Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Clinical Research
  • Published:

Plasma cell-free DNA-based predictors of response to abiraterone acetate/prednisone and prognostic factors in metastatic castration-resistant prostate cancer

Prostate Cancer and Prostatic Diseases volume 23, pages 705–713 (2020)Cite this article

Subjects

Abstract

Background

The combination of abiraterone acetate and prednisone (AA/P) is used to treat metastatic prostate cancer, but molecular predictors of treatment response are not well elucidated. We evaluated plasma circulating tumor DNA- (ctDNA-) based copy number alterations (CNAs) to determine treatment-related predictive and prognostic biomarkers for metastatic castration-resistant prostate cancer (mCRPC).

Methods

Serial plasma specimens were prospectively collected from 88 chemotherapy-naive mCRPC patients before and after 12 weeks of AA/P treatment. Sequencing-based CNA analyses were performed on 174 specimens. We evaluated CNA-associated 12-week responses for primary resistance, time to treatment change (TTTC) for secondary resistance, and overall survival for prognosis (P < 0.05). Associations with primary resistance were analyzed using the Fisher exact test. Kaplan–Meier survival curves and Cox regression analyses were used to determine the associations of CNAs with acquired resistance and overall survival.

Results

ctDNA reduced by 3.89% in responders and increased by 0.94% in nonresponders (P = 0.0043). Thirty-one prostate cancer-related genes from whole genome CNAs were tested. AR and AR enhancer amplification were associated with primary resistance (P = 0.0039) and shorter TTTC (P = 0.0003). ZFHX3 deletion and PIK3CA amplification were associated with primary resistance (P = 0.026 and P = 0.017, respectively), shorter TTTC (P = 0.0008 and P = 0.0016, respectively), and poor survival (P = 0.0025 and P = 0.0022, respectively). CNA-based risk scores combining selected significant associations (AR, NKX3.1, and PIK3CA) at the univariate level with TTTC were predictive of secondary resistance (P = 0.0002). and established prognoses for survival based on CNAs in ZFHX3, RB1, PIK3CA, and OPHN1 (P = 0.002). Multigene risk scores were more predictive than individual genes or clinical risk factors (P < 0.05).

Conclusion

Plasma ctDNA CNAs and risk scores can predict mCRPC-state treatment and survival outcomes.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Landscape of copy number alterations in plasma cell-free DNA of metastatic castration-resistant prostate cancer patients.
Fig. 2: Dynamic circulating tumor DNA content changes during abiraterone acetate and prednisone treatment.
Fig. 3: Circulating tumor DNA-based copy number alterations of biologically relevant driver genes and abiraterone acetate and prednisone resistance in baseline plasma samples.
Fig. 4: Association of locus-specific copy number alterations with clinical outcomes at baseline plasma samples.

Similar content being viewed by others

References

  1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin. 2016;66:7–30.

    Article  Google Scholar 

  2. Sridhar SS, Freedland SJ, Gleave ME, Higano C, Mulders P, Parker C, et al. Castration-resistant prostate cancer: from new pathophysiology to new treatment. Eur Urol. 2014;65:289–99.

    Article  Google Scholar 

  3. Gartrell BA, Saad F. Abiraterone in the management of castration-resistant prostate cancer prior to chemotherapy. Ther Adv Urol. 2015;7:194–202.

    Article  CAS  Google Scholar 

  4. Ryan CJ, Smith MR, de Bono JS, Molina A, Logothetis CJ, de Souza P, et al. Abiraterone in metastatic prostate cancer without previous chemotherapy. N Engl J Med. 2013;368:138–48.

    Article  CAS  Google Scholar 

  5. Grasso CS, Wu YM, Robinson DR, Cao X, Dhanasekaran SM, Khan AP, et al. The mutational landscape of lethal castration-resistant prostate cancer. Nature. 2012;487:239–43.

    Article  CAS  Google Scholar 

  6. Robinson D, Van Allen EM, Wu YM, Schultz N, Lonigro RJ, Mosquera JM, et al. Integrative clinical genomics of advanced prostate cancer. Cell. 2015;161:1215–28.

    Article  CAS  Google Scholar 

  7. Kumar A, Coleman I, Morrissey C, Zhang X, True LD, Gulati R, et al. Substantial interindividual and limited intraindividual genomic diversity among tumors from men with metastatic prostate cancer. Nat Med. 2016;22:369–78.

