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.

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.

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.

Metformin reverses the drug resistance of cisplatin in irradiated CNE-1 human nasopharyngeal carcinoma cells through PECAM-1 mediated MRPs down-regulation.

Objective: To explore a way to reverse the drug resistance for irradiated CNE-1 human nasopharyngeal carcinoma cells and try to develop a new high efficacy with low toxicity therapeutic approach. Methods: 300 Gy irradiated the CNE-1 human nasopharyngeal carcinoma cells, and then treated with single-agent cisplatin or metformin, or combination of both drugs. MTT assay and FCM were applied to detect cell viability and apoptosis. Western blot and RT-PCR were used to characterize the protein and mRNA expression after various drug administrations. Results: The results presented single-agent metformin was capable of arresting the tumor growth and inducing apoptosis in irradiated CNE-1 cells and also demonstrated a synergy effect with cisplatin. Furthermore, metformin down-regulates the PECAM-1 expression, which could regulate Multi-drug Resistance-associate Proteins (MRPs) expression leading to cisplatin resistance of irradiated CNE-1 cells. A pan-MRP inhibitor, probenecid, can resecure cisplatin resistance leading by radiation. Conclusions: Metformin, due to its independent effects on PECAM-1, had a unique anti-proliferative effect on irradiated CNE-1 cells. It would be a new therapeutic option to conquer cisplatin resistance for advanced NPC patients after radiotherapy.

Label-free liquid biopsy based on blood circulating DNA detection using SERS-based nanotechnology for nasopharyngeal cancer screening.

Development of a sensitive, rapid and easy-to-use liquid biopsy method is of imperative clinical value for point-of-care caner diagnostics. Here, a label-free and modification-free nanotechnology based on surface-enhanced Raman spectroscopy (SERS) was employed for DNA analysis. Using the SERS signals of phosphate backbone as internal standard, quantitative detection for nucleobases was achieved even at single base level. The method combined with principal component analysis and linear discriminant analysis was further applied for real blood circulating DNA detection for the first time, and an ideal diagnostic sensitivity of 83.3% and specificity of 82.5% could be obtained for differentiating the nasopharyngeal cancer from the normal group, demonstrating promising potential as an alternative nanotechnology for nasopharyngeal cancer screening based on liquid biopsy.

Metal Carbonyls for the Biointerference-Free Ratiometric Surface-Enhanced Raman Spectroscopy-Based Assay for Cell-Free Circulating DNA of Epstein-Barr Virus in Blood.

By taking advantage of the spectral properties of metal carbonyls, we have designed a surface-enhanced Raman spectroscopy (SERS) ratiometric assay for measuring cell-free circulating DNA (cfDNA) from Epstein-Barr virus in blood for nasopharyngeal carcinoma (NPC). This assay consists of a rhenium carbonyl (Re-CO) to serve as a DNA probe, an osmium carbonyl (Os-CO) embedded within the SERS-active substrate as an internal reference, and a streptavidin layer on the surface of the substrate. Hybridization of cfDNA with biotinylated-capture sequence leads to immobilization of cfDNA on the substrate. The binding of Re-CO via daunorubicin (DNR) to cfDNA is accompanied by an appearance of a strong symmetry stretching vibrations peak at 2113 cm-1, which has spectral overlap with Os-CO (2025 cm-1). This results in an increase in the I2113/ I2025 ratio and quantitatively correlates with cfDNA. This SERS assay can be readily used to detect cfDNA in blood samples from patients due to the intensity ratio of I2113/ I2025 lying in a silent region (1780-2200 cm-1) in the SERS spectrum of the biomolecules.

Diagnostic potential of polarized surface enhanced Raman spectroscopy technology for colorectal cancer detection.

The purpose of this study was to develop a more powerful blood analysis method based on polarized surface enhanced Raman spectroscopy (SERS) technology for non-invasive and sensitive colorectal cancer (CRC) detection. The efficiency of different polarized scattering signals (non-polarization, parallel polarization and perpendicular polarization) on blood serum SERS was explored for the first time. Results demonstrated that polarized SERS was more sensitive to explore distinctive spectral differences between cancer and normal groups. And higher diagnostic accuracy of 91.6% could be achieved using polarized SERS integrated with PCA-LDA for classification of the two serum groups in comparison to conventional SERS technology. This exploratory study demonstrated that the nanobiosensor based on polarized SERS technique in conjunction with PCA-LDA provided a novel strategy for blood SERS analysis, and had the potential as a clinical complement for CRC screening.

