Tumor microenvironment characterization in head and neck cancer identifies prognostic and immunotherapeutically relevant gene signatures

Predictive value of cuproptosis and disulfidptosis-related lncRNA in head and neck squamous cell carcinoma prognosis and treatment

Objective

Head and neck squamous cell carcinoma (HNSCC) is a highly lethal and prevalent malignant tumor with a poor prognosis due to its high recurrence rate, This study aims to develop a prognostic index for HNSCC patients based on Cuproptosis and Disulfidptosis-related long noncoding RNA.

Methods

Gene expression and clinical data for HNSCC were obtained from The Cancer Genome Atlas (TCGA). Using Lasso regression and multivariate Cox regression, we established a risk scoring model. The predictive ability of the nomogram, based on clinical features and risk scores, was verified using receiver operating characteristics and calibration curves. We compared independent prognostic parameters, risk score distribution, and survival between high-risk and low-risk groups, followed by preliminary validity evaluations of the model.

Results

Our systematic evaluation of prognostic risk provides a new direction for improving the survival prognosis of HNSCC patients in clinical practice, The model effectively categorized patients into high- and low-risk groups with distinct outcomes, identifying numerous gene mutations in these groups, A low-risk score was associated with a better prognosis and higher survival rates.

Conclusion

The risk score prognostic prediction system developed in this study shows potential efficacy in predicting the prognosis of HNSCC patients and has practical applications in clinical settings.

Exploring the therapeutic mechanisms of Coptidis Rhizoma in gastric precancerous lesions: a network pharmacology approach

BACKGROUND

Gastric precancerous lesions are a critical stage in the development of gastric cancer or gastric adenocarcinoma, and their outcome plays an important role in the malignant progression of gastric cancer. Coptidis Rhizoma has a good effect on Gastric precancerous lesions. However, the specific mechanisms of its action remain incompletely elucidated.

METHODS

Network pharmacology and molecular docking techniques were used to explore the active ingredients and molecular mechanism of Coptidis Rhizoma in treating gastric precancerous lesions. The active compounds of Coptidis Rhizoma and their potential gastric precancerous lesions related targets were obtained from TCMSP, GeneCards, and OMIM databases. An interaction network based on protein-protein interactions (PPIs) was constructed to visualize the interactions between hub genes. Analysis of GO enrichment and KEGG pathway were conducted using the DAVID database. An investigation of interactions between active compounds and potential targets was carried out by molecular docking. Finally, animal experiments were conducted to verify the effect and mechanism of Coptidis Rhizoma in treating precancerous lesions of gastric cancer.

RESULTS

A total of 11 active compounds and 95 anti-gastric precancerous lesions targets of Coptidis Rhizoma were screened for analysis. GO enrichment analysis showed that the mechanism of Coptidis Rhizoma acting on gastric precancerous lesions involves gene expression regulation and apoptosis regulation. KEGG pathway enrichment analysis showed that Coptidis Rhizoma against gastric precancerous lesions involving the AKT /HIF-1α/VEGF signalling pathway. Molecular docking simulations indicated potential interactions between these compounds and core targets involved in anti-gastric precancerous lesions activity. In addition, it was confirmed in vivo that Berberine and Coptidis Rhizoma may reverse atrophy and potential intestinal metaplasia by inhibiting the expression of p-AKT, HIFA, and VEGF.

CONCLUSION

Bioactive compounds in Coptidis Rhizoma have the potential to prevent atrophy and intestinal metaplasia. These compounds function by regulating the proteins implicated in AKT /HIF-1α/VEGF signalling pathways that are crucial in gastric epithelial cell differentiation, proliferation and maturation.

Development and experimental validation of an M2 macrophage and platelet-associated gene signature to predict prognosis and immunotherapy sensitivity in bladder cancer

Platelets and M2 macrophages both play crucial roles in tumorigenesis, but their relationship and the prognosis value of the relative genes in bladder cancer (BLCA) remain obscure. In the present study, we found that platelets stimulated by BLCA cell lines could promote M2 macrophage polarization, and platelets were significantly associated with the infiltration of M2 macrophages in BLCA samples. Through the bioinformatic analyses, A2M, TGFB3, and MYLK, which were associated with platelets and M2 macrophages, were identified and verified in vitro and then included in the predictive model. A platelet and M2 macrophage-related gene signature was constructed to evaluate the prognosis and immunotherapeutic sensitivity, helping to guide personalized treatment and to disclose the underlying mechanisms.

