Prognostic Value of Eight-Gene Signature in Head and Neck Squamous Carcinoma

Deciphering the prognostic potential of a necroptosis-related gene signature in head and neck squamous cell carcinoma: a bioinformatic analysis

Background

Necroptosis, an alternative mode of programmed cell death (PCD) that overcomes apoptosis resistance, has been implicated in the progression and drug resistance of cancer. The aim of this study is to find the biological and prognostic significance of necroptosis in patients with head and neck squamous cell carcinoma (HNSCC).

Methods

Integrated clinical datasets from The Cancer Genome Atlas (TCGA) HNSCC cohort underwent analysis. R package "DESeq2" was used to conduct differential gene expression analysis between normal and tumor tissues in the cohort, resulting in the identification of 2,172 differentially expressed genes (DEGs). A total of 159 necroptosis-related genes (NRGs) were extracted and performed a Venn analysis to identify the optimal necroptosis-related DEGs, resulting in the selection of 25 genes specifically associated with necroptosis in HNSCC. Then prognostic analyze, Cox regression analysis and prognostic model were demonstrated the ability to predict the extent of immunological infiltration in HNSCC.

Results

Among these DEGs, five genes (FADD, H2AZ1, PYGL, JAK3, and ZBP1) were found to have prognostic value (P<0.05). Then, bioinformatic analyses were conducted, and the biological and clinical significance of these five genes were demonstrated. Furthermore, Cox regression analysis was performed to develop a prognostic gene model based on these genes, which effectively classified HNSCC patients into low- or high-risk groups. The prognostic model also demonstrated the ability to predict the extent of immunological infiltration in HNSCC. Additionally, a predictive nomogram based on the clinicopathological features of these five prognostic DEGs was constructed.

Conclusions

We performed a systematic bioinformatic analysis to identify necroptosis-related prognostic genes in HNSCC patients. These genes' prognostic value was synthesized into a predictive nomogram for forecasting HNSCC progression.

Deciphering a Prognostic Signature Based on Soluble Mediators Defines the Immune Landscape and Predicts Prognosis in HNSCC

BACKGROUND

The study on Head and Neck Squamous Cell Carcinoma (HNSCC), a prevalent and aggressive form of head and neck cancer, focuses on the often-overlooked role of soluble mediators. The objective is to leverage a transcriptome-based risk analysis utilizing soluble mediator-related genes (SMRGs) to provide novel insights into prognosis and immunotherapy efficacy in HNSCC patients.

METHODS

We analyzed the expression and prognostic significance of 10,859 SMRGs using 502 HNSCC and 44 normal samples from the TCGA-HNSC cohort in The Cancer Genome Atlas (TCGA). The samples were divided into training and test sets in a 7:3 ratio, with an additional external validation using 40 tumor samples from the International Cancer Genome Consortium (ICGC). Key differentially expressed genes (DEGs) with prognostic significance were identified through univariate and Lasso-Cox regression analyses. A prognostic model based on 20 SMRGs was developed using Lasso and multivariate Cox regression. We assessed the clinical outcomes and immune status in high-risk (HR) and low-risk (LR) HNSCC patients utilizing the BEST databases and single-sample Gene Set Enrichment Analysis (ssGSEA).

RESULTS

The 20 SMRGs were crucial in predicting the prognosis of HNSCC, with the SMRG signature emerging as an independent prognostic indicator. Patients classified in the HR group exhibited poorer outcomes compared to those in the LR group. A nomogram, integrating clinical characteristics and risk scores, demonstrated substantial prognostic value. Immunotherapy appeared to be more effective in the LR group, possibly attributed to enhanced immune infiltration and expression of immune checkpoints.

CONCLUSIONS

The model based on soluble mediator-associated genes offers a fresh perspective for assessing the pre-immune efficacy and showcases robust predictive capabilities. This innovative approach holds significant promise in advancing the field of precision immuno-oncology research, providing valuable insights for personalized treatment strategies in HNSCC.

Correlation analysis of plasma lipid profiles and the prognosis of head and neck squamous cell carcinoma

PURPOSE

This study aims to clarify whether blood lipid profiles are indicators of prognosis in patients with head and neck squamous cell carcinoma (HNSCC).

METHODS

This retrospective study included 512 T1/2N0M0 HNSCC patients. The correlation between blood lipid profiles and progression-free survival (PFS) and disease-specific survival (DSS) was analyzed by multivariate analysis. The data from TCGA was also analyzed to investigate the expression levels and prognostic values of different lipoprotein receptors essential for specific lipid uptake.

