Abstract
Background/Aim: Biomarkers that would identify patients unlikely to respond to immunotherapy with immune checkpoint inhibitors (ICIs) remain an unmet medical need. Patients and Methods: In the present study, we have retrospectively evaluated the association between biomarkers of immune activation and outcome in metastatic renal cell carcinoma (mRCC) patients treated with ICIs. The laboratory and clinical data of 79 consecutive patients with histologically confirmed mRCC treated with ICI-based immunotherapy have been analyzed. Results: Patients who progressed or died at 4 months had higher prognostic score, higher serum C-reactive protein (CRP) and neopterin, and urinary neopterin, and lower serum albumin and hemoglobin concentration. Conclusion: Biomarkers of activation of immune response, in particular serum neopterin/creatinine ratio, are associated with outcome in mRCC patients treated with ICI immunotherapy.
The advent of immunotherapy has transformed in a fundamental manner the management of metastatic renal cell carcinoma (mRCC). First introduced as monotherapy in patients failing tyrosine kinase inhibitors (TKI) (1, 2), immune checkpoint inhibitors (ICI) have subsequently demonstrated superiority in the first-line setting as part of combination regimens (3-5). Combination of programmed death-ligand 1 (PD-L1) and anti-CTLA4 monoclonal antibodies, as well as regimens based on combination of immunotherapeutic agents and TKI have been shown to be the best option for patients in the first line therapy (6-8). Despite a major improvement in efficacy, including a substantial proportion of patients with prolonged and, possibly, long-term response, the majority of patients treated with immunotherapy will, irrespective of the line of treatment, ultimately progress. Biomarkers that would identify patients unlikely to respond to immunotherapy in whom alternative treatment approaches or experimental therapies should be used remains an unmet medical need. Predictive biomarkers have a potentially crucial role when selecting treatment in mRCC, given the multiple treatment options with different mechanisms of action.
Increased concentrations of circulating biomarkers of the activation of immune and inflammatory response like C-reactive protein (CRP), interleukin-6 (IL-6), interleukin-1 (IL-1) or neopterin have been shown to be associated with poor prognosis in patients with a range of solid tumors, including mRCC (9-11). High concentrations of inflammatory biomarkers have been also associated with the lack of response to immunotherapy (12). Dynamics of serum CRP concentrations has been shown to be associated with overall response rate (ORR) and progression-free survival (PFS) in patients treated with nivolumab (13). Similarly, increased concentrations of circulating cytokines including IL1α, IL6, chemokine CCL4, and interleukin-13 were negatively associated with overall survival (OS) and PFS in patients treated with atezolizumab, although the dynamics of these cytokines during therapy with atezolizumab were not predictive of response (14).
In the present study, we have retrospectively evaluated the association between biomarkers of immune activation and outcome in mRCC patients treated with ICIs.
Patients and Methods
The laboratory and clinical data of 79 consecutive patients with histologically confirmed mRCC, 59 males and 20 females, treated with ICI-based immunotherapy have been retrospectively analyzed. The histology was clear cell RCC in 75 patients, papillary RCC in 2 cases, collecting duct carcinoma in one case, and in one case the histology was not specified. Thirty-three patients were treated in the first line, 26 patients were treated in the second line, 10 patients were treated in the third line, and 10 patients were treated in the fourth or higher line of therapy. Fifty patients were treated with nivolumab monotherapy (3 mg/kg or 240 mg flat dose every 2 weeks, or 480 mg flat dose every 4 weeks), and 29 patients were treated with the combination of ipilimumab (1 mg/kg) and nivolumab (3 mg/kg or 240 mg flat dose) every 3 weeks for 4 cycles with sequential administration of nivolumab (3 mg/kg or 240 mg flat dose every 2 weeks, or 480 mg flat dose every 4 weeks). The response was evaluated by standard radiological methods in 2 to 3-month intervals, and the treatment was administered until the repeated confirmation of progression or manifestation of serious toxicity. PFS was defined as freedom or progression or death by any cause. Eastern Cooperative Oncology Group performance status was recorded, and International Metastatic RCC Database Consortium (IMDC) and Memorial Sloan-Kettering Cancer Center (MSKCC) scores and the Charlson Comorbidity Index (CCI) were calculated based on pre-treatment parameters in each patient. The analysis was part of a project approved by the institutional ethical committee and the patients signed informed consent.
The peripheral blood samples were transported immediately to the laboratory and centrifuged (1,600 × g for 8 min at 16°C). The serum was separated and analyzed immediately or frozen at −20°C until analysis. CRP, creatinine, lactate dehydrogenase, and albumin were determined using commercially available kits on Cobas c 8000 system (Roche Diagnostics, Mannheim, Germany) according to the manufacturer’s instructions. Serum neopterin was measured by Neopterin ELISA Kit (IBL International, Hamburg, Germany) using an automated microplate processor for enzyme immnoassays EVOLIS (Bio-Rad Laboratories, Hercules, CA, USA). Measurements were performed in an ISO 15189-accredited laboratory.
