, immune infiltration molecules, immune characteristics, immune checkpoint expression, IC50 of several classical sensitive drugs, and immunotherapy efficacy. Meanwhile, the Human Protein Atlas (HPA) database was used to determine the protein expression of 18 PRF characteristic genes. Through our study, we aimed to clarify the role of PRFs in the development of PRAD, especially in castration resistance, and to explore the role of PRFs in the tumor microenvironment of PRAD, and to discuss their value in treatment and prognosis prediction (Figure 1).

Currently, the consensus suggests that the incidence of PC is mainly related to the inactivation of tumor suppressor genes and the activation of oncogenes caused by persistent genetic and epigenetic variation. However, pathogen infection, physical and chemical factors, diet and many other factors related to exposure are also closely related to the incidence of PC (Johny et al., 2007; Kotb et al., 2015). Gollapudi et al. (2013) analyzed TAM density in benign prostatic hyperplasia, prostate intraepithelial neoplasia, and PC tissues, and found that their levels in PC were significantly higher than that in benign prostatic hyperplasia and prostate intraepithelial neoplasia. Moreover, the TAM density in Gleason Stage 4 patients was significantly higher than that in Gleason Stage 3 patients. In addition, Hu et al. (2015) found that the concentration of TAMs in PC tissues with distant metastasis was significantly higher than in those of patients with no distant metastasis. Gannon et al. (2009) found that the CD68 ⁺ macrophage number was significantly increased after ADT treatment using an optimized computer-aided statistical analysis. Therefore, the aforementioned study indicated that the increased density of TAMs in the prostate tissue may be involved in the development of PC and is closely related to castration resistance. Tumor-associated inflammation is one of the key features of cancer and phagocytic factors, chemokines and lymphokines are involved in the mediation and regulation of inflammation (Dvorak, 2015; Yasmin et al., 2015). There exists complex relationships among various cytokines as well as between their membrane receptors and soluble receptors, such as mutual coordination, inhibition, and antagonism, forming a cytokine regulatory network. The malignant tumor cytokine network is complex and plays an important role in various factors associated with tumor biology (Madalyn et al., 2017) and TAMs are a source of various cytokines. Like macrophages, cytokines such as PRFs may play an important role in the occurrence and development of tumors. However, to date, the mechanism action of PRFs in prostate cancer has not been reported. We are the first to demonstrate an enrichment of PRFs in PRAD and their correlation with the expression of PRFs. These results demonstrated that the genes with the highest correlation were significantly positively correlated with enrichment scores, implying that PRFs played an important role in PRAD. Furthermore, we went on to compare the differences in expressions between tumor samples and normal samples in PRAD and found that some phagocytic factors had higher expression levels in tumor samples when compared to normal samples. As a PRF, TIMMDC1 (also termed C3 or f1) was found to be significantly increased in metastatic lung cancer when compared to non-metastatic lung cancer (Wu et al., 2014). Liu et al. (2018) found that TIMMDC1 could regulate the Akt/GSK-3β/β-catenin signaling pathway in gastric adenocarcinoma SGC-7901 and BCC-823 cells, and downregulate the expression of TIMMDC1, thus reducing the mitochondrial energy metabolism and glycolysis of gastric cancer cells as well as inhibiting the proliferation, migration, and invasion of these cells (Liu, 2018). As a member of the ATPR (4-amino-2-trifluoromethylphenyl Retina) family of proteins, RPL21 is involved in the metabolism, as well as the PI3K-Akt and TGF-β signaling pathways and other cancer-related signaling pathways. It strongly inhibits proliferation and can induce the differentiation of tumor cells (Feng et al., 2019; Li et al., 2020). Consistent with previous studies, our results demonstrated that PRFs in PC were mainly enriched to several biological processes such as phagocytosis-related and energy metabolism, such as cellular phagocytosis and ATP synthesis, as well as pathways including oxidative phosphorylation, which are all related to the development of tumorigenesis in PRAD.

