A reliable transcriptomic risk-score applicable to formalin-fixed paraffin-embedded biopsies improves outcome prediction in localized prostate cancer.
Molecular diagnostic testing
Molecular pathology
Personalized medicine
Prognostic biomarker
Prostate cancer
Transcriptome
Journal
Molecular medicine (Cambridge, Mass.)
ISSN: 1528-3658
Titre abrégé: Mol Med
Pays: England
ID NLM: 9501023
Informations de publication
Date de publication:
01 Feb 2024
01 Feb 2024
Historique:
received:
11
07
2023
accepted:
22
01
2024
medline:
2
2
2024
pubmed:
2
2
2024
entrez:
2
2
2024
Statut:
epublish
Résumé
Clinical manifestation of prostate cancer (PCa) is highly variable. Aggressive tumors require radical treatment while clinically non-significant ones may be suitable for active surveillance. We previously developed the prognostic ProstaTrend RNA signature based on transcriptome-wide microarray and RNA-sequencing (RNA-Seq) analyses, primarily of prostatectomy specimens. An RNA-Seq study of formalin-fixed paraffin-embedded (FFPE) tumor biopsies has now allowed us to use this test as a basis for the development of a novel test that is applicable to FFPE biopsies as a tool for early routine PCa diagnostics. All patients of the FFPE biopsy cohort were treated by radical prostatectomy and median follow-up for biochemical recurrence (BCR) was 9 years. Based on the transcriptome data of 176 FFPE biopsies, we filtered ProstaTrend for genes susceptible to FFPE-associated degradation via regression analysis. ProstaTrend was additionally restricted to genes with concordant prognostic effects in the RNA-Seq TCGA prostate adenocarcinoma (PRAD) cohort to ensure robust and broad applicability. The prognostic relevance of the refined Transcriptomic Risk Score (TRS) was analyzed by Kaplan-Meier curves and Cox-regression models in our FFPE-biopsy cohort and 9 other public datasets from PCa patients with BCR as primary endpoint. In addition, we developed a prostate single-cell atlas of 41 PCa patients from 5 publicly available studies to analyze gene expression of ProstaTrend genes in different cell compartments. Validation of the TRS using the original ProstaTrend signature in the cohort of FFPE biopsies revealed a relevant impact of FFPE-associated degradation on gene expression and consequently no significant association with prognosis (Cox-regression, p-value > 0.05) in FFPE tissue. However, the TRS based on the new version of the ProstaTrend-ffpe signature, which included 204 genes (of originally 1396 genes), was significantly associated with BCR in the FFPE biopsy cohort (Cox-regression p-value < 0.001) and retained prognostic relevance when adjusted for Gleason Grade Groups. We confirmed a significant association with BCR in 9 independent cohorts including 1109 patients. Comparison of the prognostic performance of the TRS with 17 other prognostically relevant PCa panels revealed that ProstaTrend-ffpe was among the best-ranked panels. We generated a PCa cell atlas to associate ProstaTrend genes with cell lineages or cell types. Tumor-specific luminal cells have a significantly higher TRS than normal luminal cells in all analyzed datasets. In addition, TRS of epithelial and luminal cells was correlated with increased Gleason score in 3 studies. We developed a prognostic gene-expression signature for PCa that can be applied to FFPE biopsies and may be suitable to support clinical decision-making.
Sections du résumé
BACKGROUND
BACKGROUND
Clinical manifestation of prostate cancer (PCa) is highly variable. Aggressive tumors require radical treatment while clinically non-significant ones may be suitable for active surveillance. We previously developed the prognostic ProstaTrend RNA signature based on transcriptome-wide microarray and RNA-sequencing (RNA-Seq) analyses, primarily of prostatectomy specimens. An RNA-Seq study of formalin-fixed paraffin-embedded (FFPE) tumor biopsies has now allowed us to use this test as a basis for the development of a novel test that is applicable to FFPE biopsies as a tool for early routine PCa diagnostics.