Early morning, urine samples were collected and stored at −20°C until analysis. Urinary neopterin was determined using the high-performance liquid chromatography method described earlier (15) and slightly modified. Briefly, after centrifugation (5 min, 1,300 × g) and dilution of 100 μl of urine specimens with 1.0 ml of the mobile phase, the samples were filtered using Microtiter, AcroPrep 96 Filter Plate 0.2 μm/350 μl (Pall Life Science, Ann Arbor, MI, USA) and Vacuum manifold (Pall Life Science) and then injected onto a column. Neopterin was determined using the Prominence LC20 HPLC system (Shimadzu, Kyoto, Japan) composed of rack changer/C-special autosampler for microtitration plates, degasser DGU-20A5, two liquid chromatograph LC-20 AB pumps, auto sampler SIL-20 AC, column oven CTO-20 AC thermostat, fluorescence detector RF-20Axs, diode array detector SPD-M20A, and communications bus module CBM-20A. Phosphate buffer, 15 mmol/l, pH 6.4, with a flow rate of 1 ml/min, was used as the mobile phase. Separation was performed using monolithic analytical columns connected in series, Chromolith Speed Rod RP-18e 50×4.6 mm and Chromolith Performance RP-18e 100×3 mm with column guard Chromolith RP-18e 10×4.6 mm (Merck, Darmstadt, Germany), at 25°C; the injection volume was 1 μl. Neopterin was identified by its native fluorescence (353 nm excitation wavelength, 438 nm emission wavelength). Creatinine was monitored simultaneously in the same urine specimen with a diode array detector at 235 nm. The time of analysis for urine neopterin and creatinine was 6 min, and the analytes were quantified by external standard calibration. The results were expressed as neopterin to creatinine ratio.
Peripheral blood cell count was determined using Sysmex XN series (XN-3100, XN-1000) hematology analyzers (Sysmex, Kobe, Japan) according to the instructions of manufacturer. Erythrocytes and thrombocytes were detected by impedance method using hydrodynamic focusing. Hemoglobin was measured by photometric method using sodiumlaurylsulfate without cyanide. Leukocyte counts, including differential counts, were measured by fluorescence flow cytometry technology. Neutrophil-to-lymphocyte, platelet-to-lymphocyte, and lymphocyte-to-monocyte ratios were calculated.
The correlations were studied using the Spearman rank correlation coefficient. The difference between subgroups of patients defined by survival at a given time point was investigated using the Mann–Whitney U-test and the Number Crunchers Statistical Systems software (Number Cruncher Statistical Systems, Kaysville, UT, USA). The decision on statistical significance was based on the p<0.05 level.
Results
The correlation of clinical and biochemical parameters with inflammatory biomarkers is shown in Table I. Serum CRP, albumin, and neopterin and urinary neopterin correlated with IMDC and MSKCC scores, hemoglobin concentrations, platelet count, platelet-to-lymphocyte ratio and red distribution width.
Correlations between the parameters investigated.
All patients were followed for a minimum of 4 months at which point 33 patients had progressed or died, and 46 patients were without progression. Patients who progressed or died at 4 months had higher MSKCC score, higher serum CRP and neopterin, and urinary neopterin, and lower serum albumin, hemoglobin concentration and CCI (Table II). Most marked difference was observed for serum neopterin/creatinine ratio. In general, similar pattern of differences was observed when PFS was evaluated at 6 (42 events), 8 (45 events) and 12 (49 events) months; only the difference in CCI was not significant.
Comparison of baseline parameters in patients without or with progression after 4 months of immunotherapy.
At 6 months, 61 patients were alive and 17 patients had died. Patients who were dead at 6 months had significantly higher IMDC and MSKCC score, ECOG performance status, serum CRP, neopterin, urinary neopterin, leukocyte count, monocyte count, neutrophil count, platelet count, red distribution width and platelet-to-lymphocyte ratio, and significantly lower serum albumin and mean platelet volume (Table III). Most marked difference was again observed for serum neopterin/creatinine ratio, and similar trend of differences was noted when OS was evaluated at 4 (7 events), 8 (20 events), and 12 (29 events) months.
Comparison of baseline parameters in patients alive or not after 6 months of immunotherapy.
