Skip to main content

Advertisement

Springer Nature Link
Log in

Clinical significance of novel DNA methylation biomarkers for renal clear cell carcinoma

  • Original Article – Cancer Research
  • Published:
Journal of Cancer Research and Clinical Oncology Aims and scope Submit manuscript

Abstract

Objective

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney tumor characterized by the highest mortality rate of the genitourinary cancers, and, therefore, new diagnostic and/or prognostic biomarkers are urgently needed.

Methods

Based on genome-wide DNA methylation profiling in 11 pairs of ccRCC and non-cancerous renal tissues (NRT), the methylation at regulatory regions of ZNF677, FBN2, PCDH8, TFAP2B, TAC1, and FLRT2 was analyzed in 168 renal tissues and 307 urine samples using qualitative and quantitative methylation-specific PCR (MSP).

Results

Significantly higher methylation frequencies for all genes were found in ccRCC tissues compared to NRT (33–60% vs. 0–11%). The best diagnostic performance demonstrated a panel of ZNF677, FBN2, PCDH8, TFAP2B & TAC1 with 82% sensitivity and 96% specificity. Hypermethylation of ZNF677 and PCDH8 in the tissue samples was significantly related to numerous adverse clinicopathologic parameters. For the urine-based ccRCC detection, the highest diagnostic power (AUC = 0.78) was observed for a panel of ZNF677 & PCDH8 (with or without FBN2 or FLRT2) with 69–78% sensitivity and 69–80% specificity, albeit with lower values in the validation cohort. Besides, methylation of PCDH8 was significantly related to higher tumor stage and fat invasion in the study and validation cohorts. Moreover, PCDH8 was strongly predictive for OS (HR, 5.7; 95% CI 1.16–28.12), and its prognostic power considerably increased in combination with ZNF677 (HR, 12.5; 95% CI 1.47–105.58).

Conclusion

In summary, our study revealed novel, potentially promising DNA methylation biomarkers of ccRCC with the possibility to be applied for non-invasive urine-based ccRCC detection and follow-up.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Availability of data and materials

All data supporting the results reported in the article is available from the corresponding author upon a reasonable request.

Abbreviations

AUC:

Area under the curve

ASC:

Asymptomatic control

ccRCC:

Clear cell renal cell carcinoma

CI:

Confidence interval

MC:

In vitro methylated control

MSP:

Methylation-specific polymerase chain reaction

qMSP:

Quantitative methylation-specific polymerase chain reaction

NRT:

Non-cancerous renal tissue

NTC:

No-template control

HR:

Hazard ratio

UC:

Unmethylated control

M:

Methylated

U:

Unmethylated

ROC:

Receiver operating characteristic

AUC:

Area under the curve

DSe:

Diagnostic sensitivity

DSp:

Diagnostic specificity

WHO/ISUP:

World health organization/International Society of Urological Pathology

References

  • Bae H, Kim B, Lee H, Lee S, Kang HS, Kim SJ (2017) Epigenetically regulated Fibronectin leucine rich transmembrane protein 2 (FLRT2) shows tumor suppressor activity in breast cancer cells. Sci Rep 7(1):272

    Article  PubMed  PubMed Central  Google Scholar 

  • Bakavicius A, Daniunaite K, Zukauskaite K, Barisiene M, Jarmalaite S, Jankevicius F (2019) Urinary DNA methylation biomarkers for prediction of prostate cancer upgrading and upstaging. Clin Epigenet 11(1):115

    Article  Google Scholar 

  • Battagli C, Uzzo RG, Dulaimi E, Ibanez de Caceres I, Krassenstein R, Al-Saleem T et al (2003) Promoter hypermethylation of tumor suppressor genes in urine from kidney cancer patients. Cancer Res 63:8695–8699

    CAS  PubMed  Google Scholar 

  • Bedke J, Buse S, Pritsch M, Macher-Goeppinger S, Schirmacher P, Haferkamp A et al (2009) Perinephric and renal sinus fat infiltration in pT3a renal cell carcinoma: possible prognostic differences. BJU Int 103(10):1349–1354

    Article  PubMed  Google Scholar 

  • Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig L et al (2015) STARD Group. STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. BMJ 351:h5527

