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Clinical Studies

Immunoglobulin G and Subclasses as Potential Biomarkers in Metastatic Melanoma Patients Starting Checkpoint Inhibitor Treatment

Diem, Stefan*,†,‡; Fässler, Mirjam*,§; Bomze, David*; Ali, Omar Hasan*,§; Berner, Fiamma*; Niederer, Rebekka*; Hillmann, Dorothea; Mangana, Joanna; Levesque, Mitchell P.; Dummer, Reinhard; Risch, Lorenz∥,#,**; Recher, Mike††; Risch, Martin∥,‡‡; Flatz, Lukas*,†,§,¶

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doi: 10.1097/CJI.0000000000000255
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Checkpoint inhibitors (CIs) have revolutionized the treatment of several cancer types including melanoma, which is reflected in a significantly increased patient survival. CIs targeting the CTLA4-B7 (iplimumab) or PD1-PDL1 (nivolumab, pembrolizumab) axis have been approved for melanoma and show response rates around 40% with anti-PD1 monotherapy and 60% with the combination of ipilimumab and nivolumab.1–6

Melanoma is a rather immunogenic tumor. Spontaneous tumor regression has been reported on several occasions. Consistently, it shows a higher incidence in immunosuppressed patients.7,8 This implies immunosurveillance of melanoma and likely explains the clinical effectiveness of immunomodulatory agents including CIs in metastatic melanoma.

Total serum immunoglobulin G (IgG) levels range from 7 to 16 g/L in normal individuals and consist of 4 IgG subclasses. IgG1 is quantitatively the most abundant IgG subclass known to be produced in response to soluble antigens and membrane proteins and functions to neutralize toxins and pathogens.9 Immunoglobulin G2 (IgG2) is produced in response to bacterial capsular polysaccharide antigens and has the unique feature of not binding to Fc receptors on antigen-presenting cells. Immunoglobulin G3 (IgG3) is a potent proinflammatory antibody but has a low in vivo half-life explaining its relatively low abundance in serum.10 Immunoglobulin G4 (IgG4) is thought to play an important role in allergic reactions together with immunoglobulin E (IgE). Unlike other IgG subclasses, it does not activate the complement system following antigen binding and is thus believed to act as an immune-regulatory IgG subclass. Consistently, during desensitizing immunotherapy to treat allergies, relief of symptoms correlates with the emergence of allergen-specific IgG4 antibodies.11

As IgG production requires functional antigen-presenting, T-helper and B cells, serum IgG subclass levels reflect the immunocompetence of an individual. Hypogammaglobulinemia, including selective IgG deficiencies, are known to result in susceptibility for infections and are also associated with autoimmunity.12 As checkpoint inhibition requires a functional immune system, our hypothesis was that preexisting IgG and the composition of the IgG subclasses might be associated with efficacy of CI therapy in patients with metastatic melanoma. The aim of this prospective study was, therefore, to test whether pretreatment serum IgG and IgG subclass levels (IgG1, IgG2, IgG3, and IgG4) correlate with antitumor response and survival following CI therapy.


Patient Cohort

We prospectively included patients with metastatic melanoma starting treatment with anti-PD1 or anti-CTLA4 antibodies at the Kantonsspital St. Gallen and University Hospital Zürich.

Patients had at least 2 treatment cycles of either nivolumab (Opdivo; Bristol-Myers Squibb SA, 3 mg/kg every 2 weeks), pembrolizumab (Keytruda; MSD Merck Sharp & Dohme AG, 2 mg/kg every 3 weeks), ipilimumab (Yervoy; Bristol-Myers Squibb SA, 3 mg/kg every 3 weeks) or the combination of nivolumab and ipilimumab (1 and 3 mg/kg every 3 weeks). Serum samples were collected at the day of treatment start. Computed tomographic scans (CT) were performed after 10–12 weeks, and response was assessed according to RECIST 1.1 criteria.13 Patients with progressive disease (PD) at the first CT scan were confirmed with another scan after 4–6 weeks with focus on potential pseudoprogression.14 Responders were defined as complete remission (CR) or partial remission (PR). Nonresponders were defined as stable disease (SD) or PD.

The study was approved by the local ethics committees (EKOS 16/079, respectively, EK 647, EK800) and was carried out in accordance with the declaration of Helsinki principles.