Label-free optical sensor based on red blood cells laser tweezers Raman spectroscopy analysis for ABO blood typing.

The clinical significance of ABO blood typing extends beyond transfusion medicine and is demonstrated to be associated with susceptibility to various diseases, even including cancer. In this study, a home-made laser tweezers Raman spectroscopy (LTRS) system was applied to detect red blood cells (RBCs) with the aim to develop a label-free, simple and objective blood typing method for the first time. High-quality Raman spectra of RBCs in the fingerprint region of 420-1700 cm-1 can be obtained, meanwhile exciting blood typing results can be achieved, especially with an accuracy of 100% for identifying Type AB from other blood types with the use of multivariate statistical analysis based on principal component analysis (PCA) combined with linear discriminant analysis (LDA). This primary work demonstrates that the label-free RBCs LTRS analysis in conjunction with PCA-LDA diagnostic algorithms has great potential as a biosensor for ABO blood typing.

Is Gemcitabine and Cisplatin Induction Chemotherapy Superior in Locoregionally Advanced Nasopharyngeal Carcinoma?

OBJECTIVE: To investigate the outcome of locoregionally advanced nasopharyngeal carcinoma (NPC) treated with induction chemotherapy followed by chemoradiotherapy. METHODS: Between June 2005 and October 2007, 604 patients with locoregionally advanced NPC were analyzed, of whom 399 and 205 were treated with conventional radiotherapy and intensity-modulated radiotherapy (IMRT) respectively. Meanwhile, 153 patients received concurrent chemotherapy, and 520 were given induction chemotherapy. RESULTS: With a median follow-up time of 65 months, the 3-, and 5-year overall survival (OS), locoregional free survival (LRFS), and distant-metastasis free survival (DMFS) rates were 82.5% vs. 72.6%, 90.6% vs. 87.1%, and 82.5% vs. 81.2%, respectively. Induction chemotherapy was not an independent prognostic factor for OS (P=0.193) or LRFS, but there was a positive tendency for DMFS (P=0.088). GP regimen (gemcitabine + cisplatin) was an independent prognostic factor for OS (P = 0.038) and it had a trend toward improved DMFS (P = 0.109). TP regimen (taxol + cisplatin) was only a significant prognostic factor for DMFS (P =0.038). CONCLUSIONS: Adding induction chemotherapy had no survival benefit, but GP regimen benefited overall survival and had a trend toward improved DMFS. GP regimen may be superior to TP/FP regimen (fluorouracil + cisplatin) in treating locoregionally advanced NPC.

Advantages of intensity modulated radiotherapy in recurrent T1-2 nasopharyngeal carcinoma: a retrospective study.

BACKGROUND: Recurrent T1-2 Nasopharyngeal Carcinoma (rT1-2) may be salvaged by 3D - CRT (3D-Conformal Radiotherapy), IMRT (Intensity Modulated Radiotherapy), Brachytherapy (BT), BT with external radiotherapy. The purpose of this study is to address the efficacy and toxicity profile of aforementioned four modalities for rT1-2 NPC. METHODS: 168 patients, median age 48 years (range 16-75 years) proven rT1-2 NPC were diagnosed and treated with four different irradiation modalities (3D-CRT, IMRT, BT, BT with external radiotherapy). Median time to recurrence was 30 months (range 1-180 months). The median follow-up time was 28 months (range, 4-135 months). RESULTS: 161 patients completed a median dose of 6445 cGy (ranging 30 to 87 Gy). Seven patients prematurely terminated their treatment due to acute side-effects and received 30-49 Gy. The 1- and 3-year local regional recurrent free survival (LRRFS), distant free survival (DFS), and overall survival (OS) rates were 82.03% vs. 82.03% vs. 82.58%, 51.33% vs. 51.33% vs. 53.41, respectively. Gender and recurrence T-classification were the two significant adverse prognostic factors for LRRFS, DFS, and OS rates. Grade 3 or 4 toxicities were tolerable. CONCLUSION: 3D-CRT, IMRT, BT, BT with external radiotherapy are feasible and efficacious for rT1-2 NPC. In toxicity 3D-CRT/IMRT group is lower than BT group. IMRT is superior for rT1-2 NPC.

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.

Molecular separation-assisted label-free SERS combined with machine learning for nasopharyngeal cancer screening and radiotherapy resistance prediction.

