Prostate cancer is the most common cancer and the second most common cause of cancer death in men (Siegel et al., 2021), and there continues to be a pressing need for new diagnostic and therapeutic approaches for this disease, as well as better prognostic biomarkers to guide treatment. Long non-coding RNA (lncRNA) species are increasingly recognized as having regulatory functions in tumorigenesis, and nucleic acid-based therapeutics are being developed as a promising means of targeting pathogenic lncRNAs (Arun et al., 2018). Several lncRNAs have recently been found to associate with prostate cancer, and the best known of these, prostate cancer associated 3 (PCA3; formerly prostate cancer antigen 3) has been used clinically for many years as the most specific diagnostic biomarker for prostate cancer (Bussemakers et al., 1999; de Kok et al., 2002); however, its prognostic significance remains uncertain. Strikingly, PCA3 emerged first only in mammals, with further evolution in primates (Clarke et al., 2009), and, given aspects of the sequence and genomic organization, we have hypothesized that it might have been introduced into the genome by an ancient oncogenic virus (Teixeira et al., 2017). In humans, PCA3 has an unusual genomic organization, being present in an antisense direction within an intron of the protein-coding gene PRUNE2. Somewhat surprisingly for a molecule that is well established as a Food and Drug Administration (FDA)- and European Medical Agency (EMA)-approved biomarker, relatively little was known about the biological function of PCA3 until recently. Ferreira et al., 2012, showed that PCA3 is androgen-regulated and that it promotes prostate cancer cell survival. Subsequently, we have established that PCA3 downregulates the expression of PRUNE2 in a rather unusual way: at the RNA level by RNA editing mediated via adenosine deaminase RNA-specific family members (Salameh et al., 2015). We have shown that expressing ectopic PCA3 or, alternatively, silencing PRUNE2 induced cell transformation and cell proliferation in vitro, increased adhesion and migration of prostate cancer cells, and yielded larger tumors in xenograft tumor models. The opposite biological effects were seen with PCA3 silencing or ectopic PRUNE2 expression (Salameh et al., 2015). Preliminary studies of human prostate cancer samples compared to normal prostate showed increased PCA3 expression, decreased PRUNE2 expression, and evidence for RNA editing of these genes. Based on these experimental findings, we proposed that there is a functional molecular axis in human prostate cancer in which PCA3 acts as a transdominant-negative oncogene to downregulate a previously unrecognized tumor suppressor gene, PRUNE2 (Salameh et al., 2015).

Here, we propose that this molecular interplay may serve as a translational target for diagnostic and/or therapeutic intervention in human prostate cancer. First, we present additional correlative evidence from two retrospective post-surgical primary prostate cancer cohorts in support of our experimental model of PCA3 as a dominant-negative oncogene and PRUNE2 as a tumor suppressor gene and for their co-regulation in human prostate cancer. Moreover, we examine the dysregulation of the PCA3/PRUNE2 regulatory axis across tumors of different grades (patterns), stages, and groups (Gordetsky and Epstein, 2016; van Leenders et al., 2020). Finally, we assess whether tumor expression levels of PCA3 and/or PRUNE2 are prognostic of biochemical disease recurrence after surgery.

Here, we assessed the tumor and control adjacent normal prostatic glandular tissue expression of the lncRNA PCA3 and the protein-coding PRUNE2 gene in two independent retrospective cohorts of patients with primary organ-confined prostate cancer after treatment by radical prostatectomy (Figure 4). As compared with normal prostate, we found that prostate cancer showed consistent increased expression of PCA3 and consistent decreased expression of PRUNE2 in tumors across a broad range of pathological attributes (i.e., Gleason grades, scores, groups, and stages) in both patient cohorts. Although the magnitude of the change of expression between normal and tumor appears greater for PCA3 than for PRUNE2 in both cohorts (Figure 1A and Figure 3A), we attribute this to the reciprocal nature of the comparison, in conjunction with the very low level of normal prostatic PCA3 expression as compared with the higher expression of PRUNE2 in normal prostate. Overall, the findings support the mechanistic role of a tumor-specific molecular axis in which PCA3 acts as dominant-negative oncogene and PRUNE2 as a tumor suppressor gene in human prostate cancer and indicate that the interplay between these genes is dysregulated early in prostate cancer.