RNA splicing regulator EIF3D regulates the tumor microenvironment through immunogene-related alternative splicing in head and neck squamous cell carcinoma

Study finds that eukaryotic translation initiation factor 3 subunit D (EIF3D) may play an important role in aberrant alternative splicing (AS) events in tumors. AS possesses a pivotal role in both tumour progression and the constitution of the tumour microenvironment (TME). Regrettably, our current understanding of AS remains circumscribed especially in the context of immunogene-related alternative splicing (IGAS) profiles within Head and Neck Squamous Cell Carcinoma (HNSC). In this study, we comprehensively analyzed the function and mechanism of action of EIF3D by bioinformatics analysis combined with in vitro cellular experiments, and found that high expression of EIF3D in HNSC was associated with poor prognosis of overall survival (OS) and progression-free survival (PFS). The EIF3D low expression group had a higher degree of immune infiltration and better efficacy against PD1 and CTLA4 immunotherapy compared to the EIF3D high expression group. TCGA SpliceSeq analysis illustrated that EIF3D influenced differentially spliced alternative splicing (DSAS) events involving 105 differentially expressed immunogenes (DEIGs). We observed an induction of apoptosis and a suppression of cell proliferation, migration, and invasion in EIF3D knock-down FaDu cells. RNA-seq analysis unveiled that 531 genes exhibited differential expression following EIF3D knockdown in FaDu cells. These include 52 DEIGs. Furthermore, EIF3D knockdown influenced the patterns of 1923 alternative splicing events (ASEs), encompassing 129 IGASs. This study identified an RNA splicing regulator and revealed its regulatory role in IGAS and the TME of HNSC, suggesting that EIF3D may be a potential target for predicting HNSC prognosis and immunotherapeutic response.

Prognostic Significance of Primary Tumor Surgery in Adenoid Cystic Carcinoma Patients With Distant Metastases at Diagnosis: A Population-Based Database Analysis in Head and Neck Region

Purpose: Adenoid cystic carcinoma (ACC) is an aggressive cancer that often leads to poor prognosis, especially when it has metastasized. The prognostic significance of primary tumor surgery (PTS) for ACC with distant metastasis (DM) at the time of diagnosis has not been extensively studied. Methods: Using data from the surveillance, epidemiology, and end results (SEER) database from 2010 to 2019, we identified patients with ACC in head and neck region and synchronous DM. We evaluated the effect of PTS on different patterns of metastasis using Kaplan-Meier analysis, log-rank tests, and multivariate Cox regression analysis to assess the therapeutic benefit of PTS in the overall cohort and various subgroups. Results: Of the 192 identified patients with synchronous metastatic ACC of head and neck, 91 (47.4%) underwent PTS. Patients who received PTS had significantly better survival than nonsurgical patients (median overall survival: 19 vs 43 months, P = .006). Cox regression analysis also showed that PTS was associated with improved survival (HR = .46, 95% CI: 0.42-0.88; P = .028). In sub-analyses, except for patients with liver metastases [overall survival (OS), P = .107, cancer-specific survival (CSS), P = .153], PTS consistently conferred significant survival benefits in patients with bone metastases (OS, P = .041, CSS, P = .065) and lung metastases (OS, P = .016, CSS, P = .027). PTS also led to better survival in patients who did not receive radiotherapy (median OS: 13 vs 52 months, P = .007). Conclusion: Our study suggests that PTS in metastatic ACC patients of head and neck improved overall and CSS, particularly in those with bone or lung metastases and those who did not receive radiotherapy. However, further prospective studies are needed to confirm these findings, and the indications for PTS in metastatic ACC should be carefully evaluated by a multidisciplinary board.

Stromal Interaction Molecule 1 (STIM1) is a Potential Prognostic Biomarker and Correlates with Immune Infiltrates in Solid Tumors

Increasing evidence has shown that stromal interaction molecule 1 (STIM1), a key subunit of store-operated Ca2+ entry (SOCE), is closely associated with tumor growth, development, and metastasis. However, there is no report of a comprehensive assessment of STIM1 in pan-cancer. This study aimed to perform a general analysis of STIM1 in human tumors, including its molecular characteristics, functional mechanisms, clinical significance, and immune infiltrates correlation based on pan-cancer data from The Cancer Genome Atlas (TCGA). Gene expression analysis was investigated using TCGA RNA-seq data, the Tumor Immune Estimation Resource (TIMER). Phosphorylation analysis was undertaken using the Clinical Proteomic Tumor Analysis Consortium (CP-TAC) and the PhosphoNET database. Genetic alterations of STIM1 were analyzed using cBioPortal. Prognostic analysis was via the R package "survival" function and the Kaplan-Meier plotter. Functional enrichment analysis was via by the R package "cluster Profiler" function. The association between STIM1 and tumor-infiltrating immune cells and immune markers was by the R package "GSVA" function and TIMER. STIM1 was differentially expressed and associated with distinct clinical stages in multiple tumors. The phosphorylation of STIM1 at S673 is highly expressed in clear cell renal carcinoma and lung adenocarcinoma tumors compared to normal tissues. STIM1 genetic alterations correlate with poor prognosis in several tumors, including ovarian cancer and lung squamous cell carcinomas. High STIM1 expression is associated with good or poor prognosis across diverse tumors. Overall survival (OS) analysis indicated that STIM1 is a favorable prognostic factor for patients with BRCA, KIRC, LIHC, LUAD, OV, SARC, and UCEC, and is a risk prognostic factor for BLCA, KIRP, STAD, and UVM. There is a close correlation between STIM1 expression and immune cell infiltration, immune-regulated genes, chemokines, and immune checkpoints in a variety of tumors. STIM1 functions differently in diverse tumors, playing an oncogenic or antitumor role. Moreover, It may serve as a prognostic biomarker and an immunotherapy target across multiple tumors.