RESULTS

A high level of low-density lipoprotein cholesterol (LDL-C) indicated better PFS and DSS, and a low level of apolipoprotein A-I (Apo A-I) indicated better PFS, while a high level of apolipoprotein B (Apo B) indicated poorer PFS and DSS. The Apo A-I receptor gene SCARB1 was upregulated and associated with poor survival in HNSCC patients. Activation of SCARB1 was implicated in a series of tumor-promoting pathways. There was no significant correlation between the expression of LDL-C and Apo B-related receptors and prognosis.

CONCLUSION

A high level of LDL-C and a low level of Apo A-I are protective factors for HNSCC, while a high level of Apo B is a risk factor. The upregulation of SCARB1 may participate in the progression of HNSCC.

MHL-Net: A Multistage Hierarchical Learning Network for Head and Neck Multiorgan Segmentation

Accurate segmentation of head and neck organs at risk is crucial in radiotherapy. However, the existing methods suffer from incomplete feature mining, insufficient information utilization, and difficulty in simultaneously improving the performance of small and large organ segmentation. In this paper, a multistage hierarchical learning network is designed to fully extract multidimensional features, combined with anatomical prior information and imaging features, using multistage subnetworks to improve the segmentation performance. First, multilevel subnetworks are constructed for primary segmentation, localization, and fine segmentation by dividing organs into two levels-large and small. Different networks both have their own learning focuses and feature reuse and information sharing among each other, which comprehensively improved the segmentation performance of all organs. Second, an anatomical prior probability map and a boundary contour attention mechanism are developed to address the problem of complex anatomical shapes. Prior information and boundary contour features effectively assist in detecting and segmenting special shapes. Finally, a multidimensional combination attention mechanism is proposed to analyze axial, coronal, and sagittal information, capture spatial and channel features, and maximize the use of structural information and semantic features of 3D medical images. Experimental results on several datasets showed that our method was competitive with state-of-the-art methods and improved the segmentation results for multiscale organs.

Influence of tumor topography on clinical-morphological profile of laryngeal malignancies

AIM

Laryngeal cancers are redoubtable because they are still diagnosed in advanced stages which results in poor survival and the decline of life quality. The authors intend to identify if the tumor topography influences clinical behavior, the morphological profile and therapeutic strategy.

PATIENTS, MATERIALS AND METHODS

The study group included 188 patients with laryngeal malignancies diagnosed and treated in an Ear, Nose and Throat (ENT) Department. The patients have been divided into four groups according to the tumor topography and extension. Three categories of parameters were defined (epidemiological, clinical, and morphological) and analyzed comparatively between the four groups using filter scales and the χ² (chi-squared) correlation test.

RESULTS

Epidemiological parameters (sex, age, socio-economic status) showed no significant differences between the four groups. Clinical parameters (symptoms, lymphadenopathies, surgical procedures, and hospitalization) instead registered significant differences between the four groups. Morphological parameters (longitudinal diameter, transverse diameter, shape, gross aspect, histopathological aspect, grade, local invasion - pT, lymph node invasion - pN, metastases - pM and tumor stage), excepting shape, registered too significant differences between the four groups. The analysis of the whole set of parameters in each group revealed different, distinct profiles for each of the topographic groups, especially for glottic and large tumors. Our results concerning the entire series of tumors ranged in the limits of variation of each of the parameters observed in the literature.

CONCLUSIONS

Our study revealed that tumors placed in different regions of the larynx have distinct profiles from epidemiological, clinical, and morphological points of view. However, the profile of our entire group of tumors proved to be comparable with the literature data.

Circadian rhythm-related genes index: A predictor for HNSCC prognosis, immunotherapy efficacy, and chemosensitivity

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is the most common head and neck cancer and is highly aggressive and heterogeneous, leading to variable prognosis and immunotherapy outcomes. Circadian rhythm alterations in tumourigenesis are of equal importance to genetic factors and several biologic clock genes are considered to be prognostic biomarkers for various cancers. The aim of this study was to establish reliable markers based on biologic clock genes, thus providing a new perspective for assessing immunotherapy response and prognosis in patients with HNSCC.

