Clinical efficacy of different monoclonal antibody regimens among non-hospitalised patients with mild to moderate COVID-19 at high risk for disease progression: a prospective cohort study.

This study aimed to compare the clinical progression of COVID-19 in high-risk outpatients treated with the monoclonal antibodies (mAb) bamlanivimab, bamlanivimab-etesevimab and casirivimab-imdevimab. This is an observational, multi-centre, prospective study conducted from 18 March to 15 July 2021 in eight Italian tertiary-care hospitals including mild-to-moderate COVID-19 outpatients receiving bamlanivimab (700 mg), bamlanivimab-etesevimab (700-1400 mg) or casirivimab-imdevimab (1200-1200 mg). All patients were at high risk of COVID-19 progression according to Italian Medicines Agency definitions. In a patient subgroup, SARS-CoV-2 variant and anti-SARS-CoV-2 serology were analysed at baseline. Factors associated with 28-day all-cause hospitalisation were identified using multivariable multilevel logistic regression (MMLR) and summarised with adjusted odds ratio (aOR) and 95% confidence interval (CI). A total of 635 outpatients received mAb: 161 (25.4%) bamlanivimab, 396 (62.4%) bamlanivimab-etesevimab and 78 (12.2%) casirivimab-imdevimab. Ninety-five (15%) patients received full or partial SARS-CoV-2 vaccination. The B.1.1.7 (Alpha) variant was detected in 99% of patients. Baseline serology showed no significant differences among the three mAb regimen groups. Twenty-eight-day all-cause hospitalisation was 11.3%, with a significantly higher proportion (p 0.001) in the bamlanivimab group (18.6%), compared to the bamlanivimab-etesevimab (10.1%) and casirivimab-imdevimab (2.6%) groups. On MMLR, aORs for 28-day all-cause hospitalisation were significantly lower in patients receiving bamlanivimab-etesevimab (aOR 0.51, 95% CI 0.30-0.88 p 0.015) and casirivimab-imdevimab (aOR 0.14, 95% CI 0.03-0.61, p 0.009) compared to those receiving bamlanivimab. No patients with a history of vaccination were hospitalised. The study suggests differences in clinical outcomes among the first available mAb regimens for treating high-risk COVID-19 outpatients. Randomised trials are needed to compare efficacy of mAb combination regimens in high-risk populations and according to circulating variants.

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

BackgroundThe role of host immunity in emergence of evasive SARS-CoV-2 Spike mutations under therapeutic monoclonal antibody (mAb) pressure remains to be explored.MethodsIn 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.ResultsPatients 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.ConclusionsOur 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.FundingThe ORCHESTRA project/European Union's Horizon 2020 research and innovation program.

Using machine learning to predict antibody response to SARS-CoV-2 vaccination in solid organ transplant recipients: the multicentre ORCHESTRA cohort.

OBJECTIVES: The study aim was to assess predictors of negative antibody response (AbR) in solid organ transplant (SOT) recipients after the first booster of SARS-CoV-2 vaccination. METHODS: Solid organ transplant recipients receiving SARS-CoV-2 vaccination were prospectively enrolled (March 2021-January 2022) at six hospitals in Italy and Spain. AbR was assessed at first dose (t0), second dose (t1), 3 ± 1 month (t2), and 1 month after third dose (t3). Negative AbR at t3 was defined as an anti-receptor binding domain titre <45 BAU/mL. Machine learning models were developed to predict the individual risk of negative (vs. positive) AbR using age, type of transplant, time between transplant and vaccination, immunosuppressive drugs, type of vaccine, and graft function as covariates, subsequently assessed using a validation cohort. RESULTS: Overall, 1615 SOT recipients (1072 [66.3%] males; mean age±standard deviation [SD], 57.85 ± 13.77) were enrolled, and 1211 received three vaccination doses. Negative AbR rate decreased from 93.66% (886/946) to 21.90% (202/923) from t0 to t3. Univariate analysis showed that older patients (mean age, 60.21 ± 11.51 vs. 58.11 ± 13.08), anti-metabolites (57.9% vs. 35.1%), steroids (52.9% vs. 38.5%), recent transplantation (<3 years) (17.8% vs. 2.3%), and kidney, heart, or lung compared with liver transplantation (25%, 31.8%, 30.4% vs. 5.5%) had a higher likelihood of negative AbR. Machine learning (ML) algorithms showing best prediction performance were logistic regression (precision-recall curve-PRAUC mean 0.37 [95%CI 0.36-0.39]) and k-Nearest Neighbours (PRAUC 0.36 [0.35-0.37]). DISCUSSION: Almost a quarter of SOT recipients showed negative AbR after first booster dosage. Unfortunately, clinical information cannot efficiently predict negative AbR even with ML algorithms.

Clinical Impact of Monoclonal Antibodies in the Treatment of High-Risk Patients with SARS-CoV-2 Breakthrough Infections: The ORCHESTRA Prospective Cohort Study.

