Advancements in laboratory techniques for early cancer detection and monitoring

Heba Mustafa Shaheen, Abdulrahman Jaber Harbi, Abdullah Mohsen Khormi, Reda Salah Abuzaid, Abdullah Muneer Alshahrani, Mansoor Musa Geteni, Nossiba Hussain Arkoubi, Abdulrahman Mohammed Al Suyan, Majidah Bakr Banaemah, Essa Hasan Alqahtani
{"title":"Advancements in laboratory techniques for early cancer detection and monitoring","authors":"Heba Mustafa Shaheen, Abdulrahman Jaber Harbi, Abdullah Mohsen Khormi, Reda Salah Abuzaid, Abdullah Muneer Alshahrani, Mansoor Musa Geteni, Nossiba Hussain Arkoubi, Abdulrahman Mohammed Al Suyan, Majidah Bakr Banaemah, Essa Hasan Alqahtani","doi":"10.18203/2394-6040.ijcmph20233848","DOIUrl":null,"url":null,"abstract":"In years, there have been advancements in laboratory methods for detecting and monitoring cancer at its earliest stages. These breakthroughs have revolutionized the field of cancer care with a focus on treatment strategies. This review explores a range of laboratory-based approaches, including biopsies, advanced imaging technologies like PET, MRI, and CT scans, genomic profiling techniques such as next-generation sequencing novel biomarkers, innovative assay platforms, and the use of artificial intelligence-driven analytics. Liquid biopsies are particularly valuable as they provide real-time insights into tumor dynamics and responses to treatment by analyzing circulating tumor cells and cell-free DNA. Advanced imaging modalities offer enhanced sensitivity and resolution for the detection and monitoring of tumors. Genomic profiling techniques help unravel the complexities of tumors to guide therapies. Novel biomarkers show promise in types of cancer by aiding in screening prognosis determination and treatment monitoring. Innovative assay platforms allow for the analysis of biomarkers to improve diagnosis. The integration of intelligence (AI) and machine learning has been instrumental in interpreting clinical and molecular data alongside traditional laboratory techniques. However, despite progress made far challenges related to standardization, cost effectiveness, and ethical considerations persist. It is crucial to integrate these techniques into clinical practice to fully exploit their potential in enhancing cancer care.","PeriodicalId":73438,"journal":{"name":"International journal of community medicine and public health","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of community medicine and public health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18203/2394-6040.ijcmph20233848","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In years, there have been advancements in laboratory methods for detecting and monitoring cancer at its earliest stages. These breakthroughs have revolutionized the field of cancer care with a focus on treatment strategies. This review explores a range of laboratory-based approaches, including biopsies, advanced imaging technologies like PET, MRI, and CT scans, genomic profiling techniques such as next-generation sequencing novel biomarkers, innovative assay platforms, and the use of artificial intelligence-driven analytics. Liquid biopsies are particularly valuable as they provide real-time insights into tumor dynamics and responses to treatment by analyzing circulating tumor cells and cell-free DNA. Advanced imaging modalities offer enhanced sensitivity and resolution for the detection and monitoring of tumors. Genomic profiling techniques help unravel the complexities of tumors to guide therapies. Novel biomarkers show promise in types of cancer by aiding in screening prognosis determination and treatment monitoring. Innovative assay platforms allow for the analysis of biomarkers to improve diagnosis. The integration of intelligence (AI) and machine learning has been instrumental in interpreting clinical and molecular data alongside traditional laboratory techniques. However, despite progress made far challenges related to standardization, cost effectiveness, and ethical considerations persist. It is crucial to integrate these techniques into clinical practice to fully exploit their potential in enhancing cancer care.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
用于早期癌症检测和监测的实验室技术的进步
多年来,用于检测和监测癌症早期阶段的实验室方法不断进步。这些突破彻底改变了以治疗策略为重点的癌症治疗领域。本综述探讨了一系列基于实验室的方法,包括活检、PET、MRI 和 CT 扫描等先进成像技术、下一代测序等基因组剖析技术、新型生物标记物、创新检测平台以及人工智能驱动分析技术的使用。液体活检尤其有价值,因为它可以通过分析循环肿瘤细胞和无细胞DNA,实时了解肿瘤动态和对治疗的反应。先进的成像模式提高了检测和监测肿瘤的灵敏度和分辨率。基因组剖析技术有助于揭示肿瘤的复杂性,为治疗提供指导。新型生物标志物可帮助筛查预后判断和治疗监测,在癌症类型中大有可为。创新的检测平台可对生物标记物进行分析,从而改进诊断。智能(AI)和机器学习的整合在解释临床和分子数据以及传统实验室技术方面发挥了重要作用。然而,尽管取得了很大进展,但与标准化、成本效益和伦理考虑有关的挑战依然存在。将这些技术融入临床实践至关重要,这样才能充分发挥它们在加强癌症护理方面的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Assessment of socio-demographic factors associated with depression among couples attending a tertiary-care infertility clinic Determinants of measles-rubella vaccine second dose uptake among 24 to 35 month-old children in Wajir Town, Kenya A comparative study of ProRithm and standard monitoring techniques for non-invasive blood pressure measurement using photoplethysmography and electrocardiography signals through artificial intelligence/machine learning methods Clinico-socio demographic characteristics of neonates at NICU, Mediciti Hospital, Medchal, Telangana, India Exploring human mammaglobin: as a possible diagnostic and prognostic indicator in breast cancer tissue
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1