The prospective trajectory of exosomes-based cancer nanomedicine

Divya Mirgh, Swarup Sonar, Sidhanti Nyahatkar, Ketki Kalele, Manab Deb Adhikari

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Clinical and Translational Discovery ›› 2024, Vol. 4 ›› Issue (3) : e318. DOI: 10.1002/ctd2.318
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The prospective trajectory of exosomes-based cancer nanomedicine

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Abstract

Extracellular vesicles (EVs), including exosomes, ectosomes, and apoptotic bodies, play crucial roles in cellular communication and disease processes. Among these, exosomes are particularly significant for diagnosing, and cancer (which remains a leading cause of death worldwide). Exosomes offer cutting-edge approaches in cancer nanomedicine, cancer biomarkers investigation (diagnosis and prognosis), and therapeutic. Exosomes are found in several body fluids (Blood, plasma, serum, urine, saliva, sweat, CSF, tear). It transforms the liquid biopsy method with more specificity. Exosome-based sensor (electrochemical and aptamer-based) developers were more effective and sensitive for cancer scanning. Therapeutic prospect stem cell-derived exosomes, and plant-derived exosomes become more promising. Due to its non-toxicity (depending on the source), non-immunogenic, biocompatibility and ability to cross biological membranes. Exosomes are an exciting nano-drug transporter with specificity. Current time-modified exosomes support to development of effective, efficient, and cost-effective nanomedicine against cancer. Advanced nanotechnology and exosome combining (single exosome profiling, exosome barcoding)transform cancer theranostics approaches. Exosomes introduce a new horizon of cancer nanomedicine.

Keywords

cancer / exosomes / nanomedicine / sensor / therapeutic

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Divya Mirgh, Swarup Sonar, Sidhanti Nyahatkar, Ketki Kalele, Manab Deb Adhikari. The prospective trajectory of exosomes-based cancer nanomedicine. Clinical and Translational Discovery, 2024, 4(3): e318 https://doi.org/10.1002/ctd2.318

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2024 2024 The Authors. Clinical and Translational Discovery published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.
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