Analyses of Immunoglobulins

Immunoglobulin levels were assessed by commercially available immunoturbidimetric methods (Binding site, Birmingham, UK) using an SPA plus analyzer (Binding site, Birmingham, UK). IgG subgroup concentrations (ie, IgG1, IgG2, IgG3, and IgG4) were determined using a Behring nephelometer II (BNII) (Siemens Diagnostics, Zurich, Switzerland) using reagents from Siemens (Siemens Diagnostics, Zurich, Switzerland). In our hands, the imprecision of the utilized methods, as assessed by coefficient of variations (CV) obtained from serial measurements of commercially available control materials, was as follows: 3% for total IgG (at concentrations of 7.1 and 13.2 g/L). The respective CVs for the IgG subgroups were as follows: 4.0% (at a concentration of 4.63 g/L) and 2.76% (at a concentration of 8.42%) for IgG1, 4.5% (at concentrations of 2.22 and 4.06 g/L) for IgG2, 6.17% (at a concentration of 0.22 g/L) and 5.07% (at a concentration of 0.4 g/L) for IgG3, and 5.7% (at concentrations of 0.38 and 0.96 g/L) for IgG4.

Statistical Analyses

R software (version 3.5.0) was used for all statistical analyses. The “survival” and “survminer” packages were used for survival analysis.15,16

The package “maxstat” was implemented to identify optimal cutpoints for biomarker levels that correspond to the most significant relation with progression-free survival (PFS) and overall survival (OS), using the maximally selected log-rank statistic.17 The minimal proportion (“minprop” argument) in each group was set to 0.30. Kaplan-Meier plots were generated for OS and PFS, and the patients were categorized into “high” and “low” groups on the basis of the optimal cutpoint for continuous levels of total IgG and IgG subclasses. Hazard ratios (HR) for each biomarker were calculated using Cox’s proportional hazards model. The association between IgG levels and PFS or OS was examined using the log-rank test.


A total of 49 patients were enrolled into the study. A total of 42 (86%) patients received monotherapy with an anti-PD1 antibody (nivolumab or pembrolizumab), 5 patients (10%) were treated with a combination of nivolumab plus ipilimumab, and 2 patients (4%) received an ipilimumab monotherapy.

One patient had a CR (2%) at the first CT scan, 23 had a PR (47%), 10 reached SD (20%), and 15 patients had PD (31%). Responders (CR, PR) versus nonresponders (SD, PD) were distributed as follows: 49% (n=24) versus 51% (n=25). Detailed patient characteristics are presented in Table 1. A total of 29 patients (59%) developed an adverse event of any grade (8 gastrointestinal, 8 endocrine, 7 skin, 3 renal, 2 pneumonitis, and 1 hematological).

Patient Characteristics

IgG2 levels before initiation of CI therapy were significantly higher in the responder group versus the nonresponder-group (P=0.011). No significant differences were observed for total IgG, IgG1, IgG3, and IgG4 between responders and nonresponders (Fig. 1).

Baseline IgG and subclass levels before checkpoint inhibitor treatment in R versus NR. Reference values for total IgG and IgG subclasses in the white population of matching age to the subjects in this study are as follows: 7.00–16.00 g/L for total IgG; 4.05–10.11 g/L for IgG1; 1.69–7.86 g/L for IgG2; 0.11–0.85 g/L for IgG3; and 0.03–2.01 g/L for IgG4. IgG indicates immunoglobulin G; NR, nonresponder; R, responder.

Next, we evaluated whether specific levels of IgG and IgG subclasses were associated with PFS and OS. The median follow-up time was 20.7 months (interquartile range, 17.5–24.3 mo). For the calculated optimal cutpoints (see the Materials and methods section), PFS was significantly better in patients with high levels of total IgG [>9.66 g/L, HR=0.43, confidence interval: 0.18–0.98, P=0.038], IgG1 (>6.22 g/L, HR=0.32, confidence interval: 0.11–0.92, P=0.025), IgG2 (>2.42 g/L, HR=0.41, confidence interval: 0.19–0.88, P=0.019), and IgG3 (>0.21 g/L, HR=0.45, confidence interval: 0.21–0.96, P=0.034) (Fig. 2). Furthermore, OS was significantly prolonged in patients with IgG2 levels >2.42 g/L (HR=0.41, confidence interval: 0.17–1.00, P=0.043) (Fig. 3). All the significant associations remained such after a false discovery rate of 0.10 was imposed using the Benjamini-Hochberg correction for multiple comparisons.

