Head And Neck Squamous Cell Carcinoma Subtypes Research Articles

Role of mitophagy in head and neck squamous cell carcinoma: Prognosis and immune insights

ObjectiveTo explore the correlation between mitophagy and the tumor microenvironment (TME) in patients with head and neck squamous cell carcinoma (HNSCC), with an aim to enhance therapeutic efficacy for HNSCC. MethodsA machine learning-based multigene prognostic signature was developed based on mitophagy-related differentially expressed genes (MRGs) identified in The Cancer Genome Atlas cohort. This signature was correlated with the TME using gene set enrichment analysis. The association between this prognostic signature and various immunological features of the TME was explored, including status of tumor-infiltrating immune cells, expression of immune checkpoint molecules, and the immunoscore. Immunohistochemistry validated the expression of hub gene CSNK2A2 and assessed its relationship with immunomarker expression. Quantitative PCR validated CSNK2A2 knockdown in HNSCC cell lines. Functional experiments including Transwell assays to determine cell migration and invasion, Cell Counting Kit 8 assay, and 5-ethynyl-2-deoxyuridine assay were performed to confirm the role of CSNK2A2 in HNSCC. Finally, a subcutaneous xenograft model was generated in C3H mice to validate our findings. ResultsThe MRG-based prognostic signature showed excellent predictive performance. High-risk patients had significantly shorter progression-free and overall survival (P ​< ​0.0001) than low-risk patients. CD8+ T cell infiltration was lower in high-risk groups, whereas low-risk groups showed higher immunological marker expression. Thus, the low-risk HNSCC subtype may benefit from immune therapy, while high-risk subtypes may benefit from chemotherapy (P ​< ​0.001). CSNK2A2 was highly expressed and strongly correlated with CD8 and PD-L1 based on immunohistochemistry of the HNSCC tissue microarray. CSNK2A2 knockdown reduced cell migration, invasion, and proliferation, and arrested cells in G1 phase. In vivo, it led to slower tumor growth and smaller tumor volumes. ConclusionWe established a potential prognostic signature that could improve HNSCC management in the future. CSNK2A2 may be a new biomarker to predict immunotherapy efficacy in HNSCC.

CD24 and Oct4: Cancer stem markers expression correlates with histological subtyping of head and neck squamous cell carcinoma

Background Head and neck squamous cell carcinoma (HNSCC) encompasses a diverse range of tumors with varying degrees of differentiation. Within tumors, cancer stem cells (CSCs) are believed to play a crucial role in tumor initiation, progression, and resistance to treatment. This study aimed to explore the expression of two CSC markers i.e. CD24 and Oct4, in patients with HNSCC. Methods The study included 85 patients diagnosed with HNSCC. Immunohistochemistry was used to evaluate the expression of CD24 and Oct4 in tumor tissues obtained from patients with HNSCC. Staining intensity and the proportion of positive tumor cells were analyzed and compared across the various HNSCC grades and histological subtypes. Results The findings revealed that the mean immunoreactivity score (IRS) for CD24 was significantly higher in non-conventional HNSCC subtypes compared to conventional types (p = 0.019). Additionally, a significant statistical association was observed between the IRS status of CD24 and histological subtypes (p = 0.043). Other demographic, clinical, and histological parameters showed non-significant associations with staining intensity, proportion score (PC), IRS status, and mean IRS (all p values &gt; 0.05). Conclusions These findings indicate that CD24 could potentially serve as a CSC marker for distinguishing between conventional and non-conventional histological types of HNSCC. This suggests that CD24 holds promise as a valuable tool in identifying specific HNSCC subtypes characterized by CSCs.

Identification of two distinct head and neck squamous cell carcinoma subtypes based on fatty acid metabolism-related signatures: Implications for immunotherapy and chemotherapy.

