Signature of miR-21 and MEG-2 and their correlation with TGF-β signaling in breast cancer

Abstract

Breast cancer is highly prevalent and considered the main challenge to public health among females in Egypt as in other countries. MicroRNA-21 (miR-21) and MEG-2 are noncoding RNA attributed to their aberrant expression in several diseases, including breast cancer. This study aimed to assess the reliability of serum expression levels of miR-21 and MEG-2 in discriminating stages of breast cancer and scrutinize their correlations with the targeted transforming growth factor-beta (TGF-β) expression. One hundred and 30 participants whose ages ranged from 28 to 62 years were included in this study, divided into one hundred breast cancer patients and 30 healthy participants. miR-21 and TGF-β expression levels showed upregulation in patients with BC and elevated miR-21/TGF-β levels consistent with the BC stage. In addition, LncRNA (MEG-2) showed down-regulation in patients with BC. MEG-2 expression levels revealed a gradual decrease consistent with the BC stage. In addition, a negative relationship between the MEG-2 and the miR-21 and TGF-β differential expression was also noticed. This study suggested that miR-21 and MEG-2 can be used as prospective diagnostic biomarkers and emphasized the crucible role of TGF-β as therapeutic targets for BC.

Keywords

Breast cancer miR-21 MEG-2 TGF-β biomarkers

Introduction

Breast cancer is highly prevalent and considered the main challenge to public health among females worldwide.¹ Breast cancer is still the most prevalent disease in Egypt and the Middle East, which has been linked to a lack of awareness of the disease and inadequate medical access to screening and care.^2,3

Noncoding RNA molecules with a length of roughly 17–25 nucleotides are known as microRNAs (miRNAs) and are highly conserved. They interact with a specific target messenger RNA (mRNA), which they use to control gene expression at the post-transcriptional stage.^4–6 Interestingly, aberrant expression of miRNAs is associated with the molecular pathogenesis of the progression of many diseases.^4,7

miR-21 has a crucible role in various cancers and is an oncogenic mediator; located on chromosome 17q23.2.⁸ Interestingly, postoperative decreases in circulating miR-21 levels only occurred in cancer patients who had received chemotherapy or potentially curative procedures.⁹ Thus, miR-21 could consider a long-term follow-up biomarker in tumor progression.

PTP-MEG2; MEG2, a member of the protein tyrosine phosphatases.¹⁰ Moreover, it acts as a tumor suppressor gene in the progression of various cancer like liver, gastric, and breast cancer.¹¹

Transforming growth factors-β (TGF-β) is a pluripotent cell regulatory polypeptide that affects cell growth, differentiation, matrix production, and immune function.^12,13 TGF-β seems to provide a protection for mammary cells against carcinogenesis by inducing cellular apoptosis and creating a cell microenvironment that inhibits tumor invasion and metastasis. However, aberrant expression of TGF-β in breast cancer, converting its tumor suppressor properties to oncogenic factors, promotes breast cancer and metastasis.¹⁴ Furthermore, according to Dooley and Dijke,¹⁵ TGF-β is a regulator of disease progression via inflammation and fibrosis.

Interestingly, recent studies have demonstrated that noncoding RNAs could participate in the regulation of processes that drive fibrosis which includes; the TGF-β signaling axis. This study sought to evaluate the expression levels of miR-21/MEG-2 and scrutinize their correlations with the targeted TGF-β expression.

Subjects and methods

One hundred and 30 participants whose ages ranged from 28 to 62 years were included in this study from the oncology Department, Faculty of Medicine, Beni-Suef University, and divided into four groups, including 100 breast cancer patients (stage I, stage II, and stage III), we depended on AJCC eighth edition for staging, the following tumor characteristics were noted: tumor size, tumor-node-metastasis (TNM) stage, and estrogen/progesterone status. The other group included 30 healthy volunteers. The study was undertaken as per the Declaration of Helsinki and approved by the Ethics Committee for Research at Beni-Suef University (FMBSUREC/02102022). All participants in the study signed an informed written agreement. Patients undergoing chemotherapy or radiation treatment or who have an acute infection are eligible for exclusion from participation in the current study.

Peripheral blood samples from each participant were collected in separated vacuum tubes then two consecutive centrifugation steps were conducted to remove cellular debris. Sera were stored at −80°C until use for MEG-2 and miR-21 expression assay and Western blot assessment of TGF-β.

