Abstract:was observed in patients with a lower absolute baseline Neutrophil count (Less than 7500); conversely, a higher absolute Lymphocyte baseline count was linked with a longer TTP (3.7 months vs 1.8; Cox regression rate (HR) 0.9994947, p¼ 0.055 (CI 0.9989785-1.000011). NLR was correlated with Time to Progression (TTP), that was longer in patients with NLR less than 4 (3.71 months vs 1.87 ; Cox regression rate (HR) 1.144335, p¼ 0.001 (CI 1.068327-1.22575) (Figure). Conclusion: These preliminary findings highlight t… Show more
“…In recent years, many studies have confirmed that Nanog can increase the malignancy of tumors, leading to an increased risk of prognostic death in patients with malignant tumors ( 10 - 12 ). In this study, the Nanog positive rate of NSCLC tissues was 68.54%, which was significantly higher than that of normal tissues adjacent to the tumor, which is consistent with the results reported in previous studies ( 13 ). It has also been reported that the Nanog protein may play an important role in the initial stages of lung cancer occurrence and development ( 14 ).…”
Background: This study aimed to explore the expression of Nanog and fibroblast growth factor-inducible molecule 14 (Fn14) in patients with non-small cell lung cancer (NSCLC), and to explore their relationship with pathological characteristics and prognosis. Methods: The clinical data of 89 patients with NSCLC admitted to this hospital from March 2015 to January 2019 were analyzed. The expression of Nanog and Fn14 in NSCLC tissues and normal tissues (5 cm around the tumor tissue) were analyzed by immunohistochemical staining. The relationship between Nanog and Fn14 expression and the patients' pathological parameters was analyzed. Receiver operating characteristic curve (ROC) and Kaplan-Meier survival curves were drawn to analyze the influence of Nanog and Fn14 expression on prognosis, and logistic regression analysis was used to examine the related factors affecting the 2-year prognostic mortality of patients. Results: The positive rates of Nanog and Fn14 in the observation group were significantly higher than those in the control group (P<0.05). The positive expression rates of Nanog and Fn14 were higher in patients with moderate/high differentiation, TNM stage III-IV, and lymph node metastasis (P<0.05). Among 89 patients with NSCLC, 25 patients died within 2 years of follow-up, with a survival rate of 71.91%. The mortality of patients with positive expression of Nanog and Fn14 was significantly higher than that of patients with negative expression (P<0.05). The median survival times of patients with negative and positive Nanog expression were (20.60±2.71) months and (18.03±2.11) months, respectively. The median survival times of patients with negative and positive Fn14 expression were (19.55±2.60) months and (15.65±2.14) months, respectively. The Kaplan-Meier survival curve showed that patients with both negative expression of Nanog and Fn14 had a longer survival time (P<0.05). Poor differentiation, TNM stage III-IV, lymph node metastasis, positive expression of Nanog, and positive expression of Fn14 were identified as risk factors affecting the prognostic mortality of patients with NSCLC (P<0.05).Conclusions: Nanog and Fnl4 are closely related to the occurrence, development, and prognosis of NSCLC. Detection of their expression levels can provide reliable information for the early diagnosis of patients with NSCLC.
“…In recent years, many studies have confirmed that Nanog can increase the malignancy of tumors, leading to an increased risk of prognostic death in patients with malignant tumors ( 10 - 12 ). In this study, the Nanog positive rate of NSCLC tissues was 68.54%, which was significantly higher than that of normal tissues adjacent to the tumor, which is consistent with the results reported in previous studies ( 13 ). It has also been reported that the Nanog protein may play an important role in the initial stages of lung cancer occurrence and development ( 14 ).…”
Background: This study aimed to explore the expression of Nanog and fibroblast growth factor-inducible molecule 14 (Fn14) in patients with non-small cell lung cancer (NSCLC), and to explore their relationship with pathological characteristics and prognosis. Methods: The clinical data of 89 patients with NSCLC admitted to this hospital from March 2015 to January 2019 were analyzed. The expression of Nanog and Fn14 in NSCLC tissues and normal tissues (5 cm around the tumor tissue) were analyzed by immunohistochemical staining. The relationship between Nanog and Fn14 expression and the patients' pathological parameters was analyzed. Receiver operating characteristic curve (ROC) and Kaplan-Meier survival curves were drawn to analyze the influence of Nanog and Fn14 expression on prognosis, and logistic regression analysis was used to examine the related factors affecting the 2-year prognostic mortality of patients. Results: The positive rates of Nanog and Fn14 in the observation group were significantly higher than those in the control group (P<0.05). The positive expression rates of Nanog and Fn14 were higher in patients with moderate/high differentiation, TNM stage III-IV, and lymph node metastasis (P<0.05). Among 89 patients with NSCLC, 25 patients died within 2 years of follow-up, with a survival rate of 71.91%. The mortality of patients with positive expression of Nanog and Fn14 was significantly higher than that of patients with negative expression (P<0.05). The median survival times of patients with negative and positive Nanog expression were (20.60±2.71) months and (18.03±2.11) months, respectively. The median survival times of patients with negative and positive Fn14 expression were (19.55±2.60) months and (15.65±2.14) months, respectively. The Kaplan-Meier survival curve showed that patients with both negative expression of Nanog and Fn14 had a longer survival time (P<0.05). Poor differentiation, TNM stage III-IV, lymph node metastasis, positive expression of Nanog, and positive expression of Fn14 were identified as risk factors affecting the prognostic mortality of patients with NSCLC (P<0.05).Conclusions: Nanog and Fnl4 are closely related to the occurrence, development, and prognosis of NSCLC. Detection of their expression levels can provide reliable information for the early diagnosis of patients with NSCLC.