The dysregulation of lipid metabolism is a critical factor in the initiation and progression of tumors. In this investigation, we aim to characterize the molecular subtypes of head and neck squamous cell carcinoma (HNSCC) based on their association with fatty acid metabolism and develop a prognostic risk model. The transcriptomic and clinical data about HNSCC were obtained from public databases. Clustering analysis was conducted on fatty acid metabolism genes (FAMG) associated with prognosis, utilizing the non-negative matrix factorization algorithm. The immune infiltration, response to immune therapy, and drug sensitivity between molecular subtypes were evaluated. Differential expression genes were identified between subtypes, and a prognostic model was constructed using Cox regression analyses. A nomogram for HNSCC was constructed and evaluated. Thirty FAMGs have been found to exhibit differential expression in HNSCC, out of which three are associated with HNSCC prognosis. By performing clustering analysis on these 3 genes, 2 distinct molecular subtypes of HNSCC were identified that exhibit significant heterogeneity in prognosis, immune landscape, and treatment response. Using a set of 7778 genes that displayed differential expression between the 2 molecular subtypes, a prognostic risk model for HNSCC was constructed comprising 11 genes. This model has the ability to stratify HNSCC patients into high-risk and low-risk groups, which exhibit significant differences in prognosis, immune infiltration, and immune therapy response. Moreover, our data suggest that this risk model is negatively correlated with B cells and most T cells, but positively correlated with macrophages, mast cells, and dendritic cells. Ultimately, we constructed a nomogram incorporating both the risk signature and radiotherapy, which has demonstrated exceptional performance in predicting prognosis for HNSCC patients. A molecular classification system and prognostic risk models were developed for HNSCC based on FAMGs. This study revealed the potential involvement of FAMGs in modulating tumor immune microenvironment and response to treatment.

Molecular subtype identification and prognosis stratification based on golgi apparatus-related genes in head and neck squamous cell carcinoma

BackgroundAbnormal dynamics of the Golgi apparatus reshape the tumor microenvironment and immune landscape, playing a crucial role in the prognosis and treatment response of cancer. This study aims to investigate the potential role of Golgi apparatus-related genes (GARGs) in the heterogeneity and prognosis of head and neck squamous cell carcinoma (HNSCC).MethodsTranscriptional data and corresponding clinical information of HNSCC were obtained from public databases for differential expression analysis, consensus clustering, survival analysis, immune infiltration analysis, immune therapy response assessment, gene set enrichment analysis, and drug sensitivity analysis. Multiple machine learning algorithms were employed to construct a prognostic model based on GARGs. A nomogram was used to integrate and visualize the multi-gene model with clinical pathological features.ResultsA total of 321 GARGs that were differentially expressed were identified, out of which 69 were associated with the prognosis of HNSCC. Based on these prognostic genes, two molecular subtypes of HNSCC were identified, which showed significant differences in prognosis. Additionally, a risk signature consisting of 28 GARGs was constructed and demonstrated good performance for assessing the prognosis of HNSCC. This signature divided HNSCC into the high-risk and low-risk groups with significant differences in multiple clinicopathological characteristics, including survival outcome, grade, T stage, chemotherapy. Immune response-related pathways were significantly activated in the high-risk group with better prognosis. There were significant differences in chemotherapy drug sensitivity and immune therapy response between the high-risk and low-risk groups, with the low-risk group being more suitable for receiving immunotherapy. Riskscore, age, grade, and radiotherapy were independent prognostic factors for HNSCC and were used to construct a nomogram, which had good clinical applicability.ConclusionsWe successfully identified molecular subtypes and prognostic signature of HNSCC that are derived from GARGs, which can be used for the assessment of HNSCC prognosis and treatment responses.

CXCL family-related classification predicts prognosis and response to immunotherapy in patients with head and neck squamous cell carcinoma based on TCGA and GEO databases.

Head and neck squamous cell carcinoma (HNSCC) is the sixth most prevalent malignant cancer worldwide. The cysteine X cysteine (CXC) chemokine family contains 17 members, which are reportedly crucial for the growth, invasion, metastasis, and microenvironment of tumor cells. Although the precise functions of CXC ligands (CXCLs) in HNSCC are unclear, these proteins may play important roles in controlling tumor growth and forming the tumor immune environment. We downloaded the RNA sequencing and matched clinicopathological data of 379 patients with HNSCC as the training set from The Cancer Genome Atlas and two datasets from the Gene Expression Omnibus for use as validation sets. Through consensus clustering, we identified two subtypes of HNSCC associated with the CXCL family, named cluster1 and cluster2. Patients with the cluster1 subtype showed favourable clinical outcomes, significant immune cell infiltration, and improved immune response signalling pathway modulation. We also developed a nomogram of CXCL family scores for therapeutic use and for predicting the overall survival (OS) of patients with HNSCC. Patients with lower scores showed longer OS and higher immune cell infiltration in their tissues. We developed a new classification method for HNSCC using the CXCL gene family, which can be used clinically to evaluate the prognosis and response to immunotherapy in patients with HNSCC.

