Overall Survival Of Head And Neck Squamous Cell Carcinoma Patients Research Articles

Comprehensive bioinformatic profiling of matrix metalloproteinases and their inhibitors: Expression and interaction patterns in head and neck cancer toward predictive biomarkers and personalized therapies

ObjectiveMatrix metalloproteinases (MMPs) and Tissue inhibitors of metalloproteinases (TIMPs) are involved in the turnover of extracellular matrix (ECM) components. Overexpression of MMPs facilitates tumour progression by promoting ECM turnover, angiogenesis, and cell migration. Head and neck squamous cell carcinoma (HNSCC) exhibits significant upregulation of multiple MMPs and TIMPs, correlating with poor prognosis, using bioinformatics tools to analyse the expression profiles and prognostic significance of MMPs and TIMPs in HNSCC. Materials and methodsGEPIA and UALCAN databases were used to analyse the expression of MMPs and TIMPs in HNSCC tissues. Immunohistochemistry confirmed high protein levels of several MMPs in tumour samples. GeneMANIA, STRING, and Metascape analyses highlighted key functional relationships and pathways enriched in MMPs and TIMPs. Kaplan-Meier survival analyses were conducted to assess the prognostic significance of TIMPs in HNSCC. ResultsThe study found significant overexpression of MMP1, MMP2, MMP3, MMP9, and MMP14 in HNSCC tissues. Immunohistochemistry confirmed elevated protein levels of these MMPs in tumour samples. PPI network analyses indicated crucial interactions among MMPs and their regulatory pathways. TIMP1 was significantly upregulated in HNSCC, while TIMP3 downregulation correlated with increased MMP activity and tumour progression. According to Kaplan-Meier survival analyses, higher TIMP expression was associated with poor overall survival in HNSCC patients. ConclusionThis comprehensive study emphasises the dysregulation of MMPs and TIMPs in HNSCC, proposing them as potential biomarkers for early diagnosis and prognostic evaluation and suggesting them as therapeutic targets to improve clinical outcomes in HNSCC patients.

The expression of immune co-stimulators as a prognostic predictor of head and neck squamous cell carcinomas and oral squamous cell carcinomas

Background/purposeT cells require second immune checkpoint molecules for activation and immune memory after antigen presentation. We found that inducible co-stimulator (ICOS) has been a favorable prognostic factor amongst B7 immune checkpoint co-stimulators (ICSs) families in head and neck squamous cell carcinoma (HNSCC) and oral SCC (OSCC). Materials and methodsThis study analyzed the expression of non-B7 tumor necrosis factor (TNF) superfamily ICSs in the Cancer Genome Atlas (TCGA) HNSCC cohort, our OSCC cohort, and TCGA pan-cancer datasets. The correlation in expression, prognosis, and immune status was assessed. ResultsThe higher expression of CD27, CD30, CD40L, death domain 3 (DR3), and OX40, presumably on the T cell surface, defined better overall survival of HNSCC patients. Besides, CD27, CD30, CD40L, and OX40 were highly correlated with ICOS expression in tumors. CD27, CD40L, and DR3 expression are higher in HPV+ HNSCC tumors than in HPV- tumors. The combined expression level of CD27/OX40 or CD27/CD40L/OX40 enables the potent survival prediction of small, less nodal involvement, early stage, and HPV + tumor subsets. Tumors expressing high CD27, CD30, CD40L, ICOS, and OX40 exhibited enhanced immune cell infiltration. The high correlation in the expression of these ICSs was also noted in the vast majority of tumor types in TCGA datasets. ConclusionThe findings of this study not only confirm the potential of the concordant stimulation of CD27, CD30, CD40L, ICOS, and OX40 as a crucial strategy in cancer immunotherapy but also inspire further exploration into the field, highlighting the promising future of cancer treatment.