Discussion
The present results demonstrated an association between pretreatment concentrations of inflammatory biomarkers and outcome in mRCC patients treated with immunotherapy. As expected, a correlation was observed between biomarkers of inflammation and immune activation and parameters of peripheral blood cell count, in particular hemoglobin concentration and platelet count. In some series, increased baseline level of lymphocytes has been observed as a prognostic and predictive biomarker with better response to immunotherapy (16). Significant correlation was also observed between prognostic risk scores and CRP (11, 12), albumin and neopterin concentrations. The most commonly used mRCC prognostic models, MSKCC and IMDC, have been defined in the era of cytokine treatment and TKI therapy, respectively, but are still of widespread use in the present immunotherapy era (17). Most importantly, CRP and neopterin concentrations were higher and albumin concentrations were significantly lower in patients who progressed or died (18). A Swedish analysis identified serum albumin level as an independent prognostic factor in patients treated with targeted therapy, and increased platelet count was also associated with shorter OS (19). Guanylate-binding protein 2 (GBP2), an interferon-induced GTPase may also serve as a prognostic biomarker (20).
Urinary neopterin concentration is expressed as neopterin/creatinine ratio, while serum neopterin concentrations are usually given in absolute values. Absolute values of serum neopterin could be problematic in mRCC patients because of prior nephrectomy and decreased glomerular filtration rate. In the present study, correlations with biomarkers of inflammation and peripheral blood cell count were markedly stronger when serum neopterin concentration was expressed as neopterin/creatinine ratio. This indicates that creatinine ratio may be the preferred option for expressing the results also for serum neopterin concentrations in mRCC patients.
CRP and albumin represent acute phase reactants, although the concentrations move in opposite directions (21). The correlation of these acute phase reactants with neopterin concentrations, and the correlations between acute phase reactants or neopterin and hemoglobin concentration or platelet count have been amply documented in patients with solid tumors, as well as in patients with different non-malignant conditions associated with inflammation (22-26).
As expected, the biomarkers of immune and inflammatory response and associated parameters like hemoglobin concentration or leukocyte count were associated with progression and survival events during the course of follow up, with lowest p-values observed for the serum neopterin/creatinine ratio. An association between increased biomarkers of inflammation or immune response and inferior outcome of ICI-based therapy has been reported in earlier studies (27, 28). Present data indicate that the serum neopterin/creatinine ratio could represent a good candidate biomarker for investigation in future prospective studies in mRCC patients treated with immunotherapy.
An obvious aim of future biomarker trials would be to identify both the patients likely, as well as those unlikely to benefit from ICI-based therapy. Patients unlikely to respond could then be offered other treatment options or, preferentially, enrolled in clinical trials of novel agents or combination regimens.
Because of the exploratory nature of the study, the Bonferroni correction was not performed. However, the association between the concentrations of inflammatory biomarkers and outcome was consistent in analyses performed at different time points. Moreover, the differences in serum neopterin/creatinine ratio would remain highly significant even after applying the Bonferroni correction.
The present study has other obvious important limitations. First, this was a retrospective study. Second, the population studied was heterogeneous in terms of lines of therapy and regimens used. The follow up was short, and the survival data were relatively immature at the time of this analysis. On the other hand, the present cohort reflects more patients encountered in real life.
The advent of ICI has transformed the landscape of mRCC systemic therapy, but the data on predictors of efficacy of therapy are limited, and at this point, we do not have any biomarker that would reliably predict the occurrence or lack of response. An ideal biomarker should be easily repetitively sampled to assess the on-treatment dynamic changes. Most studied markers are PD-L1 expression and tumor-infiltrating immune cells, but even though these have been studied extensively since the beginning of ICI era, the role of the management remains inconclusive (29). There is strong theoretical rationale behind biomarkers of immune and inflammatory activation as negative predictors of response that is supported by the data from this, as well as other studies (27, 30). However, these results should be confirmed in prospective studies in more homogeneous patient populations.
Conclusion
In conclusion, biomarkers of activation of immune response, in particular serum neopterin/creatinine ratio, are associated with outcome in mRCC patients treated with immunotherapy. In patients with mRCC, serum neopterin concentrations may be preferentially expressed as creatinine ratio. The potential role of neopterin as a prognostic and predictive biomarker in mRCC during immunotherapy should be confirmed in a larger prospective cohort.
Acknowledgements
This manuscript was supported by Czech Science Foundation (IGA LF 2022 003) project No. SPP 911103671/31.
Footnotes
Authors’ Contributions
BM is the guarantor of the study. MS, AZ and HŠ led the analysis. JJ, TA, KM, LJ, LKK and DT analysed the samples. All contributed to the analysis and interpretation of the data. MS wrote the first draft and all contributed to subsequent drafts and the final paper.
Conflicts of Interest
The Authors declare no potential conflicts of interest in relation to this study.
- Received November 2, 2022.
- Revision received November 8, 2022.
- Accepted November 10, 2022.
- Copyright © 2023, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).