Identification and Biological Validation of a Chemokine/Chemokine Receptor-Based Risk Model for Predicting Immunotherapeutic Response and Prognosis in Head and Neck Squamous Cell Carcinoma

Over 80% of head and neck squamous cell carcinoma (HNSCC) patients failed to respond to immunotherapy, which can likely be attributed to the tumor microenvironment (TME) remolding mediated by chemokines/chemokine receptors (C/CR). This study aimed to establish a C/CR-based risk model for better immunotherapeutic responses and prognosis. After assessing the characteristic patterns of the C/CR cluster from the TCGA-HNSCC cohort, a six-gene C/CR-based risk model was developed to stratify patients by LASSO Cox analysis. The screened genes were multidimensionally validated by RT-qPCR, scRNA-seq, and protein data. A total of 30.4% of patients in the low-risk group had better responses to anti-PD-L1 immunotherapy. A Kaplan-Meier analysis showed that patients in the low-risk group had longer overall survival. A time-dependent receiver operating characteristic curve and Cox analyses indicated that risk score served as an independent predictive indicator. The robustness of the immunotherapy response and prognosis prediction was also validated in independent external datasets. Additionally, the TME landscape revealed that the low-risk group was immune activated. Furthermore, the cell communication analysis on the scRNA-seq dataset revealed that cancer-associated fibroblasts were the main communicators within the C/CR ligand-receptor network of TME. Collectively, The C/CR-based risk model simultaneously predicted immunotherapeutic response and prognosis, potentially optimizing personalized therapeutic strategies of HNSCC.

High eukaryotic initiation factor 5A2 expression predicts poor prognosis and may participate in the SNHG16/miR-10b-5p/EIF5A2 regulatory axis in head and neck squamous cell carcinoma

BACKGROUND

This study attempted to investigate the significance of eukaryotic initiation factor 5A2 (EIF5A2) in the prognosis and regulatory network of head and neck squamous cell carcinoma (HNSCC).

METHODS

EIF5A2 expression, prognostic information, and methylation levels of HNSCC were collected from the Cancer Genome Atlas (TCGA) database. Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) and Western blot analyses were performed to determine EIF5A2 levels in HNSCC and normal tissue samples. R software was employed for expression analysis and prognosis assessment of EIF5A2 in HNSCC. A competing endogenous RNA (ceRNA) network was generated with the starBase database. Gene set enrichment analysis (GSEA) was used to determine the enriched physiological functions and network related to high expression of EIF5A2 in HNSCC. Immune infiltration-related outcomes were acquired from the CIBERSORT and Tumor Immune Estimation Resource (TIMER) database.

RESULTS

EIF5A2 overexpression was observed in HNSCC and linked to poor progression-free survival and overall survival time. Cox regression analyses showed that EIF5A2 level was a stand-alone indicator of HNSCC patients' prognosis. A ceRNA network analysis highlighted the SNHG16/miR-10b-5p/EIF5A2 axis in EIF5A2 regulation. The GSEA results indicated that EIF5A2 was involved in complex signaling pathways. The CIBERSORT and TIMER databases revealed significant associations between EIF5A2 expression and immune cell infiltration.

CONCLUSION

EIF5A2 overexpression may be a risk factor for prognosis in HNSCC and may be regulated by the SNHG16/miR-10b-5p/EIF5A2 axis.

Multiomics Integrative Analysis Identifying EPC1 as a Prognostic Biomarker in Head and Neck Squamous Cell Carcinoma

Background

Biomarker research in head and neck squamous cell carcinoma (HNSCC) is constantly revealing promising findings. An enhancer of polycomb homolog 1 (EPC1) was found to play a procancer role in nasopharyngeal carcinoma (NPC), but its role in HNSCC with strong heterogeneity is still unclear. Herein, we investigated the prognostic significance and related mechanisms of EPC1 in HNSCC.