MEG-2 and miR-21 expression assay

Total RNAs were extracted from samples utilizing TRIzol reagent (Cat#R2072, USA), SuperScript IV One-Step RT-PCR kit (Cat# 12594100), which was utilized for reverse transcription followed by quantitative real-time PCR. Amplification of the cDNA was carried out by SYBR Green and the following primers for miRNA-21 and MEG-2 versus the corresponding housekeeping gene U6 and GAPDH, as shown in Table 1, respectively. To measure the gene expression of these candidates, the RQ was analyzed and normalized to the housekeeping gene according to the calculation 2^-∆∆Ct method.¹⁶

Table 1.

Primers sequence of all studied genes.

Primers	Forward sequence	Reverse sequence
miR-21	GTACCACCTTGTCGGATAGC	TGTCAGACAGCCCATCGACT
MEG-2	GTGGTGAAGACGCCAGTGGA	CCTGCCTTAGACTGGGACT
U6	CGCTTCGGCAGCACATATAC	AAATATGGAACGCTTCACGA
GAPDH	CAATGACCCCTTCATTGACC	GACAAGCTTCCCGTTCTCAG

Western blot assay for TGF-β

A Western blotting technique was used to evaluate the TGF-β expression PVDF membrane was used to separate the 20 μg of protein from each sample using SDS polyacrylamide gel electrophoresis, ReadyPrepTM protein extraction kit (total protein) from Bio-Rad Inc (Catalog #163-2086) were used. Membranes were sealed for 1 hour at room temperature with 5% skimmed-milk powder in a buffered Tris-saline solution. Primary antibodies for TGF-β and β-actin were incubated on PVDF membranes for a whole night at 4°C. The secondary antibodies were conjugated to HRP and incubated along with the membranes. With an enhanced chemiluminescence kit from Bio-Rad Inc (Catalog#170-5060) and the imaging program, the intensity of the bands was visualized and evaluated by Odyssey Imaging System (LI-COR Biosciences, Lincoln, NE, USA), according to the method described by Harlow, Lane.¹⁷

Statistical analysis

Results were analyzed using statistical analysis software SPSS 22 software and multiple post-hoc comparison tests (Duncan) used for pairwise comparison. Data were accessible as means ± standard error means (SEM) or percentages when appropriate. Pearson’s correlation analysis assessed the relations between the variables studied.

Results

One hundred and 30 participants whose ages ranged from 28 to 62 years were included in this study, divided into four groups, including 100 breast cancer patients (stage I, stage II, and stage III), and 30 healthy volunteers (Table 2).

Table 2.

Demographic characteristics of the studied groups.

Variables	Healthy participants(n = 30)	Breast cancer patients(n = 100)
Family history
Yes	0	75
No	30	25
Menstrual history
Premenopausal	24 (80%)	73 (73%)
Postmenopausal	6 (20%)	27 (27%)
Tumor size
<5 cm		68
>5 cm		33
Tumor stage
Stage I		30
Stage II		39
Stage III		31
Lymph node
N1		22
N2		53
N3		25
PR/ER status
Negative		93 (93%)
Positive		7 (7%)
Metastasis
M0		100

Data were expressed as number (%). PR/ER: Progesterone receptor/Estrogen receptor.

The data analysis of the selected biomarkers showed that miR-21 and TGF-β upregulated in BC patients, and the upsurge expression of miR-21 and TGF-β was in the BC stage III patients with remarkable significance from stages I and II (Figure 1). Additionally, MEG-2 was down-regulated in BC patients and the lowest expression pattern of MEG-2 was in the BC stage III patients with noticeable significance from stages I and II (Table 3).

Figure 1.

Relative expression of TGF-β levels among study participants. The different letters indicate statistical significance different means. G1: healthy control; G2: BC patients with stage I; G2:BC patients with stage II; G3: BC patients with stage III.

Table 3.

Expression levels of miR-21,and MEG-2 among study participants.

Variables	miR-21	MEG-2
Healthy control	0.988 ± 0.004^a	0.994 ± 0.005^d
Stage I	1.656 ± 0.066^b	0.781 ± 0.022^c
Stage II	2.535 ± 0.167^c	0.668 ± 0.014^b
Stage III	3.216 ± 0.199^d	0.392 ± 0.025^a
F-ratio	45.175	184.447
p- value	<0.001	<0.001

Data were expressed as mean ± SEM; According to the Duncan multiple range test, the different letters indicate statistical significance different means. miR-21: microRNA-21; TGF-β: Transforming growth factors-β.

Pearson’s correlation analysis demonstrated a strong positive correlation (p < 0.001) between the differential expression of miR-21 and TGF-β in breast cancer participants (Table 4, Figure 2(a)). In addition, a negative relationship between the MEG-2 and the miR-21 and TGF-β differential expression were also noticed (Table 4, Figure 2(b) and (c)).

