High Risk-Human Papillomavirus in HNSCC: Present and Future Challenges for Epigenetic Therapies

Comparison of preclinical efficacy of immunotherapies against HPV-induced cancers

INTRODUCTION

Persistent infections with the human papilloma viruses, HPV16 and HPV18, are associated with multiple cancers. Although prophylactic vaccines that induce HPV-neutralizing antibodies are effective against primary infections, they have no effect on HPV-mediated malignancies against which there is no approved immuno-therapy. Active research is ongoing on immunotherapy of these cancers.

AREAS COVERED

In this review, we compared the preclinical efficacy of vaccine platforms used to treat HPV-induced tumors in the standard model of mice grafted with TC-1 cells, which express the HPV16 E6 and E7 oncoproteins. We searched for the key words, 'HPV,' 'vaccine,' 'therapy,' 'E7,' 'tumor,' 'T cells' and 'mice' for the period from 2005 to 2023 in PubMed and found 330 publications. Among them, we selected the most relevant to extract preclinical antitumor results to enable cross-sectional comparison of their efficacy.

EXPERT OPINION SECTION

We compared these studies for HPV antigen design, immunization regimen, immunogenicity, and antitumor effect, considering their drawbacks and advantages. Among all strategies used in murine models, certain adjuvanted proteins and viral vectors showed the strongest antitumor effects, with the use of lentiviral vectors being the only approach to result in complete tumor eradication in 100% of experimental individuals while providing the longest-lasting memory.

Emerging paradigms: unmasking the role of oxidative stress in HPV-induced carcinogenesis

The contribution of the human papillomavirus (HPV) to cancer is significant but not exclusive, as carcinogenesis involves complex mechanisms, notably oxidative stress. Oxidative stress and HPV can independently cause genome instability and DNA damage, contributing to tumorigenesis. Oxidative stress-induced DNA damage, especially double-strand breaks, aids in the integration of HPV into the host genome and promotes the overexpression of two viral proteins, E6 and E7. Lifestyle factors, including diet, smoking, alcohol, and psychological stress, along with genetic and epigenetic modifications, and viral oncoproteins may influence oxidative stress, impacting the progression of HPV-related cancers. This review highlights various mechanisms in oxidative-induced HPV-mediated carcinogenesis, including altered mitochondrial morphology and function leading to elevated ROS levels, modulation of antioxidant enzymes like Superoxide Dismutase (SOD), Glutathione (GSH), and Glutathione Peroxidase (GPx), induction of chronic inflammatory environments, and activation of specific cell signaling pathways like the Phosphoinositide 3-kinase, Protein kinase B, Mammalian target of rapamycin (PI3K/AKT/mTOR) and the Extracellular signal-regulated kinase (ERK) signaling pathway. The study highlights the significance of comprehending and controlling oxidative stress in preventing and treating cancer. We suggested that incorporating dietary antioxidants and targeting cancer cells through mechanisms involving ROS could be potential interventions to mitigate the impact of oxidative stress on HPV-related malignancies.

A prognostic model built on amino acid metabolism patterns in HPV-associated head and neck squamous cell carcinoma

OBJECTIVES

To compare amino acid metabolism patterns between HPV-positive and HPV-negative head and neck squamous cell carcinoma (HNSCC) patients and identify key genes for a prognostic model.

DESIGN

Utilizing the Cancer Genome Atlas dataset, we analyzed amino acid metabolism genes, differentiated genes between HPV statuses, and selected key genes via LASSO regression for the prognostic model. The model's gene expression was verified through immunohistochemistry in clinical samples. Functional enrichment and CIBERSORTx analyses explored biological functions, molecular mechanisms, and immune cell correlations. The model's prognostic capability was assessed using nomograms, calibration, and decision curve analysis.

RESULTS

We identified 1157 key genes associated with amino acid metabolism in HNSCC and HPV status. The prognostic model, featuring genes like IQCN, SLC22A1, SYT12, and TLX3, highlighted functions in development, metabolism, and pathways related to receptors and enzymes. It significantly correlated with immune cell infiltration and outperformed traditional staging in prognosis prediction, despite immunohistochemistry results showing limited clinical identification of HPV-related HNSCC.

