Developing Multiple Media Approach to Investigate Reproducible Characteristic VOCs of Lung Cancer Cells

化学 肺癌 环境化学 癌症 色谱法 纳米技术 癌症研究 内科学 医学 材料科学 生物
作者
Jijuan Zhou,Dianlong Ge,Yue Liu,Yajing Chu,Xiangxue Zheng,Yan Lu,Yannan Chu
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:96 (52): 20398-20405
标识
DOI:10.1021/acs.analchem.4c03894
摘要

Cellular volatile organic compound (VOC) detection is crucial for studying lung cancer biomarkers. However, the reported VOC biomarkers from the same cell line seem to be inconsistent across different research groups. It is possibly related to the variation in culture media, and the result obtained by a conventional single medium approach (SMA) depends on what medium is used in the cell experiment. This study proposes a multiple media approach (MMA) to investigate reproducible characteristic VOCs of lung cancer cells. Using solid-phase microextraction–gas chromatography–mass spectrometry (SPME-GC-MS) in combination with untargeted analysis, we conducted two independently repetitive experiments to compare lung cancer cells (A549) and normal lung cells (BEAS-2B) under three culture media conditions (RPMI 1640, DMEM, and Ham's F12). Both experiments indicated that, compared with 62–96 VOCs obtained by the SMA, only two VOCs (3-methyl-1-butanol and 2-methyl-1-butanol) were reproducibly achieved by the MMA. Moreover, their concentrations were significantly lower in lung cancer cells than in normal cells. Further targeted analysis confirmed the downregulation trend of both VOCs in subcutaneous and primary tumor tissues from the lung cancer model mouse. The present work demonstrated that the MMA cell experiment, just like the multicenter trials for cell lines, can facilitate the discovery of reproducible characteristic VOCs. This provides a cellular experimental basis and scientific evidence for lung cancer biomarker investigation and even breath biopsy technique development.
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
D_D完成签到,获得积分10
1秒前
2秒前
李健应助Oliver采纳,获得10
2秒前
2秒前
半颗糖完成签到,获得积分10
4秒前
糊涂的元珊完成签到 ,获得积分10
5秒前
Xeon完成签到,获得积分10
5秒前
Reese完成签到 ,获得积分10
6秒前
randylch完成签到,获得积分0
6秒前
陈怀祚发布了新的文献求助10
6秒前
昭昭完成签到,获得积分10
6秒前
胖胖完成签到,获得积分10
7秒前
沐白发布了新的文献求助10
7秒前
fun完成签到 ,获得积分10
8秒前
骆驼牛子完成签到,获得积分10
8秒前
9秒前
jason完成签到 ,获得积分10
9秒前
Jasper应助sunjij采纳,获得10
9秒前
青山完成签到 ,获得积分10
12秒前
13秒前
胖胖发布了新的文献求助10
13秒前
14秒前
博雅雅雅雅雅完成签到,获得积分10
15秒前
华仔应助陈亮采纳,获得10
15秒前
勤奋的夜春完成签到,获得积分20
16秒前
everglow发布了新的文献求助30
18秒前
琥珀川完成签到,获得积分10
18秒前
愉快之槐完成签到,获得积分10
19秒前
Owen应助悦耳听芹采纳,获得10
19秒前
沙世平完成签到,获得积分10
20秒前
科研小蔡发布了新的文献求助30
20秒前
20秒前
21秒前
甜椒完成签到,获得积分10
21秒前
21秒前
23秒前
劲秉应助英俊的小恐龙采纳,获得10
23秒前
liherong完成签到,获得积分10
23秒前
24秒前
方园完成签到,获得积分10
24秒前
高分求助中
All the Birds of the World 4000
Production Logging: Theoretical and Interpretive Elements 3000
Animal Physiology 2000
Les Mantodea de Guyane Insecta, Polyneoptera 2000
Am Rande der Geschichte : mein Leben in China / Ruth Weiss 1500
CENTRAL BOOKS: A BRIEF HISTORY 1939 TO 1999 by Dave Cope 1000
Machine Learning Methods in Geoscience 1000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3736852
求助须知:如何正确求助?哪些是违规求助? 3280817
关于积分的说明 10020999
捐赠科研通 2997447
什么是DOI,文献DOI怎么找? 1644596
邀请新用户注册赠送积分活动 782083
科研通“疑难数据库(出版商)”最低求助积分说明 749698