METHODS

We used 502 HNSCC samples and 44 normal samples from the TCGA-HNSCC dataset as the training set. 97 samples from GSE41613 were used as an external validation set. Prognostic characteristics of circadian rhythm-related genes (CRRGs) were established by Lasso, random forest and stepwise multifactorial Cox. Multivariate analysis revealed that CRRGs characteristics were independent predictors of HNSCC, with patients in the high-risk group having a worse prognosis than those in the low-risk group. The relevance of CRRGs to the immune microenvironment and immunotherapy was assessed by an integrated algorithm.

RESULTS

6-CRRGs were considered to be strongly associated with HNSCC prognosis and a good predictor of HNSCC. The riskscore established by the 6-CRRG was found to be an independent prognostic factor for HNSCC in multifactorial analysis, with patients in the low-risk group having a higher overall survival (OS) than the high-risk group. Nomogram prediction maps constructed from clinical characteristics and riskscore had good prognostic power. Patients in the low-risk group had higher levels of immune infiltration and immune checkpoint expression and were more likely to benefit from immunotherapy.

CONCLUSION

6-CRRGs play a key predictive role for the prognosis of HNSCC patients and can guide physicians in selecting potential responders to prioritise immunotherapy, which could facilitate further research in precision immuno-oncology.

John M, Fuentes-Bayne H, Patel SP, Mardiros A, Xu H, Ng EW, Go WY, Wong DJ, Sunwoo JB, Welch JS. Genomic Immune Evasion: Diagnostic and Therapeutic Opportunities in Head and Neck Squamous Cell Carcinomas

Head and neck squamous cell cancers (HNSCCs) represent a diverse group of tumors emerging within different mucosal surfaces of the oral cavity, nasopharynx, oropharynx, larynx, and hypopharynx. HNSCCs share common clinical risk factors and genomic features, including smoking, alcohol, age, male sex, aneuploidy, and TP53 mutations. Viral initiating and contributing events are increasingly recognized in HNSCCs. While both Epstein-Barr Virus (EBV) and human papilloma virus (HPV) are observed, EBV is more frequently associated with nasopharyngeal cancers whereas HPV is associated with oropharyngeal cancers. HNSCCs are associated with high tumor mutational burden and loss of tumor suppressor gene function, especially in TP53 and X-linked genes. Multiple lines of evidence suggest that HNSCCs are subject to immunologic surveillance and immune-induced evolutionary pressure that correlate with negative clinical outcomes. This review will discuss genomic mechanisms related to immune-mediated pressures and propose prognostic and therapeutic implications of detectable immune escape mechanisms that drive tumorigenesis and disease progression.

Acircadian rhythm-related gene signature for predicting survival and drug response in HNSC

Head and neck squamous cell carcinoma (HNSC) represents one of the most common malignant carcinomas worldwide. Because the 5-year survival rate of patients with HNSC is poor, it is necessary to develop an effective signature for predicting the risk of HNSC. To identify a circadian rhythm (CR)-related predictive signature, we analyzed the RNA-seq data of patients with HNSC from The Cancer Genome Atlas and Gene Expression Omnibus cohorts. Nine CR-related genes (PER2, PER3, GHRL, CSF2, HDAC3, KLF10, PRKAA2, PTGDS, and RORB) were identified to develop a CR-related signature. The area under the curve values for 5-year overall survival were 0.681, 0.700, and 0.729 in the training set, validation set, and an external independent test set (GSE41613), respectively. The Kaplan‒Meier curve analysis showed that the high-risk group had a reduced relapse-free survival compared with the low-risk group in the training set, validation set, and test set (P < 0.05). Finally, we observed that the CR-related gene signature was associated with the tumor immune microenvironment, somatic nucleotide variation, and drug response in HNSC. In conclusion, we developed a circadian rhythm-related gene signature for predicting overall survival in HNSC.

An ion-channel-gene-based prediction model for head and neck squamous cell carcinoma: Prognostic assessment and treatment guidance

PURPOSE

Head and neck squamous cell carcinoma (HNSCC) is a very diverse malignancy with a poor prognosis. The purpose of this study was to develop a new signature based on 12 ion channel genes to predict the outcome and immune status of HNSCC patients.