METHODS
METHODS
All patients of the FFPE biopsy cohort were treated by radical prostatectomy and median follow-up for biochemical recurrence (BCR) was 9 years. Based on the transcriptome data of 176 FFPE biopsies, we filtered ProstaTrend for genes susceptible to FFPE-associated degradation via regression analysis. ProstaTrend was additionally restricted to genes with concordant prognostic effects in the RNA-Seq TCGA prostate adenocarcinoma (PRAD) cohort to ensure robust and broad applicability. The prognostic relevance of the refined Transcriptomic Risk Score (TRS) was analyzed by Kaplan-Meier curves and Cox-regression models in our FFPE-biopsy cohort and 9 other public datasets from PCa patients with BCR as primary endpoint. In addition, we developed a prostate single-cell atlas of 41 PCa patients from 5 publicly available studies to analyze gene expression of ProstaTrend genes in different cell compartments.
RESULTS
RESULTS
Validation of the TRS using the original ProstaTrend signature in the cohort of FFPE biopsies revealed a relevant impact of FFPE-associated degradation on gene expression and consequently no significant association with prognosis (Cox-regression, p-value > 0.05) in FFPE tissue. However, the TRS based on the new version of the ProstaTrend-ffpe signature, which included 204 genes (of originally 1396 genes), was significantly associated with BCR in the FFPE biopsy cohort (Cox-regression p-value < 0.001) and retained prognostic relevance when adjusted for Gleason Grade Groups. We confirmed a significant association with BCR in 9 independent cohorts including 1109 patients. Comparison of the prognostic performance of the TRS with 17 other prognostically relevant PCa panels revealed that ProstaTrend-ffpe was among the best-ranked panels. We generated a PCa cell atlas to associate ProstaTrend genes with cell lineages or cell types. Tumor-specific luminal cells have a significantly higher TRS than normal luminal cells in all analyzed datasets. In addition, TRS of epithelial and luminal cells was correlated with increased Gleason score in 3 studies.
CONCLUSIONS
CONCLUSIONS
We developed a prognostic gene-expression signature for PCa that can be applied to FFPE biopsies and may be suitable to support clinical decision-making.
Identifiants
pubmed: 38302875
doi: 10.1186/s10020-024-00789-9
pii: 10.1186/s10020-024-00789-9
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
19Informations de copyright
© 2024. The Author(s).
Références
Abeshouse A, Ahn J, Akbani R, Ally A, Amin S, Andry CD, Annala M, Aprikian A, Armenia J, Arora A, Auman JT. The molecular taxonomy of primary prostate cancer. Cell. 2015;163(4):1011–25.
doi: 10.1016/j.cell.2015.10.025
Abrams-Pompe RS, Fanti S, Schoots IG, Moore CM, Turkbey B, Vickers AJ, et al. The role of magnetic resonance imaging and positron emission tomography/computed tomography in the primary staging of newly diagnosed prostate cancer: a systematic review of the literature. Eur Urol Oncol. 2021;4:370–95. https://doi.org/10.1016/j.euo.2020.11.002 .
doi: 10.1016/j.euo.2020.11.002
pubmed: 33272865
Adams TS, Schupp JC, Poli S, Ayaub EA, Neumark N, Ahangari F, et al. Single-cell RNA-seq reveals ectopic and aberrant lung-resident cell populations in idiopathic pulmonary fibrosis. Sci Adv. 2020;6: eaba1983. https://doi.org/10.1126/sciadv.aba1983 .
doi: 10.1126/sciadv.aba1983
pubmed: 32832599
pmcid: 7439502
Adiconis X, Borges-Rivera D, Satija R, DeLuca DS, Busby MA, Berlin AM, et al. Comparative analysis of RNA sequencing methods for degraded or low-input samples. Nat Methods. 2013;10:623–9. https://doi.org/10.1038/nmeth.2483 .
doi: 10.1038/nmeth.2483
pubmed: 23685885
pmcid: 3821180
Briganti A, Larcher A, Abdollah F, Capitanio U, Gallina A, Suardi N, et al. Updated nomogram predicting lymph node invasion in patients with prostate cancer undergoing extended pelvic lymph node dissection: the essential importance of percentage of positive cores. Eur Urol. 2012;61:480–7. https://doi.org/10.1016/j.eururo.2011.10.044 .
