Abstract
Background:
Our understanding of protective immunity after natural viral infections in children with cancer and hematological diseases is restricted. Current cancer treatments cause significant immunosuppression, affecting both innate and adaptive immunity which leads to reduced B-cell and antibody responses. The aim of this study was to characterize SARS-CoV-2 immune response in children with cancer or hematological disease.
Methods:
A single-center study was conducted from June 2020 to June 2023, including 135 patients and 14 healthy siblings. Blood samples were obtained for serological analysis and cell-based assays. SARS-CoV-2 IgG and IgA responses were quantified using suspension multiplex immunoassay (SMIA) and enzyme-linked immunosorbent assay (IgG ELISA) while neutralizing antibody (nAb) responses were assessed by plaque reduction neutralization tests (PRNT). The memory B-cell (MBC) population was evaluated through flow cytometry and MBC responses through FluoroSpot, respectively.
Results:
In total, 78 patients seroconverted in response to SARS-Co-V-2 but neither immunosuppression nor cancer diagnosis significantly affected seroconversion. SARS-CoV-2 IgG and IgA levels correlated positively with increasing age, and IgA seroconversion was significantly associated with the presence of nAbs. Antigen-specific MBC responses against both spike and receptor-binding domain (RBD) were elevated in older children, while children on immunosuppression had significantly lower RBD IgG-secreting cells.
Conclusion:
Our results show that most pediatric oncological and hematological patients can mount a broad antibody response upon SARS-CoV-2 natural infection or vaccination, although there is a variability in their responses influenced by increasing age. MBC responses in children with immunosuppression were blunted with fewer RBD IgG-secreting cells. Essentially, our findings underscore that young children with severe treatment-related immunosuppression are at risk for less effective B-cell responses upon viral infection.
Introduction
To date, our knowledge regarding protective immunity after viral infections in children with cancer is limited, yet children with cancer frequently suffer from viral infections during therapy. The emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2020 sparked tremendous efforts to gain new insight into the interplay between humoral and cellular immunity to achieve immune control of SARS-CoV-2 in both children and adults. Early reports indicated that children experienced more favorable outcomes than adults upon infection, in addition to lower antibody and cellular responses compared to adults upon acute infection (, ). In the oncological setting, the clinical outcomes of SARS-CoV-2 infections in children with cancer were also reported to be less severe compared to adult cancer patients (–).
Modern treatment of most childhood cancers involves multimodal therapies consisting of chemotherapy, surgery, and/or irradiation with the addition of immunotherapy and autologous or allogeneic hematological stem-cell transplantation (auto-HSCT or allo-HSCT) in selected cases. It is widely established that cancer treatment causes a high degree of immunosuppression, affecting both the innate and adaptive immune systems. Immune recovery post-treatment has been shown to take several months to years (, ), with several studies indicating that humoral immunity and B cells are particularly vulnerable to treatment-related immunosuppression (–). This, in turn, leads to reduced B-cell and antibody responses to infection and vaccination as well as the loss of previously acquired immunity, all in all resulting in an increased vulnerability to infections (, , ).
In the first years of life, the immune system matures rapidly, influencing both the quantity and quality of the humoral immune response in children (, ). In response to a variety of exposures, the memory B-cell (MBC) pool is established with long-lived plasma cells mainly residing in the bone marrow, ensuring long-term protection (, , ). Neutralizing antibodies (nAbs) in children are of particular interest given their role in inhibiting viral cell entry, replication, and spread to other cells (). In SARS-CoV-2 infection, nAbs primarily target the viral receptor-binding domain (RBD) of the viral spike (S) glycoprotein and thus interfere with viral binding to the angiotensin-converting enzyme 2 (ACE-2) receptor on the host cell. Children have previously been shown to seroconvert after both symptomatic and asymptomatic SARS-CoV-2 infection and to develop nAbs with similar or even longer durability compared with adults (–). Vaccination with a SARS-CoV-2 mRNA vaccine in children undergoing active cancer treatment has been shown to result in both cellular and humoral immune responses with long-lasting (> one year) strong antibody responses (, ).
To understand if the quantity and quality of the humoral response to SARS-CoV-2 infection was influenced by patient- and/or treatment-related factors in children with cancer or hematological disease, we performed an in-depth characterization of SARS-CoV-2 infection and immune response in pediatric oncology and hematology patients. We initiated a single-center longitudinal study where patients were included and followed from June 2020 to June 2023 with repeated sampling for SARS-CoV-2 seroconversion and immunological analysis (). Within the scope of this study, we performed an extensive serological evaluation of SARS-CoV-2 immune responses in singular individual samples from 135 patients and 14 healthy siblings, including analyses of antibodies against various SARS-CoV-2 variants, production of nAbs and assessment of MBC responses to SARS-CoV-2.
