Recent Advances in the Biosensors for the Detection of Lung Cancer Biomarkers: A Review

肺癌 医学 癌症 鉴定(生物学) 肺癌的治疗 肺病 疾病 癌症检测 病理 癌症生物标志物 肿瘤科 生物传感器 正电子发射断层摄影术 癌症研究 内科学 评论文章 计算机断层摄影术
作者
Pooja Rahar,Saravjeet Singh
出处
期刊:Critical Reviews in Analytical Chemistry [Taylor & Francis]
卷期号:: 1-13
标识
DOI:10.1080/10408347.2025.2606194
摘要

Nearly 10 million deaths from cancer occurred in 2020, making it a major cause of death globally, according to the WHO and other important statistics. Given that lung cancer is one of the most prevalent types of cancer, it accounts for around 25% of all deaths from cancer-related causes. The two forms of lung cancer that are treated and characterized differently are small-cell and non-small-cell lung cancer. To identify malignant cells, several techniques have been used in recent decades, including MRI (magnetic resonance imaging), CT (computed tomography scans), and PET (positron emission tomography). The standard detection threshold of conventional assays is insufficient for early-stage detection. As a result, numerous detection techniques have been used to identify lung cancer early. The stages of lung cancer are indicated by the amounts of these biomarkers. As a result, lung cancer screening and clinical diagnosis can be accomplished by the identification of biomarkers. EGFR, CEA, CYFRA 21-1, ENO1, NSE, CA 19-9, CA 125, and VEGF are among the many biomarkers for lung cancer. To identify lung cancer disease biomarkers, an organized summary of several biosensing platforms is given in this article. In particular, it addresses the most recent advancements in optical and electrochemical biosensors, the analytical capabilities of various biosensors, the challenges, and potential directions for future study in regular clinical analysis. Therefore, this study reviews the latest developments and enhancements (2011-2025) in biosensors for the identification of biomarkers for lung cancer.
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
1秒前
YJH发布了新的文献求助10
2秒前
esdese完成签到,获得积分10
2秒前
深情沧海完成签到,获得积分10
2秒前
洛敏夕5743完成签到,获得积分10
2秒前
小蘑菇应助英勇的红酒采纳,获得10
2秒前
蔡博颖完成签到,获得积分10
2秒前
hahaha发布了新的文献求助10
3秒前
傅寒天完成签到,获得积分10
4秒前
4秒前
5秒前
123完成签到,获得积分10
5秒前
油条完成签到,获得积分10
5秒前
朴实雨竹发布了新的文献求助10
5秒前
yuncong323完成签到,获得积分0
6秒前
esdese发布了新的文献求助10
6秒前
Lianna完成签到 ,获得积分10
7秒前
爱唱歌的yu仔完成签到,获得积分10
7秒前
干净之槐完成签到,获得积分0
7秒前
思源应助goldNAN采纳,获得10
8秒前
搜集达人应助Jabowoo采纳,获得10
8秒前
张晓芳完成签到,获得积分10
8秒前
风中冰蝶发布了新的文献求助10
8秒前
曹博完成签到,获得积分10
8秒前
zz应助爱吃小龙虾采纳,获得10
9秒前
tb168tb完成签到,获得积分10
9秒前
欢呼妙菱完成签到,获得积分10
9秒前
迷人无剑完成签到,获得积分10
9秒前
9秒前
Zzz呀完成签到 ,获得积分10
10秒前
lk完成签到 ,获得积分10
10秒前
Isaac完成签到,获得积分10
10秒前
阳光少女完成签到,获得积分10
10秒前
ckbadwny完成签到,获得积分10
11秒前
aaabbb完成签到,获得积分10
11秒前
无花果应助哈哈哈哈哈采纳,获得10
11秒前
仁青完成签到,获得积分10
12秒前
柚子完成签到,获得积分10
12秒前
lijiajun完成签到,获得积分10
12秒前
Puffkten完成签到 ,获得积分10
13秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Development of a Bridge Weigh-In-Motion System: A technology to convert the bridge response to the passage of traffic into data on vehicle configurations, speeds, times of travel and weights 1000
ズームレンズの光学設計に関する研究 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
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 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7282625
求助须知:如何正确求助?哪些是违规求助? 8903361
关于积分的说明 18834686
捐赠科研通 6953315
什么是DOI,文献DOI怎么找? 3207575
关于科研通互助平台的介绍 2377861
邀请新用户注册赠送积分活动 2182778