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Tumor Biology

, Volume 37, Issue 8, pp 10115–10122 | Cite as

Use of two gene panels for prostate cancer diagnosis and patient risk stratification

  • Kefeng Xiao
  • Jinan Guo
  • Xuhui Zhang
  • Xiaoyan Feng
  • Heqiu Zhang
  • Zhiqiang Cheng
  • Heather Johnson
  • Jenny L. Persson
  • Lingwu Chen
Original Article

Abstract

Currently, no ideal prostate cancer (PCa) diagnostic or prognostic test is available due to the lack of biomarkers with high sensitivity and specificity. There is an unmet medical need to develop combinations of multiple biomarkers which may have higher accuracy in detection of PCa and stratification of aggressive and indolent cancer patients. The aim of this study was to test two biomarker gene panels in distinguishing PCa from benign prostate and high-risk, aggressive PCa from low-risk, indolent PCa, respectively. We identified a five-gene panel that can be used to distinguish PCa from benign prostate. The messenger RNA (mRNA) expression signature of the five genes was determined in 144 PCa and benign prostate specimens from prostatectomy. We showed that the five-gene panel distinguished PCa from benign prostate with sensitivity of 96.59 %, specificity of 92.86 %, and area under the curve (AUC) of 0.992 (p < 0.0001). The five-gene panel was further validated in a 137 specimen cohort and showed sensitivity of 84.62 %, specificity of 91.84 %, and AUC of 0.942 (p < 0.0001). To define subtypes of PCa for treatment guidance, we examined mRNA expression signature of an eight-gene panel in 87 PCa specimens from prostatectomy. The signature of the eight-gene panel was able to distinguish aggressive PCa (Gleason score >6) from indolent PCa (Gleason score ≤6) with sensitivity of 90.28 %, specificity of 80.00 %, and AUC of 0.967 (p < 0.0001). This panel was further validated in a 158 specimen cohort and showed significant difference between aggressive PCa and indolent PCa with sensitivity of 92.57 %, specificity of 70.00 %, and AUC of 0.962 (p < 0.0001). Our findings in assessing multiple biomarkers in combination may provide new tools to detect PCa and distinguish aggressive and indolent PCa for precision and personalized treatment. The two biomarker panels may be used in clinical settings for accurate PCa diagnosis and patient risk stratification for biomarker-guided treatment.

Keywords

Prostate cancer Prostate cancer diagnosis Prostate cancer prognosis Indolent prostate cancer Aggressive prostate cancer Prostate cancer biomarkers 

Notes

Acknowledgments

This study was supported by grants from The Swedish Cancer Foundation, the Lund University Medical Faculty Grant, the Malmö Cancer Foundation, and the Skåne University Hospital Foundation (to Jenny Persson), funds from Olympia Diagnostics, Inc. (to Heather Johnson), funds from The First Affiliated Hospital of Sun Yat-Sen University (to Lingwu Chen), funds from Shenzhen People’s Hospital (to Kefeng Xiao), and grant from the Project of Health and Family Planning Commission of Shenzhen Municipality (201402007) (to Jinan Guo).

Compliance with ethical standards

Conflicts of interest

The author Heather Johnson declares financial interest and employment with Olympia Diagnostics, Inc. No potential conflict of interest or financial interest was identified/declared by other authors.

