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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

TitleIdentification of 15 T cell restricted genes evaluates t cell infiltration of human healthy tissues and cancers and shows prognostic and predictive potential
Publication TypeArticolo su Rivista peer-reviewed
Year of Publication2019
AuthorsCari, Luigi, De Rosa Francesca, Petrillo Maria Grazia, Migliorati Graziella, Nocentini Giuseppe, and Riccardi Carlo
JournalInternational Journal of Molecular Sciences
Type of ArticleArticle
Keywordsarticle, 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

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.


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

Citation KeyCari2019
PubMed ID31652661