Mononuclear phagocyte system-related multi-omics features yield head and neck squamous cell carcinoma subtypes with distinct overall survival, drug, and immunotherapy responses

BackgroundRecent research reported that mononuclear phagocyte system (MPS) can contribute to immune defense but the classification of head and neck squamous cell carcinoma (HNSCC) patients based on MPS-related multi-omics features using machine learning lacked.MethodsIn this study, we obtain marker genes for MPS through differential analysis at the single-cell level and utilize “similarity network fusion” and “MoCluster” algorithms to cluster patients’ multi-omics features. Subsequently, based on the corresponding clinical information, we investigate the prognosis, drugs, immunotherapy, and biological differences between the subtypes. A total of 848 patients have been included in this study, and the results obtained from the training set can be verified by two independent validation sets using “the nearest template prediction”.ResultsWe identified two subtypes of HNSCC based on MPS-related multi-omics features, with CS2 exhibiting better predictive prognosis and drug response. CS2 represented better xenobiotic metabolism and higher levels of T and B cell infiltration, while the biological functions of CS1 were mainly enriched in coagulation function, extracellular matrix, and the JAK-STAT signaling pathway. Furthermore, we established a novel and stable classifier called “getMPsub” to classify HNSCC patients, demonstrating good consistency in the same training set. External validation sets classified by “getMPsub” also illustrated similar differences between the two subtypes.ConclusionsOur study identified two HNSCC subtypes by machine learning and explored their biological difference. Notably, we constructed a robust classifier that presented an excellent classifying prediction, providing new insight into the precision medicine of HNSCC.

Abstract B004: Molecular crosstalk between NF-κB and NRF2 signaling affects prognosis in HPV-associated head and neck cancer

Abstract The incidence of head and neck squamous cell carcinoma (HNSCC) is on the rise and is expected to increase by 50% by 2030. Around half of the patient population affected are diagnosed when the tumor is at a locally advanced stage. These patients are usually treated with intense radiotherapy, leading to severe side-effects. Precision medicine would revolutionize the treatment of head and neck cancer by accurately identifying patients that are at low risk of recurrence, reduce treatment related side-effects and aid in overall improvement in quality of life of patients after treatment. This generates the need to develop biomarkers to identify patients with less aggressive tumors as candidates for treatment de-escalation. We applied an unbiased approach (weighted gene correlation network analysis (WGCNA)) that allows detection of autocorrelated gene sets on 3 independent cohorts of HPV+ HNSCC and created 22 consensus transcriptional modules by selecting genes that grouped together in WGCNA analyses from all 3 cohorts. Interestingly, only 1 module intrinsically divided HPV+ HNSCC into 2 subtypes, displaying different mutational profiles, mutational signatures, HPV gene expression patterns, HPV integration status, and patient survival. Gene set enrichment analysis revealed that this module was enriched in NF-kB genes and strongly associated with NF-κB signaling, confirming our prior findings that defined HPV+ HNSCC subtypes by presence or absence of NF-kB regulators, TRAF3 or CYLD defects and by the NF-κB activity classifier. We hypothesized that NF-kB-driven intrinsic tumor characteristics contribute to increased sensitivity of NF-kB active HPV+ head and neck tumors to radiation, providing patients survival benefits. Indeed, TRAF3 or CYLD deletion dramatically increased radiation sensitivity of HPV+ head and neck cancer cells. As we began to investigate mechanisms of radiation sensitization associated with TRAF3 and CYLD deletion, we found that activation of NF-κB significantly correlated with marked downregulation of nuclear factor erythroid 2-related factor 2 (NRF2) activity in tumors from 3 independent cohorts, as well as in HPV+ HNSCC cells that harbor constitutively active NF-kB due to deletion of TRAF3 or CYLD. Interestingly, TRAF3 CRISPR KO cells had lower NRF2 protein levels that were restored by MG132 treatment, indicating an involvement of KEAP1/CUL3 mediated proteasomal degradation of NRF2. In summary, our data showcases an inverse correlation between NF-kB and NRF2 pathways in HPV+ HNSCC. Currently, there are no prognostic biomarkers to distinguish patients who require aggressive therapy versus those that are appropriate for reduced intensity treatment. Identification of markers distinguishing the 2 subtypes of HPV+ HNSCC (high NF-kB and low NRF2 activity) may serve as prognostic biomarkers to help clinicians with therapeutic decisions. Citation Format: Aditi Kothari, Travis Schrank, Wendell Yarbrough, Natalia Isaeva. Molecular crosstalk between NF-κB and NRF2 signaling affects prognosis in HPV-associated head and neck cancer [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr B004.

