A nomogram based on nutritional and inflammatory parameters to predict DMFS and identify beneficiaries of adjuvant chemotherapy in IVA-stage nasopharyngeal carcinoma.

OBJECTIVE: This study aims to develop a nomogram integrating inflammation (NLR), Prognostic Nutritional Index (PNI), and EBV DNA (tumor burden) to achieve personalized treatment and prediction for stage IVA NPC. Furthermore, it endeavors to pinpoint specific subgroups that may derive significant benefits from S-1 adjuvant chemotherapy. METHODS: A total of 834 patients diagnosed with stage IVA NPC were enrolled in this study and randomly allocated into training and validation cohorts. Multivariate Cox analyses were conducted to identify independent prognostic factors for constructing the nomogram. The predictive and clinical utility of the nomogram was assessed through measures including the AUC, calibration curve, DCA, and C-indexes. IPTW was employed to balance baseline characteristics across the population. Kaplan-Meier analysis and log-rank tests were utilized to evaluate the prognostic value. RESULTS: In our study, we examined the clinical features of 557 individuals from the training cohort and 277 from the validation cohort. The median follow-up period was 50.1 and 49.7 months, respectively. For the overall cohort, the median follow-up duration was 53.8 months. The training and validation sets showed 3-year OS rates of 87.7% and 82.5%, respectively. Meanwhile, the 3-year DMFS rates were 95.9% and 84.3%, respectively. We created a nomogram that combined PNI, NRI, and EBV DNA, resulting in high prediction accuracy. Risk stratification demonstrated substantial variations in DMFS and OS between the high and low risk groups. Patients in the high-risk group benefited significantly from the IC + CCRT + S-1 treatment. In contrast, IC + CCRT demonstrated non-inferior 3-year DMFS and OS compared to IC + CCRT + S-1 in the low-risk population, indicating the possibility of reducing treatment intensity. CONCLUSIONS: In conclusion, our nomogram integrating NLR, PNI, and EBV DNA offers precise prognostication for stage IVA NPC. S-1 adjuvant chemotherapy provides notable benefits for high-risk patients, while treatment intensity reduction may be feasible for low-risk individuals.

An immune-related prognostic model predicts neoplasm-immunity interactions for metastatic nasopharyngeal carcinoma.

Background: The prognosis of nasopharyngeal carcinoma (NPC) has been recognized to improve immensely owing to radiotherapy combined with chemotherapy. However, patients with metastatic NPC have a poor prognosis. Immunotherapy has dramatically prolonged the survival of patients with NPC. Hence, further research on immune-related biomarkers is imperative to establish the prognosis of metastatic NPC. Methods: 10 NPC RNA expression profiles were generated from patients with or without distant metastasis after chemoradiotherapy from the Fujian Cancer Hospital. The differential immune-related genes were identified and validated by immunohistochemistry analysis. The method of least absolute shrinkage and selection operator (LASSO)was used to further establish the immune-related prognostic model in an external GEO database (GSE102349, n=88). The immune microenvironment and signal pathways were evaluated in multiple dimensions at the transcriptome and single-cell levels. Results: 1328 differential genes were identified, out of which 520 were upregulated and 808 were downregulated. Notably, most of the immune genes and pathways were down-regulated in the metastasis group. A prognostic immune model involving nine hub genes. Patients in low-risk group were characterized by survival advantage, hot immune phenotype and benefit from immunotherapy. Compared with immune cells, malignant cell exhibited the most active levels of risk score by ssGSEA. Accordingly, intercellular communications including LT, CD70, CD40 and SPP1, and the like, between high-risk and low-risk were explored by the R package "Cellchat". Conclusion: We have constructed a model based on immunity of metastatic NPC and determined its prognostic value. The model identified the level of immune cell infiltration, cell-cell communication, along with potential immunotherapy for metastatic NPC.

The Prognostic Role of Cuproptosis in Head and Neck Squamous Cell Carcinoma Patients: A Comprehensive Analysis.

Purpose: Head and neck squamous cell carcinoma (HNSCC) exhibits a high mortality and morbidity rate, and its treatment is facing clinical challenges. Cuproptosis, a copper-dependent cell death process, can help derive new forms of cancer therapies. However, the potential of cuproptosis-related genes (CRGs) as novel biomarkers for risk prediction, screening, and prognosis remains to be further explained in HNSCC. Methods: We built a prognostic multigene signature with CRGs, which is associated with the tumor immune microenvironment (TME) by gene set enrichment analysis (GSEA), in the TCGA cohort. Furthermore, we systematically correlated risk signature with immunological characteristics in TME including tumor-infiltrating immune cells (TIICs), immune checkpoints, T cell inflamed score, and cancer immunity cycles. We also thoroughly investigated the biological functions of cuproptosis-associated lncRNAs and its immunological characteristics. Results: CRGs-related prognostic model showed good prediction performance. A higher risk score was associated with a poorer overall survival (OS) than those with low-risk scores, according to the results of the survival analysis (p < 0.0001). The risk score was significantly related to the variable clinicopathological factors. Samples with high-risk scores had lower levels of CD8+ T cells infiltration. Immune therapy might be effective for the low-risk subtype of HNSCC patients (p < 0.05). Moreover, 11 differentially expressed lncRNAs as the independent prognostic factor could also predict TME in an accurate manner. Conclusion: Our study identified and validated novel cuproptosis-related biomarkers for HNSCC prognosis and screening, which offer better insights into developing accurate, reliable, and novel cancer therapies in the era of precision medicine.