    Article  PubMed  PubMed Central  Google Scholar 

  • Capitanio U, Bensalah K, Bex A et al (2019) Epidemiology of renal cell carcinoma. Eur Urol 75(1):74–84

    Article  PubMed  Google Scholar 

  • Chow WH, Dong LM, Devesa SS (2010) Epidemiology and risk factors for kidney cancer. Nat Rev Urol 7:245–257

    Article  PubMed  PubMed Central  Google Scholar 

  • Costa VL, Henrique R, Danielsen SA, Knaes M, Patrício P, Morais A et al (2011) TCF21 and PCDH17 methylation: an innovative panel of biomarkers for a simultaneous detection of urological cancers. Epigenetics 6:1120–1130

    Article  CAS  PubMed  Google Scholar 

  • Daniunaite K, Jarmalaite S, Kalinauskaite N, Petroska D, Laurinavicius A, Lazutka JR et al (2014) Prognostic value of RASSF1 promoter methylation in prostate cancer. J Urol 192(6):1849–1855

    Article  CAS  PubMed  Google Scholar 

  • Daniunaite K, Serenaite I, Misgirdaite R, Gordevicius J, Unguryte A, Fleury-Cappellesso S et al (2015) Epigenetic regulation of human adipose-derived stem cells differentiation. Mol Cell Biochem 410:111–120

    Article  CAS  PubMed  Google Scholar 

  • Daniūnaitė K, Jarmalaitė S, Kriukienė E (2019) Epigenomic technologies for deciphering circulating tumor DNA. Curr Opin Biotechnol 55:23–29

    Article  PubMed  Google Scholar 

  • Delahunt B, Cheville JC, Martignoni G, Humphrey PA, Magi-Galluzzi C, McKenney J et al (2013) The International Society of Urological Pathology (ISUP) grading system for renal cell carcinoma and other prognostic parameters. Am J Surg Pathol 37:1490

    Article  PubMed  Google Scholar 

  • Eckert D, Buhl S, Weber S, Jäger R, Schorle H (2005) The AP-2 family of transcription factors. Genome Biol 6(13):246

    Article  PubMed  PubMed Central  Google Scholar 

  • Flintoff KA, Arudchelvan Y, Gong SG (2014) FLRT2 interacts with fibronectin in the ATDC5 chondroprogenitor cells. J Cell Physiol 229(10):1538–1547

    Article  CAS  PubMed  Google Scholar 

  • Fuhrman SA, Lasky LC, Limas C (1982) Prognostic significance of morphologic parameters in renal cell carcinoma. Am J Surg Pathol 6:655–663

    Article  CAS  PubMed  Google Scholar 

  • Gerlinger M, Horswell S, Larkin J, Rowan AJ, Salm MP, Varela I et al (2014) Genomic architecture and evolution of clear cell renal cell carcinomas defined by multiregion sequencing. Nat Genet 46(3):225–233

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Heller G, Altenberger C, Schmid B, Marhold M, Tomasich E, Ziegler B et al (2015) DNA methylation transcriptionally regulates the putative tumor cell growth suppressor ZNF677 in non-small cell lung cancers. Oncotarget 6:394–408

    Article  PubMed  Google Scholar 

  • Hoque MO, Begum S, Topaloglu O, Jeronimo C, Mambo E, Westra WH et al (2004) Quantitative detection of promoter hypermethylation of multiple genes in the tumor, urine, and serum DNA of patients with renal cancer. Cancer Res 64(15):5511–5517

    Article  CAS  PubMed  Google Scholar 

  • Hsieh JJ, Purdue MP, Signoretti S, Swanton C, Albiges L, Schmidinger M et al (2017a) Renal cell carcinoma. Nat Rev Dis Primers 3:17009

    Article  PubMed  PubMed Central  Google Scholar 

  • Hsieh JJ, Manley BJ, Khan N, Gao JJ, Carlo MI, Cheng EH (2017b) Overcome tumor heterogeneity-imposed therapeutic barriers through convergent genomic biomarker discovery: a braided cancer river model of kidney cancer. Semin Cell Dev Biol 64:98–106