doi: 10.1016/j.eururo.2011.10.044
pubmed: 22078338
Cagiannos I, Karakiewicz P, Eastham JA, Ohori M, Rabbani F, Gerigk C, et al. A preoperative nomogram identifying decreased risk of positive pelvic lymph nodes in patients with prostate cancer. J Urol. 2003;170:1798–803. https://doi.org/10.1097/01.ju.0000091805.98960.13 .
doi: 10.1097/01.ju.0000091805.98960.13
pubmed: 14532779
Carm KT, Hoff AM, Bakken AC, Axcrona U, Axcrona K, Lothe RA, et al. Interfocal heterogeneity challenges the clinical usefulness of molecular classification of primary prostate cancer. Sci Rep. 2019;9:13579. https://doi.org/10.1038/s41598-019-49964-7 .
doi: 10.1038/s41598-019-49964-7
pubmed: 31537872
pmcid: 6753093
Chen S, Zhu G, Yang Y, Wang F, Xiao Y-T, Zhang N, et al. Single-cell analysis reveals transcriptomic remodellings in distinct cell types that contribute to human prostate cancer progression. Nat Cell Biol. 2021;23:87–98. https://doi.org/10.1038/s41556-020-00613-6 .
doi: 10.1038/s41556-020-00613-6
pubmed: 33420488
Cooperberg MR, Hilton JF, Carroll PR. The CAPRA-S score: a straightforward tool for improved prediction of outcomes after radical prostatectomy. Cancer. 2011;117:5039–46. https://doi.org/10.1002/cncr.26169 .
doi: 10.1002/cncr.26169
pubmed: 21647869
Creed JH, Berglund AE, Rounbehler RJ, Awasthi S, Cleveland JL, Park JY, et al. Commercial gene expression tests for prostate cancer prognosis provide paradoxical estimates of race-specific risk. Cancer Epidemiol Biomark Prev. 2020;29:246–53. https://doi.org/10.1158/1055-9965.EPI-19-0407 .
doi: 10.1158/1055-9965.EPI-19-0407
Cullen J, Rosner IL, Brand TC, Zhang N, Tsiatis AC, Moncur J, et al. A biopsy-based 17-gene genomic prostate score predicts recurrence after radical prostatectomy and adverse surgical pathology in a racially diverse population of men with clinically low- and intermediate-risk prostate cancer. Eur Urol. 2015;68:123–31. https://doi.org/10.1016/j.eururo.2014.11.030 .
doi: 10.1016/j.eururo.2014.11.030
pubmed: 25465337
Cuzick J, Swanson GP, Fisher G, Brothman AR, Berney DM, Reid JE, et al. Prognostic value of an RNA expression signature derived from cell cycle proliferation genes in patients with prostate cancer: a retrospective study. Lancet Oncol. 2011;12:245–55. https://doi.org/10.1016/S1470-2045(10)70295-3 .
doi: 10.1016/S1470-2045(10)70295-3
pubmed: 21310658
pmcid: 3091030
Cuzick J, Stone S, Fisher G, Yang ZH, North BV, Berney DM, et al. Validation of an RNA cell cycle progression score for predicting death from prostate cancer in a conservatively managed needle biopsy cohort. Br J Cancer. 2015;113:382–9. https://doi.org/10.1038/bjc.2015.223 .
doi: 10.1038/bjc.2015.223
pubmed: 26103570
pmcid: 4522632
Davis S, Meltzer PS. GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor. Bioinformatics. 2007;23:1846–7. https://doi.org/10.1093/bioinformatics/btm254 .
doi: 10.1093/bioinformatics/btm254
pubmed: 17496320
Dong B, Miao J, Wang Y, Luo W, Ji Z, Lai H, et al. Single-cell analysis supports a luminal-neuroendocrine transdifferentiation in human prostate cancer. Commun Biol. 2020;3:778. https://doi.org/10.1038/s42003-020-01476-1 .
doi: 10.1038/s42003-020-01476-1
pubmed: 33328604
pmcid: 7745034
Edgar R, Domrachev M, Lash AE. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2002;30:207–10. https://doi.org/10.1093/nar/30.1.207 .
