Background: To investigate the relationship between CXCR4-related circular RNAs (circRNAs) in exosomes and lymph node metastasis of lung adenocarcinoma. Methods: Totally 41 lung adenocarcinoma tissues (21 with lymph node metastasis and 20 without) were collected. Expression of CXCR4 protein was detected by western blotting analysis. A stable PC9/CXCR4-shRNA and PC14/CXCR4-shRNA knockdown lung adenocarcinoma cell lines were established and subjected to functional assays (cell proliferation, colony formation, migration and invasion) for phenotype changes. Exo-hsa-circRNAs (has-circRNAs in exosomes) were detected in vivo and in vitro. The diagnostic value of differentially expressed exo-has-circRNAs was evaluated. Results: Expression levels of CXCR4 were higher in patients with lymph node metastasis than in those without (P = 0.001). Silencing CXCR4 expression in PC9 and PC14 cell lines with short hairpin RNA could effectively abolish colony formation frequency, proliferation rate, migration rate, and the number of invasive cells (all P < 0.001). Exo_circRNA_0056616 was detected in both PC-9/CXCR4-shRNA cells and lung adenocarcinoma plasma at significantly higher levels than in the corresponding control (P < 0.001). When a receiver operating characteristic (ROC) curve for plasma exo-hsa_circRNA_0056616 levels and diagnosis of lymph node metastasis of lung adenocarcinoma was generated, a cutoff value of 0.394 was identified with an area under the curve of 0.812 (95% confidence interval 0.720-0.903), a sensitivity of 0.792, and specificity of 0.810. Conclusions: Taken together, our findings suggested that CXCR4 was higher in the lung adenocarcinoma tissues with lymph node metastasis. Higher plasma levels of exo-hsa_circRNA_0056616 in these patients also suggest that this circRNA represents a potential biomarker for lymph node metastasis predictor in lung adenocarcinoma.

BackgroundMolecular typing based on single omics data has its limitations and requires effective integration of multiple omics data for tumor typing of colorectal cancer (CRC).MethodsTranscriptome expression, DNA methylation, somatic mutation, clinicopathological information, and copy number variation were retrieved from TCGA, UCSC Xena, cBioPortal, FireBrowse, or GEO. After pre-processing and calculating the clustering prediction index (CPI) with gap statistics, integrative clustering analysis was conducted via MOVICS. The tumor microenvironment (TME) was deconvolved using several algorithms such as GSVA, MCPcounter, ESTIMATE, and PCA. The metabolism-relevant pathways were extracted through ssGSEA. Differential analysis was based on limma and enrichment analysis was carried out by Enrichr. DNA methylation and transcriptome expression were integrated via ELMER. Finally, nearest template or hemotherapeutic sensitivity prediction was conducted using NTP or pRRophetic.ResultsThree molecular subtypes (CS1, CS2, and CS3) were recognized by integrating transcriptome, DNA methylation, and driver mutations. CRC patients in CS3 had the most favorable prognosis. A total of 90 differentially mutated genes among the three CSs were obtained, and CS3 displayed the highest tumor mutation burden (TMB), while significant instability across the entire chromosome was observed in the CS2 group. A total of 30 upregulated mRNAs served as classifiers were identified and the similar diversity in clinical outcomes of CS3 was validated in four external datasets. The heterogeneity in the TME and metabolism-related pathways were also observed in the three CSs. Furthermore, we found CS2 tended to loss methylations while CS3 tended to gain methylations. Univariate and multivariate Cox regression revealed that the subtypes were independent prognostic factors. For the drug sensitivity analysis, we found patients in CS2 were more sensitive to ABT.263, NSC.87877, BIRB.0796, and PAC.1. By Integrating with the DNA mutation and RNA expression in CS3, we identified that SOX9, a specific marker of CS3, was higher in the tumor than tumor adjacent by IHC in the in-house cohort and public cohort.ConclusionThe molecular subtypes based on integrated multi-omics uncovered new insights into the prognosis, mechanisms, and clinical therapeutic targets for CRC.