[Prognostic and predictive methylation biomarkers in HNSCC : Epigenomic diagnostics for head and neck squamous cell carcinoma (HNSCC)]

Deciphering the role of HPV-mediated metabolic regulation in shaping the tumor microenvironment and its implications for immunotherapy in HNSCC

Head and neck squamous cell carcinoma (HNSCC), as a complex and variable malignancy, poses a significant threat to human health. Since the intricate association between HPV and HNSCC emerged, its role within the TME has garnered extensive attention. HPV+HNSCC exhibits distinct immunological characteristics within the TME, intricately intertwined with mechanisms of immune evasion. HPV employs multifaceted pathways to intervene in metabolic regulation within the TME, exerting influence over immune cell functionality and neoplastic cell genesis. Furthermore, the heightened immune reactivity exhibited by HPV+HNSCC within the TME augments responses to immune interventions such as immune checkpoint inhibitors. Therefore, amidst the current limitations of therapeutic approaches, immunotherapy stands as a promising strategy to overcome the conventional confines of treating HNSCC. This article comprehensively outlines the impact of HPV on the inception and progression of HNSCC while discussing the amalgamation of metabolic regulation within the TME and immunotherapeutic strategies. By intervening in the reciprocal interactions between HPV and HNSCC within the TME, the potential to modulate the efficacy of immune-based treatments becomes evident. Concurrently, a synthesis of pertinent biomarker development is summarized. Such endeavors hold paramount significance for personalized therapeutic approaches and the more effective management of HNSCC patients.

Methylation status, mRNA and protein expression of the SMAD4 gene in patients with non-melanocytic skin cancers

BACKGROUND

SMAD4 is a potent tumor suppressor. SMAD4 loss increases genomic instability and plays a critical role in the DNA damage response that leads to skin cancer development. We aimed to investigate SMAD4 methylation effects on mRNA and protein expression of SMAD4 in cancer and healthy tissues from patients with basal cell carcinoma (BCC), cutaneous squamous cell carcinoma (cSCC), and basosquamous skin cancer (BSC).

METHODS AND RESULTS

The study included 17 BCC, 24 cSCC and nine BSC patients. DNA and RNA were isolated from cancerous and healthy tissues following punch biopsy. Methylation-specific polymerase chain reaction (PCR) and real-time quantitative PCR methods were used to examine SMAD4 promoter methylation and SMAD4 mRNA levels, respectively. The percentage and intensity of staining of the SMAD4 protein were determined by immunohistochemistry. The percentage of SMAD4 methylation was increased in the patients with BCC (p = 0.007), cSCC (p = 0.004), and BSC (p = 0.018) compared to the healthy tissue. SMAD4 mRNA expression was decreased in the patients with BCC (p˂0.001), cSCC (p˂0.001), and BSC (p = 0.008). The staining characteristic of SMAD4 protein was negative in the cancer tissues of the patients with cSCC (p = 0.00). Lower SMAD4 mRNA levels were observed in the poorly differentiated cSCC patients (p = 0.001). The staining characteristics of the SMAD4 protein were related to age and chronic sun exposure.

CONCLUSIONS

Hypermethylation of SMAD4 and reduced SMAD4 mRNA expression were found to play a role in the pathogenesis of BCC, cSCC, and BSC. A decrease in SMAD4 protein expression level was observed only in cSCC patients. This suggests that epigenetic alterations to the SMAD4 gene are associated with cSCC.

TRIAL REGISTRATION

The name of the trial register: SMAD4 Methylation and Expression Levels in Non-melanocytic Skin Cancers; SMAD4 Protein Positivity. The registration number: NCT04759261 ( https://clinicaltrials.gov/ct2/results?term=NCT04759261 ).

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 < 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.