ACTN1 promotes HNSCC tumorigenesis and cisplatin resistance by enhancing MYH9-dependent degradation of GSK-3β and integrin β1-mediated phosphorylation of FAK

BackgroundHead and neck squamous cell carcinoma (HNSCC) is one of the most common malignant tumors globally. Understanding the molecular basis of tumor progression and drug resistance can offer innovative strategies to enhance clinical outcomes for HNSCC patients.MethodsThe cytoskeletal remodeling genes associated with cisplatin resistance were screened using a PCR array. The role of alpha-actinin 1 (ACTN1) in modulating cisplatin resistance and tumorigenesis in HNSCC was evaluated both in vitro and in vivo. Co-immunoprecipitation (Co-IP), IP-mass spectrometry (MS), western blotting, dual-luciferase assay, and bioinformatics analysis were performed to elucidate the underlying mechanisms involved.ResultsOur study identifies ACTN1 as a crucial contributor to cisplatin resistance and tumorigenesis in HNSCC, as evidenced across cellular, animal, and patient-derived xenograft models. From a clinical perspective, overexpression of ACTN1 significantly correlates with a suboptimal response to neoadjuvant chemotherapy and reduced overall survival in HNSCC patients. Mechanistically, ACTN1 predominantly activates β-catenin-mediated signaling by promoting the interaction between myosin heavy chain 9 (MYH9) and GSK-3β, leading to the ubiquitin-dependent degradation of GSK-3β. ACTN1 also interacts with integrin β1, subsequently activating the FAK/PI3K/AKT pathway, providing an additional avenue for the activation of β-catenin signaling. Our study also unveils that the β-catenin/c-Myc axis transcriptionally regulates ACTN1, thereby creating a positive feedback loop promoting HNSCC tumorigenesis and drug resistance.ConclusionsThese insights underscore the novel mechanisms that highlight ACTN1's pivotal role in driving HNSCC progression and resistance to chemotherapy, suggesting ACTN1 as a promising therapeutic target in HNSCC management.

MTDH enhances radiosensitivity of head and neck squamous cell carcinoma by promoting ferroptosis based on a prognostic signature.

Ionizing radiation (IR) induces ferroptosis in head and neck squamous cell carcinoma (HNSCC). But, it remains unclear whether ferroptosis affects the prognosis of HNSCC patients after receiving radiotherapy. This study aims to develop a ferroptosis signature to predict the radiosensitivity and prognosis of HNSCC. Ferroptosis-related genes, clinical data and RNA expression profiles were obtained from the FerrDb database, The Cancer Genome Atlas and GEO database. Prognostic genes were identified by random survival forest, univariate Cox regression, Kaplan-Meier and ROC analyses. Principal component analysis, multivariate Cox regression, nomogram and DCA analyses were conducted to estimate its predictive ability. Functional enrichment and immune-related analyses were performed to explore potential biological mechanisms and tumor immune microenvironment. The effect of the hub gene on ferroptosis and radiosensitivity was verified using flow cytometry, quantitative real-time PCR and clonogenic survival assay. We constructed a ferroptosis-related signature, including IL6, NCF2, metadherin (MTDH) and CBS. We classified patients into high-risk (HRisk) and low-risk groups according to the risk scores. The risk score was confirmed to be an independent predictor for overall survival (OS). Combining the clinical stage with the risk score, we established a predictive nomogram for OS. Furthermore, pathways related to tumorigenesis and tumor immune suppression were mainly enriched in HRisk. MTDH was verified to have a potent effect on IR-induced ferroptosis and consequently promoted radiosensitivity. We constructed a ferroptosis-related signature to predict radiosensitivity and OS in HNSCC patients. MTDH was identified as a promising therapeutic target in radioresistant HNSCC patients.

Analysis of the relationship between GLUT family in the progression and immune infiltration of head and neck squamous carcinoma

Head and neck squamous cell carcinoma (HNSCC) causes much health and economic burden, and the therapeutic results must be improved. Glucose metabolism is an essential component of tumor metabolism and is instrumental in its development. Glucose transporter types (GLUTs) can uptake glucose from the extracellular matrix (ECM), regulating cellular metabolism in several cancers. However, the function of different GLUT proteins in HNSCC remains unclear. To clarify the role of GLUTs in HNSCC, several open-access online databases (Oncomine, GEPIA, Kaplan–Meier, cBioPortal, GeneMANIA, and TIMER) were used to evaluate the differential expression, clinical significance, genetic alteration, and relative immune cell infiltration. The expression of GLUTs was detected in clinical patient samples by immunohistochemistry. The mRNA level of SLC2A1/3 significantly increased in HNSCC, while SLC2A4 reduced. SLC2A3 was related to the advanced clinical stage and short overall survival (OS) in HNSCC. Also, higher SLC2A1/2 mRNA expression was related to shorter OS in HNSCC patients. The expression of GLUTs was related to diverse immune cells, including B cells, CD4+ T cells, CD8+ T cells, dendritic cells (DCs), macrophages, and Treg cells in HNSCC. Moreover, the high expression of GLUTs was demonstrated by immunohistochemistry in patient tissues. GLUTs might have a potential role in HNSCC's progression and development. Therefore, the current findings might offer a novel perception for selecting GLUT family prognostic markers and treatment for HNSCC patients.