CONCLUSIONS

Distinct amino acid metabolism patterns differentiate HPV-positive from negative HNSCC patients, underscoring the prognostic model's utility in predicting outcomes and guiding therapeutic strategies.

Deciphering the immune landscape of head and neck squamous cell carcinoma: A single-cell transcriptomic analysis of regulatory T cell responses to PD-1 blockade therapy

Immunotherapy is changing the Head and Neck Squamous Cell Carcinoma (HNSCC) landscape and improving outcomes for patients with recurrent or metastatic HNSCC. A deeper understanding of the tumor microenvironment (TME) is required in light of the limitations of patients' responses to immunotherapy. Here, we aimed to examine how Nivolumab affects infiltrating Tregs in the HNSCC TME. We used single-cell RNA sequencing data from eight tissues isolated from four HNSCC donors before and after Nivolumab treatment. Interestingly, the study found that Treg counts and suppressive activity increased following Nivolumab therapy. We also discovered that changes in the CD44-SSP1 axis, NKG2C/D-HLA-E axis, and KRAS signaling may have contributed to the increase in Treg numbers. Furthermore, our study suggests that decreasing the activity of the KRAS and Notch signaling pathways, and increasing FOXP3, CTLA-4, LAG-3, and GZMA expression, may be mechanisms that enhance the killing and suppressive capacity of Tregs. Additionally, the result of pseudo-temporal analysis of the HNSCC TME indicated that after Nivolumab therapy, the expression of certain inhibitory immune checkpoints including TIGIT, ENTPD1, and CD276 and LY9, were decreased in Tregs, while LAG-3 showed an increased expression level. The study also found that Tregs had a dense communication network with cluster two, and that certain ligand-receptor pairs, including SPP1/CD44, HLA-E/KLRC2, HLA-E/KLRK1, ANXA1/FPR3, and CXCL9/FCGR2A, had notable changes after the therapy. These changes in gene expression and cell interactions may have implications for the role of Tregs in the TME and in response to Nivolumab therapy.

CellEnBoost: A Boosting-Based Ligand-Receptor Interaction Identification Model for Cell-to-Cell Communication Inference

Cell-to-cell communication (CCC) plays important roles in multicellular organisms. The identification of communication between cancer cells themselves and one between cancer cells and normal cells in tumor microenvironment helps understand cancer genesis, development and metastasis. CCC is usually mediated by Ligand-Receptor Interactions (LRIs). In this manuscript, we developed a Boosting-based LRI identification model (CellEnBoost) for CCC inference. First, potential LRIs are predicted by data collection, feature extraction, dimensional reduction, and classification based on an ensemble of Light gradient boosting machine and AdaBoost combining convolutional neural network. Next, the predicted LRIs and known LRIs are filtered. Third, the filtered LRIs are applied to CCC elucidation by combining CCC strength measurement and single-cell RNA sequencing data. Finally, CCC inference results are visualized using heatmap view, Circos plot view, and network view. The experimental results show that CellEnBoost obtained the best AUCs and AUPRs on the collected four LRI datasets. Case study in human head and neck squamous cell carcinoma (HNSCC) tissues demonstrates that fibroblasts were more likely to communicate with HNSCC cells, which is in accord with the results from iTALK. We anticipate that this work can contribute to the diagnosis and treatment of cancers.

Differentially Expressed Genes, miRNAs and Network Models: A Strategy to Shed Light on Molecular Interactions Driving HNSCC Tumorigenesis

