Castration-resistant prostate cancer is the lethal form of prostate cancer and most commonly remains dependent on androgen receptor (AR) signaling. Current therapies use AR signaling inhibitors (ARSI) exemplified by abiraterone acetate, a P450c17 inhibitor, and enzalutamide, a potent AR antagonist. However, drug resistance to these agents occurs within 12-18 months and they only prolong overall survival by 3-4 months. Multiple mechanisms can contribute to ARSI drug resistance. These mechanisms can include but are not limited to germline mutations in the AR, post-transcriptional alterations in AR structure, and adaptive expression of genes involved in the intracrine biosynthesis and metabolism of androgens within the tumor. This review focuses on intracrine androgen biosynthesis, how this can contribute to ARSI drug resistance, and therapeutic strategies that can be used to surmount these resistance mechanisms. The seminal discoveries of Charles Huggins showed that surgical castration followed by adrenalectomy with replacement glucocorticoids led to remission and that the disease could be treated with androgen deprivation treatment (ADT),3. It is noteworthy that these studies implied that there could be two sources of androgens for the tumor to continue to grow, the testis and the adrenal glands. These observations led to the introduction of surgical castration and later leuprolide and other LH-RH agonists to cause a chemical castration as the mainstay of first-line ADT-6. R-Biaclutamide (Casodex), an androgen receptor antagonist, is often added to this regimen. Furthermore, R-biaclutamide can now be replaced with more potent AR antagonists such as enzalutamide. Following, ADT, there is a period of remission, however, the cancer invariably returns to give rise to castration-resistant prostate cancer (CRPC),10.Prostate cancer is a leading cause of cancer in the U.S. male population resulting in 160,000 new cases per year and 34,000 deaths annually. Castrate levels of androgens does not indicate an absence of androgens but only the presence of very low androgen levels in the circulation. Dependence on AR signaling can arise due to changes in the AR,13. These changes include AR gene amplification so that it can respond to trace ligand, AR mutation so that the receptor becomes ligand promiscuous-17, the appearance of splice variants that have lost their ligand binding domain and thus are constitutively active in the absence of ligand, and phosphorylation to activate the receptor in the absence of ligand,20. In addition, the tumor adapts to make its own androgens in response to castration. Traditional ADT does not address the adrenal source of androgens even though the work of Huggins identified that this was an important source. The ability of tumors to make their own steroid hormones is referred to as intracrine synthesis, and Labrie coined the phrase “intracrinology” to describe this process,22. It is now recognized that enzymes and transporters involved in the regulation of ligands for steroid receptors determine the pre-receptor concentration of ligand for hormone action,24.CRPC is the lethal form of prostate cancer and is often detected by a rising serum prostatic-specific antigen (PSA). PSA is an androgen-dependent gene and this implies that despite castrate levels of circulating androgens, the disease remains dependent on androgen receptor (AR) signaling-28; and the other class of agents were the P450c17  inhibitors, represented by abiraterone acetate,29,30 and second-generation analogs galeterone,32 and orterenol. Both classes of ARSIs improve progression-free survival but drug resistance emerges so the increase in overall survival may only be 3-4 months compared to standard ADT. ARSI drug resistance can involve increases in intracrine androgen synthesis mediated by transporters and enzymes, which determine the amount of ligand for the AR, and these mechanisms are the subject of this review.Changes in AR and intracrine androgen biosynthesis are both adaptive responses to ADT. To attenuate these adaptive responses, androgen receptor signaling inhibitors (ARSI) were introduced and belong to two classes of agents. One class of agents are the potent AR antagonists enzalutamide and its second-generation analogs apalutamide and darolutamide4, Δ4-androstene-3,17-dione (Δ4-AD), and the 11-oxygenated androgens (11β-hydroxy-Δ4-AD and 11-oxo-Δ4-AD). Of these, DHEA-SO4 is the dominant serum steroid, and is present in a huge excess compared to all other circulating steroids,34.In a castrate environment, the major source of precursors of potent androgens in the tumor are those derived from the adrenal glands. The adrenal androgens of interest are the C19 steroids dehydroepiandrosterone (DHEA), DHEA-SO, there is no compelling evidence to support the conversion of C27 steroids (cholestanes) into C19 steroids (androgens) by flux measurements-37. Moreover, the large amount of DHEA-SO4 that exists in the systemic circulation with and without P450c17 inhibition makes it seem unlikely that the tumor needs to adapt to castration or ADT to make its own DHEA.In addition to the contribution from adrenal steroids, intracrine steroid hormone biosynthesis could start from cholesterol using the side-chain cleavage enzyme (P450Scc) to produce pregnenolone. Tumor P540c17 would then convert pregnenolone to DHEA. While changes in transcripts for these enzymes have been observed in prostate cancer cell lines and in CRPC tumor biospecimens4 to be utilized by prostate tumors, two events have to take place. First, the anionic steroid needs to be transported by an organic anion transporter protein of the SLCO gene family and, second, steroid sulfatase (STS) needs to remove the sulfate group to generate free DHEA 4-AD by the bifunctional enzyme HSD3B1, which has both 3β-hydroxysteroid dehydrogenase activity and ketosteroid isomerase activity. Δ4-AD represents a junction point; it can be converted by the canonical pathway to testosterone (T) by type 5 17β-hydroxysteroid dehydrogenase (AKR1C3) and then reduced by steroid 5α-reductase (SRD5A1 and SRD5A2) to 5α-dihydrotestosterone (DHT) as demonstrated in clinical specimens,39. Alternatively, Δ4-AD can be converted by steroid 5α-reductase (SRD5A1 and SRD5A2) to yield 5α-androstane-3,17-dione, which is then reduced by AKR1C3 to yield DHT. The latter pathway bypasses T altogether and has been demonstrated in prostate cancer cell lines and xenografts as being the preferred pathway and was confirmed to occur in hormone refractory cancer. However, in CRPC patients and soft tissue metastasis the ratio of T:DHT favors formation of T which can be explained by a down regulation of SRD5A2 and up-regulation of AKR1C3. DHEA is also reduced to 5-androstene-3β,17β-diol by AKR1C3, and then converted to T by HSD3B1. Finally, there is a backdoor pathway in which 5α-androstane-3,17-dione is reduced to androsterone by AKR1C2, and then further reduced by AKR1C3 to 5α-androstane-3α,17β-diol. The diol is then oxidized by HSD17B6 to DHT,45.For DHEA-SO4-AD to produce 11-keto-T and 11-keto-DHT. In addition, the bypass pathway could convert 11-keto-Δ4-AD to 11-keto-5α-androstane-3, 17-dione on route to 11-keto-DHT and thereby bypass 11-Keto-T altogether-484-AD and 11-keto-5α-androstane-3,17-dione are the preferred substrates for AKR1C3 over Δ4-AD and 5α-androstane-3,17-dione,50. Both 11-keto-T and 11-keto-DHT are equipotent to T and DHT in AR driven luciferase reporter gene assays. These pathways underscore the importance of AKR1C3 in all pathways to form potent ligands for the AR.The canonical pathway described above can also convert 11-keto-Δ. AKR1C1 works predominately as a 3-ketosteroid reductase on DHT leading to the formation of 5α-androstane-3β,17β-diol, a pro-apoptotic ligand for estrogen receptor β. AKR1C2 works predominately as a 3-ketosteroid reductase on DHT leading to the formation of the inactive androgen 5α-androstane-3α,17β-diol. Similar reactions are possible with 11-keto-DHT. As described above, HSD17B6 is involved in the back conversion of 5α-androstane-3α,17β-diol to DHT, and compelling evidence exists that by working in opposite directions, AKR1C2 (3-ketosteroid reductase) and HSD17B6 (3a-hydroxysteroid oxidase) work as the molecular switch that determines DHT ligand access to the AR in the normal and diseased prostate. HSD17B2 and HSD17B4 by working as 17β-hydroxysteroid oxidases convert T and DHT to their inactive counterparts, e.g., Δ4-AD and 5α-androstane-3,17-dione, respectively, and are implicated in the inactivation of these hormones,55. The 5α-androstanediols once formed by AKR1C1 and AKR1C2, can then be glucuronidated by UGT family members UGT2B15 and UGT2B17,57. Both UGT2B15 and UGT2B17 expression have been shown to be increased in CRPC.By contrast, the related AKR1C enzymes, AKR1C1 and AKR1C2 play important roles in the inactivation of DHT4 in the serum following leuprolide treatment,59, while enzalutamide will have no effect on adrenal androgens following chemical or surgical castration. For example, the amount of DHEA-SO4 that remains even after combined leuprolide and abiraterone treatment is 4,000 times higher than the castrate amounts of T achieved. Resistance to ARSI can be enhanced when there is either upregulation or activating germline mutations in SLCO transporters or androgen biosynthesis genes or down-regulation or inactivating germline mutations in androgen metabolizing genes that result in elevated intra-tumoral T and DHT 4 that exist in patients on ARSI coupled with increased intracrine formation of T and DHT combined with increased AR expression create a “perfect-storm” for drug resistance.Intracrine androgen biosynthesis has an important role in resistance to ARSI. Abiraterone acetate and other P450c17 inhibitors leave behind a significant reservoir of DHEA-SOSLCO1A2, SLCO1B1 and SLCO1B2 are increased 4-fold, 2.5-fold, and 1.74-fold respectively in LNCaP and 22Rv1 prostate cancer cells grown under conditions of androgen depletion to mimic ADT. Increased SLCO expression led to increased cellular uptake of [3H]-DHEA-SO4 and increased cellular proliferation stimulated by DHEA-SO4. The cellular proliferation in response to DHEA-SO4 was attenuated by SLCO1A2 knockdown, indicating the requirement of these transporters to facilitate intra-tumoral androgen biosynthesis. SLCO1B1- and SLCO2B1-expressing prostate cancer xenografts showed a 3.9-fold and 1.9-fold increase in tumor accumulation of DHEA-SO4, respectively. SLCO genes are also overexpressed in CRPC metastases. When 1,309 Caucasian prostate cancer patients were genotyped, nsSNPs in SLCO were associated with a poor progression-free survival. For example, three SNPs in SLCO2B1 rs1242149, , rs1789693 (intronic), and rs1077858 (intronic) were associated with decreased time to progression on ADT (P < 0.05). When the SLCO2B1 SNP variant rs1242149  was transfected into LNCaP cells, transfected cells exhibited higher maximal DHEA-SO4 accumulation when compared with the wild-type allele. It is predicted that variants in the SLCO genes may serve as predictors of DHEA-SO4 uptake and ARSI resistance (see Transcripts of STS) which is required for the deconjugation of DHEA-SO4 to from free DHEA for downstream androgen biosynthesis. Knockdown of STS in castrate-resistant prostate cancer cell lines demonstrates the dependency of T and DHT synthesis on active STS. However, inhibition of STS for the treatment of CRPC is not a good strategy, since STS deficiency leads to ichthyosis which has been observed naturally in X-linked ichthyosis.There is only one steroid sulfatase gene  results in the amino acid change Asn367Thr. This mutation does not change the kinetic properties of the enzyme but leads to a more stable protein that is resistant to degradation suggesting that the variant will lead to increased intra-tumoral androgen biosynthesis and ARSI drug resistance. Although it is not possible to determine how this mutation affects protein stability without a crystal structure for the enzyme, clinical studies show that the adrenal permissive mutation 1245 A→C is associated with inferior outcomes to ADT,67.A common 1245 A→C missense- single nucleotide polymorphism in 5-ene in its structure and can be metabolized to Δ4-abiratreone by HSD3B1, which is then converted to 5α-abiraterone by SRD5A1/SRD5A2. Each of these metabolites have their own activity. Δ4-Abiraterone has anti-tumor activity since it inhibits P450c17, HSD3B1, and is an antagonist of the AR, leading to the concept that abiraterone acetate may be a pro-drug and that Δ4-abiraterone is the active metabolite. By contrast, 5α-abiraterone will activate the AR, potentially driving cancer progression. Thus, the mutant HSD3B1 allele can contribute to ARSI drug resistance by this mechanism.The ARSI abiraterone has a 3β-hydroxyl- ΔAKR1C3 is one of the most highly expressed steroidogenic genes in CRPC; this has been seen by RT-PCR and Affymetrix microarray. AKR1C3 is upregulated by androgen deprivation in prostate cancer cells, xenografts, and patient tumor samples-74. Castration also induces up-regulation of AKR1C3 in an orthotopic VCaP human prostate cancer xenograft and leads to tumor growth. Ten or more separate studies have replicated the finding that AKR1C3 is overexpressed in CRPC-73,75,76. One such study showed AKR1C3 overexpression in primary lesion re-biopsies at the time of metastatic disease. Consecutive prostate cancer specimens revealed increased AKR1C3 expression during progression to CRPC. It is estimated that approximately 30% of CRPC patients will overexpress this enzyme. AKR1C3 has since been proposed as a biomarker for the CRPC. Experiments aimed at determining the mechanism of AKR1C3 over-expression have implicated the involvement of the TMPRSS2-ERG fusion protein in its regulation. The TMPRSS2-ERG fusion protein arises in late-stage disease based on Gleason grade, where ERG acts as a transcription factor to increase AKR1C3 expression and remove the repressive effect of the AR on the AKR1C3 promoter. In this mechanism, ERG binds to the AKR1C3 promoter to induce gene transcription to increase T or DHT production which in turn increases TMPRSS2-ERG expression to induce AKR1C3 expression in a “feed-forward” manner.AKR1C3 gene,80. C4-2B prostate cancer cells when grown in the presence of either abiraterone or enzalutamide over-express AKR1C3 and are resistant to growth inhibition by these drugs. The drug-resistant cell lines are, however, sensitive to growth inhibition in colony formation assays in soft agar and in xenografts to the AKR1C3 competitive inhibitor indomethacin,80. The efficacy of indomethacin to improve progression-free survival and overall survival is being tested in a clinical trial in patients that progress on enzalutamide , and in patients that progress on abiraterone acetate . Similarly, AKR1C3 inhibitors could be used to surmount resistance to apalutamide and darolutamide, discussed later in this paper.Treatment of prostate cancer cells with abiraterone or enzalutamide all increase AKR1C3 expression consistent with androgen-dependent repression of the AKR1C3 non-synonymous single nucleotide polymorphisms (nsSNPs) with varying global frequencies. The top-most frequently occurring variant (His5Gln) occurs in over 50% of the global population with an occurrence of 43% in African Americans. Lys104Asp, Glu77Gly, Arg258Cys have minor allelic frequencies of 15%, 3.7%, and 3.3%, respectively. All of these mutations were examined for their ability to conduct 17-ketosteroid reduction of the aromatase inhibitor exemestane, and each gave a significant reduction in catalytic efficiency that was 17-170 fold lower than the wild-type enzyme. The remainder of the nsSNPs have a minor allelic frequency (MAF) of > 1%. It is unknown if these nsSNPs are enriched in prostate cancer patients. These nsSNPs can be mapped to the crystal structure of AKR1C3 and do not reside in the cofactor binding site, steroid binding cavity, or at the active site. AKR1C3 has a a/b8-barrel structure which is evolutionarily conserved across phyla in the AKR gene superfamily. In AKR1C3 there are seven nsSNPs that are in amino acids that are evolutionarily conserved in the structure . These amino acids are conserved since they likely maintain protein folding and therefore mutations in these amino acids likely affect protein stability. It is predicted that carriers of these allelic