RESUMO
Although children and adolescents with acute lymphoblastic leukaemia (ALL) have high survival rates, approximately 15-20% of patients relapse. Risk of relapse is routinely estimated at diagnosis by biological factors, including flow cytometry data. This high-dimensional data is typically manually assessed by projecting it onto a subset of biomarkers. Cell density and "empty spaces" in 2D projections of the data, i.e. regions devoid of cells, are then used for qualitative assessment. Here, we use topological data analysis (TDA), which quantifies shapes, including empty spaces, in data, to analyse pre-treatment ALL datasets with known patient outcomes. We combine these fully unsupervised analyses with Machine Learning (ML) to identify significant shape characteristics and demonstrate that they accurately predict risk of relapse, particularly for patients previously classified as 'low risk'. We independently confirm the predictive power of CD10, CD20, CD38, and CD45 as biomarkers for ALL diagnosis. Based on our analyses, we propose three increasingly detailed prognostic pipelines for analysing flow cytometry data from ALL patients depending on technical and technological availability: 1. Visual inspection of specific biological features in biparametric projections of the data; 2. Computation of quantitative topological descriptors of such projections; 3. A combined analysis, using TDA and ML, in the four-parameter space defined by CD10, CD20, CD38 and CD45. Our analyses readily extend to other haematological malignancies.
Assuntos
Neoplasias Hematológicas , Leucemia-Linfoma Linfoblástico de Células Precursoras , Criança , Adolescente , Humanos , Recidiva Local de Neoplasia , Leucemia-Linfoma Linfoblástico de Células Precursoras/patologia , Citometria de Fluxo , Imunofenotipagem , RecidivaRESUMO
AIM: The immune status of children recovering from SARS-CoV-2 infection is not completely understood. We describe IgG antispike persistence in children infected during the first two pandemic waves. In addition, we compared with healthy controls their leukocyte populations and CD64 expression. METHODS: Cross-sectional study. Carried out from October 2021 to February 2022 in nonreinfected and nonvaccinated children with SARS-CoV-2 in 2020. The presence of antispike IgG was studied using chemiluminescent immunoassay. Leukocyte populations were analysed using flow cytometry and marked for CD45, CD4, CD8 and CD64. Statistical minor than 0.05 was considered significant. RESULTS: One hundred and eighty-three control and 77 patients were included. IgG antispike determinations were performed after a median of 501 days (262-464); 52 of 77 children were positive. Cases showed significantly higher percentages of monocytes, lymphocytes, CD8+ and CD4+ . In addition, CD64 expression was higher in monocytes and neutrophils. The presence of IgG antispike was accompanied by a higher percentage of CD64+ neutrophils. CONCLUSION: In our series, the SARS-CoV-2 IgG antispike protein was usually positive beyond 1 year after infection. Furthermore, leukocyte populations from cases differ from controls, with higher CD64 expression on neutrophils and monocytes. Prospective clinical observations are required to confirm the implications of these findings.
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COVID-19 , SARS-CoV-2 , Humanos , Criança , Estudos Prospectivos , Estudos Transversais , Receptores de IgG/genética , Receptores de IgG/metabolismo , Imunoglobulina G , Anticorpos AntiviraisRESUMO
Haematopoiesis is the process of generation of blood cells. Lymphopoiesis generates lymphocytes, the cells in charge of the adaptive immune response. Disruptions of this process are associated with diseases like leukaemia, which is especially incident in children. The characteristics of self-regulation of this process make them suitable for a mathematical study. In this paper we develop mathematical models of lymphopoiesis using currently available data. We do this by drawing inspiration from existing structured models of cell lineage development and integrating them with paediatric bone marrow data, with special focus on regulatory mechanisms. A formal analysis of the models is carried out, giving steady states and their stability conditions. We use this analysis to obtain biologically relevant regions of the parameter space and to understand the dynamical behaviour of B-cell renovation. Finally, we use numerical simulations to obtain further insight into the influence of proliferation and maturation rates on the reconstitution of the cells in the B line. We conclude that a model including feedback regulation of cell proliferation represents a biologically plausible depiction for B-cell reconstitution in bone marrow. Research into haematological disorders could benefit from a precise dynamical description of B lymphopoiesis.
Assuntos
Linfócitos B , Linfopoese , Linhagem da Célula , Criança , Retroalimentação , Humanos , Modelos TeóricosRESUMO
[This corrects the article DOI: 10.3389/fimmu.2023.1280580.].
