# Humoral immune response to Covid-19 vaccination in patients with cancer – Results from the ANRS0001S COV-POPART study

Liem Binh Luong Nguyen, Lyvia Magloire, Alexis François, David Billard, Frank Priou, Jennifer Arrondeau, Claude Linassier, Ines Ben Ghezala, Marine Gross-Goupil, Julie Charles, et al.

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## To cite this version:

Liem Binh Luong Nguyen, Lyvia Magloire, Alexis François, David Billard, Frank Priou, et al. Humoral immune response to Covid-19 vaccination in patients with cancer – Results from the ANRS0001S COV-POPART study. Vaccine, 2025, 63, pp.127633. 10.1016/j.vaccine.2025.127633. hal-05288940

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# Humoral immune response to Covid-19 vaccination in patients with cancer – Results from the ANRS0001S COV-POPART study

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Liem Binh Luong Nguyen<sup>a,b,c,*</sup>, Lyvia Magloire<sup>d</sup>, Alexis François<sup>d</sup>, David Billard<sup>e</sup>, Frank Priou<sup>f</sup>, Jennifer Arrondeau<sup>g</sup>, Claude Linassier<sup>h</sup>, Ines Ben Ghezala<sup>i</sup>, Marine Gross-Goupil<sup>j,k</sup>, Julie Charles<sup>l</sup>, Nadine Dohollou<sup>m</sup>, Philippe Vanhems<sup>n</sup>, Claire Cracowski<sup>o</sup>, Anne Marie Leroi<sup>p</sup>, Fabrice Lainé<sup>q</sup>, Florence Galtier<sup>r</sup>, Karine Barthelemy<sup>s</sup>, Stéphane Priet<sup>s</sup>, Mariam Gharib<sup>t</sup>, Mathieu Chalouni<sup>d</sup>, Aude Barquin<sup>d</sup>, Paul Loubet<sup>a,u,v</sup>, Xavier de Lamballerie<sup>s</sup>, Odile Launay<sup>a,b,c</sup>, Linda Wittkop<sup>d,w,x</sup>, Jean-Yves Blay<sup>y,z,l</sup>, Jean-Philippe Spano<sup>aa,1</sup>, on behalf of the ANRS0001S COV-POPART cohort study group

## ARTICLE INFO

Keywords:
Vaccine
COVID-19
Immunogenicity

## ABSTRACT

**Background:** Patients with cancer, whose immune responses to vaccines are commonly weaker than those of the general population, are recommended a booster dose after two initial doses of Covid-19 vaccine. Our objective was to compare the humoral immunogenicity of Covid-19 vaccines in patients with cancer compared to healthy adults (control group) after primary vaccine series and after a booster dose.

<footnote><sup>a</sup> INSERM, F-CRIN, Reseau Innovative Clinical Research in Vaccinology (IREIVAC), Paris, France</footnote>

<footnote><sup>b</sup> Centre d'Investigation Clinique Cochin Pasteur, Paris, France</footnote>

<footnote><sup>c</sup> Université de Paris, Paris, France</footnote>

<footnote><sup>d</sup> Univ. Bordeaux, INSERM, MART, UMS 54, F-33000 Bordeaux, France</footnote>

<footnote><sup>e</sup> Oncologie et soins de support, Hopital Foch, Suresnes, France</footnote>

<footnote><sup>f</sup> Service Oncohématologie Médecine Interne, Centre Hospitalier Départemental Vendée, La Roche-Sur-Yon, France</footnote>

<footnote><sup>g</sup> Department of Medical Oncology, Cochin University Hospital, Institut du Cancer Paris CARPEM, AP-HP, Paris, France</footnote>

<footnote><sup>h</sup> Department of Medical Oncology, Centre Hospitalier Régional Universitaire, 37000 Tours, France</footnote>

<footnote><sup>i</sup> INSERM, CIC 1432, Clinical Investigation Center, Clinical Epidemiology/Clinical Trials Unit, University Hospital Dijon-Burgundy, Dijon, France</footnote>

<footnote><sup>j</sup> Department of Medical Oncology, Saint-André University Hospital, Bordeaux, France</footnote>

