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. 2024 Jul 10;10(14):e33933.
doi: 10.1016/j.heliyon.2024.e33933. eCollection 2024 Jul 30.

EV-miRNAs from breast cancer patients of plasma as potential prognostic biomarkers of disease recurrence

Rhafaela Lima Causin  1 , Mariana Regatieri Polezi  1 , Ana Julia Aguiar de Freitas  1 , Stéphanie Calfa  1 , Wanessa Fernanda Altei  1   2 , Júlia Oliveira Dias  1 , Ana Carolina Laus  1 , Danielle Pessôa-Pereira  1 , Tatiana Takahasi Komoto  1 , Adriane Feijó Evangelista  1   3 , Cristiano de Pádua Souza  4 , Rui Manuel Reis  1   5   6 , Marcia Maria Chiquitelli Marques  1
Affiliations

EV-miRNAs from breast cancer patients of plasma as potential prognostic biomarkers of disease recurrence

Rhafaela Lima Causin et al. Heliyon. .

Abstract

Background: Extracellular vesicles (EVs), ubiquitously released by blood cells, facilitate intercellular communication. In cancer, tumor-derived EVs profoundly affect the microenvironment, promoting tumor progression and raising the risk of recurrence. These EVs contain miRNAs (EV-miRNAs), promising cancer biomarkers. Characterizing plasma EVs and identifying EV-miRNAs associated with breast cancer recurrence are crucial aspects of cancer research since they allow us to discover new biomarkers that are effective for understanding tumor biology and for being used for early detection, disease monitoring, or approaches to personalized medicine. This study aimed to characterize plasma EVs in breast cancer (BC) patients and identify EV-miRNAs associated with BC recurrence.

Methods: This retrospective observational study included 24 BC patients divided into recurrence (n= 11) and non-recurrence (n= 13) groups. Plasma EVs were isolated and characterized. Total RNA from EVs was analyzed for miRNA expression using NanoString's nCounter® miRNA Expression Assays panel. MicroRNA _target prediction used mirDIP, and pathway interactions were assessed via Reactome.

Results: A stronger presence of circulating EVs was found to be linked with a less favorable prognosis (p = 0.0062). We discovered a distinct signature of EV-miRNAs, notably including miR-19a-3p and miR-130b-3p, which are significantly associated with breast cancer recurrence. Furthermore, miR-19a-3p and miR-130b-3p were implicated in the regulation of PTEN and MDM4, potentially contributing to breast cancer progression.A notable association emerged, indicating a high concentration of circulating EVs predicts poor prognosis (p = 0.0062). Our study found a distinct EV-miRNA signature involving miR-19a-3p and miR-130b-3p, strongly associated with disease recurrence. We also presented compelling evidence for their regulatory roles in PTEN and MDM4 genes, contributing to BC development.

Conclusion: This study revealed that increased plasma EV concentration is associated with BC recurrence. The prognostic significance of EVs is closely tied to the unique expression profiles of miR-19a-3p and miR-130b-3p. These findings underscore the potential of EV-associated miRNAs as valuable indicators for BC recurrence, opening new avenues for diagnosis and treatment exploration.

