Background: Lung cancer has been the leading cause of tumor related death, and 80%~85% of it is non-small cell lung cancer (NSCLC). Even with the rising molecular targeted therapies, for example EGFR, ROS1 and ALK, the treatment is still challenging. The study is to identify credible responsible genes during the development of NSCLC using bioinformatic analysis, developing new prognostic biomarkers and potential gene targets to the disease. Methods: Firstly, three genes expression profiles GSE44077, GSE18842 and GSE33532 were picked from Gene Expression Omnibus (GEO) to analyze the genes with different expression level (GDEs) between NSCLC and normal lung samples, and the cellular location, molecular function and the biology pathways the GDEs enriched in were analyzed. Then, gene function modules of GDEs were explored based on the protein-protein interaction network (PPI), and the top module which contains most genes was identified, followed by containing genes annotation and survival analysis. Moreover, multivariate cox regression analysis was performed in addition to the Kaplan meier survival to narrow down the key genes scale. Further, the clinical pathological features of the picked key genes were explored using TCGA data. Results: Three GEO profiles shared a total of 664 GDEs, including 232 up-regulated and 432 down-regulated genes. Based on the GDEs PPI network, the top function module containing a total of 69 genes was identified, and 31 of 69 genes were mitotic cell cycle regulation related. And survival analysis of the 31 genes revealed that 17/31 genes statistical significantly related to NSCLC overall survival, including 4 spindle assembly checkpoints, namely NDC80, BUB1B, MAD2L1 and AURKA. Further, multivariate cox regression analysis identified NDC80 and MAD2L1 as independent prognostic indicators in lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) respectively. Interestingly, pearson correlation analysis indicated strong connection between the four genes NDC80, BUB1B, MAD2L1 and AURKA, and their clinical pathological features were addressed.
Checkpoint with Forkhead-associated and Ring finger domains (CHFR) is a G2/M checkpoint and tumor-suppressor gene. Recent publications showed the correlation of CHFR promoter methylation with clinicopathological significance of non-small cell lung cancer (NSCLC), however, the results remain inconsistent. The aim of this study is to investigate the Clinicopathological significance of CHFR promoter methylation in NSCLC with a meta-analysis. A total of nine studies were included in the meta-analysis that 816 patients were involved. Our data indicated that the frequency of CHFR promoter methylation was higher in NSCLC than in normal lung tissue, Odd Ratios (OR) was 9.92 with 95% corresponding confidence interval (CI) 2.17–45.23, p = 0.003. Further subgroup analysis revealed that CHFR promoter was more frequently methylated in squamous cell carcinoma (SCC) than in adenocarcinoma (ADC), OR was 4.46 with 95% CI 1.65–12.05, p = 0.003, suggesting the mechanism of SCC pathogenesis is different from ADC. Notably, CHFR promoter methylation was correlated with smoking behavior in NSCLC. In conclusion, CHFR could be a biomarker for diagnosis of NSCLC, and a promising drug target for development of gene therapy in SCC. CHFR promoter methylation is potentially associated with poor overall survival, additional studies need to be carried out for confirmation in future.
Background Lung cancer has been the leading cause of tumor related death, and 80%~85% of it is non-small cell lung cancer (NSCLC). Even with the rising molecular targeted therapies, for example EGFR, ROS1 and ALK, the treatment is still challenging. The study is to identify credible responsible genes during the development of NSCLC using bioinformatic analysis, developing new prognostic biomarkers and potential gene targets to the disease. Methods Firstly, three genes expression profiles GSE44077, GSE18842 and GSE33532 were picked from Gene Expression Omnibus (GEO) to analyze the genes with different expression level (GDEs) between NSCLC and normal lung samples, and the cellular location, molecular function and the biology pathways the GDEs enriched in were analyzed. Then, gene function modules of GDEs were explored based on the protein-protein interaction network (PPI), and the top module which contains most genes was identified, followed by containing genes annotation and survival analysis. Moreover, multivariate cox regression analysis was performed in addition to the Kaplan meier survival to narrow down the key genes scale. Further, the clinical pathological features of the picked key genes were explored using TCGA data. Results Three GEO profiles shared a total of 664 GDEs, including 232 up-regulated and 432 down-regulated genes. Based on the GDEs PPI network, the top function module containing a total of 69 genes was identified, and 31 of 69 genes were mitotic cell cycle regulation related. And survival analysis of the 31 genes revealed that 17/31 genes statistical significantly related to NSCLC overall survival, including 4 spindle assembly checkpoints, namely NDC80, BUB1B, MAD2L1 and AURKA. Further, multivariate cox regression analysis identified NDC80 and MAD2L1 as independent prognostic indicators in lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) respectively. Interestingly, pearson correlation analysis indicated strong connection between the four genes NDC80, BUB1B, MAD2L1 and AURKA, and their clinical pathological features were addressed. Conclusions Using bioinformatic analysis of GEO combined with TCGA data, we revealed two independent prognostic indicators in LUAD and LUSC respectively and analyzed their clinical features. However, more detailed experiments and clinical trials are needed to verify their drug targets role in clinical medical use.
Urbanization is an extreme form of habitat modification that can alter ecological relationships among organisms, but these can be hard to study because much of the urban landscape is inaccessible private property. We show that citizen science can be a powerful tool to overcome this challenge. We used photo-vouchered observations submitted to the citizen science platform iNaturalist to assess predation and parasitism across urbanization gradients in a secretive yet widespread species, the Southern Alligator Lizard (Elgaria multicarinata), in Southern California, USA. From photographs, we quantified predation risk by assessing tail injuries and quantified parasitism rates by counting tick loads on lizards.We estimated urbanization intensity by determining percent impervious surface around each lizard observation. We found that tail injuries increased with age of the lizard and with urbanization, suggesting that urban areas are riskier habitats, likely because of elevated populations of predators such as outdoor cats. Conversely, parasitism decreased with urbanization likely due to a loss of mammalian hosts and anti-tick medications used on companion animals. Moreover, our citizen science approach allowed us to generate a large dataset on a secretive species extremely rapidly and at an immense spatial scale that facilitated quantitative measures of urbanization (e.g. percent impervious surface cover) as opposed to 2 qualitative measures (e.g. urban vs rural). This study demonstrates that citizen science is allowing researchers to answer ecological questions that otherwise would go unanswered.
In gravure printing process, it is easy to trigger an explosion for the explosive volatile solvents of drying system accumulated. In this paper, the lower explosion limit (LEL) is introduced to drying system of the gravure press, and the LEL value is calculated. Then added the LEL sensor to the drying system to monitor and control the concentration of gas in the solvent evaporation. Finally, the structure of the drying system is optimized. It is showed that the consumption of the steam is reduced sharply, the drying system has pronounced energy-saving effect, and operated more steadily and more efficiently.
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.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.