<footnote><sup>k</sup> Inserm, F-CRIN, Réseau Innovative Clinical Research in Vaccinology (I-REIVAC), Paris, France</footnote>

<footnote><sup>l</sup> Dermatology Department, CHU Grenoble Alpes, University Grenoble Alpes, INSERM U 1209, CNRS UMR 5309, Institut for Advanced Biosciences, Grenoble, France</footnote>

<footnote><sup>m</sup> Department of Medical Oncology, Polyclinique Bordeaux Nord Aquitaine, Unicancer Bordeaux, France</footnote>

<footnote><sup>n</sup> Service Hygiène, Épidémiologie, Infectio vigilance Et Prévention, Hôpital Edouard Herriot, Hospices Civils de Lyon – Equipe Epidémiologie et Santé Publique Université
Claude Bernard Lyon 1, Lyon, France</footnote>

<footnote><sup>o</sup> Inserm Centre d'Investigation Clinique 1406, Centre Hospitalier Grenoble-Alpes, Grenoble, France</footnote>

<footnote><sup>p</sup> Univ Rouen Normandie, CIC-CRB 1404, CHU Rouen, F-76000 Rouen, France</footnote>

<footnote><sup>q</sup> INSERM CIC 1414, Centre Hospitalier Universitaire de Rennes, Hôpital Pontchaillou, Rennes, France</footnote>

<footnote><sup>r</sup> INSERM CIC 1411, Centre Hospitalier Universitaire de Montpellier, Hôpital Saint-Eloi, Montpellier, France</footnote>

<footnote><sup>s</sup> Unité des Virus Émergentes (UVE: Aix-Marseille Univ, Université di Corsica, IRD 190, Inserm 1207, IRBA), France</footnote>

<footnote><sup>t</sup> ANRS Maladies infectieuses émergentes (ANRS MIE), Paris, France</footnote>

<footnote><sup>u</sup> Service des Maladies Infectieuses et Tropicales, CHU de Nîmes, Nîmes, France</footnote>

<footnote><sup>v</sup> INSERM U1047 - Université de Montpellier, Nîmes, France</footnote>

<footnote><sup>w</sup> CHU de Bordeaux, Service d'information médicale, INSERM, Institut Bergonie, CIC-EC 1401, Bordeaux, France</footnote>

<footnote><sup>x</sup> Inria équipe SISTM, Talence, France</footnote>

<footnote><sup>y</sup> Centre Léon-Bérard, Département de cancérologie médicale, Lyon, France</footnote>

<footnote><sup>z</sup> Université Bernard Lyon, Unicancer, Lyon, France</footnote>

<footnote><sup>aa</sup> Sorbonne université, Inserm, institut Pierre-Louis d'épidémiologie et de santé publique (IPLESP), équipe TheraVir, AP-HP, Hôpital universitaire Pitié-Salpetrière, Oncologie médicale, CLIP<sup>2</sup> Galilée, Paris, France</footnote>

<footnote>* Corresponding author at: CIC Cochin Pasteur, 27, rue du Faubourg Saint Jacques, 75014 Paris, France.
E-mail address: liem.luong@aphp.fr (L.B. Luong Nguyen).</footnote>

<footnote n="1">¹ These authors contributed equally.</footnote>
Booster
cancer

**Methods:** We included participants aged ≤75 and vaccinated with two doses in the primary vaccine series and a booster, from the French national prospective Covid-19 vaccine cohort study (ANRS0001S COV-POPART) and excluded those with SARS-CoV-2 infection. Percentage of responders, geometric mean titers (GMT) of anti-SARS-CoV-2 IgG antibodies (ELISA) and specific neutralizing antibodies against original strain, Delta and Omicron variants of concern, were estimated one month after the primary vaccine series, then one month and six months after a booster dose.

**Results:** We included 183 patients with cancer and 1173 controls. The most frequent cancers were breast (37.2 %) and lung cancer (17.5 %). Patients with cancer were older and had lower anti-Spike IgG levels after the primary vaccine series (GMT = 132.4 vs 332.7 BAU/mL, *P* < 0.0001), but they developed similar response at one month (GMT = 2146.1 vs 1841.3 BAU/mL, *P* = 0.16) and six months after booster (602.0 vs 574.4 BAU/mL, *P* = 0.80). Neutralizing antibodies levels confirmed these results.