EXT2: a novel prognostic and predictive biomarker for head and neck squamous cell carcinoma

ObjectiveThis study focused on EXT2, a member of the EXT family involved in heparan sulfate synthesis, to evaluate its potential as a prognostic and predictive biomarker in head and neck squamous cell carcinoma (HNSCC). Materials and MethodsThe present study used The Cancer Genome Atlas Head-Neck Squamous Cell Carcinoma (TCGA-HNSC) dataset-based UALCAN databases to analyze the EXT2 expression and its clinicopathological features. In addition, we recruited 51 oral squamous cell carcinoma patients (OSCC), the most common HNSCC subtype, to validate the EXT2 mRNA expression analysis. In addition, we identified the role of EXT2 in prognosis using a Kaplan-Meier plot and immune signature using the tumor infiltration level. Furthermore, functional roles were analyzed using the EXT2 gene and protein networks. ResultsThe expression of EXT2 mRNA was significantly upregulated in OSCC tumors, which is consistent with the UALCAN-based results. EXT2 protein was also significantly overexpressed in HNSCC samples and was correlated with clinicopathological features. High EXT2 expression is associated with poor survival outcomes in HNSCC patients. Functional analysis of EXT2 using in silico tools revealed its involvement in critical pathways, including Wnt signaling, proteoglycans in cancer, and cellular responses to fibroblast growth and inflammation. ConclusionThese findings highlight the potential of EXT2 as a prognostic and predictive biomarker of HNSCC.

Molecular classification of human papilloma virus-negative head and neck squamous cell carcinomas: Cell cycle-based classifier and prognostic signature.

The molecular classification of human papillomavirus (HPV)-negative head and neck squamous cell carcinomas (HNSCCs) remains questionable. Differentially expressed genes were detected between tumor and normal tissues and GSEA showed they are associated with cell cycle pathways. This study aimed to classify HPV-negative HNSCCs based on cell cycle-related genes. The established gene pattern was correlated with tumor progression, clinical prognosis, and drug treatment efficacy. Biological analysis was performed using HNSCC patient sample data obtained from the Cancer Genome Atlas (TCGA), Clinical Proteomic Tumor Analysis Consortium (CPTAC), and Gene Expression Omnibus (GEO) databases. All samples included in this study contained survival information. RNA sequencing data from 740 samples were used for the analysis. Previously characterized cell cycle-related genes were included for unsupervised consensus clustering. Two subtypes of HPV-negative HNSCCs (C1, C2) were identified. Subtype C1 displayed low cell cycle activity, 'hot' tumor microenvironment (TME), earlier N stage, lower pathological grade, better prognosis, and higher response rate to the immunotherapy and targeted therapy. Subtype C2 was associated with higher cell cycle activity, 'cold' TME, later N stage, higher pathological grade, worse prognosis, and lower response rate to the treatment. According to the nearest template prediction method, classification rules were established and verified. Our work explored the molecular mechanism of HPV-negative HNSCCs in the view of cell cycle and might provide new sights for personalized anti-cancer treatment.

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.

Identification of the HNSC88 Molecular Signature for Predicting Subtypes of Head and Neck Cancer.

