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.

The causal impact of complement C3d receptor 2 on head and neck cancer microenvironment and its implications for immunotherapy response prediction.

This research dives into the intricate immune landscape of head and neck cancer (HNC), with a keen focus on the roles of specific immune cell subpopulations and their linked genes. We used tumour RNA-seq (in-house cohort: n = 192, TCGA-HNSC: n = 546) and Mendelian randomization to pinpoint key SNPs in immune cells that have a causal connection to HNC. Our discoveries unveil a spectrum of tumour immune phenotypes that either offer protection against or increase the risk of HNC. We underscore the therapeutic promise of Complement C3d Receptor 2 (CR2), a gene closely tied to immune cells, with its increased expression in tumour tissues linked to a more favourable prognosis. This is correlated with heightened immune pathway activity, stronger resistance to radiochemotherapy, and improved immunotherapy responses. Our research emphasises the pivotal role of CR2 in immune regulation and the significance of immune cells in tumour progression, highlighting the potential of CR2-targeted therapeutic interventions.

Comorbidity profiling identifies potential subtype of elderly patients with nasopharyngeal carcinoma.

BACKGROUND: Few studies have assessed the comprehensive associations among comorbid diseases in elderly patients with nasopharyngeal carcinoma (NPC). This study sought to identify potential comorbidity patterns and explore the relationship of comorbidity patterns with the mortality risk in elderly patients with NPC. METHODS: A total of 452 elderly patients with NPC were enrolled in the study. The network analysis and latent class analysis were applied to mine comorbidity patterns. Propensity score matching was used for adjusting confounders. A restricted cubic spline model was used to analyze the nonlinear association between age and the risk of all-cause mortality. RESULTS: We identified 2 comorbidity patterns, metabolic disease-related comorbidity (MDRC) and organ disease-related comorbidity (ODRC) in elderly patients with NPC. Patients in MDRC showed a significantly higher risk of all-cause mortality (71.41% vs 87.97%, HR 1.819 [95% CI, 1.106-2.994], P = .031) and locoregional relapse (68.73% vs 80.88%, HR 1.689 [95% CI, 1.055-2.704], P = .042). Moreover, in patients with MDRC pattern, we observed an intriguing inverted S-shaped relationship between age and all-cause mortality among patients aged 68 years and older. The risk of mortality up perpetually with age increasing in ODRC group, specifically within the age range of 68-77 years (HR 4.371, 1.958-9.757). CONCLUSION: Our study shed light on the potential comorbidity patterns in elderly patients with NPC, thereby providing valuable insights into the development of comprehensive health management strategies for this specific population.

Machine learning-based survival prediction nomogram for postoperative parotid mucoepidermoid carcinoma.

Parotid mucoepidermoid carcinoma (P-MEC) is a significant histopathological subtype of salivary gland cancer with inherent heterogeneity and complexity. Existing clinical models inadequately offer personalized treatment options for patients. In response, we assessed the efficacy of four machine learning algorithms vis-à-vis traditional analysis in forecasting the overall survival (OS) of P-MEC patients. Using the SEER database, we analyzed data from 882 postoperative P-MEC patients (stages I-IVA). Single-factor Cox regression and four machine learning techniques (random forest, LASSO, XGBoost, best subset regression) were employed for variable selection. The optimal model was derived via stepwise backward regression, Akaike Information Criterion (AIC), and Area Under the Curve (AUC). Bootstrap resampling facilitated internal validation, while prediction accuracy was gauged through C-index, time-dependent ROC curve, and calibration curve. The model's clinical relevance was ascertained using decision curve analysis (DCA). The study found 3-, 5-, and 10-year OS rates of 0.887, 0.841, and 0.753, respectively. XGBoost, BSR, and LASSO stood out in predictive efficacy, identifying seven key prognostic factors including age, pathological grade, T stage, N stage, radiation therapy, chemotherapy, and marital status. A subsequent nomogram revealed a C-index of 0.8499 (3-year), 0.8557 (5-year), and 0.8375 (10-year) and AUC values of 0.8670, 0.8879, and 0.8767, respectively. The model also highlighted the clinical significance of postoperative radiotherapy across varying risk levels. Our prognostic model, grounded in machine learning, surpasses traditional models in prediction and offer superior visualization of variable importance.