Figure 4 with 1 supplement see all

Download asset Open asset

Specifically, when we compared PCA3 expression in the validation cohort from TCGA, although average expression in all grades, stages, and groups was higher than in normal prostate, we found that among tumors there was significantly decreased PCA3 expression in tumors with higher grades (Gleason Score >7) and in higher stages (>pT2), as compared with lower grades, stages, or groups, respectively. These paradoxical findings are consistent with several early studies (Salagierski et al., 2010; Balcerczak et al., 2003) and in particular with a recent tissue-based study of PCA3 expression in prostate cancer (Alshalalfa et al., 2017). In that large cohort study, lower levels of tumor PCA3 in both biopsy and radical prostatectomy specimens were associated with high-grade tumors, and in radical prostatectomy specimens decreased PCA3 expression was associated with features of higher stages. Based on these results, it has been proposed that PCA3 might actually represent a differentiation marker in human prostate cancer (Alshalalfa et al., 2017). The finding of decreasing PCA3 expression with increasing tumor grades and stages in both our study and others is broadly consistent with another previous study (Reis et al., 2004), which found that the class of antisense intronic RNAs was markedly over-represented among the top transcripts associated with tumor differentiation in human prostate cancer. The finding of an inverse association between PCA3 expression and increasing grades and stages may also relate to links between PCA3 expression and androgen receptor (AR) signaling and the likelihood of PCA3 having an important role in the early steps of prostate cancer carcinogenesis, with a reduced role when the disease is more advanced. Indeed, previous work by our own group and by others indicates that PCA3 is upregulated by AR signaling (Teixeira et al., 2017; Ferreira et al., 2012; Salameh et al., 2015), and that PCA3 is also involved in modulating AR signaling (Ferreira et al., 2012; Lemos et al., 2016). Interestingly, it has also been shown in vitro that PCA3 silencing sensitizes prostate cancer cells to enzalutamide-induced decreased cell growth (Özgür et al., 2017). Alshalalfa et al., 2017, suggest that because low pretreatment serum testosterone levels are associated with diseases with higher grades and stages, and because of the relationship between AR signaling and PCA3 expression, therefore lower PCA3 expression may reflect the lower serum testosterone in these patients. However, we do not have any data on the pretreatment serum concentration of testosterone and other androgens, and we are not able to test that hypothesis in this study.

Because prostate cancers, especially Gleason Score 7 (Grade Groups 2 and 3) tumors, are quite frequent (about half of the total cases) and show divergent clinical behavior, there is great interest in developing prognostic biomarkers for risk stratification. Studies on the association of PCA3 expression levels with outcome and prognosis show conflicting results (Loeb and Partin, 2011), and unlike this present study, most prior reports are based on urinary PCA3 expression (Loeb et al., 2015; Lemos et al., 2019; Fenstermaker et al., 2017). Our exploration of the validation cohort from TCGA, which comprised a wide spectrum of tumor grades and stages, revealed an association between lower levels of tumor PCA3 expression and biochemical recurrence; however, this association was not found after taking grade and stage into account. This finding makes sense, as increasing grade and stage are both variables that are associated with lower PCA3 expression. In their tissue-based cohort, Alshalalfa et al., 2017, also found an association between low PCA3 levels and adverse outcomes, including biochemical recurrence, metastasis, and prostate cancer-specific mortality; however, it is not clear whether such findings are independent of clinical and pathological variables (such as Gleason grade, stage, and group), as a multivariable analysis was not reported. Nevertheless, the demonstration of an (unadjusted) association between PCA3 levels and outcome may have potential relevance in the liquid biopsy setting. For the discovery cohort of patients, we selected organ-confined, intermediate-risk tumors (Gleason Grade Groups 2 and 3, with tumor stages pT2 and pT3) where prognostic information might be expected to be most helpful clinically, to test for an association with outcome. We did not see any association between tumor PCA3 expression and biochemical recurrence in this particular grade and stage setting.

PRUNE2, a human homolog of the Drosophila prune gene, encodes for a protein with BCH, DHHA2, and PPX1 functional domains (Ferreira et al., 2012). The BCH domain can inhibit the Rho family of proteins, small GTPases with roles in cell transformation, migration and metastasis, and cell cycle progression (Clarke et al., 2009; Iwama et al., 2011). Evidence is accumulating that PRUNE2 might act as a tumor suppressor gene. Loss-of-function mutations have been described in several tumor types, including germline and somatic mutations in parathyroid cancer (Yu et al., 2015) and somatic mutations in solid papillary carcinoma (Alsadoun et al., 2018), while high expression of PRUNE2 protein correlates with favorable prognosis in neuroblastoma (Machida et al., 2006). Others have shown evidence of inactivating PRUNE2 mutations in Merkel cell carcinoma (Harms et al., 2015) and that the restoration of downregulated PRUNE2 in oral cancer suppresses tumor cell migration (Su et al., 2021), further supporting the role of PRUNE2 as a tumor suppressor. In prostate cancer, the evidence is limited and controversial: an early report found that PRUNE2 expression was upregulated in prostate cancer and metastases in a small number of samples, and was androgen-inducible in prostate cancer cells (Clarke et al., 2009). However, a subsequent study on a larger number of samples found that PRUNE2 expression either decreased or did not increase in aggressive prostate cancer, and that PRUNE2 expression was not androgen-inducible (Salagierski et al., 2010). While this work was under external peer-review, Cardoso et al. have shown that PRUNE2 is a prostate cancer predisposition gene, which is consistent with our results and interpretations (Cardoso et al., 2022).