**Conclusion:** Patients with cancer have comparable response rates to controls one month and six months after a booster dose. Our results support the benefit of a booster dose in patients with cancer.

# 1. Introduction

Since the beginning of the SARS-CoV-2 pandemic and even in the context of Omicron Variant Of Concern (VOC) circulation, patients with cancer have consistently been identified to be at higher risk of severe disease and mortality [1-4]. With the lifting of generalized non-pharmaceutical prevention policies and limited options for passive immunization treatment, vaccination remains the best way to prevent severe Covid-19 and death [5]. For patients with cancer, the French guidelines recommend a primary vaccine series with two doses, a booster dose three to six months afterwards, and regular booster once or twice a year [6-8]. These recommendations are based on early data on the effectiveness of booster dose in patients with cancer [9,10]. However, the compared durability of the immune response after a booster dose in patients with cancer and healthy individuals have seldom been reported [3]. We present here the humoral immune responses in patients with cancer one month after the primary vaccine series, and one month and six months after a booster dose (corresponding to 12 months after the primary vaccine series), as part of the ANRS0001S COV-POPART, a French national cohort study designed to measure and compare the immunogenicity of Covid-19 vaccines among vulnerable population, as compared with healthy adults (control group) [11].

# 2. Methods

## 2.1. Study design

The ANRS0001S COV-POPART study is a French national multi-center prospective cohort study designed to evaluate humoral response at 1, 6, 12 and 24 months after the first two doses of Covid-19 vaccines (primary vaccine series) in 11 specific subpopulations, including patients with cancer, compared to healthy adults (control group), who are participants aged ≥18 years old who have not any conditions defining specific subpopulations, nor conditions that would influence the vaccine immune response. Following the implementation of a booster dose six months after the primary vaccine series, an additional assessment of the immune response was made one month after the booster dose. Thus, the humoral response at twelve months post primary vaccine series corresponds to six months post booster. The study was conducted in 36 participating centers in France in collaboration with the I-REIVAC network (32 COVIREIVAC centers and 4 cancer centers), ten national academic societies, and seven patients' associations. Patients were included during the first phase of the French vaccination campaign, which started in France on 27th December 2020. The study protocol (No. EudraCT/ID-RCB: 2021-A00348-33) was conducted in accordance with the Declaration of Helsinki principles, the French law governing research involving human subjects (known as 'Loi Jardé'), and in full compliance with EU GDPR (General Data Protection Regulation) requirements. The protocol was approved by the 'CPP Nord-Ouest IV' institutional review board (file number: 21.02.12.47147) and the

French national data protection authority 'CNIL' (authorization number 921111v1).

## 2.2. Study population

Inclusion criteria for the solid cancer subpopulation were: 1) having been treated for the last two years for a solid cancer, and belonging to one of the four following subgroups defined by the timing and type of treatment: patients undergoing long-term follow-up for cancer, without cancer treatment for at least six months, and included less than two years after the end of treatment (subgroup 1); patients who have received active cancer treatment other than chemotherapy (e.g targeted therapy, radiotherapy, surgery, hormonotherapy) in the previous month (subgroup 2); patients treated with chemotherapy (alone or in combination with immunotherapy, radiotherapy, or targeted therapy) in the previous month (subgroup 3); patients who had been treated with immunotherapy, combined with anti-PD1, anti-PD-L1, or anti-CTLA4 antibodies, without chemotherapy (subgroup 4); 2) having received two vaccine doses in the primary vaccine series. To assess the humoral response post booster, we had an additional inclusion criteria, 3) a documented booster dose at least a booster injection six months (+/- one month) after the primary vaccine series. The main exclusion criteria were pregnancy or breastfeeding, history of known SARS-CoV-2 infection, and any contraindications to vaccination. Finally, for the analysis of each studied timepoints, we excluded participants with missing serological results and those tested positive for SARS-CoV-2 anti-nucleocapsid (NCP) antibodies (to exclude asymptomatic SARS-CoV-2 infections).