Methods

The Kaplan-Meier plotter was used to evaluate the prognostic significance of EPC1. Based on a range of published public databases, the multiomics expression of EPC1 in HNSCC was explored to investigate the mechanisms affecting prognosis.

Results

According to the clinical data, high EPC1 expression in HNSCC was a predictor of patient prognosis (hazard ratio (HR) = 0.64; 95% confidence interval (CI) 0.49-0.83; P < 0.01). EPC1 expression varied among clinical subtypes and was related to key factors, such as TP53 and human papillomavirus (HPV) (P < 0.05). At the genetic level, EPC1 expression level may be associated with protein phosphorylation, cell adhesion, cancer-related pathways, etc. For the noncoding region, a competing endogenous RNA network was constructed, and 6 microRNAs and 12 long noncoding RNAs were identified. At the protein level, a protein-protein interaction (PPI) network related to EPC1 expression was constructed and found to be involved in HPV infection, endocrine resistance, and multiple cancer pathways. At the immune level, EPC1 expression was correlated with a variety of immune cells and immune molecules, which together constituted the immune microenvironments of tumors.

Conclusion

High EPC1 expression may predict a better prognosis in HNSCC, as it is more frequently found in HNSCC with HPV infection. EPC1 may participate in the genomics, transcriptomics, proteomics, and immunomics of HNSCC, and the results can provide a reference for the development of targeted drugs and evaluation of patient prognosis.

Prognostic signature of endoplasmic reticulum stress-related long noncoding RNAs in head and neck squamous cell carcinoma: Association with somatic mutation and tumor immune microenvironment

Background/purpose

Analysis of endoplasmic reticulum stress (ERS)-related long noncoding RNAs (LncRNAs) may enable prognostic stratification in patients with head and neck squamous cell carcinoma (HNSCC). This study aimed to comprehensively analyze the ERS-related LncRNAs signature and its effects on the prognosis, tumorigenesis, and tumor immune microenvironment in HNSCC.

Materials and methods

The transcriptome data of HNSCC were obtained from TCGA. Least absolute shrinkage selection operator algorithm, and multivariate Cox regression were used to screen LncRNAs for the signature construction. Somatic mutation, gene enrichment, and immune infiltration analyses were further performed.

Results

458 ERS-related LncRNAs were identified and 55 of which were correlated with HNSCC prognosis. Ten ERS-related LncRNAs were selected to establish a risk prediction signature. When dividing patients into high-risk and low-risk groups by signature score, high-risk group correlated with worse survival rates (hazard ratio = 1.211; 95% confidence interval 1.123-1.306, P < 0.001). The area under the curve was 0.751 and 0.716 in the training and validation cohorts at 3-year. Moreover, high-risk group have increased somatic mutation rates and reduced infiltration abundancy of B cells and CD8+ T cells.

Conclusion

The prognostic signature based on ERS-related LncRNAs may serve as a predictor of altered oncogene mutations and immune microenvironment, which provided an insight into the relationship between ERS, LncRNAs, and tumor progression.

Nine-gene signature and nomogram for predicting survival in patients with head and neck squamous cell carcinoma

Background: Head and neck squamous cell carcinomas (HNSCCs) are derived from the mucosal linings of the upper aerodigestive tract, salivary glands, thyroid, oropharynx, larynx, and hypopharynx. The present study aimed to identify the novel genes and pathways underlying HNSCC. Despite the advances in HNSCC research, diagnosis, and treatment, its incidence continues to rise, and the mortality of advanced HNSCC is expected to increase by 50%. Therefore, there is an urgent need for effective biomarkers to predict HNSCC patients’ prognosis and provide guidance to the personalized treatment.

Methods: Both HNSCC clinical and gene expression data were abstracted from The Cancer Genome Atlas (TCGA) database. Intersecting analysis was adopted between the gene expression matrix of HNSCC patients from TCGA database to extract TME-related genes. Differential gene expression analysis between HNSCC tissue samples and normal tissue samples was performed by R software. Then, HNSCC patients were categorized into clusters 1 and 2 via NMF. Next, TME-related prognosis genes (p &lt; 0.05) were analyzed by univariate Cox regression analysis, LASSO Cox regression analysis, and multivariate Cox regression analysis. Finally, nine genes were selected to construct a prognostic risk model and a prognostic gene signature. We also established a nomogram using relevant clinical parameters and a risk score. The Kaplan–Meier curve, survival analysis, time-dependent receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), and the concordance index (C-index) were carried out to assess the accuracy of the prognostic risk model and nomogram. Potential molecular mechanisms were revealed by gene set enrichment analysis (GSEA). Additionally, gene correlation analysis and immune cell correlation analysis were conducted for further enriching our results.