Cancer is known to have six characteristics: the ability to self-induce proliferation; insensitive to anti-proliferative signaling molecules; anti-apoptosis; unlimited proliferation potential; the ability to promote angiogenesis; and the ability to infiltrate and metastasize surrounding tissues. PRFs, as common cytokines, are expressed in almost all cancers and promote all six characteristics of cancer cells, thus promoting tumorigenesis. The tumor microenvironment provides the necessary immunosuppressive and hypermetabolic environment for tumor growth and progression, and TAMs play an important role in the inhibition of tumor immunity, while PRFs play important roles in the regulation of tumor immune cell induction, especially macrophages and T cells. In a study from Nature, researchers used intercellular CRISPR screening to identify PRFs (TIMMDC1, PDCD10, RPL21, GTPBP3, KIF23, PIK3R5, FOXO1, NFIA, ARPC2, HMGB2, NDUFV1, FADD, PACS2, HMHA1, CMC1, ANAPC7, and MIB2) in cancer cells. This work revealed an intrinsic cancer regulator that was sensitive to antibody-driven phagocytosis, expanding our understanding of the mechanisms by which cancer was resistant to phagocytosis by macrophages (Roarke et al., 2021). The programmed cell death molecule 10 (PDCD10), another PRF, is highly evolutionarily conserved and encodes for a gene that plays a role in the regulation of angiogenesis, proliferation, apoptosis, and migration of tumor cells (Lambertz et al., 2015). Over-expression of PDCD10 can increase proliferation and inhibit apoptosis of NSCLC A549 cells (Yang et al., 2018). Some studies have also found that PDCD10 expression was significantly increased in PC, and downregulation of PDCD10 expression could inhibit the proliferation and migration of these cells (Fu et al., 2016). The PRF GTPBP4 is a member of the GTPBP family, and its coding gene sequence is of highly conserved genes and widely distributed in various eukaryotes from yeast to humans (Young-Il et al., 2014). Recent studies have reported that the observed decrease in the expression of GTPBP4 could inhibit the proliferation of human colon cancer cells, while its increased expression was related to a decreased survival rate in colon and breast cancer patients (Andrea et al., 2010; Yu et al., 2016). The PRF FOXO1 (fork head frame transcription factor O1), also known as FKHR, plays an important role in cell proliferation and cancer biology (Kim et al., 2018) and its aberrant expression is associated with the occurrence of a variety of tumors (Shi et al., 2018); over-expression is associated with rhabdomyosarcoma (Ryder et al., 2017), breast cancer (Yu et al., 2019), and ovarian cancer (Han et al., 2019), and low expression is associated with colon cancer (Chae et al., 2019) and prostate cancer (Zhang et al., 2011). Studies have shown that the phagocytic regulatory factor NFIA was one of the key genes involved in the regulation of osteoclast formation and osteoclast activity, and the formation of bone metastasis of various tumors (Li et al., 2012). Actin-related protein complex2 (ARPC2) is one of the subunits associated with an actin-related protein2/3 (arp2/3) complex involved in the regulation of cytoskeletal motility and composition and participates in the regulation of cell growth, invasion, and other processes. ARPC2 expression is up-regulated in breast cancer, gastric cancer, and other tumor tissues, and the down-regulation of ARPC2 inhibits the invasion and migration of tumor cells, suggesting that it may be an oncogene (Zhang et al., 2017). In our study, the samples were divided into two groups (high- and low-risk score groups) according to the median expression of PRFs, and the results from the survival analysis showed that 27 genes were significantly associated with OS in PRAD. Furthermore, the survival analysis from the six most relevant phagocytic factors in PRAD were conducted and the results showed that six phagocytic factors were closely related to progression free survival (PFS) in PRAD patients, and PFS in the low-risk score group was significantly greater than that in the high-risk score group. Significant differences in prognoses were found between the high- and low-risk score groups based on the survival analysis, with the high-risk score group having a significantly worsening prognosis. Therefore, our results showed that there was a significant correlation between the risk score and clinical characteristics of PRAD such as age, recurrence, TNM stage, lymph node metastasis, PSA levels, and Gleason score. Moreover, the results from multivariate analyses demonstrated