Materials and methods
Study design and participants
The present study was conducted as part of a prospective, longitudinal cohort study, previously described in Sundberg et al. (). Children with cancer or hematological diseases receiving treatment or follow-up care in Uppsala, Sweden, as well as their healthy siblings, were included (Figure 1). The Swedish Ethical Review Authority granted ethical approval (2020–02154, 2020–04672, 2022-02068-02). The study cohort consisted of the first seropositive [Immunoglobulin (Ig) G+] blood sample from patients who seroconverted (n = 78), a matched seronegative (IgG-) blood sample within a similar time frame from patients who did not seroconvert (n = 57), as well as blood samples from healthy siblings (n = 14), resulting in 149 unique blood samples from 149 children. Of note, no children within the current study experienced severe symptoms of COVID-19. Neither PCR testing nor vaccination were performed for study purposes and study participation was independent of previous infections and SARS-CoV-2 vaccination.
Figure 1
Collection of clinical data
Clinical patient data were collected through medical records, and sibling data were collected through a brief questionnaire. The degree of immunosuppression at the time of blood sampling was assessed by two pediatric oncologists using set criteria previously published (
Collection of blood samples and total immunoglobulin analysis
Peripheral venous blood was sampled from patients in conjunction with previously planned clinical interventions, while blood sampling of siblings occurred at scheduled appointments. For the collection of serum, blood samples were collected in CAT Serum Clot Activator VACUETTE tubes (Greiner Bio-One Gmbh, Austria) and centrifuged before serum was aliquoted and stored in ultra-low temperature freezers. All serum samples were analyzed for total (i.e., not SARS-CoV-2-specific) IgG, IgA, and IgM at the local hospital laboratory (Department of Clinical Chemistry, Uppsala Academic Hospital, Uppsala, Sweden) using a Cobas Pro c503 (Roche, Switzerland).
For isolation of peripheral blood mononuclear cells (PBMCs), peripheral venous blood was collected in CPT™ Mononuclear Preparation Tubes with sodium heparin (BD Biosciences, Franklin Lakes, NJ, USA), according to the manufacturer´s instructions. Briefly, PBMCs were separated through centrifugation, washed twice with phosphate-buffered saline (PBS; Gibco, Invitrogen, Carlsbad, Ca, USA) before resuspension in freezing medium (10% dimethyl sulfoxide (Invitrogen, Carlsbad, Ca, USA) in fetal bovine serum (Sigma-Aldrich, St Louis, MO, USA)) for cryopreservation in liquid nitrogen. Due to sampling limitations, PBMCs were not obtained from all patients at all time-points.
SARS-CoV-2 antibody quantification through a suspension multiplex immunoassay
Serum samples were analyzed using a coronavirus disease 2019 (COVID-19) suspension multiplex immunoassay (SMIA) to detect anti-SARS-CoV-2 IgG and IgA (
Enzyme-linked immunosorbent assay for confirmation of SARS-CoV-2 IgG
In addition to MFI IgG serostatus, human IgG antibodies against SARS-CoV-2 S protein (trimer) were also quantified in serum samples through a solid‐phase sandwich Enzyme‐Linked Immunosorbent Assay (ELISA) Kit (#BMS2325, Thermo Fischer Scientific, Waltham, MA, USA), according to the manufacturer’s protocol. Absorbance was measured at 450 nm using a FLUOstar Omega multimode microplate reader (BMG Labtech, Ortenberg, Germany). For quantification in seropositive samples, IgG concentrations (Units/mL) were calculated based on a standard curve generated from serial dilutions of the High Control. Values above the standard curve were further diluted and the optical density (OD) values still out of range at dilution 1:2,000 (n = 10) were assigned the highest concentration x2. To confirm seronegativity, IgG serostatus was determined by performing the qualitative method recommended by the manufacturer.
Plaque reduction neutralization test for the quantification of neutralizing antibody responses
For determination of antibody neutralizing capability, a plaque reduction neutralization test (PRNT) was performed as previously described (
Immunophenotyping through flow cytometry
PBMCs were washed and incubated with a dead cell marker (#L34957, Fixable Dead Cell Stain kit, Invitrogen, Carlsbad, CA, USA). After washing, the cells were once again stained with fluorescent-conjugated antibodies against several surface antigens, including CD14, CD3, and CD19 (BD Biosciences, Franklin Lakes, NJ, USA). Bulk B cells were defined by gating live CD14–CD3-CD19+ single cells. Data were acquired using the Novocyte 3000 (ACEA Biosciences, Santa Clara, CA, USA) and analyzed with FlowJo software (v. 10.10, FlowJo LLC, Ashland, OR, USA).
Determination of SARS-CoV-2-specific memory B- and T-cell responses through FluoroSpot
The number of SARS-CoV-2-specific MBCs was determined with the FluoroSpot Path SARS-CoV-2 (S+RBD) Human IgG kit (#FSP-05E-RS1-1, Mabtech AB, Nacka Strand, Sweden), according to the manufacturer’s instructions. In brief, 106 PBMCs/mL were stimulated with 1 mg/mL R848 and 10 ng/mL IL-2 for 72 hrs. Subsequently, 105 cells were transferred to wells for total IgG analysis and 3.5x105 cells into wells for antigen-specific analysis and incubated ON (37°C, 5% CO2). Plates were then developed according to the manufacturer’s instructions. The method was validated with medium-only wells as blanks, PBMCs from pre-pandemic samples of healthy adults as negative controls, and PBMCs from SARS-CoV-2-immunized healthy adults as positive controls (data not shown). RBD and S spot-forming unit (SFU) counts were normalized to the total IgG SFU count to account for varying B-cell counts in patients.