Nasopharyngeal cancer (NPC) is a malignant tumor with high prevalence in Southeast Asia and highly invasive and metastatic characteristics. Radiotherapy is the primary strategy for NPC treatment, however there is still lack of effect method for predicting the radioresistance that is the main reason for treatment failure. Herein, the molecular profiles of patient plasma from NPC with radiotherapy sensitivity and resistance groups as well as healthy group, respectively, were explored by label-free surface enhanced Raman spectroscopy (SERS) based on surface plasmon resonance for the first time. Especially, the components with different molecular weight sizes were analyzed via the separation process, helping to avoid the possible missing of diagnostic information due to the competitive adsorption. Following that, robust machine learning algorithm based on principal component analysis and linear discriminant analysis (PCA-LDA) was employed to extract the feature of blood-SERS data and establish an effective predictive model with the accuracy of 96.7% for identifying the radiotherapy resistance subjects from sensitivity ones, and 100% for identifying the NPC subjects from healthy ones. This work demonstrates the potential of molecular separation-assisted label-free SERS combined with machine learning for NPC screening and treatment strategy guidance in clinical scenario.

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.

High buttocks supine position to reduce small bowel exposure in gynecological radiotherapy.

PURPOSE: To minimize radiation exposure to the small bowel (SB) in patients undergoing treatment for gynecological tumors by adopting a comfortable positioning method. METHODS AND PATIENTS: All 76 women undergoing Intensity-Modulated Radiation Therapy (IMRT) were included in this study. Patients were immobilized in a supine position using a vacuum bag and thermoplastic cast formation. In the trial group (n = 36), patients raised their buttocks and a solid foam pad was placed under the sacral tail before immobilization. The control group (n = 40) received treatment in the standard supine position. The SB was delineated from the pubic symphysis to the total iliac bifurcation in computed tomography (CT) scans. RESULT: In the trial group, a significant reduction in SB volume within the pelvic cavity was observed (mean 399.17 ± 158.7 cc) compared to the control group (mean 547.48 ± 166.9 cc), with a p-value less than 0.001. The trial group showed a statistically significant reduction in the absolute volume of irradiated SB at each dose, ranging from the low dose (10 Gy) to the high dose (45 Gy). In the control group, a negative correlation was found between SB and bladder volumes (R = -0.411, P = 0.008), whereas in the trial group, this correlation was weaker (R = -0.286, P = 0.091), with no significant relationship observed between bladder volume and SB. CONCLUSION: The high buttocks supine position effectively reduces SB radiation exposure without the need for bladder distension. This positioning method holds promise for reducing SB irradiation in various pelvic tumors.

Early recurrence as a pivotal event in nasopharyngeal carcinoma: identifying predictors and key molecular signals for survivors.

PURPOSE: The duration of response to treatment is a significant prognostic indicator, with early recurrence (ER) often predicting poorer survival outcomes in nasopharyngeal carcinoma (NPC) survivors. This study seeks to elucidate the factors contributing to the onset of ER following radiotherapy in NPC survivors. METHODS: This investigation encompassed 2,789 newly diagnosed NPC patients who underwent radical intensity-modulated radiotherapy. Ordinal logistic regression analysis was employed to evaluate the independent predictors of earlier recurrence. A machine learning-based prediction model of NPC recurrence patterns was developed. Tumorous RNA-sequencing (in-house cohort: N = 192) and biological tipping point analysis were utilized to infer potential molecular mechanisms associated with ER. RESULTS: Our results demonstrated that ER within 24 months post-initial treatment was the optimal time frame for identifying early malignant progression in NPC survivors. The ER cohort (150 of 2,789, 5.38%) exhibited a notably short median overall survival of 48.6 months. Multivariate analyses revealed that male gender, T4 stage, local or regional residual disease, detectable pre- and post-radiotherapy EBV DNA, and the absence of induction chemotherapy were significant predictors of earlier recurrence. The machine learning-based predictive model further underscored the importance of tumor-related factors in NPC recurrence. Moreover, ER emerged as a pivotal stage in NPC progression, with 15 critical transition signals identified potentially associated with the negative modulation of the immune response. CONCLUSIONS: Our comprehensive analysis of NPC recurrence patterns has unveiled insights into the key factors driving ER and provided novel insights into potential early warning biomarkers and the mechanisms underlying NPC progression.

Inhibition of PNCK inflames tumor microenvironment and sensitizes head and neck squamous cell carcinoma to immune checkpoint inhibitors.