Results: A novel HNSCC prognostic model was established based on the nine genes (GTSE1, LRRN4CL, CRYAB, SHOX2, ASNS, KRT23, ANGPT2, HOXA9, and CARD11). The value of area under the ROC curves (AUCs) (0.769, 0.841, and 0.816) in TCGA whole set showed that the model effectively predicted the 1-, 3-, and 5-year overall survival (OS). Results of the Cox regression assessment confirmed the nine-gene signature as a reliable independent prognostic factor in HNSCC patients. The prognostic nomogram developed using multivariate Cox regression analysis showed a superior C-index over other clinical signatures. Also, the calibration curve had a high level of concordance between estimated OS and the observed OS. This showed that its clinical net can precisely estimate the one-, three-, and five-year OS in HNSCC patients. The gene set enrichment analysis (GSEA) to some extent revealed the immune- and tumor-linked cascades.

Conclusion: In conclusion, the TME-related nine-gene signature and nomogram can effectively improve the estimation of prognosis in patients with HNSCC.

The analysis of tumor-infiltrating immune cell and ceRNA networks in laryngeal squamous cell carcinoma

BACKGROUND

Laryngeal squamous cell carcinoma (LSCC) is one of the most common forms of head and neck cancers. However, few studies have focused on the correlation between competing endogenous RNA (ceRNAs) and immune cells in LSCC.

METHODS

RNAseq expression of LSCC and adjacent tissues were downloaded from The Cancer Genome Atlas to establish a ceRNA network. The key gene in ceRNA was screened by the cox regression analysis to establish a prognostic risk assessment model. The CIBERSORT algorithm was then used to screen important tumor-infiltrating cells related to LSCC. Finally, co-expression analysis was applied to explore the relationship between key genes in the ceRNA network and tumor-infiltrating cells. The external datasets were used to validate critical biomarkers.

RESULTS

We constructed a prognostic risk assessment model of key genes in the ceRNA network. As it turned out, Kaplan-Meier survival analysis showed significant differences in overall survival rates between high-risk and low-risk groups (P < .001). The survival rate of the high-risk group was drastically lower than that of the low-risk group, and the AUC of 1 year, 3 years, and 5 years were all above 0.7. In addition, some immune infiltrating cells were also found to be related to LSCC. In the co-expression analysis, there is a negative correlation between plasma cells and TUBB3 (r = -0.33, P = .0013). External dataset validation also supports this result.

CONCLUSION

In this study, we found that some key genes (SLC35C1, CLDN23, HOXB7, STC2, TMEM158, TNFRSF4, TUBB3) and immune cells (plasma cells) may correspond to the prognosis of LSCC.

The Significance of Tumor Microenvironment Score for Breast Cancer Patients

Purpose

This study was designed to clarify the prognostic value of tumor microenvironment score and abnormal genomic alterations in TME for breast cancer patients.

Method

The TCGA-BRCA data were downloaded from TCGA and analyzed with R software. The results from analyses were further validated using the dataset from GSE96058, GSE124647, and GSE25066.

Results

After analyzing the TCGA data and verifying it with the GEO data, we developed a TMEscore model based on the TME infiltration pattern and validated it in 3273 breast cancer patients. The results suggested that our TMEscore model has high prognostic value. TME features with the TMEscore model can help to predict breast cancer patients' response to immunotherapy and provide new strategies for breast cancer treatment. Signature 24 was first found in breast cancer. In focal SCNAs, a total of 95 amplified genes and 169 deletion genes in the TMEscore high group were found to be significantly related to the prognosis of breast cancer patients, while 61 amplified genes and 174 deletion genes in the TMEscore low group were identified. LRRC48, CFAP69, and cg25726128 were first discovered and reported to be related to the survival of breast cancer patients. We identified specific mutation signatures that correlate with TMEscore and prognosis.

Conclusion

TMEscore model has high predictive value regarding prognosis and patients' response to immunotherapy. Signature 24 was first found in breast cancer. Specific mutation signatures that correlate with TMEscore and prognosis might be used for providing additional indicators for disease evaluation.

Characterization of Epigenomic Alterations in HPV16+ Head and Neck Squamous Cell Carcinomas

BACKGROUND

Epigenetic changes associated with human papillomavirus (HPV)-driven tumors have been described; however, HPV type-specific alterations are less well understood. We sought to compare HPV16-specific methylation changes with those in virus-unassociated head and neck squamous cell carcinomas (HNSCC).