    Article  CAS  Google Scholar 

  8. Ren S, Wei GH, Liu D, Wang L, Hou Y, Zhu S, et al. Whole-genome and transcriptome sequencing of prostate cancer identify new genetic alterations driving disease progression. Eur Urol. 2017;73:322–39.

    Article  Google Scholar 

  9. Wang L, Dehm SM, Hillman DW, Sicotte H, Tan W, Gormley M, et al. A prospective genome-wide study of prostate cancer metastases reveals association of wnt pathway activation and increased cell cycle proliferation with primary resistance to abiraterone acetate-prednisone. Ann Oncol. 2018;29:352–60.

    Article  CAS  Google Scholar 

  10. Watson PA, Arora VK, Sawyers CL. Emerging mechanisms of resistance to androgen receptor inhibitors in prostate cancer. Nat Rev Cancer. 2015;15:701–11.

    Article  CAS  Google Scholar 

  11. Jimenez RE, Atwell TD, Sicotte H, Eckloff B, Wang L, Barman P, et al. A prospective correlation of tissue histopathology with nucleic acid yield in metastatic castration-resistant prostate cancer biopsy specimens. Mayo Clin Proc Innov Qual Outcomes. 2019;3:14–22.

    Article  Google Scholar 

  12. Danila DC, Heller G, Gignac GA, Gonzalez-Espinoza R, Anand A, Tanaka E, et al. Circulating tumor cell number and prognosis in progressive castration-resistant prostate cancer. Clin Cancer Res. 2007;13:7053–8.

    Article  CAS  Google Scholar 

  13. Wyatt AW, Azad AA, Volik SV, Annala M, Beja K, McConeghy B, et al. Genomic alterations in cell-free DNA and enzalutamide resistance in castration-resistant prostate cancer. JAMA Oncol. 2016;2:1598–606.

    Article  Google Scholar 

  14. Ulz P, Belic J, Graf R, Auer M, Lafer I, Fischereder K, et al. Whole-genome plasma sequencing reveals focal amplifications as a driving force in metastatic prostate cancer. Nat Commun. 2016;7:12008.

    Article  CAS  Google Scholar 

  15. Hovelson DH, Liu CJ, Wang Y, Kang Q, Henderson J, Gursky A, et al. Rapid, ultra low coverage copy number profiling of cell-free DNA as a precision oncology screening strategy. Oncotarget. 2017;8:89848–66.

    Article  Google Scholar 

  16. Azad AA, Volik SV, Wyatt AW, Haegert A, Le Bihan S, Bell RH, et al. Androgen receptor gene aberrations in circulating cell-free DNA: biomarkers of therapeutic resistance in castration-resistant prostate cancer. Clin Cancer Res. 2015;21:2315–24.

    Article  CAS  Google Scholar 

  17. Kohli M, Li J, Du M, Hillman DW, Dehm SM, Tan W, et al. Prognostic association of plasma cell-free DNA-based androgen receptor amplification and circulating tumor cells in pre-chemotherapy metastatic castration-resistant prostate cancer patients. Prostate Cancer Prostatic Dis. 2018;21:411–8.

    Article  CAS  Google Scholar 

  18. Romanel A, Gasi Tandefelt D, Conteduca V, Jayaram A, Casiraghi N, Wetterskog D, et al. Plasma AR and abiraterone-resistant prostate cancer. Sci Transl Med. 2015;7:312re310.

    Article  Google Scholar 

  19. Choudhury AD, Werner L, Francini E, Wei XX, Ha G, Freeman SS, et al. Tumor fraction in cell-free DNA as a biomarker in prostate cancer. JCI Insight. 2018;3:1–14. https://www.ncbi.nlm.nih.gov/pubmed/30385733.

    Article  Google Scholar 

  20. Mayrhofer M, De Laere B, Whitington T, Van Oyen P, Ghysel C, Ampe J, et al. Cell-free DNA profiling of metastatic prostate cancer reveals microsatellite instability, structural rearrangements and clonal hematopoiesis. Genome Med. 2018;10:85.