Evaluation of the MVCT-based radiomic features as prognostic factor in patients with head and neck squamous cell carcinoma

BackgroundMegavoltage computed tomography (MVCT) images acquired during each radiotherapy session may be useful for delta radiomics. However, no studies have examined whether the MVCT-based radiomics has prognostic power. Therefore, the purpose of this study was to examine the prognostic power of the MVCT-based radiomics for head and neck squamous cell carcinoma (HNSCC) patients.Methods100 HNSCC patients who received definitive radiotherapy were analyzed and divided into two groups: training (n = 70) and test (n = 30) sets. MVCT images obtained using TomoTherapy for the first fraction of radiotherapy and planning kilovoltage CT (kVCT) images obtained using Aquilion LB CT scanner were analyzed. Primary gross tumor volume (GTV) was propagated from kVCT to MVCT images using rigid registration, and 107 radiomic features were extracted from the GTV in MVCT and kVCT images. Least absolute shrinkage and selection operator (LASSO) Cox regression model was used to examine the association between overall survival (OS) and rad score calculated for each patient by weighting the feature value through the coefficient when features were selected. Then, the predictive values of MVCT-based and kVCT-based rad score and patient-, treatment-, and tumor-specific factors were evaluated.ResultsC-indices of the rad score for MVCT- and kVCT-based radiomics were 0.667 and 0.685, respectively. The C-indices of 6 clinical factors were 0.538–0.622. The 3-year OS was significantly different between high- and low-risk groups according to the MVCT-based rad score (50% vs. 83%; p < 0.01).ConclusionsOur results suggested that MVCT-based radiomics had stronger prognostic power than any single clinical factor and was a useful prognostic factor when predicting OS in HNSCC patients.

Multi-Omics Identification of Genetic Alterations in Head and Neck Squamous Cell Carcinoma and Therapeutic Efficacy of HNC018 as a Novel Multi-Target Agent for c-MET/STAT3/AKT Signaling Axis.

Amongst the most prevalent malignancies worldwide, head and neck squamous cell carcinoma (HNSCC) is characterized by high morbidity and mortality. The failure of standard treatment modalities, such as surgery, radiotherapy, and chemotherapy, demands the need for in-depth understanding of the complex signaling networks involved in the development of treatment resistance. A tumor's invasive growth and high levels of intrinsic or acquired treatment resistance are the primary causes of treatment failure. This may be a result of the presence of HNSCC's cancer stem cells, which are known to have self-renewing capabilities that result in therapeutic resistance. Using bioinformatics methods, we discovered that elevated expressions of MET, STAT3, and AKT were associated with poor overall survival in HNSCC patients. We then evaluated the therapeutic potential of our newly synthesized small molecule HNC018 towards its potential as a novel anticancer drug. Our computer-aided structure characterization and target identification study predicted that HNC018 could target these oncogenic markers implicated in HNSCC. Subsequently, the HNC018 has demonstrated its anti-proliferative and anticancer activities towards the head and neck squamous cell carcinoma cell lines, along with displaying the stronger binding affinities towards the MET, STAT3, and AKT than the standard drug cisplatin. Reduction in the clonogenic and tumor-sphere-forming ability displays HNC018's role in decreasing the tumorigenicity. Importantly, an vivo study has shown a significant delay in tumor growth in HNC018 alone or in combination with cisplatin-treated xenograft mice model. Collectively with our findings, HNC018 highlights the desirable properties of a drug-like candidate and could be considered as a novel small molecule for treating head and neck squamous cell carcinoma.

Use of machine learning derived features from CT and H&amp;E whole-slide images to predict overall survival in head and neck squamous cell carcinoma.

