Specific Cellular and Humoral Immune Responses to the Neoantigen RBD of SARS-CoV-2 in Patients with Primary and Secondary Immunodeficiency and Healthy Donors.

Patients with antibody deficiency disorders, such as primary immunodeficiency (PID) or secondary immunodeficiency (SID) to B-cell lymphoproliferative disorder (B-CLPD), are two groups vulnerable to developing the severe or chronic form of coronavirus disease caused by SARS-CoV-2 (COVID-19). The data on adaptive immune responses against SARS-CoV-2 are well described in healthy donors, but still limited in patients with antibody deficiency of a different cause. Herein, we analyzed spike-specific IFN-γ and anti-spike IgG antibody responses at 3 to 6 months after exposure to SARS-CoV-2 derived from vaccination and/or infection in two cohorts of immunodeficient patients (PID vs. SID) compared to healthy controls (HCs). Pre-vaccine anti-SARS-CoV-2 cellular responses before vaccine administration were measured in 10 PID patients. Baseline cellular responses were detectable in 4 out of 10 PID patients who had COVID-19 prior to vaccination, perceiving an increase in cellular responses after two-dose vaccination (p < 0.001). Adequate specific cellular responses were observed in 18 out of 20 (90%) PID patients, in 14 out of 20 (70%) SID patients and in 74 out of 81 (96%) HCs after vaccination (and natural infection in some cases). Specific IFN-γ response was significantly higher in HC with respect to PID (1908.5 mUI/mL vs. 1694.1 mUI/mL; p = 0.005). Whereas all SID and HC patients mounted a specific humoral immune response, only 80% of PID patients showed positive anti-SARS-CoV-2 IgG. The titer of anti-SARS-CoV-2 IgG was significantly lower in SID compared with HC patients (p = 0.040), without significant differences between PID and HC patients (p = 0.123) and between PID and SID patients (p =0.683). High proportions of PID and SID patients showed adequate specific cellular responses to receptor binding domain (RBD) neoantigen, with a divergence between the two arms of the adaptive immune response in PID and SID patients. We also focused on the correlation of protection of positive SARS-CoV-2 cellular response to omicron exposure: 27 out of 81 (33.3%) HCs referred COVID-19 detected by PCR or antigen test, 24 with a mild course, 1 with moderate symptoms and the remaining 2 with bilateral pneumonia that were treated in an outpatient basis. Our results might support the relevance of these immunological studies to determine the correlation of protection with severe disease and for deciding the need for additional boosters on a personalized basis. Follow-up studies are required to evaluate the duration and variability in the immune response to COVID-19 vaccination or infection.

Evidence of exhausted lymphocytes after the third anti-SARS-CoV-2 vaccine dose in cancer patients.

Introduction: Evidence is scant regarding the long-term humoral and cellular responses Q7 triggered by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNA vaccines in cancer patients after repeated booster doses. The possibility of T-cell exhaustion following these booster doses in this population has not yet been fully studied and remains uncertain. Methods: In this single-center prospective observational study, we explored the specific humoral and cellular response to S1 antigen in 36 patients with solid malignancies at baseline, and after the second and third doses of the mRNA-1273 vaccine. Results: A dual behavior was observed: 24 (66.7%) patients showed partial specific IFN-γ response after the second dose that was further enhanced after the third dose; and 11 (30.5%) already showed an optimal response after the second dose and experienced a marked fall-off of specific IFN-γ production after the third (4 patients negativization), which might suggest T cell exhaustion due to repetitive priming to the same antigen. One (2.8%) patient had persistently negative responses after all three doses. Seroconversion occurred in all patients after the second dose. We then studied circulating exhausted CD8+ T-cells in 4 patients from each of the two response patterns, those with increase and those with decrease in cellular response after the third booster. The patients with decreased cellular response after the booster had a higher expression of PD1+CD8+ and CD57+PD1+CD8+ exhausted T cells compared with those with an increased cellular response both in vivo and in vitro. The proportion of PD1+CD8+ and CD57+PD1+CD8+ exhausted T cells inversely correlated with IFN-γ production. Discussion: Our preliminary data show that the two-dose SARS-CoV-2 vaccine regimen was beneficial in all cancer patients of our study. An additional booster seems to be beneficial in suboptimal vaccine seroconverters, in contrast to maximal responders that might develop exhaustion. Our data should be interpreted with caution given the small sample size and highlight the urgent need to validate our results in other independent and larger cohorts. Altogether, our data support the relevance of immunological functional studies to personalize preventive and treatment decisions in cancer patients.

SEOM clinical guidelines for the prophylaxis of infectious diseases in cancer patients (2021).

Infections are still a major cause of morbi-mortality in patients with cancer. Some of these infections are preventable through specific measures, such as vaccination or prophylaxis. This guideline aims to summarize the evidence and recommendations for the prevention of infections in cancer patients, devoting special attention to the most prevalent preventable infectious disease. All the evidences will be graded according to The Infectious Diseases Society of America grading system.

