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Identification of 15 T cell restricted genes evaluates t cell infiltration of human healthy tissues and cancers and shows prognostic and predictive potential

TitoloIdentification of 15 T cell restricted genes evaluates t cell infiltration of human healthy tissues and cancers and shows prognostic and predictive potential
Tipo di pubblicazioneArticolo su Rivista peer-reviewed
Anno di Pubblicazione2019
AutoriCari, Luigi, De Rosa Francesca, Petrillo Maria Grazia, Migliorati Graziella, Nocentini Giuseppe, and Riccardi Carlo
RivistaInternational Journal of Molecular Sciences
Volume20
Type of ArticleArticle
ISSN16616596
Parole chiavearticle, B lymphocyte, bioinformatics, Biomarkers, Brain Neoplasms, brain tumor, cancer prognosis, cell motion, Cell Movement, clear cell carcinoma cell line, clinical evaluation, controlled study, dendritic cell, Drug Resistance, Gene expression, gene expression level, gene identification, gene overexpression, genetics, granulocyte, high throughput sequencing, histology, human, human cell, human tissue, Humans, lung adenocarcinoma, lymphocytic infiltration, lymphoid tissue, macrophage, malignant neoplasm, medulloblastoma, memory T lymphocyte, metabolism, microarray analysis, mRNA expression level, Neoplasm, Neuroblastoma, Nivolumab, parenchyma, Pathology, physiology, predictive value, RNA extraction, RNA sequence, Sensitivity analysis, T lymphocyte, T-Lymphocytes, Tumor, tumor marker
Abstract

T cell gene signatures are used to evaluate T cell infiltration of non-lymphoid tissues and cancers in both experimental and clinical settings. However, some genes included in the available T cell signatures are not T cell-restricted. Herein, we propose a new human T cell signature that has been developed via a six-step procedure and comprises 15 T cell restricted genes. We demonstrate the new T cell signature, named signature-H, that differs from other gene signatures since it shows higher sensitivity and better predictivity in the evaluation of T cell infiltration in healthy tissues as well as 32 cancers. Further, results from signature-H are highly concordant with the immunohistochemistry methods currently used for assessing the prognosis of neuroblastoma, as demonstrated by the Kaplan–Meier curves of patients ranked by tumor T cell infiltration. Moreover, T cell infiltration levels calculated using signature-H correlate with the risk groups determined by the staging of the neuroblastoma. Finally, multiparametric analysis of tumor-infiltrating T cells based on signature-H let us favorably predict the response of melanoma to the anti-PD-1 antibody nivolumab. These findings suggest that signature-H evaluates T cell infiltration levels of tissues and may be used as a prognostic tool in the precision medicine perspective after appropriate clinical validation. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.

Note

Cited by: 4; All Open Access, Gold Open Access, Green Open Access

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85074134456&doi=10.3390%2fijms20205242&partnerID=40&md5=47638a22aa76966f92e1fabd25425880
DOI10.3390/ijms20205242
Citation KeyCari2019
PubMed ID31652661