| Literature DB >> 32185135 |
Victor C Kok1,2.
Abstract
Starting in 2014, large phase III clinical trials began to disclose the study results of using programmed death (PD)-1 immune checkpoint inhibitors (ICIs) (pembrolizumab, nivolumab) and PD-ligand (L)1 (atezolizumab, durvalumab, avelumab) ICIs immunotherapy in patients with advanced head and neck squamous cell carcinoma (HNSCC). In the recurrent and metastatic (R/M), cisplatin-refractory setting, nivolumab achieved a 2.2-fold increase of the median 1-year overall survival as compared with investigators' choice of salvage chemotherapy (36.0 vs. 16.6%). A paradigm shift to the winning regimen, pembrolizumab combined with platinum and infusional fluorouracil, has outperformed the past gold standard of cetuximab-based platinum and fluorouracil combination in terms of overall survival (median, 13.6 vs. 10.1 mo) when administered as the first-line treatment for R/M HNSCC. Nevertheless, many patients still did not respond to the PD-1/PD-L1 checkpoint inhibitor treatment, indicating innate, adapted, or quickly acquired resistance to the immunotherapy. The mechanisms of resistance to ICIs targeting the PD-1/PD-L1 signaling pathway in the context of HNSCC are the focus of this review. The past 5 years have seen improved understanding of the mechanisms underlying checkpoint inhibition resistance in tumor cells, such as: tumor cell adaption with malfunction of the antigen-presenting machinery via class I human leukocyte antigen (HLA), reintroduction of cyclin D-cyclin-dependent kinase (CDK) 4 complex to cell cycles, enrichment of CD44+ cancer stem-like cells, or development of inactivating mutation in IKZF1 gene; impairment of T-cell functions and proliferation through mutations in the interferon-γ-regulating genes, suppression of the stimulator of interferon genes (STING) pathway, or resulted from constitutional nutritional iron deficiency state; metabolic reprogramming by cancer cells with changes in metabolites such as GTP cyclohydrolase 1, tetrahydrobiopterin, kynurenine, indoleamine 2,3-dioxygenase, and arginase 1; defective dendritic cells, CD-69 sufficient state; and the upregulation or activation of the alternative immune checkpoints, including lymphocyte activation gene-3 (LAG3), T-cell immunoglobulin and ITIM domain (TIGIT)/CD155 pathway, T-cell immunoglobulin mucin-3 (TIM-3), and V domain-containing Ig suppressor of T-cell activation (VISTA). Several potential biomarkers or biosignatures, which could predict the response or resistance to the PD-1/PD-L1 checkpoint immunotherapy, are also discussed.Entities:
Keywords: HNSCC; PD-1/PD-L1 signaling pathway; adapted resistance; cancer immunotherapy; head and neck cancer; immune checkpoint blockade; immune evasion; innate resistance
Year: 2020 PMID: 32185135 PMCID: PMC7058818 DOI: 10.3389/fonc.2020.00268
Source DB: PubMed Journal: Front Oncol ISSN: 2234-943X Impact factor: 6.244
Summary of data demonstrating the evolving new paradigms of systemic treatment for R/M HNSCC over 12 years.
| No. of patients | |||
| Overall Response Rate (95% CI) | 20% (15–25%) | 36% (29–42%) | 36.4% (not given) |
| Progression-Free Survival (mo.) | 3.3 (2.9–4.3) | 5.6 (5.0–6.0) | HR = 0.84 (95% CI, 0.69–1.02) |
| Overall Survival in mo. (95% CI) | 7.4 (6.4–8.3) | 10.1 (8.6–11.2) | 13.6 (not given) |
| Hazard ratio for OS (95% CI) | 0.80 (0.64–0.99) | ||
| 0.65 (0.53–0.80) | |||
Results shown here represent the subgroup of patients whose Combined Positive Score (CPS) for PD-L1 was ≥1. The exact figure for progression-free survival was not given in the Abstract.
Summary of clinical trial results of PD-1 or PD-L1 blockade in R/M HNSCC and NPC showing overall response rate (ORR), duration of response (DoR), progression-free survival (PFS), and overall survival (OS).
