Prognostic Value of Systemic Inflammatory Biomarkers in Patients with Metastatic Renal Cell Carcinoma

Abstract

Metastatic renal cell carcinoma (mRCC) encompasses a heterogeneous group of neoplasms with distinct clinical behavior and prognoses. As a result of the increasing number of therapeutic options in the metastatic setting, it is crucial to improve prognostic stratification ability. We aimed to evaluate the prognostic value of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and combination platelet count and neutrophil lymphocyte ratio (COP-NLR) in patients with mRCC. We evaluated a cohort of mRCC patients treated with first-line pazopanib or sunitinib. Levels of NLR, PLR and COP-NLR were measured prior to systemic treatment and evaluated as prognostic predictors. Primary endpoint was overall survival (OS). Data from 276 patients were included, of which 54.7% received first-line pazopanib and 45.3%, sunitinib. Memorial Sloan-Kettering Cancer Center risk classification was intermediate and poor in 50% and 42.6% of patients, respectively. High NLR (> 3.5) was associated with inferior OS (median 9.6 vs 17.8 months, P < 0.001). A high PLR (> 200) was associated with inferior OS (median 10.3 vs 17 months, P = 0.002). The median OS in the COP-NLR 1, 2 and 3 groups were 19.0 months (95% CI 15.3–26.0), 13.1 months (95% CI 9.8–17.0) and 7.4 months (95% CI 3.6–11.9), respectively (P < 0.001). In the multivariate analysis, high NLR and high COP-NLR were associated with inferior OS. Both high NLR and high COP-NLR were associated with poorer OS in our cohort of patients with mRCC treated with first-line pazopanib or sunitinib.

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References

  1. 1.

    Siegel RL, Miller KD, Jemal A (2018) Cancer statistics, 2018. CA Cancer J Clin 68:7–30. https://doi.org/10.3322/caac.21442

    Article  Google Scholar 

  2. 2.

    Howlader N, Noone AM, Krapcho M, Miller D, Bishop K, Altekruse SF, Kosary CL, Yu M, Ruhl J, Tatalovich Z, Mariotto A, Lewis DR, Chen HS, Feuer EJ CK (2016) SEER Cancer statistics review, 1975–2013, National Cancer Institute. Bethesda, MD,. In: SEER web site. https://seer.cancer.gov/archive/csr/1975_2013/. Accessed 3 Apr 2018

  3. 3.

    Kidney and Renal Pelvis Cancer - Cancer Stat Facts. https://seer.cancer.gov/statfacts/html/kidrp.html. Accessed 1 May 2019

  4. 4.

    Lalani A-KA, Xie W, Martini DJ et al (2018) Change in neutrophil-to-lymphocyte ratio (NLR) in response to immune checkpoint blockade for metastatic renal cell carcinoma. J Immunother cancer 6:5. https://doi.org/10.1186/s40425-018-0315-0

    Article  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Motzer RJ, Mazumdar M, Bacik J et al (1999) Survival and prognostic stratification of 670 patients with advanced renal cell carcinoma. J Clin Oncol 17:2530–2530. https://doi.org/10.1200/JCO.1999.17.8.2530

    CAS  Article  PubMed  Google Scholar 

  6. 6.

    Heng DYC, Xie W, Regan MM et al (2009) Prognostic factors for overall survival in patients with metastatic renal cell carcinoma treated with vascular endothelial growth factor-targeted agents: results from a large, multicenter study. J Clin Oncol 27:5794–5799. https://doi.org/10.1200/JCO.2008.21.4809

    CAS  Article  PubMed  Google Scholar 

  7. 7.

    Amin MB, Edge SB, American Joint Committee on Cancer (2017) AJCC cancer staging manual, 8th ed. Springer, Switzerland

  8. 8.

    Delahunt B, Cheville JC, Martignoni G et al (2013) The International Society of Urological Pathology (ISUP) grading system for renal cell carcinoma and other prognostic parameters. Am J Surg Pathol 37:1490–1504. https://doi.org/10.1097/PAS.0b013e318299f0fb

    Article  PubMed  Google Scholar 

  9. 9.

    Wei S, Al-Saleem T (2017) The pathology and molecular genetics of Sarcomatoid renal cell carcinoma: a mini-review. J Kidney Cancer VHL 4:19–23. https://doi.org/10.15586/jkcvhl.2017.70

    Article  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Network TCGAR (2013) Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature 499:43–49. https://doi.org/10.1038/nature12222

    CAS  Article  Google Scholar 

  11. 11.