METHODS

Within The Cancer Genome Atlas, 59 HPV16+ HNSCC, 238 nonviral HNSCC (no detectable HPV or other viruses), and 50 normal head and neck tissues were evaluated. Significant differentially methylated regions (DMR) were selected, and key associated genes were identified. Partial least squares models were generated to predict HPV16 status in additional independent samples.

RESULTS

HPV infection in HNSCC is associated with type-specific methylomic profiles. Multiple significant DMRs were identified between HPV16+, nonviral, and normal samples. The most significant differentially methylated genes, SYCP2, MSX2, HLTF, PITX2, and GRAMD4, demonstrated HPV16-associated methylation patterns with corresponding alterations in gene expression. Phylogenetically related HPV types (alpha-9 species; HPV31, HPV33, and HPV35) demonstrated a similar methylation profile to that of HPV16 but differed from those seen in other types, such as HPV18 and 45 (alpha-7).

CONCLUSIONS

HNSCC linked to HPV16 and types from the same alpha species are associated with a distinct methylation profile. This HPV16-associated methylation pattern is also detected in cervical cancer and testicular germ cell tumors. We present insights into both shared and unique methylation alterations associated with HPV16+ tumors and may have implications for understanding the clinical behavior of HPV-associated HNSCC.

IMPACT

HPV type-specific methylomic changes may contribute to understanding biologic mechanisms underlying differences in clinical behavior among different HPV+ and HPV- HNSCC.

The role of induction chemotherapy in patients with locally advanced head and neck squamous cell carcinoma: A nationwide population-based matched study

INTRODUCTION

Induction chemotherapy (IC) has a proven role in organ preservation and reducing distant failure. However, its ability to prolong survival remains controversy. Herein, our study aimed to investigate the impact of primary tumor location on survival in patients with locally advanced head and neck squamous cell carcinoma (LA-HNSCC) treated with IC.

METHODS

Patients who were older than 18 years and diagnosed with LA-HNSCC between 2007 and 2016 were retrospectively identified from Taiwan National Health Insurance Research Database and Taiwan Cancer Registry. Patients were categorized into two group: IC group and CCRT group. In order to reduce the selection bias, IC patients were individually matched with the CCRT patients. The oncologic outcomes were presented with overall survival (OS).

RESULTS

A total of 5547 patients were identified. After matching, 2208 patients were analyzed for outcomes comparison, including 1104 patients in each group. In general, median OS were 27.3 months versus 28.5 months in IC and CCRT group, respectively (p = 0.6151). Patients were stratified by primary tumor location. For patients with oral cavity cancers, the median OS was significantly inferior in IC group than those in CCRT group, while for patients with non-oral cavity cancer, the median OS was superior in IC group than those in CCRT group.

CONCLUSIONS

Primary tumor location has a significant impact on survival in patients with LA-HNSCC treated with IC. Our study provides a strong evidence that primary tumor location should be taken into consideration during multidisciplinary approach.

Fusobacterium nucleatum is associated with inflammation and poor survival in early-stage HPV-negative tongue cancer

Persistent pathogen infection is a known cause of malignancy, although with sparse systematic evaluation across tumor types. We present a comprehensive landscape of 1060 infectious pathogens across 239 whole exomes and 1168 transcriptomes of breast, lung, gallbladder, cervical, colorectal, and head and neck tumors. We identify known cancer-associated pathogens consistent with the literature. In addition, we identify a significant prevalence of Fusobacterium in head and neck tumors, comparable to colorectal tumors. The Fusobacterium-high subgroup of head and neck tumors occurs mutually exclusive to human papillomavirus, and is characterized by overexpression of miRNAs associated with inflammation, elevated innate immune cell fraction and nodal metastases. We validate the association of Fusobacterium with the inflammatory markers IL1B, IL6 and IL8, miRNAs hsa-mir-451a, hsa-mir-675 and hsa-mir-486-1, and MMP10 in the tongue tumor samples. A higher burden of Fusobacterium is also associated with poor survival, nodal metastases and extracapsular spread in tongue tumors defining a distinct subgroup of head and neck cancer.

Recent progress of biomarkers in oral cancers

Oral cancers are the seventh most common cancer globally. While progresses in oral cancer treatment have been made, not all patients respond to these therapies in the same way. To overcome this difficulty, numerous studies have been devoted to identifying biomarkers, which enable early identification of patients who may benefit from a particular treatment modality or at risk for poor prognosis. Biomarkers are protein molecules, gene expression, DNA variants, or metabolites that are derived from tumors, adjacent normal tissue or bodily fluids, which can be acquired before treatment and during follow-up, thus extending their use to the evaluation of cancer progression and prediction of treatment outcome. In this review, we employed a basic significance level (<0.05) as the minimal requirement for candidate biomarkers. Effect sizes of the biomarkers in terms of odds ratio, hazard ratio, and area under the receiver operating characteristic curves were subsequently used to evaluate the potential of their clinical use. We identified the CCND1 from the tumor, human papillomavirus, HSP70, and IL-17 from the peripheral blood, and high density of CD45RO+ tumor-infiltrating lymphocytes as the clinically relevant biomarkers for oral cancers.