METHODS

Clinicopathological information and gene sequencing data of HNSCC patients were generated from the Cancer Genome Atlas and Gene Expression Omnibus databases. A set of 323 ion channel genes was obtained from the HUGO Gene Nomenclature Committee database and literature review. Using univariate Cox regression analysis, the ion channel genes related to HNSCC prognosis were identified. A prognostic signature and nomogram were then created using machine learning methods. Kaplan-Meier analysis was used to explore the relevance of the risk scores and overall survival (OS). We also investigated the association between risk scores, tumor immune infiltration, and gene mutational status. Finally, we detected the expression levels of the signature genes by quantitative real-time polymerase chain reaction, western blotting, and immunohistochemistry.

RESULTS

We separated the patients into high- and low-risk groups according to the risk scores computed based on these 12 ion channel genes, and the OS of the low-risk group was significantly longer (p<0.001). The area under the curve for predicting 3-year survival was 0.729. Univariate and multivariate analyses showed that the 12-ion-channel-gene risk model was an independent prognostic factor. We also developed a nomogram model based on risk scores and clinicopathological variables to forecast outcomes. Furthermore, immune cell infiltration, gene mutation status, immunotherapy response, and chemotherapeutic treatment sensitivity were all linked to risk scores. Moreover, high expression levels of ANO1, AQP9, and BEST2 were detected in HNSCC tissues, whereas AQP5, SCNN1G, and SCN4A expression was low in HNSCC tissues, as determined by experiments.

CONCLUSION

The 12-ion-channel-gene prognostic signatures have been demonstrated to be highly efficient in predicting the prognosis, immune microenvironment, gene mutation status, immunotherapy response, and chemotherapeutic sensitivity of HNSCC patients.

Construction of the prognostic signature of alternative splicing revealed the prognostic predictor and immune microenvironment in head and neck squamous cell carcinoma

Background: Head and neck squamous cell carcinoma (HNSC) is a prevalent and heterogeneous malignancy with poor prognosis and high mortality rates. There is significant evidence of alternative splicing (AS) contributing to tumor development, suggesting its potential in predicting prognosis and therapeutic efficacy. This study aims to establish an AS-based prognostic signature in HNSC patients.

Methods: The expression profiles and clinical information of 486 HNSC patients were downloaded from the TCGA database, and the AS data were downloaded from the TCGA SpliceSeq database. The survival-associated AS events were identified by conducting a Cox regression analysis and utilized to develop a prognostic signature by fitting into a LASSO-regularized Cox regression model. Survival analysis, univariate and multivariate Cox regression analysis, and receiver operating characteristic (ROC) curve analysis were performed to evaluate the signature and an independent cohort was used for validation. The immune cell function and infiltration were analyzed by CIBERSORT and the ssGSEA algorithm.

Results: Univariate Cox regression analysis identified 2726 survival-associated AS events from 1714 genes. The correlation network reported DDX39B, PRPF39, and ARGLU1 as key splicing factors (SF) regulating these AS events. Eight survival-associated AS events were selected and validated by LASSO regression to develop a prognostic signature. It was confirmed that this signature could predict HNSC outcomes independent of other variables via multivariate Cox regression analysis. The risk score AUC was more than 0.75 for 3 years, highlighting the signature’s prediction capability. Immune infiltration analysis reported different immune cell distributions between the two risk groups. The immune cell content was higher in the high-risk group than in the low-risk group. The correlation analysis revealed a significant correlation between risk score, immune cell subsets, and immune checkpoint expression.

Conclusion: The prognostic signature developed from survival-associated AS events could predict the prognosis of HNSC patients and their clinical response to immunotherapy. However, this signature requires further research and validation in larger cohort studies.

Natural killer cell-related prognosis signature characterizes immune landscape and predicts prognosis of HNSCC

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC), the most common head and neck cancer, is highly aggressive and heterogeneous, resulting in variable prognoses and immunotherapeutic outcomes. Natural killer (NK) cells play essential roles in malignancies' development, diagnosis, and prognosis. The purpose of this study was to establish a reliable signature based on genes related to NK cells (NRGs), thus providing a new perspective for assessing immunotherapy response and prognosis of HNSCC patients.

METHODS

In this study, NRGs were used to classify HNSCC from the TCGA-HNSCC and GEO cohorts. The genes were evaluated using univariate cox regression analysis based on the differential analysis of normal and tumor samples in TCGA-HNSCC conducted using the "limma" R package. Thereafter, we built prognostic gene signatures using LASSO-COX analysis. External validation was carried out in the GSE41613 cohort. Immunity analysis based on NRGs was performed via several methods, such as CIBERSORT, and immunotherapy response was evaluated by TIP portal website.

