Skip to main content
SpringerLink
Log in

Renal Cell Carcinoma Biomarkers in Proximal Fluids

  • Chapter
  • First Online:
Cancer Biomarkers in Body Fluids

  • 456 Accesses

Abstract

Key Topics

  • Epidemiology and risk factors of renal cell carcinoma (RCC)

  • Urine and proximal fluid of urogenital tract cancers

  • RCC biomarkers in urine

  • Non-urogenital tract cancer biomarkers in urine

Key Points

  • RCC is the commonest histopathologic variant of renal tumors.

  • It is the 14th most diagnosed cancer globally.

  • Because of late diagnosis, RCC is often associated with poor prognosis.

  • RCC biomarkers in urine should augment early detection efforts.

  • Given the different structures associated with the urogenital tract, identifying RCC-specific biomarkers in urine has been challenging.

  • Promising biomarkers including aquaporin 1 and perilipin 2 have been identified and validated.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bosschieter J, Bach S, Bijnsdorp IV, et al. A protocol for urine collection and storage prior to DNA methylation analysis. PLoS One. 2018;13:e0200906.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Morrissey JJ, Mellnick VM, Luo J, et al. Evaluation of urine aquaporin-1 and perilipin-2 concentrations as biomarkers to screen for renal cell carcinoma: a prospective cohort study. JAMA Oncol. 2015;1:204–12.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Morrissey JJ, Mobley J, Figenshau RS, et al. Urine aquaporin 1 and perilipin 2 differentiate renal carcinomas from other imaged renal masses and bladder and prostate cancer. Mayo Clin Proc. 2015;90:35–42.

    Article  CAS  PubMed  Google Scholar 

  4. Song JB, Morrissey JJ, Mobley JM, et al. Urinary aquaporin 1 and perilipin 2: can these novel markers accurately characterize small renal masses and help guide patient management? Int J Urol. 2019;26:260–5.

    Article  CAS  PubMed  Google Scholar 

  5. Morrissey JJ, Mobley J, Song J, et al. Urinary concentrations of aquaporin-1 and perilipin-2 in patients with renal cell carcinoma correlate with tumor size and stage but not grade. Urology. 2014;83:256 e259–14.

    Article  Google Scholar 

  6. Morrissey JJ, Kharasch ED. The specificity of urinary aquaporin 1 and perilipin 2 to screen for renal cell carcinoma. J Urol. 2013;189:1913–20.

    Article  CAS  PubMed  Google Scholar 

  7. Sreedharan S, Petros JA, Master VA, et al. Aquaporin-1 protein levels elevated in fresh urine of renal cell carcinoma patients: potential use for screening and classification of incidental renal lesions. Dis Markers. 2014;2014:135649.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Mijuskovic M, Stanojevic I, Milovic N, et al. Tissue and urinary KIM-1 relate to tumor characteristics in patients with clear renal cell carcinoma. Int Urol Nephrol. 2018;50:63–70.

    Article  CAS  PubMed  Google Scholar 

  9. Morrissey JJ, London AN, Lambert MC, Kharasch ED. Sensitivity and specificity of urinary neutrophil gelatinase-associated lipocalin and kidney injury molecule-1 for the diagnosis of renal cell carcinoma. Am J Nephrol. 2011;34:391–8.

    Article  CAS  PubMed  Google Scholar 

  10. Vasudev NS, Sim S, Cairns DA, et al. Pre-operative urinary cathepsin D is associated with survival in patients with renal cell carcinoma. Br J Cancer. 2009;101:1175–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Yang Y, Xu J, Zhang Q. Detection of urinary survivin using a magnetic particles-based chemiluminescence immunoassay for the preliminary diagnosis of bladder cancer and renal cell carcinoma combined with LAPTM4B. Oncol Lett. 2018;15:7923–33.

    PubMed  PubMed Central  Google Scholar 

  12. Kaya K, Ayan S, Gokce G, et al. Urinary nuclear matrix protein 22 for diagnosis of renal cell carcinoma. Scand J Urol Nephrol. 2005;39:25–9.

    Article  CAS  PubMed  Google Scholar 

  13. Huang S, Rhee E, Patel H, et al. Urinary NMP22 and renal cell carcinoma. Urology. 2000;55:227–30.

    Article  CAS  PubMed  Google Scholar 

  14. Teratani T, Domoto T, Kuriki K, et al. Detection of transcript for brain-type fatty acid-binding protein in tumor and urine of patients with renal cell carcinoma. Urology. 2007;69:236–40.