BACKGROUND: The landscape of the tumor microenvironment (TME) is intricately linked to the development of head and neck squamous cell carcinoma (HNSCC) and significantly influences immunotherapy efficacy. Recent research has underscored the pivotal role of PNCK in cancer progression, yet its relationship with immunotherapy remains elusive. METHODS: We leveraged sequencing data from our cohort and public databases to evaluate PNCK expression, prognostic significance, and immune efficacy prediction. In vitro and in vivo experiments explored the role of PNCK in HNSCC progression. Animal models assessed the therapeutic effects and survival benefits of PNCK knockdown combined with immune checkpoint inhibitors (ICIs). Single-cell transcriptomics analyzed the impact of PNCK on the TME, and proteomic studies elucidated the mechanisms. RESULTS: PNCK exerts multifaceted critical roles in the progression of HNSCC. Lower PNCK expression is associated with improved prognosis, enhanced immune cell infiltration, and increased responsiveness to ICIs. Conversely, PNCK promotes HNSCC cell migration, invasion, proliferation, colony formation, zebrafish angiogenesis, and tumor growth in mice. Moreover, targeting PNCK enhances sensitivity to ICIs and leads to significant alterations in the T-cell and B-cell ratios within the TME. These changes are attributed to the inhibition of nuclear transcription of PNCK-phosphorylated ZEB1, which restricts cytokine release and inflames the immune microenvironment to regulate the TME. CONCLUSIONS: Inhibition of PNCK may be a potential strategy for treating HNSCC, as it may activate the immune response and improve the TME, thereby enhancing the efficacy of immunotherapy for HNSCC patients.

Prognostic value of immune-inflammatory and nutrition indicators in non-metastatic nasopharyngeal carcinoma with negative plasma Epstein-Barr virus DNA.

Background: Plasma Epstein-Barr virus (EBV) DNA has been identified as a significant prognostic marker for nasopharyngeal carcinoma (NPC), yet there is limited research on the prognosis of NPC patients with negative EBV DNA. Objectives: We explore the prognostic value of comprehensive immune-inflammatory and nutritional indicators to offer personalized treatment recommendations and prognosis predictions for non-metastatic NPC patients with negative EBV DNA. Design: This was a retrospective study. Methods: This study retrospectively analyzed 257 non-metastatic NPC patients with negative EBV DNA between January 2015 and December 2019. The Kaplan-Meier survival curves evaluated survival endpoints, and group discrepancies were assessed with log-rank tests. Principal component analysis (PCA) reduced data dimensionality. Univariate and multivariate Cox regression analyses identified significant prognostic variables. Risk stratification was performed based on recursive partitioning analysis (RPA). A robust prognostic model was constructed by nomogram and evaluated by calibration curves, decision curves, and the time-dependent area under the curve analysis. Results: PCA was employed to compute the immune-inflammation index (III) and nutrition index (NI). Multivariate Cox regression analysis revealed lactate dehydrogenase, III, and NI as significant prognostic variables for overall survival (OS). Utilizing RPA, we stratified the risk into three categories: low-risk group (low III + high NI), middle-risk group (low III + low NI), and high-risk group (high III). Both the middle- (p = 0.025) and high-risk groups (p < 0.001) exhibited poorer OS compared with the low-risk group. The nomogram model exhibited superior predictive accuracy compared to tumor lymph node metastasis stage alone (C-index: 0.774 vs 0.679). Conclusion: Our study validated the prognostic significance of III and NI in non-metastatic NPC patients with negative EBV DNA. Additionally, a clinical risk stratification was constructed to offer valuable insights into the individualized treatment of these patients.

Biomarkers of inflammation and nutrition can effectively predict the prognosis of EBV DNA-negative non-metastatic nasopharyngeal carcinoma Why was the study done? Plasma Epstein-Barr virus (EBV) DNA has shown efficacy in predicting survival and disease progression in individuals with nasopharyngeal carcinoma (NPC). However, a subset of patients exhibit negative EBV DNA levels. Currently, there is limited research available on the prognostic implications for this particular patient population. What did the researchers do? The researchers gathered clinical data from Fujian Cancer Hospital between 2015 and 2019 in order to investigate the potential of immune-inflammatory and nutritional markers in predicting both survival rates and disease progression among patients diagnosed with EBV DNA-negative, non-metastatic NPC. Additionally, the study aimed to assess the feasibility of utilizing these markers to offer personalized treatment recommendations for this specific patient population. What did the researchers find? A total of 257 non-metastatic NPC patients with negative EBV DNA were included in the study for clinical data collection. The findings suggest that a lower immune-inflammation index and a higher nutrition index were correlated with extended overall survival (OS) in this patient population. Furthermore, the study indicates that the survival advantage of abstaining from induction chemotherapy (IC) may be more pronounced in this particular cohort. What do the findings mean? This study has identified immune-inflammatory and nutritional markers as predictive of survival in NPC patients with EBV DNA-negative and raised thinking about reducing treatment intensity and improving the quality of life in this population patients in the future.