Altogether, the findings in the current study provide additional support for our previous findings (Salameh et al., 2015) that PRUNE2 acts as a functional tumor suppressor gene in human prostate cancer. Here, we described consistently lower expression of PRUNE2 in prostate cancers of all grades and stages as compared to normal prostate. The findings in our present study are also consistent with the negative regulation of PRUNE2 by PCA3 in prostate cancer. We found no significant differences in PRUNE2 expression across tumor stage, and only a small decrease in expression with increasing tumor grade, suggesting that loss of PRUNE2 tumor suppressor activity is an early molecular event in prostate cancer. We are not aware of any prior reports of the prognostic significance of tumor PRUNE2 expression in prostate cancer but, at least in this retrospective study of two independent prostate cancer patient cohorts, we did not find any association between PRUNE2 expression and biochemical outcomes.

Strengths of this study include that broadly consistent findings were described in the two independent well-characterized clinically annotated primary prostate cancer cohorts used for analysis, and that the findings were robust across multiple assays in the discovery patient cohort and between the different methods of measurement of gene expression used in the two cohorts. The assessment of PCA3 expression directly and specifically in tissue (as opposed to urine) is a novelty and a strength as our primary goal was the study of the PRUNE2/PCA3 regulatory axis in human prostate cancer. We reasoned that the study of tissue expression is likely more informative of tumor biology than traditional urinalysis, not least of all because urinary expression, though very well characterized, could by subject to potential confounding issues such as RNA stability in urine or the contribution of differential urinary shedding. However, from the standpoint of assessment of prognostic information, a drawback of analyzing tissue PCA3 expression is that the results are not directly comparable to the multiple previous studies that measured urinary PCA3 scores and ultimately led to FDA and EMA approval for clinical applications in the US and EU. Moreover, while we did find consistent findings with a large tissue cohort study relating PCA3 expression and biochemical recurrence (Alshalalfa et al., 2017), the analysis presented here was limited in its ability to unequivocally determine the prognostic value of PCA3 and PRUNE2 expression as the overall proportion of patients with biochemical recurrences was relatively low. Finally, we were not able to fully address the relationship of reciprocal gene expression of PCA3 and PRUNE2 to the outcomes of metastases and prostate cancer-specific deaths, again due to the relative paucity of these events.

In conclusion, we found consistent upregulation of PCA3 and downregulation of PRUNE2 in prostate cancer as compared with normal prostate in two retrospective and independent patient cohorts (summarized in Figure 4, Figure 4—figure supplement 1), supporting that PCA3 and PRUNE2 function as an oncogene and a tumor suppressor gene, respectively, in human prostate cancer. The inverse correlation of PCA3 and PRUNE2 expression is consistent with our prior findings of a functional interplay between the two genes as part of a unique regulatory unit functioning at a single genetic locus in prostate cancer cells with PCA3 negatively downregulating PRUNE2 expression (Salameh et al., 2015). The mechanistic dysregulation of PCA3 and PRUNE2 is observed across the spectrum of tumor grades and stages, suggesting that this is an early and stable molecular event in prostate cancer. On the other hand, we have not detected any regulatory effects of PRUNE2/PCA3 in late genetic events such as prostate cancer progressing to biochemical recurrence, which includes the development of local tumor recurrence and/or the development of metastatic disease. The findings presented here represent additional evidence for the functional reciprocal co-regulation of PCA3 and PRUNE2 in the setting of early tumorigenesis but not in late events in human prostate cancer. Taken together along with the well-documented specificity of PCA3 overexpression, our findings establish the PCA3/PRUNE2 regulatory axis as an attractive early molecular target candidate for intervention in the therapy of human prostate cancer.

For the discovery cohort, all data generated or analyzed are included in the manuscript and source data files, except for patient-level ethnicity data. Patient-level ethnicity data is not included due to the potential for identifiability. However detailed summary ethnicity data is presented in the manuscript and in Table 1. Requests to access the patient level ethnicity data should be directed to the corresponding author with a project proposal. Source codes are also available in the supplemental source code file. For the Validation Cohort, clinicopathological patient characteristics and gene level transcription data from The Cancer Genome Atlas (TCGA) were accessed from the UCSC Xena Resource.

