P57.10 Clinicopathological Analysis of Anti-Tumor Immunology-Related Factors After Chemoradiotherapy for Lung Cancer

2021 ◽  
Vol 16 (10) ◽  
pp. S1142
Author(s):  
M. Noguchi ◽  
H. Date ◽  
T. Menju ◽  
M. Hamaji ◽  
A. Ohsumi ◽  
...  
Author(s):  
Hiromitsu Kanzaki ◽  
Yasushi Hamamoto ◽  
Kei Nagasaki ◽  
Toshiyuki Kozuki

Abstract Purpose Neutrophil-to-lymphocyte ratio (NLR) has been reported to be associated with treatment outcomes in various cancers; however, the optimal timing to measure NLR is unclear. In this study, “average-NLR” was newly devised, which reflects the NLR throughout the course of radiotherapy, and its usefulness was assessed for stage III non-small cell lung cancer (NSCLC) patients treated with chemoradiotherapy. Materials and methods A total of 111 patients who received definitive chemoradiotherapy for unresectable stage III NSCLC were reviewed. Patient/tumor-related factors, treatment-related, and NLR-related factors (average-NLR, pre- and post-radiotherapy NLR, NLR-nadir, NLR-maximum) were assessed using univariate and multivariate analyses. Results The median follow-up period was 43.8 months among the survivors. In the multivariate analysis, average-NLR and post-radiotherapy NLR were significant factors for the overall survival (OS) (p = 0.016 and 0.028) and distant failure (DF) (p = 0.008 and 0.040). For the patients with low, intermediate, and high average-NLR, the median OS was 41.2, 37.7, and 14.8 months, respectively, and the median DF free time was 52.5, 13.5, and 8.9 months, respectively. Conclusion Average-NLR and post-radiotherapy NLR were significant factors for the OS and DF. Average-NLR, which was available immediately after the completion of chemoradiotherapy, seemed to be helpful for treatment decisions.


Author(s):  
Jiongwei Pan ◽  
Gang Huang ◽  
Zhangyong Yin ◽  
Xiaoping Cai ◽  
Enhui Gong ◽  
...  

AbstractSignificantly high-expressed circFLNA has been found in various cancer cell lines, but not in lung cancer. Therefore, this study aimed to explore the role of circFLNA in the progression of lung cancer. The target gene of circFLNA was determined by bioinformatics and luciferase reporter assay. Viability, proliferation, migration, and invasion of the transfected cells were detected by CCK-8, colony formation, wound-healing, and transwell assays, respectively. A mouse subcutaneous xenotransplanted tumor model was established, and the expressions of circFLNA, miR-486-3p, XRCC1, CYP1A1, and related genes in the cancer cells and tissues were detected by RT-qPCR, Western blot, or immunohistochemistry. The current study found that miR-486-3p was low-expressed in lung cancer. MiR-486-3p, which has been found to target XRCC1 and CYP1A1, was regulated by circFLNA. CircFLNA was located in the cytoplasm and had a high expression in lung cancer cells. Cancer cell viability, proliferation, migration, and invasion were promoted by overexpressed circFLNA, XRCC1, and CYP1A1 but inhibited by miR-486-3p mimic and circFLNA knockdown. The weight of the xenotransplanted tumor was increased by circFLNA overexpression yet reduced by miR-486-3p mimic. Furthermore, miR-486-3p mimic reversed the effect of circFLNA overexpression on promoting lung cancer cells and tumors and regulating the expressions of miR-486-3p, XRCC1, CYP1A1, and metastasis/apoptosis/proliferation-related factors. However, overexpressed XRCC1 and CYP1A1 reversed the inhibitory effect of miR-486-3p mimic on cancer cells and tumors. In conclusion, circFLNA acted as a sponge of miR-486-3p to promote the proliferation, migration, and invasion of lung cancer cells in vitro and in vivo by regulating XRCC1 and CYP1A1.


2017 ◽  
Vol 35 (5) ◽  
pp. 345-357 ◽  
Author(s):  
Li-Fang Zhou ◽  
Mao-Xin Zhang ◽  
Ling-Qian Kong ◽  
Gary H. Lyman ◽  
Ke Wang ◽  
...  

2010 ◽  
Vol 11 (3) ◽  
pp. 117-120 ◽  
Author(s):  
Ahmet Emin Erbaycu ◽  
Mehmet Gulpek ◽  
Fevziye Tuksavul ◽  
Ozgur Uslu ◽  
Salih Zeki Guclu

2014 ◽  
Vol 48 (1) ◽  
pp. 10 ◽  
Author(s):  
Dae Hyun Song ◽  
In Ho Choi ◽  
Sang Yun Ha ◽  
Kang Min Han ◽  
Jae Jun Lee ◽  
...  

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