variants may be more responsive to ARSI therapy.There are 14 HSD17B6 gene has a number of aliases, e.g., RL-HSD, and actually functions as a 3α-hydroxysteroid dehydrogenase and epimerase rather than a 17β-HSD. It was identified as the major oxidoreductase responsible for the back conversion of 5α-andostane-3α,17β-diol to DHT in prostate cancer,45. Few SNPs have been reported in this gene to date.The SRD5A2 deficiency [. There are more than 114 different mutations in the SRDA2 gene . However, less than 20 have been expressed to determine the consequences of these mutations on enzyme function. The protein is predicted to have two putative functional domains, an NADPH cofactor binding domain and a steroid binding domain. Ser14Arg, Arg145Trp, Arg171Ser, Phe229Ser, Ser245Tyr result in either complete loss of enzyme activity or seriously diminished enzyme activity. Arg145Trp, Arg171Ser, and Ser245Tyr are predicted to have diminished affinity for NADPH. Many SNPs have been associated with prostate cancer and lead to the following amino acid changes: Val3Ile, Ala49Thr, Val63Met, Phe118Leu, Gly183Asp, Val189Ala, Gly191Glu, Leu221Pro, Leu226Pro, and Ala248Val, and have been kinetically characterized. Of these, Ala49Thre and Leu226Pro had significantly higher utilization ratios (Vmax/Km). The loss-of-function mutations in prostate cancer patients are likely to make the tumor more dependent on T rather than DHT, and may, therefore, have a neutral effect in response to ARSI therapy, and their occurrence is unlikely to be a major mechanism of drug resistance.Abnormal SRD5A3) has also been identified. However, there has been controversy as to whether this reductase is really involved in the conversion of T to DHT. There is strong evidence that this gene instead encodes for a polyprenol reductase required for the synthesis of dolichol, and that mutations in this gene lead to a congenital glycosylation disorder.A third steroid 5α-reductase gene . Three of these  are in evolutionarily conserved residues, whereas Arg258Cys has a MAF of 0.064. In addition, Phe46Tyr has a MAF of 0.0649, but the MAF of the remainder are > 0.0034. The effect of some of these allelic variants on the in vitro metabolism of DHT has been examined. Unfortunately, the authors examined the effect of these variants following expression in Sf9 insect cell lysates and used a catalytic inactive mutant Tyr55Phe as a control. Under these conditions, a significant background turnover of DHT was noted in the presence of the catalytically inactive Tyr55Phe mutant making it difficult to interpret these data. The authors concluded that Phe46Tyr (0.0649 MAF) and Leu172Gln (not in NCBI) reduced the apparent Vmax and that Leu172Gln, Lys185Glu and Arg258Cys all reduced the apparent Km. However, their effect on the utilization ratio Vmax/Km for reduction of DHT by these variants was modest and varied by only 2- to 3-fold.There are a number of nsSNPs in HSD17B2 expression is reduced in prostate cancer patients, and consistently a HSD17B2 gene deletion was found in both primary and metastatic prostate cancer. In xenograft models over-expression of HSD17B2 suppressed androgen-induced cell proliferation and xenograft growth, consistent with its enzyme activity to inactivate 17β-hydroxyandrogens. Mechanisms responsible for this reduced expression included DNA methylation and mRNA alternative splicing. Two new catalytic-deficient shorter isoforms generated by alternative splicing were found to bind to the full-length enzyme promoting its degradation and are involved in the functional silencing of HSD17B2. It is unknown if this alternative splicing mechanism occurs more frequently in ARSI drug resistance.HSD17B4 expression can increase in CRPC and predicts poor prognosis which appears counterintuitive based on its role to inactive androgens. However, there are five alternatively spliced isoforms, and only isoform 2 inactivates T and DHT, and it is this isoform that is suppressed in CRPC. Genetic knockdown of HSD17B4 isoform 2 increases T and DHT to stimulate the AR and CRPC development in xenograft models. It is unknown if reduced HSD17B4 expression contributes to ARSI drug resistance.UGT2B15 and UGT2B17 are actively involved in the elimination of hydroxyandrogens as glucuronides from prostate cancer cells. These genes are characterized by common polymorphisms and copy number variants that affect enzymatic activity and expression. Whole-gene deletions in UGT2B15 and UGT2B17 are observed in 27% and 13.5% of Caucasians and over 50% have a deletion of one of these genes. The nsSNP in UGT2B15  increases Vmax by several fold and has a MAF of 0.32. Both these changes have been associated with increased prostate cancer risk. The expression of UGT2B17 is inversely correlated with activation of the full-length AR receptor consistent with maintaining a homeostasis of AR signaling in normal prostate and castration sensitive prostate cancer. However, castration resistance leads to the expression of the constitutively active AR-V7 splice variant which upregulates UGT2B17 expression-92. Although this seems counterintuitive, increased expression of UGT2B17 induced by AR-SV could be part of a coordinated response to make the tumor remain dependent on AR signaling in the absence of ligand. Additional UGT2B15 polymorphisms  rs9994887 (upstream), rs13112099 (upstream), rs7686914 (upstream), and rs7696472 (upstream) have been associated with an increased risk of PCa in a multiethnic study.. AR coactivators are AR-interacting proteins that amplify AR-dependent gene transcription in the presence of ligand. AKR1C3 is a selective coactivator of AR, having no effect on the transcription mediated by other nuclear receptors. Furthermore, AKR1C3 acts as coactivator on AR with an activity comparable to SRC-2. The co-activator domain of AKR1C3 maps to amino acid residues 171-237 which is distinct from the active-site. This region contains a putative p160 coactivator peptide of LxxIL buried within α-helix 5, were the consensus sequence to bind to the ligand binding domain of AR is LxxLL. Although this motif can bind to the AF-2 region of the ligand binding domain of the AR, this interaction is out competed by a N/C interdomain interaction involving the FxxLF motif in the N-terminus of AR,97, leaving the identity of the coactivator peptide domain of AKR1C3 uncertain. The LxxLL motif present in AKR1C3 is also conserved within the AKR1C1 and AKR1C2 sequence and these proteins do not have coactivator properties. Comparison of the 171-237 region in all three enzymes shows a difference in amino acid residues in these enzymes. In AKR1C3, the sequence corresponds to 222QRDKRW227 whereas in AKR1C1 and AKR1C2 the sequence corresponds to 222HREEPW227. Mapping this region to the AKR1C3 crystal structure shows that this peptide is in a disordered loop. It is likely that this loop interacts with the NTD pf the AR Several of the steroidogenic enzymes have other properties that contribute to their role in ARSI drug resistance. One such enzyme is AKR1C3, that can act as a coactivator of the AR. In addition, AKR1C3 binds and stabilizes the ubiquitin ligase Siah-2, inhibiting its degradation, thereby enhancing Siah-2-dependent down-regulation of the AR corepressor NCoR in prostate cancer cells.Confocal microscopy and proximity ligation assays have validated the interaction between AKR1C3 and the AR, and the co-translocation of both proteins to the nucleus. While many different coactivators exist for the AR, AKR1C3 has a unique property of being up-regulated by androgen deprivation in CRPC. AKR1C3 stabilizes AR-V7, a major AR-SV observed in clinical specimens2α epimers that can activate the FP1 receptor. Activation of the receptor leads to activation of the MAPK pathway and phosphorylation of PPARγ, leading to its inactivation. Inactivation of PPARγ is considered a pro-proliferative signal since it prevents cellular differentiation. The involvement of this pathway in CRPC remains to be determined.Another function of AKR1C3 is its ability to be the dominant prostaglandin F2α synthase in humans. This enzyme function leads to the formation of PGF,102. There has been much debate as to whether this was due to increased