Non-coding RNA-related FCGBP downregulation in head and neck squamous cell carcinoma: a novel biomarker for predicting paclitaxel resistance and immunosuppressive microenvironment.

In head and neck squamous cell carcinoma (HNSC), chemoresistance is a major reason for poor prognosis. Nevertheless, there is a lack of validated biomarkers to screen for patients for categorical chemotherapy. Fc gamma binding protein (FCGBP) is a mucus protein associated with mucosal epithelial cells and has immunological functions that protect against tumors and metastasis. However, the effect of FCGBP on HNSC is unclear. In pan-cancer tissues, the expression of FCGBP and the survival status of patients were analyzed using information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Correlation analysis and Cox regression analysis were conducted to confirm the relationship and survival outcome. Bioinformatics analysis was utilized to predict the probable upstream non-coding RNA. FCGBP functioned as a potential tumor suppressor gene in HNSC. Notably, FCGBP expression was negatively correlated with enriched tumor-infiltrating macrophages and paclitaxel resistance. Cox regression with gene, clinical, and immune factors showed that FCGBP was a risk factor acting in an independent manner. In HNSC, the utmost possibly upstream non-coding RNA-related pathway of FCGBP was also discovered to be the PART1/AC007728.2/LINC00885/hsa-miR-877-5p/FCGBP axis. According to the present study, non-coding RNA-related low levels of FCGBP are a prognostic indicator and are linked to an HNSC-related immunosuppressive state.

Identification of novel molecular subtypes to improve the classification framework of nasopharyngeal carcinoma.

BACKGROUND: Nasopharyngeal carcinoma (NPC) treatment is largely based on a 'one-drug-fits-all' strategy in patients with similar pathological characteristics. However, given its biological heterogeneity, patients at the same clinical stage or similar therapies exhibit significant clinical differences. Thus, novel molecular subgroups based on these characteristics may better therapeutic outcomes. METHODS: Herein, 192 treatment-naïve NPC samples with corresponding clinicopathological information were obtained from Fujian Cancer Hospital between January 2015 and January 2018. The gene expression profiles of the samples were obtained by RNA sequencing. Molecular subtypes were identified by consensus clustering. External NPC cohorts were used as the validation sets. RESULTS: Patients with NPC were classified into immune, metabolic, and proliferative molecular subtypes with distinct clinical features. Additionally, this classification was repeatable and predictable as validated by the external NPC cohorts. Metabolomics has shown that arachidonic acid metabolites were associated with NPC malignancy. We also identified several key genes in each subtype using a weighted correlation network analysis. Furthermore, a prognostic risk model based on these key genes was developed and was significantly associated with disease-free survival (hazard ratio, 1.11; 95% CI, 1.07-1.16; P < 0.0001), which was further validated by an external NPC cohort (hazard ratio, 7.71; 95% CI, 1.39-42.73; P < 0.0001). Moreover, the 1-, 3-, and 5-year areas under the curve were 0.84 (95% CI, 0.74-0.94), 0.81 (95% CI, 0.73-0.89), and 0.82 (95% CI, 0.73-0.90), respectively, demonstrating a high predictive value. CONCLUSIONS: Overall, we defined a novel classification of nasopharyngeal carcinoma (immune, metabolism, and proliferation subtypes). Among these subtypes, metabolism and proliferation subtypes were associated with advanced stage and poor prognosis of NPC patients, whereas the immune subtype was linked to early stage and favorable prognosis.

Radiomics and Deep Learning in Nasopharyngeal Carcinoma: A Review.

