ABSTRACT
BACKGROUND: Tumor-derived exosomes (TEXs) are involved in tumor progression and the immune modulation process and mediate intercellular communication in the tumor microenvironment. Although exosomes are considered promising liquid biomarkers for disease diagnosis, it is difficult to discriminate TEXs and to develop TEX-based predictive biomarkers. METHODS: In this study, the gene expression profiles and clinical information were collected from The Cancer Genome Atlas (TCGA) database, IMvigor210 cohorts, and six independent Gene Expression Omnibus datasets. A TEXs-associated signature named TEXscore was established to predict overall survival in multiple cancer types and in patients undergoing immune checkpoint blockade therapies. RESULTS: Based on exosome-associated genes, we first constructed a tumor-derived exosome signature named TEXscore using a principal component analysis algorithm. In single-cell RNA-sequencing data analysis, ascending TEXscore was associated with disease progression and poor clinical outcomes. In the TCGA Pan-Cancer cohort, TEXscore was elevated in tumor samples rather than in normal tissues, thereby serving as a reliable biomarker to distinguish cancer from non-cancer sources. Moreover, high TEXscore was associated with shorter overall survival across 12 cancer types. TEXscore showed great potential in predicting immunotherapy response in melanoma, urothelial cancer, and renal cancer. The immunosuppressive microenvironment characterized by macrophages, cancer-associated fibroblasts, and myeloid-derived suppressor cells was associated with high TEXscore in the TCGA and immunotherapy cohorts. Besides, TEXscore-associated miRNAs and gene mutations were also identified. Further experimental research will facilitate the extending of TEXscore in tumor-associated exosomes. CONCLUSIONS: TEXscore capturing tumor-derived exosome features might be a robust biomarker for prognosis and treatment responses in independent cohorts.
Subject(s)
Exosomes , Melanoma , Biomarkers, Tumor/genetics , Humans , Immunotherapy , Melanoma/genetics , Melanoma/therapy , Prognosis , Single-Cell Analysis , Tumor MicroenvironmentABSTRACT
Tyrosine kinase inhibitors (TKI) play a pivotal role in the treatment of non-small-cell lung cancer (NSCLC) with mutations in epidermal growth factor receptor (EGFR) and rearrangements in anaplastic lymphoma kinase (ALK). However, the influences of TKIs on the tumor immune microenvironment (TIM), especially dynamic changes of responders, have not yet been fully elucidated. Therefore, RNA sequencing and whole-exome sequencing were performed on EGFR/ALK-positive NSCLC samples before and after TKI treatment. In combination with neoantigen and mutational-load estimations, xCell and single-sample gene set enrichment analysis (ssGSEA) were used to assess tumor immune-cell infiltration and activity. Furthermore, weighted-gene correlation network analysis and the bottleneck method were used to identify the hub genes that affected treatment-related immune responses. We found that TKI treatment remodeled the TIM in treatment-responsive samples. Profound increases in the rate of anti-tumor cell infiltration and cytotoxicity was observed following TKI treatment, while antigen presentation was limited in ALK-rearranged samples. However, no significant change in anti-tumor cell infiltration or cytotoxicity was found between pre-treatment and post-progression samples. Subsequently, we found that neurofilament heavy (NEFH) mutations were enriched in samples after TKI treatment and were associated with reduced neutrophil infiltration. The cytotoxicity of EGFR-mutant NSCLCs with co-driver TP53 mutation and ALK-rearranged samples with wild-type TP53 seems to be more easily induced by TKI. Finally, the immune-associated score generated by hub genes was positively correlated with immune infiltration, immune activation, and a favorable prognosis. In conclusion, the dynamic changes in the TIM provide clues to drug selection and timing for TKI-immunotherapy combinations.