| Chow/2016/( | Phase | Pembrolizumab at a fixed dose, 200 mg Q3W | Irrespective of biomarker status | 57% failed two or more lines of chemo | 6-mo. PFS = 23%; |
| Bauml/2017/( | Phase | Pembrolizumab | 82% PD-L1 positive (CPS ≥ 1%) | 75% failed platinum and cetuximab or more | ORR = 16% (95% CI, 11% to 23%). |
| Hsu/2017/( | Phase | Pembrolizumab | Dako 22C3 positive ≥ 1% | 70.4% failed three or more lines | ORR = 25.9% (95% CI, 11.1 to 46.3) |
| Cohen/2019/( | Phase | Pembrolizumab at a fixed-dose, 200 mg Q3W | PD-L1 tumor proportion score (≥ 50% vs. < 50%) | Failed platinum-containing chemo | ORR = 14·6% (95% CI, 10.4–19.6); |
| Rischin/2019/( | Phase | Pembrolizumab vs. pembrolizumab + PF vs. cetuximab + PF | CPS for PD-L1 protein expression. | First-line for R/M HNSCC | In the CPS ≥ 1 group, ORR = 36.4% and median OS = 13.6 mo. (in pembrolizumab + PF) vs. ORR, 35.7%; OS, 10.4 mo. (in cetuximab + PF); HR = 0.65, 95% CI, 0.53–0.80). |
| Ferris/2016/( | Phase | Nivolumab 3 mg/kg Q2W | Dako positive ≥ 1%, ≥ 5%, vs. ≥ 10%. | Failed within 6 mo. of platinum therapy | ORR = 13.3% (9.3–18.3); OS = 7.7 mo. (5.7–8.8). 24-mo. OS = 16.9%. |
| Colevas/2018/( | Phase | Atezolizumab | Responses observed irrespective of HPV or PD-L1 status. | Heavily pretreated | ORR = 22% (95% CI, 9–40%); PFS = 2.6 mo. (0.5–48.4 mo.); |
| Segal/2019/( | Phase | Durvalumab 10 mg/kg Q2W for 12 mo | 32.3% had tumor cell PD-L1 expression ≥ 25% | Failed median of 2 prior systemic treatments (range, 1-13) | ORR = 6.5% (15.0% for PD-L1 ≥ 25%, 2.6% for < 25%); TTP = 2.7 months (range, 1.2-5.5); PFS = 1.4 mo; OS = 8.4 mo. |
| Siu/2018/( | Phase | Durvalumab (10 mg/kg Q2W) monotherapy | PD-L1–low/negative | Failed 1 platinum-containing regimen | ORR = 9.2% (3.46-19.02) |
| Siu/2018/( | Phase | Durvalumab + tremelimumab (anti-CTLA-4) | PD-L1–low/negative | Failed 1 platinum-containing regimen | ORR = 7.8% (3.78-13.79%) |
| Bahig/2019/( | Phase | Durvalumab (1500 mg Q4W) + tremelimumab (75 mg Q4W × 4 doses) + SBRT to metastases at cycles 2 and 3 of immunotherapy | Biomarker-unselected | Patients with ≥ 2 extracranial metastatic lesions. | Ongoing study |
| Elbers/2019( | Phase | Cetuximab-radiotherapy + avelumab (concurrent 10 mg/kg Q2W + 4 months maintenance) | None | Unfit for cisplatin but with an indication for concurrent bioradiotherapy | At 12 (median, 95% CI, 8–26) months follow-up, recurrence occurred in 4/8 patients (50%). |
| Merlano/2018/( | Phase | Avelumab 10 mg/kg Q2W + Cyclophosphamide 50 mg daily + 8 Gy radiotherapy day 8. | None | Failed at least therapy with platinum, fluorouracil, and cetuximab | Ongoing study. |
EudraCT, European Union Drug Regulating Authorities Clinical Trials; NPC, nasopharyngeal carcinoma; SBRT, stereotactic body radiotherapy; CPS, Combined Positive Score.
Figure 1This schematic diagram highlights the immunosuppressive tumor microenvironment (TME) in which a variety of immune cells are polarized to possess pro-tumoral features, stimulated cancer-associated fibroblasts, which release transforming growth factor-β, and even angiogenesis contribute to the immunosuppressive state. Additionally, several molecules, such as kynurenine, adenosine, indoleamine 2,3-dioxygenase, arginase 1, interleukin (IL)-8, and IL-10, were identified to contribute to a pro-tumoral immunosuppressive TME or at extreme, an immune-desert. The figure was created with BioRender.com and was exported under a paid subscription.
Mechanisms of immune escape that are implicated in HNSCC.