In addition, the number of SARS-CoV-2 specific IFN-γ and IL-2 secreting T-cells following polyclonal or SARS-CoV-2 specific stimuli was also determined in a subset of patients using a FluoroSpot kit (FluoroSpot Path: Human IFN-γ/IL-2, SARS-CoV-2, S+NMO, Mabtech AB, Sweden) according to the manufacturer’s instructions. Briefly, in plates pre-coated with monoclonal antibodies (mAbs) specific to human IFN-γ and IL-2, a total of 100,000 PBMCs/well were activated with an anti-CD3 mAb as well as an anti-CD28 mAb (for polyclonal activation). In separate wells, 350,000 PBMCs were instead added into each well and stimulated with anti-CD28 mAb as well as 2μg/mL of SARS-CoV-2 peptides, followed by incubation 20 hr at 37°C and humidified 5% CO2 atmosphere. A Mabtech IRIS ELISpot/FluoroSpot reader (Mabtech AB, Nacka Strand, Sweden) was used for the quantification of spot-forming B and T cells (SFCs). Data analysis was carried out with the Mabtech Apex software (version 2.0, Mabtech AB, Nacka Strand, Sweden).
Statistical analysis
Demographic data were statistically assessed with the use of Fisher’s exact test. For statistical comparisons of total IgG, MFI, flow cytometry and FluoroSpot data, Kruskal-Wallis tests with Dunn’s multiple comparison were performed for comparisons between three groups, and Mann-Whitney tests were performed for comparisons between two groups. Simple linear regressions were carried out to assess correlations between age and total Ig levels and IgG MFI levels in patients. Data regarding nAbs were statistically analyzed with Fisher’s exact tests for categorical variables and Mann-Whitney tests for data with continuous variables. For FACS data, outliers were identified through the ROUT method (
Results
Demography of the study cohort
When comparing SARS-CoV-2 IgG+ patients (n = 78) with the IgG- patients (n = 57), there were no significant differences regarding sex, current level of immunosuppression, or diagnosis (Table 1). Six patients received intravenous IgG (IvIG) replacement therapy within six months before sampling of which four children were SARS-CoV-2 IgG+. Most patients (five out of six) on IvIG had a medical history of allo-HSCT. However, significant differences were found with regards to age, where IgG+ patients and siblings, all IgG+, had a significantly higher median age than IgG- patients (p < 0.01). Previous COVID-19 vaccination also differed, where 17.9% of IgG+ patients had been vaccinated compared to only 1.8% vaccinated in IgG- patients (p < 0.001). Within this pediatric oncological and hematological cohort, neither immunosuppression nor cancer diagnosis influenced a patient’s ability to seroconvert in response to SARS-CoV-2.
Table 1
| Clinical characteristics | SARS-CoV-2 IgG- patients (n = 57) | SARS-CoV-2 IgG+ patients (n = 78) | Siblings (n = 14) | p-value |
|---|---|---|---|---|
| Age in years, median (range) | 6 (0–18) | 10 (1–17) | 13 (2–15) | < 0.01 |
| Age groups | < 0.05 | |||
| 0–3 years old (n = 36) | 20 (35.1%) | 15 (19.2%) | 1 (7.1%) | |
| 4–10 years old (n = 52) | 23 (40.4%) | 25 (32.1%) | 4 (28.6%) | |
| 11–18 years old (n = 61) | 14 (24.6%) | 38 (48.7%) | 9 (64.3%) | |
| Sex | ns | |||
| Boy (n = 74) | 26 (45.4%) | 40 (51.3%) | 8 (57.1%) | |
| Girl (n = 75) | 31 (54.4%) | 38 (48.7%) | 6 (42.9%) | |
| Diagnosis# | ns | |||
| Lymphoma (n = 13) | 5 (8.8%) | 8 (10.3%) | – | |
| Leukemia (n = 45) | 15 (26.3%) | 30 (38.5%) | – | |
| Solid tumor (n = 39) | 18 (31.6%) | 21 (26.9%) | – | |
| CNS tumor (n = 21) | 14 (24.6%) | 7 (9.0%) | – | |
| Non-malignant disorder (n = 17) | 5 (8.8%) | 12 (15.4%) | – | |
| Immunosuppression | ns | |||
| None (n = 22) | 9 (15.8%) | 13 (16.7%) | – | |
| Mild (n = 34) | 19 (33.3%) | 15 (19.2%) | – | |
| Moderate (n = 28) | 12 (21.1%) | 16 (20.5%) | – | |
| Severe (n = 51) | 17 (39.8%) | 34 (43.6%) | – | |
| IvIG replacement therapy | 1 (1.8%) | 5(6.4%) | ns | |
| COVID-19 vaccinated | < 0.001 | |||
| Yes (n = 22) | 1 (1.8%) | 14 (17.9%) | 7 (50.0%) | |
| No (n = 116) | 51 (89.5%) | 58 (74.4%) | 7 (50.0%) | |
| Unknown (n = 11) | 5 (8.8%) | 6 (7.7%) | 0 (0.0%) |
Clinical characteristics in patients and healthy siblings.