Table 4.

Pearson correlation coefficient between miR-21, MEG-2, and TGF-β.

Parameter	miR-21		MEG-2		TGF-β
Parameter	R	p	R	p	R	p
miR-21	—	—	−0.468**	<0.001	0.529**	<0.001
MEG-2	−0.468**	<0.001	—	—	−0.592**	<0.001
TGF-β	0.529**	<0.001	−0.592**	<0.001	—	—

miR-21: microRNA-21; TGF-β: Transforming growth factors-β. ** Significant linear correlation at p < 0.001 (2-tailed).

Figure 2.

Correlations between (a) miR-21, and MEG-2 (b) miR-21 and TGF-β (c) MEG-2 and TGF-β of the study participants.

Diagnostic performance of serum miR-21 and MEG-2

With an AUC of 0.918, serum miR-21 able to distinguish healthy controls from breast cancer patients in ROC curve analysis, with 95% CI = 0.868 to 0.968, p < 0.001, with 90% sensitivity, and 100% specificity, as appeared in Figure 3(a). Serum MEG-2 discriminated healthy controls from breast cancer patients with 0.987 AUC, 95% CI = 0.969 to 1.005, with 88.24% sensitivity, and 100% specificity, as appeared in Figure 3(b).

Figure 3.

Receiver operating characteristic curves (ROC) for miR-21 and MEG-2 in (a, b) between breast cancer patients and healthy participants; and (c, d) stage III breast cancer from breast cancer patients.

With an AUC of 0.787, miR-21 discriminated patients with stage 3 breast cancer from breast cancer patients with 95% confidence interval = 0.672 –0.901, p < 0.001, 70.97% sensitivity, and 95.65% specificity (Figure 3(c)). In addition, with an AUC of 0.956, serum MEG-2 distinguished patients with stage 3 breast cancer from breast cancer patients with 95% CI = 0.907–1.005, p < 0.001, 90.32% sensitivity, and 95.65% specificity (Figure 3(d)).

Discussion

In the present study, miR-21, MEG-2, and TGF-β expression levels were assessed as potential diagnostic biomarkers of breast cancer. To our knowledge it is the first investigation to reveal the association of miR-21, MEG-2, and TGF-β levels with each other in breast cancer patients. Herein, our findings showed that patients with breast cancer had significantly higher levels of miR-21 and TGF-β expression as well as a substantial decrease in MEG-2 expression. Accordingly, previous studies have reported remarkable elevation in the expression levels of TGF-β in patients with breast cancer.^18,19

Recent studies pointed out that the role of sustained TGF-β expression in breast cancer is mainly associated with the advanced stages of the disease.^20,21 Our results revealed that TGF-β elevated gradually among BC stages. Here, the TGF-β elevation in expression level is related to the tumor progression and its association with oncogenic activity. TGF-β upregulation accelerates tumor growth and metastasis while preventing immune surveillance.^21–23

Herein, the present investigation set out the expression patterns of miR-21 and MEG-2 as bioindicators for breast cancer. According to our findings, miR-21 and MEG-2 expression levels in patients with BC are considerably distinguishable from healthy controls. Our results are consistence with Han et al.,²⁴ and Wang et al.,²⁵ who reported that miR-21 expression levels were elevated in BC patients and considered miR-21 a crucial biomarker for breast cancer diagnosis and a promising strategy in breast cancer therapy. Additionally, miR-21 expression levels of breast cancer patients tended to elevate gradually among BC stages, and the expression levels of miR-21 were associated with the BC stages. Therefore, miR-21 might be a viable biomarker for detecting breast cancer and predicting its prognostications. Previous studies on breast cancer showed that miR-21 expression is elevated and consistent with our results about the oncogenic effects of miR-21 on breast cancer.^9,26

Along with the upregulation of miR-21 and TGF-β expression, MEG-2 expression downregulation was observed in BC patients as previously described.²⁷ It is hypothesized that the MEG-2/TGF-β axis plays a crucial role in controlling genes involved in the progression of cancer and metastasis. Additionally, our results were consistent with Liu et al.,¹¹ who found that MEG2 is downregulated in human gastric cancer. Furthermore, according to Ying et al.,¹⁰ MEG2 blocks the AKT pathway, hich in turn prevents hepatocellular carcinoma from proliferating and metastasizing.