patient monitoring and frequency of needle biopsy, despite the increase in high-grade disease being small. Nonetheless, the FDA has issued black-box warnings for their use in prostate cancer therapy. Inhibitors of HSD17B6 appear to be in their infancy. Thus, the focus of our discussion will be on inhibitor development for AKR1C3.Drug resistance to ARSI could be attenuated by inhibitors of HSD3B1, AKR1C3, HSD17B6, and SRD5A2/A1. However, there are no inhibitors that have the desired selectivity for HSD3B1 over HSD3B2, and inhibition of these enzymes would block all steroid hormone biosynthesis. Both finasteride (SRD5A1 inhibitor) and dutasteride  have been shown in chemoprevention trials to give rise to a reduction in tumor incidence but also cause an increase in high-grade disease as determined by Gleason grade.A large number of small-molecule AKR1C3 inhibitors have been developed for the potential treatment of CRPC as a monotherapy and to surmount ARSI drug resistance. Effective compounds need to show potency and selectivity for the target. Compounds must not inhibit AKR1C1 or AKR1C2 which would inactivate DHT. This can be challenging since the AKR1C enzymes exhibit 86% sequence identity and have similar crystal structuresN-phenylanthranilic acid, indomethacin and R-naproxen analogs-106, and their bioisoteres, as well as 3--ylsulfonyl)benzoic acids, caffeic acid phenethyl esters, berberine analogs, 1-(4-(piperidin-1-ylsulfonyl)phenyl)pyrrolidin-2-ones, 2,3-diarylpropenoic acids, and ASP9521 (developed by Astellas),114, GTx-560 (developed by GTx-therapeutics); the natural product analogs based on baccharin and amaryllidaceae alkaloids; and finally the steroidal based analogs developed by Bayer, e.g., BAY1128688, that are proprietary. Crystal structures of AKR1C3•NADP+•Inhibitor complexes exist for many of these agents, and there is a good structural basis for their mode of inhibition. Carboxylic acid analogs or those that contain an organic anion form a counter ion with the catalytic tetrad in which Tyr55 has TyrOH2+ character. Depending on the appendages to the anion, side chains can occupy three different pockets: the steroid binding cavity, sub-pocket (SP)1 , SP2 , and SP3 . A recent patent review on many of these agents was published by our group. Rather than review all these agents a few highlight points will be made.AKR1C3 inhibitors that have been developed are both non-steroidal and steroidal in nature. The non-steroidal inhibitors include re-purposed NSAID analogs that no longer inhibit Cox-1 and Cox-2, based on .First, indomethacin has made it into clinical trial for patients who progress on enzalutamide. Due to the gastrointestinal side effects associated with chronic use of this NSAID, indomethacin analogs, that are more potent and selective for AKR1C3 than the parent compound and that do not inhibit the COX isozymes, offer promise to replace indomethacin,114. However, there were several reasons why this trial failed. Of the small number of patients enrolled 6/13 failed to complete their drug regimen. Patients were excluded from the trial if they had been on abiraterone or R-biaclutamide before the commencement of the trial but these would be the very treatments that would upregulate AKR1C3. Moreover, there was no determination of whether the patient tumors were AKR1C3 positive, even though there is an IHC grade monoclonal Ab available.Second, ASP9521 is an AKR1C3 inhibitor that went into a phase 1/2 clinical trial and was found to be well tolerated but without efficacy. However, this does not mean that other monofunctional AKR1C3 inhibitors will not behave the same way. They have not yet been screened in drug combinations.Third, the baccharin anlogs (Kv37) are the only agents that have been shown to have synergistic anti-proliferative effects with enzalutamide in vitro, where the combination index shows up to a 200-fold synergistic effect. However, it is not clear whether the compound was counter screened against other AKRs, including AKR1C4 and AKR1D1 that are essential for bile acid biosynthesis.Fourth, steroidal analogs, e.g., BAY1128688, run the risk of also inhibiting other steroid-transforming enzymes or steroid receptors. It is noteworthy that BAY1128688 went into a phase 2 clinical trial for endometriosis that was halted due to hepatic toxicityN-phenylaminobenzoates based on N-phenylanthranilic acids gave rise to the N-naphthylaminobenzoate (BMT4-158) that is a “first-in-class” bifunctional AKR1C3 inhibitor and AR antagonist. In a recent head to head comparison of this agent with ASP9521 and GTx-560, BMT-4-158 out-performed these agents since it was the only compound that acted as a competitive inhibitor in AR binding assays and displaced R1881 in AR competitive binding assays.Fifth, the . The agent had anti-tumor activity in xenograft models of prostate cancer, and it is unclear why this compound was not taken into clinical trials. This compound and its analogs offer promise to block two mechanisms of ARSI resistance, intra-tumoral androgen biosynthesis, and AR coactivation.Sixth, GTx-560 is a “first-in-class” bifunctional AKR1C3 inhibitor that competitively inhibits the enzyme function of AKR1C3 but also blocks its coactivator function on the ARIt is apparent that a large number of competitive inhibitors of AKR1C3 exist that have the desired potency and selectivity, however, if used as monofunctional agents, it is likely that other mechanisms of drug resistance will emerge, e.g., the appearance of AR splice variants (AR-SVs). Bifunctional inhibitors BMT4-158 and GTx-560 offer the promise of blocking intra-tumoral androgen biosynthesis and AR transactivation.4-AD and 5α-DHT. When combined with upregulation of AKR1C3 these changes could lead to increases in steroidogenesis that is greater than that achieved by either change alone. A second mechanism involves the appearance of AR-SVs as the disease emerges,123. AR-SVs have lost their ligand binding domain and some of these AR-SVs are constitutively active in the absence of ligand. AR-V7 is stabilized by AKR1C3 so that overexpression of the latter will increase the steady state concentration of AR-V7. AR-V7 is one of the most prominent AR-SVs, leading to attempts to develop clinical assays to detect this variant in biospecimens to determine whether ARSI drug therapy should be discontinued-126. A third mechanism involves phosphorylation of the AR-MED1 transcriptional complex mediated by cyclin-dependent kinase 7 (CDK7). Phosphorylation on AR Ser81 is sufficient to activate the AR in the absence of ligand and may contribute to resistance to enzalutamide, darolutamide, and apalutamide. It is unknown whether AKR1C3 could act as a coactivator of phosphorylated AR. A fourth mechanism involves the hijacking of the glucocorticoid receptor (GR) to substitute for the AR. It is noteworthy that both the GR and AR bind to the same hormone response elements in the promoter of regulated genes.Upregulation of AKR1C3 in response to ADT and its contribution to drug resistance to ARSI is only one mechanism of resistance to these agents. Multiple mechanisms may contribute to the drug resistance phenotype, they may not be mutually exclusive, they may also synergize with each other, and different mechanisms may contribute differently based on the patient. One mechanism involves mutations in other steroidogenic genes such as HSD3B1, where the stability mutant enabled increased formation of ΔIt is apparent that intracrine androgen biosynthesis is an important component of resistance to ADT and ARSI inhibitors, and is clinically actionable. Knowledge of the nsSNPs that alter the activity or stability of the enzymes involved can determine who will benefit and who will not benefit from ARSI inhibitors. The enzyme that appears to be most important in mediating drug resistance is AKR1C3, and this is endorsed by the large number of small-molecule inhibitors that have been developed for this target both by academic laboratories and industry. Studies have moved beyond target validation and time will tell whether some of these compounds can transit preclinical development and make their way into well designed clinical trials for ARSI drug resistance. It is also apparent that AKR1C3 inhibitors do not necessarily have to be used as a monotherapy, but may improve progression-free survival in combination with other ARSIs.