    Article  PubMed  Google Scholar 

  15. Minamida S, Iwamura M, Kodera Y, et al. 14-3-3 protein beta/alpha as a urinary biomarker for renal cell carcinoma: proteomic analysis of cyst fluid. Anal Bioanal Chem. 2011;401:245–52.

    Article  CAS  PubMed  Google Scholar 

  16. Kaneko S, Matsumoto K, Minamida S, et al. Incremental expression of 14-3-3 protein beta/alpha in urine correlates with advanced stage and poor survival in patients with clear cell renal cell carcinoma. Asian Pac J Cancer Prev. 2016;17:1399–404.

    Article  PubMed  Google Scholar 

  17. Sandim V, Pereira Dde A, Kalume DE, et al. Proteomic analysis reveals differentially secreted proteins in the urine from patients with clear cell renal cell carcinoma. Urol Oncol. 2016;34(5):e11–25.

    Google Scholar 

  18. Chinello C, Cazzaniga M, De Sio G, et al. Tumor size, stage and grade alterations of urinary peptidome in RCC. J Transl Med. 2015;13:332.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Papale M, Vocino G, Lucarelli G, et al. Urinary RKIP/p-RKIP is a potential diagnostic and prognostic marker of clear cell renal cell carcinoma. Oncotarget. 2017;8:40412–24.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Frantzi M, Metzger J, Banks RE, et al. Discovery and validation of urinary biomarkers for detection of renal cell carcinoma. J Proteome. 2014;98:44–58.

    Article  CAS  Google Scholar 

  21. Wu DL, Zhang WH, Wang WJ, et al. Proteomic evaluation of urine from renal cell carcinoma using SELDI-TOF-MS and tree analysis pattern. Technol Cancer Res Treat. 2008;7:155–60.

    Article  CAS  PubMed  Google Scholar 

  22. Bosso N, Chinello C, Picozzi SC, et al. Human urine biomarkers of renal cell carcinoma evaluated by ClinProt. Proteomics Clin Appl. 2008;2:1036–46.

    Article  CAS  PubMed  Google Scholar 

  23. Alves G, Pereira DA, Sandim V, et al. Urine screening by Seldi-Tof, followed by biomarker identification, in a Brazilian cohort of patients with renal cell carcinoma (RCC). Int Braz J Urol. 2013;39:228–39.

    Article  PubMed  Google Scholar 

  24. Mandili G, Notarpietro A, Khadjavi A, et al. Beta-2-glycoprotein-1 and alpha-1-antitrypsin as urinary markers of renal cancer in von Hippel-Lindau patients. Biomarkers. 2018;23:123–30.

    Article  CAS  PubMed  Google Scholar 

  25. von Brandenstein M, Pandarakalam JJ, Kroon L, et al. MicroRNA 15a, inversely correlated to PKCalpha, is a potential marker to differentiate between benign and malignant renal tumors in biopsy and urine samples. Am J Pathol. 2012;180:1787–97.

    Article  Google Scholar 

  26. Mytsyk Y, Dosenko V, Borys Y, et al. MicroRNA-15a expression measured in urine samples as a potential biomarker of renal cell carcinoma. Int Urol Nephrol. 2018;50:851–9.

    Article  CAS  PubMed  Google Scholar 

  27. Petrozza V, Pastore AL, Palleschi G, et al. Secreted miR-210-3p as non-invasive biomarker in clear cell renal cell carcinoma. Oncotarget. 2017;8:69551–8.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Butz H, Nofech-Mozes R, Ding Q, et al. Exosomal MicroRNAs are diagnostic biomarkers and can mediate cell-cell communication in renal cell carcinoma. Eur Urol Focus. 2016;2:210–8.

    Article  PubMed  Google Scholar 

  29. Fedorko M, Juracek J, Stanik M, et al. Detection of let-7 miRNAs in urine supernatant as potential diagnostic approach in non-metastatic clear-cell renal cell carcinoma. Biochem Med (Zagreb). 2017;27:411–7.

    Article  Google Scholar 

  30. Li G, Zhao A, Peoch M, et al. Detection of urinary cell-free miR-210 as a potential tool of liquid biopsy for clear cell renal cell carcinoma. Urol Oncol. 2017;35:294–9.