Additionally, MEG-2 expression levels of breast cancer patients tended to decrease gradually among BC stages, and the expression levels of MEG-2 were associated with the TNM stage in breast cancer, indicated the tumor suppressive role of MEG-2 in BC. Previous studies were consistent with our results about the tumor suppressive effects of MEG-2 on cancer.^10,28–30

To explore the correlation underlying the signaling efficacy of TGF-β and its modulatory effect on the miR-21/MEG-2 expression axis. Herein, Pearson’s statistical analysis revealed a noticeable negative correlation between the signaling of MEG-2 and the differential expression of miR-21 and TGF-β. Moreover, remarkable positive association between the signaling of TGF-β and the expression level of miR-21 among study participants. Our results were consistent with Dai et al.³¹ demonstrated that miR-21 up-regulation in breast cancer tissue and its expression level were strongly correlated with higher TGF-1, mediating the effects of TGF-1 for cell invasion and chemoresistance by directly down-regulating phosphatase and tensin homolog (PTEN). As stated by Bao et al.,²⁹ miR-21 expression plays a crucible role in regulating MEG-2 expression in colorectal cancer (CRC), which may represent a potential target for CRC diagnosis and management. Additionally, Liu et al.¹¹ stated that the MEG-2 expression level was down-regulated in gastric cancer and was suppressed by miR-181a-5p.

The miR-21 diagnostic performance was constructed utilizing ROC curve analysis, which had good sensitivity and specificity performance in discrimination of patients with breast cancer from study participants. In concordance with our results, Han et al.,²⁴ Papadaki et al.,³² and Ali et al.,³³ have identified miR-21 expression as a discriminator biomarker between breast cancer and healthy controls, providing a potential diagnostic candidate. As far as we know, this is the first investigation pointed to the correlation of TGF-β with the miR-21/MEG-2 expression. However, The small sample size can be considered the main limitation of this study due to this study having no financial support and not being funded. Therefore, further large-scale studies and clinical trials are needed to clarify the relationship between miR-21, MEG-2, and TGF-β with the therapeutic effect in clinical trials.

Conclusion

The study revealed that miR-21 and MEG-2 can be used as prospective diagnostic biomarkers and emphasized the significant correlation of TGF-β with miR-21 and MEG-2 expression in breast cancer.

Footnotes

Author contributions

Ekram Desouky, Saeed Mohamed and Nabil Hasona contributed to the study’s conception and design. Material preparation, data collection and analysis were performed by Nabil Hasona, Saeed Mohamed, and Amal Khaliefa. The first draft of the manuscript was written by Nabil Hasona, Ekram Desouky and Amal Khaliefa. All authors read and approved the final manuscript.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethics approval

This study was conducted in compliance with the Declaration of Helsinki, and approved by the Faculty of Medicine’s Ethics Committee at Beni-Suef University.

Informed consent

Patient consent for publication was covered by the informed consent document.

Data availability

All data generated or analysed during this study are included in this published article.

ORCID iD

NA Hasona

References

Sung

Ferlay

Siegel

, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2021; 71: 209–249.

Abdelaziz

Shawki

Shaaban

, et al. Breast cancer awareness among Egyptian women and the impact of caring for patients with breast cancer on family caregivers’ knowledge and behavior. Res Oncol 2021; 17(1): 1–8.

Saadeh

Abdel-Razeq

. Breast cancer in the Arab world. In: Al-Shamsi

Abu-Gheida

Iqbal

, et al. (eds) Cancer in the Arab World. Singapore: Springer, 2022.

Abdel Hameed

Shaker

Hasona

. Significance of LINC00641 and miR-378 as a potential biomarker for colorectal cancer. Comp Clin Pathol 2022; 31: 807–814, DOI: 10.1007/s00580-022-03384-8.

O'Brien

Hayder

Zayed

, et al. Overview of microRNA biogenesis, mechanisms of actions, and circulation. Front Endocrinol 2018; 9: 402. DOI: 10.3389/fendo.2018.00402.

Yamamura

Imai-Sumida

Tanaka

, et al. Interaction and cross-talk between non-coding RNAs. Cell Mol Life Sci 2018; 75: 467–484.

Khalil

Shaker

Hasona

. Impact of rs2107425 polymorphism and expression of lncH19 and miR-200a on the susceptibility of colorectal cancer. Ind J Clin Biochem. Epub ahead of print 2022. DOI: 10.1007/s12291-022-01052-w.

Feng

Tsao

. Emerging role of microRNA-21 in cancer. Biomed Rep 2016; 5(4): 395–402.