Chlamydomonas reinhardtii were detected when it was compared with seven other higher plants. In addition, Guanylate_cyc existed in more genes of lower plants than of higher plants. In our PSSRD, we constructed an interactive plotting function in the chart interface, and users can easily view the detailed information of SSRs. All SSR information, including sequences, primers, and annotations, can be downloaded from our database. Moreover, we developed Web SSR Finder and Batch SSR Finder tools, which can be easily used for identifying SSRs. Our database was developed using PHP, HTML, JavaScript, and MySQL, which are freely available at http://www.pssrd.info/. We conducted an analysis of the Myb gene families and flowering genes as two applications of the PSSRD. Further analysis indicated that whole-genome duplication and whole-genome triplication played a major role in the expansion of the Myb gene families. These SSR markers in our database will greatly facilitate comparative genomics and functional genomics studies in the future.Simple sequence repeats (SSRs) are one of the most important genetic markers and widely exist in most species. Here, we identified 249,822 SSRs from 3,951,919 genes in 112 plants. Then, we conducted a comprehensive analysis of these SSRs and constructed a plant SSR database (PSSRD). Interestingly, more SSRs were found in lower plants than in higher plants, showing that lower plants needed to adapt to early extreme environments. Four specific enriched functional terms in the lower plant  The development and comparative analysis of molecular markers could help us reveal genetic variation underlying various biological functional genes4. To date, researchers have found several molecular markers, such as restriction fragment length polymorphisms, random amplified polymorphism DNA, sequence tag sites, amplified fragment length polymorphism, diversity array technology markers, single-nucleotide polymorphisms, specific locus amplified fragments, and simple sequence repeats (SSRs)6.Since molecular marker technology was developed in the 1980s, an increasing number of molecular marker types have been identified, which has rapidly accelerated genetic improvements in species8. There have been many studies of molecular markers in model plants9. For example, several kinds of molecular markers were used to identify genes related to leaf senescence, leaf shape, chlorophyll, and embryogenesis in Arabidopsis12. Similarly, most genes determining disease resistance and major agronomic traits, such as grain quality, grain weight, and grain size, were also detected using molecular markers in rice16. In horticultural plants, molecular markers are also widely used for plant breeding in most species, including Brassica rapa, Brassica oleracea, Solanum lycopersicum, Cucumis melo, Vitis vinifera, Fragaria ananassa, and pear22. Furthermore, progress in molecular genetics, genomic selection, and genome editing has provided deep insights into the understanding of molecular markers and greatly complemented breeding strategies1.These molecular markers play important roles in genetic map construction, quantitative trait locus detection, marker-assisted selection (MAS), and fine localization of important functional genes to fulfill various demands of breeders25. SSRs have become extremely popular for phylogenetic analysis and have expanded our knowledge related to plant breeding28. The development of bioinformatics technology has enabled the development of SSR markers for many species31. Recently, there have been many reports on SSR development and application38. These studies have confirmed that SSRs are the classic, popular molecular markers used in plant science.SSR markers are present in almost all species, particularly in eukaryotes. These markers have many applications, such as constructing linkage maps, fine mapping of genes, and selective breeding through genomic selectionWith an increasing number of plant genomes being released, it has become possible to construct a plant SSR database (PSSRD) using the SSRs identified from all genes in these plants. Compared with those in existing databases, all the species in the database in this study have undergone complete genome sequencing. In addition, the PSSRD provides primer information and Pfam function annotation, which allows researchers to use these SSRs in a more convenient manner than those in other databases. More importantly, we not only provide more comprehensive and representative SSR information with the construction of this database but also conduct large-scale systematic and comparative analyses of SSRs in 112 plants.B. rapa, Brassica oleracea, Capsicum annuum, Daucus carota, and S. lycopersicum), fruits , and flowers . On average, primers were successfully designed for 98.82% of the SSRs for further study. Using these available datasets and related bioinformatics tools, we built a PSSRD, which helps users easily query, compare, and download SSR markers, primers, and functional annotations of several or all species simultaneously. All species used in this study were taxonomically classified to facilitate selection and use. The SSR information was stored in backend tables using MySQL  that can be accessed using the frontend web application of PSSRD , and 8 lower plants, respectively Fig. . Among tSRD Fig. . Here, wSRD Fig. .Fig. 1ThTm) value, and size), amplified production size, and related gene information (gene ID and links of Pfam annotation). Furthermore, we also integrated the search function at the browse interface, which allows the users to find related information according to gene ID, SSR type, and SSR sequences. Moreover, we provided a variety of export formats, including Excel, pdf, csv, duplicate, and print functions.To make the database easy to use by researchers, we divided all species into different groups according to their taxa Fig. . For eacThe chart interface provides several interactive plots to view the SSR data of all species Fig. . First, In addition, we provide further graphical representations of the SSR information for each species. Each species has six plots with pie charts, bar plots, and line charts, which show detailed information on SSRs, including SSR type, SSR length, product size, most frequent SSR, base number, and frequency of SSR distribution for each type. These diagrams could help users intuitively understand the SSR information of each species.The SSR information and statistics for each species can be downloaded from this interface Fig. . Four fiIn addition to providing SSR information retrieval, graphical display, and download services for existing species, we developed two tools, the Web SSR Finder (WSF) and Batch SSR Finder (BSF) programs Fig. . These tFor the WSF, users can upload nucleic acid sequences in the FASTA format and then set the minimum number of repetitions for various types of SSRs. Finally, the start button can be clicked, and after a moment, the relevant SSR identification results are obtained.The BSF program can batch-detect SSRs in multiple species on the local server. Although the previous MISA program could identify SSRs, it only detected the SSR of one species at a time. Therefore, we have modified and updated the MISA program and named the new program BSF. In addition to some basic SSR identification files, we also provide comparative analysis files of SSRs between different species. With the completion of additional genome sequencing, a batch-comparison study needs to be conducted on the SSR information of a large number of species. Therefore, the updated BSF program is more convenient for users to carry out batch SSR identification and multispecies comparative studies. Anyone engaged in scientific research can download and freely use or further edit this program according to their own analysis needs.For the resource interface, we collected most of the SSR research-related databases and provide relevant links for users to easily query and compare studies Fig. . For theChenopodium quinoa) to 12,663 (lower plant: C. reinhardtii). The average number of trinucleotide SSRs was 1610 in 112 plants, followed by dinucleotide SSRs (229) and hexanucleotide SSRs (219)  Fig. . This re19) Fig. .Fig. 3ThTo explore the relationship between the factors related to different SSR characteristics, we conducted a correlation analysis for these factors. Here, we investigated several factors related to SSR characteristics, including SSR number, SSR density (SSR number per Mb), number of genes containing SSRs, and percentage of genes containing SSRs. In addition, the factors total gene number and total length of gene sequences were also used for the comparative analysis in all examined plants.P value < 0.01)  Fig. . HoweverOur analyses showed that among the plants, the different lower plants had the largest SSR variations, including variations in SSR number, SSR density, number of genes containing SSRs, and percentage of genes containing SSRs Fig. . The aveMicromonas pusilla CCMP1545 and C. reinhardtii , with 12,799 SSRs, followed by P. mume (17.58%) and C. melo (15.96%)  with 5991 SSRs, followed by Oryza glaberrima (11.80%) and Oryza sativa (9.05%)  was found in spider flowers (6%) Fig. . In mono5%) Fig. .q value < 0.05 and fold change ≥2 , other higher plants (65.29), and lower plants (60.27%) Table . We furt≥2 Table . Our enr≥2 Table . This req values < 3.32e − 78  was found in 27,984 sequences from 4096 species according to the Pfam database. Among these sequences, 12,485 sequences from 918 species belonged to Eukaryota, while most of the other sequences belonged to bacteria Fig. . In EukaKlebsormidium nitens and Chara braunii), which contained six and two genes with the Guanylate_cyc domain, respectively , one Lycophyte (Selaginella moellendorffii), and one angiosperm (Ricinus communis). All identified SSRs located in these genes with the Guanylate_cyc domain could be used as markers for functional studies in the future.Among the five species from Streptophyta, two species belonged to Charophyta  and higher plants, including the horticultural plant B. rapa, eudicot model plant Arabidopsis thaliana, monocot model plant O. sativa, basal angiosperm Amborella trichopoda, gymnosperm Picea abies, Lycopodiophyta S. moellendorffii, and Bryophyta P. patens . The most significantly enriched functional terms were detected in O. sativa (33), followed by in B. rapa (10), P. abies (8), C. reinhardtii (4), A. thaliana (2), A. trichopoda (1), and S. moellendorffii (1)  Fig. . HoweverO. sativa, B. rapa, P. abies, and C. reinhardtii, respectively , whereas in Arabidopsis, the number of gene duplications was lower than the number of gene losses  event since its divergence from Arabidopsis according to a previous report39. Therefore, we inferred that WGT events might play important roles in the expansion of the Myb_DNA-binding gene family in B. rapa.Among the eight species, the most genes were identified in ies Fig. . In B. rses Fig. . BrassicO. sativa and P. patens, and these duplications occurred in one or several whole-genome duplication (WGD) events. For the other four Myb gene families, we found that they had similar trends in gene duplications and losses as those of the Myb_DNA-binding gene family , phytochrome-dependent late flowering , and cryptochrome 2  genes contained SSRs in B. rapa. These SSRs will be useful for MAS breeding for flowering in Brassica in the future. Similarly, users could also search for SSRs in other functional genes of 112 species from the PSSRD. Therefore, our database can provide researchers with plentiful SSR resources.Most flowering-time genes have been reported and functionally characterized in ram Fig. . Furtherapa Fig. . For exaB. rapa. The green indicates that the flowering-time genes contained SSR markers.The distribution of flowering-time genes on ten chromosomes in 50. Guanylate cyclases are part of the G-protein signaling cascade, which is inhibited by high intracellular calcium levels but activated by low calcium levels52. Therefore, the genes with the Guanylate_cyc domain might play critical roles in lower plants, animals, and bacteria. This finding provides a new perspective for the functional study of SSR-related genes.In this study, we comprehensively identified SSRs from all the gene-coding sequences (CDSs) of 112 plants and further performed functional enrichment analysis for SSR-related genes. Among the top 20 significant functional enrichment terms, the Guanylate_cyc term had the largest fold change for SSR-related genes relative to the whole-genome level. Interestingly, further investigation showed that the Guanylate_cyc domain existed in lower plants and other nonplant species, while it was rarely found in higher plants. Based on previous reports, guanylate cyclases catalyze guanosine triphosphate to cyclic guanosine monophosphate (cGMP). As an intracellular messenger, cGMP activates kinases and regulates ion channels57. This result indicated that SSRs might play critical roles in regulating plant stresses. Further comparative analysis of eight representative plants showed that several specific and common enriched functional terms were detected. Among all functional enriched genes, Myb-related gene families existed in most plants. The Myb gene family has a wide range of effects on plant growth, development, and stress resistance, such as anther development, axillary meristem formation, cell-wall thickening, and sperm cell formation60. The Myb gene family is also involved in several biosynthesis pathways, such as anthocyanin and flavonol synthesis, and hormone responses62. Our further analysis indicated that WGD and WGT played a major role in the expansion of the Myb gene families. This finding provided new insights and guidance into SSRs and other gene families.Our findings showed that the most significantly expanded functional terms were transcription factor families related to the regulation of abiotic stresses, such as Myb, AP2, and WRKY. Most of these gene families played important roles in stress resistance in plants according to previous reports65. However, most existing SSR databases were constructed several years ago and have not been updated with novel sequence information, or they cannot be accessed. Therefore, we constructed a PSSRD in this study, and it will be updated with new SSR datasets and information promptly in the future. With the increasing number of genome sequences released, we will continuously collect novel genomic datasets and identify SSRs and store them in our PSSRD for users. We also encourage users to submit their new SSR datasets to us to further enrich and refine the database. Moreover, we welcome all users to send us feedback for further improvement of our database. We believe that the PSSRD will be a useful and user-friendly database for researchers.Currently, an increasing number of genomes have been sequenced, and it is possible to develop a large number of SSR markers at the whole-genome level in different species from each main kingdom. To date, several databases have been constructed to collect SSRs from one or more species, such as the Plant Microsatellite Database, FishMicroSat, and Microsatellite DatabaseIn conclusion, we constructed a PSSRD for widely collected SSR sequences from 112 plants. Interestingly, we found that more SSRs were detected in the lower plants than in the higher plants. Moreover, a comprehensive comparative analysis of SSRs was conducted to reveal their basic characteristics and functional enrichment in different plants. This PSSRD can be used for comparative genomic analysis and molecular MAS studies of plants in the future.http://useast.ensembl.org/index.html). The alternative splice sequences within the species were removed by custom Perl script to ensure no redundancy of the datasets. We have provided detailed information on the 112 plants used in this study, such as the classification, genome information, and related references in Table 67.The CDSs and protein sequences of each plant in Fasta format were downloaded from the ensemble database (68. The parameters were set as follows: monomers (×16), 2-mers (×8), 3-mers (×6), 4-mers (×5), 5-mers (×4), 6-mers (×4), 7-mers (×3), 8-mers (×3), and 9-mers (×3)69. This program