Impact of SARS-CoV-2 Infection on Patients with Cancer: Retrospective and Transversal Studies in Spanish Population

[EN] Background: Studies of patients with cancer affected by coronavirus disease 2019 (COVID-19) are needed to assess the impact of the disease in this sensitive population, and the influence of different cancer treatments on the COVID-19 infection and seroconversion. Material and Methods: We performed a retrospective analysis of all patients hospitalized with RT-PCR positive for COVID-19 in our region to assess the prevalence of cancer patients and describe their characteristics and evolution (Cohort 1). Concurrently, a transversal study was carried out in patients on active systemic cancer treatment for symptomatology and seroprevalence (IgG/IgM by ELISA-method) against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) (Cohort 2). Results: A total of 215 patients (Cohort 1) were admitted to hospital with a confirmed COVID-19 infection between February 28 and April 30, 2020, and 17 died (7.9%). A medical record of cancer was noted in 43 cases (20%), 6 of them required Intensive care unit ICU attention (14%), and 7 died (16%). There were thirty-six patients (83%) who tested IgG/IgM positive for SARS-CoV-2. Patients on immunosuppressive therapies presented a lower ratio of seroconversion (40% vs. 8%; p = 0.02). In Cohort 2, 166 patients were included in a symptoms-survey and tested for SARS-CoV-2. Any type of potential COVID-19-related symptom was referred up to 67.4% of patients (85.9% vs. 48.2% vs. 73.9%, for patients on chemotherapy, immunotherapy and targeted therapies respectively, p < 0.05). The seroprevalence ratio was 1.8% for the whole cohort with no significant differences by patient or treatment characteristics. Conclusion: Patients with cancer present higher risks for hospital needs for COVID-19 infection. The lack of SARS-CoV-2 seroconversion may be a concern for patients on immunosuppressive therapies. Patients receiving systematic therapies relayed a high rate of potentially COVID-19-related symptoms, particularly those receiving chemotherapy. However, the seroconversion rate remains low and in the range of general population.We thank all the patients who consented to this study, and the frontline healthcare professionals who are involved in patients' care during this pandemic. We also thank the technical assistants: M. Portero Hernandez, A. Real Perez, and M. Ocasar Garcia. VGB's research work is partially supported by the Ministerio de Ciencia e Innovacion of Spain under grant No. PID2019-110442GB-I00.Garde-Noguera, J.; Fernández-Murga, ML.; Giner-Bosch, V.; Domínguez-Márquez, V.; García Sánchez, J.; Soler-Cataluña, JJ.; López Chuliá, F.... (2020). Impact of SARS-CoV-2 Infection on Patients with Cancer: Retrospective and Transversal Studies in Spanish Population. Cancers. 12(12):1-11. https://doi.org/10.3390/cancers12123513S1111212Munster, V. J., Koopmans, M., van Doremalen, N., van Riel, D., & de Wit, E. (2020). A Novel Coronavirus Emerging in China — Key Questions for Impact Assessment. New England Journal of Medicine, 382(8), 692-694. doi:10.1056/nejmp2000929Coronavirus COVID-19 Global Cases by the Center for Systems Science and Engineeringhttps://coronavirus.jhu.edu/map.htmlInforme Sobre la Situación COVID-19 en España a 6 April 2020. Equipo COVID-19. RENAVE. CNE. CNM (ISCIII). Informe COVID-19 nº21https://covid19.isciii.es/Report 13: Estimating the Number of Infections and the Impact of Non-Pharmaceutical Interventions on COVID-19 in 11 European Countrieshttps://spiral.imperial.ac.uk:8443/handle/10044/1/77731Rothan, H. A., & Byrareddy, S. N. (2020). The epidemiology and pathogenesis of coronavirus disease (COVID-19) outbreak. Journal of Autoimmunity, 109, 102433. doi:10.1016/j.jaut.2020.102433Liang, W., Guan, W., Chen, R., Wang, W., Li, J., Xu, K., … He, J. (2020). Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China. The Lancet Oncology, 21(3), 335-337. doi:10.1016/s1470-2045(20)30096-6Sharpe, A. H., & Pauken, K. E. (2017). The diverse functions of the PD1 inhibitory pathway. Nature Reviews Immunology, 18(3), 153-167. doi:10.1038/nri.2017.108Fisher, R. A. (1922). On the Interpretation of χ 2 from Contingency Tables, and the Calculation of P. Journal of the Royal Statistical Society, 85(1), 87. doi:10.2307/2340521Mehta, C. R., & Patel, N. R. (1983). A Network Algorithm for Performing Fisher’s Exact Test in r × c Contingency Tables. Journal of the American Statistical Association, 78(382), 427. doi:10.2307/2288652Wilcoxon, F. (1945). Individual Comparisons by Ranking Methods. Biometrics Bulletin, 1(6), 80. doi:10.2307/3001968Kuderer, N. M., Choueiri, T. K., Shah, D. P., Shyr, Y., Rubinstein, S. M., Rivera, D. R., … de Lima Lopes, G. (2020). Clinical impact of COVID-19 on patients with cancer (CCC19): a cohort study. The Lancet, 395(10241), 1907-1918. doi:10.1016/s0140-6736(20)31187-9Zhang, L., Zhu, F., Xie, L., Wang, C., Wang, J., Chen, R., … Zhou, M. (2020). Clinical characteristics of COVID-19-infected cancer patients: a retrospective case study in three hospitals within Wuhan, China. Annals of Oncology, 31(7), 894-901. doi:10.1016/j.annonc.2020.03.296Winter, A. K., & Hegde, S. T. (2020). The important role of serology for COVID-19 control. The Lancet Infectious Diseases, 20(7), 758-759. doi:10.1016/s1473-3099(20)30322-4Venkatesulu, B. P., Thoguluva Chandrasekar, V., Giridhar, P., Advani, P., Sharma, A., Hsieh, C. E., … Krishnan, S. (2020). A systematic review and meta-analysis of cancer patients affected by a novel coronavirus. doi:10.1101/2020.05.27.20115303Van Assen, S., Holvast, A., Benne, C. A., Posthumus, M. D., van Leeuwen, M. A., Voskuyl, A. E., … Bijl, M. (2010). Humoral responses after influenza vaccination are severely reduced in patients with rheumatoid arthritis treated with rituximab. Arthritis & Rheumatism, 62(1), 75-81. doi:10.1002/art.25033Rousseau, B., Loulergue, P., Mir, O., Krivine, A., Kotti, S., Viel, E., … Tournigand, C. (2012). Immunogenicity and safety of the influenza A H1N1v 2009 vaccine in cancer patients treated with cytotoxic chemotherapy and/or targeted therapy: the VACANCE study. Annals of Oncology, 23(2), 450-457. doi:10.1093/annonc/mdr141Di Cosimo, S., Malfettone, A., Pérez-García, J. M., Llombart-Cussac, A., Miceli, R., Curigliano, G., & Cortés, J. (2020). Immune checkpoint inhibitors: a physiology-driven approach to the treatment of coronavirus disease 2019. European Journal of Cancer, 135, 62-65. doi:10.1016/j.ejca.2020.05.026Bersanelli, M., Scala, S., Affanni, P., Veronesi, L., Colucci, M. E., Banna, G. L., … Liotta, F. (2020). Immunological insights on influenza infection and vaccination during immune checkpoint blockade in cancer patients. Immunotherapy, 12(2), 105-110. doi:10.2217/imt-2019-0200Pollán, M., Pérez-Gómez, B., Pastor-Barriuso, R., Oteo, J., Hernán, M. A., Pérez-Olmeda, M., … Fernández de Larrea, N. (2020). Prevalence of SARS-CoV-2 in Spain (ENE-COVID): a nationwide, population-based seroepidemiological study. The Lancet, 396(10250), 535-544. doi:10.1016/s0140-6736(20)31483-5Choe, P. G., Perera, R. A. P. M., Park, W. B., Song, K.-H., Bang, J. H., Kim, E. S., … Oh, M. (2017). MERS-CoV Antibody Responses 1 Year after Symptom Onset, South Korea, 2015. Emerging Infectious Diseases, 23(7), 1079-1084. doi:10.3201/eid2307.170310Cao, W.-C., Liu, W., Zhang, P.-H., Zhang, F., & Richardus, J. H. (2007). Disappearance of Antibodies to SARS-Associated Coronavirus after Recovery. New England Journal of Medicine, 357(11), 1162-1163. doi:10.1056/nejmc070348Wu, L.-P., Wang, N.-C., Chang, Y.-H., Tian, X.-Y., Na, D.-Y., Zhang, L.-Y., … Liang, G.-D. (2007). Duration of Antibody Responses after Severe Acute Respiratory Syndrome. Emerging Infectious Diseases, 13(10), 1562-1564. doi:10.3201/eid1310.070576Kissler, S. M., Tedijanto, C., Goldstein, E., Grad, Y. H., & Lipsitch, M. (2020). Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period. Science, 368(6493), 860-868. doi:10.1126/science.abb579

