scholarly journals B-helper Neutrophils in Regional Lymph Nodes Correlate with Improved Prognosis in Patients with Head and Neck Cancer

Cancers ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 3092
Author(s):  
Ekaterina Pylaeva ◽  
Irem Ozel ◽  
Anthony Squire ◽  
Ilona Spyra ◽  
Charlotte Wallner ◽  
...  
Keyword(s):  
Head And Neck Cancer ◽  
Lymph Nodes ◽  
B Cell ◽  
Head And Neck ◽  
Neck Cancer ◽  
Patient Survival ◽  
Helper Cell ◽  
Cell Phenotype ◽  
Regional Lymph Nodes ◽  
Patient Prognosis

The role of neutrophils during cancer formation and elimination is diverse. Here, for the first time, we investigate neutrophil helper cells (NBH), their influence on B cell activity in the regional lymph nodes (RLN) of head-and-neck cancer patients and the effect of this neutrophil/B cell interaction on patient prognosis. Circulating and RLN neutrophils of patients with stage I–IV head-and-neck squamous cell carcinoma were investigated with flow cytometry and qPCR. In addition, neutrophil/B cell co-localization in RLNs was evaluated using immunohistochemistry. B cell proliferation was assessed and correlated with the distance to neutrophils. Patient survival was evaluated. Neutrophils with the helper cell phenotype were identified in the RLN of HNC patients. B cells in close proximity to such NBH showed significantly higher proliferation rates, together with elevated activation-induced cytidine deaminase (AID) expression. Notably, patient survival was significantly higher in individuals with high NBH frequencies in the B follicles of RLNs. Neutrophils in RLN can support T cell-independent activation of the adaptive immune system through B cell stimulation, capturing helper cell phenotype character. The presence of such helper neutrophils in the RLNs of HNC patients positively correlates with patient prognosis.

scholarly journals Cell Immunity in Regional Lymph Nodes in Patients with Head and Neck Cancer.

1993 ◽  
Vol 86 (11) ◽  
pp. 1653-1659
Author(s):  
Yuji Kano ◽  
Hiroyuki Kakuta ◽  
Junichi Hashimoto
Keyword(s):  
Head And Neck Cancer ◽  
Lymph Nodes ◽  
Head And Neck ◽  
Neck Cancer ◽  
Regional Lymph Nodes ◽  
Cell Immunity

scholarly journals Effects of Sizofiran on Regional Lymph Nodes in Patients with Head and Neck Cancer.

1994 ◽  
Vol 87 (4) ◽  
pp. 545-552
Author(s):  
Yuji KANO ◽  
Hiroyuki KAKUTA ◽  
Junichi HASHIMOTO
Keyword(s):  
Head And Neck Cancer ◽  
Lymph Nodes ◽  
Head And Neck ◽  
Neck Cancer ◽  
Regional Lymph Nodes

Effect of sizofiran on regional lymph nodes in patients with head and neck cancer

Biotherapy ◽  
1996 ◽  
Vol 9 (4) ◽  
pp. 257-262 ◽  
Author(s):  
Yuji Kano ◽  
Hiroyuki Kakuta ◽  
Junichi Hashimoto
Keyword(s):  
Head And Neck Cancer ◽  
Lymph Nodes ◽  
Head And Neck ◽  
Neck Cancer ◽  
Regional Lymph Nodes

NF-κB1 intronic region polymorphisms as risk factor for head and neck cancer in HPV-infected population from Pakistan

2021 ◽  
Vol 21 ◽  
Author(s):  
Sumaira Sarwar ◽  
Muammad Usman Tareen ◽  
Maimoona Sabir ◽  
Aneesa Sultan ◽  
Salman A Malik
Keyword(s):  
Head And Neck Cancer ◽  
Lymph Nodes ◽  
Head And Neck ◽  
Tobacco Use ◽  
Neck Cancer ◽  
Direct Sequencing ◽  
Hpv Infection ◽  
Pakistani Population ◽  
Specific Pcr ◽  
Increased Risk

Background: Head and neck cancer (HNC) developed due to the number of risk factors, including infection of Human Papillomavirus (HPV). The genetic predisposition also plays an important role in deregulating the NF-κB pathway, and certain polymorphisms are reported to affect the pathway genes. Objectives: The present study was conducted for the detection of HPV and polymorphisms in the NF-κB1 gene of HNC patients in the Pakistani population. Methods: Genomic DNA from HNC tumors samples were extracted using the Exgene SV DNA extraction Kit. Allele-specific PCR and direct sequencing were done for analysis of NF-κB1 SNPs, 94ins/del (rs28362491), rs1598858, and rs4648068. Results: The genotypes AG (36.2%/ 12%) of rs1598858, and AG (28.3%/ 12%) and GG (28.3%/ 22%) of rs4648068 were associated with significantly (p≤0.05) increased risk of head and neck cancer in studied population. Furthermore, among the HNC cases, genotypes AGrs1598858 (p≤0.014) and GGrs4648068 (p≤0.001) had increased risk of HPV related cancers. Tobacco use (OR-3.158442; [1.140, 8.754]), lymph nodes involvement (OR 4.05128; [1.854, 8.852]), and poorly differentiated tumors (OR 1.997155; [0.940, 4.245]) were positively associated with HPV induced cancers. Conclusion: It was the first comprehensive study from Pakistan, to evaluate the polymorphic variants of NF-κB1. Genotypes AGrs4648068, GGrs4648068, and AGrs1598858 of NF-κB1 gene are associated with increased risk of head and neck cancers in the Pakistani population. It can be concluded that HPV infection, lymph nodes and tobacco use can act synergetic to each other and add up in modulating HNC when present together with intronic SNPs of NF-κB1 gene.

scholarly journals Predictive quantitative ultrasound radiomic markers associated with treatment response in head and neck cancer

2020 ◽  
Vol 6 (1) ◽  
pp. FSO433 ◽  
Author(s):  
William T Tran ◽  
Harini Suraweera ◽  
Karina Quaioit ◽  
Daniel Cardenas ◽  
Kai X Leong ◽  
...  
Keyword(s):  
Head And Neck Cancer ◽  
Lymph Nodes ◽  
Head And Neck ◽  
Treatment Response ◽  
Neck Cancer ◽  
Quantitative Ultrasound ◽  
Area Under The Curve ◽  
Imaging Features ◽  
Metastatic Lymph Nodes ◽  
Metastatic Lymph

Aim: We aimed to identify quantitative ultrasound (QUS)-radiomic markers to predict radiotherapy response in metastatic lymph nodes of head and neck cancer. Materials & methods: Node-positive head and neck cancer patients underwent pretreatment QUS imaging of their metastatic lymph nodes. Imaging features were extracted using the QUS spectral form, and second-order texture parameters. Machine-learning classifiers were used for predictive modeling, which included a logistic regression, naive Bayes, and k-nearest neighbor classifiers. Results: There was a statistically significant difference in the pretreatment QUS-radiomic parameters between radiological complete responders versus partial responders (p < 0.05). The univariable model that demonstrated the greatest classification accuracy included: spectral intercept (SI)-contrast (area under the curve = 0.741). Multivariable models were also computed and showed that the SI-contrast + SI-homogeneity demonstrated an area under the curve = 0.870. The three-feature model demonstrated that the spectral slope-correlation + SI-contrast + SI-homogeneity-predicted response with accuracy of 87.5%. Conclusion: Multivariable QUS-radiomic features of metastatic lymph nodes can predict treatment response a priori.

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