Purpose: We investigated whether in human head and neck squamous cell carcinoma (HNSCC) high levels of expression of stress keratin 17 (K17) are associated with poor survival and resistance to immunotherapy. Experimental Design: We investigated the role of K17 in regulating both the tumor microenvironment and immune responsiveness of HNSCC using a syngeneic mouse HNSCC model, MOC2. MOC2 gives rise to immunologically cold tumors that are resistant to immune-checkpoint blockade (ICB). We engineered multiple, independent K17 knockout (KO) MOC2 cell lines and monitored their growth and response to ICB. We also measured K17 expression in human HNSCC of patients undergoing ICB. Results: MOC2 tumors were found to express K17 at high levels. When knocked out for K17 (K17KO MOC2), these cells formed tumors that grew slowly or spontaneously regressed and had a high CD8+ T-cell infiltrate in immunocompetent syngeneic C57BL/6 mice compared with parental MOC2 tumors. This phenotype was reversed when we depleted mice for T cells. Whereas parental MOC2 tumors were resistant to ICB treatment, K17KO MOC2 tumors that did not spontaneously regress were eliminated upon ICB treatment. In a cohort of patients with HNSCC receiving pembrolizumab, high K17 expression correlated with poor response. Single-cell RNA-sequencing analysis revealed broad differences in the immune landscape of K17KO MOC2 tumors compared with parental MOC2 tumors, including differences in multiple lymphoid and myeloid cell types. Conclusions: We demonstrate that K17 expression in HNSCC contributes to immune evasion and resistance to ICB treatment by broadly altering immune landscapes of tumors.

Low response rates in immune check-point blockade (ICB)-treated head and neck squamous cell carcinoma (HNSCC) drive a critical need for robust, clinically validated predictive biomarkers. Our group previously showed that stress keratin 17 (CK17) suppresses macrophage-mediated CXCL9/CXCL10 chemokine signaling involved in attracting activated CD8+ T cells into tumors, correlating with decreased response rate to pembrolizumab-based therapy in a pilot cohort of ICB-treated HNSCC (n = 26). Here, we performed an expanded analysis of the predictive value of CK17 in ICB-treated HNSCC according to the REMARK criteria and investigated the gene expression profiles associated with high CK17 expression. Pretreatment samples from pembrolizumab-treated HNSCC patients were stained via immunohistochemistry using a CK17 monoclonal antibody (n = 48) and subjected to spatial transcriptomic profiling (n = 8). Our findings were validated in an independent retrospective cohort (n = 22). CK17 RNA expression in pembrolizumab-treated patients with various cancer types was investigated for predictive significance. Of the 48 patients (60% male, median age of 61.5 years), 21 (44%) were CK17 high, and 27 (56%) were CK17 low. A total of 17 patients (35%, 77% CK17 low) had disease control, while 31 patients (65%, 45% CK17 low) had progressive disease. High CK17 expression was associated with a lack of disease control (p = 0.037), shorter time to treatment failure (p = 0.025), and progression-free survival (PFS, p = 0.004), but not overall survival (OS, p = 0.06). A high CK17 expression was associated with lack of disease control in an independent validation cohort (p = 0.011). PD-L1 expression did not correlate with CK17 expression or clinical outcome. CK17 RNA expression was predictive of PFS and OS in 552 pembrolizumab-treated cancer patients. Our findings indicate that high CK17 expression may predict resistance to ICB in HNSCC patients and beyond.

