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Abstract

This study aimed at investigating the expression of candidate microRNAs (miRs), at initial diagnosis, during neoadjuvant chemotherapy, and after the tumor resection in locally advanced breast cancer patients. Plasma samples were collected from locally advanced breast cancer patients (n = 30) and healthy subjects (n = 20) for the detection of candidate miRs’ expression using the real-time quantitative polymerase chain reaction. At initial locally advanced breast cancer diagnosis, the expression of miR-21, miR-181a, and miR-10b was significantly increased, whereas that of miR-145 and let-7a was significantly decreased, compared to the healthy individuals. The diagnostic accuracy of miR-21 was superior to both carcinoembryonic antigen and carcinoma antigen 15-3 as diagnostic biomarkers for locally advanced breast cancer. By the end of the treatment, the expression of altered miRs rebound to control values. The expression levels of candidate plasma miRs are useful diagnostic biomarkers, as well as monitoring a proper response for locally advanced breast cancer patients to the treatment. Furthermore, miR-10b and miR-21 can be considered as predictive biomarkers for progression-free survival.

Keywords

MicroRNAs locally advanced breast cancer neoadjuvant chemotherapy tumor resection real-time polymerase chain reaction

Introduction

Breast cancer is the most commonly diagnosed cancer in women worldwide, and the principal cause of cancer-related mortality in over 100 countries.^1,2 In Egypt, the incidence of breast cancer ranks second after liver cancer, with 23,081 newly diagnosed cases in 2018, representing 35.1% of all female cancers (23,081/65,693), and 9,254 deaths that represent 23.8% of all female cancer deaths (9,254/38,814).³ Locally advanced breast cancer (LABC) is classified as stage III breast cancer, according to the guidelines from the US National Comprehensive Cancer Network, without distant metastasis.⁴

MicroRNAs (miRs) are endogenous short non-coding transcripts (∼23 nucleotides RNAs) that play important gene-regulatory roles in animals and plants by pairing to the mRNAs of protein-coding genes to direct their post-transcriptional repression.⁵ MiRs act as potential oncogenes (oncomiRs) or tumor suppressors and their altered expression in biological fluids was linked to the existence of many cancers, including breast cancer.⁶

MiR-10b, which is encoded by a highly conserved genomic region located near the homeobox D (HOXD) cluster on chromosome 2, is linked to a range of functions, including regulation of angiogenesis and promotion of cell invasion.⁷ It induces its tumor-promoting properties primarily through direct interaction with downstream targets, including homeobox D10 (HOXD10), neurofibromatosis type 1 (NF1), Krüppel-like factor 4 (KLF4), and phosphatase and tensin homolog (PTEN). Inhibiting miR-10b expression in breast cancer models can effectively suppress cancer proliferation, migration, and invasion.^8–11 MiR-21 is located on chromosome 17 (17q.23.1) in the 11^th intron of the transmembrane protein 49 (TMEM49) gene. MiR-21 is an oncomiR, which promotes the development of tumors through inhibiting tumor suppressor genes. It targets many different gene transcripts, such as programmed cell death 4 (PDCD4), PTEN, hypoxia-inducible factor (HIF1α), tissue inhibitor of metalloproteinases-3 (TIMP3), or tropomyosin-1 (TM1). Also, the expression of Bcl2 (an anti-apoptotic protein) can be induced by miR-21 binding to its 3′ UTR, decreasing, therefore, apoptosis and increasing proliferation by dysregulating the Bax/Bcl2 ratio. Furthermore, existing evidence demonstrates that transforming growth factor-beta (TGF-β) stimulation increases the miR-21 expression in cancer cells, which in turn up-regulates the process of epithelial-mesenchymal transition (EMT). This is associated with the induction of breast cancer stem cell (BCSC)-like phenotype and increase of HIF1α levels.^12–18 MiR-155 is a multifunctional miR that is encoded by chromosome 21. It is an important oncogenic miR in human cancers, including breast cancer. Its up-regulation promotes proliferation and metastasis through target genes, such as RAS homolog family member A (RHOA), C-X-C chemokine receptor type 4 (CXCR4), SRY-box transcription factor 1 (SOX1), tumor protein (p53), and forkhead box O3 (FOXO3).^19–25 The up-regulation of the miR-181a gene, which is located on chromosome 1, promotes metastasis and invasion of human cancers, as well as inhibiting apoptosis of breast cancer cells through target genes, such as ataxia telangiectasia mutated (ATM).^26,27 MiR-145 is located on chromosome 5 (5q32-33) and inhibits proliferation, angiogenesis, and metastasis of human breast cancer through multiple target genes, including epidermal growth factor receptor (EGFR), c-myc, sex-determining region Y-box2 (SOX2), vascular endothelial growth factor (VEGF), neural cadherin (NCAD), HIF2α, transmembrane glycoprotein Mucin1 (MUCIN 1), human epidermal growth factor receptor (HER3), and rho-associated coiled-coil kinase (ROCK1). Down-regulation of miR-145 induces metastasis in human breast cancer.^28–32 Let-7a, a member of the let-7 family, is regulated by p53 and is, therefore, a tumor suppressor miR. Its up-regulation inhibits proliferation, angiogenesis, and metastasis in human breast cancer through target genes, including high mobility group AT-hook 2 (HMGA2), h-ras, k-ras, c-myc, cyclin D2, and PBX homeobox 3 (PBX3), whereas its down-regulation induces breast cancer proliferation, angiogenesis, and metastasis. Also, its loss or down-regulation is associated with cancer aggressiveness.^33–41

