The non-small cell lung cancer immune landscape: emerging complexity, prognostic relevance and prospective significance in the context of immunotherapy
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Immunotherapy of non-small cell lung cancer (NSCLC), by immune checkpoint inhibitors, has profoundly improved the clinical management of advanced disease. However, only a fraction of patients respond and no effective predictive factors have been defined. Here, we discuss the prospects for identification of such predictors of response to immunotherapy, by fostering an in-depth analysis of the immune landscape of NSCLC. The emerging picture, from several recent studies, is that the immune contexture of NSCLC lesions is a complex and heterogeneous feature, as documented by analysis for frequency, phenotype and spatial distribution of innate and adaptive immune cells, and by characterization of functional status of inhibitory receptor+ T cells. The complexity of the immune landscape of NSCLC stems from the interaction of several factors, including tumor histology, molecular subtype, main oncogenic drivers, nonsynonymous mutational load, tumor aneuploidy, clonal heterogeneity and tumor evolution, as well as the process of epithelial–mesenchymal transition. All these factors contribute to shape NSCLC immune profiles that have clear prognostic significance. An integrated analysis of the immune and molecular profile of the neoplastic lesions may allow to define the potential predictive role of the immune landscape for response to immunotherapy.
KeywordsNon-small cell lung cancer Immune landscape Immune checkpoint blockade Immunotherapy NIBIT 2016
Early effector cell
Epithelial mesenchymal transition
Immune checkpoint blockade
Myeloid-derived suppressor cell
Non-neoplastic lung tissue
Non-small cell lung cancer
Squamous cell carcinoma
Somatic copy number alteration
T cell receptor
T effector memory
T effector memory RA
Exhausted T cell
Type 1 T Helper cell
Type 2 T Helper cell
T Helper 17 cell
Tumor-induced bronchus-associated lymphoid tissues
Tertiary lymphoid structure
Regulatory T cell
Terminal respiratory unit
t-distributed stochastic neighbor embedding
The authors gratefully acknowledge the excellent technical contribution of Mrs. Claudia Vegetti, Alessandra Molla, Ilaria Bersani and Paola Baldassari to the work mentioned in this paper.
AA designed the structure of the review and took the lead in writing the paper. ET and GG contributed to select and review the mentioned literature and to the final revision of the text. RM contributed to design and writing of the paper and to selecting and reviewing all of the mentioned literature.
The work mentioned in this paper was supported by Grant #17431 from Associazione Italiana per la Ricerca sul Cancro (A. I. R. C.) to Andrea Anichini. Elena Tassi was supported by a fellowship from Fondazione Beretta-Berlucchi. Giulia Grazia was supported by a fellowship from Fondazione Italiana per la Ricerca sul Cancro (FIRC).
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Conflict of interest
The authors declare that they have no conflicts of interest.
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