Prognostic factors at admission on patients with cancer and COVID-19: Analysis of HOPE registry data Factores pronósticos en pacientes oncológicos con COVID-19 a su llegada a urgencias: Análisis de los datos del registro internacional HOPE

<h4>Background</h4> Previous works seem to agree in the higher mortality of cancer patients with COVID-19. Identifying potential prognostic factors upon admission could help identify patients with a poor prognosis. <h4>Methods</h4> We aimed to explore the characteristics and evolution of COVID-19 cancer patients admitted to hospital in a multicenter international registry (HOPE COVID-19). Our primary objective is to define those characteristics that allow us to identify cancer patients with a worse prognosis (mortality within 30 days after the diagnosis of COVID-19). <h4>Results</h4> 5838 patients have been collected in this registry, of whom 770 had cancer among their antecedents. In hospital mortality reached 258 patients (33.51%). The median was 75 years (65–82). Regarding the distribution by sex, 34.55% of the patients (266/770) were women. The distribution by type of cancer: genitourinary 238/745 (31.95%), digestive 124/745 (16.54%), hematologic 95/745 (12.75%). In multivariate regression analysis, factors that are independently associated with mortality at admission are: renal impairment (OR 3.45, CI 97.5% 1.85–6.58), heart disease (2.32, 1.47–3.66), liver disease (4.69, 1.94–11.62), partial dependence (2.41, 1.34–4.33), total dependence (7.21, 2.60–21.82), fatigue (1.84, 1.16–2.93), arthromialgias (0.45, 0.26–0.78), SatO2 < 92% (4.58, 2.97–7.17), elevated LDH (2.61, 1.51–4.69) and abnormal decreased Blood Pressure (3.57, 1.81–7.15). Analitical parameters are also significant altered. <h4>Conclusion</h4> In patients with cancer from the HOPE registry, 30-day mortality from any cause is high and is associated with easily identifiable clinical factors upon arrival at the hospital. Identifying these patients can help initiate more intensive treatments from the start and evaluate the prognosis of these patients.

Prognostic factors at admission on patients with cancer and COVID-19: Analysis of HOPE registry data.

BACKGROUND: Previous works seem to agree in the higher mortality of cancer patients with COVID-19. Identifying potential prognostic factors upon admission could help identify patients with a poor prognosis. METHODS: We aimed to explore the characteristics and evolution of COVID-19 cancer patients admitted to hospital in a multicenter international registry (HOPE COVID-19).Our primary objective is to define those characteristics that allow us to identify cancer patients with a worse prognosis (mortality within 30 days after the diagnosis of COVID-19). RESULTS: 5838 patients have been collected in this registry, of whom 770 had cancer among their antecedents. In hospital mortality reached 258 patients (33.51%). The median was 75 years (65-82). Regarding the distribution by sex, 34.55% of the patients (266/770) were women.The distribution by type of cancer: genitourinary 238/745 (31.95%), digestive 124/745 (16.54%), hematologic 95/745 (12.75%).In multivariate regression analysis, factors that are independently associated with mortality at admission are: renal impairment (OR 3.45, CI 97.5% 1.85-6.58), heart disease (2.32, 1.47-3.66), liver disease (4.69, 1.94-11.62), partial dependence (2.41, 1.34-4.33), total dependence (7.21, 2.60-21.82), fatigue (1.84, 1.16-2.93), arthromialgias (0.45, 0.26-0.78), SatO2 < 92% (4.58, 2.97-7.17), elevated LDH (2.61, 1.51-4.69) and abnormal decreased Blood Pressure (3.57, 1.81-7.15). Analitical parameters are also significant altered. CONCLUSION: In patients with cancer from the HOPE registry, 30-day mortality from any cause is high and is associated with easily identifiable clinical factors upon arrival at the hospital. Identifying these patients can help initiate more intensive treatments from the start and evaluate the prognosis of these patients.