1. 1. University of North Carolina TCGA genome characterization center

   (2017) TCGA Prostate Cancer (PRAD) TCGA.PRAD.sampleMap/HiSeqV2

   ID 20,531. TCGA prostate adenocarcinoma (PRAD) gene expression by RNAseq (polyA+ IlluminaHiSeq).

   https://xenabrowser.net/datapages/?dataset=TCGA.PRAD.sampleMap%2FHiSeqV2&host=https%3A%2F%2Ftcga.xenahubs.net&removeHub=https%3A%2F%2Fxena.treehouse.gi.ucsc.edu%3A443

1. 1. Alsadoun N
   2. MacGrogan G
   3. Truntzer C
   4. Lacroix-Triki M
   5. Bedgedjian I
   6. Koeb M-H
   7. El Alam E
   8. Medioni D
   9. Parent M
   10. Wuithier P
   11. Robert I
   12. Boidot R
   13. Arnould L

   (2018) Solid papillary carcinoma with reverse polarity of the breast harbors specific morphologic, immunohistochemical and molecular profile in comparison with other benign or malignant papillary lesions of the breast: a comparative study of 9 additional cases

   Modern Pathology 31:1367–1380.

   https://doi.org/10.1038/s41379-018-0047-1

   • PubMed
   • Google Scholar
2. 1. Alshalalfa M
   2. Verhaegh GW
   3. Gibb EA
   4. Santiago-Jiménez M
   5. Erho N
   6. Jordan J
   7. Yousefi K
   8. Lam LLC
   9. Kolisnik T
   10. Chelissery J
   11. Seiler R
   12. Ross AE
   13. Karnes RJ
   14. Schaeffer EM
   15. Lotan TT
   16. Den RB
   17. Freedland SJ
   18. Davicioni E
   19. Klein EA
   20. Schalken JA

   (2017) Low PCA3 expression is a marker of poor differentiation in localized prostate tumors: exploratory analysis from 12,076 patients

   Oncotarget 8:50804–50813.

   https://doi.org/10.18632/oncotarget.15133

   • PubMed
   • Google Scholar
3. 1. Arun G
   2. Diermeier SD
   3. Spector DL

   (2018) Therapeutic targeting of long non-coding rnas in cancer

   Trends in Molecular Medicine 24:257–277.

   https://doi.org/10.1016/j.molmed.2018.01.001

   • PubMed
   • Google Scholar
4. 1. Balcerczak E
   2. Mirowski M
   3. Sasor A
   4. Wierzbicki R

   (2003)

   Expression of p65, DD3 and c-erbb2 genes in prostate cancer

   Neoplasma 50:97–101.

   • PubMed
   • Google Scholar
5. 1. Bussemakers MJ
   2. van Bokhoven A
   3. Verhaegh GW
   4. Smit FP
   5. Karthaus HF
   6. Schalken JA
   7. Debruyne FM
   8. Ru N
   9. Isaacs WB

   (1999)

   DD3: a new prostate-specific gene, highly overexpressed in prostate cancer

   Cancer Research 59:5975–5979.

   • PubMed
   • Google Scholar
6. 1. Cancer Genome Atlas Research Network

   (2015) The molecular taxonomy of primary prostate cancer

   Cell 163:1011–1025.

   https://doi.org/10.1016/j.cell.2015.10.025

   • PubMed
   • Google Scholar
7. 1. Cardoso M
   2. Maia S
   3. Brandão A
   4. Sahasrabudhe R
   5. Lott P
   6. Belter N
   7. Carvajal-Carmona LG
   8. Paulo P
   9. Teixeira MR

   (2022) Exome sequencing of affected duos and trios uncovers PRUNE2 as a novel prostate cancer predisposition gene

   British Journal of Cancer.

   https://doi.org/10.1038/s41416-022-02125-6

   • PubMed
   • Google Scholar
8. 1. Clarke RA
   2. Zhao Z
   3. Guo AY
   4. Roper K
   5. Teng L
   6. Fang ZM
   7. Samaratunga H
   8. Lavin MF
   9. Gardiner RA

   (2009) New genomic structure for prostate cancer specific gene PCA3 within BMCC1: implications for prostate cancer detection and progression

   PLOS ONE 4:e4995.

   https://doi.org/10.1371/journal.pone.0004995

   • PubMed
   • Google Scholar
9. 1. de Kok JB
   2. Verhaegh GW
   3. Roelofs RW
   4. Hessels D
   5. Kiemeney LA
   6. Aalders TW
   7. Swinkels DW
   8. Schalken JA