6086 Background: Computed tomography (CT) and H&amp;E whole-slide images (WSI) have been found to carry rich prognostic information for patients diagnosed with head and neck squamous cell carcinoma (HNSCC). However, most machine learning models aimed for outcome prediction only took advantage of single image modality. In this work, we developed and validated a prognostic machine learning method incorporating both CT and WSI to predict overall survival in HNSCC patients. Methods: Matched radiographic CT scans and digitized WSI were acquired from the Cleveland Clinic for 167 HNSCC patients, including 120 HPV-associated oropharyngeal cancer and 47 laryngeal cancer. Both primary tumor and the largest suspicious lymph node were annotated on CT scans and primary tumor was delineated on H&amp;E WSI. We split the dataset into training and validation set using a 7:3 ratio, which resulted in 119 patients in the training set and 48 for hold-out validation. We applied a machine learning model (M_ML) using both CT and WSI as input to perform end-to-end predictions of overall survival. We used the harrell’s concordance index (C-index) to evaluate the prognostic performance. Finally, we performed the multivariable cox proportional hazard analysis adjusting for clinicopathological variables (i.e. age, gender, smoking pack-year [PY], AJCC 7th edition overall stage, and treatment modality) to validate the independent prognostic significance of the model. Results: The combined machine learning model M_ML (C-index = 0.81) outperformed the model using CT images alone (C-index = 0.63) and WSI alone (C-index = 0.64) on the validation set. In multivariable analysis, M_ML is still statistically significant accounting for clinicopathologic factors (p = 0.0007). Conclusions: This pilot study shows that a multi-omic machine learning model utilizing both radiographic CT and digitized WSI can predict HNSCC overall survival and outperforms models using only a single modality. [Table: see text]

Prognostic biomarker GSTK1 in head and neck squamous cell carcinoma and its correlation with immune infiltration and DNA methylation.

Background: Glutathione S-transferase kappa 1 (GSTK1) is critical in sarcoma and breast cancer (BRCA) development. However, the clinical significance of GSTK1 in head and neck squamous cell carcinoma (HNSC) remains unclear. This study is the first investigation into the role of GSTK1 in HNSC. Methods: All original data were downloaded from the Cancer Genome Atlas (TCGA) dataset and verified by R Base Package 4.2.0. The expression of GSTK1 in various cancers was explored with TIMER and TCGA databases. Prognostic value of GSTK1 was analyzed via survival module of Kaplan-Meier plotter and Human Protein Atlas database and Cox regression analysis. The association between GSTK1 and clinical features was evaluated by Wilcoxon signed-rank test and logistic regression analysis. The relationship between GSTK1 and immune infiltration and methylation level was further explored. The expression of GSTK1 and its correlation with immune cell infiltration was verified by Immunohistochemical staining (IHC). Results: GSTK1 was lower in HNSC, BRCA, Lung squamous cell carcinoma, and Thyroid carcinoma than in para-carcinoma. Low GSTK1 expression was associated with worse overall survival in Bladder urothelial carcinoma, Kidney renal papillary cell carcinoma, BRCA, and HNSC. However, only in BRCA and HNSC, GSTK1 expression in tumors was lower than that in normal tissues. Cox regression analyses confirmed that GSKT1 was an independent prognostic factor of overall survival in HNSC patients. The decrease in GSTK1 expression in HNSC was significantly correlated with high T stage and smoker history. IHC showed that the expression level of GSTK1 in HNSC was lower than that in para-carcinoma. In addition, GSEA showed that three pathways related to immune infiltration were positively correlated, while two pathways related to DNA methylation were negatively correlated with expression of GSTK1. Further analysis showed that GSTK1 was moderately positively correlated with the infiltration level of T cells and Cytotoxic cells, which was further confirmed by IHC. The methylation level of GSTK1 was associated with prognosis in patients with HNSC. Conclusion: Low GSTK1 expression may be a potential molecular marker for poor prognosis in HNSC and provide new insight for the development of diagnostic marker or therapeutic target.

NLRP3 in tumor-associated macrophages predicts a poor prognosis and promotes tumor growth in head and neck squamous cell carcinoma.

The NOD-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome plays cell- and tissue-specific roles in cancer, meaning that its activation in different tumors or cells may play different roles in tumor progression. We have previously described the tumor-promoting function of tumor-intrinsic NLRP3/IL-1β signaling in head and neck squamous cell carcinoma (HNSCC), but its role in immune cells remains unclear. In this study, we found that NLRP3 was highly expressed in tumor-associated macrophages (TAMs) in both mouse and human HNSCC, and the expression of NLRP3 was positively correlated with the density of TAMs according to immunohistochemistry, immunofluorescence, and flow cytometry analyses. Importantly, the number of NLRP3high TAMs was related to worse overall survival in HNSCC patients. Knocking out NLRP3 inhibited M2-like macrophage differentiation in vitro. Moreover, the carcinogenic effect induced by 4-nitroquinoline-1-oxide was decreased in Nlrp3-deficient mice, which had smaller tumor sizes. Genetic depletion of NLRP3 reduced the expression of protumoral cytokines, such as IL-1β, IL-6, IL-10, and CCL2, and suppressed the accumulation of TAMs and myeloid-derived suppressor cells (MDSCs) in mouse HNSCC. Thus, activation of NLRP3 in TAMs may contribute to tumor progression and have prognostic significance in HNSCC.