    Article  CAS  Google Scholar 

  21. Annala M, Vandekerkhove G, Khalaf D, Taavitsainen S, Beja K, Warner EW, et al. Circulating tumor DNA genomics correlate with resistance to abiraterone and enzalutamide in prostate cancer. Cancer Discov. 2018;8:444–57.

    Article  CAS  Google Scholar 

  22. De Laere B, Oeyen S, Mayrhofer M, Whitington T, van Dam PJ, Van Oyen P, et al. TP53 outperforms other androgen receptor biomarkers to predict abiraterone or enzalutamide outcome in metastatic castration-resistant prostate cancer. Clin Cancer Res. 2019;25:1766–73.

    Article  Google Scholar 

  23. Torquato S, Pallavajjala A, Goldstein A, Toro PV, Silberstein JL, Lee J, et al. Genetic alterations detected in cell-free DNA are associated with enzalutamide and abiraterone resistance in castration-resistant prostate cancer. JCO Precis Oncol. 2019;3. https://www.ncbi.nlm.nih.gov/pubmed/31131348.

  24. Xia S, Kohli M, Du M, Dittmar RL, Lee A, Nandy D, et al. Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer. Oncotarget. 2015;6:16411–21.

    Article  Google Scholar 

  25. Li J, Dittmar RL, Xia S, Zhang H, Du M, Huang CC, et al. Cell-free DNA copy number variations in plasma from colorectal cancer patients. Mol Oncol. 2017;11:1099–111.

    Article  CAS  Google Scholar 

  26. Adalsteinsson VA, Ha G, Freeman SS, Choudhury AD, Stover DG, Parsons HA, et al. Scalable whole-exome sequencing of cell-free DNA reveals high concordance with metastatic tumors. Nat Commun. 2017;8:1324.

    Article  Google Scholar 

  27. Scher HI, Halabi S, Tannock I, Morris M, Sternberg CN, Carducci MA, et al. Design and end points of clinical trials for patients with progressive prostate cancer and castrate levels of testosterone: recommendations of the Prostate Cancer Clinical Trials Working Group. J Clin Oncol. 2008;26:1148–59.

    Article  Google Scholar 

  28. Quigley DA, Dang HX, Zhao SG, Lloyd P, Aggarwal R, Alumkal JJ, et al. Genomic hallmarks and structural variation in metastatic prostate cancer. Cell. 2018;174:758–69.e9.

    Article  CAS  Google Scholar 

  29. Luijten MNH, Lee JXT, Crasta KC. Mutational game changer: chromothripsis and its emerging relevance to cancer. Mutat Res. 2018;777:29–51.

    Article  CAS  Google Scholar 

  30. Wyatt AW, Annala M, Aggarwal R, Beja K, Feng F, Youngren J, et al. Concordance of circulating tumor DNA and matched metastatic tissue biopsy in prostate cancer. J Natl Cancer Inst. 2017;109. https://www.ncbi.nlm.nih.gov/pubmed/29206995.

  31. Newcombe PJ, Connolly S, Seaman S, Richardson S, Sharp SJ. A two-step method for variable selection in the analysis of a case-cohort study. Int J Epidemiol. 2018;47:597–604.

    Article  CAS  Google Scholar 

  32. Wang F, Koul HK. Androgen receptor (AR) cistrome in prostate differentiation and cancer progression. Am J Clin Exp Urol. 2017;5:18–24.

    PubMed  PubMed Central  Google Scholar 

  33. AR enhancer amplification drives castration-resistant prostate cancer. Cancer Discov. 2018;8:OF17. https://doi.org/10.1158/2159-8290.CD-RW2018-105.

  34. Takeda DY, Spisak S, Seo JH, Bell C, O’Connor E, Korthauer K, et al. A somatically acquired enhancer of the androgen receptor is a noncoding driver in advanced prostate. Cancer Cell. 2018;174:422–32.e13.

    CAS  Google Scholar 

  35. Viswanathan SR, Ha G, Hoff AM, Wala JA, Carrot-Zhang J, Whelan CW, et al. Structural alterations driving castration-resistant prostate cancer revealed by linked-read genome sequencing. Cell. 2018;174:433–47.e19.

    Article  CAS  Google Scholar 

  36. Goto K, Oue N, Hayashi T, Shinmei S, Sakamoto N, Sentani K, et al. Oligophrenin-1 is associated with cell adhesion and migration in prostate cancer. Pathobiology. 2014;81:190–8.