doi: 10.1093/nar/30.1.207
pubmed: 11752295
pmcid: 99122
Epstein JI, Egevad L, Amin MB, Delahunt B, Srigley JR, Humphrey PA. The 2014 International Society of Urological Pathology (ISUP) consensus conference on Gleason grading of prostatic carcinoma definition of grading patterns and proposal for a new grading system. Am J Surg Pathol. 2016;40:244–52. https://doi.org/10.1097/PAS.0000000000000530 .
doi: 10.1097/PAS.0000000000000530
pubmed: 26492179
Erho N, Crisan A, Vergara IA, Mitra AP, Ghadessi M, Buerki C, et al. Discovery and validation of a prostate cancer genomic classifier that predicts early metastasis following radical prostatectomy. PLoS ONE. 2013;8: e66855. https://doi.org/10.1371/journal.pone.0066855 .
doi: 10.1371/journal.pone.0066855
pubmed: 23826159
pmcid: 3691249
Fine ND, LaPolla F, Epstein M, Loeb S, Dani H. Genomic classifiers for treatment selection in newly diagnosed prostate cancer. BJU Int. 2019. https://doi.org/10.1111/bju.14799 .
doi: 10.1111/bju.14799
pubmed: 31055874
Frampton GM, Fichtenholtz A, Otto GA, Wang K, Downing SR, He J, et al. Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing. Nat Biotechnol. 2013;31:1023–31. https://doi.org/10.1038/nbt.2696 .
doi: 10.1038/nbt.2696
pubmed: 24142049
pmcid: 5710001
Fraser M, Sabelnykova VY, Yamaguchi TN, Heisler LE, Livingstone J, Huang V, et al. Genomic hallmarks of localized, non-indolent prostate cancer. Nature. 2017;541:359–64. https://doi.org/10.1038/nature20788 .
doi: 10.1038/nature20788
pubmed: 28068672
Fu R, Gillen AE, Sheridan RM, Tian C, Daya M, Hao Y, et al. clustifyr: an R package for automated single-cell RNA sequencing cluster classification. F1000Research. 2020;9:223. https://doi.org/10.12688/f1000research.22969.2 .
doi: 10.12688/f1000research.22969.2
pubmed: 32765839
pmcid: 7383722
Gao J, Aksoy BA, Dogrusoz U, Dresdner G, Gross B, Sumer SO, et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal. 2013;6:pl1. https://doi.org/10.1126/scisignal.2004088 .
doi: 10.1126/scisignal.2004088
pubmed: 23550210
pmcid: 4160307
Gentleman R, Carey V, Huber W, Hahne F. genefilter: genefilter: methods for filtering genes from high-throughput experiments. R package version 1.72.1. 2018.
Gerhauser C, Favero F, Risch T, Simon R, Feuerbach L, Assenov Y, et al. Molecular evolution of early-onset prostate cancer identifies molecular risk markers and clinical trajectories. Cancer Cell. 2018;34:996-1011.e8. https://doi.org/10.1016/j.ccell.2018.10.016 .
doi: 10.1016/j.ccell.2018.10.016
pubmed: 30537516
pmcid: 7444093
Groelz D, Sobin L, Branton P, Compton C, Wyrich R, Rainen L. Non-formalin fixative versus formalin-fixed tissue: a comparison of histology and RNA quality. Exp Mol Pathol. 2013;94:188–94. https://doi.org/10.1016/j.yexmp.2012.07.002 .
doi: 10.1016/j.yexmp.2012.07.002
pubmed: 22814231
Hao Y, Hao S, Andersen-Nissen E, Mauck WM, Zheng S, Butler A, et al. Integrated analysis of multimodal single-cell data. Cell. 2021;184:3573-3587.e29. https://doi.org/10.1016/j.cell.2021.04.048 .
doi: 10.1016/j.cell.2021.04.048
pubmed: 34062119
pmcid: 8238499
Henry GH, Malewska A, Joseph DB, Malladi VS, Lee J, Torrealba J, et al. A cellular anatomy of the normal adult human prostate and prostatic urethra. Cell Rep. 2018;25:3530-3542.e5. https://doi.org/10.1016/j.celrep.2018.11.086 .