“…By combining HRs of high NLR versus low NLR with regard to PFS from 10 studies, 16–19,26,28,32,33,35,36 the pooled result using random effect model showed that the estimated effect was 1.44(95%CI: 1.18, 1.77), indicating NSCLC patients with low pre-treatment NLR had a 1.44 times of getting better PFS(Figure 2A). As shown in Figure 2B, the pooled HRs of OS from eight studies 16,18,19,28,30,33,35,36 using random effect model was 1.75(95%CI: 1.33, 2.30), favoring NSCLC patients with low pre-treatment NLR.10.1080/2162402X.2018.1507262-F0002Figure 2.Comparisons of PFS and OS in Nivolumab treated NSCLC patients with different baseline NLR.…”
Section: Combined Resultsmentioning
confidence: 99%
“…The studies 16-19,26,28,32,33,35,36 included reported the HRs of high NLR versus low NLR on PFS in the treatment of advanced NSCLC. As shown in Figure 3A, the estimated effect of NLR < 5 was 1.19 (95%CI: 1.00, 1.41; p = 0.06), and it was 1.73(95%CI: 1.14, 2.62; p = 0.009) for NLR ≥ 5.…”
Objective: Nivolumab has been used for treating non-small cell lung cancer (NSCLC) worldwide. Whether neutrophil-lymphocyte ratio (NLR) can predict the prognosis of NSCLC treated with Nivolumab is still under debate. This meta-analysis was to assess the significance of NLR as a predictive factor in NSCLC patients receiving Nivolumab.Methods: Databases including PubMed, Embase, and the Cochrane library were searched to identify eligible studies evaluating the role of NLR in predicting prognosis of NSCLC treated with Nivolumab until March 2018 without language restrictions. The meta-analysis was performed using hazard ratio (HR) of progression free survival (PFS) and overall survival (OS) in NSCLC patients with various NLR.Results: A total of 14 retrospective studies consisting of 1225 NSCLC patients were included. The combined results showed that relatively higher baseline NLR was associated with poor PFS (HR = 1.44; 95% confidence interval (CI):1.18–1.77; p < 0.05) and OS (HR = 1.75; 95% CI: 1.33–2.30; p < 0.05) after treatment of Nivolumab. Subgroup analysis suggested that NLR ≥ 5 was more reliable for PFS (HR = 1.73; 95%CI: 1.14, 2.62; p < 0.05) and OS (HR = 1.76; 95%CI: 1.47, 2.10; p < 0.05). In addition, post-treatment NLR also had predictive roles for PFS (HR = 3.17; 95%CI: 1.48, 6.82; p < 0.05) and OS (HR = 2.26; 95%CI: 1.05, 4.86; p < 0.05).Conclusion: Our findings suggest that NLR can be used as a prognostic biomarker for NSCLC treating with Nivolumab, and the recommended cutoff value of NLR is 5.
“…At present, monoclonal antibody-targeted drugs are leading to innovations in the treatment of lung cancer. Most notably, immunotherapy with programmed cell death protein 1 (PD-1) and CD274 as targets has achieved significant results in clinical trials of lung cancer treatment (Galetta et al, 2017 ; Choy et al, 2019 ). Currently, these targeted drugs can be used as first or second-line drugs for lung cancer since more than 50% of tumor cells in patients express programmed death-ligand 1 (PD-L1) (Ru and Zhuang, 2018 ).…”
Background: Lung cancer is one of the most common types of cancer, and it has a poor prognosis. It is urgent to identify prognostic biomarkers to guide therapy.Methods: The immune gene expression profiles for patients with lung adenocarcinomas (LUADs) were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). The relationships between the expression of 45 immune checkpoint genes (ICGs) and prognosis were analyzed. Additionally, the correlations between the expression of 45 biomarkers and immunotherapy biomarkers, including tumor mutation burden (TMB), mismatch repair defects, neoantigens, and others, were identified. Ultimately, prognostic ICGs were combined to determine immune subgroups, and the prognostic differences between these subgroups were identified in LUAD.Results: A total of 11 and nine ICGs closely related to prognosis were obtained from the GEO and TCGA databases, respectively. CD200R1 expression had a significant negative correlation with TMB and neoantigens. CD200R1 showed a significant positive correlation with CD8A, CD68, and GZMB, indicating that it may cause the disordered expression of adaptive immune resistance pathway genes. Multivariable Cox regression was used to construct a signature composed of four prognostic ICGs (IDO1, CD274, CTLA4, and CD200R1): Risk Score = −0.002*IDO1+0.031*CD274−0.069*CTLA4−0.517*CD200R1. The median Risk Score was used to classify the samples for the high- and low-risk groups. We observed significant differences between groups in the training, testing, and external validation cohorts.Conclusion: Our research provides a method of integrating ICG expression profiles and clinical prognosis information to predict lung cancer prognosis, which will provide a unique reference for gene immunotherapy for LUAD.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
