Dendritic cell effector mechanisms and tumor immune microenvironment infiltration define TLR8 modulation and PD-1 blockade.

The potent immunostimulatory effects of toll-like receptor 8 (TLR8) agonism in combination with PD-1 blockade have resulted in various preclinical investigations, yet the mechanism of action in humans remains unknown. To decipher the combinatory mode of action of TLR8 agonism and PD-1 blockade, we employed a unique, open-label, phase 1b pre-operative window of opportunity clinical trial (NCT03906526) in head and neck squamous cell carcinoma (HNSCC) patients. Matched pre- and post-treatment tumor biopsies from the same lesion were obtained. We used single-cell RNA sequencing and custom multiplex staining to leverage the unique advantage of same-lesion longitudinal sampling. Patients receiving dual TLR8 agonism and anti-PD-1 blockade exhibited marked upregulation of innate immune effector genes and cytokines, highlighted by increased CLEC9A+ dendritic cell and CLEC7A/SYK expression. This was revealed via comparison with a previous cohort from an anti-PD-1 blockade monotherapy single-cell RNA sequencing study. Furthermore, in dual therapy patients, post-treatment mature dendritic cells increased in adjacency to CD8+ T-cells. Increased tumoral cytotoxic T-lymphocyte densities and expanded CXCL13+CD8+ T-cell populations were observed in responders, with increased tertiary lymphoid structures (TLSs) across all three patients. This study provides key insights into the mode of action of TLR8 agonism and anti-PD-1 blockade immune targeting in HNSCC patients.

Immune Cell Densities Predict Response to Immune Checkpoint-Blockade in Head and Neck Cancer.

Immune checkpoint blockade (ICB) is the standard of care for recurrent/metastatic head and neck squamous cell carcinoma (HNSCC), yet efficacy remains low. The current approach for predicting the likelihood of response to ICB is a single proportional biomarker (PD-L1) expressed in immune and tumor cells (Combined Positive Score, CPS) without differentiation by cell type, potentially explaining its limited predictive value. Tertiary Lymphoid Structures (TLS) have shown a stronger association with ICB response than PD-L1. However, their exact composition, size, and spatial biology in HNSCC remain understudied. A detailed understanding of TLS is required for future use as a clinically applicable predictive biomarker. Methods: Pre-ICB tumor tissue sections were obtained from 9 responders (complete response, partial response, or stable disease) and 11 non-responders (progressive disease) classified via RECISTv1.1. A custom multi-immunofluorescence (mIF) staining assay was designed, optimized, and applied to characterize tumor cells (pan-cytokeratin), T cells (CD4, CD8), B cells (CD19, CD20), myeloid cells (CD16, CD56, CD163), dendritic cells (LAMP3), fibroblasts (α Smooth Muscle Actin), proliferative status (Ki67) and immunoregulatory molecules (PD1). Spatial metrics were compared among groups. Serial tissue sections were scored for TLS in both H&E and mIF slides. A machine learning model was employed to measure the effect of these metrics on achieving a response to ICB (SD, PR, or CR). Results: A higher density of B lymphocytes (CD20+) was found in responders compared to non-responders to ICB (p=0.022). A positive correlation was observed between mIF and pathologist identification of TLS (R 2 = 0.66, p-value= <0.0001). TLS trended toward being more prevalent in responders to ICB (p=0.0906). The presence of TLS within 100 µm of the tumor was associated with improved overall (p=0.04) and progression-free survival (p=0.03). A multivariate machine learning model identified TLS density as a leading predictor of response to ICB with 80% accuracy. Conclusion: Immune cell densities and TLS spatial location within the tumor microenvironment play a critical role in the immune response to HNSCC and may potentially outperform CPS as a predictor of ICB response.

Immunotherapy time of infusion impacts survival in head and neck cancer: A propensity score matched analysis.

The adaptive immune response is physiologically regulated by the circadian rhythm. Data in lung and melanoma malignancies suggests immunotherapy infusions earlier in the day may be associated with improved response; however, the optimal time of administration for patients with head and neck squamous cell carcinoma (HNSCC) is not known. We aimed to evaluate the association of immunotherapy infusion time with overall survival (OS) and progression free survival (PFS) in patients with HNSCC in an Institutional Review Board-approved, retrospective cohort study. 113 patients met study inclusion criteria and 98 patients were included in a propensity score-matched cohort. In the full unmatched cohort (N = 113), each additional 20 % of infusions received after 1500 h conferred an OS hazard ratio (HR) of 1.35 (95 % C.I.1.2-1.6; p-value = 0.0003) and a PFS HR of 1.34 (95 % C.I.1.2-1.6; p-value < 0.0001). A propensity score-matched analysis of patients who did or did not receive ≥20 % of infusions after 1500 h showed that those who were administered ≥20 % of infusions after 1500 h trended towards a shorter OS (HR = 1.35; p-value = 0.26) and a shorter PFS (HR = 1.57, 95 % C.I. 1.02-2.42, p-value = 0.04). Each additional 20 % of infusions received after 1500 h remained robust in the matched cohort multivariable analysis and was associated with shorter OS (adjusted HR = 1.4 (95 % C.I.1.2-1.8), p-value < 0.001). Patients with advanced HNSCC who received more of their infusions in the afternoon were associated with shorter OS and PFS and scheduling immunotherapy infusions earlier in the day may be warranted.

Comparing the Diagnostic Performance of Quantitative PCR, Digital Droplet PCR, and Next-Generation Sequencing Liquid Biopsies for Human Papillomavirus-Associated Cancers.

Human papillomavirus (HPV)-associated cancers, including oropharyngeal squamous cell carcinoma (HPV + OPSCC), cervical cancer, and squamous cell carcinoma of the anus (HPV + SCCA), release circulating tumor HPV DNA (ctHPVDNA) into the blood. The diagnostic performance of ctHPVDNA detection depends on the approaches used and the individual assay metrics. A comparison of these approaches has not been systematically performed to inform expected performance, which in turn affects clinical interpretation. A meta-analysis was performed using Ovid MEDLINE, Embase, and Web of Science Core Collection databases to assess the diagnostic accuracy of ctHPVDNA detection across cancer anatomic sites, detection platforms, and blood components. The population included patients with HPV + OPSCC, HPV-associated cervical cancer, and HPV + SCCA with pretreatment samples analyzed by quantitative PCR (qPCR), digital droplet PCR (ddPCR), or next-generation sequencing (NGS). Thirty-six studies involving 2986 patients met the inclusion criteria. The sensitivity, specificity, and quality of each study were assessed and pooled for each analysis. The sensitivity of ctHPVDNA detection was greatest with NGS, followed by ddPCR and then qPCR when pooling all studies, whereas specificity was similar (sensitivity: ddPCR > qPCR, P < 0.001; NGS > ddPCR, P = 0.014). ctHPVDNA from OPSCC was more easily detected compared with cervical cancer and SCCA, overall (P = 0.044). In conclusion, detection platform, anatomic site of the cancer, and blood component used affects ctHPVDNA detection and must be considered when interpreting results. Plasma NGS-based testing may be the most sensitive approach for ctHPVDNA overall.