Integrated multi-omics landscape of non-small cell lung cancer with distant metastasis.

Abstract

Background: Distant metastasis is one of the important factors affecting the prognosis of lung cancer patients. Extracellular vesicles (EVs) play an important role in the occurrence, development, and metastasis of cancer. However, it is currently unclear whether EVs in BALF are involved in distant tumor metastasis.

Methods: we collected bronchoalveolar lavage fluid (BALF) from patients with metastatic and non-metastatic non-small cell lung cancer (NSCLC) to isolate exosomes, which were then characterized by nanoparticle tracking analysis (NTA) and transmission electron microscopy (TEM), followed by comprehensive metabolomic and proteomic analysis to ultimately construct a distant metastasis prediction model for non-small cell lung cancer.

Results: Our research has found that the BALF of NSCLC patients is rich in EVs, which have typical morphology and size. There are significant differences in protein expression and metabolite types between patients with distant metastasis and those without distant metastasis. Sphingolipid metabolism pathways may be a key factor influencing distant metastasis in NSCLC. Subsequently, we constructed a predictive model for distant metastasis in NSCLC based on differentially expressed proteins identified by proteomics. This model has been proven to have high predictive value.

Conclusion: The multi-omic analysis generated in this study provided a global overview of the molecular changes, which may provide useful insight into the therapy and prognosis of NSCLC metastasis.