allowed the identification and localization of perfect and compound microsatellites. When the sequence length between two SSRs was <100 bp, we defined them as a compound SSR according to previous reports and the default parameters of the MISA software71.The SSRs of the gene sequences in the selected species were identified using a batch SSR search program, which was written according to the Microsatellite identification tool (MISA)72. The main parameters were set as follows according to a previous report2: (i) the optimum primer length was 20 nucleotides, and the range was from 18 to 27 bases. (ii) The optimum temperature of the Tm was 60 °C, and the range was from 55 to 65 °C. (c) The optimum size of the target PCR products was 150 bp, and the range was from 100 to 280 bp. All other parameters were set to the default values according to the Primer3 program.The primers were designed for the identified SSRs using the Primer3 programhttps://cran.r-project.org/web/packages/ggpubr/index.html). Correlation coefficients and significance tests were performed using the Hmisc and Performance Analytics packages of the R program (https://www.r-project.org/). The definition of significant correlation was an absolute value of correlation coefficients > 0.80 and a P value < 0.01.Violin plots with boxplots of SSR number, SSR density, and the percentage of genes containing SSRs were drawn using the ggviolin function in the ggpubr package of the R program (http://pfam.sanger.ac.uk)73. The Venn diagram was drawn by TBtools74. The functional enrichment analysis of the SSR-related genes compared with the whole-genome genes was conducted using the SciPy package of Python75. Then, R was used to perform Benjamini and Hochberg correction on the P value of significance test, and the parameters for significant functional enrichment terms were defined as q value < 0.05 and fold change ≥ 277.The functional annotation of the genes containing SSRs and all other genes was conducted using the localized Pfam database .Pfam was used to perform a domain search on the amino acid sequences of each species. The genes containing the domains of “Myb_DNA binding” (PF00249), “Myb_DNA-bind_3” (PF12776), “Myb_DNA-bind_4” (PF13837), “Myb_DNA-bind_5” (PF13873), “Myb_DNA-bind_6” (PF13921), and “Myb_DNA-bind_7” (PF15963) were extracted by self-programmed Perl with an 80. FastTree (v2.1.11) software was used to perform phylogenetic analysis using the maximum-likelihood method81. The Jones-Taylor-Thorton model was adopted, and the bootstrap replications were set as 1000. The phylogenetic trees of each Myb gene family were illustrated using the iTOL program to add SSR-related information or gene function67. Gene duplication and gene loss analysis were performed using the Notung2.9 software82.The amino acid sequences of each Myb gene family were aligned using Mafft v7.471 with the maxiterate set as 100083. More importantly, two tools, WSF and BSF, are provided, which were rewritten according to the MISA68. These two tools will greatly facilitate the online or local batch identification of SSRs for users.The PSSRD was constructed by applying various software packages, including MySQL database management, PHP, JavaScript, HTML, and CSS. The collected datasets were processed using Python or Perl, and several bioinformatics programs were used for interpreting biological data analysis and mining. The PSSRD contains several databases that store processed SSR-related data in MySQL. The interactive Web interface was constructed to enable users to conveniently access the PSSRD and obtain information for basic research using any popular browser on their devices. PHP, HTML, and JavaScript were used to transmit query requirements and extract data rapidly from the MySQL database to create report pages. The interactive plotting system was developed using d3.js and nvd3 helper librariesSupplementary Figures 1-7Supplementary tables 1-12


NRDP1 is an E3 ubiquitin ligase that has been shown by our group and others to target ErbB3 for proteasomal degradation in prostate and breast cancer cells and thereby decrease the likelihood cancer progression. Our group has found that NRDP1 can be located in the nucleus as well as the cytoplasm of prostate cancer (CaP) cells, which is unexpected as NRDP1 lacks a nuclear localization signal. Here we elucidate the mechanism by which nuclear translocation of NRDP1 can occur and demonstrate that nuclear NRDP1 retains its ubiquitin ligase activity. Our patient data and cell line studies indicate that increased levels of nuclear NRDP1 contributes CaP progression, thereby underscoring the clinical relevance of our findings and supporting continued investigation and elucidation of the specific role(s) played by NRDP1 in the nucleus of CaP cells.p = 0.007) and that higher levels of nuclear NRDP1 are found in castration resistant cell lines (CWR22Rv1 and PC3) compared to androgen sensitive cell lines (LNCaP and MDA-PCa-3B). The combined data indicate that NRDP1 plays a role in mediating CaP progression and supports further investigation of both the mechanism by which nuclear transport occurs and the identification of specific nuclear targets.To our knowledge, our group is the first to demonstrate that NRDP1 is located in the nucleus as well as the cytoplasm of CaP cells. Subcellular fractionation, immunohistochemistry, and immunofluorescence analysis combined with confocal microscopy were used to validate this finding. Subcellular fractionation followed by western blot analysis revealed a strong association between AR and NRDP1 localization when AR expression and/or cellular localization was manipulated via treatment with R1881, AR-specific siRNA, or enzalutamide. Transfection of LNCaP with various NRDP1 and AR constructs followed by immunoprecipitation confirmed binding of NRDP1 to AR is possible and determined that binding requires the hinge region of AR. Co-transfection with NRDP1 constructs and HA-ubiquitin followed by subcellular fractionation confirmed that nuclear NRDP1 retains its ubiquitin ligase activity. We also show that increased nuclear NRDP1 is associated with PSA recurrence in CaP patients (n = 162, odds ratio; 1.238,  Ubiquitin ligases play a key role in the post-translational regulation of cellular protein levels and their dysregulation has been shown to contribute to the development and/or progression of several cancer types including gliomas and breast and prostate cancers ,2. UbiquOur group has previously demonstrated that NRDP1 can be transcriptionally regulated by AR in CaP cells; activated AR is able to bind to the NRDP1 promoter region and drive NRDP1 expression ,15. ThisThe main goals of the current study were to validate our finding that NRDP1 can be located in the nucleus of CaP cells, to elucidate the mechanism by which nuclear translocation occurs, and to determine whether nuclear NRDP1 retains its ubiquitin ligase activity. We also conducted experiments to determine how nuclear NRDP1 levels are regulated and conducted patient studies to establish whether levels of nuclear NRDP1 in biopsy samples from CaP patients with localized disease are associated with disease progression.All data were collected with approval from the VA Northern California Health Care System (VANCHCS) Institutional Review Board. Sections from formalin fixed paraffin-embedded prostate tumors of 162 patients who underwent prostatectomy at VANCHCS were analyzed for these studies. Patient characteristics are described in Primary antibodies; Androgen receptor , tubulin (cat#9F3), Lamin A/C (cat#2032), and HA-TAG (cat#3724S) primary antibodies , NRDP1 , GAPDH , FLAG . Secondary antibodies; HRP-linked anti-mouse IgG , HRP-linked goat anti-rabbit secondary . siRNA; AR siRNA was a pool of 4 duplexes with the following sequences; #1: 5′-CAGUCCCACUUGUGUCAAATT-3′, #2: 5′-CUGAUCUGUGGAGAUGAATT-3′, #3: 5′-GUCGUCUUCGGAAAUGUUATT-3′, #4: 5′-GACAGUGUCACACAUUGAATT-3′ . Control siRNA was a pool of 4 scrambled non-specific siRNA duplexes . Drugs; R1881 , Enzalutamide, Cycloheximide, MG132 .2 in air.The following CaP cell lines were used; LNCaP, 22Rv1, MDA-PCa-2B and PC3 . LNCaP, 22Rv1, and PC3 were cultured in RPMI1640 media  supplemented with 10% fetal bovine