    Gerlinger M, Rowan AJ, Horswell S et al (2012) Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med 366:883–892. https://doi.org/10.1056/NEJMoa1113205

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Mantovani A, Allavena P, Sica A, Balkwill F (2008) Cancer-related inflammation. Nature 454:436–444. https://doi.org/10.1038/nature07205

    CAS  Article  PubMed  Google Scholar 

  13. 13.

    Watt DG, Proctor MJ, Park JH, et al (2015) The neutrophil-platelet score (NPS) predicts survival in primary operable colorectal Cancer and a variety of common cancers. https://doi.org/10.1371/journal.pone.0142159

  14. 14.

    Tsujino T, Komura K, Matsunaga T et al (2017) Preoperative measurement of the modified Glasgow prognostic score predicts patient survival in non-metastatic renal cell carcinoma prior to nephrectomy. Ann Surg Oncol 24:2787–2793. https://doi.org/10.1245/s10434-017-5948-6

    Article  PubMed  Google Scholar 

  15. 15.

    Boissier R, Campagna J, Branger N et al (2017) The prognostic value of the neutrophil-lymphocyte ratio in renal oncology: a review. Urol Oncol Semin Orig Investig 35:135–141. https://doi.org/10.1016/J.UROLONC.2017.01.016

    Article  Google Scholar 

  16. 16.

    Semeniuk-Wojtaś A, Lubas A, Stec R et al (2018) Neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and C-reactive protein as new and simple prognostic factors in patients with metastatic renal cell Cancer treated with tyrosine kinase inhibitors: a systemic review and meta-analysis. Clin Genitourin Cancer. https://doi.org/10.1016/J.CLGC.2018.01.010

  17. 17.

    Tsujino T, Komura K, Ichihashi A et al (2017) The combination of preoperative platelet count and neutrophil lymphocyte ratio as a prognostic indicator in localized renal cell carcinoma. Oncotarget 8:110311–110325. https://doi.org/10.18632/oncotarget.22688

    Article  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Hu H, Yao X, Xie X et al (2017) Prognostic value of preoperative NLR, dNLR, PLR and CRP in surgical renal cell carcinoma patients. World J Urol 35:261–270. https://doi.org/10.1007/s00345-016-1864-9

    CAS  Article  PubMed  Google Scholar 

  19. 19.

    Bilen MA, Dutcher GMA, Liu Y et al (2018) Association between pretreatment neutrophil-to-lymphocyte ratio and outcome of patients with metastatic renal cell carcinoma treated with nivolumab. Clin Genitourin Cancer. https://doi.org/10.1016/J.CLGC.2017.12.015

  20. 20.

    Tanaka N, Mizuno R, Yasumizu Y et al (2017) Prognostic value of neutrophil-to-lymphocyte ratio in patients with metastatic renal cell carcinoma treated with first-line and subsequent second-line targeted therapy: a proposal of the modified-IMDC risk model. Urol Oncol Semin Orig Investig 35:39.e19–39.e28. https://doi.org/10.1016/J.UROLONC.2016.10.001

    Article  Google Scholar 

  21. 21.

    Chrom P, Stec R, Bodnar L, Szczylik C (2018) Incorporating neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in place of neutrophil count and platelet count improves prognostic accuracy of the international metastatic renal cell carcinoma database consortium model. Cancer Res Treat 50:103–110. https://doi.org/10.4143/crt.2017.033

    CAS  Article  PubMed  Google Scholar 

  22. 22.

    Koo AS, Armstrong C, Bochner B et al (1992) Interleukin-6 and renal cell cancer: production, regulation, and growth effects. Cancer Immunol Immunother 35:97–105

    CAS  Article  Google Scholar 

  23. 23.

    Negrier S, Perol D, Menetrier-Caux C et al (2004) Interleukin-6, interleukin-10, and vascular endothelial growth factor in metastatic renal cell carcinoma: prognostic value of interleukin-6 - from the Groupe Français d’Immunothérapie. J Clin Oncol 22:2371–2378. https://doi.org/10.1200/JCO.2004.06.121

    CAS  Article  PubMed  Google Scholar 

  24. 24.

    Menetrier-Caux C, Montmain G, Dieu MC et al (1998) Inhibition of the differentiation of dendritic cells from CD34(+) progenitors by tumor cells: role of interleukin-6 and macrophage colony-stimulating factor. Blood 92:4778–4791

    CAS  Article  Google Scholar 

  25. 25.