   (2002) DD3(PCA3), a very sensitive and specific marker to detect prostate tumors

   Cancer Research 62:2695–2698.

   https://doi.org/10.1016/S1569-9056(02)80019-7

   • PubMed
   • Google Scholar
10. 1. Fenstermaker M
    2. Mendhiratta N
    3. Bjurlin MA
    4. Meng X
    5. Rosenkrantz AB
    6. Huang R
    7. Deng F-M
    8. Zhou M
    9. Huang WC
    10. Lepor H
    11. Taneja SS

    (2017) Risk stratification by urinary prostate cancer gene 3 testing before magnetic resonance imaging-ultrasound fusion-targeted prostate biopsy among men with no history of biopsy

    Urology 99:174–179.

    https://doi.org/10.1016/j.urology.2016.08.022

    • PubMed
    • Google Scholar
11. 1. Ferreira LB
    2. Palumbo A
    3. de Mello KD
    4. Sternberg C
    5. Caetano MS
    6. de Oliveira FL
    7. Neves AF
    8. Nasciutti LE
    9. Goulart LR
    10. Gimba ERP

    (2012) PCA3 noncoding RNA is involved in the control of prostate-cancer cell survival and modulates androgen receptor signaling

    BMC Cancer 12:507.

    https://doi.org/10.1186/1471-2407-12-507

    • PubMed
    • Google Scholar
12. 1. Goldman MJ
    2. Craft B
    3. Hastie M
    4. Repečka K
    5. McDade F
    6. Kamath A
    7. Banerjee A
    8. Luo Y
    9. Rogers D
    10. Brooks AN
    11. Zhu J
    12. Haussler D

    (2020) Visualizing and interpreting cancer genomics data via the xena platform

    Nature Biotechnology 38:675–678.

    https://doi.org/10.1038/s41587-020-0546-8

    • PubMed
    • Google Scholar
13. 1. Gordetsky J
    2. Epstein J

    (2016) Grading of prostatic adenocarcinoma: current state and prognostic implications

    Diagnostic Pathology 11:25.

    https://doi.org/10.1186/s13000-016-0478-2

    • PubMed
    • Google Scholar
14. 1. Harms PW
    2. Vats P
    3. Verhaegen ME
    4. Robinson DR
    5. Wu Y-M
    6. Dhanasekaran SM
    7. Palanisamy N
    8. Siddiqui J
    9. Cao X
    10. Su F
    11. Wang R
    12. Xiao H
    13. Kunju LP
    14. Mehra R
    15. Tomlins SA
    16. Fullen DR
    17. Bichakjian CK
    18. Johnson TM
    19. Dlugosz AA
    20. Chinnaiyan AM

    (2015) The distinctive mutational spectra of polyomavirus-negative merkel cell carcinoma

    Cancer Research 75:3720–3727.

    https://doi.org/10.1158/0008-5472.CAN-15-0702

    • PubMed
    • Google Scholar
15. 1. Iwama E
    2. Tsuchimoto D
    3. Iyama T
    4. Sakumi K
    5. Nakagawara A
    6. Takayama K
    7. Nakanishi Y
    8. Nakabeppu Y

    (2011) Cancer-related PRUNE2 protein is associated with nucleotides and is highly expressed in mature nerve tissues

    Journal of Molecular Neuroscience 44:103–114.

    https://doi.org/10.1007/s12031-010-9490-2

    • PubMed
    • Google Scholar
16. 1. Lemos AEG
    2. Ferreira LB
    3. Batoreu NM
    4. de Freitas PP
    5. Bonamino MH
    6. Gimba ERP

    (2016) PCA3 long noncoding RNA modulates the expression of key cancer-related genes in lncap prostate cancer cells

    Tumour Biology 37:11339–11348.

    https://doi.org/10.1007/s13277-016-5012-3

    • PubMed
    • Google Scholar
17. 1. Lemos AEG
    2. Matos A
    3. Ferreira LB
    4. Gimba ERP

    (2019) The long non-coding RNA pca3: an update of its functions and clinical applications as a biomarker in prostate cancer

    Oncotarget 10:6589–6603.

    https://doi.org/10.18632/oncotarget.27284

    • PubMed
    • Google Scholar
18. 1. Li B
    2. Dewey CN

    (2011) RSEM: accurate transcript quantification from RNA-seq data with or without a reference genome

    BMC Bioinformatics 12:323.

    https://doi.org/10.1186/1471-2105-12-323

    • PubMed
    • Google Scholar
19. 1. Livak KJ
    2. Schmittgen TD

    (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(-delta delta C(T)) method

    Methods 25:402–408.

    https://doi.org/10.1006/meth.2001.1262

    • PubMed
    • Google Scholar
20. 1. Loeb S
    2. Partin AW

    (2011)

    Review of the literature: PCA3 for prostate cancer risk assessment and prognostication

    Reviews in Urology 13:e191-5.