To improve the treatment quality and the survivability rate of breast cancer patients, high accuracy in the early detection is crucial.⁴² Even though mammography and core needle biopsy are the most reliable detection methods, they are not sensitive or comfortable enough for women to select as routine examinations for breast cancer. Also, several limitations still exist for the tumor markers: carcinoembryonic antigen (CEA) or carcinoma antigen 15-3 (CA 15-3) because of their low sensitivity in early detection.⁴³ Accordingly, this study aimed at analyzing the expression of a panel of some circulating oncomiRs and tumor suppressor miRs, including miR-10b, miR-21, miR-145, miR-155, miR-181a, and let-7a, as non-invasive molecular biomarkers for the initial detection of LABC, treatment response, and predicting relapse or metastasis.

Subjects and methods

Subjects

The study comprised 30 newly diagnosed female patients (aged from 30 to 61 years) with LABC selected from the Outpatient Clinics at the National Cancer Institute (Cairo University, Cairo, Egypt) before receiving neoadjuvant chemotherapy. Diagnosis of all patients was based on standard clinical criteria, including echo-Doppler study, bilateral digital mammography, complementary ultrasound, histological study, digitalized X-ray examination of the chest, bone scan, and immunohistochemistry for estrogen receptor (ER), progesterone receptor (PR), human epidermal growth receptor 2 (HER2), as well as the serum tumor markers CEA and CA 15-3. The characteristics of patients at baseline are depicted in Table 1. In addition, 20 clinically healthy volunteer female subjects (visitors to the Outpatient Clinics at the Egyptian National Cancer Institute) were selected to include an age distribution that was comparable to the patient group. None of the healthy controls had been previously diagnosed with any malignancies. Furthermore, they had no family history of breast cancer.

Table 1.

Clinicopathological data of LABC patients at baseline (pre-treatment) included in the study.

Clinical features		n = 30	%
Age of patients (years)	<40	9	30
	>40	21	70
Menopause	Pre-menopause	11	36.7
	Post-menopause	19	63.3
Body mass index	<30	12	40
	>30	18	60
Stage	III	30	100
Lymph nodes	Positive	19	63.3
	Negative	11	36.7
Family history	Positive	5	16.7
	Negative	25	83.3
Estrogen receptor (ER)	Positive	21	70
	Negative	9	30
Progesterone receptor (PR)	Positive	21	70
	Negative	9	30
HER2/neu	Positive	11	36.7
	Negative	19	63.3
Subtypes
Luminal A (LA)	(+ve ER; +ve PR; −ve HER2)	15	50
Luminal B (LB)	(+ve ER; +ve PR; +ve HER2)	6	20
HER2/neu	(−ve ER; −ve PR; +ve HER2)	5	16.7
Triple negative	(−ve ER; −ve PR; −ve HER2)	4	13.3

LABC: locally advanced breast cancer; HER2: human epidermal growth factor receptor 2.

