Plasma Exosomal miRNA Levels after Radiotherapy Are Associated with Early Progression and Metastasis of Cervical Cancer: A Pilot Study

Abstract

Plasma exosomal miRNAs are key regulators of cell-cell interactions associated with several biological functions in patients with cancer. This pilot study aimed to investigate the log₂ fold change (log₂FC) of the expression of exosomal miRNAs and related mRNAs in the blood of patients with cervical cancer to identify prognostic markers better than those currently available. We sequenced plasma exosomal RNA from 56 blood samples collected from 28 patients with cervical cancer, who had been treated with concurrent chemoradiotherapy (CCRT). Changes in the expression of miRNAs and mRNAs before and after CCRT were represented as log₂FC. Their biological functions were studied by miRNA-mRNA network analysis, using ingenuity pathway analysis, after the selection of two groups of miRNAs, each associated with early progression (EP) and metastasis, also described as initial stage. Seven patients experienced EP, three of whom died within four months after progression. Reduced levels of miR-1228-5p, miR-33a-5p, miR-3200-3p, and miR-6815-5p and increased levels of miR-146a-3p in patients with EP revealed unresolved inflammation, with accompanying increased expression of PCK1 and decreased expression of FCGR1A. Increased levels of miR-605-5p, miR-6791-5p, miR-6780a-5p, and miR-6826-5p and decreased levels of miR-16-1-3p (or 15a-3p) were associated with the degree of metastasis and led to the systemic activation of myeloid, endothelial, and epithelial cells, as well as neurons, phagocytes, and platelets. Log₂FCs in the expression of miRNAs and mRNAs from plasma exosomes after CCRT are associated with EP and metastasis, reflecting unresolved inflammation and systemic microenvironmental factors, respectively. However, this study, supported by preliminary data insufficient to reach clear conclusions, should be verified in larger prospective cohorts.

Keywords: cervical cancer; early progression; exosome; fold change; metastasis; transcriptomics.

Figure 1

Transcriptomic analysis of miRNAs within exosomes isolated from the plasma of 28 patients with cervical cancer. (A) Clinical endpoints and blood sampling timeline. (B) Bar graph of follow-up duration and description of early progression and second-line treatment. (C) Metastatic sites according to the 2018 International Federation of Gynecology and Obstetrics (FIGO) staging. One patient with bladder invasion (stage IVA) also showed para-aortic lymph node metastasis.

Figure 2

Selection of miRNAs associated with early progression and stage in cervical cancer. (A) Five miRNAs, selected after obtaining adjusted R values from multiple regressions of all possible combinations of 19 miRNAs, were significantly associated with early progression. (B) In two groups related to early progression status, the difference of sum and subtraction of the selected 5 miRNAs was greater than that of the six selected miRNAs. (C) Pre-treatment normal transformed miR-16-1-3p correlated better with miR-15a-3p among all miRNAs. (D) Five miRNAs, selected after obtaining adjusted R values from multiple linear regressions of all possible combinations of 10 miRNAs, were significantly associated with stage. (E) Sum and difference of the selected 5 miRNAs were positively correlated with stage. (F) Correlation between miR-605-5p+miR-6791-5p+miR-6826-5p+miR-6780a-5p, miR-16-1-3p (or 15a-3p), and extrapelvic metastasis.

Figure 3

Ingenuity pathway analysis-based selection of RNAs using functional categories related to early progression and stage. (A) (Sub)categories for early progression are sorted by relevance. Five categories and four subcategories are selected based on the assumption of uncontrolled inflammation. (B) Venn diagram representing four categories; RNAs overlapping with the cancer category are highlighted. (C) (Sub)categories for stage are sorted by relevance. Four categories and 10 subcategories are selected based on the assumption of the correlation between tumor microenvironment and metastasis. (D) Venn diagram representing four categories; RNAs overlapping with the cancer category are highlighted.

Figure 4

Simplified network of miRNA-mRNA interactions in early progression. (A) A simplified network is presented from 10 RNAs involved in the shortest pathway connecting 5 mRNAs and 45 RNAs within four functional categories related to early progression. RNAs altered by the five main miRNAs are displayed by number(s) above vertices in red (downregulation) or blue (upregulation), and in bold (p < 0.05) or plain (p $\ge$ 0.05) fonts. Red and blue edges correspond to positive and negative correlations, respectively. (B) Subcategories are displayed to show the difference in Z-scores according to early progression; subcategories were selected based on significant Z-scores in all patients using the log₂FC values of all 48 RNAs included in this network. Functional categories are defined below the boxplots as ID (inflammatory disease), and IR (inflammatory response). ns, p $\ge$ 0.05; *, p < 0.05. (C) Diseases and biological functions associated with the 43 RNAs and five groups formed by primary miRNAs in the network are shown using boxplots. Statistical analysis was performed using the Wilcoxon rank-sum test or Kruskal–Wallis test. Downregulation and upregulation of RNAs refer to log₂FC < −1.5 and log₂FC > 1.5, respectively.

Figure 5

Simplified network of miRNA-mRNA interactions in metastasis. (A) A simplified network is presented from 15 RNAs involved in the shortest pathway connecting 5 mRNAs and 65 RNAs within four functional categories related to metastasis. RNAs changed by the five main miRNAs are displayed by number(s) above the vertices in red (downregulation) or blue (upregulation), and in bold (p < 0.05) or plain (p $\ge$ 0.05) fonts. Red and blue edges correspond to positive and negative correlations, respectively. (B) Subcategories show the difference in Z-scores according to extrapelvic metastasis; subcategories were selected based on significant Z-scores in all patients using the log₂FC values of all 72 RNAs included in this network. * p < 0.05, ** p < 0.01, *** p < 0.001. (C) Biological functions associated with the 67 RNAs and five groups formed by primary miRNAs in the network are shown using boxplots. Statistical analysis was performed using the Wilcoxon rank-sum test or Kruskal–Wallis test. Downregulation and upregulation of RNAs refer to log₂FC < −1.5 and log₂FC > 1.5, respectively.