Progression-free survival depending on baseline serum IgG and IgG subclass levels (below and above cutpoint). HR indicates hazard ratio; IgG, immunoglobulin G.
Overall survival depending on baseline serum IgG and IgG subclass levels (below and above cutpoint). HR indicates hazard ratio; IgG, immunoglobulin G.

No statistically significant difference of IgG levels between responders and nonresponders (St. Gallen cohort) was seen during the course of treatment, and no statistically significant association was seen with adverse events.


To our knowledge, this is the first study providing evidence that baseline serum immunoglobulin levels may serve as predictive markers for response to CI therapy. Furthermore, a prognostic association of IgG subclass levels and survival was demonstrated. Until now, several baseline immune blood parameters were evaluated for their effect on response and survival for treatment with CIs in metastatic melanoma. Associations between better outcome and high lymphocyte count,18–21 a low neutrophil count,22 and a low neutrophil/lymphocyte ratio are known.23 All these results underline the importance of T-cell activity against cancer cells. Our study focusing on the role of humoral immunity for CI therapy hypothesizes that B cells also may be involved.

Of note, measuring immunoglobulins in the serum is a simple, reliable, and rather cheap procedure readily available in virtually all routine medical laboratories.

Low serum IgG2 and IgG4, but not IgG3, have been recently shown to be associated with the clinical diagnosis of antibody deficiency in a retrospective analysis.24 Thus, patients with low IgG2 and IgG4 may suffer from a mild form of immunodeficiency that was previously not recognized in these patients. It is interesting to note that, in 2013, Karagiannis et al25 described an association between high IgG4 levels and poor survival in 57 patients diagnosed with stage I–IV malignant melanoma. However, this study did not include patients receiving CI therapy.

Low serum IgG levels may result from functional abnormalities of B cells but also T cells. This is exemplarily shown in human CTLA4 insufficiency, which is thought to be a T-cell intrinsic defect, associated with antibody deficiency in most patients.26 Subsequent prospective studies are needed to test B and T-cell intrinsic functions in patients with normal or low IgG2 levels.

Elevated IgG2 antibody levels in responders might reflect the presence of specific antibodies against melanoma self-antigens such as TRP1, TRP2, and gp100 or the cancer-testis antigen NY-ESO-1. The presence of these antibodies may, therefore, be a surrogate marker for inflamed tumors.

The following limitations have to be addressed. First, the relatively small number of patients does not allow us to perform extensive multivariable analyses. Nevertheless, our findings are statistically significant. Second, we do not have a validation cohort. However, the fact that our study is prospective strengthens the hypothesis that these findings are generally applicable.

Furthermore, a certain number of uveal and mucosal melanoma patients was included, in which CI treatment is less effective with lower response rates.

In conclusion, serum total IgG and IgG subclass measurements at baseline may serve as biomarkers for checkpoint inhibitor efficacy in patients with metastatic melanoma. These findings are hypothesis generating and have to be confirmed in prospective studies with larger patient cohorts.


The authors thank all the patients who participated in this study. The contribution of Christoph Seger, PhD, and Thomas Lung, PhD, for realizing routine laboratory analysis is also acknowledged. The authors especially thank the Zulian family for their financial support.

Conflicts of Interest/Financial Disclosures

Supported by Swiss National Science Foundation Professorship to L.F. (PP00P3_157448). M.R. is supported by a Swiss National Science Foundation Professorship (PP00P3_173186). The study coordination of this patient cohort was supported by a grant from the Forschungsförderung of the Kantonsspital St. Gallen and partly funded by the University of Zurich Research Priority Program (URPP). The URPP biobank also provided the samples from consenting melanoma patients.

All authors have declared that there are no financial conflicts of interest with regard to this work.