RESULTS

With the TCGA-HNSCC data, we established a nomogram based on the 17-NRGs signature and a variety of clinicopathological characteristics. The low-risk group exhibited a better effect when it came to immunotherapy.

CONCLUSIONS

17-NRGs signature and nomograms demonstrate excellent predictive performance and offer new perspectives for assessing pre-immune efficacy, which will facilitate future precision immuno-oncology research.

A Four-Gene Signature Associated with Radioresistance in Head and Neck Squamous Cell Carcinoma Identified by Text Mining and Data Analysis

Purpose

Head and neck squamous cell carcinoma (HNSCC) is the sixth leading cancer globally, and radiotherapy plays a crucial part in its treatment. This study was designed to identify potential genes related to radiation resistance in HNSCC.

Method

We first used text mining to obtain common genes related to radiotherapy resistance and HNSCC in published articles. Functional enrichment analyses were conducted to identify the significantly enriched pathways and genes. Protein and protein interactions were performed, and the most significant gene modules were determined; then, genes in the gene modules were validated at transcriptional levels and overall survival. Gene set variation analysis (GSVA) score was calculated, and the association between GSVA score and survival/pathway was estimated. Immune cell infiltration, methylation, and genetic alteration analysis of these genes was conducted in HNSCC patients. Finally, potential sensitive anticancer drugs related to target genes were obtained.

Result

We identified 583 common genes through text mining. After further validation, a four-gene signature (EPHB2, SPP1, SERPINE1, and VEGFC) was constructed. The patients with higher GSVA scores have a worse prognosis than those with lower GSVA scores. Differences in methylation of these four genes in HNSCC tumor tissue and normal tissue were compared, with higher methylation levels of EBPH2 and SPP1 in normal tissue and higher methylation levels of SERPINE1 in the tumor. Immune cell infiltration revealed that the increased expression of these genes was closely related to the infiltration level of CD4+ T cell, neutrophil, macrophage, and dendritic cell. Thirty drugs, including 22 positively and eight negatively correlated drugs that most correlated with related genes, were available for treating HNSCC.

Conclusion

In this study, we identified four potential genes as well as corresponding drugs that might be related to radioresistance in HNSCC patients. These candidate genes may provide a promising avenue to further elevate radiotherapy efficacy.

Identification of therapeutically potential targets and their ligands for the treatment of OSCC

Recent advancements in cancer biology have revealed molecular changes associated with carcinogenesis and chemotherapeutic exposure. The available information is being gainfully utilized to develop therapies targeting specific molecules involved in cancer cell growth, survival, and chemoresistance. Targeted therapies have dramatically increased overall survival (OS) in many cancers. Therefore, developing such targeted therapies against oral squamous cell carcinoma (OSCC) is anticipated to have significant clinical implications. In the current work, we have identified drug-specific sensitivity-related prognostic biomarkers (BOP1, CCNA2, CKS2, PLAU, and SERPINE1) using gene expression, Cox proportional hazards regression, and machine learning in OSCC. Dysregulation of these markers is significantly associated with OS in many cancers. Their elevated expression is related to cellular proliferation and aggressive malignancy in various cancers. Mechanistically, inhibition of these biomarkers should significantly reduce cellular proliferation and metastasis in OSCC and should result in better OS. It is pertinent to note that no effective small-molecule candidate has been identified against these biomarkers to date. Therefore, a comprehensive in silico drug design strategy assimilating homology modeling, extensive molecular dynamics (MD) simulation, and ensemble molecular docking has been applied to identify potential compounds against identified targets, and potential molecules have been identified. We hope that this study will help in deciphering potential genes having roles in chemoresistance and a significant impact on OS. It will also result in the identification of new targeted therapeutics against OSCC.

Gα12 and Gα13: Versatility in Physiology and Pathology

G protein-coupled receptors (GPCRs), as the largest family of receptors in the human body, are involved in the pathological mechanisms of many diseases. Heterotrimeric G proteins represent the main molecular switch and receive cell surface signals from activated GPCRs. Growing evidence suggests that Gα₁₂ subfamily (Gα_12/13)-mediated signaling plays a crucial role in cellular function and various pathological processes. The current research on the physiological and pathological function of Gα_12/13 is constantly expanding, Changes in the expression levels of Gα_12/13 have been found in a wide range of human diseases. However, the mechanistic research on Gα_12/13 is scattered. This review briefly describes the structural sequences of the Gα_12/13 isoforms and introduces the coupling of GPCRs and non-GPCRs to Gα_12/13. The effects of Gα_12/13 on RhoA and other signaling pathways and their roles in cell proliferation, migration, and immune cell function, are discussed. Finally, we focus on the pathological impacts of Gα_12/13 in cancer, inflammation, metabolic diseases, fibrotic diseases, and circulatory disorders are brought to focus.

