COVID-19 is associated with a wide range of clinical manifestations, including autoimmune features and autoantibody production. Here we develop three protein arrays to measure IgG autoantibodies associated with connective tissue diseases, anti-cytokine antibodies, and anti-viral antibody responses in serum from 147 hospitalized COVID-19 patients. Autoantibodies are identified in approximately 50% of patients but in less than 15% of healthy controls. When present, autoantibodies largely target autoantigens associated with rare disorders such as myositis, systemic sclerosis and overlap syndromes. A subset of autoantibodies targeting traditional autoantigens or cytokines develop de novo following SARS-CoV-2 infection. Autoantibodies track with longitudinal development of IgG antibodies recognizing SARS-CoV-2 structural proteins and a subset of non-structural proteins, but not proteins from influenza, seasonal coronaviruses or other pathogenic viruses. We conclude that SARS-CoV-2 causes development of new-onset IgG autoantibodies in a significant proportion of hospitalized COVID-19 patients and are positively correlated with immune responses to SARS-CoV-2 proteins.

Six p53 wild-type cancer cell lines from infrequently p53-mutated entities (neuroblastoma, rhabdomyosarcoma, and melanoma) were continuously exposed to increasing concentrations of the murine double minute 2 inhibitor nutlin-3, resulting in the emergence of nutlin-3-resistant, p53-mutated sublines displaying a multi-drug resistance phenotype. Only 2 out of 28 sublines adapted to various cytotoxic drugs harboured p53 mutations. Nutlin-3-adapted UKF-NB-3 cells (UKF-NB-3rNutlin10 μM, harbouring a G245C mutation) were also radiation resistant. Analysis of UKF-NB-3 and UKF-NB-3rNutlin10 μM cells by RNA interference experiments and lentiviral transduction of wild-type p53 into p53-mutated UKF-NB-3rNutlin10 μM cells revealed that the loss of p53 function contributes to the multi-drug resistance of UKF-NB-3rNutlin10 μM cells. Bioinformatics PANTHER pathway analysis based on microarray measurements of mRNA abundance indicated a substantial overlap in the signalling pathways differentially regulated between UKF-NB-3rNutlin10 μM and UKF-NB-3 and between UKF-NB-3 and its cisplatin-, doxorubicin-, or vincristine-resistant sublines. Repeated nutlin-3 adaptation of neuroblastoma cells resulted in sublines harbouring various p53 mutations with high frequency. A p53 wild-type single cell-derived UKF-NB-3 clone was adapted to nutlin-3 in independent experiments. Eight out of ten resulting sublines were p53-mutated harbouring six different p53 mutations. This indicates that nutlin-3 induces de novo p53 mutations not initially present in the original cell population. Therefore, nutlin-3-treated cancer patients should be carefully monitored for the emergence of p53-mutated, multi-drug-resistant cells.

A prospective study was performed to assess the potential value of interleukin (IL)-8, IL-6, and C-reactive protein (CRP) serum levels to predict fever, gram-negative bacteremia and complicated infection in neutropenic patients with cancer. Serum samples were obtained three times a week during 208 neutropenic episodes following cytotoxic chemotherapy. Fever of any cause developed during 104 out of 191 evaluable episodes. Serum levels of neither cytokine nor CRP were predictive of fever within more than 24 h before its onset. Unlike CRP, both IL-6 and IL-8 serum levels were significantly different between microbiologically documented infections and unexplained fevers. The highest values of IL-6 and IL-8 were observed in episodes of gram-negative bacteremia. Using receiver-operating-characteristic curves, the analysis of cytokine levels measured around the onset of fever indicated that IL-8 is potentially useful for predicting gram-negative bacteremia, with a high negative predictive value of > 90% and a moderate positive predictive value of 50% (sensitivity, 70%; specificity, 91%). In patients with persistent fever, predictions of further clinical complications, defined as prolonged fever of more than 7 days' duration, pneumonia, shock and/or death due to infection, were best predicted by IL-6. With an IL-6 cutoff value of 250 pg/ml in samples obtained 8 to 32 h after onset of fever, the positive predictive value was 92%, the negative predictive value 91% (sensitivity, 85%; specificity, 95%). The positive predictive value of IL-6 in samples obtained another 24 h later from patients still febrile remained > 90%, but the negative predictive value dropped to 47%. In any of the analyses, the predictive values of CRP levels were poor and inferior to either cytokine. These findings may have clinical value in identifying subgroups of patients requiring different therapeutic approaches.

Coronavirus Disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), is associated with a wide range of clinical manifestations, including autoimmune features and autoantibody production. We developed three different protein arrays to measure hallmark IgG autoantibodies associated with Connective Tissue Diseases (CTDs), Anti-Cytokine Antibodies (ACA), and anti-viral antibody responses in 147 hospitalized COVID-19 patients in three different centers. Autoantibodies were identified in approximately 50% of patients, but in <15% of healthy controls. When present, autoantibodies largely targeted autoantigens associated with rare disorders such as myositis, systemic sclerosis and CTD overlap syndromes. Anti-nuclear antibodies (ANA) were observed in ∼25% of patients. Patients with autoantibodies tended to demonstrate one or a few specificities whereas ACA were even more prevalent, and patients often had antibodies to multiple cytokines. Rare patients were identified with IgG antibodies against angiotensin converting enzyme-2 (ACE-2). A subset of autoantibodies and ACA developed de novo following SARS-CoV-2 infection while others were transient. Autoantibodies tracked with longitudinal development of IgG antibodies that recognized SARS-CoV-2 structural proteins such as S1, S2, M, N and a subset of non-structural proteins, but not proteins from influenza, seasonal coronaviruses or other pathogenic viruses. COVID-19 patients with one or more autoantibodies tended to have higher levels of antibodies against SARS-CoV-2 Nonstructural Protein 1 (NSP1) and Methyltransferase (ME). We conclude that SARS-CoV-2 causes development of new-onset IgG autoantibodies in a significant proportion of hospitalized COVID-19 patients and are positively correlated with immune responses to SARS-CoV-2 proteins.

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