Head and neck squamous cell carcinoma (HNSC) exhibits genetic heterogeneity in etiologies, tumor sites, and biological processes, which significantly impact therapeutic strategies and prognosis. While the influence of human papillomavirus on clinical outcomes is established, the molecular subtypes determining additional treatment options for HNSC remain unclear and inconsistent. This study aims to identify distinct HNSC molecular subtypes to enhance diagnosis and prognosis accuracy. In this study, we collected three HNSC microarrays (n = 306) from the Gene Expression Omnibus (GEO), and HNSC RNA-Seq data (n = 566) from The Cancer Genome Atlas (TCGA) to identify differentially expressed genes (DEGs) and validate our results. Two scoring methods, representative score (RS) and perturbative score (PS), were developed for DEGs to summarize their possible activation functions and influence in tumorigenesis. Based on the RS and PS scoring, we selected candidate genes to cluster TCGA samples for the identification of molecular subtypes in HNSC. We have identified 289 up-regulated DEGs and selected 88 genes (called HNSC88) using the RS and PS scoring methods. Based on HNSC88 and TCGA samples, we determined three HNSC subtypes, including one HPV-associated subtype, and two HPV-negative subtypes. One of the HPV-negative subtypes showed a relationship to smoking behavior, while the other exhibited high expression in tumor immune response. The Kaplan-Meier method was used to compare overall survival among the three subtypes. The HPV-associated subtype showed a better prognosis compared to the other two HPV-negative subtypes (log rank, p = 0.0092 and 0.0001; hazard ratio, 1.36 and 1.39). Additionally, within the HPV-negative group, the smoking-related subgroup exhibited worse prognosis compared to the subgroup with high expression in immune response (log rank, p = 0.039; hazard ratio, 1.53). The HNSC88 not only enables the identification of HPV-associated subtypes, but also proposes two potential HPV-negative subtypes with distinct prognoses and molecular signatures. This study provides valuable strategies for summarizing the roles and influences of genes in tumorigenesis for identifying molecular signatures and subtypes of HNSC.

Telomere maintenance genes-derived prognosis signature characterizes immune landscape and predicts prognosis of head and neck squamous cell carcinoma.

Telomere dysfunction has been identified as a biological marker of cancer progression in several types of cancer, including Head and Neck Squamous Cell Carcinoma (HNSCC). This study aimed to characterize the telomere maintenance genes (TMG)-related signature in prognosis and treatment response in HNSCC. The transcriptome and clinical data of HNSCC were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases, respectively. Non-negative matrix factorization (NMF) was used to identify molecular subtypes derived from TMG. Gene set enrichment analysis (GSEA) was performed to analyze the differentially expressed pathways between subtypes, and a risk score model derived from TMG was established. Kaplan-Meier survival analysis was used to evaluate inter-group prognostic features, and the correlation between TMG-derived molecular subtypes and risk score model with immune infiltration, immunotherapy, and chemosensitivity was assessed. Two HNSCC subtypes were identified based on 59 TMG-related genes, which exhibit significant heterogeneity in prognosis, immune cell infiltration, and treatment response. Additionally, a TMG-derived risk signature containing 9 genes was developed to assess the prognosis of HNSCC patients. The signature had significant predictive ability for HNSCC prognosis and was significantly correlated with immune cell infiltration and immunotherapy response. A nomogram integrating the risk signature, N stage and radiotherapy was constructed to predict 1-, 3-, and 5-year overall survival (OS) of HNSCC patients, which had better performance than other prognostic models and included TMG-derived risk score, radiotherapy, and N stage. This study identified TMG-derived molecular subtypes in HNSCC and developed a novel prognostic score model, highlighting the potential value of TMG in HNSCC prognosis and immunotherapy.

Proportion of CD44+ Subset of Tumour Cells in Single Cell Suspension Prepared from FFPET Sections Directly Correlates with Histological Subtyping of Head and Neck Squamous Cell Carcinoma

CD44 expression in tumours imparts potential to progress, metastasize, recurrence, and resistance against antineoplastic therapy. In this study, we sought to describe the variation in the immuno-expression and numeration of MDR1+ and CD44+ potential cancer stem cells in different histological grades and subtypes of head and neck squamous cell carcinoma (HNSCC). Flow-cytometric analysis was performed on single cell suspension prepared from formalin fixed paraffin embedded tissue (FFPET) sections of HNSCC using anti-CD44 and anti-MDR1/ABCB-1 primary monoclonal antibodies. Immunohistochemical (IHC) staining was also carried out using both of these antibodies on HNSCC tissue sections mounted on super frosted glass slides. On immunohistochemical analysis, the mean IRS for CD44 and MDR1 were 8.6364 ±3.02114 and 1.5909 ±1.27674 respectively. When mean immune-expression scores of CD44 antibody and MDR1/ABCB-1 were compared with histological grades and subtypes of HNSCC, the relationship was found to be statistically insignificant. Interestingly, a strong statistical difference (p = 0.000) was observed when the mean score of subset of dysplastic squamous epithelial cells with characteristics of cell stemness (CD326+CD44+) was compared among different histological subtypes of HNSCC using flowcytometric analysis. While no statistically significant association was observed when the mean score for subset of dysplastic cells with potential of drug resistance (CD44+MDR1+) was compared among different histological subtypes of HNSCC. Although potential cancer stem cell marker CD44 and the multidrug resistance maker ABCB-1/MDR1 co-expressed in HNSCC but the proportion of CD326+CD44+ subset of tumour cells (potential cancer stem cells/CSCs) significantly correlates with least aggressive to more aggressive tumour subtypes.