Keywords: Biomarkers; Breast cancer; Disease recurrence; Extracellular vesicles; MicroRNA.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Characterization of the EVs isolated from breast cancer patients' plasma. A-C. Western blot analysis for three EV markers (ALIX, Flotillin-1, and CD63), positive control (ꞵ-Actin), and negative control (Calnexin) (median ± interquartile). D. Nanoparticle tracking analysis results showed the relative concentration of isolated particles (particles/mL) and their size mostly at 72 nm. The images demonstrate six representative samples from each group. However, western blotting was performed for all 24 samples (group 1, n= 11 and group 2, n= 13). E. Dot plots representing EVs mean concentration in the plasma samples (**p= 0.0062). ns = not statistically significant; WCL: whole cell lysate.
Fig. 2
Fig. 2
The heatmap of unsupervised hierarchical analysis of the 34 miRNAs differentially expressed by nCounter miRNA expression technology. Student's T test was used to compare the miRNA expression differences between the two study groups: patients with disease recurrence (light green bar, n= 10) and patients without disease recurrence (dark green bar, n= 13). Thirty-four miRNAs displayed statistically significant results (p < 0.05). Samples are arranged in columns, miRNA expression levels are in rows, and both are hierarchically clustered using Euclidean distance with the average linkage of nodes. Red shades indicate increased relative expression; green shades indicate reduced expression; black indicates median expression. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3
Fig. 3
Pathway enrichment analysis for miR-19a-3p and miR-130b-3p with genes associated with Breast Cancer (BC) recurrence. (A) miRNA-RNAm interaction network predicted to miR-19a-3p and miR-130b-3p described for BC, according to the Cancer Gene Index Annotations (provided by the National Cancer Institute, NCI) using the REACTOME plugin. (B) Dotplot of enrichment pathway result to miR-19a-3p and miR-130b-3p associated with BC recurrence using http://www.bioinformatics.com.cn/. (C) GEPIA 2 database analysis revealed low expression in PTEN breast cancer tissues (BRCA). (D) GEPIA 2 database analysis revealed low expression in MDM4 breast cancer tissues (BRCA). (E) GEPIA 2 database analysis revealed high expression in TP53 breast cancer tissues (BRCA). K= Kegg pathways; R= Reactome; B= BioCarta. In the boxplots, the red boxes indicate breast cancer tissue samples, while the gray boxes indicate normal samples. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 4
Fig. 4
Western blot analysis for t-p53 and p-p53 in the EVs isolated from both groups (recurrence and non-recurrence patients). The relative p-p53/t-p53 expression is shown as median ± interquartile. ****p < 0.0001. WCL: whole cell lysate.
Fig. 5
Fig. 5
Prognostic evaluation of miR-19a-3p, miR-130b-3p, PTEN, MDM4, and TP53 in breast cancer patients. (A) Kaplan-Meier curve analysis of overall survival (OS) in breast cancer patients with high and low expression of EV-miR-19a-3p. (B) Kaplan-Meier curve analysis of relapse-free survival (RFS) in breast cancer patients with high and low expression of EV-miR-19a-3p. (C) Kaplan-Meier curve analysis of OS in breast cancer patients with high and low expression of EV-miR-130b-3p. (D) Kaplan-Meier curve analysis of RFS in breast cancer patients with high and low expression of EV-miR-130b-3p. (E) Analysis of the association between miR-19a-3p expression and OS in breast cancer patients using the Kaplan-Meier plotter database. Log-rank test: n = 1262; P = 0.120 (METABRIC dataset). (F) Analysis of the association between miR-130b-3p expression and OS in breast cancer patients using the Kaplan-Meier plotter database. Log-rank test: n = 1262; P < 0.0001 (METABRIC dataset). (G) Analysis of the association between PTEN expression and OS in breast cancer patients using the Kaplan-Meier plotter database. Log-rank test: n = 1880; P = 0.026 (225363_at dataset). (H) Analysis of the association between PTEN expression and RFS in breast cancer patients using the Kaplan-Meier plotter database. Log-rank test: n = 4934; P = 0.092 (225363_at dataset). (I) Analysis of the association between MDM4 expression and OS in breast cancer patients using the Kaplan-Meier plotter database. Log-rank test: n = 1880; P < 0.0001 (225740_x_at dataset). (J) Analysis of the association between MDM4 expression and RFS in breast cancer patients using the Kaplan-Meier plotter database. Log-rank test: n = 4934; P < 0.0001 (225740_x_at dataset). (K) Analysis of the association between TP53 expression and OS in breast cancer patients using the Kaplan-Meier plotter database. Log-rank test: n = 1880; P = 0.130 (201746_at_x_at dataset). (L) Analysis of the association between TP53 expression and RFS in breast cancer patients using the Kaplan-Meier plotter database. Log-rank test: n = 4934; P = 0.023 (201746_at dataset). P values for the Log-rank analysis are provided in the figure.
Fig. 6
Fig. 6
Graphic summary on the regulation of EV-miR-19a-3p and EV-miR-130b-3p expression in recurrent and non-recurrent breast cancer.
Fig. S1
Fig. S1
Images of gels from membranes revealed with 90 % of ECL substrate and 10 % of SuperSignal West Femto for 2 min, scanned on an ImageQuant LAS 4000 mini-imaging system for five proteins (ALIX, ꞵ-Actin; Calnexin; Flotillin-1, and CD6) in the EVs isolated from both groups (recurrence and non-recurrence patients). A. ALIX; B. ꞵ-Actin; C. Calnexin; D. CD63; E. Flotillin-1. Non-recurrence group ID: 1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11 and Recurrence ID: 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22.
Fig. S2
Fig. S2
Images of gels from membranes revealed with 90 % of ECL substrate and 10 % of SuperSignal West Femto for 2 min, scanned on an ImageQuant LAS 4000 mini-imaging system for A. t-p53 and B. p-p53 in the EVs isolated from both groups (recurrence and non-recurrence patients). Non-recurrence group ID: 1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11 and Recurrence ID: 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22.
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