The first research hotspot in the field of sequencing and omics studies in PCa was the molecular pathogenesis of PCa. Through bibliometric analysis and large amounts of literature reading, we found that the rearrangement of ETS family genes was regarded as the most important pathogenesis of PCa. ETS family proteins were a large family of 28 transcription factors, which had long been implicated in tumorigenesis (25). Five members of them, ERG, ETV1, ETV4, ETV5 and FL1, were seriatim identified by researchers, illustrating their oncogenic function in PCa. Tomlins et al. initially identified the rearrangements of ERG and ETV1 in 50% and 5-10% of PCa (26–28), followed by the discovery of the rearrangements of ETV4 and ETV5 (29–32). FL1, fused to SLC45A3 gene, was the fifth rearranged ETS family gene identified in PCa (33). TMPRSS2, a prostate-specific androgen reactive gene, was the most frequent gene fused to ETS family genes to form the gene rearrangements. Apart from this, other genes sharing analogous functions like SLC45A3, HERV-K_22q11.23 also took part in the rearrangements of ETS family genes. Here, we intended to elaborate the pathogenesis of TMPRSS2-ETS (+) PCa, in which the 5’ untranslated region of TMPRSS2 was fused to ETS, due to its highest occurrence in PCa (26). Other rearrangements of ETS family genes may harbor similar oncogenic mechanisms.

TMPRSS2 was activated by androgen, and launched the expression of ETS family genes. Then, the overexpressed ETS proteins combined with ETS targets and induced the down-stream signaling pathways. It was of great importance to explore the ETS target genes and the corresponding down-stream mechanisms so as to figure out the complicated oncogenic function of ETS rearrangements. Most of the studies were conducted to discover the target genes of ERG. Manuel R Teixeira et al. filtrated seven tumor-associated ERG target genes (CACNA1D, PLA1A, HLA-DMB, ATP8A2, PDE3B, TDRD1, and TMBIM1) in PCa (34). Among them, TDRD1 was the first confirmed gene that was directly regulated by ERG, and encoded the tudor domain-containing protein 1, involved in male germ cell differentiation and in the small RNAs pathway. But its special function in PCa had not been uncovered (34). Olli Kallioniemi et al. identified the up-regulation of histone deacetylase 1 (HDAC1) as the most common characteristic in PCa with TMPRSS2-ERG gene fusion (35). HDAC1 could induce the activation of urokinase-type plasminogen activator (uPA), matrix metalloprotease-1 (MMP-1) and MMP-2, but suppressed E-cadherin in order to accelerate the invasion and migration of prostate cancer cells (36–38).

Cell dedifferentiation was an important characteristic of tumorigenesis, and the differentiation degree of malignant cells usually represented the malignant grade of PCa. As for MMPs, ERG had been discovered to activate the transcription of MMP-1, resulting in loss of cell adhesion, which led to the dedifferentiation of prostate cells (39). Besides, C-MYC and polycomb group protein EZH2, a stemness-related gene, were also found to be down-stream factors of ERG influencing the dedifferentiation process (40, 41). EZH2 could also catalyze the methylation of ERG at the lysine 263 residue, and reversely enhance the oncogenic activity of ERG (42, 43).

Epithelial-mesenchymal transition (EMT) referred to the biological process of the transformation from epithelial cells to mesenchymal cells, characterized by less cell polarity and weaker cell adhesion, which played a role in oncogenesis (44). Wnt/β-catenin pathway was activated by ERG and resulted in EMT to increase the survival and invasive properties of prostate cells (45). TMPRSS2-ERG could also directly bind to Zinc finger e-box binding homeobox 1 (ZEB1) promoter and ZEB2 modulators and increase the expression of ZEB1 and ZEB2, which were key regulators in the EMT (46, 47).

Cell adhesion might affect the migration of cancer cells, and lead to the progression of cancers. Chemokine receptor type 4 (CXCR4) was activated by TMPRSS2-ERG. Combined with its ligand CXCL12, CXCR4/CXCL12 axis increased the aggressiveness of PCa and enhanced the ability of prostate cancer cells to adhere to the extracellular matrix. The axis could also indirectly accelerate the tumorigenesis via increasing the expression of MMPs (48–51).

Several other down-stream targets of ERG were also identified. MicroRNAs (MiRNAs) were another target of ERG. It had been revealed that ERG inhibited the expression of miR-200c, which down-regulated EMT-related genes and acted as a tumor suppressor (52). MiR-221, a cell cycle-related miRNA regulating the phase transition from G0 to S, showed a decreased expression in patients with TMPRSS2-ERG gene fusion (53, 54). As for cell cycle, ETS-E2F fusion oncoproteins destroyed the normal cell cycle control and took part in the tumorigenesis of PCa (55). Changmeng Cai et al. discovered that soluble guanylyl cyclase (sGC) might be a novel transcription target of TMPRSS2-ERG. The NO-cGMP pathway mediated by sGC played an important role in accelerating the proliferation of cancer cells (56).