Ethics approval and consent to participate

Ethical approval was granted by the Institutional Review Board of the Egyptian National Cancer Institute (approval no. 201516010.3). The study was conducted following the Helsinki Declaration, and informed written consents were obtained from all participants.

Study design

In this study, the first blood sample (pre-treatment) was collected from breast cancer patients at baseline before the beginning of the neoadjuvant chemotherapy. The second blood sample (inter-treatment) was collected from the patients after they received four cycles of adriamycin/cyclophosphamide (intravenous infusion of 60/600 mg/m², one cycle/3 weeks). One week later, after collecting the second blood sample, the patients received weekly Taxol^® (Paclitaxel) (intravenous infusion of 80 mg/m²) for 12 consecutive weeks (patients with +ve HER2/neu expression received intravenous infusions of trastuzumab (6 mg/kg) once every 3 weeks along with Taxol^®). One week later, after the last Taxol^® dose, all patients underwent tumor resection and the third blood sample was collected 1 week later (post-treatment). The change in the level of candidate miRs in the plasma was evaluated.

Blood sample collection and storage

A volume of 3–5 mL venous peripheral blood was collected from control subjects and patients into sterile ethylenediaminetetraacetic acid (EDTA)-containing vacutainer labeled tubes that were centrifuged at 4°C for 10 min at 1,900 g. The plasma was transferred to a sterile tube, and then centrifuged once again for a further 10 min at 1,600 g at 4°C. Plasma samples were stored at −80°C for the analysis of candidate miRs expression. Another blood sample was collected into Serum-Gel tubes containing clot activator. The tubes were left at 37°C for 15 min to clot, and then centrifuged for 10 min at 1,900 g. Serum samples were transferred to new tubes that were stored at −80°C for further analysis of tumor markers (CEA and CA 15-3).

RNA extraction, cDNA synthesis, and quantitative real-time polymerase chain reaction analysis of selected miRs

Total RNA, including miRs, was isolated from plasma using the miRNeasy Mini kit (Qiagen, Hilden, Germany). MiRs were converted to cDNA by the miScript II real-time (RT) kit (Qiagen) using the Biometra Thermal Cycler (Analytik Jena, Upland, CA, USA). The relative expression of the candidate miRs (miR-10b, miR-21, miR-155, miR-181a, miR-145, and let-7a) was analyzed by quantitative real-time polymerase chain reaction (qRT-PCR) using the miScript SYBR Green PCR kit (Qiagen) and the miScript Primers assays (Qiagen) in the ViiA 7 RT PCR System (Applied BioSystems, Life Technologies, Carlsbad, CA, USA). The primer sequences were as follows: miR-10b (hsa-miR-10b-3p; ACAGAUUCGAUUCUAGGGGAAU), miR-21 (hsa-miR-21-3p; CAACACCAG UCGAUGGGCUGU), miR-155 (hsa-miR-155-3p; CUCCUACAUAUUAGCAUUAACA), miR-181a (hsa-miR-181a-3p; ACCAUCGACCGUUGAUUGUACC), miR-145 (hsa-miR-145-3p; GGAUUCCUGGAAAUACUGUUCU), let-7a (hsa-let-7a-3p; CUAUACAAUCUACUGUCUUUC), and the housekeeping miR-16 (hsa-miR-16-3p; CCAGUAUUAACUGUGCUGCUGA). The amplification protocol consisted of an initial denaturation step at 95°C for 15 min, followed by 40 cycles (94°C for 15 s, 55°C for 30 s, and 70°C for 30 s). The relative expression of selected miRs was normalized to an internal control (miR-16) and relative to a calibrator (respective miRs from normal plasma sample) and was calculated using the comparative threshold cycle method of Schmittgen and Livak.⁴⁴

Serum CEA and CA 15-3 analyses

CEA and CA 15-3 levels were determined using enzyme-linked immunosorbent assay (ELISA) kits provided by Cell Biolabs, Inc. (San Diego, CA, USA).