ANTECEDENTES: Trabajos previos parecen coincidir en la mayor mortalidad de los pacientes con cáncer y COVID-19. La identificación de posibles factores pronósticos en el momento del ingreso podría ayudar a identificar a los pacientes con mal pronóstico. MÉTODOS: Nos propusimos explorar las características y la evolución de los pacientes con cáncer y COVID-19 ingresados en un registro internacional multicéntrico (HOPE COVID-19).Nuestro objetivo principal es definir aquellas características que nos permitan identificar a los pacientes con cáncer de peor pronóstico (mortalidad en los 30 días siguientes al diagnóstico de COVID-19). RESULTADOS: En este registro se ha recogido a 5.838 pacientes, de los cuales 770 tenían cáncer entre sus antecedentes. La mortalidad hospitalaria alcanzó a 258 pacientes (33,51%). La mediana fue de 75 años (65-82). En cuanto a la distribución por sexo, el 34,55% de los pacientes eran mujeres (266/770).La distribución por tipo de cáncer: genitourinario 238/745 (31,95%), digestivo 124/745 (16,54%) y hematológico 95/745 (12,75%).En el análisis de regresión multivariante, los factores que se asocian de forma independiente con la mortalidad al ingreso son: insuficiencia renal (OR 3,45; IC 97,5%: 1,85-6,58), cardiopatía (2,32; 1,47-3,66), hepatopatía (4,69; 1,94-11,62), dependencia parcial (2,41; 1,34-4,33), dependencia total (7,21; 2,60-21,82), fatiga (1,84, 1;16-2,93), artromialgias (0,45; 0,26-0,78), SatO2 < 92% (4,58; 2,97-7,17), LDH elevada (2,61; 1,51-4,69) y disminución anormal de la presión arterial (3,57; 1,81-7,15). Los parámetros analíticos también están significativamente alterados. CONCLUSIÓN: En los pacientes con cáncer del registro HOPE, la mortalidad a los 30 días por cualquier causa es elevada y se asocia a factores clínicos fácilmente identificables a su llegada al hospital. La identificación de estos pacientes puede ayudar a iniciar tratamientos más intensivos desde el principio y evaluar el pronóstico de estos pacientes.

Prognostic factors at admission on patients with cancer and COVID-19: Analysis of HOPE registry data.

BACKGROUND: Previous works seem to agree in the higher mortality of cancer patients with COVID-19. Identifying potential prognostic factors upon admission could help identify patients with a poor prognosis. METHODS: We aimed to explore the characteristics and evolution of COVID-19 cancer patients admitted to hospital in a multicenter international registry (HOPE COVID-19). Our primary objective is to define those characteristics that allow us to identify cancer patients with a worse prognosis (mortality within 30 days after the diagnosis of COVID-19). RESULTS: 5838 patients have been collected in this registry, of whom 770 had cancer among their antecedents. In hospital mortality reached 258 patients (33.51%). The median was 75 years (65-82). Regarding the distribution by sex, 34.55% of the patients (266/770) were women. The distribution by type of cancer: genitourinary 238/745 (31.95%), digestive 124/745 (16.54%), hematologic 95/745 (12.75%). In multivariate regression analysis, factors that are independently associated with mortality at admission are: renal impairment (OR 3.45, CI 97.5% 1.85-6.58), heart disease (2.32, 1.47-3.66), liver disease (4.69, 1.94-11.62), partial dependence (2.41, 1.34-4.33), total dependence (7.21, 2.60-21.82), fatigue (1.84, 1.16-2.93), arthromialgias (0.45, 0.26-0.78), SatO2<92% (4.58, 2.97-7.17), elevated LDH (2.61, 1.51-4.69) and abnormal decreased Blood Pressure (3.57, 1.81-7.15). Analitical parameters are also significant altered. CONCLUSION: In patients with cancer from the HOPE registry, 30-day mortality from any cause is high and is associated with easily identifiable clinical factors upon arrival at the hospital. Identifying these patients can help initiate more intensive treatments from the start and evaluate the prognosis of these patients.

A snapshot of COVID-19 infection in patients with solid tumors.

Coronavirus disease 2019 (COVID-19) pandemic is affecting a high percentage of the population at an unprecedented rate. Cancer patients comprise a subgroup especially vulnerable to this infection. Herein, we present a prospective analysis of epidemiological, clinical, radiological and laboratory data of consecutive adult cancer patients seen in the Clínico San Carlos University Hospital (Madrid, Spain), and admitted to hospital and tested for COVID-19 between 21 February 2020 and 8 May 2020 due to clinical suspicion of infection. Data from 73 patients with confirmed COVID-19 and active solid tumors or diagnosed within the previous 5 years were analyzed. The most frequent malignancy was lung cancer (19%) and 54 patients (74%) were on active cancer treatment. Most common findings on presentation included cough (55%), fever (52%) and dyspnea (45%), and 32 (44%) patients showed oxygen saturation levels below 95%. Radiologically, 54 (73%) patients presented an abnormal pattern, the most frequent being infiltrates (64%). 18 (24.7%) patients died in hospital and 55 (75.3%) were discharged with clinical resolution of the event. Multivariable logistic regression adjusted for age and tumor stage showed higher odds of in-hospital death associated with a history of cardiovascular disease, hospitalization in the previous 30 days, and several features on admission including dyspnea, higher qSOFA score, higher C-reactive protein levels and an abnormal neutrophil count. We present prospective, real-world evidence that can help articulate cancer care protocols for patients infected with SARS-CoV-2, with special focus on features on admission that can stratify patients with a higher risk of death from COVID-19.