Basis of Arginine Sensitivity of Microbial N-Acetyl-l-Glutamate Kinases: Mutagenesis and Protein Engineering Study with the Pseudomonas aeruginosa and Escherichia coli Enzymes▿

N-Acetylglutamate kinase (NAGK) catalyzes the second step of arginine biosynthesis. In Pseudomonas aeruginosa, but not in Escherichia coli, this step is rate limiting and feedback and sigmoidally inhibited by arginine. Crystal structures revealed that arginine-insensitive E. coli NAGK (EcNAGK) is homodimeric, whereas arginine-inhibitable NAGKs, including P. aeruginosa NAGK (PaNAGK), are hexamers in which an extra N-terminal kinked helix (N-helix) interlinks three dimers. By introducing single amino acid replacements in PaNAGK, we prove the functionality of the structurally identified arginine site, as arginine site mutations selectively decreased the apparent affinity for arginine. N-helix mutations affecting R24 and E17 increased and decreased, respectively, the apparent affinity of PaNAGK for arginine, as predicted from enzyme structures that revealed the respective formation by these residues of bonds favoring inaccessible and accessible arginine site conformations. N-helix N-terminal deletions spanning ≥16 residues dissociated PaNAGK to active dimers, those of ≤20 residues decreased the apparent affinity for arginine, and complete N-helix deletion (26 residues) abolished arginine inhibition. Upon attachment of the PaNAGK N-terminal extension to the EcNAGK N terminus, EcNAGK remained dimeric and arginine insensitive. We concluded that the N-helix and its C-terminal portion after the kink are essential but not sufficient for hexamer formation and arginine inhibition, respectively; that the N-helix modulates NAGK affinity for arginine and mediates signal transmission between arginine sites, thus establishing sigmoidal arginine inhibition kinetics; that the mobile αH-β16 loop of the arginine site is the modulatory signal receiver; and that the hexameric architecture is not essential for arginine inhibition but is functionally essential for physiologically relevant arginine control of NAGK

Liver gene expression assays in immunocompetent and immunosuppressed mice, fed either <i>B</i>.<i>uniformis</i> CECT 7771 or placebo.

<p>Control, mouse group fed placebo daily by gavage for 6 days (n = 5); Control + B, mouse group that received a daily dose of 2 x 10⁹ CFU <i>B</i>. <i>uniformis</i> CECT 7771 by gavage for 6 days (n = 5); IMM, immunosuppressed mouse group fed placebo daily by gavage for 6 days (n = 5); and IMM+B, immunosuppressed mouse group receiving a daily dose of 2 x10⁹CFU <i>B</i>. <i>uniformis</i> CECT 7771 by gavage for 6 days (n = 5). Data are expressed as the mean value ± SEM. Differences between groups were established using an unpaired Student's <i>t</i>-test. Results with a two-sided <i>p</i>-value <0.05 were considered statistically significant. These measurements were taken in triplicate for each sample.</p

Histology of colon section from immunocompetent and immunosuppressed mice, fed either <i>B</i>. <i>uniformis</i> CECT 7771 or placebo.

