The IL-10/STAT3 Axis Nasopharyngeal Carcinoma Cancer stem cell and radio resistance DOI Creative Commons
Lijun Wang, Ying Zhao,

Yan-sheng Wang

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Dec. 30, 2024

One of the primary reasons for failure therapy in nasopharyngeal cancer (NPC) is radio resistance-related localized one, which may lead to tumor residuals or recurrences. Several studies have linked interleukin-10 (IL-10) crucial functions development and response therapy. Its function NPC's resistance is, however, not well understood. Enzyme-linked immunosorbent assay (ELISA) quantitative real-time PCR were utilized confirming IL-10 expression NPC cell lines. The prognostic significance was also assessed via Kaplan-Meier analysis. CNE2R, a radioresistant line, expressed at high levels, shown be considerably elevated individuals with NPC, as measured by ELISA. Moreover, levels poor clinical outcomes prognosis cases. We showed some evidence link between hypoxia-inducible factor 1-alpha (HIF-1 A) serum NPC. Meanwhile, we find that up-regulated CSC. enhanced self-renewal tumorigenesis In terms mechanism, enhances CSC activating STAT3 pathway. IL-10/STAT3 Axis Nasopharyngeal Carcinoma Cancer stem resistance.

Language: Английский

Epidemiology of nasopharyngeal carcinoma: current insights and future outlook DOI
Zhi Yi Su, Pui Yan Siak,

Yu Yu Lwin

et al.

Cancer and Metastasis Reviews, Journal Year: 2024, Volume and Issue: 43(3), P. 919 - 939

Published: March 2, 2024

Language: Английский

Citations

38
An introduction to machine learning and generative artificial intelligence for otolaryngologists—head and neck surgeons: a narrative review DOI
Isaac L. Alter,

Karly Chan,

Jérôme R. Lechien

et al.

European Archives of Oto-Rhino-Laryngology, Journal Year: 2024, Volume and Issue: 281(5), P. 2723 - 2731

Published: Feb. 23, 2024

Language: Английский

Citations

15
Precision medicine in nasopharyngeal carcinoma: comprehensive review of past, present, and future prospect DOI Creative Commons
Pui Yan Siak, Win Sen Heng,

Sharon Siew Hoon Teoh

et al.

Journal of Translational Medicine, Journal Year: 2023, Volume and Issue: 21(1)

Published: Nov. 6, 2023

Nasopharyngeal carcinoma (NPC) is an aggressive malignancy with high propensity for lymphatic spread and distant metastasis. It prominent as endemic in Southern China Southeast Asia regions. Studies on NPC pathogenesis mechanism the past decades such through Epstein Barr Virus (EBV) infection oncogenic molecular aberrations have explored several potential targets therapy diagnosis. The EBV introduces oncoviral proteins that consequently hyperactivate many promitotic pathways block cell-death inducers. so prevalent patients serological tests were used to diagnose screen patients. On other hand, downstream effectors of mechanisms, can potentially be exploited therapeutically. With apparent heterogeneity distinct tumor, focus has turned into a more personalized treatment NPC. Herein this comprehensive review, we depict current status screening, diagnosis, treatment, prevention Subsequently, based limitations those aspects, look at their improvements moving towards path precision medicine. importance recent advances key aberration involved medicine progression also been reported present review. Besides, challenge future outlook management will highlighted.

Language: Английский

Citations

14
Application of image recognition technology in pathological diagnosis of blood smears DOI Creative Commons

Wangxinjun Cheng,

Jingshuang Liu, Chaofeng Wang

et al.

Clinical and Experimental Medicine, Journal Year: 2024, Volume and Issue: 24(1)

Published: Aug. 6, 2024

Abstract Traditional manual blood smear diagnosis methods are time-consuming and prone to errors, often relying heavily on the experience of clinical laboratory analysts for accuracy. As breakthroughs in key technologies such as neural networks deep learning continue drive digital transformation medical field, image recognition technology is increasingly being leveraged enhance existing processes. In recent years, advancements computer have led improved efficiency identification cells smears through use technology. This paper provides a comprehensive summary steps involved utilizing algorithms diagnosing diseases smears, with focus malaria leukemia. Furthermore, it offers forward-looking research direction development cell pathological detection system.

Language: Английский

Citations

4
Advances in Nasopharyngeal Carcinoma Staging: from the 7th to the 9th Edition of the TNM System and Future Outlook DOI

Binhao Wu,

Xiaozhong Chen, Caineng Cao

et al.

Current Oncology Reports, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 25, 2025

Language: Английский

Citations

0
Global utilization of artificial intelligence in the diagnosis and management of voice disorders over the past five years DOI Creative Commons

Amna Suleman,

Amy L. Rutt

Eye & ENT Research, Journal Year: 2025, Volume and Issue: unknown

Published: April 3, 2025

Abstract Objective This review evaluates the worldwide use of artificial intelligence (AI) for diagnosis and treatment voice disorders. Methods An electronic search was completed in Embase, Pubmed, Ovid MEDLINE, Scopus, Google Scholar, Web Science. Studies English from 2019 to 2024 evaluating AI detection management disorders were included. Preferred Reporting Items Systematic Reviews Meta‐Analyses guidelines followed. Results Eighty‐one studies recognized. Thirty‐three chosen screened quality assessment. Of these, 16 used determine normal versus pathological voice. The convolutional neural network (CNN) most employed algorithm among all machine learning algorithms. Conclusion revealed significant interest utilizing Gaps included limited, inconsistent data sets, lack validation, emphasis on rather than disorder. These are areas opportunity techniques improved diagnostic accuracy.