Upregulation of PNCK Promotes Metastasis and Angiogenesis via Activating NF-κB/VEGF Pathway in Nasopharyngeal Carcinoma.

Background: Distant metastasis is the major cause of treatment failure in patients with nasopharyngeal carcinoma (NPC). Thus, the identification of the molecular mechanisms and the development of novel therapeutic strategies are important. Previous studies suggest that PNCK promotes tumor growth by suppressing PI3K/AKT/mTOR signaling in NPC. However, the underlying regulatory mechanism of PNCK for NPC invasion and metastasis remains unclear. Methods: The PNCK expression level was evaluated in nonmetastatic and metastatic NPC specimens by mRNA sequencing and immunohistochemistry. In vitro migration and invasion and in vivo nude mouse metastasis model and zebrafish model were used to evaluate the effects of PNCK ectopic expression on the metastatic ability of NPC cells. Gene set enrichment and western blot analyses were used to investigate the PNCK downstream signaling pathway. Results: Human metastatic NPC samples showed elevated PNCK expression at both mRNA and protein levels. Upregulated PNCK promoted in vitro NPC cell migration, invasion, and the formation of lung metastases; the vascular-labeled fluorescence signal increased in the in vivo zebrafish model. Mechanistically, pathway analysis showed that the upregulation of PNCK may promote cell metastasis by activating the NF-κB/VEGF signaling pathway. Conclusions: These findings revealed the specific critical role of PNCK in promoting NPC metastasis and angiogenesis, which suggested that PNCK may have implications as a potential therapeutic target for individualized NPC treatment.

Identification of a ferroptosis-associated gene signature and the related therapeutic targets in head and neck squamous carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) has a poor prognosis due to its high rates of recurrence and metastasis. Herein, we designed and validated an individualized ferroptosis-associated gene signature (FGS) and further probed the potential survival mechanisms along with therapeutic targets for HNSCC. METHODS: The FGS risk score was constructed using stepwise regression analysis and validated in the GSE41613 cohort. Characterization of the tumor microenvironment (TME) in patients with HNSCC, involving immune cells and immunomodulatory genes, was performed to investigate the survival mechanisms and therapeutic targets associated with FGS. To validate the role of FGS in TME, multiplex fluorescent immunohistochemistry (mfIHC) was performed on tissue sections from 55 patients with oral squamous carcinoma. RESULTS: The risk score obtained from FGS showed good predictive power as an independent predictor of overall survival. From the tumor immune dysfunction and exclusion (TIDE) prediction, it was found that patients at low risk may benefit from immunotherapy. Furthermore, FGS was significantly associated with CD276, which was highly expressed in fibroblasts that enriched in angiogenesis and epithelial-mesenchymal transition pathways at a single-cell resolution, suggesting CD276 may play a critical mediator of the immunosuppressive microenvironment. Lastly, we identified ATG5 as a critical gene in FGS. And the immune-bioinformatics analysis combined with experimental validation showed a negative correlation between ATG5 expression and CD8 + T cells. CONCLUSION: The FGS model provides a novel and effective method to predict the prognosis of patients with HNSCC and their survival can be prolonged through TME-related therapeutic targets.

A Novel Prognostic Signature Based on Metabolism-Related Genes to Predict Survival and Guide Personalized Treatment for Head and Neck Squamous Carcinoma.

Metabolic reprogramming contributes to patient prognosis. Here, we aimed to reveal the comprehensive landscape in metabolism of head and neck squamous carcinoma (HNSCC), and establish a novel metabolism-related prognostic model to explore the clinical potential and predictive value on therapeutic response. We screened 4752 metabolism-related genes (MRGs) and then identified differentially expressed MRGs in HNSCC. A novel 10-MRGs risk model for prognosis was established by the univariate Cox regression analysis and the least absolute shrinkage and selection operator (Lasso) regression analysis, and then verified in both internal and external validation cohort. Kaplan-Meier analysis was employed to explore its prognostic power on the response of conventional therapy. The immune cell infiltration was also evaluated and we used tumor immune dysfunction and exclusion (TIDE) algorithm to estimate potential response of immunotherapy in different risk groups. Nomogram model was constructed to further predict patients' prognoses. We found the MRGs-related prognostic model showed good prediction performance. Survival analysis indicated that patients suffered obviously poorer survival outcomes in high-risk group (p < 0.001). The metabolism-related signature was further confirmed to be the independent prognostic value of HNSCC (HR = 6.387, 95% CI = 3.281-12.432, p < 0.001), the efficacy of predictive model was also verified by internal and external validation cohorts. We observed that HNSCC patients would benefit from the application of chemotherapy in the low-risk group (p = 0.029). Immunotherapy may be effective for HNSCC patients with high risk score (p < 0.01). Furthermore, we established a predictive nomogram model for clinical application with high performance. Our study constructed and validated a promising 10-MRGs signature for monitoring outcome, which may provide potential indicators for metabolic therapy and therapeutic response prediction in HNSCC.