Exosome biosensors for detection of Lung cancer.

Lung cancer is the leading cause of cancer-related mortality worldwide. It is frequently diagnosed at an advanced stage and exhibits significant morphological and molecular heterogeneity, encompassing both small- and non-small-cell types, as well as major histological variations. Conventional imaging and tissue biopsies are invasive and may fail to reflect dynamic tumor biology. Exosomes (30-150 nm, extracellular vesicles that are products of the endosome) are present in plasma, serum, saliva, and urine and contain tumor-reflective proteins, lipids, and RNAs. This review summarizes the strategies used in biosensors to detect exosomes in lung cancer using various approaches, including electrochemical, optical, microfluidic, and nanomaterial-assisted biosensors, which detect various markers, such as PD-L1, EGFR, and oncogenic miRNAs/lncRNAs. Exosomes possess inherent biocompatibility, intrinsic cargo protection, and the ability to target tumors (homing capabilities), attributes that synthetic nanocarriers, such as liposomes, polymeric, and inorganic nanoparticles, lack. These characteristics render exosomes advantageous for biosensing and delivery applications. We also discuss exosome-enabled therapeutic directions, such as drug- and nucleic-acid-loaded exosomes and immunomodulatory cargos, and indicate the new clinical-study environment. The most important obstacles are the non-uniformity of vesicles, variability in isolation/quantification, and lack of standardization. The discussion concludes with an examination of the practice performance standards, reporting priorities, and emerging trends. These include AI-assisted analysis and the use of portable point-of-care devices, which aim to expedite the development of clinically deployable exosome platforms for lung cancer diagnosis. We examined the integration of a sample into an answer, validation of assays on cohorts, and conceptual implications of regulatory considerations for reproducible measurements. This approach facilitates practical applications, such as screening, treatment monitoring, and early relapse detection.