    Article  CAS  PubMed  Google Scholar 

  • Hu CY, Mohtat D, Yu Y, Ko YA, Shenoy N, Bhattacharya S et al (2014) Kidney cancer is characterized by aberrant methylation of tissue-specific enhancers that are prognostic for overall survival. Clin Cancer Res 20(16):4349–4360

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Jayson M, Sanders H (1998) Increased incidence of serendipitously discovered renal cell carcinoma. Urology 51(2):203–205

    Article  CAS  PubMed  Google Scholar 

  • Kabaria R, Klaassen Z, Terris MK (2016) Renal cell carcinoma: links and risks. Int J Nephrol Renovasc Dis 9:45–52

    PubMed  PubMed Central  Google Scholar 

  • Kubiliute R, Jarmalaite S (2021) Epigenetic biomarkers of renal cell carcinoma for liquid biopsy tests. Int J Mol Sci 22(16):8846

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Larsen LK, Lind GE, Guldberg P, Dahl Ch (2019) DNA-methylation-based detection of urological cancer in urine: overview of biomarkers and considerations on biomarker design, source of DNA, and detection technologies. Int J Mol Sci 20(11):2657

    Article  CAS  PubMed Central  Google Scholar 

  • Lasseigne BN, Brooks JD (2018) The role of DNA methylation in renal cell carcinoma. Mol Diagn Ther 22(4):431–442

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lehmann U, Langer F, Feist H, Glöckner S, Hasemeier B, Kreipe H (2002) Quantitative assessment of promoter hypermethylation during breast cancer development. Am J Pathol 160(2):605–612

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Li Y, Yang Q, Guan H, Shi B, Ji M, Hou P (2018) ZNF677 suppresses Akt phosphorylation and tumorigenesis in thyroid cancer. Cancer Res 78(18):5216–5228

    Article  CAS  PubMed  Google Scholar 

  • Li L, Shi L, Zhang J, Fan Y, Li Q (2021) The critical impact of tumor size in predicting cancer special survival for T3aM0M0 renal cell carcinoma: A proposal of an alternative T3aN0M0 stage. Cancer Med 10(2):605–614

    Article  CAS  PubMed  Google Scholar 

  • Lin YL, Wang YL, Fu XL, Ma JG (2014) Aberrant methylation of PCDH8 is a potential prognostic biomarker for patients with clear cell renal cell carcinoma. Med Sci Monit 20:2380–2385

    Article  PubMed  PubMed Central  Google Scholar 

  • Lin Y, Ge X, Zhang X, Wu Z, Liu K, Lin F et al (2018) Protocadherin-8 promotes invasion and metastasis via laminin subunit γ2 in gastric cancer. Cancer Sci 109(3):732–740

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lopez-Beltran A, Scarpelli M, Montironi R, Kirkali Z (2006) 2004 WHO classification of the renal tumors of the adults. Eur Urol 49:798–805

    Article  PubMed  Google Scholar 

  • Lu T, Li J (2017) Clinical applications of urinary cell-free DNA in cancer: current insights and promising future. Am J Cancer Res 7(11):2318–2332

    CAS  PubMed  PubMed Central  Google Scholar 

  • Maleckaite R, Zalimas A, Bakavicius A, Jankevicius F, Jarmalaite S, Daniunaite K (2019) DNA methylation of metallothionein genes is associated with the clinical features of renal cell carcinoma. Oncol Rep 41(6):3535–3544

    CAS  PubMed  Google Scholar 

  • McMahon KW, Karunasena E, Ahuja N (2017) The roles of DNA methylation in the stages of cancer. Cancer J 23(5):257–261

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Morris MR, Ricketts CJ, Gentle D, McRonald F, Carli N, Khalili H et al (2011) Genome-wide methylation analysis identifies epigenetically inactivated candidate tumor suppressor genes in renal cell carcinoma. Oncogene 30(12):1390–1401

    Article  CAS  PubMed  Google Scholar 

  • Moser M, Pscherer A, Roth C, Becker J, Mücher G, Zerres K et al (1997) Enhanced apoptotic cell death of renal epithelial cells in mice lacking transcription factor AP-2beta. Genes Dev 11(15):1938–1948