A novel nomogram and risk classification system for predicting overall survival in head and neck squamous cell cancer with distant metastasis at initial diagnosis.

Head and neck squamous cell carcinoma (HNSCC) is one of the most invasive cancer types globally, and distant metastasis (DM) is associated with apoor prognosis. The objective of this study was designed to construct a novel nomogram and risk classification system to predict overall survival (OS) in HNSCC patients presenting with DM at initial diagnosis. HNSCC patients with initially diagnosed DM between 2010 and 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Firstly, all patients were randomly assigned to atraining cohort and validation cohort (8:2), respectively. The Cox proportional hazards regression model was used to analyze the prognostic factors associated withOS. Then, the nomogram based on the prognostic factors and the predictive ability of the nomogram were assessed by the calibration curves, receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Finally, a risk classification system was established according to the nomogram scores. A total of 1240 patients initially diagnosed with HNSCC with DM were included, and the 6-, 12- and 18-month OS of HNSCC with DM were 62.7%, 40.8% and 30%, respectively. The independent prognostic factors for HNSCC patients with DM included age, marital status, primary site, T stage, N stage, bone metastasis, brain metastasis, liver metastasis, lung metastasis, surgery, radiotherapy and chemotherapy. Based on the independent prognostic factors, a nomogram was constructed to predict OS in HNSCC patients with DM. The C-index values of the nomogram were 0.713 in the training cohort and 0.674 in the validation cohort, respectively. The calibration curves and DCA also indicated the good predictability of the nomogram. Finally, a risk classification system was built and it revealed a statistically significant difference among the three groups of patients according to the nomogram scores. Factors associated with the overall survival of HNSCC patients with DM were found. According to the identified factors, we generated a nomogram and risk classification system to predict the OS of patients with initially diagnosed HNSCC with DM. The prognostic nomogram and risk classification system can help to assess survival time and provide guidance when making treatment decisions for HNSCC patients with DM.

The CC ligand chemokine family members CCL17/CCL22 predict the survival and response to immune checkpoint blockade therapy of patients with head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is considered an immunosuppressive malignancy. Cross-talk between cancer cells and immune cells is modulated in part by CC ligand (CCL) chemokines, having a major effect on tumor progression. However, the predictive value and function of CCL family members in HNSCC have not been elucidated. Here, the predictive value of CCL members in cancer prognosis and Immune checkpoint blockade therapy response was investigated. CCL17 and CCL22 were screened as the key CCL chemokines in HNSCC through co-expression analysis. Further, the correlation between CCL17/CCL22 expression and cancer immune infiltration were evaluated based on TIMER and were validated by a set of scRNA-seq data. Moreover, the expression level of CCL17/CCL22 we evaluated to predict the response to Immune checkpoint blockade therapy in a panel of cancer types by using the TIDE database. Results indicated that CCL17/CCL22 had a high co-expression correlation and had a marginally statistical significance with the overall survival in HNSCC patients (P value = 0.057 and 0.055, respectively). Our findings showed high expression of CCL17/CCL22 was positively correlated with CD4+ T cell infiltration levels in HNSCCs and activate mTORC1 signaling pathway in CD4+ T cells. Further analysis from TIDE showed the high expression of CCL17/CCL22 might predict favorable responses to immune checkpoint blockade therapy in HNSCC patients. These findings provide an insight into the predictive roles of CCL17/CCL22 in HNSCC.

Immune Infiltration-Related ceRNA Network Revealing Potential Biomarkers for Prognosis of Head and Neck Squamous Cell Carcinoma.

