Overcoming immunotherapy resistance in non-small cell lung cancer (NSCLC) - novel approaches and future outlook

Abstract

Immunotherapy (IO) has revolutionized the therapy landscape of non-small cell lung cancer (NSCLC), significantly prolonging the overall survival (OS) of advanced stage patients. Over the recent years IO therapy has been broadly integrated into the first-line setting of non-oncogene driven NSCLC, either in combination with chemotherapy, or in selected patients with PD-L1^high expression as monotherapy. Still, a significant proportion of patients suffer from disease progression. A better understanding of resistance mechanisms depicts a central goal to avoid or overcome IO resistance and to improve patient outcome.We here review major cellular and molecular pathways within the tumor microenvironment (TME) that may impact the evolution of IO resistance. We summarize upcoming treatment options after IO resistance including novel IO targets (e.g. RIG-I, STING) as well as interesting combinational approaches such as IO combined with anti-angiogenic agents or metabolic targets (e.g. IDO-1, adenosine signaling, arginase). By discussing the fundamental mode of action of IO within the TME, we aim to understand and manage IO resistance and to seed new ideas for effective therapeutic IO concepts.

Keywords: Immunotherapy resistance; NSCLC; Targeted therapy; Tumor microenvironment heterogeneity.

Fig. 1

Overview of the cellular TME composition and major molecular pathways associated with IO sensitivity (left) and resistance (right). IO sensitivity is depicted by an immunogenic TME, comprising the activation of effector immune cells (e.g. tumor infiltrating lymphocytes (TIL), dendritic cells (CD) and natural killer cells (NK)). Naïve T cells undergo activation and priming in close association to B cells within tertiary lymphoid structures (TLS). T effector cells transmigrate to the stromal TME compartment via high endothelial venules (HEV), tightly regulated by immunomodulatory tumor endothelial cells (TEC; not illustrated) in the HEV endothelium. Cancer cell intrinsic molecular pathways that enhance TME immunogenicity involve interferon type I (IFN I) expression, which is, amongst other stressors, induced by cytosolic RIG-I or by an activated STING pathway. IO sensitivity is enhanced in a TME with high PD-L1 expression by cancer and immune cells. High neo-antigen expression by cancer cells as result of high tumor mutational burden (TMB), e.g. induced by PARP inhibition, enhances TME immunogenicity and IO sensitivity. IO resistance is marked by an immunosuppressive TME and includes, on a cellular basis, infiltration of T regulatory cells (Treg) and myeloid derived suppressor cells (MDSC) as well as M2 macrophages (not shown). CD73 and, thus, adenosine expression by cancer cells or fibroblasts leads to inhibition of TIL and promotion of Treg; CD73 upregulation associates with cancer immune evasion. Also, up-regulation of alternative immune checkpoints e.g. LAG-3 and TIM-1 by immune cells enhances IO resistance. Cancer associated fibroblasts (CAF) depict both immunosuppressive and immunostimulatory functions, e.g. via chemokine release. Upregulation of the chemokine receptor CCR-4 is associated with IO resistance. Vascular endothelial growth factor (VEGF) gets ubiquitously expressed in the TME (not illustrated, see Fig. 2). It has immunosuppressive functions by inhibiting effector immune cells (e.g. TIL, NK, DC), upregulating inhibitory immune checkpoints (e.g. PD-L1) and by promoting Treg and MDSC. Tumor growth promoting neo-angiogenesis (not illustrated) is driven by hypoxia and, thus, VEGF expression

Fig. 2

The gene expression heterogeneity of the NSCLC TME, illustrated by gene expression in stromal and cancer cells. 52.698 single cells from 4 non-malignant and 15 tumor samples of five patients were analyzed. (a-f) tSNE plots of the 52.698 cells, with (a) clusters color-coded according to the associated class of cell types, or with (b-f) cells colored according to the expression of the indicated marker gene, illustrating the heterogeneity of gene expression by the various cell types within the TME. Gene expression is shown ranging from grey to red (low to high). (e) CD274 is the gene alias for PD-L1. (f) NTE5 is the gene alias for CD73. (g) Expression levels of selected genes (gene alias in brackets), involved in immunomodulation in tumors shown separately for each cell type based on single cell RNA sequencing. Expression levels in cancer cells are shown separately for each patient, while the subtypes of T cells, innate immune cells, endothelial cells and fibroblasts represent pooled patient data. Data are derived from reference [2]