Abstract 6164: NF-κB and NRF2 signaling pathways affect prognosis in HPV-associated head and neck cancer

Abstract Incidence of HPV associated head and neck squamous cell carcinoma (HNSCC) is on the rise, displaying a significantly favorable prognosis and overall better survival as compared to HPV negative HNSCC. Intense radiotherapy is the primary medical care leading to treatment associated morbidity in patients, thereby generating a need for de-intensification strategies. Biomarkers that can identify patients with less aggressive tumors as candidates for de-escalation therapy would revolutionize treatment. We applied an unbiased approach (weighted gene correlation network analysis (WGCNA)) that allows detection of autocorrelated gene sets on 3 independent cohorts of HPV+ HNSCC and created 22 consensus transcriptional modules by selecting genes that grouped together in WGCNA analyses from all 3 cohorts. Interestingly, only 1 module intrinsically divided HPV+ HNSCC into 2 subtypes, displaying different mutational profiles, mutational signatures, HPV gene expression patterns, HPV integration status, and patient survival. Gene set enrichment analysis revealed that this module was enriched in NF-kB genes and strongly associated with NF-κB signaling, confirming our prior findings that defined HPV+ HNSCC subtypes by presence or absence of NF-kB regulators, TRAF3 or CYLD defects and by the NF-κB activity classifier. Our studies show that NF- κB -driven intrinsic tumor characteristics contribute to increased sensitivity of NF- κB active HPV+ head and neck tumors to radiation, providing patients survival benefits. Indeed, TRAF3 or CYLD deletion activated NF-kB and dramatically increased radiation sensitivity of HPV+ head and neck cancer cells. In line with our RNA seq analysis, we found that activation of NF-κB via TRAF3/CYLD deletion significantly correlated with marked downregulation of NRF2 activity and reduced nuclear localization in in HPV+ HNSCC cells. Interestingly, TRAF3 CRISPR KO cells had lower NRF2 protein levels that were restored by MG132 treatment, indicating an involvement of KEAP1/CUL3 mediated proteasomal degradation of NRF2. In summary, our data unveils a unique relation between NF-κB pathway and radiosensitivity in HPV+ HNSCC. The distinct biological characteristics that separate patients into two subclasses associated with favorable prognosis could serve as a biomarker for personalized therapy. Citation Format: Aditi Kothari, Travis Parke Schrank, Wendell Gray Yarbrough, Natalia Isaeva. NF-κB and NRF2 signaling pathways affect prognosis in HPV-associated head and neck cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6164.

Cellular states are coupled to genomic and viral heterogeneity in HPV-related oropharyngeal carcinoma.

Head and neck squamous cell carcinoma (HNSCC) includes a subset of cancers driven by human papillomavirus (HPV). Here we use single-cell RNA-seq to profile both HPV-positive and HPV-negative oropharyngeal tumors, uncovering a high level of cellular diversity within and between tumors. First, we detect diverse chromosomal aberrations within individual tumors, suggesting genomic instability and enabling the identification of malignant cells even at pathologically negative margins. Second, we uncover diversity with respect to HNSCC subtypes and other cellular states such as the cell cycle, senescence and epithelial-mesenchymal transitions. Third, we find heterogeneity in viral gene expression within HPV-positive tumors. HPV expression is lost or repressed in a subset of cells, which are associated with a decrease in HPV-associated cell cycle phenotypes, decreased response to treatment, increased invasion and poor prognosis. These findings suggest that HPV expression diversity must be considered during diagnosis and treatment of HPV-positive tumors, with important prognostic ramifications.

Screening of Tumor Antigens and Construction of Immune Subtypes for mRNA Vaccine Development in Head and Neck Squamous Cell Carcinoma.