<p>Control, mouse group fed placebo daily by gavage for 6 days (n = 5); Control + B, mouse group that received a daily dose of 2 x10⁹ CFU <i>B</i>. <i>uniformis</i> CECT 7771 by gavage for 6 days (n = 5); IMM, immunosuppressed mouse group fed placebo daily by gavage for 6 days (n = 5); and IMM+B, immunosuppressed mouse group receiving a daily dose of 2 x10⁹CFU <i>B</i>. <i>uniformis</i> CECT 7771 by gavage for 6 days (n = 5). Data are expressed as means and SEM. The differences were determined by applying the Mann-Whitney <i>U</i> test. In every case, p-values <0.05 were considered statistically significant. These measurements were taken in 10 fields for each sample. Photomicrographs 20 x of representative HE-stained slides are shown. G, goblet cells; C, crypts.</p

Gene expression assays in colon from immunocompetent and immunosuppressed mice, fed either <i>B</i>.<i>uniformis</i> CECT 7771 or placebo.

<p>Control, mouse group fed placebo daily by gavage for 6 days (n = 5); Control + B, mouse group that received a daily dose of 2 x10⁹ CFU <i>B</i>. <i>uniformis</i> CECT 7771 by gavage for 6 days (n = 5); IMM, immunosuppressed mouse group fed placebo daily by gavage for 6 days (n = 5); and IMM+B, immunosuppressed mouse group receiving a daily dose of 2 x 10⁹CFU <i>B</i>. <i>uniformis</i> CECT 7771 by gavage for 6 days (n = 5). Data are expressed as the mean value ± SEM. Differences between groups were established using an unpaired Student's <i>t</i>-test. Results with a two-sided <i>p</i>-value <0.05 were considered statistically significant. These measurements were taken in triplicate for each sample.</p

Blood biochemistry measurements in immunocompetent and immunosuppressed mice, fed either <i>B</i>. <i>uniformis</i> CECT 7771 or placebo.

<p>Control, mouse group fed placebo daily by gavage for 6 days (n = 10); Control + B, mouse group that received a daily dose of 2 x10⁹ CFU <i>B</i>. <i>uniformis</i> CECT 7771 by gavage for 6 days (n = 10); IMM, immunosuppressed mouse group fed placebo daily by gavage for 6 days (n = 10); and IMM+B, immunosuppressed mouse group receiving a daily dose of 2 x10⁹CFU <i>B</i>. <i>uniformis</i> CECT 7771 by gavage for 6 days (n = 10). Data are expressed as means and SEM. The differences were determined by applying the Mann-Whitney U test. In every case, p-values <0.05 were considered statistically significant. Measurements were taken in triplicate for each sample.</p

Cytokine production in jejunum samples from immunocompetent and immunosuppressed mice, fed either <i>B</i>.<i>uniformis</i> CECT 7771 or placebo.

<p>Control, mouse group fed placebo daily by gavage for 6 days (n = 10); Control + B, mouse group that received a daily dose of 2 x10⁹ CFU <i>B</i>. <i>uniformis</i> CECT 7771 by gavage for 6 days (n = 10); IMM, immunosuppressed mouse group fed placebo daily by gavage for 6 days (n = 10); and IMM+B, immunosuppressed mouse group receiving a daily dose of 2 x10⁹CFU <i>B</i>. <i>uniformis</i> CECT 7771 by gavage for 6 days (n = 10). Data are expressed as means ± SEM. The differences were determined by applying the Mann-Whitney <i>U</i> test. In every case, p-values <0.05 were considered statistically significant. These measurements were taken in triplicate for each sample.</p

PPAR-γ and iNOS protein expression in colon from immunocompetent and immunosuppressed mice, fed either <i>B</i>.<i>uniformis</i> CECT 7771 or placebo.