Diverse Chromobox Family Members: Potential Prognostic Biomarkers and Therapeutic Targets in Head and Neck Squamous Cell Carcinoma

Background

The Chromobox (CBX) family members were involved in a variety of physiological and oncological processes through the regulation of the epigenetic modification of chromatin. However, the comprehensive analysis of the CBX family in head and neck squamous cell carcinoma (HNSC) is lacking.

Methods

In this work, we used multiple online databases and tools to investigate the roles of CBX family in aspects of gene expression, prognostic evaluation, genetic alteration, immune micro-environment of tumor, and status of methylation.

Results

The mRNA expression levels of CBX1, CBX3, and CBX5 were aberrantly increased in patients with HNSC, while CBX7 was aberrantly decreased. Higher expression of CBX7 was significantly associated with longer OS. Within the 5–11% of genetic alteration rate of CBXs, CBX3 ranked the highest and CBX5/7 ranked the lowest. SPRR1B, S100A7, CASP14, CDSN, LCE3D were the top 5 neighbor genes with the strongest association with CBXs in HNSC patients. Signaling pathways such as epidermal cell differentiation, cornification, and peptide cross-linking were demonstrated to have a strong association with CBX genes. The profiles of immune cell infiltration had high similarity for the group of HNSC patients stratified by expression of CBXs. The methylation levels of CBX1 and CBX5 significantly decreased, while that of CBX7 significantly increased in HNSC samples when compared with normal tissue.

Conclusion

In conclusion, the CBX family showed its valuation for further investigation in HNSC. Our research highlighted that CBX7 had the potential to be a novel diagnostic and prognostic biomarker for patients with HNSC.

Combination of Radiosensitivity Gene Signature and PD-L1 Status Predicts Clinical Outcome of Patients With Locally Advanced Head and Neck Squamous Cell Carcinoma: A Study Based on The Cancer Genome Atlas Dataset

Aim: The aim of our study was to investigate the potential predictive value of the combination of radiosensitivity gene signature and PD-L1 expression for the prognosis of locally advanced head and neck squamous cell carcinoma (HNSCC).

Methods: The cohort was selected from The Cancer Genome Atlas (TCGA) and classified into the radiosensitive (RS) group and radioresistant (RR) group by a radiosensitivity-related gene signature. The cohort was also grouped as PD-L1-high or PD-L1-low based on PD-L1 mRNA expression. The least absolute shrinkage and selection operator (lasso)-based Cox model was used to select hub survival genes. An independent validation cohort was obtained from the Gene Expression Omnibus (GEO) database.

Results: We selected 288 locally advanced HNSCC patients from TCGA. The Kaplan–Meier method found that the RR and PD-L1-high group had a worse survival than others (p = 0.033). The differentially expressed gene (DEG) analysis identified 553 upregulated genes and 486 downregulated genes (p < 0.05, fold change >2) between the RR and PD-L1-high group and others. The univariate Cox analysis of each DEG and subsequent lasso-based Cox model revealed five hub survival genes (POU4F1, IL34, HLF, CBS, and RNF165). A further hub survival gene-based risk score model was constructed, which was validated by an external cohort. We observed that a higher risk score predicted a worse prognosis (p = 0.0013). The area under the receiver operating characteristic curve (AUC) plots showed that this risk score model had good prediction value (1-year AUC = 0.684, 2-year AUC = 0.702, and 3-year AUC = 0.688). Five different deconvolution methods all showed that the B cells were lower in the RR and PD-L1-high group (p < 0.05). Finally, connectivity mapping analysis showed that the histone deacetylase (HDAC) inhibitor trichostatin A might have the potential to reverse the phenotype of RR and PD-L1-high in locally advanced HNSCC (p < 0.05, false discovery rate <0.1).

Conclusion: The combination of 31-gene signature and the PD-L1 mRNA expression had a potential predictive value for the prognosis of locally advanced HNSCC who had RT. The B cells were lower in the RR and PD-L1-high group. The identified risk gene signature of locally advanced HNSCC and the potential therapeutic drug trichostatin A for the RR and PD-L1-high group are worth being further studied in a prospective homogenous cohort.