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Introduction: Loss of B-cell aplasia (BCA) is a well-known marker of functional loss of CD19 CAR-T. Most relapses and loss of BCA occur in the first months after CD19 CAR-T infusion. In addition, high tumor burden (HTB) has shown to have a strong impact on relapse, especially in CD19-negative. However, little is known about the impact of late loss of BCA or the relationship between BCA and pre-infusion tumor burden in patients infused with tisagenlecleucel for relapsed/refractory B-cell acute lymphoblastic leukemia. Therefore, the optimal management of patients with loss of BCA is yet to be defined. Methods: We conducted a Spanish, multicentre, retrospective study in patients infused with tisagenlecleucel after marketing authorization. A total of 73 consecutively treated patients were evaluated. Results: Prior to infusion, 39 patients had HTB (≥ 5% bone marrow blasts) whereas 34 had a low tumor burden (LTB) (<5% blasts). Complete remission was achieved in 90.4% of patients, of whom 59% relapsed. HTB was associated with inferior outcomes, with a 12-month EFS of 19.3% compared to 67.2% in patients with LTB (p<0.001) with a median follow-up of 13.5 months (95% CI 12.4 - 16.2). In the HTB subgroup relapses were mainly CD19-negative (72%) whereas in the LTB subgroup they were mainly CD19-positive (71%) (p=0.017). In the LTB group, all CD19-positive relapses were preceded by loss of BCA whereas only 57% (4/7) of HTB patients experienced CD19-positive relapse. We found a positive correlation between loss of BCA and CD19-positive relapse (R-squared: 74) which persisted beyond six months post-infusion. We also explored B-cell recovery over time using two different definitions of loss of BCA and found a few discrepancies. Interestingly, transient immature B-cell recovery followed by BCA was observed in two pediatric patients. In conclusion, HTB has an unfavorable impact on EFS and allo-SCT might be considered in all patients with HTB, regardless of BCA. In patients with LTB, loss of BCA preceded all CD19-positive relapses. CD19-positive relapse was also frequent in patients who lost BCA beyond six months post-infusion. Therefore, these patients are still at significant risk for relapse and close MRD monitoring and/or therapeutic interventions should be considered.
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Leucemia-Linfoma Linfoblástico de Células Precursoras , Receptores de Antígenos de Linfócitos T , Receptores de Antígenos Quiméricos , Salicilatos , Humanos , Criança , Adulto Jovem , Receptores de Antígenos Quiméricos/uso terapêutico , Estudos Retrospectivos , Leucemia-Linfoma Linfoblástico de Células Precursoras/tratamento farmacológico , Recidiva , Linfócitos T , Efeitos Psicossociais da DoençaRESUMO
BACKGROUND: A new clinical syndrome named Paediatric Inflammatory Multisystem Syndrome Temporally Associated with SARS-CoV-2 (PIMS-TS) has been described. This new disease is a leading cause of hospital and paediatric intensive care unit (PICU). It has been related to immunity dysregulation. METHODS: Prospective-retrospective observational study to describe the innate cell signature and immunophenotype of children admitted to PICU because of PIMS-TS (from March 2020 to September 2020). The immunophenotype was done through the expression analysis of these proteins of mononuclear cells: CD64, CD18, CD11a and CD11b. They were compared with previous healthy controls and children admitted to PICU because of bacterial infection, viral infection and Kawasaki disease (KD). Two hundred and forty-seven children were studied: 183 healthy controls, 25 viral infections, 20 bacterial infections, 6 KD and 13 PIMS-TS. RESULTS: PIMT-TS showed the lowest percentage of lymphocytes and monocytes with higher relative numbers of CD4+ (p = .000). Monocytes and neutrophils in PIMS-TS showed higher levels of CD64 expression (p = .000). Also, CD11a and CD11b were highly expressed (p =,000). CONCLUSION: We observed a differential cell innate signature in PIMS-TS. These findings are consistent with a proinflammatory status (CD64 elevated expression) and lymphocyte trafficking to tissues (CD11a and CD11b). More studies should be carried out to confirm our results.
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Infecções Bacterianas , COVID-19 , Síndrome de Linfonodos Mucocutâneos , Viroses , COVID-19/complicações , Criança , Humanos , Síndrome de Linfonodos Mucocutâneos/complicações , Estudos Prospectivos , Receptores de IgG , SARS-CoV-2 , Síndrome de Resposta Inflamatória Sistêmica/complicaçõesRESUMO
Artificial intelligence methods may help in unveiling information that is hidden in high-dimensional oncological data. Flow cytometry studies of haematological malignancies provide quantitative data with the potential to be used for the construction of response biomarkers. Many computational methods from the bioinformatics toolbox can be applied to these data, but they have not been exploited in their full potential in leukaemias, specifically for the case of childhood B-cell Acute Lymphoblastic Leukaemia. In this paper, we analysed flow cytometry data that were obtained at diagnosis from 56 paediatric B-cell Acute Lymphoblastic Leukaemia patients from two local institutions. Our aim was to assess the prognostic potential of immunophenotypical marker expression intensity. We constructed classifiers that are based on the Fisher's Ratio to quantify differences between patients with relapsing and non-relapsing disease. We also correlated this with genetic information. The main result that arises from the data was the association between subexpression of marker CD38 and the probability of relapse.