ETV1, another important member of ETS family, also harbored unique function in PCa, even sometimes opposite to the function of ERG. Although phosphatase and tensin homolog gene (PTEN), MMPs, urokinase type plasminogen activator/urokinase type plasminogen activator receptor (uPA/uPAR) systems had been described as ETV1-related genes (33, 57), we still lacked large amounts of studies to describe the global landscape of gene expressions regulated by ETV1. We intended not to illustrate the down-stream biological process of other ETS family genes in detail, due to their relatively low occurrence of rearrangements in PCa.

Subsequent studies elaborated the complicated mechanisms of oncogenic ETS family acting on their targets. A category of enhancers combined with ETS family had been identified in PCa. These enhancers had a special ETS-binding sequence named AP-1, which was composed of dimers of JUN and FOS family transcription factors (58). ETS/AP-1 enhancer elements were found to be located near the genes associated with cell migration, cell morphogenesis, and cell development, like PLAU, VIM, etc., and might affect the expression of these genes (59). In addition, ETS family was associated with androgen receptor (AR) signaling pathways. Whole-genome ChIP-seq had shown the overlap between the ERG-binding area and AR-binding area. Thus, the overexpression of ERG may have an influence on AR-binding genes in PCa. Arul M Chinnaiyan et al. had raised a model in which the overexpression of ERG inhibited the AR-regulated differentiation but induced the dedifferentiation mediated by the H3K27 methyltransferase EZH2 (60). However, ERG showed an opposite function of enhancing AR-related pathways when PTEN, a phosphatase inhibiting the development of tumor by antagonizing the activity of phosphorylases, was lost (61). ETV1 was found to cooperate with the AR signaling pathways in LNCaP cells (hormone-dependent human PCa cell lines) and PTEN deficient mouse models of PCa. Additionally, ETV1 could also directly up-regulated genes associated with steroid hormone synthesis and androgen metabolism to increase the expression of testosterone, followed by an up-regulated transcriptional activity of AR (62, 63). Besides, Peter C. Hollenhorst et al. found that ETS family could bind an unusual regulatory sequence consisting of repeats of the sequence GGAA, called GGAA microsatellites, and activate the down-stream target genes (64). Apart from this, ETS family genes functioned as transcriptional activators or suppressors when they were combined with different molecules. CBP/p300, MED25 could combine with ETS family to perform a transcriptional activated function, while EZH2, HDAC1, HDAC2, and FOXO1 inhibited ETS-induced gene transcription (65). Last but not least, ETS family could significantly impact the topology of chromatin to influence the gene transcription, since the interaction of ETS family with many chromatin modifying enzymes like p300, HDAC1, EZH2, PRMT5, KDM4A, SETPB1, etc. (66–70).

The overall pathogenesis of TMPRSS2-ETS gene fusion in PCa could be concluded as a ‘Double-Hit’ model. Previous genetic alterations like gene mutations, inhibition of tumor suppressors and activation of tumor promoters might accelerate the progression of prostatic intraepithelial neoplasia (PIN), and the subsequent molecular biological change mediated by ETS rearrangements promoted the development of invasive PCa. The combination of the biological effects of ETS rearrangements and existed genetic alterations contributed to the tumorigenesis of PCa together (28).

The application of sequencing and omics studies in PCa had revealed certain population that were more susceptible to PCa. In a Genome Wide Association Study (GWAS) in 2008, common sequence variants on 2p15 and Xp11.22 were found to be associated with susceptibility to PCa (71). Another study revealed toll-like receptor 4 (TLR-4), a candidate inflammatory gene, was associated to high risk of PCa when its 3’-untranslated region suffered mutations (72). Through a large multiancestry GWAS meta-analysis, 86 novel risk variants associated with the susceptibility to PCa were identified. Integrated with the known risk loci for prostate cancer, ‘genetic risk score (GRS)’ was conducted on the basis of 269 risk variants for PCa. GRS could effectively stratify the risk of PCa across populations, and had been verified in two independent cohorts of men of European and African ancestry (73).

The diagnosis of PCa was currently based on the microscopic evaluation of prostate tissue obtained via needle biopsy. A pathologist examined these tissues and reported the Gleason grade of the predominant histological pattern and the secondary histological pattern. Then, clinicians classified PCa into low-, intermediate-, and high-risk groups according to the sum of Gleason patterns, PSA, and clinical stage. However, the biomarker of PSA harbored a certain probability of false positives and false negatives, and the biopsy was an invasive procedure that may induce discomfort and pain in patients (74). We urgently demanded more specific and sensitive biomarkers to improve the diagnosis effectiveness of PCa.