A growing number of clinical studies have confirmed that mRNA vaccines are effective in the treatment of malignant tumors; however, their efficacy in head and neck squamous cell carcinoma (HNSCC) has not been determined. This study aimed to identify the potential antigens of HNSCC for mRNA vaccine development and further distinguish the immune subtypes of HNSCC to select suitable patients for vaccination. We obtained gene expression profiles and corresponding clinical information of HNSCC from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). We visualized the genetic alterations of potential antitumor antigens using cBioPortal and obtained the immune gene set from Immport. The correlation between the expression of the identified antigens and the infiltration of antigen-presenting cells was visualized by Tumor Immune Estimation Resource (TIMER). We evaluated the potential biological functions of different samples and described the immune landscape. Increased expression of three potential tumor antigens, CCR4, TMCO1, and SPACA4, associated with superior prognoses and infiltration of antigen-presenting cells, was identified in HNSCC. Three immune subtypes (C1-C3) with different molecular, cellular, and clinical characteristics were defined. Patients with C3 tumor had a better prognosis, representing an immune "cold" phenotype, which may be more suitable for mRNA vaccination. In addition, different immune characteristics were observed among the three immune subtypes, including markers of immune cells, mutation burden, expression of immune checkpoints, and immune modulators. Finally, the immune landscape of HNSCC showed a high degree of heterogeneity between individual patients. CCR4, TMCO1, and SPACA4 may be potential antigens for developing mRNA vaccines against HNSCC, especially for patients with C3 tumor. This study could provide a theoretical basis for the development of an mRNA vaccine against HNSCC.

Characterization of oral microbiota in HPV and non-HPV head and neck squamous cell carcinoma and its association with patient outcomes

ObjectiveTo investigate the interplay among the oral microbiota, HPV infection, traditional risk factors and patient outcomes in head and neck squamous cell carcinoma (HNSCC). Materials and MethodsA multi-center study of HNSCC patients with paired tumor and control tissues. We characterized the oral microbiota and HPV infection of tissues in 166 Chinese adults by sequencing the bacterial 16S rRNA V3-V4 and HPV L1 regions, respectively, and examined the associations among the oral microbiota, HPV and clinical features. ResultsA total of 15.7% of the surveyed HNSCC patients were positive for HPV DNA, with infection rates varying from 66.7% in oropharyngeal SCC to 10.4% in oral cavity SCC (OSCC). No HPV infection was detected in the surveyed hypopharyngeal SCC. HPV16 was largely the predominant type. HPV infection in non-OSCC, especially oropharyngeal SCC, was associated with advanced N stage and superior survival outcomes. Oral microbiota dysbiosis was observed in HNSCC tumors, with differentially abundant taxa mainly associated with HNSCC subtype, T stage, survival/relapse, HPV infection, and smoking. Notably, the enrichment of Fusobacterium in tumor tissues of OSCC patients was associated with no smoking, early T stage, early N stage, and better 3-year disease-specific survival. ConclusionOur findings underscore the involvement of oral microbiota dysbiosis in OSCC pathogenesis, Fusobacterium is involved with improved OSCC patient outcomes, especially in patients lacking traditional risk factors. Understanding the complex interactions among the oral microbiota, HPV infection and other risk factors for HNSCC will provide important insights into the pathogenesis of HNSCC.

Single-Cell Transcriptome Analysis Reveals Different Immune Signatures in HPV- and HPV + Driven Human Head and Neck Squamous Cell Carcinoma.