that the risk score was an independent risk factor correlated with the overall survival for PRAD in both the training datasets. Peng et al. (2014) reported a model based on the expression signature of VGLL3, IGFBP3 and F3. They found that compared with the prediction model that used only the clinical parameters, the addition of the tumor subtype classification could improve specificity of the overall survival of 5-year prediction. The area under the receiver operating characteristic curve value was increased from 0.755 to 0.815 in overall survival prediction, from 0.726 to 0.793 in PC-specific survival prediction, and from 0.730 to 0.793 in non-PC-specific survival prediction, respectively. Jhun et al. built a gene expression signature incorporated 49 genes including BUB1, CENPE, CENPF, DLGAP5, PRC1, and SMC4, which alone had an AUC of 0.68 and 0.76 for predicting recurrence and ML progression, respectively. Adding the signature to a logistic regression model that included clinicopathological factors could significantly improve the goodness of the fit of the model for recurrence and ML progression. The AUC increased by 3% and 6% for recurrence and ML progression, respectively (Jhun et al., 2017). In our study, the high risk score group having a significantly inferior prognosis and ROC curves were used to assess the AUC values for OS predictive efficacy of the risk scores’ model (0.79 at 1 year, 0.82 at 3 years, and 0.81 at 5 years, respectively.). However, in the validation cohort, the AUC values for OS predictive efficacy of the risk scores’ model was 0.7 at 1 year, 0.57 at 3 years, and 0.63 at 5 years, respectively. The ROC values about the PRF signature in the validation cohort set are not high enough. However, it is the first gene signature about PFs in PC, which can provide a new gene signature for predicting a prognosis of patients with PC. In the future, we could further explore how much predictive values the risk score would add to the model in addition to the clinical variables, such as comparing AUCs between the risk score and risk score + clinical variables.

Recent studies have shown that the occurrence and development of tumors are not only related to its genomic changes, but also affected by changes in TAM recruitment and polarization at the tumor immune microenvironment (Quail and Joyce, 2013; Hirsch et al., 2017; Wu and Dai, 2017; Alanazi et al., 2018). Therefore, understanding the tumor immune microenvironment may provide a new direction for the development of tumor therapy. TAMs with high density invasion in a variety of gynecological tumors, lung cancer, esophageal cancer, and other tumors are closely related to a poor prognosis (Krishnan et al., 2018; Li et al., 2018; Yagi et al., 2019). Therefore, TAMs may be a potential target for tumor therapy, and TAM-related therapeutic drugs have become an important area of research in recent years. TAMs are mostly derived from circulating monocytes, and recruitment of monocytes and macrophages is affected by signaling molecules secreted by tumor cells (Sica et al., 2008). Within the tumor microenvironment, vascular endothelial growth factor (VEGF), uPA, and other factors secreted by macrophages can promote tumor metastasis and new angiogenesis (Deng et al., 2018). Liu et al. (2018) demonstrated that apatinib, a small molecule inhibitor of vegFR-2, could significantly reduce the secretion of hepatocyte growth factor (HGF) from M2-type macrophages, thereby inhibiting Met phosphorylation in A549 and H1975 cells induced by M2-type macrophages. TAM-induced epithelial–mesenchymal transition (EMT) is attenuated by the hGF-MET signaling pathway. Conventional treatments for prostate cancer include radical prostatectomy, radiotherapy, chemotherapy, and endocrine therapy. Immunotherapy for prostate cancer is an emerging therapy, in which programmed cell death-1 (PD-1)/programmed cell death-ligand1 (PD-L1) inhibitors can improve the body’s anti-tumor immunity by activating its own immune system to cause tumor cell death, thus providing a new direction for immunotherapy in prostate cancer (Modena et al., 2016). Another immune checkpoint CTLA-4 inhibitor, ipilimumab has achieved good clinical efficacy in CRPC patients, with a PSA reduction of more than 50% in eight out of 50 patients (Slovin et al., 2013). Blocking the PD-1/PD-L1 immune checkpoint while blocking the CTLA-4 immune checkpoint may represent a novel, potential immunotherapy for prostate cancer. In our study, to further explore the relationship between the risk score and immune microenvironment, differences in different