A Kruskal-Wallis test was performed for the continuous variable and Fisher’s exact tests were performed for all categorical variables. Statistically significant p-values ≤ 0.05 are indicated in bold
-, negative; +, positive; CNS, central nervous system; COVID-19, coronavirus disease 2019; IvIG, intravenous immunoglobulin; ns, not significant; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.
# A detailed description of diagnoses is found in Supplementary Table 1.
Total immunoglobulin levels reflect the degree of immunosuppression
Total (i.e., not SARS-CoV-2-specific) IgG, IgA, and IgM levels were determined and analyzed in all patients to give an overview of the B-cell compartment and to validate the clinically assessed degree of immunosuppression (Figure 2). With regards to age, there was a significant trend of higher total IgG levels in older children within the patient cohort (median of 4.90 g/L for 0–3-year-olds vs 7.15 g/L for 4–10-year-olds, p < 0.001 and vs 7.90 g/L for 11–18-year-olds, p < 0.0001, Figure 2A). A similar trend was seen with regards to total IgA levels where significantly higher concentrations were observed in 4–10-year-olds and 11–18-year-olds compared to toddlers of 0–3 years of age (median of 0.41 g/L for 0–3-year-olds vs 0.85 g/L for 4–10-year-olds, p < 0.01 and vs 1.50 g/L for 11–18-year-olds, p < 0.0001, Figure 2A). No differences were seen in total IgM levels with age. Diagnosis did not impact on immunoglobulin levels. Children substituted with IvIG had normal IgG values according to age (data not shown).
Figure 2

Differences in total immunoglobulin in immunosuppressed children and healthy siblings. (A) Levels of total immunoglobulin (Ig) G, IgA, and IgM (g/L) between groups of patients according to age (n = 135) and (B) current immunosuppressive treatment (n = 149, including healthy siblings (n = 14)). (C) Linear regressions of total IgG, IgA, and IgM levels according to age for all three levels of immunosuppressive treatment and healthy siblings (n = 149). For IgG: p < 0.01 and R2 = 0.36 for patients with no immunosuppression, p < 0.0001 and R2 = 0.27 for patients with mild/moderate immunosuppression, p < 0.001 and R2 = 0.20 for patients with severe immunosuppression and p < 0.05 and R2 = 0.42 for siblings; for IgA: p < 0.001 and R2 = 0.50 for patients with no immunosuppression, p < 0.001 and R2 = 0.20 for mild/moderate, p < 0.01 and R2 = 0.20 for severe and p < 0.05 and R2 = 0.37 for siblings; for IgM: p < 0.05 and R2 = 0.08 for patients with mild/moderate immunosuppression and p < 0.05 and R2 = 0.44 for siblings. A Kruskal-Wallis test with Dunn’s multiple comparison test was performed to determine significant differences in age and immunosuppressive groups. Simple linear regressions were run for graphs with total Ig levels plotted against age as a continuous fact. Statistical significance was defined as p ≤ 0.05 (** p ≤ 0.01, *** p ≤ 0.001, **** p ≤ 0.0001) with medians shown as red horizontal lines.
With regards to the varying degrees of immunosuppression in the patient cohort (Figure 2B), total IgG levels were significantly lower in patients with ongoing severe immunosuppression compared both to patients without ongoing immunosuppression and patients with only mild/moderate immunosuppression (median of 5.80 g/L in patients with severe immunosuppression vs median of 8.50 g/L in patients with no immunosuppression, p < 0.001, and vs 7.55 g/L with mild/moderate immunosuppression, p < 0.001, Figure 2B). Once again, a similar trend was seen when looking at total IgA levels, where patients with severe immunosuppression had significantly lower total IgA concentrations when compared to patients without ongoing immunosuppression (median of 0.66 g/L vs 1.35 g/L, p < 0.01). Finally, with regards to IgM, severely immunosuppressed patients once again had lower levels of IgM compared to non-immunosuppressed patients (median of 0.41 g/L vs 0.81 g/L, p < 0.01). Healthy siblings showed similar levels of total IgA and IgG, and slightly higher IgM levels, compared to patients without ongoing immunosuppression (Figure 2B). The differences in total immunoglobulin levels between the groups confirmed the clinically assessed severity of immunosuppression following treatment and its effect on the B-cell compartment.