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Neuzillet C, Tijeras-Raballand A, Cohen R, Cros J, Faivre S, Raymond E et al (2015) Targeting the TGFbeta pathway for cancer therapy. Pharmacol Ther 147:22–31

    Article  CAS  PubMed  Google Scholar 

  • Outeiro-Pinho G, Barros-Silva D, Aznar E, Sousa AI, Vieira-Coimbra M, Oliveira J et al (2020) MicroRNA-30a-5pme: a novel diagnostic and prognostic biomarker for clear cell renal cell carcinoma in tissue and urine samples. J Exp Clin Cancer Res 39(1):98

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Pires-Luís AS, Costa-Pinheiro P, Ferreira MJ, Antunes L, Lobo F, Oliveira J et al (2017) Identification of clear cell renal cell carcinoma and oncocytoma using a three-gene promoter methylation panel. J Transl Med 15:149

    Article  PubMed  PubMed Central  Google Scholar 

  • Rameshwar P, Gascón P (1996) Induction of negative hematopoietic regulators by neurokinin-A in bone marrow stroma. Blood 88(1):98–106

    Article  CAS  PubMed  Google Scholar 

  • Ricketts CJ, Hill VK, Linehan WM (2014) Tumor-specific hypermethylation of epigenetic biomarkers, including SFRP1, predicts for poorer survival in patients from the TCGA Kidney Renal Clear Cell Carcinoma (KIRC) project. PLoS ONE 9(1):e85621

    Article  PubMed  PubMed Central  Google Scholar 

  • Rossi SH, Prezzi D, Kelly-Morland C, Goh V (2018) Imaging for the diagnosis and response assessment of renal tumours. World J Urol 36(12):1927–1942

    Article  PubMed  PubMed Central  Google Scholar 

  • Sauerbrei W, Taube SE, McShane LM, Cavenagh MM, Altman DG (2018) Reporting recommendations for tumor marker prognostic studies (REMARK): an abridged explanation and elaboration. J Natl Cancer Inst 110(8):803–811

    Article  PubMed  PubMed Central  Google Scholar 

  • Siegel RL, Miller KD, Jemal A (2015) Cancer statistics, 2015. CA Cancer J Clin 65:5–29

    Article  Google Scholar 

  • Sobin LH, Gospodarowicz MK, Wittekind C (eds) (2009) TNM classification of malignant tumours, 7th Edition. UICC International Union Against Cancer. 7:310

  • Sohlberg EM, Metzner TJ, Leppert JT (2019) The harms of overdiagnosis and overtreatment in patients with small renal masses: A mini-review. Eur Urol Focus 5(6):943–945

  • The Cancer Genome Atlas Research Network (2013) Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature 499(7456):43–49

    Article  PubMed Central  Google Scholar 

  • Turajlic S, Xu H, Litchfield K, Rowan A, Horswell S, Chambers T et al (2018a) Deterministic evolutionary trajectories influence primary tumor growth: TRACERx renal. Cell 173:595–610

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Turajlic S, Swanton Ch, Boshoff Ch (2018b) Kidney cancer: The next decade. J Exp Med 215(10):2477–2479

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • van Loon K, Yemelyanenko-Lyalenko J, Margadant C, Griffioen AW, Huijbers EJM (2020) Role of fibrillin-2 in the control of TGF-β activation in tumor angiogenesis and connective tissue disorders. Biochim Biophys Acta Rev Cancer 1873(2):188354

    Article  PubMed  Google Scholar 

  • van Vlodrop IJ, Baldewijns MM, Smits KM, Schouten LJ, van Neste L, van Criekinge W et al (2010) Prognostic significance of Gremlin1 (GREM1) promoter CpG island hypermethylation in clear cell renal cell carcinoma. Am J Pathol 176(2):575–584

    Article  PubMed  PubMed Central  Google Scholar 

  • van Vlodrop IJH, Joosten SC, De Meyer T, Smits KM, Van Neste L, Melotte V et al (2017) A four-gene promoter methylation marker panel consisting of GREM1, NEURL, LAD1, and NEFH predicts survival of clear cell renal cell cancer patients. Clin Cancer Res 23(8):2006–2018

    Article  PubMed  Google Scholar 

  • Warren AY, Harrison D (2018) WHO/ISUP classification, grading and pathological staging of renal cell carcinoma: standards and controversies. World J Urol 36(12):1913–1926