Nasopharyngeal carcinoma is a common head and neck malignancy with distinct clinical management compared to other types of cancer. Precision risk stratification and tailored therapeutic interventions are crucial to improving the survival outcomes. Artificial intelligence, including radiomics and deep learning, has exhibited considerable efficacy in various clinical tasks for nasopharyngeal carcinoma. These techniques leverage medical images and other clinical data to optimize clinical workflow and ultimately benefit patients. In this review, we provide an overview of the technical aspects and basic workflow of radiomics and deep learning in medical image analysis. We then conduct a detailed review of their applications to seven typical tasks in the clinical diagnosis and treatment of nasopharyngeal carcinoma, covering various aspects of image synthesis, lesion segmentation, diagnosis, and prognosis. The innovation and application effects of cutting-edge research are summarized. Recognizing the heterogeneity of the research field and the existing gap between research and clinical translation, potential avenues for improvement are discussed. We propose that these issues can be gradually addressed by establishing standardized large datasets, exploring the biological characteristics of features, and technological upgrades.

A Comprehensive Analysis of Prognostic Indicators in Serous Ovarian Cancer Based on Leukocyte Migration and Immune Microenvironment.

BACKGROUND: High-grade serous ovarian cancer (HGSOC) treatment is facing clinical challenges. The tumor immune microenvironment (TME) has recently been shown to perform a critical function in the prediction of clinical outcomes as well as the effectiveness of treatment. Leukocyte migration is enhanced in malignant tumors and promotes immunity. However, its role in how to underlie the migration of immune cells into the TME remains to be further explained in HGSOC. METHODS: We built a prognostic multigene signature with leukocyte migration-related differentially expressed genes (LMDGs), which is associated with TME by single-sample gene set enrichment analysis (ssGSEA), in the The Cancer Genome Atlas (TCGA) cohort. Furthermore, we systematically correlated risk signature with immunological characteris-tics in TME, mutational profiles of HGSOC, and potential value in predicting efficacy of platinum-based chemotherapy and immunotherapy. Screening of the most important prognostic factor among risk signatures by Friends analysis, and immunofluorescence was employed to examine both the expression of CD2 as well as its relationship with CD8 and PD-1. RESULTS: LMDGs-related prognostic model showed good prediction performance. Patients who had high-risk scores exhibited significantly reduced progression-free survival (PFS) and overall survival (OS) than those with low-risk scores, according to the results of the survival analysis (p < 0.001). In the TCGA cohort, the risk signature was found to have independent prognostic sig-nificance for HGSOC (HR =1.829, 95% CI = 1.460-2.290, p < 0.001) and validated in the Gene Expression Omnibus (GEO) cohort. Samples with high-risk scores had lower levels of CD8+ T cells infiltration. The low-risk signature shapes an inflamed TME in HGSOC. Furthermore, immune therapy might be effective for the low-risk subtype of HGSOC patients (p < 0.001). Friends analysis revealed that CD2 was the most important prognostic gene among risk signatures. Real-time quantitative PCR analysis showed the expression of CD2 was greater in tumor cells as opposed to normal ovarian cells. CD8, PD-1, and CD2 were shown to be co-localized in HGSOC tissues, according to immunofluorescence analyses. CD2 was significantly correlated with CD8 (r = 0.47). CONCLUSIONS: Our study identified and validated a promising LMDGs signature associated with inflamed TME, which might offer some prospective clinical implications for the treatment of SOC. CD2 might be a novel biomarker to predict immune efficacy.

Prognostic model on overall survival in elderly nasopharyngeal carcinoma patients: a recursive partitioning analysis identifying pre-treatment risk stratification.

BACKGROUND: We aimed to evaluate the optimal management for elderly patients with nasopharyngeal carcinoma (NPC) with intensity-modulated radiotherapy (IMRT). METHODS: A total of 283 elderly patients with NPC diagnosed from 2015 to 2019 were enrolled in the study. Overall survival (OS) was the primary endpoint. Univariate and multivariate Cox regression analyses were preformed to identify potential prognostic factors. The recursive partitioning analysis (RPA) was used for risk stratification. Kaplan-Meier survival curves were applied to evaluate the survival endpoints, and log-rank test was utilized to assess differences between groups. The prognostic index (PI) was constructed to further predict patients' prognosis displayed by nomogram model. The area under the receiver operating characteristic (ROC) curves (AUC) and the calibration curves were applied to assess the effectiveness of the model. RESULTS: Based on RPA-based risk stratification, we demonstrated that elderly NPC patients who were treated with IC followed by RT had similar OS as those with induction chemotherapy (IC) combined with concurrent chemoradiotherapy (CCRT) in the middle- (stage I-III and pre-treatment EBV > 1840 copies/ml) and high-risk groups (stage IVA). IMRT alone may be the optimal treatment option for the low-risk group (stage I-III with pre-treatment EBV ≤ 1840 copies/ml). We established an integrated PI which was indicted with stronger prognostic power than each of the factors alone for elderly NPC patients (The AUC of PI was 0.75, 0.80, and 0.82 for 1-, 3-, 5-year prediction of OS, respectively). CONCLUSION: We present a robust model for clinical stratification which could guide individual therapy for elderly NPC patients.