    • PubMed
    • Google Scholar
21. 1. Loeb S
    2. Bruinsma SM
    3. Nicholson J
    4. Briganti A
    5. Pickles T
    6. Kakehi Y
    7. Carlsson SV
    8. Roobol MJ

    (2015) Active surveillance for prostate cancer: a systematic review of clinicopathologic variables and biomarkers for risk stratification

    European Urology 67:619–626.

    https://doi.org/10.1016/j.eururo.2014.10.010

    • PubMed
    • Google Scholar
22. 1. Machida T
    2. Fujita T
    3. Ooo ML
    4. Ohira M
    5. Isogai E
    6. Mihara M
    7. Hirato J
    8. Tomotsune D
    9. Hirata T
    10. Fujimori M
    11. Adachi W
    12. Nakagawara A

    (2006) Increased expression of proapoptotic BMCC1, a novel gene with the BNIP2 and cdc42gap homology (BCH) domain, is associated with favorable prognosis in human neuroblastomas

    Oncogene 25:1931–1942.

    https://doi.org/10.1038/sj.onc.1209225

    • PubMed
    • Google Scholar
23. 1. Özgür E
    2. Celik AI
    3. Darendeliler E
    4. Gezer U

    (2017) PCA3 silencing sensitizes prostate cancer cells to enzalutamide-mediated androgen receptor blockade

    Anticancer Research 37:3631–3637.

    https://doi.org/10.21873/anticanres.11733

    • PubMed
    • Google Scholar
24. 1. Reis EM
    2. Nakaya HI
    3. Louro R
    4. Canavez FC
    5. Flatschart AVF
    6. Almeida GT
    7. Egidio CM
    8. Paquola AC
    9. Machado AA
    10. Festa F
    11. Yamamoto D
    12. Alvarenga R
    13. da Silva CC
    14. Brito GC
    15. Simon SD
    16. Moreira-Filho CA
    17. Leite KR
    18. Camara-Lopes LH
    19. Campos FS
    20. Gimba E
    21. Vignal GM
    22. El-Dorry H
    23. Sogayar MC
    24. Barcinski MA
    25. da Silva AM
    26. Verjovski-Almeida S

    (2004) Antisense intronic non-coding RNA levels correlate to the degree of tumor differentiation in prostate cancer

    Oncogene 23:6684–6692.

    https://doi.org/10.1038/sj.onc.1207880

    • PubMed
    • Google Scholar
25. 1. Salagierski M
    2. Verhaegh GW
    3. Jannink SA
    4. Smit FP
    5. Hessels D
    6. Schalken JA

    (2010) Differential expression of PCA3 and its overlapping PRUNE2 transcript in prostate cancer

    The Prostate 70:70–78.

    https://doi.org/10.1002/pros.21040

    • PubMed
    • Google Scholar
26. 1. Salameh A
    2. Lee AK
    3. Cardó-Vila M
    4. Nunes DN
    5. Efstathiou E
    6. Staquicini FI
    7. Dobroff AS
    8. Marchiò S
    9. Navone NM
    10. Hosoya H
    11. Lauer RC
    12. Wen S
    13. Salmeron CC
    14. Hoang A
    15. Newsham I
    16. Lima LA
    17. Carraro DM
    18. Oliviero S
    19. Kolonin MG
    20. Sidman RL
    21. Do KA
    22. Troncoso P
    23. Logothetis CJ
    24. Brentani RR
    25. Calin GA
    26. Cavenee WK
    27. Dias-Neto E
    28. Pasqualini R
    29. Arap W

    (2015) PRUNE2 is a human prostate cancer suppressor regulated by the intronic long noncoding RNA PCA3

    PNAS 112:8403–8408.

    https://doi.org/10.1073/pnas.1507882112

    • PubMed
    • Google Scholar
27. 1. Siegel RL
    2. Miller KD
    3. Fuchs HE
    4. Jemal A

    (2021) CA cancer

    Jornal Dos Clinicos 71:7–33.

    https://doi.org/10.3322/caac.21654

    • PubMed
    • Google Scholar
28. 1. Su SC
    2. Yeh CM
    3. Lin CW
    4. Hsieh YH
    5. Chuang CY
    6. Tang CH
    7. Lee YC
    8. Yang SF

    (2021) A novel melatonin-regulated lncrna suppresses TPA-induced oral cancer cell motility through replenishing PRUNE2 expression

    Journal of Pineal Research 71:e12760.