doi: 10.1016/j.celrep.2018.11.086
pubmed: 30566875
pmcid: 6411034
Jain S, Lyons CA, Walker SM, McQuaid S, Hynes SO, Mitchell DM, et al. Validation of a metastatic assay using biopsies to improve risk stratification in patients with prostate cancer treated with radical radiation therapy. Ann Oncol. 2018;29:215–22. https://doi.org/10.1093/annonc/mdx637 .
doi: 10.1093/annonc/mdx637
pubmed: 29045551
Kämpf C, Specht M, Scholz A, Puppel S-H, Doose G, Reiche K, et al. uap: reproducible and robust HTS data analysis. BMC Bioinform. 2019;20:1–9.
doi: 10.1186/s12859-019-3219-1
Kosaka T, Miyajima A, Nagata H, Maeda T, Kikuchi E, Oya M. Human castration resistant prostate cancer rather prefer to decreased 5α-reductase activity. Sci Rep. 2013;3:1268. https://doi.org/10.1038/srep01268 .
doi: 10.1038/srep01268
pubmed: 23429215
pmcid: 3572449
Kreuz M, Otto DJ, Fuessel S, Blumert C, Bertram C, Bartsch S, et al. ProstaTrend—a multivariable prognostic RNA expression score for aggressive prostate cancer. Eur Urol. 2020;78:452–9. https://doi.org/10.1016/j.eururo.2020.06.001 .
doi: 10.1016/j.eururo.2020.06.001
pubmed: 32631745
Leapman MS, Westphalen AC, Ameli N, Lawrence HJ, Febbo PG, Cooperberg MR, Carroll PR. Association between a 17-gene genomic prostate score and multi-parametric prostate MRI in men with low and intermediate risk prostate cancer (PCa). PLoS ONE. 2017;12: e0185535. https://doi.org/10.1371/journal.pone.0185535 .
doi: 10.1371/journal.pone.0185535
pubmed: 29016610
pmcid: 5634556
Li J, Xu C, Lee HJ, Ren S, Zi X, Zhang Z, et al. A genomic and epigenomic atlas of prostate cancer in Asian populations. Nature. 2020;580:93–9. https://doi.org/10.1038/s41586-020-2135-x .
doi: 10.1038/s41586-020-2135-x
pubmed: 32238934
Li R, Zhu J, Zhong W-D, Jia Z. PCaDB—a comprehensive and interactive database for transcriptomes from prostate cancer population cohorts. bioRxiv. 2021. https://doi.org/10.1101/2021.06.29.449134 .
doi: 10.1101/2021.06.29.449134
pubmed: 34981065
pmcid: 8722592
Li R, Zhu J, Zhong W-D, Jia Z. Comprehensive evaluation of machine learning models and gene expression signatures for prostate cancer prognosis using large population cohorts. Cancer Res. 2022;82:1832–43. https://doi.org/10.1158/0008-5472.CAN-21-3074 .
doi: 10.1158/0008-5472.CAN-21-3074
pubmed: 35358302
Long Q, Xu J, Osunkoya AO, Sannigrahi S, Johnson BA, Zhou W, et al. Global transcriptome analysis of formalin-fixed prostate cancer specimens identifies biomarkers of disease recurrence. Cancer Res. 2014;74:3228–37. https://doi.org/10.1158/0008-5472.CAN-13-2699 .
doi: 10.1158/0008-5472.CAN-13-2699
pubmed: 24713434
pmcid: 4058362
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550. https://doi.org/10.1186/s13059-014-0550-8 .
doi: 10.1186/s13059-014-0550-8
pubmed: 25516281
pmcid: 4302049
Luca B-A, Brewer DS, Edwards DR, Edwards S, Whitaker HC, Merson S, et al. DESNT: a poor prognosis category of human prostate cancer. Eur Urol Focus. 2018;4:842–50. https://doi.org/10.1016/j.euf.2017.01.016 .
