Role of hemoglobin alpha and hemoglobin beta in non‐small‐cell lung cancer based on bioinformatics analysis

生物 下调和上调 小桶 细胞周期 基因 肺癌 癌症研究 基因表达 分子生物学 遗传学 转录组 内科学 医学
作者
Ning Kang,Wenjia Qiu,Bin Wang,Dongfang Tang,Xiaoyong Shen
出处
期刊:Molecular Carcinogenesis [Wiley]
卷期号:61 (6): 587-602 被引量:9
标识
DOI:10.1002/mc.23404
摘要

Abstract The differentially expressed genes (DEGs) were identified and screened differentially in non‐small‐cell lung cancer (NSCLC) using information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases, and the correlation of DEGs in protein interaction, function, and pathway enrichment were analyzed to search for new biomarkers and potential therapeutic targets for NSCLC. Protein–protein interaction network (PPI) analysis showed that CDK1 and GNGT1 were the most significantly upregulated hub nodes, while FPR2 was the most significantly downregulated. Gene Ontology enrichment analysis showed that upregulated DEGs were significantly enriched in protein heterodimerization activity and other functions, while downregulated DEGs were enriched in functions such as heparin‐binding. Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that upregulation of DEGs were significantly associated with neuroactive ligand‐receptor interaction pathways, while downregulation of DEGs were significantly associated with malaria pathways. According to the analysis results, we identified hemoglobin alpha (HBA) and hemoglobin beta (HBB) as the genes of interest for further study. Through tissue level and cell level experiments, we found that the expressions of HBA and HBB in NSCLC tissues were significantly lower than those in paracancerous tissues, and downregulation of HBA and HBB could significantly affect the proliferation ability of NSCLC cells. In addition, we also found that changes in HBA and HBB may affect NSCLC cells through the p38/MAPK pathway and JNK pathway, and ultimately affect the occurrence and development of NSCLC.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
flyxga870825发布了新的文献求助10
刚刚
詹姆斯完成签到,获得积分10
刚刚
小菜鸡发布了新的文献求助10
刚刚
草莓熊完成签到,获得积分10
刚刚
思源应助悟空采纳,获得10
1秒前
1秒前
小喵完成签到 ,获得积分10
1秒前
3秒前
烂漫的飞松完成签到,获得积分10
3秒前
3秒前
烂漫的中蓝完成签到,获得积分20
3秒前
3秒前
赘婿应助詹姆斯采纳,获得10
5秒前
Cutewm完成签到,获得积分10
5秒前
小小户完成签到 ,获得积分10
5秒前
5秒前
6秒前
6秒前
FashionBoy应助777采纳,获得10
6秒前
顾矜应助愉博采纳,获得10
7秒前
8秒前
实验体8567号完成签到,获得积分10
8秒前
mmr完成签到,获得积分10
9秒前
荷盖应助八九采纳,获得10
9秒前
ylz发布了新的文献求助10
9秒前
海浪发布了新的文献求助10
9秒前
9秒前
濮阳盼曼发布了新的文献求助10
10秒前
小美发布了新的文献求助10
10秒前
zzq完成签到,获得积分20
10秒前
Vicky完成签到 ,获得积分10
10秒前
11秒前
11秒前
12秒前
13秒前
amber发布了新的文献求助10
14秒前
Cutewm发布了新的文献求助10
15秒前
15秒前
李健的小迷弟应助doc采纳,获得10
15秒前
Nathan完成签到,获得积分10
15秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Kelsen’s Legacy: Legal Normativity, International Law and Democracy 1000
Conference Record, IAS Annual Meeting 1977 610
The Laschia-complex (Basidiomycetes) 600
Interest Rate Modeling. Volume 3: Products and Risk Management 600
Interest Rate Modeling. Volume 2: Term Structure Models 600
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3540542
求助须知:如何正确求助?哪些是违规求助? 3117849
关于积分的说明 9332719
捐赠科研通 2815618
什么是DOI,文献DOI怎么找? 1547675
邀请新用户注册赠送积分活动 721099
科研通“疑难数据库(出版商)”最低求助积分说明 712445