Exosomes as Powerful Biomarkers in Cancer: Recent Advances in Isolation and Detection Techniques

Abstract

Exosomes, small extracellular vesicles derived from cells, are known to carry important bioactive molecules such as proteins, nucleic acids, and lipids. These bioactive components play crucial roles in cell signaling, immune response, and tumor metastasis, making exosomes potential diagnostic biomarkers for various diseases. However, current methods for detecting tumor exosomes face scientific challenges including low sensitivity, poor specificity, complicated procedures, and high costs. It is essential to surmount these obstacles to enhance the precision and dependability of diagnostics that rely on exosomes. Merging DNA signal amplification techniques with the signal boosting capabilities of nanomaterials presents an encouraging strategy to overcome these constraints and improve exosome detection. This article highlights the use of DNA signal amplification technology and nanomaterials’ signal enhancement effect to improve the detection of exosomes. This review seeks to offer valuable perspectives for the enhancement of amplification methods applied in practical cancer diagnosis and prognosis by providing an overview of how these novel technologies are utilized in exosome-based diagnostic procedures.

Graphical Abstract

Keywords:

• tumor
• exosomes
• nanomaterials
• DNA signal amplification

Disclosure

Qiongdan Zhang and Huizhen Wang are co-first authors for this study. The authors declare no conflicts of interest in this work.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (Grant No. 82074122 and 82304890) and Research Foundation of Education Bureau of Hunan Province (Grant No. 23A0280) and Key Research and Development Programs of Hunan Science and Technology Department (Grant No. 2023SK2046) and Opening Funding of Traditional Chinese Medicine and Ethnomedicine Innovation & Development International Laboratory (Grant No. 2022GJSYS04 and 2022GJSYS07) and Changsha Natural Science Foundation (Grant No. Kq2208193).