## 2.3. Outcomes

There were five main outcomes measured at three timepoints: one month after the primary vaccine series, one month after the booster dose, and six months after the booster dose (corresponding to 12 months after the primary vaccine series). All serological and virological analyses were centralized at the UVE (Marseille, France), details on the serological testing are provided in supplementary appendix. The first outcome was the percentage of responders, defined as detectable anti-Spike SARS-CoV-2 IgG antibodies. Responders were subcategorized as weak responders (antibodies level < 264 binding antibody units (BAU)/mL), moderate responders ([264–1401] BAU/mL), or strong responders (> 1401 BAU/mL, i.e. the median antibody level at one month after the primary vaccine series of the COV-POPART control group used as reference), as previously described and validated in the initial ANRS0001S COV-POPART study [12]. The second and third outcomes were the geometric mean titers (GMT) of anti-Spike SARS-CoV-2 IgG and anti-Receptor Binding Domain (RBD) antibodies in BAU/mL. The fourth outcome was the percentage of detectable anti-SARS-CoV-2 specific nAbs titers using in vitro neutralization assay for the original SARS-CoV-2 variant, defined as a fold dilution titer ≥20. The fifth outcome was the
<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Flow chart of the participants included in the cancer sub-study of the ANRS0001S COV-POPART cohort study. \*Participants with missing information regarding vaccine doses or a primary vaccine series at 1 or 3 doses.</figcaption></figure>
<table><caption>**Table 1**

Characteristics of participants included in cancer sub-study of the ANRS0001S COV-POPART cohort study.</caption><thead><tr><th>Parameters</th><th>Patients with cancer<br/>N = 183</th><th>Control group<br/>N = 1173</th><th>p</th></tr></thead><tbody><tr><td>Median age at inclusion in years, (IQR)</td><td>59.9<br/>(50.5;68.2)</td><td>46.8<br/>(36.5;56.6)</td><td>&lt;0.0001</td></tr><tr><td>Female, n (%)</td><td>124 (67.8)</td><td>599 (51.1)</td><td>&lt;0.0001</td></tr><tr><td>Median BMI (in kg/m²), (IQR)</td><td>24.7<br/>(21.5;27.5)</td><td>23.5<br/>(21.4;25.9)</td><td>0.0004</td></tr><tr><td>Primary vaccine series, n (%)</td><td></td><td></td><td>0.007</td></tr><tr><td>BNT162b2 + BNT162b2</td><td>148 (80.9)</td><td>984 (83.9)</td><td></td></tr><tr><td>mRNA-1273 + mRNA-1273</td><td>28 (15.3)</td><td>100 (8.5)</td><td></td></tr><tr><td>AstraZeneca + AstraZeneca</td><td>2 (1.1)</td><td>51 (4.4)</td><td></td></tr><tr><td>Others</td><td>5 (2.7)</td><td>38 (3.2)</td><td></td></tr><tr><td>Median time between 2nd dose and booster, in month (IQR)</td><td>6.2 (5.8;6.6)</td><td>6.0 (5.5;6.2)</td><td>0.042</td></tr></tbody></table>

GMT of nAbs titers, expressed in fold dilution (FD), using in vitro neutralization assay for the original SARS-CoV-2 variant for all samples, and compared with Delta and Omicron (B.1.1.529) VOC nAbs titers for a subset of the first 50 participants in the cohort, with positive anti-Spike or RBD antibodies at each timepoint, without reported SARS-CoV-2 infection. For undetectable antibodies, half of the detection cut-off was imputed (i.e. we input the value of 17.6 BAU/mL for anti-Spike SARS-CoV-2 IgG antibodies and a titer of 10 for seroneutralization antibodies). Finally, infections were characterized either by a virologically confirmed SARS-CoV-2 positive test (PCR, antigenic, auto-test) or positive SARS-CoV-2 anti-NCP antibodies. Symptoms were also collected after the test.

## 2.4. Statistical analysis

Categorical variables were expressed as numbers and percentages, and continuous variables were expressed as median (1st quartile–3rd quartile) for non-normally-distributed variables. Baseline characteristics were compared between groups using a Chi-square test (or Fisher’s exact test, as appropriate) for categorical variables and using a Student’s t-test/analysis of variance (ANOVA) (or Mann-Whitney/Kruskal-Wallis test as appropriate) for continuous variables. Humoral responses were compared at one month after the primary vaccine series, at one month and six months after the booster dose between participants with solid cancer and those in the control group. Finally, we used a tobit regression model to adjust for potential confounders (see supplementary methods).