Background Approximately 15-20% of head and neck cancer squamous cell carcinoma (HNSCC) patients respond favorably to immune checkpoint blockade (ICB). Previous single-cell RNA-Seq (scRNA-Seq) studies identified immune features, including macrophage subset ratios and T-cell subtypes, in HNSCC ICB response. However, the spatial features of HNSCC-infiltrated immune cells in response to ICB treatment need to be better characterized. Methods Here, we perform a systematic evaluation of cell interactions between immune cell types within the tumor microenvironment using spatial omics data using complementary techniques from both 10X Visium spot-based spatial transcriptomics and Nanostring CosMx single-cell spatial omics with RNA gene panel including 435 ligands and receptors. In this study, we used integrated bioinformatics analyses to identify cellular neighborhoods of co-localizing cell types in single-cell spatial transcriptomics and proteomics data. In addition, we used both publicly available scRNA-Seq and in-house spatial RNA-Seq data to identify spatially constrained Ligand-Receptor interactions in Responder patients. Results With 522,399 single cells profiled with both RNA and protein from 26 patients, in addition to spot-resolved spatial RNA-Seq from 8 patients treated with ICB together with bioinformatics analysis of publicly available single-cell and bulk RNA-Seq, we have identified a spatial and cell-type specific context-dependency of myeloid and T cell interaction difference between Responders and Non-Responders. We defined further cellular neighborhood and the sources of chemokine CXCL9/10-CXCR3 interactions in Responders, emerging targets in ICB, as well as CXCL16-CXCR6, CCL4/5-CCR5, and other underappreciated and potential markers and targets for ICB response in HNSCC. In addition, we have contributed a rich data resource of cell-cell Ligand Receptor interactions for the immunotherapy and HNSCC research community. Discussion Our work provides a comprehensive single-cell and spatial atlas of immune cell interactions that correlate with response to ICB in HNSCC. We showcase how integrating multiple technologies and bioinformatics approaches can provide new insights into potential immune-based biomarkers of ICB response. Our results suggested refining future studies using preclinical animal models in a more context-specific manner to elucidate potential underlying mechanisms that lead to improved ICB responses. What is already known on this topic Most cancer patients still do not experience clinical benefits from immune checkpoint blockade (ICB), necessitating the development of response biomarkers and new immunotherapeutic targets. What this study adds Here, we use integrated high-dimensional omics and bioinformatics approaches to identify immune cell-cell interaction markers associated with ICB response in patients with Head and neck squamous cell carcinoma. How this study might affect research, practice or policy We identified spatial and cell-type specificity of Ligand-Receptor interactions between myeloid and T cells in ICB Responder patients that may help inform further mechanistic studies and biomarker development.

Purpose: We conduct a systematic evaluation of cell–cell interactions between tumor-infiltrating immune cells in patients with head and neck squamous cell carcinoma (HNSCC) who have been treated with immune checkpoint blockade (ICB) using spatial and single-cell omics data. Experimental Design: We employed complementary techniques from both Visium spot–based spatial transcriptomics and CosMx Spatial Molecular Imager single-cell spatial omics, utilizing a 64-plex protein panel and a 1,000-gene RNA panel, which includes 435 ligands and receptors. We conducted integrated bioinformatics analyses to identify cellular neighborhoods of colocalizing cell types and ligand–receptor interactions across different single-cell and spatial data modalities. Results: With 522,399 single cells profiled for both RNA and protein from 23 patients, along with spot-resolved spatial RNA sequencing (RNA-seq) data from eight patients treated with ICB, and through bioinformatics analysis of publicly available single-cell and bulk RNA-seq, we identified a spatial and cell type–specific context dependency in the differences in myeloid and T-cell interactions between responder and nonresponder samples. We further defined the cellular neighborhood and sources of chemokine CXCL9/10–CXCR3 interactions, emphasizing the specificity of this marker in responder samples, an emerging target in ICB, as well as other underappreciated markers and targets for ICB response in HNSCC, such as CXCL16–CXCR6 and CCL4/5–CCR5. Conclusions: We have provided a valuable resource for analyzing spatial and cell–cell ligand–receptor interactions, including the cellular and spatial contexts of ICB response markers. Our data suggest that future mechanistic studies should consider this context specificity when evaluating ICB response biomarkers and targets.

Vaccine strategies aimed at eliciting HIV-specific CD8+ T cells are one major target of interest in HIV functional cure strategies. We hypothesized that CD8+ T cells elicited by therapeutic vaccination during antiretroviral therapy (ART) would be recalled and boosted by treatment with the IL-15 superagonist N-803 after ART discontinuation. We intravenously immunized four SIV+ Mauritian cynomolgus macaques (MCM) receiving ART with vesicular stomatitis virus (VSV), modified vaccinia virus Ankara strain (MVA), and recombinant adenovirus serotype 5 (rAd-5) vectors all expressing SIVmac239 Gag. Immediately after ART cessation, these animals received three doses of N-803. Four control animals received no vaccines or N-803. The vaccine regimen generated a high magnitude of Gag-specific CD8+ T cells that were proliferative and biased toward an effector memory phenotype. We then compared cells elicited by vaccination (Gag-specific) to cells elicited by SIV infection and unaffected by vaccination (Nef-specific). We found that N-803 treatment enhanced both the frequencies of bulk and proliferating antigen-specific CD8+ T cells elicited by vaccination and the antigen-specific CD8+ T cells elicited by SIV infection. In sum, we demonstrate that a therapeutic heterologous prime-boost-boost (HPBB) vaccine can elicit antigen-specific effector memory CD8+ T cells that are boosted by N-803.

Supplementary Figure 1. CONSORT-like diagram of patient cohort used for spatial omics profiling