    Article  CAS  Google Scholar 

  37. Zhao D, Ma G, Zhang X, He Y, Li M, Han X, et al. Zinc finger homeodomain factor Zfhx3 is essential for mammary lactogenic differentiation by maintaining prolactin signaling activity. J Biol Chem. 2016;291:12809–20.

    Article  CAS  Google Scholar 

  38. Gupta S, Li J, Kemeny G, Bitting RL, Beaver J, Somarelli JA, et al. Whole genomic copy number alterations in circulating tumor cells from men with abiraterone or enzalutamide-resistant metastatic castration-resistant prostate cancer. Clin Cancer Res. 2017;23:1346–57.

    Article  CAS  Google Scholar 

  39. Soave A, Chun FK, Hillebrand T, Rink M, Weisbach L, Steinbach B, et al. Copy number variations of circulating, cell-free DNA in urothelial carcinoma of the bladder patients treated with radical cystectomy: a prospective study. Oncotarget. 2017;8:56398–407.

    Article  Google Scholar 

  40. Arafeh R, Samuels Y. PIK3CA in cancer: the past 30 years. Semin Cancer Biol. 2019;59:36–49. https://doi.org/10.1016/j.semcancer.2019.02.002.

    Article  CAS  PubMed  Google Scholar 

  41. Pearson HB, Li J, Meniel VS, Fennell CM, Waring P, Montgomery KG, et al. Identification of Pik3ca mutation as a genetic driver of prostate cancer that cooperates with pten loss to accelerate progression and castration-resistant growth. Cancer Discov. 2018;8:764–79.

    Article  CAS  Google Scholar 

  42. Cancer Genome Atlas Research N. The molecular taxonomy of primary prostate cancer. Cell. 2015;163:1011–25.

    Article  Google Scholar 

  43. Baca SC, Prandi D, Lawrence MS, Mosquera JM, Romanel A, Drier Y, et al. Punctuated evolution of prostate cancer genomes. Cell. 2013;153:666–77.

    Article  CAS  Google Scholar 

  44. Nava Rodrigues D, Casiraghi N, Romanel A, Crespo M, Miranda S, Rescigno P, et al. RB1 heterogeneity in advanced metastatic castration-resistant prostate cancer. Clin Cancer Res. 2019;25:687–97.

    Article  Google Scholar 

Download references

Acknowledgements

We thank the HMGC Sequencing Core at Medical College of Wisconsin for providing DNA sequencing service. We thank Paul Fletcher and Daley Drucker (H. Lee Moffitt Cancer Center and Research Center) for editorial assistance. They were not compensated beyond their regular salaries.

Funding

This study was supported by the National Institute of Health (CA212097; to LW and MK)

Author information

Authors and Affiliations

  1. Department of the Genomic Sciences and Precision Medicine Center (GSPMC), Medical College of Wisconsin, Milwaukee, WI, USA

    Meijun Du, Yijun Tian & Liang Wang

  2. Department of Oncology, Mayo Clinic, Jacksonville, FL, USA

    Winston Tan

  3. Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA

    Liewei Wang

  4. Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA

    Liguo Wang

  5. Department of Medicine, Medical College of Wisconsin and Milwaukee VA Medical Center, Milwaukee, WI, USA

    Deepak Kilari

  6. Department of Biostatistics, University of Wisconsin, Milwaukee, WI, USA

    Chiang-Ching Huang

  7. Department of Tumor Biology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA

    Liang Wang

  8. Division of Oncology, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA

    Manish Kohli

Authors
  1. Meijun Du
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yijun Tian
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Winston Tan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Liewei Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Liguo Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Deepak Kilari
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Chiang-Ching Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Liang Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Manish Kohli
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Liang Wang or Manish Kohli.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Du, M., Tian, Y., Tan, W. et al. Plasma cell-free DNA-based predictors of response to abiraterone acetate/prednisone and prognostic factors in metastatic castration-resistant prostate cancer. Prostate Cancer Prostatic Dis 23, 705–713 (2020). https://doi.org/10.1038/s41391-020-0224-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41391-020-0224-4

This article is cited by

Search

Advanced search

Quick links