    Article  CAS  PubMed  Google Scholar 

  31. Iliev R, Fedorko M, Machackova T, et al. Expression levels of PIWI-interacting RNA, piR-823, are deregulated in tumor tissue, blood serum and urine of patients with renal cell carcinoma. Anticancer Res. 2016;36:6419–23.

    Article  CAS  PubMed  Google Scholar 

  32. Gatto F, Volpi N, Nilsson H, et al. Glycosaminoglycan profiling in patients’ plasma and urine predicts the occurrence of metastatic clear cell renal cell carcinoma. Cell Rep. 2016;15:1822–36.

    Article  CAS  PubMed  Google Scholar 

  33. Gatto F, Maruzzo M, Magro C, et al. Prognostic value of plasma and urine glycosaminoglycan scores in clear cell renal cell carcinoma. Front Oncol. 2016;6:253.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Sarica K, Turkolmez K, Soygur T, et al. Evaluation of urinary glycosaminoglycan excretion in patients with renal cell carcinoma. Eur Urol. 1997;31:54–7.

    Article  CAS  PubMed  Google Scholar 

  35. Niziol J, Bonifay V, Ossolinski K, et al. Metabolomic study of human tissue and urine in clear cell renal carcinoma by LC-HRMS and PLS-DA. Anal Bioanal Chem. 2018;410:3859–69.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Falegan OS, Ball MW, Shaykhutdinov RA, et al. Urine and serum metabolomics analyses may distinguish between stages of renal cell carcinoma. Metabolites. 2017;7:E6.

    Article  PubMed  Google Scholar 

  37. Zhang L, Li L, Kong H, Zeng F. Urinary metabolomics study of renal cell carcinoma based on gas chromatography-mass spectrometry. Nan Fang Yi Ke Da Xue Xue Bao. 2015;35:763–6.

    PubMed  Google Scholar 

  38. Kim K, Taylor SL, Ganti S, et al. Urine metabolomic analysis identifies potential biomarkers and pathogenic pathways in kidney cancer. OMICS. 2011;15:293–303.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Monteiro M, Moreira N, Pinto J, et al. GC-MS metabolomics-based approach for the identification of a potential VOC-biomarker panel in the urine of renal cell carcinoma patients. J Cell Mol Med. 2017;21:2092–105.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Wang D, Wang C, Pi X, et al. Urinary volatile organic compounds as potential biomarkers for renal cell carcinoma. Biomed Rep. 2016;5:68–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Minciu R, Tudor A, Pupca G, et al. Renal cancer diagnosed by noninvasive methods from body fluids by quantitative methylation-specific PCR(qMSP). Clin Lab. 2016;62:1563–8.

    CAS  PubMed  Google Scholar 

  42. De Palma G, Sallustio F, Curci C, et al. The three-gene signature in urinary extracellular vesicles from patients with clear cell renal cell carcinoma. J Cancer. 2016;7:1960–7.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Raimondo F, Morosi L, Corbetta S, et al. Differential protein profiling of renal cell carcinoma urinary exosomes. Mol BioSyst. 2013;9:1220–33.

    Article  CAS  PubMed  Google Scholar 

  44. Erbes T, Hirschfeld M, Rucker G, et al. Feasibility of urinary microRNA detection in breast cancer patients and its potential as an innovative non-invasive biomarker. BMC Cancer. 2015;15:193.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Pories SE, Zurakowski D, Roy R, et al. Urinary metalloproteinases: noninvasive biomarkers for breast cancer risk assessment. Cancer Epidemiol Biomark Prev. 2008;17:1034–42.

    Article  CAS  Google Scholar 

  46. Nyren-Erickson EK, Bouton M, Raval M, et al. Urinary concentrations of ADAM 12 from breast cancer patients pre- and post-surgery vs. cancer-free controls: a clinical study for biomarker validation. J Negat Results Biomed. 2014;13:5.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Yang J, Bielenberg DR, Rodig SJ, et al. Lipocalin 2 promotes breast cancer progression. Proc Natl Acad Sci U S A. 2009;106:3913–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Hu T, Shen H, Huang H, et al. Urinary circulating DNA profiling in non-small cell lung cancer patients following treatment shows prognostic potential. J Thorac Dis. 2018;10:4137–46.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Xie F, Li P, Gong J, et al. Urinary cell-free DNA as a prognostic marker for KRAS-positive advanced-stage NSCLC. Clin Transl Oncol. 2018;20:591–8.