Background Head and neck squamous cell carcinoma (HNSCC) is a significant health problem and related to poor long-term outcomes, indicating more research to be done to deeply understand the underlying pathways. Objective This current study aimed in the assessment of the viral- (especially human papilloma virus [HPV]) and carcinogen-driven head and neck squamous cell carcinoma (HNSCC) microenvironment based on single-cell sequencing analysis. Methods Data were downloaded from GEO database (GSE139324), including 131224 cells from 18 HP- HNSCC patients and 8 HPV+ HNSCC patients. Following data normalization, all highly variable genes in single cells were identified, and batch correction was applied. Differentially expressed genes were identified using Wilcoxon rank sum test. A gene enrichment analysis was performed in each cell cluster using KEGG analysis. Single-cell pseudotime trajectories were constructed with MONOCLE (version 2.6.4). Cell-cell interactions were analyzed with CellChat R package. Additionally, cell-cell communication patterns in key signal pathways were compared in different tissue groups. A hidden Markov model (HMM) was used to predict gene expression states (on or off) throughout pseudotime. Five-year overall survival outcomes were compared in both HPV+ and HPV- subsets. Results 20,978 high-quality individual cells passed quality control. RNA-seq data were used from 522 HNSCC primary tumor samples. 1,137 differentially expressed genes between HPV+ and HPV- HNSCC patients were investigated. 96 differentially expressed genes were associated with overall survival and highly enriched in B cell associated biological process. Cell composition differed between types of samples. MHC-I, MHC-II, and MIF signaling pathways were found to be most relevant. Within these pathways, some cells were either signal receiver or signal sender, depending on sample type, respectively. Six genes were obtained, AREG and TGFBI (upregulation), CD27, CXCR3, MS4A1, and CD19 (downregulation), whose expression and HPV types were highly associated with worse overall survival. AREG and TGFBI were pDC marker genes, CXCR3 and CD27 were significantly expressed in T cell-related cells, while MS4A1 and CD19 were mainly expressed in B naïve cells. Conclusions This study revealed dynamic changes in cell percentage and heterogeneity of cell subtypes of HNSCC. AREG, TGFBI, CD27, CXCR3, MS4A1, and CD19 were associated with worse overall survival in HPV-related HNSCC. Especially B-cell related pathways were revealed as particularly relevant in HPV-related HNSCC. These findings are a basis for the development of biomarkers and therapeutic targets in respective patients.

Pharmacogenomic landscape of head and neck squamous cell carcinoma informs precision oncology therapy.

Head and neck squamous cell carcinoma (HNSCC) is a common and frequently lethal cancer with few therapeutic options. In particular, there are few effective targeted therapies. Development of highly effective therapeutic strategies tailored to patients with HNSCC remains a pressing challenge. To address this, we present a pharmacogenomic study to facilitate precision treatments for patients with HNSCC. We established a large collection of 56 HNSCC patient-derived cells (PDCs), which recapitulated the molecular features of the original tumors. Pharmacological assessment of HNSCCs was conducted using a three-tiered high-throughput drug screening using 2248 compounds across these PDC models and an additional 18 immortalized cell lines. We integrated genomic, transcriptomic, and pharmacological analysis to predict biomarkers, gene-drug associations, and validated biomarkers. These results supported drug repurposing for multiple HNSCC subtypes, including the JAK2 inhibitor fedratinib, for low KRT18-expressing HNSCC cases, and the topoisomerase inhibitor mitoxantrone, for IL6R-activated HNSCC cases. Our results demonstrated concordance between susceptibility predictions from the PDCs and the matched patients' responses to standard clinical medication. Moreover, we identified and experimentally confirmed that high expression of ITGB1 elicited therapeutic resistance to docetaxel and high SOD1 expression conferred resistance to afatinib. We further validated ITGB1 as a predictive biomarker for the efficacy of docetaxel therapy in a phase 2 clinical trial. In summary, our study shows that this HNSCC cell resource, as well as the resulting pharmacogenomic profiles, is effective for biomarker discovery and for guiding precision oncology therapies in HNSCCs.

A novel anoikis-related gene signature predicts prognosis in patients with head and neck squamous cell carcinoma and reveals immune infiltration

Background: Head and neck squamous cell carcinoma (HNSCC) is a highly aggressive disease with a poor prognosis for advanced tumors. Anoikis play a key role in cancer metastasis, facilitating the detachment and survival of cancer cells from the primary tumor site. However, few studies have focused on the role of anoikis in HNSC, especially on the prognosis. Methods: Anoikis-related genes (ANRGs) integrated from Genecards and Harmonizome portals were used to identify HNSCC subtypes and to construct a prognostic model for HNSCC patients. Also, we explored the immune microenvironment and enrichment pathways between different subtypes. Finally, we provide clinical experts with a novel nomogram based on ANRGs, with DCA curves indicating the potential clinical benefit of the model for clinical strategies. Results: We identified 69 survival-related HNSCC anoikis-related DEGs, from which 7 genes were selected to construct prognostic models. The prognostic risk score was identified as an independent prognostic factor. Functional analysis showed that these high and low risk groups had different immune status and drug sensitivity. Next risk scores were combined with HNSCC clinicopathological features together to construct a nomogram, and DCA analysis showed that the model could benefit patients from clinical treatment strategies. Conclusion: The predictive seven-gene signature and nomogram established in this study can assist clinicians in selecting personalized treatment for patients with HNSCC.