Percentages and GMT were expressed with 95 % confidence interval (95 % CI). Statistical analyses were performed using SAS software (version 9.4).

# 3. Results

## 3.1. General characteristics of the population

Among the 1578 subjects included in the ANRS0001S COV-POPART cancer sub-cohort and assessed for eligibility, 1356 fulfilled the eligibility criteria and were included in this analysis (183 participants with cancer and 1173 controls) (Fig. 1). Among the 183 participants with cancer, 22 belonged to subgroup 1, 70 to subgroup 2, 73 to subgroup 3 and 18 to subgroup 4. Patients with cancer were older than controls (median age: 59.9 years, IQR = [50.5;68.2] vs 46.8, IQR = [36.5;56.6]), with a higher proportion of women (67.8 % vs 51.1 %) (Table 1). Among patients with cancer, the most frequent primary tumor locations were breast (37.2 %, 68/183), and lung (17.5 %, 32/183), the vast majority being carcinomas (95.4 %, 166/174), and nearly half of the participants had metastases at inclusion (46.4 %, 84/181). The median time since cancer diagnosis was 1.2 years (IQR = [0.4,3.9]) (Suppl. Table 1). Regarding vaccine type, mRNA-based vaccines were used for primary vaccination in 86.2 % of patients with cancer and 92.4 % of controls, and for booster vaccination in all participants (Table 1, Supplementary Tables 2 and 3). Among the study population, 54.1 % (733/1356) could be analyzed for the humoral response one month after the booster dose, and 27.1 % (368/1356) for the humoral response six months after the booster dose (Fig. 1).

## 3.2. Humoral response at one month after primary vaccine series

One month after primary vaccine series, anti-Spike antibodies response rate was 93.4 % (95 % CI = [88.8;97.0]) in patients with cancer and 99.9 % (95 % CI = [99.9;100.0]) in the control group (P < 0.0001). GMT of anti-Spike antibodies in the cancer group was significantly lower than in the control group (741.3 BAU/mL, 95 % CI = [596.3;921.6]), vs 1401.3 BAU/mL, 95 % CI = [1335.2;1470.8], P < 0.0001) (Table 2 and Fig. 2). Similar differences in response rate were found with anti-RBD antibodies. The proportion of weak, moderate and strong responders did not differ between patients with cancer and control subjects (Table 2 and Fig. 3). Regarding nAbs titers, we found 87.4 % responders for the cancer group, with lower nAbs titers compared to the control group (GMT = 132.4 FD, 95 % CI = [105.1;166.7] vs 332.7 FD 95 % CI = [312.8;354.0]) (Table 2). We then compared nAbs titers against VOCs of

<caption>**Table 2**</caption>

Humoral response at one month after the second dose, one month after booster dose and six months after booster dose in patients with cancer and healthy adults (control) of the ANRS0001S COV-POPART cohort study.