Through the application of sequencing and omics studies to PCa, a series of genetic alterations had been discovered, which was significant to the diagnosis of PCa. Since the rearrangements of ETS family was the most important pathogenesis in PCa, these genetic alternations might serve as potential diagnosis markers of PCa. Mao X et al. and Arul M Chinnaiyan et al. had detected the gene fusion of TMPRSS2-ERG in circulating tumor cells and urine sediments from PCa patients, respectively (75, 76). And the combined detection of TMPRSS2-ERG and PCA3 significantly improved the sensitivity of diagnosis (77). However, TMPRSS2-ERG, as a diagnosis biomarker, had obvious limitations due to the existence of ETS gene fusion negative PCa (28). Besides, the epigenetic modifications could also perform as diagnosis biomarkers of PCa. Xue−Yi Xue et al. demonstrated key DNA methylation-driven genes like MAOB and RTP4, as novel biomarkers for the accurate prognosis of PCa (78). In 2011, Arul M. Chinnaiyan et al. painted a DNA methylation profile of PCa. CpG islands (CGI) referred to a certain area of DNA that contained large amounts of connected cytosine and guanine. CGI usually located in the transcription regulation domain, and remained non-methylated. However, in PCa, Arul M. Chinnaiyan et al. found that the methylation level was significantly up-regulated, especially for WFDC2. The promoter of WFDC2 showed recurrent methylation in PCa, but remained non-methylated in normal tissues, which might harbor diagnostic value in PCa (79). TMEM79-SMG5, one chimeric RNA, was another potential diagnostic biomarker of PCa. In comparison with TMPRSS2-ERG, which could be found in about 50% of the PCa patients, TMEM79-SMG5 was detected by RT-PCR in approximately 90% of PCa samples tested (80). Proteins were the most common biomarkers for the diagnosis of PCa. A number of differentially expressed proteins were observed in PCa tissues, like UBE2N, PPP1CB, PSMB6, metalloproteinase inhibitor-1, PCa-24, SRM, NOLC1, and PTGIS (81–84). These proteins might offer valuable insights for the diagnosis of PCa. Besides, Brian B Haab et al. identified five serum biomarkers (von Willebrand Factor, immunoglobulinM, Alpha1-antichymotrypsin, Villin, and immunoglobulinG) exhibiting significant differential expression levels between PCa samples and control samples, which may also serve as potential diagnosis biomarkers (85). Notably, several proteins were found to be in accordance to the Gleason grade of PCa. Lukas Alfons Huber et al. discovered that the expression level of Lamin A corresponded with the Gleason grade, qualifying itself as a potential biomarker for tumor differentiation and prognosis (86). Likewise, in 2019, GYG1, LMOD1, igkvhd -20, and RNASET2 were also identified as four proteins correlated with the Gleason grade of PCa (87). Metabolites well reflected the physiological process in an individual. Metabolome, located in the downstream of central dogma, was more directly associated to the phenotype and harbored more direct clinical significance, compared to genome, transcriptome, etc. The study of metabolomics provided a useful way to identify potential biomarkers in biofluid, which may offer non-invasive diagnosis indexes for PCa. The most reported biomarkers in PCa situated in urine, serum, and seminal fluid. In urine, several metabolites exhibited upregulation, including glycocholic acid, hippurate, 7-methylguanine, FABP5, BCAAs, AMBP, CDK6, etc., while taurocholic acid, kynurenic acid, glucoronate, glycine, etc. showed obvious down-regulation (81, 88–94). In serum samples, an elevated expression was observed for sarcosine, alanine, pyruvate, decanoylcarnitine, etc., but glycine, citrate, phosphatidylcholine diacyl exhibited the opposite trend (95–97). Concerning seminal fluid, citrate was down-regulated in 2 reported studies, but AMACR was up-regulated (98–100). However, the metabolomic biomarkers identified in tissues may be more significantly changed than those in biofluid. Citrate, histidine, acetate, creatinine, valine, glycine, lysine, leucine, glutamine, and choline were decreased in PCa tissues, however, uridine and formate were oppositely increased (101, 102). The number of biomarkers that had been identified was so huge to list, but hardly any of them were applied to clinical practice. Multi-omics studies might provide a novel method of diagnosis based on the integrated data. In 2018, epigenomics, transcriptomics, proteomics, and metabolomics studies were applied to a set of patients receiving radical prostatectomy. The prediction model merging the data of DNA methylation, transcripts, proteins, and glycosylation biomarkers successfully increased prognosis predicting accuracy of PCa (103).