References

  1. 1.
    Barry MJ. Evaluation of symptoms and quality of life in men with benign prostatic hyperplasia. Urology. 2001;58(6):25–32.CrossRefPubMedGoogle Scholar
  2. 2.
    Schröder FH. PSA screening—a review of recent studies. Eur J Cancer. 2009;45(1):402–4.CrossRefPubMedGoogle Scholar
  3. 3.
    Groskopf J, Aubin S, Deras IL, Blase A, Bodrug S, Clark C, et al. APTIMA PCA3 molecular urine test: development of a method to aid in the diagnosis of prostate cancer. Clin Chem. 2006;52(6):1089–95.CrossRefPubMedGoogle Scholar
  4. 4.
    de la Taille A, Irani J, Graefen M, Chun F, de Reijke T, Kil P, et al. Clinical evaluation of the PCA3 assay in guiding initial biopsy decisions. J Urol. 2011;185(6):2119–25.CrossRefPubMedGoogle Scholar
  5. 5.
    Laxman B, Tomlins SA, Mehra R, Morris DS, Wang L, Helgeson BE, et al. Noninvasive detection of TMPRSS2:ERG fusion transcripts in the urine of men with prostate cancer. Neoplasia. 2006;8(10):885–8.CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Hessels D, Smit FP, Verhaegh GW, Witjes JA, Cornel EB, Schalken JA. Detection of TMPRSS2-ERG fusion transcripts and prostate cancer antigen 3 in urinary sediments may improve diagnosis of prostate cancer. Clin Cancer Res. 2007;13(17):5103–8.CrossRefPubMedGoogle Scholar
  7. 7.
    de la Calle C, Patil D, Wei JT, Scherr DS, Sokoll L, Chan DW, et al. Multicenter evaluation of the prostate health index to detect aggressive prostate cancer in biopsy naïve men. J Urol. 2015;194(1):65–72.CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Comstock CES, Revelo MP, Buncher CR, Knudsen KE. Impact of differential cyclin D1 expression and localisation in prostate cancer. Br J Cancer. 2007;96(6):970–9.CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Varambally S, Dhanasekaran SM, Zhou M, Barrette TR, Kumar-Sinha C, Sanda MG, et al. The polycomb group protein EZH2 is involved in progression of prostate cancer. Nature. 2002;419:624–9.CrossRefPubMedGoogle Scholar
  10. 10.
    Saramaki OR, Tammela TL, Martikainen PM, Vessella RL, Visakorpi T. The gene for polycomb group protein enhancer of zeste homolog 2 (EZH2) is amplified in late-stage prostate cancer. Genes Chrom Cancer. 2006;45:639–45.CrossRefPubMedGoogle Scholar
  11. 11.
    Varambally S, Laxman B, Mehra R, Cao Q, Dhanasekaran SM, Tomlins SA, et al. Golgi protein GOLM1 is a tissue and urine biomarker of prostate cancer. Neoplasia. 2008;10(11):1285–94.CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Harries LW, Perry JRB, McCullagh P, Crundwell M. Alterations in LMTK2, MSMB and HNF1B gene expression are associated with the development of prostate cancer. BMC Cancer. 2010;10:315–27.CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Shin YJ, Kim J. The role of EZH2 in the regulation of the activity of matrix metalloproteinases in prostate cancer cells. PLoS One. 2012;7(1):e30393.CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Kojima S, Enokida H, Yoshino H, Itesako T, Chiyomaru T, Kinoshita T, et al. The tumor-suppressive microRNA-143/145 cluster inhibits cell migration and invasion by targeting GOLM1 in prostate cancer. J Hum Genet. 2014;59(2):78–87.CrossRefPubMedGoogle Scholar
  15. 15.
    Merola R, Tomao L, Antenucci A, Sperduti I, Sentinelli S, Masi S, et al. PCA3 in prostate cancer and tumor aggressiveness detection on 407 high-risk patients: a National Cancer Institute experience. J Exp Clin Cancer Res. 2015;34(1):15.CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Irshad S, Bansal M, Castillo-Martin M, Zheng T, Aytes A, Wenske S, et al. A molecular signature predictive of indolent prostate cancer. Sci Transl Med. 2013;5(202):202ra122.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Kelly KA, Setlur SR, Ross R, Anbazhagan R, Waterman P, Rubin MA, et al. Detection of early prostate cancer using a hepsin-targeted imaging agent. Cancer Res. 2008;68(7):2286–91.CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Goel MM, Agrawal D, Natu SM, Goel A. Hepsin immunohistochemical expression in prostate cancer in relation to Gleason’s grade and serum prostate specific antigen. Indian J Pathol Microbiol. 2011;54(3):476–81.CrossRefPubMedGoogle Scholar
  19. 19.
    Hudson BD, Kulp KS, Loots GG. Prostate cancer invasion and metastasis: insights from mining genomic data. Brief Funct Genomics. 2013;12(5):397–410.CrossRefPubMedGoogle Scholar
  20. 20.
    Tang X, Mahaja SS, Nguyen LT, Béliveau F, Leduc R, Simo JA, et al. Targeted inhibition of cell-surface serine protease hepsin blocks prostate cancer bone metastasis. Oncotarget. 2014;5(5):1352–62.CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Jamaspishvili T, Kral M, Khomeriki I, Student V, Kolar Z, Bouchal J. Urine markers in monitoring for prostate cancer. Prostate Cancer Prostatic Dis. 2010;13(1):12–9.CrossRefPubMedGoogle Scholar
  22. 22.
    Laxman B, Morris DS, Yu J, Siddiqui J, Cao J, Mehra R, et al. A first-generation multiplex biomarker analysis of urine for the early detection of prostate cancer. Cancer Res. 2008;68(3):645–9.CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Bishoff JT, Freedland SJ, Gerber L, Tennstedt P, Reid J, Welbourn W, et al. Prognostic utility of the cell cycle progression score generated from biopsy in men treated with prostatectomy. J Urol. 2014;192:409–14.CrossRefPubMedGoogle Scholar
  24. 24.
    Wu CL, Schroeder BE, Ma XJ, Cutie CJ, Wu S, Salunga R, et al. Development and validation of a 32-gene prognostic index for prostate cancer progression. Proc Natl Acad Sci. 2013;110:6121–6.CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Klein EA, Cooperberg MR, Magi-Galluzzi C, Simko JP, Falzarano SM, Maddala T, et al. A 17-gene assay to predict prostate cancer aggressiveness in the context of Gleason grade heterogeneity, tumor multifocality, and biopsy undersampling. Eur Urol. 2014;66:550–60.CrossRefPubMedGoogle Scholar
  26. 26.
    Köksal IT, Ozcan F, Kadioglu TC, Esen T, Kiliçaslan I, Tunç M. Discrepancy between Gleason scores of biopsy and radical prostatectomy specimens. Eur Urol. 2000;37(6):670–4.CrossRefPubMedGoogle Scholar

Copyright information

© International Society of Oncology and BioMarkers (ISOBM) 2016

Authors and Affiliations

  • Kefeng Xiao
    • 1
  • Jinan Guo
    • 1
  • Xuhui Zhang
    • 2
  • Xiaoyan Feng
    • 2
  • Heqiu Zhang
    • 2
  • Zhiqiang Cheng
    • 3
  • Heather Johnson
    • 4
  • Jenny L. Persson
    • 5
  • Lingwu Chen
    • 6
  1. 1.Department of UrologyJinan University School of Medicine and Shenzhen People’s HospitalShenzhenChina
  2. 2.Department of Bio-Diagnosis, Institute of Basic Medical SciencesBeijingChina
  3. 3.Department of PathologyJinan University School of Medicine and Shenzhen People’s HospitalShenzhenChina
  4. 4.Olympia Diagnostics, Inc.SunnyvaleUSA
  5. 5.Department of Translational MedicineLund UniversityMalmöSweden
  6. 6.Department of UrologyThe First Affiliated Hospital of Sun Yat-Sen UniversityGuangzhouChina

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