{"title":"Tumor-educated platelets in lung cancer","authors":"Md Sadique Hussain , Ehssan Moglad , Ahsas Goyal , M.M. Rekha , Girish Chandra Sharma , Karthikeyan Jayabalan , Samir Sahoo , Anita Devi , Kavita Goyal , Gaurav Gupta , Moyad Shahwan , Sami I. Alzarea , Imran Kazmi","doi":"10.1016/j.cca.2025.120307","DOIUrl":null,"url":null,"abstract":"<div><div>Non-invasive diagnostic monitoring techniques have become essential for treating lung cancer (LC), which continues to be the primary cause of cancer-related death worldwide. The new diagnostic biomarkers called tumour-educated platelets (TEPs) show strong prospects for providing vital information about tumor biology, tumor spread pathways, and treatment reaction patterns. Despite lacking a nucleus, platelets exhibit an active RNA profile that develops through interactions with tumor-derived compounds and the tumor microenvironments (TME). This review explains platelet-tumour interaction regulatory mechanisms while focusing on platelet contributions toward cancer development, immune system avoidance, and blood clot formation. The detection and classification of LC show promise through the analysis of RNA molecules extracted from platelets that encompass mRNAs and non-coding RNAs. RNA sequencing technology based on TEP demonstrates excellent diagnostic power by correctly identifying LC patients alongside their oncogenic alterations of EGFR, KRAS, and ALK. Treatment predictions have proven successful using platelet RNA profiles, specifically in immunotherapy and targeted therapy. Integrating next-generation sequencing with machine learning and artificial intelligence enhances TEP-based diagnostic tools, improving detection accuracy. Standardizing platelet extraction methods and vesicle purification from tumor material needs better development for effective and affordable clinical use. Future investigations should combine TEPs with circulating tumor DNA and exosomal RNA markers to enhance both earliest-stage LC diagnosis and patient-specific therapeutic approaches. TEPs introduce a groundbreaking technique in oncology since they can transform non-invasive medical diagnostics and therapeutic monitoring for cancer.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"573 ","pages":"Article 120307"},"PeriodicalIF":3.2000,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinica Chimica Acta","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S000989812500186X","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL LABORATORY TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Non-invasive diagnostic monitoring techniques have become essential for treating lung cancer (LC), which continues to be the primary cause of cancer-related death worldwide. The new diagnostic biomarkers called tumour-educated platelets (TEPs) show strong prospects for providing vital information about tumor biology, tumor spread pathways, and treatment reaction patterns. Despite lacking a nucleus, platelets exhibit an active RNA profile that develops through interactions with tumor-derived compounds and the tumor microenvironments (TME). This review explains platelet-tumour interaction regulatory mechanisms while focusing on platelet contributions toward cancer development, immune system avoidance, and blood clot formation. The detection and classification of LC show promise through the analysis of RNA molecules extracted from platelets that encompass mRNAs and non-coding RNAs. RNA sequencing technology based on TEP demonstrates excellent diagnostic power by correctly identifying LC patients alongside their oncogenic alterations of EGFR, KRAS, and ALK. Treatment predictions have proven successful using platelet RNA profiles, specifically in immunotherapy and targeted therapy. Integrating next-generation sequencing with machine learning and artificial intelligence enhances TEP-based diagnostic tools, improving detection accuracy. Standardizing platelet extraction methods and vesicle purification from tumor material needs better development for effective and affordable clinical use. Future investigations should combine TEPs with circulating tumor DNA and exosomal RNA markers to enhance both earliest-stage LC diagnosis and patient-specific therapeutic approaches. TEPs introduce a groundbreaking technique in oncology since they can transform non-invasive medical diagnostics and therapeutic monitoring for cancer.
期刊介绍:
The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC)
Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells.
The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.