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Development of a Molecular Blood-Based Immune Signature Classifier as Biomarker for Risks Assessment in Lung Cancer Screening.
Fortunato, Orazio; Huber, Veronica; Segale, Miriam; Cova, Agata; Vallacchi, Viviana; Squarcina, Paola; Rivoltini, Licia; Suatoni, Paola; Sozzi, Gabriella; Pastorino, Ugo; Boeri, Mattia.
Afiliação
  • Fortunato O; Tumor Genomics Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
  • Huber V; Unit of Immunotherapy of Human Tumors, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
  • Segale M; Tumor Genomics Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
  • Cova A; Unit of Immunotherapy of Human Tumors, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
  • Vallacchi V; Unit of Immunotherapy of Human Tumors, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
  • Squarcina P; Unit of Immunotherapy of Human Tumors, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
  • Rivoltini L; Unit of Immunotherapy of Human Tumors, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
  • Suatoni P; Thoracic Surgery Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
  • Sozzi G; Tumor Genomics Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
  • Pastorino U; Thoracic Surgery Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
  • Boeri M; Tumor Genomics Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Cancer Epidemiol Biomarkers Prev ; 31(11): 2020-2029, 2022 11 02.
Article em En | MEDLINE | ID: mdl-36112827
BACKGROUND: Low-dose CT (LDCT) screening trials have shown that lung cancer early detection saves lives. However, a better stratification of the screening population is still needed. In this respect, we generated and prospectively validated a plasma miRNA signature classifier (MSC) able to categorize screening participants according to lung cancer risk. Here, we aimed to deeply characterize the peripheral immune profile and develop a diagnostic immune signature classifier to further implement blood testing in lung cancer screening. METHODS: Peripheral blood mononuclear cell (PBMC) samples collected from 20 patients with LDCT-detected lung cancer and 20 matched cancer-free screening volunteers were analyzed by flow cytometry using multiplex panels characterizing both lymphoid and myeloid immune subsets. Data were validated in PBMC from 40 patients with lung cancer and 40 matched controls and in a lung cancer specificity set including 27 subjects with suspicious lung nodules. A qPCR-based gene expression signature was generated resembling selected immune subsets. RESULTS: Monocytic myeloid-derived suppressor cell (MDSC), polymorphonuclear MDSC, intermediate monocytes and CD8+PD-1+ T cells distinguished patients with lung cancer from controls with AUCs values of 0.94/0.72/0.88 in the training, validation, and lung cancer specificity set, respectively. AUCs raised up to 1.00/0.84/0.92 in subgroup analysis considering only MSC-negative subjects. A 14-immune genes expression signature distinguished patients from controls with AUC values of 0.76 in the validation set and 0.83 in MSC-negative subjects. CONCLUSIONS: An immune-based classifier can enhance the accuracy of blood testing, thus supporting the contribution of systemic immunity to lung carcinogenesis. IMPACT: Implementing LDCT screening trials with minimally invasive blood tests could help reduce unnecessary procedures and optimize cost-effectiveness.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: MicroRNAs / Neoplasias Pulmonares Tipo de estudo: Diagnostic_studies / Etiology_studies / Risk_factors_studies / Screening_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: MicroRNAs / Neoplasias Pulmonares Tipo de estudo: Diagnostic_studies / Etiology_studies / Risk_factors_studies / Screening_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article