The application of sequencing and omics studies in PCa helped us to discover the novel potential therapeutic targets of PCa. A series of studies had shown that the increased copy numbers and the point mutation of AR were the most frequent genetic alterations in castration-resistant prostate cancer (CRPC) (104–106). The complicated rearrangements of AR included highly recurrent tandem duplications concerned an up-stream enhancer of AR (107). More recent studies had illustrated the heterogeneity of AR-activity in primary PCa as well. The subtype of primary PCa with low AR-activity harbored similar biological characteristics to mCRPC, and was more likely to develop the resistance to ADT, docetaxel, etc. (108). Since the AR-related pathways were of great importance in PCa, several target drugs had been developed. Abiraterone, which targeted CYP17, the key enzyme in the synthesis of androgen, and enzalutamide, the second-generation AR inhibitors had been widely applied in the therapy of CRPC (109). DNA damage repair (DDR) deficiency was another frequent genetic alteration in PCa. It had been discovered that the inactivation of core homologous recombination (HR) and HR-associated genes, such as BRCA1, BRCA2, CHEK2, PALB2, CDK12, CHD1, ATM, RAD54L, RAD51B, or PTEN, occurred in a considerable proportion of localized PCa, even more frequently in metastatic PCa (110). This particular subtype of PCa was sensitive to PARPis via the mechanism of synthetic lethality, as PARPi blocked the other DDR pathway, base excision repair, as well (111). Several PARPi including olaparib, rucaparib had been studied in phase 3 trial to treat PCa (112, 113). Last but not least, prostate-specific membrane antigen (PSMA), a type II transmembrane glycoprotein, was fairly lowly expressed in normal prostate tissues, but showed a massive expression in PCa tissues, offering another therapeutic target for PCa (114). As a result, a series of PSMA target therapies, including PSMA-targeted radionuclide therapy (PSMA-TRT), PSMA-antibody-drug conjugates (PSMA-ADC), PSMA-based chimeric antigen receptor (CAR)-T cells therapy had been developed, especially for ¹⁷⁷Lu-PSMA-617 TRT (115). Several relatively less reported therapeutic targets were also revealed by the application of sequencing and omics studies in PCa. Felix Y Feng et al. conducted a systematic study of mCRPC integrating whole-genome, whole-methylome, and whole-transcriptome sequencing. A novel epigenetic CpG Methylator Phenotype (CMP) subtype of mCRPC was identified, with characteristics of hyper-methylation both within and outside of CpG islands, shelves, and shores. This subtype harbored potential therapeutic significance as methylation inhibitors were FDA-approved anti-tumor drugs (116). Another transcriptomics-proteomics-metabolomics combined study revealed the CDK9 (cyclin-dependent kinase 9)-inhibition responses of PCa cells. Acute metabolic stress was induced by using pan-CDK-inhibitor AT7519. AT7519 treatment caused the accumulation of acyl-carnitines, metabolic intermediates in fatty acid oxidation (FAO) produced by carnitine palmitoyltransferase (CPT) enzymes 1 and 2. Co-inhibition of CDK9 and CPT1/CPT2 was lethal to PCa cells (117).

Apart from the potential of discovering therapeutic targets, the application of sequencing and omics studies in PCa could also help evaluate the therapeutic effect and reveal the mechanisms of drug resistance. AR-inhibitor was one of the most effective therapies in PCa, but therapeutic effects varied among patients. Transcriptomic heterogeneity of AR activity well explained the interesting phenomenon (108). Besides, patients receiving AR-inhibitor therapy had shown an activation of atypical Wnt pathway, and the ectopic expression of Wnt5a reduced the anti-proliferation function of AR inhibitors (118). Moreover, the mutations of AR also contributed to the failure of API treatment. With the assistance of sequencing technology, androgen receptor splice variant 7 (AR-V7), characterized by a truncated ligand-binding domain (LBD), was found to be associated to the drug resistance of API, as LBD was the direct target of enzalutamide and indirect target of abiraterone (119). Supraphysiological testosterone (SPT)-based therapy to some extent improved life quality of some CRPC patients, but the resistance of SPT was still a severe problem in front of us. Through transcriptomics study, Eva Corey et al. discovered that SPT durable response was associated with the sustained suppression of E2F and AR-V7 transcriptional output and the impairment of DDR. The combination therapy of SPT and AR-V7/DDR targeted drugs may well improve the response of SPT (120). Last but not least, as for radiotherapy, in 2020, a genome-wide association meta-analysis confirmed several common genetic variants associated with the susceptibility to radiotoxicity of PCa therapy, including rs1801516, rs17055178, etc. (121).