Identification of the Nerve-Cancer Cross-Talk-Related Prognostic Gene Model in Head and Neck Squamous Cell Carcinoma

The incidence of head and neck squamous cell carcinoma (HNSC) is increasing year by year. The nerve is an important component of the tumor microenvironment, which has a wide range of cross-talk with tumor cells and immune cells, especially in highly innervated organs, such as head and neck cancer and pancreatic cancer. However, the role of cancer-nerve cross-talk-related genes (NCCGs) in HNSC is unclear. In our study, we constructed a prognostic model based on genes with prognostic value in NCCGs. We used Pearson’s correlation to analyze the relationship between NCCGs and immune infiltration, microsatellite instability, tumor mutation burden, drug sensitivity, and clinical stage. We used single-cell sequencing data to analyze the expression of genes associated with stage in different cells and explored the possible pathways affected by these genes via gene set enrichment analysis. In the TCGA-HNSC cohort, a total of 23 genes were up- or downregulated compared with normal tissues. GO and KEGG pathway analysis suggested that NCCGs are mainly concentrated in membrane potential regulation, chemical synapse, axon formation, and neuroreceptor-ligand interaction. Ten genes were identified as prognosis genes by Kaplan-Meier plotter and used as candidate genes for LASSO regression. We constructed a seven-gene prognostic model (NTRK1, L1CAM, GRIN3A, CHRNA5, CHRNA6, CHRNB4, CHRND). The model could effectively predict the 1-, 3-, and 5-year survival rates in the TCGA-HNSC cohort, and the effectiveness of the model was verified by external test data. The genes included in the model were significantly correlated with immune infiltration, microsatellite instability, tumor mutation burden, drug sensitivity, and clinical stage. Single-cell sequencing data of HNSC showed that CHRNB4 was mainly expressed in tumor cells, and multiple metabolic pathways were enriched in high CHRNB4 expression tumor cells. In summary, we used comprehensive bioinformatics analysis to construct a prognostic gene model and revealed the potential of NCCGs as therapeutic targets and prognostic biomarkers in HNSC.

Prognostic Value of a Ferroptosis-Related Gene Signature in Patients With Head and Neck Squamous Cell Carcinoma

Background: Ferroptosis is an iron-dependent programmed cell death (PCD) form that plays a crucial role in tumorigenesis and might affect the antitumor effect of radiotherapy and immunotherapy. This study aimed to investigate distinct ferroptosis-related genes, their prognostic value and their relationship with immunotherapy in patients with head and neck squamous cell carcinoma (HNSCC). Methods: The differentially expressed ferroptosis-related genes in HNSCC were filtered based on multiple public databases. To avoid overfitting and improve clinical practicability, univariable, least absolute shrinkage and selection operator (LASSO) and multivariable Cox algorithms were performed to construct a prognostic risk model. Moreover, a nomogram was constructed to forecast individual prognosis. The differences in tumor mutational burden (TMB), immune infiltration and immune checkpoint genes in HNSCC patients with different prognoses were investigated. The correlation between drug sensitivity and the model was firstly analyzed by the Pearson method. Results: Ten genes related to ferroptosis were screened to construct the prognostic risk model. Kaplan-Meier (K-M) analysis showed that the prognosis of HNSCC patients in the high-risk group was significantly lower than that in the low-risk group (P < 0.001), and the area under the curve (AUC) of the 1-, 3- and 5-year receiver operating characteristic (ROC) curve increased year by year (0.665, 0.743, and 0.755). The internal and external validation further verified the accuracy of the model. Then, a nomogram was build based on the reliable model. The C-index of the nomogram was superior to a previous study (0.752 vs. 0.640), and the AUC (0.729 vs. 0.597 at 1 year, 0.828 vs. 0.706 at 3 years and 0.853 vs. 0.645 at 5 years), calibration plot and decision curve analysis (DCA) also shown the satisfactory predictive capacity. Furthermore, the TMB was revealed to be positively correlated with the risk score in HNSCC patients (R = 0.14; P < 0.01). The differences in immune infiltration and immune checkpoint genes were significant (P < 0.05). Pearson analysis showed that the relationship between the model and the sensitivity to antitumor drugs was significant (P < 0.05). Conclusion: Our findings identified potential novel therapeutic targets, providing further potential improvement in the individualized treatment of patients with HNSCC.