Background Head and neck squamous cell carcinoma (HNSCC) is a frequently lethal malignancy, and the mortality is considerably high. The tumor microenvironment (TME) has been identified as a critical participation in cancer development, treatment, and prognosis. However, competing endogenous RNA (ceRNA) networks grouping with immune/stromal scores of HNSCC patients need to be further illustrated. Therefore, our study aimed to provide clues for searching promising prognostic markers of TME in HNSCC. Materials and Methods ESTIMATE algorithm was used to calculate immune scores and stromal scores of the enrolled HNSCC patients. Differentially expressed genes (DEGs), lncRNAs (DELs), and miRNAs (DEMs) were identified by comparing the expression difference between high and low immune/stromal scores. Then, a ceRNA network and protein-protein interaction (PPI) network were constructed for selecting hub regulators. In addition, survival analysis was performed to access the association between immune scores, stromal scores, and differentially expressed RNAs in the ceRNA network and the overall survival (OS) of HNSCC patients. Then, the GSE65858 datasets from Gene Expression Omnibus (GEO) database was used for verification. At last, the difference between the clinical characteristics and immune cell infiltration in different expression groups of IL10RA, PRF1, and IL2RA was analyzed. Results Survival analysis showed a better OS in the high immune score group, and then we constructed a ceRNA network composed of 97 DEGs, 79 DELs and 22 DEMs. Within the ceRNA network, FOXP3, IL10RA, STAT5A, PRF1, IL2RA, miR-148a-3p, miR-3065-3p, and lncRNAs, including CXCR2P1, HNRNPA1P21, CTA-384D8.36, and IGHV1OR15-2, were closely correlated with the OS of HNSCC patients. Especially, using the data from GSE65858, we successfully verified that IL10RA, PRF1, and IL2RA were not only significantly upregulated in patients high immune scores, but also their high expressions were associated with longer survival time. In addition, stratified analysis showed that PRF1 and IL2RA might be involved in the mechanism of tumor progress. Conclusion In conclusion, we constructed a ceRNA network related to the TME of HNSCC, which provides candidates for therapeutic intervention and prognosis evaluation.

Potential Role of miR-196a and miR-196b as Prognostic Biomarkers of Survival in Head and Neck Squamous Cell Carcinoma: A Systematic Review, Meta-Analysis and Trial Sequential Analysis.

The etiopathogenetic mechanisms involving tumor genesis, including alteration of cell proliferation, apoptosis, invasion, migration, and death, may lead to alterations in microRNAs (miR) expression. The hypothesis is that with the presence in the literature of recent studies conducted on miR-196a and miR-196b, it is possible to clearly determine, by aggregating the results, whether miR-196 upregulation in head and neck squamous cell carcinoma (HNSCC) tissues can represent a prognostic biomarker of survival through hazard ratio (HR) analysis. The systematic review was conducted following the indications of the PRISMA, and four electronic databases were used (Science Direct, SCOPUS, PubMed, and Cochrane Central), with the addition of gray literature. Combinations of keywords were used, such as miR-196, miR-196 AND HNSCC, microRNA AND HNSCC, LSCC AND miR-196, OSCC AND miR-196, OPSCC AND miR-196, HSCC AND miR-196. The meta-analysis and trial sequential analysis (TSA) were performed using RevMan 5.41 software and Stata 13 (StataCorp, College Station, TX, USA) with the implementation of the R 4.2 software. This search identified 1593 reports and, at the end of the selection, five articles were inserted. The results of the meta-analysis report an aggregate HR for overall survival (OS), between the highest and lowest miR-196 expression of 1.67, 95% CI: [1.16, 2.49]. In this meta-analysis, we found that the forest plot is in favor of higher OS in HNSCC patients, compared with the control, with low miR-196 expression, correlating this data with a favorable prognosis, which indicated the potential role of this miRNA in strengthening the therapy sensitiveness of the HNSCC patients. Consequently, the present systematic review places itself, together with other systematic reviews on this topic, in a key role to the finding of Phase 3 clinical trials studies, in search for a prognostic model of miR-196 for HNSCC. In conclusion, with the limitations of the meta-analysis, it can be argued that miRs of the miR-196 family could be independent prognostic biomarkers of survival for HNSCC.

S100A10 might be a novel prognostic biomarker for head and neck squamous cell carcinoma based on bioinformatics analysis

Head and neck squamous cell carcinoma (HNSCC) is a frequent malignant tumor of the head and neck with a dismal survival probability due to relapse and metastasis. S100As have been identified as being involved in the tumor procession of various cancer types. However, the expressions of S100As in HNSCC and their prognostic relevance are unknown. Bioinfromatics analysis was conducted to identify the prognostic value and function of S100As in HNSCC patients. In the study, we found that high mRNA expression levels of S100A3, S100A4, S100A7A, S100A9, and low mRNA expression levels of S100A1, S100A10 were related with a good overall survival in HNSCC patients. Importantly, the prognosis model suggested that S100A10 may have a certain impact on the development of HNSCC. Moreover, single-cell RNA sequencing analysis clarified that the specific functions of S100A10 had positive regulatory effects on metastasis, blood vessel generation, EMT, hypoxia, and invasion. Our findings implied that S100A10 might be a new prognostic biomarker for HNSCC, and played a role in promoting the occurrence, and development of HNSCC.