doi: 10.1016/j.euf.2017.01.016
pubmed: 28753852
Ma X, Guo J, Liu K, Chen L, Liu D, Dong S, et al. Identification of a distinct luminal subgroup diagnosing and stratifying early stage prostate cancer by tissue-based single-cell RNA sequencing. Mol Cancer. 2020;19:147. https://doi.org/10.1186/s12943-020-01264-9 .
doi: 10.1186/s12943-020-01264-9
pubmed: 33032611
pmcid: 7545561
Makarov DV, Trock BJ, Humphreys EB, Mangold LA, Walsh PC, Epstein JI, Partin AW. Updated nomogram to predict pathologic stage of prostate cancer given prostate-specific antigen level, clinical stage, and biopsy Gleason score (Partin tables) based on cases from 2000 to 2005. Urology. 2007;69:1095–101. https://doi.org/10.1016/j.urology.2007.03.042 .
doi: 10.1016/j.urology.2007.03.042
pubmed: 17572194
McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM. Reporting recommendations for tumor marker prognostic studies (REMARK). J Natl Cancer Inst. 2005;97:1180–4. https://doi.org/10.1093/jnci/dji237 .
doi: 10.1093/jnci/dji237
pubmed: 16106022
Mottet N, van den Bergh RCN, Briers E, van den Broeck T, Cumberbatch MG, de Santis M, et al. EAU-EANM-ESTRO-ESUR-SIOG guidelines on prostate cancer-2020 update. Part 1: screening, diagnosis, and local treatment with curative intent. Eur Urol. 2021;79:243–62. https://doi.org/10.1016/j.eururo.2020.09.042 .
doi: 10.1016/j.eururo.2020.09.042
pubmed: 33172724
Park BH, Jeon HG, Jeong BC, Seo SI, Lee HM, Choi HY, Jeon SS. Influence of magnetic resonance imaging in the decision to preserve or resect neurovascular bundles at robotic assisted laparoscopic radical prostatectomy. J Urol. 2014;192:82–8. https://doi.org/10.1016/j.juro.2014.01.005 .
doi: 10.1016/j.juro.2014.01.005
pubmed: 24440235
Parker JS, Mullins M, Cheang MCU, Leung S, Voduc D, Vickery T, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol. 2009;27:1160–7. https://doi.org/10.1200/JCO.2008.18.1370 .
doi: 10.1200/JCO.2008.18.1370
pubmed: 19204204
pmcid: 2667820
Racle J, Gfeller D. EPIC: a tool to estimate the proportions of different cell types from bulk gene expression data. Methods Mol Biol. 2020;2120:233–48. https://doi.org/10.1007/978-1-0716-0327-7_17 .
doi: 10.1007/978-1-0716-0327-7_17
pubmed: 32124324
Rodon J, Soria J-C, Berger R, Miller WH, Rubin E, Kugel A, et al. Genomic and transcriptomic profiling expands precision cancer medicine: the WINTHER trial. Nat Med. 2019;25:751–8. https://doi.org/10.1038/s41591-019-0424-4 .
doi: 10.1038/s41591-019-0424-4
pubmed: 31011205
pmcid: 6599610
Ross-Adams H, Lamb AD, Dunning MJ, Halim S, Lindberg J, Massie CM, et al. Integration of copy number and transcriptomics provides risk stratification in prostate cancer: a discovery and validation cohort study. EBioMedicine. 2015;2:1133–44. https://doi.org/10.1016/j.ebiom.2015.07.017 .
doi: 10.1016/j.ebiom.2015.07.017
pubmed: 26501111
pmcid: 4588396
Salami SS, Hovelson DH, Kaplan JB, Mathieu R, Udager AM, Curci NE, et al. Transcriptomic heterogeneity in multifocal prostate cancer. JCI Insight. 2018. https://doi.org/10.1172/jci.insight.123468 .
doi: 10.1172/jci.insight.123468
pubmed: 30385730
pmcid: 6238741
Schwarzer G. meta: an R package for meta-analysis. In: R News. 2007. p. 40–5.