    https://doi.org/10.1111/jpi.12760

    • PubMed
    • Google Scholar
29. 1. Teixeira AA
    2. Marchiò S
    3. Dias-Neto E
    4. Nunes DN
    5. da Silva IT
    6. Chackerian B
    7. Barry M
    8. Lauer RC
    9. Giordano RJ
    10. Sidman RL
    11. Wheeler CM
    12. Cavenee WK
    13. Pasqualini R
    14. Arap W

    (2017) Going viral? linking the etiology of human prostate cancer to the pca3 long noncoding RNA and oncogenic viruses

    EMBO Molecular Medicine 9:1327–1330.

    https://doi.org/10.15252/emmm.201708072

    • PubMed
    • Google Scholar
30. Website

    1. University of North Carolina TCGA Genome Characterization Center

    (2017) TCGA prostate adenocarcinoma (PRAD) gene expression by rnaseq (polya+ illuminahiseq)

    Accessed May 19, 2019.

    https://xenabrowser.net/datapages/?dataset=TCGA.PRAD.sampleMap%2FHiSeqV2&host=https%3A%2F%2Ftcga.xenahubs.net&removeHub=https%3A%2F%2Fxena.treehouse.gi.ucsc.edu%3A443
31. 1. Vandesompele J
    2. De Preter K
    3. Pattyn F
    4. Poppe B
    5. Van Roy N
    6. De Paepe A
    7. Speleman F

    (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes

    Genome Biology 3:RESEARCH0034.

    https://doi.org/10.1186/gb-2002-3-7-research0034

    • PubMed
    • Google Scholar
32. 1. van Leenders GJLH
    2. van der Kwast TH
    3. Grignon DJ
    4. Evans AJ
    5. Kristiansen G
    6. Kweldam CF
    7. Litjens G
    8. McKenney JK
    9. Melamed J
    10. Mottet N
    11. Paner GP
    12. Samaratunga H
    13. Schoots IG
    14. Simko JP
    15. Tsuzuki T
    16. Varma M
    17. Warren AY
    18. Wheeler TM
    19. Williamson SR
    20. Iczkowski KA
    21. ISUP Grading Workshop Panel Members

    (2020) The 2019 international society of urological pathology (ISUP) consensus conference on grading of prostatic carcinoma

    The American Journal of Surgical Pathology 44:e87–e99.

    https://doi.org/10.1097/PAS.0000000000001497

    • PubMed
    • Google Scholar
33. 1. Yu W
    2. McPherson JR
    3. Stevenson M
    4. van Eijk R
    5. Heng HL
    6. Newey P
    7. Gan A
    8. Ruano D
    9. Huang D
    10. Poon SL
    11. Ong CK
    12. van Wezel T
    13. Cavaco B
    14. Rozen SG
    15. Tan P
    16. Teh BT
    17. Thakker RV
    18. Morreau H

    (2015) Whole-exome sequencing studies of parathyroid carcinomas reveal novel PRUNE2 mutations, distinctive mutational spectra related to APOBEC-catalyzed DNA mutagenesis and mutational enrichment in kinases associated with cell migration and invasion

    The Journal of Clinical Endocrinology and Metabolism 100:E360–E364.

    https://doi.org/10.1210/jc.2014-3238

    • PubMed
    • Google Scholar

Author details

1. Richard C Lauer

   1. University of New Mexico Comprehensive Cancer Center, Albuquerque, New Mexico, United States
   2. Division of Hematology/Oncology, Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, New Mexico, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Writing – original draft

   Contributed equally with

   Marc Barry

   Competing interests

   No competing interests declared

2. Marc Barry

   Department of Pathology, University of Utah, Salt Lake City, Utah, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Supervision, Investigation, Writing – original draft

   Contributed equally with

   Richard C Lauer

   Competing interests

   No competing interests declared

3. Tracey L Smith

   1. Rutgers Cancer Institute of New Jersey, Newark, New Jersey, United States
   2. Division of Cancer Biology, Department of Radiation Oncology, Rutgers New Jersey Medical School, Newark, New Jersey, United States

   Contribution

   Data curation, Formal analysis, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

4. Andrew Maltez Thomas

   Department of Biochemistry, Institute of Chemistry, University of São Paulo, São Paulo, Brazil

   Contribution

   Data curation, Formal analysis, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-5789-3354

5. Jin Wu

   1. University of New Mexico Comprehensive Cancer Center, Albuquerque, New Mexico, United States
   2. Department of Pathology, University of New Mexico, Albuquerque, New Mexico, United States

   Contribution

   Data curation, Formal analysis, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

6. Ruofei Du

   Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States

   Contribution

   Data curation, Formal analysis, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

