{"doi":"10.3389/fimmu.2022.1052104","title":"Distinct systemic immune networks define severe vs. mild COVID-19 in hematologic and solid cancer patients","abstract":"Introduction: The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, has impacted health across all sectors of society. A cytokine-release syndrome, combined with an inefficient response of innate immune cells to directly combat the virus, characterizes the severe form of COVID-19. While immune factors involved in the development of severe COVID-19 in the general population are becoming clearer, identification of the immune mechanisms behind severe disease in oncologic patients remains uncertain. Methods: Here we evaluated the systemic immune response through the analysis of soluble blood immune factors and anti-SARS-CoV-2 antibodies within the early days of a positive SARS-CoV-2 diagnostic in oncologic patients. Results: Individuals with hematologic malignancies that went on to die from COVID-19 displayed at diagnosis severe leukopenia, low antibody production against SARS-CoV-2 proteins, and elevated production of innate immune cell recruitment and activation factors. These patients also displayed correlation networks in which IL-2, IL-13, TNF-alpha, IFN-gamma, and FGF2 were the focal points. Hematologic cancer patients that showed highly networked and coordinated anti-SARS-CoV-2 antibody production, with central importance of IL-4, IL-5, IL-12A, IL-15, and IL-17A, presented only mild COVID-19. Conversely, solid tumor patients that had elevated levels of inflammatory cytokines IL-6, CXCL8, and lost the coordinate production of anti-virus antibodies developed severe COVID-19 and died. Patients that displayed positive correlation networks between anti-virus antibodies, and a regulatory axis involving IL-10 and inflammatory cytokines recovered from the disease. We also provided evidence that CXCL8 is a strong predictor of death for oncologic patients and could be an indicator of poor prognosis within days of the positive diagnostic of SARS-CoV-2 infection. Conclusion: Our findings defined distinct systemic immune profiles associated with COVID-19 clinical outcome of patients with cancer and COVID-19. These systemic immune networks shed light on potential immune mechanisms involved in disease outcome, as well as identify potential clinically useful biomarkers.","journal":"Frontiers in Immunology","year":2023,"id":378295,"datarank":0.16479184330021646,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.0,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9619,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":497700,"name":"Amanda Braga Figueiredo","orcid":"0000-0002-4759-6679","position":1,"is_corresponding":false},{"id":1142644,"name":"Nayane A. L. Galdino","orcid":null,"position":2,"is_corresponding":false},{"id":497702,"name":"Kátia L.P. Morais","orcid":"0000-0001-8877-5887","position":3,"is_corresponding":false},{"id":497704,"name":"Walderez O. Dutra","orcid":"0000-0002-7586-9996","position":4,"is_corresponding":false},{"id":1142645,"name":"Bianca Grassi de Miranda Silva","orcid":null,"position":5,"is_corresponding":false},{"id":1142234,"name":"Diego Feriani","orcid":"0000-0002-3733-6048","position":6,"is_corresponding":false},{"id":1142646,"name":"Flávia de Azevedo Abrantes","orcid":null,"position":7,"is_corresponding":false},{"id":1142647,"name":"Ivan Leonardo Avelino França e Silva","orcid":null,"position":8,"is_corresponding":false},{"id":1142235,"name":"Jayr Schmidt Filho","orcid":"0000-0001-8212-1620","position":9,"is_corresponding":false},{"id":1142236,"name":"Juliana Valéria de Souza Framil","orcid":"0000-0001-5055-7745","position":10,"is_corresponding":false},{"id":1142237,"name":"Marcelle Goldner Cesca","orcid":"0000-0002-9156-1641","position":11,"is_corresponding":false},{"id":1142238,"name":"Rachel P. Riechelmann","orcid":"0000-0002-0107-9617","position":12,"is_corresponding":false},{"id":1069662,"name":"Marjorie Vieira Batista","orcid":"0000-0003-0717-0873","position":13,"is_corresponding":false},{"id":497705,"name":"Kenneth J. Gollob","orcid":"0000-0003-4184-3867","position":14,"is_corresponding":false},{"id":1142233,"name":"Flávio Pignataro-Oshiro","orcid":"0000-0002-6674-1456","position":0,"is_corresponding":true}],"reference_count":48,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T01:16:44.708019Z","pmid":"36700209","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}