<table><thead><tr><th rowspan="2"></th><th colspan="2">1 month after 2nd dose</th><th colspan="2">1 month after booster</th><th colspan="2">6 months after booster</th></tr><tr><th>Cancer (n = 183)</th><th>Control (N = 1173)</th><th>Cancer (n = 85)</th><th>Control (N = 648)</th><th>Cancer (N = 51)</th><th>Control (N = 317)</th></tr></thead><tbody><tr><td colspan="7"><strong>Anti-RBD antibodies</strong></td></tr><tr><td>Responders, n (%)</td><td>168 (91.8)</td><td>1163(99.2)</td><td>84 (98.2)</td><td>646 (99.7)</td><td>48 (94.1)</td><td>301 (95.0)</td></tr><tr><td>Titers, geometric mean, in BAU [95 % CI]</td><td>356.0<br/>[277.4;456.9]</td><td>583.7<br/>[554.6;614.4]</td><td>530.8<br/>[426.6;660.3]</td><td>419.5<br/>[397.7;442.4]</td><td>156.9<br/>[111.8-220.1]</td><td>149.4<br/>[133.4-167.3]</td></tr><tr><td colspan="7"><strong>Anti-Spike antibodies</strong></td></tr><tr><td>Responders, n (%)</td><td>171 (93.4)</td><td>1172 (99.9)</td><td>85 (100.0)</td><td>648 (100.0)</td><td>49 (96.1)</td><td>316 (99.7)</td></tr><tr><td>Titers, geometric mean, in BAU [95 % CI]</td><td>741.3<br/>[596.3;921.6]</td><td>1401.3<br/>[1335.2;1470.8]</td><td>2146.1<br/>[1739.1;2648.3]</td><td>1841.3<br/>[1741.9;1946.4]</td><td>602.0<br/>[419.4-863.9]</td><td>574.4<br/>[514.8-640.9]</td></tr><tr><td>No n (%)</td><td>12 (6.5)</td><td>1 (&lt;0.1)</td><td>0 (0.0)</td><td>0 (0.0)</td><td>2 (3.9)</td><td>1 (0.3)</td></tr><tr><td>Low n (%)</td><td>24 (13.1)</td><td>44 (3.8)</td><td>3 (3.5)</td><td>7 (1.1)</td><td>10 (19.6)</td><td>75 (23.7)</td></tr><tr><td>Moderate n (%)</td><td>79 (43.2)</td><td>484 (41.3)</td><td>23 (27.1)</td><td>206 (31.8)</td><td>26 (50.9)</td><td>178 (56.1)</td></tr><tr><td>Strong n (%)</td><td>68 (37.2)</td><td>644 (54.9)</td><td>59 (69.4)</td><td>435 (67.1)</td><td>13 (25.5)</td><td>63 (19.9)</td></tr><tr><td colspan="7"><strong>Neutralizing antibodies</strong></td></tr><tr><td>Responders, n(%)</td><td>160 (87.4)</td><td>1168 (99.6)</td><td>85 (100.0)</td><td>646 (99.7)</td><td>47 (92.2)</td><td>309 (97.5)</td></tr><tr><td>Titers against original SARS-CoV-2 strain, geometric mean, in FD 95 % CI</td><td>132.4<br/>[105.1;166.7]</td><td>332.7<br/>[312.8;354.0]</td><td>1434.8<br/>[1088.0;1892.2]</td><td>1196.6<br/>[1090.5;1313.0]</td><td>275.6<br/>[163.7;463.8]</td><td>255.5<br/>[215.5;302.9]</td></tr></tbody></table>
<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Anti-Spike antibodies response at one month after the second dose, one month after booster dose and six months after booster dose in patients with cancer and healthy adults of the ANRS0001S COV-POPART cohort study. This figure represents the distribution of anti-SARS-CoV-2 IgG antibodies directed against the S1 domain of the virus Spike protein using ELISA, in patients with cancer (in yellow) and healthy adults (in red). Box plots represented the geometric means, IQR, and minimum and maximum values. IQR: interquartile range. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

the subset of 87 participants. We found 100.0 % responders in both groups for the original strain. For the Delta strains, there were 86.7 %, 95 % CI = [73.2;95.0] responders in the cancer group vs 94.6 %, 95 % CI = [81.8;99.3] in the control group. For the Omicron strains, there were 15.9 %, 95 % CI = [6.6;30.1] responders in the cancer group and 40.0 %, 95 % CI = [24.9;56.7] in the control group (Supplementary Fig. S1). No differences were observed when we stratified the results by subgroup or adjusted by potential confounders (Supplementary results and Fig. S2, Fig. S3 and Fig. S4, Table S5).

### 3.3. Humoral response at one month after the booster dose

One month after the booster, the proportion of responders was 100 % in both groups, and the GMT of anti-Spike antibodies in the cancer group was similar to that in the control group (respectively 2146.1 BAU/mL, 95 % CI = [1739.1;2648.3]), vs 1841.3 BAU/mL, 95 % CI = [1741.9;1946.4]) (Table 2 and Fig. 2). The proportions of weak, moderate and strong responders, as well as nAbs titers, were also similar (Table 2 and Fig. 3). We then compared nAbs titers against VOCs of a subset of 22 participants. We found 100.0 % responders in both groups, for the original strains and the Delta strains. For the Omicron strain, there were 86.7 %, 95 % CI = [60.0;98.3] responders in the cancer group and 57.1 %, 95 % CI = [18.4;90.1] in the control group (Supplementary Fig. S1). No differences were observed when we stratified the results by subgroup or adjusted by potential confounders (Supplementary results and Fig. S2, Fig. S3, and Fig. S4, Table S5).

