COVID-19 and Cancer: Discovery of Difference in Clinical Immune Indexes.

OBJECTIVE: This study explored the consistency and differences in the immune cells and cytokines between patients with COVID-19 or cancer. We further analyzed the correlations between the acute inflammation and cancer-related immune disorder. METHODS: This retrospective study involved 167 COVID-19 patients and 218 cancer patients. COVID-19 and cancer were each further divided into two subgroups. Quantitative and qualitative variables were measured by one-way ANOVA and chi-square test, respectively. Herein, we carried out a correlation analysis between immune cells and cytokines and used receiver operating characteristic (ROC) curves to discover the optimal diagnostic index. RESULTS: COVID-19 and cancers were associated with lymphopenia and high levels of monocytes, neutrophils, IL-6, and IL-10. IL-2 was the optimal indicator to differentiate the two diseases. Compared with respiratory cancer patients, COVID-19 patients had lower levels of IL-2 and higher levels of CD3+CD4+ T cells and CD19+ B cells. In the subgroup analysis, IL-6 was the optimal differential diagnostic parameter that had the ability to identify if COVID-19 patients would be severely affected, and severe COVID-19 patients had lower levels of lymphocyte subsets (CD3+ T cells, CD3+CD4+ T cells, CD3+CD8+T cells, and CD19+ B cells) and CD16+CD56+ NK cells and higher level of neutrophils. There were significant differences in the levels of CD3+CD4+ T cells and CD19+ B cells between T1-2 and T3-4 stages as well as IL-2 and CD19+ B cells between N0-1 and N2-3 stages while no significant differences between the metastatic and nonmetastatic cancer patients. Additionally, there were higher correlations between IL-2 and IL-4, TNF-α and IL-2, TNF-α and IL-4, TNF-α and IFN-γ, and CD16+CD56+NK cells and various subsets of T cells in COVID-19 patients. There was a higher correlation between CD3+CD4+ T cells and CD19+ B cells in cancer patients. CONCLUSION: Inflammation associated with COVID-19 or cancer had effects on patients' outcomes. Accompanied by changes in immune cells and cytokines, there were consistencies, differences, and satisfactory correlations between patients with COVID-19 and those with cancers.

SARS-CoV-2-specific immune response in COVID-19 convalescent individuals.

We collected blood from coronavirus disease 2019 (COVID-19) convalescent individuals and investigated SARS-CoV-2-specific humoral and cellular immunity in these discharged patients. Follow-up analysis in a cohort of 171 patients at 4-11 months after the onset revealed high levels of IgG antibodies. A total of 78.1% (164/210) of the specimens tested positive for neutralizing antibody (NAb). SARS-CoV-2 antigen peptide pools-stimulated-IL-2 and -IFN-γ response can distinguish COVID-19 convalescent individuals from healthy donors. Interestingly, NAb survival was significantly affected by the antigen peptide pools-stimulated-IL-2 response, -IL-8 response, and -IFN-γ response. The antigen peptide pools-activated CD8+ T cell counts were correlated with NAb. The antigen peptide pools-activated natural killer (NK) cell counts in convalescent individuals were correlated with NAb and disease severity. Our data suggested that the development of NAb is associated with the activation of T cells and NK cells. Our work provides a basis for further analysis of the protective immunity to SARS-CoV-2 and for understanding the pathogenesis of COVID-19. It also has implications for the development of an effective vaccine for SARS-CoV-2 infection.

Analysis of Lymphocyte Subpopulations and Cytokines in COVID-19-Associated Pneumonia and Community-Acquired Pneumonia.

BACKGROUND: The 2019 novel coronavirus SARS-CoV-2 caused large outbreaks of COVID-19 worldwide. COVID-19 resembles community-acquired pneumonia (CAP). Our aim was to identify lymphocyte subpopulations to distinguish between COVID-19 and CAP. METHODS: We compared the peripheral blood lymphocytes and their subsets in 296 patients with COVID-19 and 130 patients with CAP. Parameters for independent prediction of COVID-19 were calculated by logistic regression. RESULTS: The main lymphocyte subpopulations (CD3+CD4+, CD16+CD56+, and CD4+/CD8+ ratio) and cytokines (TNF-α and IFN-γ) of COVID-19 patients were significantly different from that of CAP patients. CD16+CD56+%, CD4+/CD8+ratio, CD19+, and CD3+CD4+ were identified as predictors of COVID-19 diagnosis by logistic regression. In addition, the CD3+CD4+counts, CD3+CD8+ counts, andTNF-α are independent predictors of disease severity in patients. CONCLUSIONS: Lymphopenia is an important part of SARS-CoV-2 infection, and lymphocyte subsets and cytokines may be useful to predict the severity and clinical outcomes of the disease.

Can routine laboratory tests discriminate SARS-CoV-2-infected pneumonia from other causes of community-acquired pneumonia?

BACKGROUND: The clinical presentation of SARS-CoV-2-infected pneumonia (COVID-19) resembles that of other etiologies of community-acquired pneumonia (CAP). We aimed to identify clinical laboratory features to distinguish COVID-19 from CAP. METHODS: We compared the hematological and biochemical features of 84 patients with COVID-19 at hospital admission and 221 patients with CAP. Parameters independently predictive of COVID-19 were calculated by multivariate logistic regression. The receiver operating characteristic (ROC) curves were generated and the area under the ROC curve (AUC) was measured to evaluate the discriminative ability. RESULTS: Most hematological and biochemical indexes of patients with COVID-19 were significantly different from patients with CAP. Nine laboratory parameters were identified to be predictive of a diagnosis of COVID-19. The AUCs demonstrated good discriminatory ability for red cell distribution width (RDW) with an AUC of 0.87 and hemoglobin with an AUC of 0.81. Red blood cell, albumin, eosinophil, hematocrit, alkaline phosphatase, and mean platelet volume had fair discriminatory ability. Combinations of any two parameters performed better than did the RDW alone. CONCLUSIONS: Routine laboratory examinations may be helpful for the diagnosis of COVID-19. Application of laboratory tests may help to optimize the use of isolation rooms for patients when they present with unexplained febrile respiratory illnesses.