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.

Efficacy and safety of KL-A167 in previously treated recurrent or metastatic nasopharyngeal carcinoma: a multicenter, single-arm, phase 2 study.

Background: KL-A167 is a fully humanized monoclonal antibody targeting programmed cell death-ligand 1. This phase 2 study aimed to evaluate the efficacy and safety of KL-A167 in Chinese patients with previously treated recurrent or metastatic (R/M) nasopharyngeal carcinoma (NPC). Methods: This was a multicentre, single-arm, phase 2 study of KL-A167 in R/M NPC (KL167-2-05-CTP) (NCT03848286), conducted at 42 hospitals across the People's Republic of China. Eligible patients had histologically confirmed non-keratinising R/M NPC, and had failed at least two lines of chemotherapy. Patients received KL-A167 900mg intravenously once every 2 weeks until confirmed disease progression, intolerable toxicity, or withdrawal of informed consent. The primary endpoint was objective response rate (ORR) assessed by the independent review committee (IRC) according to RECIST v1.1. Findings: Between Feb 26th, 2019 and Jan 13th, 2021, 153 patients were treated. Totally, 132 patients entered full analysis set (FAS) and were evaluated for the efficacy. As of data cutoff date on Jul 13th, 2021, the median follow-up time was 21.7 months (95%CI 19.8-22.5). For FAS population, the IRC-assessed ORR was 26.5% (95%CI 19.2-34.9%), and disease control rate (DCR) was 56.8% (95%CI 47.9-65.4%). Median progression-free survival (PFS) was 2.8 months (95%CI 1.5-4.1) . Median duration of response was 12.4 months (95%CI 6.8-16.5), and median overall survival (OS) was 16.2 months (95%CI 13.4-21.3). When using the cutoff of 1000 copies/ml, 5000 copies/ml and 10,000 copies/ml for plasma EBV DNA titer, baseline low plasma EBV DNA was consistently related with better DCR, PFS and OS. Dynamic change of plasma EBV DNA was significantly associated with ORR and PFS. Among 153 patients, treatment related-adverse events (TRAEs) occurred in 73.2% of patients, and grade ≥3 TRAEs were in 15.0% of patients. No TRAE leading to death was reported. Conclusion: In this study, KL-A167 showed promising efficacy and an acceptable safety profile in patients with previously treated R/M NPC. Baseline plasma EBV DNA copy number might be a potentially useful prognostic biomarker for KL-A167 treatment, and post-treatment EBV DNA decrease might be correlated with better response to KL-A167. Funding: Sichuan Kelun-Biotech Biopharmaceutical Co., Ltd., China National Major Project for New Drug Innovation (2017ZX09304015).

Prioritizing sufficient dose to gross tumor volume over normal tissue sparing in intensity-modulated radiotherapy treatment of T4 nasopharyngeal carcinoma.

BACKGROUND: In intensity-modulated radiation therapy (IMRT) for nasopharyngeal carcinoma (NPC), priority is often given minimize dose to the critical organs at risk (OARs) to avoid potential morbid sequelae. However, in T4 NPC, dosimetric inadequacy enforced by dose constraints on OARs may significantly impact tumor control. METHODS: This was a single-institute cohort that patients diagnosed between July 2005 and December 2010 with T4 NPC treated with IMRT. All patients were re-classification according to the 7th-AJCC stage. RESULTS: Overall, the average doses such as Dmax , D1% , D2% and D1cc for various Central nervous system (CNS) OARs including brainstem, optic nerve, chiasm, temporal lobes and spinal cord were found to exceed published guidelines as RTOG0225. However, no clinical toxicities were seen during the follow-up period except for 13% patients with temporal lobe necrosis. CONCLUSION: Our retrospective review showed that its feasible to maximize gross tumor volume dose coverage while exceeding most CNS OAR constraint standards, with ideal local control and no obvious increase of craniocerebral toxicity.