Head and neck squamous cell carcinoma (HNSCC) is among the most common cancer worldwide, accounting for hundreds thousands deaths annually. Unfortunately, most patients are diagnosed in an advanced stage and only a percentage respond favorably to therapies. To help fill this gap, we hereby propose a retrospective in silico study to shed light on gene-miRNA interactions driving the development of HNSCC. Moreover, to identify topological biomarkers as a source for designing new drugs. To achieve this, gene and miRNA profiles from patients and controls are holistically reevaluated using protein-protein interaction (PPI) and bipartite miRNA-target networks. Cytoskeletal remodeling, extracellular matrix (ECM), immune system, proteolysis, and energy metabolism have emerged as major functional modules involved in the pathogenesis of HNSCC. Of note, the landscape of our findings depicts a concerted molecular action in activating genes promoting cell cycle and proliferation, and inactivating those suppressive. In this scenario, genes, including VEGFA, EMP1, PPL, KRAS, MET, TP53, MMPs and HOXs, and miRNAs, including mir-6728 and mir-99a, emerge as key players in the molecular interactions driving HNSCC tumorigenesis. Despite the heterogeneity characterizing these HNSCC subtypes, and the limitations of a study pointing to relationships that could be context dependent, the overlap with previously published studies is encouraging. Hence, it supports further investigation for key molecules, both those already and not correlated to HNSCC.

The Effect of Xevinapant Combined with Ionizing Radiation on HNSCC and Normal Tissue Cells and the Impact of Xevinapant on Its Targeted Proteins cIAP1 and XIAP

The poor prognosis of HNSCC is partly due to treatment resistance. The SMAC mimetic Xevinapant is a promising new approach to targeted cancer therapy. Xevinapant inhibits cIAP1/2 and XIAP, leading to apoptosis, necroptosis and inhibition of prosurvival signaling. Combining Xevinapant with IR could improve therapeutic potential. The effect of Xevinapant in combination with IR on HNSCC and healthy tissue cells was investigated. Cell growth, cell death, clonogenic survival and DNA double-strand breaks (DSBs) were studied, and intracellular cIAP1 and XIAP levels were evaluated. Xevinapant had cytostatic and cytotoxic, as well as radiosensitizing, effects on the malignant cells, while healthy tissue cells were less affected. Apoptotic and necrotic cell death was particularly affected, but the increase in residual DSBs and the reduced survival implied an additional effect of Xevinapant on DNA damage repair and other cell inactivation mechanisms. cIAP1 and XIAP levels varied for each cell line and were affected by Xevinapant and IR treatment. There was an association between higher IAP levels and increased cell death. Xevinapant appears to be a potent new drug for HNSCC therapy, especially in combination with IR. IAP levels could be an indicator for impaired DNA damage repair and increased susceptibility to cellular stress.

Identification of an individualized therapy prognostic signature for head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) are the most common cancers in the head and neck. Therapeutic response-related genes (TRRGs) are closely associated with carcinogenesis and prognosis in HNSCC. However, the clinical value and prognostic significance of TRRGs are still unclear. We aimed to construct a prognostic risk model to predict therapy response and prognosis in TRRGs-defined subgroups of HNSCC.

METHODS

The multiomics data and clinical information of HNSCC patients were downloaded from The Cancer Genome Atlas (TCGA). The profile data GSE65858 and GSE67614 chip was downloaded from public functional genomics data Gene Expression Omnibus (GEO). Based on TCGA-HNSC database, patients were divided into a remission group and a non-remission group according to therapy response, and differentially expressed TRRGs between those two groups were screened. Using Cox regression analysis and Least absolute shrinkage and selection operator (LASSO) analysis, candidate TRRGs that can predict the prognosis of HNSCC were identified and used to construct a TRRGs-based signature and a prognostic nomogram.

RESULT

A total of 1896 differentially expressed TRRGs were screened, including 1530 upregulated genes and 366 downregulated genes. Then, 206 differently expressed TRRGs that was significantly associated with the survival were chosen using univariate Cox regression analysis. Finally, a total of 20 candidate TRRGs genes were identified by LASSO analysis to establish a signature for risk prediction, and the risk score of each patient was calculated. Patients were divided into a high-risk group (Risk-H) and a low-risk group (Risk-L) based on the risk score. Results showed that the Risk-L patients had better overall survival (OS) than Risk-H patients. Receiver operating characteristic (ROC) curve analysis revealed great predictive performance for 1-, 3-, and 5-year OS in TCGA-HNSC and GEO databases. Moreover, for patients treated with post-operative radiotherapy, Risk-L patients had longer OS and lower recurrence than Risk-H patients. The nomogram involves risk score and other clinical factors had good performance in predicting survival probability.