Söderström TG, Bjelfman C, Brekkan E, Ask B, Egevad L, Norlén BJ, Rane A. Messenger ribonucleic acid levels of steroid 5 alpha-reductase 2 in human prostate predict the enzyme activity. J Clin Endocrinol Metab. 2001;86:855–8. https://doi.org/10.1210/jcem.86.2.7224 .
doi: 10.1210/jcem.86.2.7224
pubmed: 11158057
Somford DM, Hamoen EH, Fütterer JJ, van Basten JP, Hulsbergen-van de Kaa CA, Vreuls W, et al. The predictive value of endorectal 3 Tesla multiparametric magnetic resonance imaging for extraprostatic extension in patients with low, intermediate and high risk prostate cancer. J Urol. 2013;190:1728–34. https://doi.org/10.1016/j.juro.2013.05.021 .
doi: 10.1016/j.juro.2013.05.021
pubmed: 23680307
Song H, Weinstein HNW, Allegakoen P, Wadsworth MH, Xie J, Yang H, et al. Single-cell analysis of human primary prostate cancer reveals the heterogeneity of tumor-associated epithelial cell states. Nat Commun. 2022;13:141. https://doi.org/10.1038/s41467-021-27322-4 .
doi: 10.1038/s41467-021-27322-4
pubmed: 35013146
pmcid: 8748675
Stephenson AJ, Scardino PT, Eastham JA, Bianco FJ, Dotan ZA, DiBlasio CJ, et al. Postoperative nomogram predicting the 10-year probability of prostate cancer recurrence after radical prostatectomy. J Clin Oncol. 2005;23:7005–12. https://doi.org/10.1200/JCO.2005.01.867 .
doi: 10.1200/JCO.2005.01.867
pubmed: 16192588
Taylor BS, Schultz N, Hieronymus H, Gopalan A, Xiao Y, Carver BS, et al. Integrative genomic profiling of human prostate cancer. Cancer Cell. 2010;18:11–22. https://doi.org/10.1016/j.ccr.2010.05.026 .
doi: 10.1016/j.ccr.2010.05.026
pubmed: 20579941
pmcid: 3198787
Therneau TM. A package for survival analysis in R. 2015. https://CRAN.R-project.org/package=survival .
Titus MA, Gregory CW, Ford OH, Schell MJ, Maygarden SJ, Mohler JL. Steroid 5alpha-reductase isozymes I and II in recurrent prostate cancer. Clin Cancer Res. 2005;11:4365–71. https://doi.org/10.1158/1078-0432.CCR-04-0738 .
doi: 10.1158/1078-0432.CCR-04-0738
pubmed: 15958619
Titus MA, Li Y, Kozyreva OG, Maher V, Godoy A, Smith GJ, Mohler JL. 5α-Reductase type 3 enzyme in benign and malignant prostate. Prostate. 2014;74:235–49. https://doi.org/10.1002/pros.22745 .
doi: 10.1002/pros.22745
pubmed: 24150795
Tuong ZK, Loudon KW, Berry B, Richoz N, Jones J, Tan X, et al. Resolving the immune landscape of human prostate at a single-cell level in health and cancer. Cell Rep. 2021;37: 110132. https://doi.org/10.1016/j.celrep.2021.110132 .
doi: 10.1016/j.celrep.2021.110132
pubmed: 34936871
pmcid: 8721283
Villani A-C, Satija R, Reynolds G, Sarkizova S, Shekhar K, Fletcher J, et al. Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors. Science. 2017. https://doi.org/10.1126/science.aah4573 .
doi: 10.1126/science.aah4573
pubmed: 28428369
pmcid: 5775029
Wang S-Y, Cowan JE, Cary KC, Chan JM, Carroll PR, Cooperberg MR. Limited ability of existing nomograms to predict outcomes in men undergoing active surveillance for prostate cancer. BJU Int. 2014;114:E18–24. https://doi.org/10.1111/bju.12554 .
doi: 10.1111/bju.12554
pubmed: 24712895
Yuan H, Yan M, Zhang G, Liu W, Deng C, Liao G, et al. CancerSEA: a cancer single-cell state atlas. Nucleic Acids Res. 2019;47:D900–8. https://doi.org/10.1093/nar/gky939 .
doi: 10.1093/nar/gky939
pubmed: 30329142