| Antigen presenting machinery (APM) via class I HLA | No data | Activated CD8+ immunologic pressure could induce transcriptional loss of HLA class one loci; deleterious alterations in | ( |
| Downregulation of the transporter associated with antigen processing (TAP)-1/2 heterodimer | APM component downregulated by the IFN-γ-phosphorylated STAT1-mediated signaling pathway; results in escaping recognition by tumor antigen-specific cytotoxic T lymphocytes. | ( | |
| JAK mutation | Both | Leads to loss of sensitivity to IFN-γ signals. | ( |
| Cyclin D–CDK4 kinase re-introduction | No data | Destabilizes PD-L1 and controls the PD-L1 abundance in tumor cells. | ( |
| Enrichment of CD44+ cancer stem-like cells | No data | Activates immunosuppressive network through cytokine release. | ( |
| IKZF1-inactivating mutations | No data | Genomic alterations of the master regulator IKZF1 correlates with low immune recruitment. | ( |
| Nutritional iron deficiency state | Both | Affects T-cell proliferation | ( |
| Mutations in interferon-γ-regulating genes | Both | Exhausted “Immune Class” enriched with M2 macrophages, WNT/TGF-β activation | ( |
| Suppression of stimulator of interferon genes (STING) pathway | HPV+ | Dampens the antitumor immune response. | ( |
| Inhibition of STAT1 phosphorylation | Both | Enhanced T-cell exhaustion and accumulation of MDSCs | ( |
| Defective dendritic cells (DC) | Both | Defective cytokine- and STAT-mediated regulation of DC. | ( |
| CD69-sufficient state | Both | Leads to effector T-cell exhaustion. | ( |
| Genetic inactivation of GTP cyclohydrolase 1 (GCP1) | No data | Drastically impairs T-cell maturation. | ( |
| Metabolite tetrahydrobiopterin (BH4) inhibited by kynurenine | No data | Will impair T cell function. | ( |
| Indoleamine 2,3-dioxygenase-1 (IDO1); Tryptophan metabolite, kynurenine (Kyn) level | Both | IDO1 inhibits T cell proliferation, restricts tumor immune infiltration, and retards antitumor immune responses. Kyn released from ϕ, and myeloid cells activate T-reg cells. | ( |
| Cancer-associated fibroblasts secrete TGF-β | Both | Results in restraining CD8+ T effector cells infiltrating into microenvironment. | ( |
| Arginase 1 expression on microenvironment myeloid cells | Both | Arg1 leads to L-arginine depletion depriving T cells and NK cells of essential nutrients required for proliferation. | ( |
| CD38-upregulation | Both | CD38 inhibits CD8+ T-cell function via adenosine receptor signaling. | ( |
| Ectonucleotidases CD39/CD73 axis | Both | CD39 is considered a tumor-specific dysfunction marker. Tregs use the axis to diminish anti-cancer killing. | ( |
| Polymorphonuclear myeloid-derived suppressor cells (PMN-MDSC) activation | Both | Through the nitric oxide pathway, PMN-MDSCs impair proliferation and expression molecules in activated T cells. | ( |
| Nucleotide-binding domain leucine-rich repeat and pyrin domain containing receptor 3 (NLRP3) inflammasome activation | Both | Leads to downstream interleukin (IL)-1β release. NLRP3 inflammasome/IL-1β axis increases MDSCs, Tregs and TAMs creating an immunosuppressive microenvironment. | ( |
| Lymphocyte activation gene-3 (LAG3) (=CD223) upregulation | More in HPV+ | Induces a state of functional exhaustion in effector T-cells. | ( |
| T-cell immunoglobulin and ITIM domain (TIGIT)/CD155 pathway activation | Both | Augments TIGIT+ T-regs, a unique T-reg subset, leading to active suppression of anti-tumor immune response and T-cell exhaustion. | ( |
| T-cell immunoglobulin mucin-3 (TIM-3) upregulation | Both | TIM-3 is considered a tumor-specific dysfunction marker. It dampens effector T-cell functions in the microenvironment. | ( |
| V domain-containing Ig suppressor of T-cell activation (VISTA) | Both | Leads to T-cell exhaustion and T-reg recruitment in the microenvironment. | ( |
Investigated mechanisms of acquired immune escape from PD-1/PD-L1 checkpoint blockade relevant to head and neck cancer.
Response prediction to anti-PD-1 immunotherapy in HNSCC.
| Combined Positive Score (CPS) for PD-L1 protein Expression | Immunohistochemistry on formalin-fixed paraffin-embedded tissue samples | CPS = number of PD-L1+ tumor cells, lymphocytes, and macrophages, divided by the total number of viable tumor cells, and multiplying by 100. In various trials, CPS ≥ 1 predicts response. | ( |
| MMR-deficient | Quantification of genomic MSI level (MSI intensity) | Higher insertion-deletion (Indel) load predicts response. | ( |
| Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC)-driven mutations | APOBEC enrichment scores. | Upregulated as an innate immune response particularly in HPV+ tumors. APOBEC3 mutation leads to driver mutation in | ( |
| Molecular exhausted immune class | Gene expression pattern analyzed by non-negative matrix factorization algorithm | Portends a worse prognosis than active immune class in overall survival. | ( |
| Molecular active immune class | Better prognosis (overall survival) than exhausted class. May predict immune responses. | ( | |
| Interferon-γ signature (6-genes) | NanoString nCounter mRNA | Low signature score did not respond to pembrolizumab. | ( |
| Expanded immune signature (18-genes) | NanoString nCounter mRNA | Low signature score did not respond to pembrolizumab. | ( |
| Somatic frameshift events in tumor suppressor genes | Targeted massively parallel sequencing | More frequently seen in HPV- responders. | ( |
| Total mutational burden (TMB) | Targeted massively parallel sequencing | Predicts response in HPV- HNSCC. | ( |
| Microenvironment infiltrating arginase 1 (Arg1)+/CD68+ macrophage-mediated immune evasion | Enzyme-Linked Immunosorbent Assay (ELISA) | Plasma Arg1 level (ng/mL) to predict immune evasion (cutoff to be determined) | ( |