Analyzing immunosuppression and age together, significant correlations were found in total IgG and IgA levels with age in all immunosuppression groups (Figure 2C). The total IgM levels in patients with no immunosuppression showed a negative, though non-significant, trend with age. Siblings and patients with mild/moderate immunosuppression had significant positive correlations between age and IgM levels (Figure 2C). The impact of age on total immunoglobulin levels, though affected by immunosuppression, was seen in all patient groups.
Quality of antibody responses to SARS-CoV-2 in children with cancer or hematologic disease
SARS-CoV-2-specific antibodies were qualitatively evaluated in the 78 SARS-CoV-2 IgG+ patients and 14 siblings (Figure 3). No significant variations in SARS-CoV-2-specific IgG MFI levels were found in SARS-CoV-2 IgG+ patients with regards to immunosuppression or age (Figure 3A, upper panel). Clinical diagnosis did not impact on the SARS-CoV-2 antibody responses (data not shown). However, weak trends could be noticed, with increasing SARS-CoV-2-specific IgG MFI with age and decreasing MFI with increasing immunosuppression. In addition, SARS-CoV-2 IgG MFI showed a weak correlation to total IgG (Supplementary Figures 1A, B).These trends were also observed when quantifying through ELISA, which correlated well with MFI levels, though, once again, no significant differences were found (Supplementary Figures 1C, D). SARS-CoV-2 IgA seroconversion occurred in fewer patients (n = 17) and showed similar trends of lower SARS-CoV-2-specific IgA MFI levels with increasing immunosuppression and slightly higher IgA MFI levels with age, though these differences were not statistically significant (Figure 3A, lower panel). Analyzing age and immunosuppression together, a significant correlation between age and SARS-CoV-2-specific IgG MFI was found in patients with no and mild/moderate immunosuppression but was non-existent in patients with severe immunosuppression (Figure 3B). Finally, it was observed that an important factor for IgG MFI levels was whether IgA seroconversion occurred or not (Figure 3C), with IgA+ patients showing significantly higher IgG MFI levels compared to IgA- patients (median of 7,186 MFI vs 1,815 MFI, p < 0.0001).
Figure 3

SARS-CoV-2 immunoglobulin levels and presence of neutralizing antibodies in seropositive patients according to age and immunosuppressive treatment. (A) SARS-CoV-2-specific immunoglobulin (Ig) G and IgA median fluorescence intensity (MFI) in IgG-seropositive patients based on age and current immunosuppressive treatment. Cut-off (dotted line) for IgG seropositivity set to 300 MFI (n = 78), cut-off (dotted line) for IgA seropositivity to 750 MFI (n = 17). (B) IgG MFI with regards to age as a continuous factor in seropositive patients of all immunosuppressive groups (n = 78), p < 0.01 and R2 = 0.52 for patients with no immunosuppression, p < 0.01 and R2 = 0.28 for patients with mild/moderate immunosuppression. (C) IgG MFI depending on IgA seroconversion (n = 78). (D) Presence of neutralizing antibodies (nAbs) based on current immunosuppression (none, n = 13; mild/moderate, n = 32; severe, n = 34; left graph) as well as IgG MFI depending on the presence of nAbs (right graph). A Kruskal-Wallis test with Dunn’s multiple comparison test was performed to determine significant differences in age and immunosuppressive groups. A Mann-Whitney test was carried out for significances in IgG MFI based on IgA seropositivity and presence of nAbs. Simple linear regressions were run for graphs with total Ig levels plotted against age as a continuous fact. Statistical significance was defined as p ≤ 0.05 (**** p ≤ 0.0001) with medians shown as red horizontal lines.
The quality of the SARS-CoV-2 antibody responses was further assessed through the determination of SARS-CoV-2 nAbs in serum. Most importantly, SARS-CoV-2 nAbs were found in patients of all ages and degrees of immunosuppression. When comparing the proportions of IgG+ patients with or without nAbs, grouped by immunosuppression, we found a slightly larger occurrence of nAbs in patients with no current immunosuppression compared to patients with mild/moderate or severe immunosuppressive treatment (76.9% vs 53.1% and 52.9%, respectively). The presence of nAbs was significantly correlated with the presence of SARS-CoV-2 IgA response, as well as increased IgG and IgA MFI levels (p < 0.0001, respectively Figure 3D; Table 2).
