Immune Infiltration Profiling in Nonsmall Cell Lung Cancer and Their Clinical Significance: Study Based on Gene Expression Measurements

免疫系统 生物 危险系数 生存分析 比例危险模型 肿瘤科 肺癌 内科学 基因表达谱 免疫学 癌症研究 置信区间 基因 基因表达 医学 遗传学
作者
Fangyao Chen,Yuhui Yang,Yaling Zhao,Leilei Pei,Hong Yan
出处
期刊:DNA and Cell Biology [Mary Ann Liebert, Inc.]
卷期号:38 (11): 1387-1401 被引量:17
标识
DOI:10.1089/dna.2019.4899
摘要

Immune cell infiltration is associated with the prognosis of cancer. This study focused on the immune infiltration profiling and their association with survival outcome in nonsmall cell lung cancer (NSCLC). Research data were obtained from the Gene Expression Omnibus and The Cancer Genome Atlas databases. CIBERSORT algorithm was applied to assess the relative proportions of 22 kinds of immune cells. Log-rank test was performed to compare the survival outcome of patients with different proportions of immune cells. The estimated hazard ratios were presented with forest plot. Multivariate Cox regression analysis was conducted to estimate the adjusted associations between different types of infiltrating immune cells and survival prognosis controlling for other clinical features and confounders. With the CIBERSORT approach, we assessed the proportions of 22 infiltrating immune cells of 2050 cases with NSCLC. By conducting survival analysis, we found different survival outcomes among cases with different proportions of certain types of infiltrating immune cells. Among the cell subsets investigated, plasma cells (hazard ratio [HR] = 0.775, 95% confidence interval [CI]: 0.669-0.898) and regulatory T cells (HR = 1.258, 95% CI: 1.091-1.451) were associated with survival outcome of NSCLC patients controlling for other covariates. Subgroup analysis suggested a good consistency and robustness of our results. Our findings might provide useful information for prognosis prediction and cellular study in NSCLC.

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
why完成签到,获得积分10
2秒前
龙06完成签到,获得积分10
2秒前
无敌兑兑兑完成签到,获得积分20
4秒前
小鬼完成签到 ,获得积分10
4秒前
5秒前
英姑应助唧唧复唧唧采纳,获得10
5秒前
Jim完成签到,获得积分0
5秒前
在水一方应助自由一一采纳,获得10
6秒前
6秒前
慕青应助司空靖琪采纳,获得10
7秒前
flashpop发布了新的文献求助10
8秒前
xiyin完成签到,获得积分10
8秒前
外向如蓉完成签到,获得积分10
9秒前
艾弗里发布了新的文献求助10
10秒前
LiuXinping完成签到,获得积分10
11秒前
11秒前
酷波er应助东君采纳,获得10
11秒前
12秒前
13秒前
丘比特应助蘑菇采纳,获得10
13秒前
香蕉觅云应助墨菲特采纳,获得10
14秒前
英俊的铭应助嘻嘻采纳,获得10
14秒前
15秒前
完美世界应助yunjian1583采纳,获得10
15秒前
明理夏波完成签到 ,获得积分10
15秒前
王路飞完成签到,获得积分10
16秒前
17秒前
烤番薯完成签到,获得积分10
17秒前
17秒前
18秒前
JamesPei应助可乐采纳,获得10
18秒前
19秒前
20秒前
20秒前
Queen完成签到 ,获得积分20
21秒前
迷路枫完成签到,获得积分20
21秒前
司空靖琪发布了新的文献求助10
21秒前
21秒前
21秒前
咸鱼饭团完成签到,获得积分10
21秒前
高分求助中
Signals, Systems, and Signal Processing 610
Annie Ernaux: De la perte au corps glorieux 600
Petrology and Plate Tectonics,2025 500
Circular Polar Constellations Providing Continuous Single or Multiple Coverage Above a Specified Latitude 400
Burger's Medicinal Chemistry and Drug Discovery 400
Probability and Stochastic Processes 333
New directions for experimental lessons in science teaching: Myth, Mystery, Necessity? by Emily K. da Silva Cunha Souto (Author), Flávia Lins Silva (Author) 333
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6743639
求助须知:如何正确求助?哪些是违规求助? 8474591
关于积分的说明 18076710
捐赠科研通 6014244
什么是DOI,文献DOI怎么找? 3004245
邀请新用户注册赠送积分活动 1980792
关于科研通互助平台的介绍 1946212