serum , 2 mM L-glutamine, and 100 U/mL penicillin-100 μg/mL streptomycin . MDA-PCa-2B were cultured in F-12K media supplemented with 20% FBS , 2 mM L-glutamine, and 100 U/mL penicillin-100 μg/mL streptomycin , 25 ng/mL cholera toxin, 100 pg/mL hydrocortisone , 10 ng/mL mouse Epidermal Growth Factor, 0.005 mM phosphoethanolamine, 45 nM sodium selenite, and 0.005 mg/mL human recombinant insulin . Cells were kept at 37 °C in a humidified environment of 5% COCells were fixed in ice cold methanol for 10 min then washed with PBST and blocked using 10% BSA in PBST prior to being incubated with primary antibodies overnight at 4 °C. Cells were then washed and incubated with either Alexa Fluor 488 conjugated goat anti-rabbit IgG secondary antibody or Alexa Fluor 555 conjugated goat anti-rabbit IgG secondary antibody  for 1.5 h before being washed again and mounted using Ultra Cruz hard-set mounting medium with DAPI . Representative fluorescence images were taken on a Leica DMR. Confocal images were taken on an Olympus FluoView FV1000 confocal microscope .g for 5 min to isolate the cytoplasmic fraction. The remaining nuclear pellet was washed three times in cytoplasmic lysis buffer before being lysed in 1× SDS sample buffer.Subcellular fractionation was performed as previously described . BrieflyLipofectamine 2000  was used for all transfections as per manufacturer’s instructions. Cells were plated in 100 mm or 150 mm dishes and allowed to attach overnight prior to transfection with siRNA or plasmid constructs. Plasmid constructs; pcDNA3, Wt-NRDP1-FLAG, CSHQ-NRDP1-FLAG, ΔCC-NRDP1-FLAG, Ubiquitin-HA-TAG, Wt-AR, AR-V7 (missing the ligand binding domain), AR-ΔDBD (missing residues 538–614 of the DNA binding domain (‘DBD’)), AR-NTD, pEL 77 AR (missing residues 647–670 of the hinge domain (‘Hinge 1’)), and AR w/o (missing residues 628–646 of the hinge domain). Cells were transfected with a total of 3.0 µg of plasmid per 100 mm or 150 mm dish. Wt-NRDP1-FLAG, CSHQ-NRDP1-FLAG  in the receptor binding region (RING finger domain), ΔCC-NRDP1-FLAG (missing the coiled coil domain), and Ubiquitin-HA-TAG were kindly provided by Dr. Kermit Carraway III. AR-V7 was kindly provided by Dr. Allen Gao. Wt-AR, AR-ΔDBD, and AR-ΔNTD were from Addgene .Protein extraction and western blot analyses were performed as previously described . BrieflyCells were plated in 100 mm or 150 mm dishes and lysed in ice cold IP lysis buffer . Protein was quantified with BCA protein assay . One milligram of protein was incubated with 4 ug of each primary antibody overnight at 4 °C followed by incubation with protein A agarose beads  overnight at 4 °C. The complex was pelleted and washed three to five times with IP lysis buffer and then eluted with SDS-sample buffer with BME and run on SDS-PAGE gels.Cell line data; at least three independent experiments were completed for each analysis described in this article. Patient data; correlations between markers were calculated using the Spearman correlation. Recurrence-free percentages at five years for low and high marker expression were calculated from Kaplan-Meier curves. The association between marker expression and PSA failure was analyzed using logistic regression models. Analyses of patient data were conducted using R version 3.6.0 (accessed on 24 April 2019).We previously demonstrated androgen receptor (AR) regulation of NRDP1 in hormone-naïve CaP , and thaTo determine whether NRDP1 is also expressed in the nuclei of castration resistant CaP (CRPC), we broadened our investigation to two CRPC cell lines-PC3 (AR null), and CWR22Rv1 . The presence of NRDP1 in the nucleus of all four CaP cells was validated by subcellular fractionation studies , which rp = 0.007 (p = 0.003), demonstrating that higher nuclear NRDP1 levels predict worse outcome  and 0.51 (<0.001), respectively. No associations were found between nuclear NRDP1 and Ki67 indicating that nuclear NRDP1 does not directly contribute to increased proliferation of CaP patient tumor cells.Dysregulation of AR, including by mutation and expression of splice variants, is well known to drive CaP progression ,21. The p < 0.001) and −0.35 (p = 0.003), respectively. Association between nuclear AR and nuclear NRDP1 was not statistically significant, possibly due to NRDP-1-mediated degradation of nuclear Nrdp1. In support of this, ubiquitination of AR by other E3 ubiquitin ligases has previously been reported [Correlation analysis revealed a strong negative association between levels of cytoplasmic AR and levels of nuclear NRDP1 in CaP patient samples . In patireported ,28. A nereported ,30 meaniSince NRDP1 does not contain a nuclear translocation signal, its transport into the nucleus must be dependent on another molecule(s). As AR activity correlated with NRDP1 nuclear localization in the primary tumors, we focused on determining whether the AR could play a role in nuclear transport of NRDP1. Binding of androgen to the AR promotes the transport of AR into the nucleus  and the NRDP1 is an E3 ubiquitin ligase which can auto-ubiquitinate as well as ubiquitinate several target molecules including ErbB3 ,33. The We demonstrate that all three NRDP1 constructs can translocate to the nucleus in LNCaP cells . It is nImmunoprecipitation studies were also conducted using the CHSQ construct and various AR constructs to determine which region of AR is required for the NRDP1-AR interaction in LNCaP cells. AR has four major domains A: The N-To determine if NRDP1 retains its ubiquitin ligase activity in the nucleus, LNCaP cells were co-transfected with wildtype NRDP1, NRDP1-CSHQ, or the NRDP1-ΔCC constructs and HA-tagged ubiquitin (HA-Ub) and separated into nuclear and cytoplasmic fractions . As woulde novo protein synthesis. Half-life of endogenous cytosolic and nuclear NRDP1 in these cells was calculated based on the changing levels of the protein over time following cycloheximide treatment  and therefore must be dependent on another molecule for entry into the nucleus. Our patient and in vitro data indicate that the AR plays a key role in mediating NRDP1 nuclear translocation; a statistically significant correlation between AR and NRDP1 localization was found in patient biopsy samples, and our in vitro studies demonstrate that AR can bind to NRDP1 and that manipulation of AR expression and activity can impact NRDP1 cellular localization. In further support of AR playing a role, AR has been shown to mediate the nuclear transport of other molecules which lack a nuclear transport signal, for example beta-catenin . Beta-caOur finding that NRDP1 can act as an E3 ubiquitin ligase within the nucleus is somewhat expected based on the fact that many other types of nuclear ubiquitin ligases play a key role in the regulation of nuclear protein levels . For exaIn our previous studies, we found an association between overall levels of Nrdp1 and levels of ErbB3; decreased expression of total levels of Nrdp1 resulted in increased levels of ErbB3 and increased CaP cell proliferation . We now Our cell line data indicate that NRDP1 levels are regulated by proteasomal degradation in some but not all CaP cell lines. We also found a difference between the half-life of cytoplasmic and nuclear NRDP1 with the latter being much longer. In addition to identifying the targets of nuclear NRDP1 and determining the precise mechanism by which NRDP1 nuclear translocation occurs in CaP cells, we also plan to further elucidate the mechanisms by which nuclear NRDP1 levels are regulated. While the degree of nuclear translocation will contribute to this, we hypothesize that molecules such as USP8 and BRUCE also play a role. It is noteworthy that BRUCE plays a key role in autophagy regulation and as such can direct degradation of NRDP1 via lysosomes ,51. ThisThe combined data support a role for nuclear NRDP1 in mediating CaP progression. Further understanding of the mechanism by which nuclear translocation occurs and how nuclear NRDP1 levels are regulated as well as identification of targets of nuclear NRDP1 could improve our understanding of CaP pathogenesis and support the development of drugs for the treatment of CaP and other cancers and disease states for which dysregulation of NRDP1 plays a role.