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.

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
Xxxxzzz完成签到,获得积分10
刚刚
刚刚
香蕉觅云应助风中迎海采纳,获得10
1秒前
S!完成签到,获得积分20
1秒前
2秒前
3秒前
3秒前
3秒前
夏山完成签到,获得积分10
3秒前
4秒前
wuming完成签到,获得积分10
4秒前
SAOKA发布了新的文献求助10
4秒前
大佬应助小谷采纳,获得10
4秒前
CipherSage应助小谷采纳,获得10
4秒前
扯扯完成签到 ,获得积分10
4秒前
萧驭枫应助123采纳,获得10
4秒前
5秒前
5秒前
5秒前
6秒前
6秒前
7秒前
8秒前
xiao发布了新的文献求助10
8秒前
DDZZGG发布了新的文献求助10
8秒前
9秒前
酷波er应助zzz采纳,获得10
9秒前
9秒前
Soojin完成签到,获得积分10
9秒前
12秒前
yar应助zhangni采纳,获得10
13秒前
123完成签到,获得积分20
13秒前
549sysfzr发布了新的文献求助10
14秒前
风中迎海发布了新的文献求助10
14秒前
15秒前
汉堡包应助zzzkyt采纳,获得10
16秒前
一一应助称心小松鼠采纳,获得10
17秒前
18秒前
谛因发布了新的文献求助10
19秒前
嘚嘚完成签到,获得积分10
19秒前
高分求助中
Production Logging: Theoretical and Interpretive Elements 2500
Востребованный временем 2500
Agaricales of New Zealand 1: Pluteaceae - Entolomataceae 1040
지식생태학: 생태학, 죽은 지식을 깨우다 600
海南省蛇咬伤流行病学特征与预后影响因素分析 500
Neuromuscular and Electrodiagnostic Medicine Board Review 500
ランス多機能化技術による溶鋼脱ガス処理の高効率化の研究 500
热门求助领域 (近24小时)
化学 医学 材料科学 生物 工程类 有机化学 生物化学 纳米技术 内科学 物理 化学工程 计算机科学 复合材料 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 电极
热门帖子
关注 科研通微信公众号,转发送积分 3461317
求助须知:如何正确求助?哪些是违规求助? 3055029
关于积分的说明 9046143
捐赠科研通 2744961
什么是DOI,文献DOI怎么找? 1505775
科研通“疑难数据库(出版商)”最低求助积分说明 695820
邀请新用户注册赠送积分活动 695264