Table 2
| Clinical characteristics | nAbs- (n = 33) | nAbs+ (n = 45) | p-value |
|---|---|---|---|
| Age in years, median (range) | 7 (1–18) | 12 (2–18) | ns |
| Age groups | < 0.05 | ||
| 0–3 years old (n = 15) | 7 (21.2%) | 8 (17.8%) | |
| 4–10 years old (n = 25) | 15 (45.5%) | 10 (22.2%) | |
| 11–18 years old (n = 38) | 11 (33.3%) | 27 (60.0%) | |
| Sex | ns | ||
| Boy (n = 40) | 14 (42.4%) | 26 (57.8%) | |
| Girl (n = 38) | 20 (57.6%) | 19 (42.2%) | |
| Diagnosis# | ns | ||
| Lymphoma (n = 8) | 5 (15.2%) | 3 (6.7%) | |
| Leukemia (n = 30) | 15 (45.5%) | 15 (33.3%) | |
| Solid tumor (n = 21) | 8 (24.2%) | 13 (28.9%) | |
| CNS tumor (n = 7) | 1 (3.0%) | 6 (13.3%) | |
| Non-malignant (n = 12) | 4 (12.1%) | 8 (17.8%) | |
| Allo-HSCT | ns | ||
| Yes (n = 14) | 5 (15.2%) | 9 (20.0%) | |
| No (n = 64) | 28 (84.4%) | 36 (80.0%) | |
| Immunosuppression | ns | ||
| None (n = 13) | 3 (9.1%) | 10 (22.2%) | |
| Mild (n = 15) | 8 (24.2%) | 7 (15.6%) | |
| Moderate (n = 16) | 6 (18.2%) | 10 (22.2%) | |
| Severe (n = 34) | 16 (48.5%) | 18 (40.0%) | |
| Total Ig, median (range) | |||
| Total IgG g/L | 6.9 (2.4–14.2) | 7.3 (2.1–27.3) | ns |
| Total IgA g/L | 0.72 (0.05–3.20) | 1.00 (0.05–4.90) | ns |
| Total IgM g/L | 0.36 (0.07–1.50) | 0.62 (0.05–2.70) | < 0.05 |
| COVID-19 vaccination | ns | ||
| Yes (n = 14) | 4 (12.1%) | 10 (22.2%) | |
| No (n = 58) | 25 (75.8%) | 33 (73.3%) | |
| Unknown (n = 6) | 4 (12.1%) | 2 (4.4%) | |
| SARS-CoV-2 IgA response | < 0.0001 | ||
| IgA- (n = 61) | 33 (100.0%) | 28 (62.2%) | |
| IgA+ (n = 17) | 0 (0.0%) | 17 (37.8%) | |
| SARS-CoV-2 MFI median (range) | |||
| IgG MFI | 1,242 (331–5,096) | 4,757 (516–11,904) | < 0.0001 |
| IgA MFI | 73 (0–421) | 542 (0–5,436) | < 0.0001 |
Clinical characteristics for patients according to presence of neutralizing antibodies.
Mann-Whitney tests were performed for all continuous variables and Fisher’s exact tests for all categorical variables. Statistically significant p-values ≤ 0.05 are indicated in bold.
Allo-HSCT, allogeneic hematological stem cell transplant; CNS, central nervous system; COVID-19, coronavirus disease 2019; IgA, immunoglobulin A; IgG, immunoglobulin G; IgM, immunoglobulin M; MFI, median fluorescence intensity; nAbs, neutralizing antibodies; ns, not significant; -, negative; +, positive; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.
# A detailed description of diagnoses is found in Supplementary Table 1.
Thereafter, an attempt was made to elucidate possible factors correlating with the presence of SARS-CoV-2 nAbs in this cohort (Table 2). There was a significant correlation with age, where the proportion of teenagers was higher in patients with nAbs compared to patients without (p < 0.05). Neither sex, immunosuppression, diagnosis, previous allo-HSCT, nor vaccination correlated with the presence of nAbs. On the other hand, nAbs was significantly correlated with higher MFI levels of IgG (p < 0.0001) and IgA (p < 0.0001) as well as SARS-CoV-2 IgA seroconversion (p < 0.0001). Finally, total IgM levels were also higher in nAbs+ patients (p < 0.05). Regardless of immunosuppression and immunoglobulin levels, age was found to be a greater determinant of the patients’ ability to effectively respond to a SARS-CoV-2 infection in terms of IgG and IgA responses and neutralizing capacity.
Memory B-cell responses to SARS-CoV-2 proteins
Although the B-cell compartment in severely immunosuppressed patients exhibited a general suppressive state, as indicated by total immunoglobulin levels, this suppression was not reflected in the levels or functionality of SARS-CoV-2-specific antibodies. To further investigate the B-cell compartment, PBMCs from both patients and their siblings were immunophenotyped, using flow cytometry. (Figure 4A). Due to the low number of PBMC samples available, both patients and siblings were from now on grouped by and compared based on age (0–10 years vs 11–18 years of age) and whether they ever experienced immunosuppressive treatment or not. As expected, the frequency of B-cells (live CD14-/CD19+ single cells) was significantly lower in children exposed to immunosuppression compared to children who had never been exposed to immunosuppression (median of 0.87% vs 7.29%, p < 0.01, Figure 4B).