    Motzer RJ, Tannir NM, McDermott DF et al (2018) Nivolumab plus Ipilimumab versus Sunitinib in advanced renal-cell carcinoma. N Engl J Med 378:1277–1290. https://doi.org/10.1056/NEJMoa1712126

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Sreeramkumar V, Adrover JM, Ballesteros I, et al (2014) Neutrophils scan for activated platelets to initiate inflammation. Science (80- ) 346:1234–1238. https://doi.org/10.1126/science.1256478

  27. 27.

    Tsimafeyeu I (2017) Management of non–clear cell renal cell carcinoma: current approaches. Urol Oncol Semin Orig Investig 35:5–13. https://doi.org/10.1016/j.urolonc.2016.07.011

    CAS  Article  Google Scholar 

  28. 28.

    Buti S, Bersanelli M, Maines F et al (2017) First-line PAzopanib in NOn–clear-cell renal cArcinoMA: the Italian retrospective multicenter PANORAMA study. Clin Genitourin Cancer 15:e609–e614. https://doi.org/10.1016/j.clgc.2016.12.024

    Article  PubMed  Google Scholar 

  29. 29.

    De Giorgi U, Procopio G, Giannarelli D et al (2019) Association of Systemic Inflammation Index and Body Mass Index with survival in patients with renal cell Cancer treated with Nivolumab. Clin Cancer Res 25:3839–3846. https://doi.org/10.1158/1078-0432.CCR-18-3661

    Article  PubMed  Google Scholar 

  30. 30.

    Bilen MA, Martini DJ, Liu Y et al (2019) The prognostic and predictive impact of inflammatory biomarkers in patients who have advanced-stage cancer treated with immunotherapy. Cancer 125:127–134. https://doi.org/10.1002/cncr.31778

    Article  PubMed  Google Scholar 

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Medical records and laboratory data are available and stored in institutional databases.

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Authors

Contributions

Guilherme Nader Marta: study conception and design, data collection, data interpretation and analysis, article drafting, critical revision of content.

Pedro Isaacsson Velho: study conception and design, data collection, critical revision of content.

Renata R. C. Colombo Bonadio: data collection, data interpretation and analysis.

Mirella Nardo: study conception and design, data collection, critical revision of content.

Sheila F. Faraj: data collection, data interpretation and analysis, critical revision of content.

Manoel Carlos L. de Azevedo Souza: data collection, critical revision of content.

David Q. B. Muniz: study conception and design, data interpretation and analysis, critical revision of content.

Diogo Assed Bastos: study conception and design, data interpretation and analysis, critical revision of content.

Carlos Dzik: study conception and design, data interpretation and analysis, critical revision of content.

Corresponding author

Correspondence to Guilherme Nader Marta.

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Conflict of Interest

Guilherme Nader Marta has received travel/accommodations grants from Bayer Schering Pharma and Roche.

Pedro Isaacsson Velho has received research funding to his institution from Bristol Myers-Squibb and honoraria/consulting fee from Roche, AstraZeneca Bristol Myers-Squibb and Pfizer.

Renata R. C. Colombo Bonadio has received travel grants from Roche.

Mirella Nardo has no conflict of interest to declare.

Sheila F. Faraj has no conflict of interest to declare.

Manoel Carlos L. de Azevedo Souza has received speakers bureau’s grants from Novartis, MSD, Bristol Myers-Squibb and Amgen and has received travel/accommodations grants from Astellas and Zodiac.

David Q. B. Muniz: has received research funding to his institution from Pfizer, travel/accommodations grants from Janssen and has received speakers bureau’s grants from Pfizer and Janssen.

Diogo Assed Bastos has received research funding to his institution from Janssen, Astellas, Pfizer and honoraria/consulting fee from Roche, Janssen, MSD.

Carlos Dzik has received consulting or advisory grants from Janssen-Cilag, Ipsen, Novartis; speakers bureau’s grants Janssen Oncology and travel/accommodations from Astellas Pharma, Janssen Oncology.

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This study was approved by the institutional research center (NP 716/14).

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Nader Marta, G., Isaacsson Velho, P., Bonadio, R.R.C. et al. Prognostic Value of Systemic Inflammatory Biomarkers in Patients with Metastatic Renal Cell Carcinoma. Pathol. Oncol. Res. (2020). https://doi.org/10.1007/s12253-020-00840-0

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Keywords

  • Renal cell carcinoma
  • Pazopanib
  • Sunitinib
  • Neutrophil-to-lymphocyte ratio
  • Platelet-to-lymphocyte ratio