<p>(A) PPAR-γ and (B) iNOS protein expression from colon protein samples were visualized using western blot analysis. Control, mouse group fed placebo daily by gavage for 6 days (n = 5); Control + B, mouse group that received a daily dose of 2 x10⁹ CFU <i>B</i>. <i>uniformis</i> CECT 7771 by gavage for 6 days (n = 5); IMM, immunosuppressed mouse group fed placebo daily by gavage for 6 days (n = 5); and IMM+B, immunosuppressed mouse group receiving a daily dose of 2 x10⁹CFU <i>B</i>. <i>uniformis</i> CECT 7771 by gavage for 6 days (n = 5).</p

Arginine Biosynthesis in Thermotoga maritima: Characterization of the Arginine-Sensitive N-Acetyl-l-Glutamate Kinase

To help clarify the control of arginine synthesis in Thermotoga maritima, the putative gene (argB) for N-acetyl-l-glutamate kinase (NAGK) from this microorganism was cloned and overexpressed, and the resulting protein was purified and shown to be a highly thermostable and specific NAGK that is potently and selectively inhibited by arginine. Therefore, NAGK is in T. maritima the feedback control point of arginine synthesis, a process that in this organism involves acetyl group recycling and appears not to involve classical acetylglutamate synthase. The inhibition of NAGK by arginine was found to be pH independent and to depend sigmoidally on the concentration of arginine, with a Hill coefficient (N) of ∼4, and the 50% inhibitory arginine concentration (I(0.5)) was shown to increase with temperature, approaching above 65°C the I(0.50) observed at 37°C with the mesophilic NAGK of Pseudomonas aeruginosa (the best-studied arginine-inhibitable NAGK). At 75°C, the inhibition by arginine of T. maritima NAGK was due to a large increase in the K(m) for acetylglutamate triggered by the inhibitor, but at 37°C arginine also substantially decreased the V(max) of the enzyme. The NAGKs of T. maritima and P. aeruginosa behaved in gel filtration as hexamers, justifying the sigmoidicity and high Hill coefficient of arginine inhibition, and arginine or the substrates failed to disaggregate these enzymes. In contrast, Escherichia coli NAGK is not inhibited by arginine and is dimeric, and thus the hexameric architecture may be an important determinant of arginine sensitivity. Potential thermostability determinants of T. maritima NAGK are also discussed

A New Paradigm in the Relationship between Gut Microbiota and Breast Cancer: β-glucuronidase Enzyme Identified as Potential Therapeutic Target

Breast cancer (BC) is the most frequently occurring malignancy and the second cancer-specific cause of mortality in women in developed countries. Over 70% of the total number of BCs are hormone receptor-positive (HR+), and elevated levels of circulating estrogen (E) in the blood have been shown to be a major risk factor for the development of HR+ BC. This is attributable to estrogen’s contribution to increased cancer cell proliferation, stimulation of angiogenesis and metastasis, and resistance to therapy. The E metabolism–gut microbiome axis is functional, with subjacent individual variations in the levels of E. It is conceivable that the estrobolome (bacterial genes whose products metabolize E) may contribute to the risk of malignant neoplasms of hormonal origin, including BC, and may serve as a potential biomarker and target. It has been suggested that β-glucuronidase (GUS) enzymes of the intestinal microbiome participate in the strobolome. In addition, it has been proposed that bacterial GUS enzymes from the gastrointestinal tract participate in hormone BC. In this review, we discuss the latest knowledge about the role of the GUS enzyme in the pathogenesis of BC, focusing on (i) the microbiome and E metabolism; (ii) diet, estrobolome, and BC development; (iii) other activities of the bacterial GUS; and (iv) the new molecular targets for BC therapeutic application