Impact of Radiotherapy Combined With Chemotherapy on Long-Term Outcomes of Patients With Recurrent Nasopharyngeal Carcinoma.

Background: It remains controversial whether the application of chemotherapy has an impact on recurrent nasopharyngeal carcinoma (rNPC) patients with salvage radiotherapy. Here, we aimed to evaluate treatment outcomes of rNPC patients and derive a prognostic model to assess the benefit of chemotherapy in patients with re-radiotherapy. Methods: This study was conducted as a retrospective study. In total, 340 rNPC patients treated with salvage intensity-modulated radiotherapy (IMRT) or radiochemotherapy (RCT) from October 2006 to September 2019 were included in this study. Overall survival (OS) was the primary outcome. Kaplan-Meier method was employed to detect the prognostic difference with Log-rank tests. The Cox regression analysis was performed to explore the potential prognostic factors while the multivariate Cox analysis was used to identify candidate variables for the prognostic model of OS. Results: The 5-year actuarial rates of OS, progression-free survival, loco-regional progression-free survival, and distant metastases-free survival did not show significant difference between the IMRT and RCT groups (P > .05). Age at recurrence and rT category were found to be the independent prognostic factors for OS. We found that rNPC patients suffered poor OS in the high-risk group (patients with higher age at recurrence and advanced rT category) (high-risk vs low-risk, HR = 1.87, 95% CI: 1.36-2.57, P < .001). Salvage RT alone may be superior to RCT for patients in the low-risk group (RCT group vs RT group, HR = 1.89, 95% CI: 1.11-3.20, P = .038). Conclusion: Salvage RT combined with chemotherapy cannot improve survival outcomes for rNPC. More novel clinical trials should be explored to develop individualized strategies to improve survival and minimize toxicities.

Shifted-excitation Raman difference spectroscopy for improving in vivo detection of nasopharyngeal carcinoma.

A strong fluorescence background is one of the common interference factors of Raman spectroscopic analysis in biological tissue. This study developed an endoscopic shifted-excitation Raman difference spectroscopy (SERDS) system for real-time in vivo detection of nasopharyngeal carcinoma (NPC) for the first time. Owing to the use of the SERDS method, the high-quality Raman signals of nasopharyngeal tissue could be well extracted and characterized from the complex raw spectra by removing the fluorescence interference signals. Significant spectral differences relating to proteins, phospholipids, glucose, and DNA were found between 42 NPC and 42 normal tissue sites. Using linear discriminant analysis, the diagnostic accuracy of SERDS for NPC detection was 100%, which was much higher than that of raw Raman spectroscopy (75.0%), showing the great potential of SERDS for improving the accurate in vivo detection of NPC.

Tumor-intrinsic YTHDF1 drives immune evasion and resistance to immune checkpoint inhibitors via promoting MHC-I degradation.

The recently described role of RNA methylation in regulating immune cell infiltration into tumors has attracted interest, given its potential impact on immunotherapy response. YTHDF1 is a versatile and powerful m6A reader, but the understanding of its impact on immune evasion is limited. Here, we reveal that tumor-intrinsic YTHDF1 drives immune evasion and immune checkpoint inhibitor (ICI) resistance. Additionally, YTHDF1 deficiency converts cold tumors into responsive hot tumors, which improves ICI efficacy. Mechanistically, YTHDF1 deficiency inhibits the translation of lysosomal genes and limits lysosomal proteolysis of the major histocompatibility complex class I (MHC-I) and antigens, ultimately restoring tumor immune surveillance. In addition, we design a system for exosome-mediated CRISPR/Cas9 delivery to target YTHDF1 in vivo, resulting in YTHDF1 depletion and antitumor activity. Our findings elucidate the role of tumor-intrinsic YTHDF1 in driving immune evasion and its underlying mechanism.