categories of immune infiltration between high- and low-risk score groups were assessed and results showed that there were significant differences in most categories of immune infiltration. Of note, it is interesting that there were significant differences between the high- and low-risk score groups about the macrophages M1 and M2 but with the opposite trend. The reason for this may be related to the different amounts of phagocytic factors released by the different types of macrophages, or the interference of phagocytic factors released by other cells. To further characterize the correlation between risk score and immunity, differential expression analysis of immune checkpoints and pro-inflammatory factors between high- and low-risk score groups was performed and the results showed that the expressions of the immune checkpoint genes PD-L1, PD-1, and CTLA-4 were significantly higher in the high-risk score group than in the low-risk score group, while there was no significant difference in the expression of pro-inflammatory factors such as IL-6 and IL-8. The aforementioned results suggested that immune checkpoint inhibitors or immune checkpoint inhibitors combined with endocrine therapy may achieve better results for patients with prostate cancer and a high-risk score, while for CRPC patients, CTLA-4 inhibitors or CTLA-4 inhibitors combined with endocrine therapy may prolong the survival of patients with a high-risk score.

Due to the heterogeneous nature of PC, it remains difficult for urologists to develop individualized clinical treatment plans for their patients (Knight, 2014). Although drugs such as docetaxel, abiraterone, and apatamide have been developed for the treatment of CRPC, which can extend life expectancy to some extent, the low survival rate of mCRPC suggests that it remains urgent for us to carry out further research into the correlation between the PRFs and classic drugs for PC. A lower IC50 always indicates better drug efficacy. In our study, we evaluated the relationship between PRF riskScore and Cisplatin, Paclitaxel, Methotrexate, Gemcitabine, Doxorubicin,Docetaxel, Gefitinib, and Repamicin in PRAD, and the results showed lower IC50 values for these drugs in the high-risk group, suggesting a good result in the high-risk group with treatment of the aforementioned drugs, which may make us have a better understanding of the effects of these drugs between the two groups. For example, if a patient with PRAD has a high PRFs riskScore, he can be combined with Docetaxel (or Cisplatin/Paclitaxel/Methotrexate/Gemcitabine/Doxorubicin) in addition to effective treatments such as surgery, endocrine therapy or radiation therapy, and may achieve a better prognosis.

To investigate the effect of immunotherapy on high- and low-risk score groups, we calculated the risk score through the BLCA dataset (n = 195 cases) and the KIRC dataset (n = 311 cases), and a survival analysis revealed significant differences in prognosis between both groups, with the high-risk score group having a significantly worse prognosis, which may imply a better treatment effect when immunotherapy is used for patients with a high-risk score. We also found that, by comparing the risk scores from different efficacy groups, we found that the CR/PR group was higher than the PD/SD group in bladder cancer, and the composition of immunotherapy efficacy categories also differed significantly between the high- and low-risk score groups, demonstrating that phagocytic factors were closely related to immunotherapy efficacy and highlighting their potential as therapeutic targets. Finally, the prognostic prediction efficiency for bladder cancer at 0.5, 1, and 2 years for the new survival model was better at indicating prognosis within 6 months of OS. We also analyzed the predicted prognosis for kidney cancer at 1, 3, and 5 years, and the result showed that the areas under the ROC curves for the survival model were 0.58, 0.57, and 0.58, respectively.

In conclusion, the multilayer changes in PRFs were related to prognoses of patients with PRAD and immune microenvironment and immunotherapy, which may provide us with a new directional approach for the future treatment of PRAD. An advantage of our study was that the data from multiple platforms were combined to construct a good indicator for use in guiding prognosis, drug treatment, and other aspects of the disease. However, it is worth noting that the immunization dataset was only clearly distinguishable with the best cut-off point, implying that only a small number of high-risk patients may benefit from immunotherapy.