Research Article| Volume 274, P59-71, June 2023

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RNA profile of immuno‐magnetically enriched lung cancer associated exosomes isolated from clinical samples


      • An immunomagnetic exosome enrichment method for disease-specific exosomal RNA analysis is developed.
      • Targeted enrichment of lung cancer associated exosomes from clinical samples.
      • Immunomagnetically captured exosomes yielded good quality RNA compatible for sequencing.
      • 1383 DEGs were identified in the enriched exosomes.
      • Functional annotation revealed DEGs involvement in cancer related and exosome biosynthetic pathways.
      • Potential for disease-specific biomarker discovery.


      Exosomal cargo secreted from cancer cells has been associated with the development and progression of the tumour. Enriching clinically relevant tissue-specific exosomes may assist in the focused analysis of RNA molecules packaged during cancer. Therefore, this study utilized a rapid immunomagnetic enrichment approach for targeted isolation of lung cancer cell-derived exosomes from human plasma, followed by analysing their cargo RNA using high throughput sequencing. The total RNA purified from these immunomagnetically enriched exosomes provided adequate RNA quality for characterization through the Illumina platform. Differential expression analysis was performed between patients and healthy controls to study the altered exosomal RNA profile during lung cancer. Further, functional enrichment analysis was performed with the list of identified differentially expressed genes (DEGs). In total, 1383 mRNAs and 64 lncRNA were identified as differentially expressed between patient plasma exosomes than healthy controls (fold change > 2, P < 0.05). Kyoto encyclopaedia of Genes and Genomes (KEGG) pathway analysis revealed that the DEGs were mainly associated with cancer-related pathways, purine metabolism, calcium, and cGMP-PKG signalling pathways. In conclusion, the presented approach successfully demonstrated a novel strategy for focused disease-specific transcriptome analysis, which provides a feasible option for identifying disease-specific exosome biomarkers for detecting non-small lung cancer.


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