Host immunological responses facilitate development of SARS-CoV-2 mutations in patients receiving monoclonal antibody treatments
Akshita Gupta, Angelina Konnova, Mathias Smet, Matilda Berkell, Alessia Savoldi, Matteo Morra, Vincent Van averbeke, Fien H.R. De Winter, Denise Peserico, Elisa Danese, An Hotterbeekx, Elda Righi, mAb ORCHESTRA working group, Pasquale De Nardo, Evelina Tacconelli, Surbhi Malhotra-Kumar, Samir Kumar-Singh
Akshita Gupta, Angelina Konnova, Mathias Smet, Matilda Berkell, Alessia Savoldi, Matteo Morra, Vincent Van averbeke, Fien H.R. De Winter, Denise Peserico, Elisa Danese, An Hotterbeekx, Elda Righi, mAb ORCHESTRA working group, Pasquale De Nardo, Evelina Tacconelli, Surbhi Malhotra-Kumar, Samir Kumar-Singh
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Clinical Research and Public Health

Host immunological responses facilitate development of SARS-CoV-2 mutations in patients receiving monoclonal antibody treatments

Abstract

Background The role of host immunity in emergence of evasive SARS-CoV-2 Spike mutations under therapeutic monoclonal antibody (mAb) pressure remains to be explored.Methods In a prospective, observational, monocentric ORCHESTRA cohort study, conducted between March 2021 and November 2022, mild-to-moderately ill COVID-19 patients (n = 204) receiving bamlanivimab, bamlanivimab/etesevimab, casirivimab/imdevimab, or sotrovimab were longitudinally studied over 28 days for viral loads, de novo Spike mutations, mAb kinetics, seroneutralization against infecting variants of concern, and T cell immunity. Additionally, a machine learning–based circulating immune-related biomarker (CIB) profile predictive of evasive Spike mutations was constructed and confirmed in an independent data set (n = 19) that included patients receiving sotrovimab or tixagevimab/cilgavimab.Results Patients treated with various mAbs developed evasive Spike mutations with remarkable speed and high specificity to the targeted mAb-binding sites. Immunocompromised patients receiving mAb therapy not only continued to display significantly higher viral loads, but also showed higher likelihood of developing de novo Spike mutations. Development of escape mutants also strongly correlated with neutralizing capacity of the therapeutic mAbs and T cell immunity, suggesting immune pressure as an important driver of escape mutations. Lastly, we showed that an antiinflammatory and healing-promoting host milieu facilitates Spike mutations, where 4 CIBs identified patients at high risk of developing escape mutations against therapeutic mAbs with high accuracy.Conclusions Our data demonstrate that host-driven immune and nonimmune responses are essential for development of mutant SARS-CoV-2. These data also support point-of-care decision making in reducing the risk of mAb treatment failure and improving mitigation strategies for possible dissemination of escape SARS-CoV-2 mutants.Funding The ORCHESTRA project/European Union’s Horizon 2020 research and innovation program.

Authors

Akshita Gupta, Angelina Konnova, Mathias Smet, Matilda Berkell, Alessia Savoldi, Matteo Morra, Vincent Van averbeke, Fien H.R. De Winter, Denise Peserico, Elisa Danese, An Hotterbeekx, Elda Righi, mAb ORCHESTRA working group, Pasquale De Nardo, Evelina Tacconelli, Surbhi Malhotra-Kumar, Samir Kumar-Singh

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Figure 6

Circulating immune-related biomarkers (CIBs) in COVID-19 patients receiving mAb therapy.

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Circulating immune-related biomarkers (CIBs) in COVID-19 patients receiv...
(A) Several CIBs were significantly up- or downregulated on D0 in COVID-19 patients who developed SARS-CoV-2 S RBD mutations after administration of mAb treatments, compared with those who did not. (B) Eleven CIBs were significantly altered on D0 in patients with de novo S RBD mutations, for which the majority (n = 8) were also altered on D2. (C) Temporal evolution of CIBs altered in patients, with or without de novo mutations, receiving mAb therapy through day 7 after treatment. Lines represent smoothed conditional means and shaded areas display 95% CIs for all measured time points. P values refer to significance of the slope of the regression lines. Vertical lines with asterisks represent the significant difference between CIB levels at the specified time points. (D) Receiving operator characteristic (ROC) curve in a random forest classifier model with synthetic minority oversampling technique (SMOTE) for the prediction of mutation versus no-mutation are depicted for D0. *P < 0.05, **P < 0.01, ***P < 0.001. †Not significant. For details on the progression of CIBs from D0 to D7 and sample numbers, see Supplemental Figures 5 and 7.