### 3.4. Humoral response six months after the booster dose

At six months after the booster (corresponding to 12 months after the primary vaccine series), anti-Spike antibodies response rate was similar between the participants with cancer and the control group, respectively 96.1 %, 95 % CI = [86.5;99.5] and 99.7 %, 95 % CI = [98.3;99.9], GMT in the cancer group was at 602.0 BAU/mL, 95 % CI = [419.4; 863.9], similar to the control group at 574.4 BAU/mL, 95 % CI = [514.8;640.9]) (Table 2 and Fig. 2). The proportion of weak, moderate and strong responders were also similar between the two groups (Table 2 and Fig. 3). Regarding nAbs titers, we found a rate of 92.2 % responders for the cancer group, with similar nAbs titers compared to the control group. We then compared nAbs titers against VOCs of a subset of 15 participants. We found 100.0 % responders in both groups, for the original and the Delta strains. For the Omicron strain, there were 88.9 %, 95 % CI = [51.8;99.7] responders in the cancer group and 50.0 %, 95 % CI = [11.8;88.2] in the control group (Supplementary Fig. S1). No differences were observed when we stratified the results by subgroup or adjusted by potential confounders (Supplementary results and Fig. S2, Fig. S3, and Fig. S4, Table S5).

### 3.5. Covid-19 infections in the cancer group

Overall, 49 participants in the cancer group had a confirmed SARS-CoV-2 infection and were therefore excluded from the analysis through the different studied timepoints. Among the 49 infections, we
<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Distribution of responders according to the strength of anti-Spike antibodies response at one month after the second dose, one month after booster dose and six months after booster dose in patients with cancer and healthy adults of the ANRS0001S COV-POPART cohort study. Participants were subcategorized as non-responders (anti-Spike SARS-CoV-2 IgG not detected, in yellow), weak responders (anti-Spike SARS-CoV-2 IgG level < 264 BAU/mL, in purple), moderate responders ([264 and 1401] BAU/mL, in blue), or strong responders (>1401 BAU/mL, in green), i.e. the median IgG anti-Spike level of the control group (used as reference), as previously described and validated in the initial ANRS0001S COV-POPART publication [12]. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

recorded 23 documented symptomatic Covid-19 infections, all occurring after December 2021, during Omicron VOC circulation, median time after booster was 3.3 months. Only one participant had only a confirmed positive test without seroconversion to anti-NCP antibodies, and one participant has died following a Covid-19 infection. Characteristics of these infections are detailed in supplementary Table 3.

## 4. Discussion

While VOCs are continuously emerging, well conducted immunogenicity studies, with precise timing for assessment, comprehensive humoral assays including seroneutralization, can help to anticipate and compare vaccine response in patients with cancer and the general population. We found lower humoral responses in participants with a solid cancer at one month after the primary vaccine series compared to controls. Noteworthy, participants with a solid cancer had similar responses compared to controls at one and six months after the first Covid-19 vaccine booster. Our results contrast with the study of La Verde et al., which compared immunogenicity of two doses of mRNA vaccine in 195 solid patients with cancer with healthy volunteers. They found a decreased immunogenicity, assessed by anti-Spike and anti-RBD IgG levels. However, their participants were older, with more advanced cancers compared to our study population and received oncological treatments more recently. Moreover, they did not perform seroneutralization assays nor humoral responses after a booster dose [13]. Looking