Abstract 6221: Tandem use of multi-omics and artificial intelligence identified novel prognostic and therapeutic biomarkers for head and neck squamous cell carcinoma

Abstract Introduction: Head and neck squamous cell carcinoma (HNSCC) is categorized into Human Papilloma Virus positive (HPV+ve) and negative (HPV-ve) tumors, with the latter being more aggressive and displaying poor overall survival (OS). There is a need to identify aggressive biomarkers for patient stratification and improved patient care. Materials and Methods: Using the multi-omics data, including somatic mutations, copy number alterations, RNA sequencing, miRNA sequencing, and methylation from 513 HNSCC patients, we performed an integrative clustering analysis to differentiate HPV+ve and HPV-ve tumors and identify novel prognostic biomarkers for survival and treatment response. Using artificial intelligence (AI) based machine learning approach by implementing scikit-learn, we developed a model to predict the patient's OS. Results: Our clustering analysis robustly segregated HNSCC patients into HPV+ve and HPV-ve tumors. Artificial intelligence-based machine learning model identified a 30 gene signature panel specific to HPV-ve tumors precisely predicting poor OS with an accuracy of 90.5±0.8% (95% CI) and AUC of 80.2%. Furthermore, the multivariate Cox regression survival model identified 12 genes as independent prognostic biomarkers in HPV-ve tumors, including overexpression of novel genes NT5E and TRIML2. Interestingly, higher expression of NT5E and TRIML2 due to promoter hypomethylation predicted therapy resistance in 62.8% and 65.1% of HNSCC patients, respectively. The prognostic signature panel of 30 genes was further validated using three additional expression data sets (n = 450) of HNSCC. Conclusion: Our multi-omics and AI analysis revealed a novel HPV-ve molecular cluster with implications for predicting disease aggressiveness, therapeutic response, and OS in HNSCC patients. Citation Format: Ajaz A. Bhat, Tariq Masoodi, Deepika Mishra, Mayank Singh, Sabah Nisar, Sheema Hashem, Sana K. Baba, Puneet Bagga, Ravinder Reddy, Davide Bedognetti, Shahab Uddin, Wael El-Rifai, Muzafar A. Macha, Mohammad Haris. Tandem use of multi-omics and artificial intelligence identified novel prognostic and therapeutic biomarkers for head and neck squamous cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6221.

Identification of pyroptosis-related gene prognostic signature in head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) is a life-threatening disease with poor prognosis. Pyroptosis has been recently disclosed as a programmed cell death triggered by invasive infection, involved in cancer development. However, the prognosis role of pyroptosis-related genes in HNSCC has not been discussed. The RNA sequence data of pyroptosis-related genes were obtained from The Cancer Genome Atlas (TCGA) database. Cox regression and the least absolute shrinkage and selection operator (LASSO) analysis were performed to screen the HNSCC survival-related signature genes. We established a HNSCC risk model with the identified prognostic genes, then divided the HNSCC patients into low- and high-risk subgroups according to median risk score. Moreover, we utilized Gene Expression Omnibus (GEO) dataset to validate the risk model. Go and KEGG analyses were conducted to reveal the potential function of differential expression of genes that identified between low- and high-risk subgroups. ESTIMATE algorithm was performed to investigate the immune infiltration of tumors. Correlation between signature gene expression and drug-sensitivity was disclosed by Spearman's analysis. We constructed a HNSCC risk model with identified seven pyroptosis-related genes (CASP1, GSDME, IL6, NLRP1, NLRP2, NLRP6, and NOD2) as prognostic signature genes. High-risk subgroup of HNSCC patients in TCGA cohort correlated with lower survival probability than patients from low-risk subgroup (p < .001), and the result is verified with GEO dataset. In addition, 161 genes were identified differentially expressed between the low- and high-risk subgroups in the TCGA cohort, mainly related to immune response. Higher PD-L1 expression level was found in the high-risk subgroup that indicated the possible employment of immune checkpoint inhibitors. IL6 was positively correlated with WZ3105 and MPS-1-IN-1 in the cancer therapeutics response portal database. We built and verified a risk model for HNSCC prognosis using seven pyroptosis-related signature genes, which could predict the overall survival of HNSCC patients and facilitate treatment.