Language: Английский

Citations

0
Pre-treatment and post-treatment nasopharyngeal carcinoma imaging: imaging updates, pearls and pitfalls DOI Creative Commons
Kwok Yan Li, Hoi Ming Kwok, Nin Yuan Pan

et al.

Neuroradiology, Journal Year: 2025, Volume and Issue: unknown

Published: April 11, 2025

Language: Английский

Citations

0
Enhancing Nasopharyngeal Carcinoma Survival Prediction: Integrating Pre- and Post-Treatment MRI Radiomics with Clinical Data DOI
Luong Huu Dang, Shih‐Han Hung, Nhi Thao Ngoc Le

et al.

Deleted Journal, Journal Year: 2024, Volume and Issue: 37(5), P. 2474 - 2489

Published: April 30, 2024

Recurrences are frequent in nasopharyngeal carcinoma (NPC) despite high remission rates with treatment, leading to considerable morbidity. This study aimed develop a prediction model for NPC survival by harnessing both pre- and post-treatment magnetic resonance imaging (MRI) radiomics conjunction clinical data, focusing on 3-year progression-free (PFS) as the primary outcome. Our comprehensive approach involved retrospective MRI data collection of 276 eligible patients from three independent hospitals (180 training cohort, 46 validation 50 external cohort) who underwent scans twice, once within 2 months prior treatment 10 after treatment. From contrast-enhanced T1-weighted images before 3404 features were extracted. These not only derived lesion but also adjacent lymph nodes surrounding tumor. We conducted appropriate feature selection pipelines, followed Cox proportional hazards models analysis. Model evaluation was performed using receiver operating characteristic (ROC) analysis, Kaplan-Meier method, nomogram construction. unveiled several crucial predictors survival, notably highlighting synergistic combination assessments. demonstrated robust performance, an accuracy AUCs 0.66 (95% CI: 0.536-0.779) 0.717 0.536-0.883) testing 0.827 0.684-0.948) cohort prognosticating patient outcomes. presented novel effective leveraging features. Its constructed provides potentially significant implications research, offering clinicians valuable tool individualized planning counseling.

Language: Английский

Citations

3
Construction of disulfidptosis-based immune response prediction model with artificial intelligence and validation of the pivotal grouping oncogene c-MET in regulating T cell exhaustion DOI Creative Commons
Pengping Li, Shaowen Wang, Hong Wan

et al.

Frontiers in Immunology, Journal Year: 2024, Volume and Issue: 15

Published: Jan. 26, 2024

Background Given the lack of research on disulfidptosis, our study aimed to dissect its role in pan-cancer and explore crosstalk between disulfidptosis cancer immunity. Methods Based TCGA, ICGC, CGGA, GSE30219, GSE31210, GSE37745, GSE50081, GSE22138, GSE41613, univariate Cox regression, LASSO multivariate regression were used construct rough gene signature based for each type cancer. SsGSEA Cibersort, followed by correlation analysis, harnessed linkage Weighted network analysis (WGCNA) Machine learning utilized make a refined prognosis model pan-cancer. In particular, customized, enhanced was made glioma. The siRNA transfection, FACS, ELISA, etc., employed validate function c-MET. Results expression comparison disulfidptosis-related genes (DRGs) tumor nontumor tissues implied significant difference most cancers. immune cell infiltration, including T exhaustion (Tex), evident, especially 7-gene constructed as glioma prognosis. A suitable DSP clustering validated predict Furthermore, two groups defined machine survival therapy response glioma, which CGGA. PD-L1 other pathways highly enriched core blue module from WGCNA. Among them, c-MET driver JAK3-STAT3-PD-L1/PD1 regulator cells. Specifically, down-regulation decreased proportion PD1+ CD8+ Conclusion To summarize, we dissected roles DRGs their relationship with immunity general external datasets consistent result. survival-predicting specifically patients ICIs. C-MET screened regulation (inducing t-cell exhaustion)

Language: Английский

Citations

1
Automatic Annotation Diagnostic Framework for Nasopharyngeal Carcinoma via Pathology–Fidelity GAN and Prior-Driven Classification DOI Creative Commons
Siqi Zeng, Xinwei Li, Yiqing Liu

et al.

Bioengineering, Journal Year: 2024, Volume and Issue: 11(7), P. 739 - 739

Published: July 22, 2024

Non-keratinizing carcinoma is the most common subtype of nasopharyngeal (NPC). Its poorly differentiated tumor cells and complex microenvironment present challenges to pathological diagnosis. AI-based models have demonstrated potential in diagnosing NPC, but reliance on costly manual annotation hinders development. To address challenges, this paper proposes a deep learning-based framework for NPC without annotation. The includes novel unpaired generative network prior-driven image classification system. With pathology-fidelity constraints, achieves accurate digital staining from H&E EBER images. system leverages specificity prior knowledge annotate training data automatically classify images This work used 232 cases study. experimental results show that reached 99.59% accuracy classifying images, which closely matched diagnostic pathologists. Utilizing PF-GAN as backbone framework, attained 0.8826 generating markedly outperforming other GANs (0.6137, 0.5815). Furthermore, F1-Score patch level diagnosis was 0.9143, exceeding those fully supervised (0.9103, 0.8777). further validate its clinical efficacy, compared with experienced pathologists at WSI level, showing comparable performance. low-cost precise optimizes early method provides an innovative strategic direction cancer

Language: Английский

Citations

1