7. Ji-Hyun Lee

   1. Department of Biostatistics, University of Florida, Gainesville, Florida, United States
   2. Division of Quantitative Sciences, University of Florida Health Cancer Center, Gainesville, Florida, United States

   Contribution

   Data curation, Formal analysis, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-6420-5150

8. Arpit Rao

   Section of Hematology and Oncology, Department of Medicine, Baylor College of Medicine, Houston, Texas, United States

   Contribution

   Data curation, Formal analysis, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

9. Andrey S Dobroff

   1. University of New Mexico Comprehensive Cancer Center, Albuquerque, New Mexico, United States
   2. Division of Molecular Medicine, Department of Medicine, Albuquerque, United States

   Contribution

   Data curation, Formal analysis, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

10. Marco A Arap

    1. Division of Urology, University of São Paulo Medical School, São Paulo, Brazil
    2. Syrian-Lebanese Hospital, São Paulo, Brazil

    Contribution

    Data curation, Formal analysis, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

11. Diana N Nunes

    Laboratory of Medical Genomics, A.C. Camargo Cancer Center, São Paulo, Brazil

    Contribution

    Data curation, Formal analysis, Investigation, Writing – review and editing

    Competing interests

    The University of New Mexico filed patent applications on PRUNE2- related technology, for which Diana Nunes was an inventor (inventors: DNN, EDN, RP, and WA). Those applications were briefly optioned by MBrace Therapeutics, but the applications have since been abandoned and the agreements terminated. No payments were made to Diana Nunes, and the author has no other competing interests to declare

12. Israel T Silva

    Laboratory of Bioinformatics and Computational Biology, A.C. Camargo Cancer Center, São Paulo, Brazil

    Contribution

    Data curation, Formal analysis, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

13. Emmanuel Dias-Neto

    Laboratory of Medical Genomics, A.C. Camargo Cancer Center, São Paulo, Brazil

    Contribution

    Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Writing – original draft

    Competing interests

    The University of New Mexico filed patent applications on PRUNE2- related technology, for which Emmanuel Dias-Neto was an inventor (inventors: DNN, EDN, RP, and WA). Those applications were briefly optioned by MBrace Therapeutics, but the applications have since been abandoned and the agreement terminated. No payments were made to Emmanuel Dias-Neto, and the author has no other competing interests to declare

14. Isan Chen

    MBrace Therapeutics, San Diego, California, United States

    Contribution

    Formal analysis, Writing – review and editing

    Competing interests

    serves as the Chief Executive Officer of MBrace Therapeutics. Mbrace did not provide financial support for the present work

15. Dennis J McCance

    1. University of New Mexico Comprehensive Cancer Center, Albuquerque, New Mexico, United States
    2. Department of Pathology, University of New Mexico, Albuquerque, New Mexico, United States

    Contribution

    Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Writing – original draft

    Competing interests

    No competing interests declared

16. Webster K Cavenee

    Ludwig Institute for Cancer Research, University of California, San Diego, La Jolla, California, United States

    Contribution

    Formal analysis, Writing – review and editing

    Competing interests

    is a founder and shareholder of Interleukin Combinatorial Therapies, Inc, InVaMet, Inc, and io9, LLC; none of these companies provided funds or participated in the present work. These arrangements are managed in accordance with the established institutional conflict of interest policies for the respective institution. The author received support for attending the Aspen Cancer Conference, and participated in a Leadership or fiduciary role. The author holds a Leadership or fiduciary role at Genetron Health for which they receive board fees, and are on the Board of Directors for the GBM AGILE Clinical Trial. The author has no other competing interests to declare

17. Renata Pasqualini

    1. Rutgers Cancer Institute of New Jersey, Newark, New Jersey, United States
    2. Division of Cancer Biology, Department of Radiation Oncology, Rutgers New Jersey Medical School, Newark, New Jersey, United States

    Contribution

    Conceptualization, Formal analysis, Supervision, Funding acquisition, Writing – original draft

    For correspondence

    renata.pasqualini@rutgers.edu

    Competing interests

    Reviewing editor, eLife

18. Wadih Arap

    1. Rutgers Cancer Institute of New Jersey, Newark, New Jersey, United States
    2. Division of Hematology/Oncology, Department of Medicine, Rutgers New Jersey Medical School, Newark, New Jersey, United States

    Contribution

    Conceptualization, Formal analysis, Supervision, Funding acquisition, Writing – original draft

    For correspondence

    wadih.arap@rutgers.edu

    Competing interests

    Reviewing editor, eLife

    "This ORCID iD identifies the author of this article:" 0000-0002-8686-4584

• 538

  Page views

• 104

  Downloads

• 1

  Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.