CD3D: a prognostic biomarker associated with immune infiltration and immunotherapeutic response in head and neck squamous cell carcinoma

ABSTRACT Recent studies have demonstrated that CD3D activates T-cell-related signal transduction and is associated with the antitumor immune response in several cancers. This study explored the role of CD3D in head and neck squamous cell carcinoma (HNSCC). A total of 499 HNSCC tissues and 44 normal controls were acquired from The Cancer Genome Atlas as the training cohort. GSE65858 included 270 HNSCC patients and was obtained from the Gene Expression Omnibus database as the test cohort. Overall, 172 HNSCC patients were collected as the validation cohort. CD3D expression in the validation cohort was measured by quantitative real-time polymerase chain reaction. The Kaplan–Meier plot revealed that high CD3D expression was associated with longer overall survival in HNSCC patients. Univariate and multivariate analyses showed that CD3D expression was an independent prognostic factor for HNSCC patients, which was confirmed in the test cohort and validation cohort. Furthermore, GO, KEGG, and GSEA analyses revealed the association of CD3D with immune-related pathways. Subsequently, ESTIMATE analysis showed the association between CD3D and the tumor microenvironment, while ssGSEA showed a remarkable positive link between CD3D and immune-related functions. Multiple algorithms demonstrated that high CD3D expression was associated with more immune effector cell infiltration. Finally, the tumor immune dysfunction and exclusion (TIDE) score and immunophenoscore (IPS) showed that patients with high CD3D could benefit from immunotherapy. In summary, CD3D was an independent favorable prognostic biomarker and correlated with immune cell infiltration and immune-related function, as well as an efficient indicator of immunotherapy response for HNSCC patients.

EGFR Mutations in Head and Neck Squamous Cell Carcinoma.

EGFR is a prototypical receptor tyrosine kinase that is overexpressed in multiple cancers including head and neck squamous cell carcinoma (HNSCC). The standard of care for HNSCC remains largely unchanged despite decades of research. While EGFR blockade is an attractive target in HNSCC patients and anti-EGFR strategies including monoclonal antibodies and kinase inhibitors have shown some clinical benefit, efficacy is often due to the eventual development of resistance. In this review, we discuss how the acquisition of mutations in various domains of the EGFR gene not only alter drug binding dynamics giving rise to resistance, but also how mutations can impact radiation response and overall survival in HNSCC patients. A better understanding of the EGFR mutational landscape and its dynamic effects on treatment resistance hold the potential to better stratify patients for targeted therapies in order to maximize therapeutic benefits.

Identification of key genes for HNSCC from public databases using bioinformatics analysis

BackgroundThe cause and underlying molecular mechanisms of head and neck squamous cell carcinoma (HNSCC) are unclear. Our study aims to identify the key genes associated with HNSCC and reveal potential biomarkers.MethodsIn this study, the expression profile dataset GSE83519 of the Gene Expression Omnibus database and the RNA sequencing dataset of HNSCC of The Cancer Genome Atlas were included for analysis. Sixteen differentially expressed genes were screened from these two datasets using R software. Gene Expression Profiling Interactive Analysis 2 (GEPIA2) was then adopted for survival analysis, and finally, three key genes related to the overall survival of HNSCC patients were identified. Furthermore, we verified these three genes using the Oncomine database and from real-time PCR and immunohistochemistry results from HNSCC tissues.ResultsThe expression data of 44 samples from GSE83519 and 545 samples from TCGA-HNSC were collected. Using bioinformatics, the two databases were integrated, and 16 DEGs were screened out. Gene Ontology (GO) enrichment analysis showed that the biological functions of DEGs focused primarily on the apical plasma membrane and regulation of anoikis. Kyoto Encyclopedia of Genes and Genomes (KEGG) signalling pathway analysis showed that these DEGs were mainly involved in drug metabolism-cytochrome P450 and serotonergic synapses. Survival analysis identified three key genes, CEACAM5, CEACAM6 and CLCA4, that were closely related to HNSCC prognosis. The Oncomine database, qRT–PCR and IHC verified that all 3 key genes were downregulated in most HNSCC tissues compared to adjacent normal tissues.ConclusionsThis study indicates that integrated bioinformatics analyses play an important role in screening for differentially expressed genes and pathways in HNSCC, helping us better understand the biomarkers and molecular mechanism of HNSCC.