    Article  PubMed  PubMed Central  Google Scholar 

  • Williamson SR, Taneja K, Cheng L (2019) Renal cell carcinoma staging: pitfalls, challenges, and updates. Histopathology 74(1):18–30

    Article  PubMed  Google Scholar 

  • Yu JS, Koujak S, Nagase S, Li CM, Su T, Wang X et al (2008) PCDH8, the human homolog of PAPC, is a candidate tumor suppressor of breast cancer. Oncogene 27:4657–4665

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Aušra Šumskaitė, Rūta Matuliavičiūtė, and Eugenijus Ganža for their assistance in DNA samples preparation and MSP analysis.

Funding

This work was funded by the 2014–2020 European Union Structural Funds according to the activity "Intelligence. Joint science-business projects" grant No. J05-LVPA-K-04–0029. SJ and KZ were supported by the European Social Fund according to the activity "Development of students' ability to carry out R&D activities" under Measure No.09.03.3-LMT-K-712 "Development of Scientific Competences of Scientists, other Researchers and Students through Practical Research Activities" (grant No. 09.03.3-LMT-K-712–15-0214 to SJ). The study was also partially supported by the Research Council of Lithuania (RCL) grant No. S-MIP-17/54.

Author information

Authors and Affiliations

  1. Institute of Biosciences, Life Sciences Center, Vilnius University, Vilnius, Lithuania

    Raimonda Kubiliūtė, Kristina Žukauskaitė, Algirdas Žalimas & Sonata Jarmalaitė

  2. National Cancer Institute, Santariskiu 1, LT‑08406, Vilnius, Lithuania

    Raimonda Kubiliūtė, Kristina Žukauskaitė, Algirdas Žalimas, Albertas Ulys, Rasa Sabaliauskaitė, Arnas Bakavičius & Sonata Jarmalaitė

  3. Vilnius University Hospital Santaros Klinikos, Vilnius, Lithuania

    Arnas Bakavičius, Arūnas Želvys & Feliksas Jankevičius

  4. Faculty of Medicine, Institute of Clinical Medicine, Vilnius University, Vilnius, Lithuania

    Arūnas Želvys & Feliksas Jankevičius

Authors
  1. Raimonda Kubiliūtė
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Kristina Žukauskaitė
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Algirdas Žalimas
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Albertas Ulys
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Rasa Sabaliauskaitė
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Arnas Bakavičius
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Arūnas Želvys
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Feliksas Jankevičius
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Sonata Jarmalaitė
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

RK: performed the DNA methylation and gene expression analysis in the tissue samples and urine samples of the validation cohort, analyzed the experimental and clinical data and drafted the manuscript; KZ: performed the DNA methylation analysis in urine samples of the study cohort, contributed to gene expression analysis; AZ, AU, RS and AB: collected the clinical data and revised the analysis; RS and AZ: critically revised the manuscript; AU and FJ: coordinated the patient selection, supervised the clinical data analysis and was involved in the conception of the study; SJ: designed the research, supervised the analysis of the clinical and experimental data, and revised the manuscript critically for important intellectual content. All authors read and approved the manuscript and agree to be accountable for all aspects of the research in ensuring that the accuracy or integrity of any part of the work is appropriately investigated and resolved.

Corresponding author

Correspondence to Sonata Jarmalaitė.

Ethics declarations

Competing interests

RK and SJ are inventors of the patent application No. PCT/IB2021/052532. The remaining authors declare that they have no conflict of interest.

Ethics approval and consent to participate

The study was approved by the Lithuanian Bioethics Committee (Nr. 158200˗18/12˗1077˗585 for Study cohort and Nr. 158200-18/12-1077-585 for Validation cohort), and written informed consent was obtained from all patients.

Consent for publication

Not applicable.

Additional information

Publisher's Note

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

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 2260 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kubiliūtė, R., Žukauskaitė, K., Žalimas, A. et al. Clinical significance of novel DNA methylation biomarkers for renal clear cell carcinoma. J Cancer Res Clin Oncol 148, 361–375 (2022). https://doi.org/10.1007/s00432-021-03837-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00432-021-03837-7

Keywords