1. Robert C, Long GV, Brady B, et al. Nivolumab in previously untreated melanoma without BRAF mutation. N Engl J Med. 2014;372:320–330.
2. Hodi FS, O’Day SJ, McDermott DF, et al. Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med. 2010;363:711–723.
3. Robert C, Thomas L, Bondarenko I, et al. Ipilimumab plus dacarbazine for previously untreated metastatic melanoma. N Engl J Med. 2011;364:2517–2526.
4. Ribas A, Puzanov I, Dummer R, et al. Pembrolizumab versus investigator-choice chemotherapy for ipilimumab-refractory melanoma (KEYNOTE-002): a randomised, controlled, phase 2 trial. Lancet Oncol. 2015;16:908–918.
5. Robert C, Schachter J, Long GV, et al. Pembrolizumab versus ipilimumab in advanced melanoma. N Engl J Med. 2015;372:2521–2532.
6. Larkin J, Chiarion-Sileni V, Gonzalez R, et al. Combined nivolumab and ipilimumab or monotherapy in untreated melanoma. N Engl J Med. 2015;373:23–34.
7. Kalialis LV, Drzewiecki KT, Klyver H. Spontaneous regression of metastases from melanoma: review of the literature. Melanoma Res. 2009;19:275–282.
8. Vajdic CM, van Leeuwen MT, Webster AC, et al. Cutaneous melanoma is related to immune suppression in kidney transplant recipients. Cancer Epidemiol Biomarkers Prev. 2009;18:2297–2303.
9. Irani V, Guy AJ, Andrew D, et al. Molecular properties of human IgG subclasses and their implications for designing therapeutic monoclonal antibodies against infectious diseases. Mol Immunol. 2015;67:171–182.
10. Sigal LH. Basic science for the clinician 58: IgG subclasses. J Clin Rheumatol. 2012;18:316–318.
11. Shamji MH, Durham SR. Mechanisms of allergen immunotherapy for inhaled allergens and predictive biomarkers. J Allergy Clin Immunol. 2017;140:1485–1498.
12. Jolles S. The variable in common variable immunodeficiency: a disease of complex phenotypes. J Allergy Clin Immunol Pract. 2013;1:545–556.
13. Eisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer. 2009;45:228–247.
14. Hodi FS, Hwu W-J, Kefford R, et al. Evaluation of immune-related response criteria and RECIST v1.1 in patients with advanced melanoma treated with pembrolizumab. J Clin Oncol. 2016;34:1510–1517.
15. Kassambara A, Kosinski M. survminer: Drawing survival curves using “ggplot2.” R package version 0.4.2. 2018. Available at:
16. Therneau TM, Grambsch PM. Modeling Survival Data: Extending the {C}ox Model. Springer; New York, 2000.
17. Hothorn T. maxstat: Maximally selected rank statistics. R package version 0.7-25. 2017.
18. Delyon J, Mateus C, Lefeuvre D, et al. Experience in daily practice with ipilimumab for the treatment of patients with metastatic melanoma: an early increase in lymphocyte and eosinophil counts is associated with improved survival. Ann Oncol. 2013;24:1697–1703.
19. Simeone E, Gentilcore G, Giannarelli D, et al. Immunological and biological changes during ipilimumab treatment and their potential correlation with clinical response and survival in patients with advanced melanoma. Cancer Immunol Immunother. 2014;63:675–683.
20. Ku GY, Yuan J, Page DB, et al. Single-institution experience with ipilimumab in advanced melanoma patients in the compassionate use setting: lymphocyte count after 2 doses correlates with survival. Cancer. 2010;116:1767–1775.
21. Martens A, Wistuba-Hamprecht K, Foppen MG, et al. Baseline peripheral blood biomarkers associated with clinical outcome of advanced melanoma patients treated with ipilimumab. Clin Cancer Res. 2016;22:2908–2918.
22. Ferrucci PF, Ascierto PA, Pigozzo J, et al. Baseline neutrophils and derived neutrophil-to-lymphocyte ratio: prognostic relevance in metastatic melanoma patients receiving ipilimumab. Ann Oncol. 2016;27:732–738.
23. Ferrucci PF, Gandini S, Battaglia A, et al. Baseline neutrophil-to-lymphocyte ratio is associated with outcome of ipilimumab-treated metastatic melanoma patients. Br J Cancer. 2015;112:1904–1910.
24. Elkuch M, Greiff V, Berger CT, et al. Low immunoglobulin E flags two distinct types of immune dysregulation. Clin Exp Immunol. 2017;187:345–352.
25. Karagiannis P, Gilbert AE, Josephs DH, et al. IgG4 subclass antibodies impair antitumor immunity in melanoma. J Clin Invest. 2013;123:1457–1474.
26. Schubert D, Bode C, Kenefeck R, et al. Autosomal dominant immune dysregulation syndrome in humans with CTLA4 mutations. Nat Med. 2014;20:1410–1416.

immunoglobulins; subclasses; metastatic melanoma; checkpoint inhibitor; biomarker; response

Copyright © 2019 The Author(s). Published by Wolters Kluwer Health, Inc.