CONCLUSIONS

The proposed risk prognostic signature and Nomogram based on TRRGs are novel promising tools for predicting therapy response and overall survival in HNSCC patients.

Identification of HPV16 E1 and E2-specific T cells in the oropharyngeal cancer tumor microenvironment

BACKGROUND

High-risk human papillomavirus (HPV) is a primary cause of an increasing number of oropharyngeal squamous cell carcinomas (OPSCCs). The viral etiology of these cancers provides the opportunity for antigen-directed therapies that are restricted in scope compared with cancers without viral components. However, specific virally-encoded epitopes and their corresponding immune responses are not fully defined.

METHODS

To understand the OPSCC immune landscape, we conducted a comprehensive single-cell analysis of HPV16+ and HPV33+ primary tumors and metastatic lymph nodes. We used single-cell analysis with encoded peptide-human leukocyte antigen (HLA) tetramers to analyze HPV16+ and HPV33+ OPSCC tumors, characterizing the ex vivo cellular responses to HPV-derived antigens presented in major Class I and Class II HLA alleles.

RESULTS

We identified robust cytotoxic T-cell responses to HPV16 proteins E1 and E2 that were shared across multiple patients, particularly in HLA-A*01:01 and HLA-B*08:01. Responses to E2 were associated with loss of E2 expression in at least one tumor, indicating the functional capacity of these E2-recognizing T cells and many of these interactions validated in a functional assay. Conversely, cellular responses to E6 and E7 were limited in quantity and cytotoxic capacity, and tumor E6 and E7 expression persisted.

CONCLUSIONS

These data highlight antigenicity beyond HPV16 E6 and E7 and nominate candidates for antigen-directed therapies.

Bioinformatic analysis identifies HPV-related tumor microenvironment remodeling prognostic biomarkers in head and neck squamous cell carcinoma

Head and neck squamous cell carcinomas (HNSCCs) are highly aggressive tumors with rapid progression and poor prognosis. Human papillomavirus (HPV) infection has been identified as one of the most important carcinogens for HNSCC. As an early event in HNSCC, infection with HPV leads to altered immune profiles in the tumor microenvironment (TME). The TME plays a key role in the progression and transformation of HNSCC. However, the TME in HNSCC is a complex and heterogeneous mix of tumor cells, fibroblasts, different types of infiltrating immune cells, and extracellular matrix. Biomarkers relevant to the TME, and the biological role of these biomarkers, remain poorly understood. To this end, we performed comprehensive analysis of the RNA sequencing (RNA-Seq) data from tumor tissue of 502 patients with HNSCC and healthy tissue of 44 control samples. In total, we identified 4,237 differentially expressed genes, including 2,062 upregulated and 2,175 downregulated genes. Further in-depth bioinformatic analysis suggested 19 HNSCC tumor tissue-specific genes. In the subsequent analysis, we focused on the biomarker candidates shown to be significantly associated with unfavorable patient survival: ITGA5, PLAU, PLAUR, SERPINE1, TGFB1, and VEGFC. We found that the expression of these genes was negatively regulated by DNA methylation. Strikingly, all of these potential biomarkers are profoundly involved in the activation of the epithelial-mesenchymal transition (EMT) pathway in HNSCCs. In addition, these targets were found to be positively correlated with the immune invasion levels of CD4+ T cells, macrophages, neutrophils, and dendritic cells, but negatively correlated with B-cell infiltration and CD8+ T-cell invasion. Notably, our data showed that the expression levels of ITGA5, PLAU, PLAUR, SERPINE1, and TGFB1 were significantly overexpressed in HPV-positive HNSCCs compared to normal controls, indicating the potential role of these biomarkers as transformation and/or malignant progression markers for HNSCCs in patients with HPV infection. Taken together, the results of our study propose ITGA5, PLAU, PLAUR, SERPINE1, and TGFB1 as potential prognostic biomarkers for HNSCCs, which might be involved in the HPV-related TME remodeling of HNSCC. Our findings provide important implications for the development and/or improvement of patient stratification and customized immunotherapies in HNSCC.