A TP53 mutation model for the prediction of prognosis and therapeutic responses in head and neck squamous cell carcinoma

BACKGROUND

Tumor protein p53 (TP53) is the most frequently mutated gene in head and neck squamous cell carcinoma (HNSC), and TP53 mutations are associated with inhibited immune signatures and poor prognosis. We established a TP53 mutation associated risk score model to evaluate the prognosis and therapeutic responses of patients with HNSC.

METHODS

Differentially expressed genes between patients with and without TP53 mutations were determined by using data from the HNSC cohort in The Cancer Genome Atlas database. Patients with HNSC were divided into high- and low-risk groups based on a prognostic risk score that was generated from ten TP53 mutation associated genes via the multivariate Cox regression model.

RESULTS

TP53 was the most common mutant gene in HNSC, and TP53 mutations were associated with immunogenic signatures, including the infiltration of immune cells and expression of immune-associated genes. Patients in the high-risk group had significantly poorer overall survival than those in the low-risk group. The high-risk group showed less response to anti-programmed cell death protein 1 (PD-1) therapy but high sensitivity to some chemotherapies.

CONCLUSION

The risk score based on our TP53 mutation model was associated with poorer survival and could act as a specific predictor for assessing prognosis and therapeutic response in patients with HNSC.

Immuno-Oncological Biomarkers for Squamous Cell Cancer of the Head and Neck: Current State of the Art and Future Perspectives

The era of immune checkpoint inhibitors has altered the therapeutic landscape in squamous cell cancer of the head and neck (SCCHN). Our knowledge about the tumor microenvironment has fueled the research in SCCHN, leading to several well-known and less-known prognostic and predictive biomarkers. The clinical staging, p16/HPV status, and PD-L1 expression are currently the main tools for assessing the patients' diagnosis and prognosis. However, several novel biomarkers have been thoroughly investigated, some reaching actual significant clinical contributions. The untangling of the immune infiltrate with the subtyping of tissue-associated tumor infiltrating lymphocytes, tumor-associated macrophages, and circulating blood-based biomarkers are an interesting avenue to be further explored and prospectively assessed. Although PD-L1 expression remains the most important response predictor for immune checkpoint inhibitors, several flaws impede proper assessment such as technical issues, different scoring protocol, and intra-, inter-, and temporal heterogeneity. In addition, the construction of an immune-related gene panel has been proposed as a prognostic and predictive stratification but lacks consensus. Recently, the role of microbioma have also been explored regarding its systemic and antitumor immunity. This review gives a comprehensive overview of the aforementioned topics in SCCHN. To this end, the integration of these clinically advantageous biomarkers via construction of an immunogram or nomogram could be an invaluable tool for SCCHN in future prospects.

Novel deep learning-based survival prediction for oral cancer by analyzing tumor-infiltrating lymphocyte profiles through CIBERSORT

The tumor microenvironment (TME) within mucosal neoplastic tissue in oral cancer (ORCA) is greatly influenced by tumor-infiltrating lymphocytes (TILs). Here, a clustering method was performed using CIBERSORT profiles of ORCA data that were filtered from the publicly accessible data of patients with head and neck cancer in The Cancer Genome Atlas (TCGA) using hierarchical clustering where patients were regrouped into binary risk groups based on the clustering-measuring scores and survival patterns associated with individual groups. Based on this analysis, clinically reasonable differences were identified in 16 out of 22 TIL fractions between groups. A deep neural network classifier was trained using the TIL fraction patterns. This internally validated classifier was used on another individual ORCA dataset from the International Cancer Genome Consortium data portal, and patient survival patterns were precisely predicted. Seven common differentially expressed genes between the two risk groups were obtained. This new approach confirms the importance of TILs in the TME and provides a direction for the use of a novel deep-learning approach for cancer prognosis.