Comparative evaluation of machine learning models in predicting overall survival for nasopharyngeal carcinoma using 18F-FDG PET-CT parameters.

PURPOSE: The objective of this study is to assess the prognostic efficacy of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET-CT) parameters in nasopharyngeal carcinoma (NPC) and identify the best machine learning (ML) prognostic model for NPC patients based on these 18F-FDG PET/CT parameters and clinical variables. METHOD: A cohort of 678 patients diagnosed with NPC between 2016 and 2020 was analyzed in this study. The model was constructed using four advanced ML algorithms, namely Random Forest (RF), Extreme Gradient Boosting (XGBoost), Least Absolute Shrinkage and Selection Operator (LASSO), and multifactor COX step-up regression. Statistical significance of the models was assessed using Kaplan-Meier (K-M) curves, with a significance level established at P < 0.05. The prognostic efficacy of the models was evaluated through the analysis of receiver operating characteristic (ROC) curves, with the area under the ROC curve (AUC) serving as a criterion for model selection. The decision curve analysis (DCA) and concordance index (C-index) were employed to assess the precision of the optimal model. RESULTS: Multivariate analysis revealed age, T stage, and metabolic tumor volume (MTV) for the primary nasopharyngeal tumor (MTVT) as significant independent prognostic factors for overall survival (OS) in NPC patients. Additionally, the LASSO model identified six key variables, including peak standardized uptake value (SUV-peak) for the primary nasopharyngeal tumor (SUV-peak(T)), MTVT, heterogeneity index for neck lymph nodes (HIN), age, pathological type, and T stage. Remarkably, the LASSO model demonstrated superior performance with a 5-year AUC of 0.849 compared to other models. Further assessment using the C-index and DCA confirmed the accuracy of the LASSO model. Subgroup analysis revealed notable risk factors, such as a high heterogeneity index (HI) for the primary nasopharyngeal tumor (HIT), MTV values for neck lymph nodes (MTVN), and HIN. CONCLUSIONS: We developed a novel prognostic machine learning model that integrates 18F-FDG PET-CT parameters and clinical characteristics, significantly enhancing prognosis prediction in NPC.

Impact of the radiotherapy rhythm on prognosis in nasopharyngeal carcinoma.

OBJECTIVE: The role of chronoradiobiology in nasopharyngeal carcinoma (NPC) has not been fully elucidated. We sought to investigate the impact of radiotherapy rhythm on the survival outcomes of individuals to explore a chronomodulated radiation strategy to improve prognosis of NPC. METHODS: A cohort comprising non-metastatic NPC patients subjected to intensity-modulated radiotherapy at Fujian Cancer Hospital between Jan. 2016 and Dec. 2019 was assembled. Rhythmic fluctuation of radiotherapy (RFRT) was quantified based on the temporal distribution of radiation delivery. Cox proportional hazard model was performed to explore the impact of radiotherapy rhythm on all-cause mortality. The maximally selected rank statistics method was employed to discern an optimal cutoff. Sensitivity analyses were conducted to ensure the robustness of observed associations. RESULTS: Our analysis encompassed 2245 patients, with a median follow-up duration of 55 months, during which 315 individuals succumbed. Multivariate Cox regression analysis unveiled a significant correlation between prolonged RFRT and heightened mortality risk in NPC patients (HR, 1.17, 95% CI, 1.07-1.27, p < .001), a relationship robust to comprehensive adjustment for confounding variables. A cutoff value of 3 h was selected for potential clinical application, beyond which patients exhibited markedly poorer survival outcomes. Subgroup analyses consistently underscored the directional consistency of observed effects. CONCLUSION: Our study sheds light on the potential advantages of scheduling radiotherapy sessions at consistent times. These findings have implications for optimizing radiotherapy schedules and warrant further investigation into personalized chronotherapy approaches in NPC management.

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.