A “lymphocyte microrna signature” as predictive biomarker of immunotherapy response and plasma pd-1/pd-l1 expression levels in patients with metastatic renal cell carcinoma: Pointing towards epigenetic reprogramming

Daniele Fanale, Chiara Brando, Viviana Bazan, Giuseppe Badalamenti, Lorena Incorvaia, Marco Bono, Antonio Russo, Juan Lucio Iovanna, Laura Algeri, Lidia Rita Corsini, Salvatore Scurria

Risultato della ricerca: Articlepeer review

1 Citazioni (Scopus)

Abstract

Introduction of checkpoint inhibitors resulted in durable responses and improvements in overall survival in advanced RCC patients, but the treatment efficacy is widely variable, and a considerable number of patients are resistant to PD-1/PD-L1 inhibition. This variability of clinical response makes necessary the discovery of predictive biomarkers for patient selection. Previous findings showed that the epigenetic modifications, including an extensive microRNA-mediated regulation of tumor suppressor genes, are key features of RCC. Based on this biological background, we hypothesized that a miRNA expression profile directly identified in the peripheral lymphocytes of the patients before and after the nivolumab administration could represent a step toward a real-time monitoring of the dynamic changes during cancer evolution and treatment. Interestingly, we found a specific subset of miRNAs, called “lymphocyte miRNA signature”, specifically induced in long-responder patients (CR, PR, or SD to nivolumab >18 months). Focusing on the clinical translational potential of miRNAs in controlling the expression of immune checkpoints, we identified the association between the plasma levels of soluble PD-1/PD-L1 and expression of some lymphocyte miRNAs. These findings could help the development of novel dynamic predictive biomarkers urgently needed to predict the potential response to immunotherapy and to guide clinical decision-making in RCC patients.
Lingua originaleEnglish
pagine (da-a)1-17
Numero di pagine17
RivistaCancers
Volume12
Stato di pubblicazionePublished - 2020

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

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