Profiling of Tumor Cell-Delivered Exosome by Surface Enhanced Raman Spectroscopy-Based Biosensor for Evaluation of Nasopharyngeal Cancer Radioresistance.

Although the advancement of radiotherapy significantly improves the survival of nasopharyngeal cancer (NPC), radioresistance associated with recurrence and poor outcomes still remains a daunting challenge in the clinical scenario. Currently, effective biomarkers and convenient detection methods for predicting radioresistance have not been well established. Here, the surface-enhanced Raman spectroscopy combined with proteomics is used to firstly profile the characteristic spectral patterns of exosomes secreted from self-established NPC radioresistance cells, and reveals specific variations of proteins expression during radioresistance formation, including collagen alpha-2 (I) chain (COL1A2) that is associated with a favorable prognosis in NPC and is negatively associated with DNA repair scores and DNA repair-related genes via bioinformatic analysis. Furthermore, deep learning model-based diagnostic model is generated to accurately identify the exosomes from radioresistance group. This work demonstrates the promising potential of exosomes as a novel biomarker for predicting the radioresistance and develops a rapid and sensitive liquid biopsy method that will provide a personalized and precise strategy for clinical NPC treatment.

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.

Highly Efficient Blood Protein Analysis Using Membrane Purification Technique and Super-Hydrophobic SERS Platform for Precise Screening and Staging of Nasopharyngeal Carcinoma.

Early screening and precise staging are crucial for reducing mortality in patients with nasopharyngeal carcinoma (NPC). This study aimed to assess the performance of blood protein surface-enhanced Raman scattering (SERS) spectroscopy, combined with deep learning, for the precise detection of NPC. A highly efficient protein SERS analysis, based on a membrane purification technique and super-hydrophobic platform, was developed and applied to blood samples from 1164 subjects, including 225 healthy volunteers, 120 stage I, 249 stage II, 291 stage III, and 279 stage IV NPC patients. The proteins were rapidly purified from only 10 µL of blood plasma using the membrane purification technique. Then, the super-hydrophobic platform was prepared to pre-concentrate tiny amounts of proteins by forming a uniform deposition to provide repeatable SERS spectra. A total of 1164 high-quality protein SERS spectra were rapidly collected using a self-developed macro-Raman system. A convolutional neural network-based deep-learning algorithm was used to classify the spectra. An accuracy of 100% was achieved for distinguishing between the healthy and NPC groups, and accuracies of 96%, 96%, 100%, and 100% were found for the differential classification among the four NPC stages. This study demonstrated the great promise of SERS- and deep-learning-based blood protein testing for rapid, non-invasive, and precise screening and staging of NPC.

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.

Highly sensitive and reliable detection of microRNA for clinically disease surveillance using SERS biosensor integrated with catalytic hairpin assembly amplification technology.

MicroRNAs (miRNAs) play an important regulatory role in several diseases, especially as a class of promising biomarkers for cancer diagnosis and prognosis. Here, a biosensor based on surface enhanced Raman spectroscopy (SERS) combined with catalytic hairpin assembly (CHA) amplification technology was developed for ultra-sensitive detection of miRNA-21 and miRNA-155 in breast cancer serum. By using CHA strategy, the extremely low concentration of target microRNA in human serum can be significantly amplified through the re-hybridization with thousands of hairpin probes to trigger amplification cycles. Besides, a sandwich SERS sensing chip with numerous hot spots and signal self-calibration was built through the linkage between two-dimensional Au-Si substrate and upper Ag@4-MBA@Au core-shell nanoparticles. Using this specially-designed biosensing platform, a low detection limit of 0.398 fM and 0.215 fM with a dynamic range from 1 fM to 10 nM can be achieved for the detection of miRNA-21 and miRNA-155, respectively. Additionally, the analysis of these two miRNAs in serum samples is capable of identifying the breast cancer subjects from normal ones with 100% of accuracy, as well as potentially evaluating the molecular types and prognosis for breast cancer. These results demonstrate that the proposed SERS with CHA technology would be an alternative method for highly sensitive and reliable detection of miRNA biomarkers contributing to breast cancer diagnosis and prognosis.