at booster induced humoral responses, our results confirm other studies showing that a booster increases humoral immunogenicity [14–18]. We provide additional follow-up data six months after a booster dose, compared with a control group. Few studies exist on real-world effectiveness of boosters, with showed contrasting results [3]. Among them, Choueri et al. demonstrated that a third dose of vaccine was still effective to prevent severe cases of Covid-19 in 2021 and 2022, and Lee et al. large study conducted in the UK showed similar primary vaccine series effectiveness after two doses compared with the general population (65.5 % vs 69.8 %), but a faster waning after three to six months (47.0 % vs 61.4 %) [10,19]. These observations are compatible with immunogenicity studies like ours and support using regular boosters, as also explored by Ehmsen et al., and recommended by public health authorities [7,20–22]. Several points need to be considered when interpreting these observational studies: we observed a high heterogeneity in the vaccine schedule, loss to follow-up and Covid-19 infections. Unfortunately, we were not able to collect information on tobacco consumption, underlying disease other than those classifying for one of the COV-POPART cohorts, and detailed treatment regimen, (e.g. corticosteroids). Our sample was not large enough to be able to further examine the differences of humoral responses among subgroups and to compare neutralizing antibodies results. Finally, it should be acknowledged that other immune compartments including T cells or mucosal immune responses play a pivotal role in protecting against currently circulating variants [23,24]. Nevertheless, our study adds evidence to support the
use for booster doses, especially in patients with cancer, who have good immunogenicity but still at higher risk for complications. Despite public campaign and recommendations, recent data on Covid-19 vaccine coverage can still be improved, vaccine hesitancy remaining high [25,26]. We believe our studies, with the others, will support healthcare provider to support a booster dose among patients with cancer.

### CRediT authorship contribution statement

**Liem Binh Luong Nguyen:** Writing – original draft, Investigation.
**Lyvia Magloire:** Writing – original draft, Visualization, Formal analysis, Data curation.
**Alexis François:** Writing – original draft, Visualization, Formal analysis, Data curation.
**David Billard:** Writing – review & editing, Investigation.
**Frank Priou:** Writing – review & editing, Investigation.
**Jennifer Arrondeau:** Writing – review & editing, Investigation.
**Claude Linassier:** Writing – review & editing, Investigation.
**Ines Ben Ghezala:** Writing – review & editing, Investigation.
**Marine Gross-Goupil:** Writing – review & editing, Investigation.
**Julie Charles:** Writing – review & editing, Investigation.
**Nadine Dohollou:** Writing – review & editing, Investigation.
**Philippe Vanhems:** Writing – review & editing, Investigation.
**Claire Cracowski:** Writing – review & editing, Investigation.
**Anne Marie Leroi:** Writing – review & editing, Investigation.
**Fabrice Lainé:** Writing – review & editing, Investigation.
**Florian Galtier:** Writing – review & editing, Investigation.
**Karine Barthelemy:** Writing – review & editing, Data curation.
**Stéphane Priet:** Writing – review & editing, Data curation.
**Marian Gharib:** Writing – review & editing, Project administration, Funding acquisition.
**Mathieu Chalouni:** Writing – original draft, Visualization, Formal analysis, Data curation.
**Aude Barquin:** Writing – review & editing, Resources, Project administration, Data curation.
**Paul Loubet:** Writing – review & editing, Writing – original draft, Validation, Supervision, Investigation, Funding acquisition, Conceptualization.
**Xavier de Lam-ballerie:** Writing – review & editing, Writing – original draft, Validation, Supervision, Funding acquisition, Conceptualization.
**Odile Launay:** Writing – review & editing, Writing – original draft, Supervision, Investigation, Funding acquisition, Conceptualization.
**Linda Wittkop:** Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Conceptualization.
**Jean-Yves Blay:** Writing – review & editing, Validation, Supervision, Investigation, Conceptualization.
**Jean-Philippe Spano:** Writing – review & editing, Validation, Supervision, Investigation, Conceptualization.

### Funding

The funding of this study is provided by ANRS-MIE.

### Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Paul Loubet has received payment or honoraria for lectures, presentations, speakers bureau, manuscript writing or educational events from AstraZeneca, GlaxoSmithKline, Janssen, Moderna, Merck Sharp & Dohme, Pfizer, Sanofi Pasteur, Seqirus.

**Jean-Philippe Spano:**

- Advisory board: Merck MSD, Pfizer, Lilly, Incyte, Novartis, Exact Science, Gilead, AZ

- Consultant: MSD, Incyte

Grant: MSD Avenir.

All remaining authors have declared no conflicts of interest.

### Acknowledgement

The authors are grateful to Beckman Coulter for supplying the automated system and tests required for the quantitative assay of anti-RBD IgG antibodies.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.vaccine.2025.127633.

### Data availability

The data that has been used is confidential.

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