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Cancer Immunology, Immunotherapy

, Volume 67, Issue 6, pp 1011–1022 | Cite as

The non-small cell lung cancer immune landscape: emerging complexity, prognostic relevance and prospective significance in the context of immunotherapy

  • Andrea AnichiniEmail author
  • Elena Tassi
  • Giulia Grazia
  • Roberta Mortarini
Focussed Research Review

Abstract

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.

Keywords

Non-small cell lung cancer Immune landscape Immune checkpoint blockade Immunotherapy NIBIT 2016 

Abbreviations

ADC

Adenocarcinoma

DFS

Disease-free survival

EEC

Early effector cell

eMDSC

Early MDSC

EMT

Epithelial mesenchymal transition

GC

Germinal center

ICB

Immune checkpoint blockade

IR

Inhibitory receptor

MDSC

Myeloid-derived suppressor cell

M-MDSC

Monocytic MDSC

nLung

Non-neoplastic lung tissue

NSCLC

Non-small cell lung cancer

OS

Overall survival

PFS

Progression-free survival

PI

Proximal inflammatory

PMN-MDSC

Polymorphonuclear MDSC

PP

Proximal proliferative

SCC

Squamous cell carcinoma

SCNA

Somatic copy number alteration

TCR

T cell receptor

TEM

T effector memory

TEMRA

T effector memory RA

Tex

Exhausted T cell

TH1

Type 1 T Helper cell

TH2

Type 2 T Helper cell

TH17

T Helper 17 cell

Ti-BALT

Tumor-induced bronchus-associated lymphoid tissues

TIL

Tumor-infiltrating lymphocyte

TLS

Tertiary lymphoid structure

Treg

Regulatory T cell

TRU

Terminal respiratory unit

t-SNE

t-distributed stochastic neighbor embedding

Notes

Acknowledgements

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.

Author contributions

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.

Funding

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).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Research, Human Tumors Immunobiology UnitFondazione IRCCS Istituto Nazionale dei TumoriMilanItaly

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