Figure 4

Difference in B-cell proportions and memory B-cell responses in children based on age and previous or ongoing immunosuppressive treatment in life. (A) Representative gating strategy of the B-cell population from peripheral blood mononuclear cells. (B) Proportion of B cells in children exposed to immunosuppression or never exposed (n = 56). In five patients, PBMCs from a subsequent time-point was used for the Fluorospot assay compared to serology. (C) Representative FluoroSpot wells from a 12-year-old patient with Diamond-Blackfans anemia showing total IgG (yellow) as well as IgG specific to spike (S) (green) and receptor-binding domain (RBD) (red) of SARS-CoV-2 following pre-stimuli with IL-2 and R848. (D) Count of total IgG spot forming cells (SFC) as well as proportion of RBD and S SFCs depending on age and previous or ongoing immunosuppression in life (n = 24 for total IgG, n = 20 for RBD and S). A Mann-Whitney test was performed to determine significant. Statistical significance was defined as p ≤ 0.05 (* ≤ 0.05, ** ≤ 0.01, *** p ≤ 0.001) with medians shown as red horizontal lines. IS, immunosuppression; SFU, spot-forming units.
Following this, an attempt was made to bring further clarity to cellular B-cell memory against SARS-CoV-2 through FluoroSpot (Figure 4C). As the flow cytometric analysis showed significant differences in B-cell proportions between children with and without immunosuppression, RBD- and S-specific IgG SFCs were normalized to total IgG SFCs to account for differences in B-cell proportions. Total IgG SFCs did not differ between young children (0–10-year-olds) compared to older children (11–18-year-olds) (Figure 4D). However, age correlated to the proportion of S-specific IgG SFCs, with a significantly higher median in older children compared to younger children (median of 9.43% vs 2.40%, p < 0.001). A similar difference was also observed in RBD-specific IgG SFCs (median of 3.03% vs 0.24%, p < 0.01). With regards to immunosuppression, there were no significant differences in total IgG SFCs between children with or without experience of immunosuppression (Figure 4D), nor were there any significant differences seen when comparing the proportions of S-specific IgG SFCs. However, children who had experienced immunosuppression showed a significantly lower proportion of RBD-specific IgG SFCs compared to those who had not (median of 3.01% vs 0.31%, p < 0.05) despite having similar age between the groups (data not shown). These results imply that age has the largest effect on specific MBCs to SARS-CoV-2 S- and RBD-specific IgG in general, while immunosuppression negatively impacts the differences seen in RBD-specific IgG-secreting cells.
Association between polyclonal and SARS-CoV-2 specific IFN-γ and IL-2 producing T-cells
Fourteen patients with IgG antibodies against SARS-CoV-2 had enough PBMCs for T-cell FluoroSpot analysis as well. Representative images of responses following T-cell activation at bulk (with anti-CD3) or at antigen-specific level (SARS-CoV-2 peptides) are depicted in Supplementary Figure 2A. Overall, activation at bulk T-cell level with antigen elicited in general higher numbers of IFN-γ and IL-2 responses compared to polyfunctional IFN-γ and IL-2 responses (Supplementary Figure 2B). As sample size was limited, no statistical significances were calculated. However, there seems to be a trend towards lower IFN-γ and especially IL-2 responses to SARS-CoV-2 peptides with more severe immunosuppression.
Discussion
The COVID-19 pandemic brought many challenges to children with cancer or hematological disease worldwide. However, it also allowed for the study of immune responses to a completely new viral pathogen in immunocompromised patients. This single-center cohort was rapidly set up in June 2020 with the overall aim to bring insights into how infection with SARS-CoV-2 affects immunosuppressed children. Previous findings from this cohort and others have shown that most children with cancer or hematological diseases have mild symptoms of COVID-19 and that antibodies against SARS-CoV-2 can be detected in patients upon infection (
First, we analyzed total immunoglobulin levels to mirror the assessed immunosuppression state, regarding both age and treatment intensity. Our findings align with previous pediatric research supporting the idea that immunoglobulin levels increase with age and immune maturation (
To our knowledge, despite their correlation with protective immunity (
To clarify the role of SARS-CoV-2 B-cell immunity, we evaluated antigen-specific MBC responses, focusing on those generated through the germinal center (GC) reaction. When stratified by age or immunosuppression status, there were no significant differences in the total number of IgG SFCs between the groups. However, SARS-CoV-2-specific responses varied significantly across age groups, with older individuals showing increased numbers of both S and RBD IgG SFCs, a finding that aligns with previous data in healthy children (
It is important to recognize that humoral immunity alone does not fully account for effective antiviral defense mechanisms. Further research is warranted to delineate the immunological impact of cancer and its treatment in pediatric populations. T-cell studies have demonstrated functional impairments following chemotherapy, which increased with increasing numbers of chemotherapy cycles (
Conclusion
Our results show that most pediatric oncological and hematological patients can mount a broad antibody response upon SARS-CoV-2 natural infection or vaccination, although there is a variability in their response mostly influenced by increasing age. MBC responses in children with immunosuppression were blunted with fewer RBD IgG-secreting cells. Essentially, our findings underscore that young children with severe treatment-related immunosuppression are at risk for less effective B-cell responses upon viral infection. This is in line with previous studies on vaccine B-cell immunity after chemotherapy and should be considered in management of clinical infections and for vaccination strategies in childhood cancer survivors.
Statements
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
The studies involving humans were approved by Swedish Ethical Review Authority granted ethical approval (2020–02154, 2020–04672, 2022-02068-02). The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participants’ legal guardians/next of kin.