The clinical impact of anti-spike monoclonal antibodies (mAb) in Coronavirus Disease 2019 (COVID-19) breakthrough infections is unclear. We present the results of an observational prospective cohort study assessing and comparing COVID-19 progression in high-risk outpatients receiving mAb according to primary or breakthrough infection. Clinical, serological and virological predictors associated with 28-day COVID-19-related hospitalization were identified using multivariate logistic regression and summarized with odds ratio (aOR) and 95% confidence interval (CI). A total of 847 COVID-19 outpatients were included: 414 with primary and 433 with breakthrough infection. Hospitalization was observed in 42/414 (10.1%) patients with primary and 8/433 (1.8%) patients with breakthrough infection (p < 0.001). aOR for hospitalization was significantly lower for breakthrough infection (aOR 0.12, 95%CI: 0.05-0.27, p < 0.001) and higher for immunocompromised status (aOR:2.35, 95%CI:1.08-5.08, p = 0.003), advanced age (aOR:1.06, 95%CI: 1.03-1.08, p < 0.001), and male gender (aOR:1.97, 95%CI: 1.04-3.73, p = 0.037). Among the breakthrough infection group, the median SARS-CoV-2 anti-spike IgGs was lower (p < 0.001) in immunocompromised and elderly patients >75 years compared with that in the immunocompetent patients. Our findings suggest that, among mAb patients, those with breakthrough infection have significantly lower hospitalization risk compared with patients with primary infection. Prognostic algorithms combining clinical and immune-virological characteristics are needed to ensure appropriate and up-to-date clinical protocols targeting high-risk categories.

Predictive model for BNT162b2 vaccine response in cancer patients based on blood cytokines and growth factors.

Background: Patients with cancer, especially hematological cancer, are at increased risk for breakthrough COVID-19 infection. So far, a predictive biomarker that can assess compromised vaccine-induced anti-SARS-CoV-2 immunity in cancer patients has not been proposed. Methods: We employed machine learning approaches to identify a biomarker signature based on blood cytokines, chemokines, and immune- and non-immune-related growth factors linked to vaccine immunogenicity in 199 cancer patients receiving the BNT162b2 vaccine. Results: C-reactive protein (general marker of inflammation), interleukin (IL)-15 (a pro-inflammatory cytokine), IL-18 (interferon-gamma inducing factor), and placental growth factor (an angiogenic cytokine) correctly classified patients with a diminished vaccine response assessed at day 49 with >80% accuracy. Amongst these, CRP showed the highest predictive value for poor response to vaccine administration. Importantly, this unique signature of vaccine response was present at different studied timepoints both before and after vaccination and was not majorly affected by different anti-cancer treatments. Conclusion: We propose a blood-based signature of cytokines and growth factors that can be employed in identifying cancer patients at persistent high risk of COVID-19 despite vaccination with BNT162b2. Our data also suggest that such a signature may reflect the inherent immunological constitution of some cancer patients who are refractive to immunotherapy.

Activation of the integrated stress response confers vulnerability to mitoribosome-targeting antibiotics in melanoma.

The ability to adapt to environmental stress, including therapeutic insult, contributes to tumor evolution and drug resistance. In suboptimal conditions, the integrated stress response (ISR) promotes survival by dampening cytosolic translation. We show that ISR-dependent survival also relies on a concomitant up-regulation of mitochondrial protein synthesis, a vulnerability that can be exploited using mitoribosome-targeting antibiotics. Accordingly, such agents sensitized to MAPK inhibition, thus preventing the development of resistance in BRAFV600E melanoma models. Additionally, this treatment compromised the growth of melanomas that exhibited elevated ISR activity and resistance to both immunotherapy and targeted therapy. In keeping with this, pharmacological inactivation of ISR, or silencing of ATF4, rescued the antitumoral response to the tetracyclines. Moreover, a melanoma patient exposed to doxycycline experienced complete and long-lasting response of a treatment-resistant lesion. Our study indicates that the repurposing of mitoribosome-targeting antibiotics offers a rational salvage strategy for targeted therapy in BRAF mutant melanoma and a therapeutic option for NRAS-driven and immunotherapy-resistant tumors.

Blood Cytokine Analysis Suggests That SARS-CoV-2 Infection Results in a Sustained Tumour Promoting Environment in Cancer Patients.

Cytokines, chemokines, and (angiogenic) growth factors (CCGs) have been shown to play an intricate role in the progression of both solid and haematological malignancies. Recent studies have shown that SARS-CoV-2 infection leads to a worse outcome in cancer patients, especially in haematological malignancy patients. Here, we investigated how SARS-CoV-2 infection impacts the already altered CCG levels in solid or haematological malignancies, specifically, whether there is a protective effect or rather a potentially higher risk for major COVID-19 complications in cancer patients due to elevated CCGs linked to cancer progression. Serially analysing immune responses with 55 CCGs in cancer patients under active treatment with or without SARS-CoV-2 infection, we first showed that cancer patients without SARS-CoV-2 infection (n = 54) demonstrate elevated levels of 35 CCGs compared to the non-cancer, non-infected control group of health care workers (n = 42). Of the 35 CCGs, 19 were common to both the solid and haematological malignancy groups and comprised previously described cytokines such as IL-6, TNF-α, IL-1Ra, IL-17A, and VEGF, but also several less well described cytokines/chemokines such as Fractalkine, Tie-2, and T cell chemokine CTACK. Importantly, we show here that 7 CCGs are significantly altered in SARS-CoV-2 exposed cancer patients (n = 52). Of these, TNF-α, IFN-ß, TSLP, and sVCAM-1, identified to be elevated in haematological cancers, are also known tumour-promoting factors. Longitudinal analysis conducted over 3 months showed persistence of several tumour-promoting CCGs in SARS-CoV-2 exposed cancer patients. These data demonstrate a need for increased vigilance for haematological malignancy patients as a part of long COVID follow-up.