    Article  CAS  PubMed  Google Scholar 

  50. Li F, Huang J, Ji D, et al. Utility of urinary circulating tumor DNA for EGFR mutation detection in different stages of non-small cell lung cancer patients. Clin Transl Oncol. 2017;19:1283–91.

    Article  CAS  PubMed  Google Scholar 

  51. Chen S, Zhao J, Cui L, Liu Y. Urinary circulating DNA detection for dynamic tracking of EGFR mutations for NSCLC patients treated with EGFR-TKIs. Clin Transl Oncol. 2017;19:332–40.

    Article  CAS  PubMed  Google Scholar 

  52. Sands J, Li Q, Hornberger J. Urine circulating-tumor DNA (ctDNA) detection of acquired EGFR T790M mutation in non-small-cell lung cancer: an outcomes and total cost-of-care analysis. Lung Cancer. 2017;110:19–25.

    Article  PubMed  Google Scholar 

  53. Zhang C, Leng W, Sun C, et al. Urine proteome profiling predicts lung Cancer from control cases and other tumors. EBioMedicine. 2018;30:120–8.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Wang W, Wang S, Zhang M. Identification of urine biomarkers associated with lung adenocarcinoma. Oncotarget. 2017;8:38517–29.

    PubMed  PubMed Central  Google Scholar 

  55. Nolen BM, Lomakin A, Marrangoni A, et al. Urinary protein biomarkers in the early detection of lung cancer. Cancer Prev Res (Phila). 2015;8:111–9.

    Article  CAS  Google Scholar 

  56. Takahashi Y, Sakaguchi K, Horio H, et al. Urinary N1, N12-diacetylspermine is a non-invasive marker for the diagnosis and prognosis of non-small-cell lung cancer. Br J Cancer. 2015;113:1493–501.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Burton C, Ma Y. Current trends in cancer biomarker discovery using urinary metabolomics: achievements and new challenges. Curr Med Chem. 2019;26:5–28.

    Article  CAS  PubMed  Google Scholar 

  58. Cui Y, Shu XO, Li HL, et al. Prospective study of urinary prostaglandin E2 metabolite and pancreatic cancer risk. Int J Cancer. 2017;141:2423–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Weeks ME, Hariharan D, Petronijevic L, et al. Analysis of the urine proteome in patients with pancreatic ductal adenocarcinoma. Proteomics Clin Appl. 2008;2:1047–57.

    Article  CAS  PubMed  Google Scholar 

  60. Roy R, Zurakowski D, Wischhusen J, et al. Urinary TIMP-1 and MMP-2 levels detect the presence of pancreatic malignancies. Br J Cancer. 2014;111:1772–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Schonemeier B, Metzger J, Klein J, et al. Urinary peptide analysis differentiates pancreatic cancer from chronic pancreatitis. Pancreas. 2016;45:1018–26.

    Article  PubMed  Google Scholar 

  62. Davis VW, Schiller DE, Eurich D, et al. Pancreatic ductal adenocarcinoma is associated with a distinct urinary metabolomic signature. Ann Surg Oncol. 2013;20(Suppl 3):S415–23.

    Article  PubMed  Google Scholar 

  63. Debernardi S, Massat NJ, Radon TP, et al. Noninvasive urinary miRNA biomarkers for early detection of pancreatic adenocarcinoma. Am J Cancer Res. 2015;5:3455–66.

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Zavesky L, Jandakova E, Turyna R, et al. Evaluation of cell-free urine microRNAs expression for the use in diagnosis of ovarian and endometrial cancers. A pilot study. Pathol Oncol Res. 2015;21:1027–35.

    Article  CAS  PubMed  Google Scholar 

  65. Zhou J, Gong G, Tan H, et al. Urinary microRNA-30a-5p is a potential biomarker for ovarian serous adenocarcinoma. Oncol Rep. 2015;33:2915–23.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Medical Sciences Division, Northern Ontario School of Medicine, Thunder Bay, ON, Canada

    Gabriel D. Dakubo

Authors
  1. Gabriel D. Dakubo
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Dakubo, G.D. (2019). Renal Cell Carcinoma Biomarkers in Proximal Fluids. In: Cancer Biomarkers in Body Fluids. Springer, Cham. https://doi.org/10.1007/978-3-030-24725-6_7

Download citation

Publish with us

Policies and ethics

Search

Navigation