Khalighfard

Alizadeh

Irani

, et al. Plasma miR-21, miR-155, miR-10b, and Let-7a as the potential biomarkers for the monitoring of breast cancer patients. Sci Rep 2018; 8: 17981.

10.

Ying

Ruan

Zhou

. MEG2 inhibits the growth and metastasis of hepatocellular carcinoma by inhibiting AKT pathway. Gene 2019; 687: 1–8.

11.

Liu

Sun

Hong

, et al. MEG2 is regulated by miR-181a-5p and functions as a tumour suppressor gene to suppress the proliferation and migration of gastric cancer cells. Mol Cancer 2017; 16(1): 133.

12.

Gordeeva

. TGFβ family signaling pathways in pluripotent and teratocarcinoma stem cells’ fate decisions: balancing between self-renewal, differentiation, and cancer. Cells 2019; 8(12): 1500.

13.

Zheng

Yuan

, et al. Transforming growth factor-β in stem cells and tissue homeostasis. Bone Res 2018; 6: 2.

14.

Batlle

Massagué

. Transforming growth factor-β signaling in immunity and cancer. Immunity 2019; 50(4): 924–940.

15.

Dooley

ten Dijke

. TGF-β in progression of liver disease. Cell Tissue Res 2012; 347: 245–256.

16.

Livak

Schmittgen

. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods 2001; 25: 402–408.

17.

Harlow

Lane

. Using antibodies: a laboratory manual. New York, NY: Cold Spring Harbor Laboratory Press, 1999.

18.

Papadopoulou

Anagnostopoulos

Tripsianis

, et al. Evaluation of predictive and prognostic significance of serum TGF-beta1 levels in breast cancer according to HER-2 codon 655 polymorphism. Neoplasma 2008; 55(3): 229–238.

19.

Al-Saadi

Abdullah

. Transforming growth factor β1 in the different stages of breast cancer patients. Indian J Public Health Res Dev 2019; 10(8): 2142–2173.

20.

Panis

Herrera

Victorino

, et al. Screening of circulating TGF-β levels and its clinicopathological significance in human breast cancer. Anticancer Res 2013; 33(2): 737–742.

21.

Batlle

Massague

. Transforming growth factor-β signaling in immunity and cancer. Immunity 2019; 50: 924–940.

22.

Sheen-Chen

Chen

Sheen

, et al. Serum levels of transforming growth factor beta1 in patients with breast cancer. Arch Surg 2001; 136(8): 937–940.

23.

Zarzynska

. Two faces of TGF-beta1 in breast cancer. Mediators Inflamm 2014; 2014: 141747.

24.

Han

Jiang

Zhang

, et al. A novel panel of serum miR-21/miR-155/miR-365 as a potential diagnostic biomarker for breast cancer. Ann Surg Treat Res 2017; 92(2): 55–66.

25.

Wang

Tan

, et al. microRNA-21 promotes breast cancer proliferation and metastasis by targeting LZTFL1. BMC Cancer 2019; 19(1): 738.

26.

. Expressions of miR-21 and miR-210 in breast cancer and their predictive values for prognosis. Iran J Public Health 2020; 49(1): 21–29.

27.

Ren

Rong

, et al. Protein tyrosine phosphatase Meg2 dephosphorylates signal transducer and activator of transcription 3 and suppresses tumor growth in breast cancer. Breast Cancer Res 2012; 14(2): R38.

28.

Yan

Liu

, et al. Downregulated expression of PTPN9 contributes to human hepatocellular carcinoma growth and progression. Pathol Oncol Res 2016; 22(3): 555–565.

29.

Bao

Gao

Zhang

, et al. The critical role of the mir-21-meg2 axis in colorectal cancer. Crit Rev Eukaryot Gene Expr 2020; 30: 509–518.

30.

Chen

Liu

Guo

, et al. Ropivacaine inhibits cervical cancer cell growth via suppression of the miR-96/MEG2/pSTAT3 axis. Oncol Rep 2020; 43: 1659–1668.

31.

Dai

Fang

, et al. miR-21 is involved in transforming growth factor β1-induced chemoresistance and invasion by targeting PTEN in breast cancer. Oncol Lett 2017; 14: 6929–6936.

32.

Papadaki

Stratigos

Markakis

, et al. Circulating microRNAs in the early prediction of disease recurrence in primary breast cancer. Breast Cancer Res 2018; 20: 72.

33.

Ali

El Gayar

Hany

, et al. MicroRNA 21 and microRNA 10b: early diagnostic biomarkers of breast cancer in Egyptian females. J Egypt Natl Canc Inst 2022; 34: 16.