CCR4, CCR8, and P2RY14 as Prognostic Factors in Head and Neck Squamous Cell Carcinoma Are Involved in the Remodeling of the Tumor Microenvironment

The tumor microenvironment (TME) plays a critical role in the initiation and progression of cancer. However, the specific mechanism of its regulation in head and neck squamous cell carcinoma (HNSCC) remains unclear. In this study, we first applied the ESTIMATE method to calculate the immune and stromal scores in patients’ tumor tissues from The Cancer Genome Atlas (TCGA) database. GSE41613, GSE30784, and GSE37991 data sets from the Gene Expression Omnibus (GEO) database were recruited for further validation. Differentially expressed genes (DEGs) were identified and then analyzed by Cox regression analysis and protein-protein interaction (PPI) network construction. DEGs significantly associated with prognosis and TME will be identified as hub genes. These genes were also validated at the protein level by immunohistochemical analysis of 10 pairs of primary tumor tissues and the adjacent normal tissues from our institution. The relationship between hub genes expression and immune cell fraction estimated by CIBERSORT software was also examined. 275 DEGs were significantly associated with TME. CCR4, CCR8, and P2RY14 have then identified as hub genes by intersection Cox and PPI analysis. Further investigation revealed that the expression of CCR4, CCR8, and P2RY14 was negatively correlated with clinicopathological characteristics (clinical stage, T stage) and positively associated with survival in HNSCC patients, especially in male patients. The expression of CCR8 and P2RY14 was lower in males than in females. CCR8 and P2RY14 were differentially expressed in tumor tissues than normal tissues, and the results were validated at the protein level by immunohistochemistry experiments. Gene set enrichment analysis (GSEA) showed that the high expression groups’ hub genes were mainly enriched for immune-related activities. In the low-expression groups, genes were primarily enriched in metabolic pathways. CIBERSORT results showed that the expression of these genes was all negatively correlated with the fraction of memory B cells and positively correlated with the fraction of the other four cells, including naive B cells, resting T cells CD4 memory, T cells follicular helper, and T cells regulatory (Tregs). The results suggest that CCR4, CCR8, and P2RY14 may be responsible for maintaining the immune dominance of TME, thus leading to a better prognosis.

The Periphery of Salivary Gland Carcinoma Tumors Reveals a PD-L1/PD-1 Biomarker Niche for the Evaluation of Disease Severity and Tumor-Immune System Interplay

The treatment options for patients with advanced salivary gland cancers (SGCs) are limited. Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment. However, the response to ICI immunotherapy is largely driven by the immune cell signatures within the tumor tissue and the para-tumoral tissue compartments. To date, there are no data on the expression of programed cell death protein-1/programed cell death protein-ligand 1 (PD-1/PD-L1) in SGC, which may enable the implementation of ICI immunotherapy for this disease. Thus, we performed an immunohistochemical analysis of PD-1 and PD-L1 expression in tumor cells and tumor-infiltrating immune cells (TIICs) in the tumor center and periphery of 62 SGC patients. The tumor periphery showed significantly higher expression of PD-L1 in tumor cells than in TIICs. Moreover, peripheral TIICs had significantly higher PD-1 expression than peripheral tumor cells. PD-1-positive tumor cells were detected exclusively in the tumor center of high-grade tumors, and most importantly, the presence of lymph node (LN) metastases and primary tumor stage significantly correlated with the presence of PD-L1-positive tumor cells in the tumor periphery. The PD-1/PD-L1 molecular signatures in SGC are clustered predominantly in the tumor periphery, reflect disease severity, and may predict the response to ICI immunotherapy in SGC patients.

Identification novel prognostic signatures for Head and Neck Squamous Cell Carcinoma based on ceRNA network construction and immune infiltration analysis

Background: Head and neck squamous cell carcinoma (HNSCC) is a common malignancy with high mortality and morbidity worldwide, but the underlying biological mechanisms of molecules and tumor infiltrating-immune cells (TIICs) are still unknown. Methods and Results: We obtained mRNAs, lncRNAs, and miRNAs expression profiles of 546 HNSCC from The Cancer Genome Atlas (TCGA) database to develop a ceRNA network. CIBERSORT was employed to estimate the fraction of 22 types of TIICs in HNSCC. Univariate and multivariate Cox regression and lasso regression analyses were used to develop prognostic signatures. Then, two novel risk signatures were constructed respectively based on six ceRNAs (ANLN, KIT, PRKAA2, NFIA, PTX3 and has-miR-148a-3p) and three immune cells (naïve B cells, regulatory T cells and Neutrophils). Kaplan-Meier (K-M) analysis and Cox regression analysis further proved that these two signatures were significant prognostic factors independent of multiple clinicopathological characteristics. Two nomograms were built based on ceRNAs-riskScore and TIICs-riskScore that could be used to predict the prognosis of HNSCC. Co-expression analysis showed significant correlations between miR-148a-3p and naive B cells, naive B cells and plasmas cells. Conclusion: Through construction of the ceRNA network and estimation of TIICs, we established two risk signatures and their nomograms with excellent utility, which indicated the potential molecular and cellular mechanisms, and predicted the prognosis of HNSCC.