Author contributions
ET: Formal Analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing, Data curation. ES: Data curation, Formal Analysis, Investigation, Writing – original draft, Writing – review & editing. ARA: Data curation, Formal Analysis, Investigation, Writing – original draft, Writing – review & editing. HA: Investigation, Writing – review & editing, Methodology, Writing – original draft. RV: Formal Analysis, Writing – review & editing, Resources, Software, Supervision, Validation. LK: Writing – review & editing, Data curation, Methodology, Validation. DA: Methodology, Writing – review & editing, Data curation, Validation. JL: Methodology, Writing – review & editing, Data curation, Validation. AH: Resources, Supervision, Writing – review & editing, Conceptualization, Funding acquisition. SSH: Writing – review & editing, Conceptualization, Formal Analysis, Investigation, Supervision. TH: Methodology, Writing – review & editing, Conceptualization, Formal Analysis, Funding acquisition, Resources, Supervision. AN: Methodology, Validation, Writing – review & editing, Conceptualization, Formal Analysis, Funding acquisition, Investigation, Project administration, Resources, Supervision, Writing – original draft.
Funding
The author(s) declare that financial support was received for the research and/or publication of this article. This work was supported by grants from the Swedish Childhood Cancer Foundation (KP2021-0034) (AN, AH), Lions cancer research fund Uppsala-Örebro (AH), and the Swedish Research Council (VR 2020-02244) (AN). TH was supported by the SciLifeLab´s Pandemic Laboratory Preparedness projects (LPP1-07; REPLP1:005), the European Union’s Horizon 2020 research innovation program (grant no. 874735; VEO), and the AXA Research fund. ES was supported by the Anna-Lisa and Arne Gustafson Foundation.
Acknowledgments
We acknowledge Bengt Rönnberg for his valuable input regarding the COVID-19 SMIA analyses.
Conflict of interest
SSH was employed by Amgen during the time of the study. Amgen was not involved and had no influence on this study. RV was employed by Mabtech. The FluoroSpot kits and reader used within this study were produced by Mabtech. Mabtech had no influence on the study design or content of this study. HA was employed by Karolinska Institutet during the time of performing experiments in the study.
The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.
Generative AI statement
The author(s) declare that no Generative AI was used in the creation of this manuscript.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2025.1613778/full#supplementary-material
Supplementary Figure 1SARS-CoV-2 IgG levels in seropositive children measured through Enzyme-Linked Immunosorbent Assay. (A) Variations in SARS-CoV-2 IgG levels in seropositive patients based on age and level of immunosuppression. (B) Correlation between quantification of SARS-CoV-2 IgG through Enzyme-Linked Immunosorbent Assay (ELISA) (Spike (S) trimer, units/mL) and suspension multiplex immunoassay (SMIA) (S1, median fluorescence intensity (MFI)). A Kruskal-Wallis test with Dunn’s multiple comparison test was performed to determine significant differences between age and immunosuppressive groups. A correlation was calculated with a nonparametric Spearman correlation (**** p < 0.0001, R = 0.8571). Statistical significance was defined as p ≤ 0.05 with medians shown as red horizontal lines.
Supplementary Figure 2Levels of IFN-γ and IL-2 secreting T cells in seropositive patients grouped by level of immunosuppression. (A) Representative Fluorospot well image for IFN-γ and IL-2 spot-forming units (SFUs) after polyclonal activation (anti-CD3+anti-CD28) (upper row) or antigen-specific activation (SARS-CoV-2 peptides+anti-CD28) (lower row). (B) Patients were group into three groups based on immunosuppression, either no ongoing immune suppression (n=3), mild/moderate immunosuppression (n=4) or severe immunosuppression (n=7). No statistical test was carried out.
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Summary
Keywords
SARS-CoV-2 infection, antibody responses, memory B cells, childhood cancer, hematological disease
Citation
Tiselius E, Sundberg E, Ramilo Amor A, Andersson H, Varnaite R, Kolstad L, Akaberi D, Ling J, Harila A, Saghafian-Hedengren S, Hoffman T and Nilsson A (2025) The quantity and quality of B-cell immunity against SARS-CoV-2 in children with cancer and hematological diseases. Front. Immunol. 16:1613778. doi: 10.3389/fimmu.2025.1613778
Received
17 April 2025
Accepted
10 June 2025
Published
02 July 2025
Volume
16 - 2025
Edited by
Shahram Salek-Ardakani, Inhibrx, United States
Reviewed by
Sergio Gil-Manso, Columbia University Irving Medical Center, United States
Mattia Moratti, University of Rome Tor Vergata, Italy
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Copyright
© 2025 Tiselius, Sundberg, Ramilo Amor, Andersson, Varnaite, Kolstad, Akaberi, Ling, Harila, Saghafian-Hedengren, Hoffman and Nilsson.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Anna Nilsson, anna.nilsson.1@ki.se
†These authors share first authorship
‡These authors share senior authorship
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.