Bioinformatics

Selected miRs related to breast cancer were retrieved from previously published studies deposited in the National Center for Biotechnology Information (NCBI)’s Gene Expression Omnibus (GEO) through the GEO2R application (https://www.ncbi.nlm.nih.gov/geo/geo2r/) with the following accession numbers: GSE70754, GSE41526, and GSE22981.

Statistical analysis

The Shapiro–Wilk test for normality (p > 0.05) showed that all data were non-parametric. The quantitative results were expressed as median, 25^th, and 75^th percentile (quartiles) values. The non-parametric Mann–Whitney U test was used for comparing results between two independent groups. Wilcoxon test for multiple comparisons of non-parametric data was applied, followed by Friedman’s test to compare repeated measurements. Spearman’s correlation was used to measure statistical dependence between two variables. Receiver operating characteristic (ROC) curves were computed; the area under the curve (AUC) and cut-off values were calculated to assess the diagnostic accuracy of the markers. The cross-tabulation analysis was carried out, and the significance (χ²) and likelihood ratio (LR) were calculated from the chosen cut-off values. All statistics were analyzed using SPSS Statistical Software version 20.0 (SPSS Inc., Chicago, IL, USA).

Results

Data represented in Figures 1 and 2 show a significant up-regulation in the relative expression of plasma miR-10b, miR-21, and miR-181a levels (p < 0.01, p < 0.001, and p < 0.05, respectively), along with a significant increase in serum CA 15-3 and CEA levels (p < 0.05 and p < 0.01, respectively) in LABC patients at initial diagnosis (pre-treatment), whereas a significant down-regulation was demonstrated in the expression of miR-145 and let-7a (p < 0.01), compared to healthy controls. However, a gradual significant decrease was recorded in the plasma miR-10b and miR-21 levels, as well as the breast tumor size, whereas a gradual significant increase in the plasma let-7a level was demonstrated among the different treatment stages of LABC patients. By contrast, a non-significant change was recorded in miR-145 and miR-181a, as well as serum CA 15-3 and CEA levels of LABC patients after receiving four cycles of adriamycin/cyclophosphamide (inter-treatment), compared to their levels at initial diagnosis (pre-treatment), whereas a significant increase was recorded in miR-145 level, while miR-181a, CA 15-3 and CEA levels were significantly decreased following Taxol^® treatment and tumor resection (post-treatment), compared to their respective pre- and inter-treatment levels. Most interestingly, a rebound to the control level in the expression of candidate miRs and tumor markers of LABC patients was observed at the end of the treatment.

Figure 1.

Expression of plasma miRs was determined by qRT-PCR in serially collected blood samples of locally advanced breast cancer (LABC) patients at three time intervals (pre-treatment at baseline; inter-treatment after receiving four cycles of adriamycin/cyclophosphamide; post-treatment after tumor resection). Mann–Whitney U test for non-parametric data was applied to compare pre- and post-treatment patients versus control subjects (significant at *p < 0.05, **p < 0.01, and ***p < 0.001). Wilcoxon test for multiple comparisons was applied followed by Friedman’s test to compare LABC patients at the three different treatment stages (different letters denote significance between stages).

Figure 2.

Statistical significance of serum tumor markers (CEA and CA 15-3) and tumor size in locally advanced breast cancer (LABC) patients at three time intervals (pre-treatment at baseline; inter-treatment after receiving four cycles of adriamycin/cyclophosphamide; post-treatment after tumor resection). Mann–Whitney U test for non-parametric data was applied to compare pre- and post-treatment patients versus control subjects (significant at *p < 0.05 and **p < 0.01). Wilcoxon test for multiple comparisons was applied followed by Friedman’s test to compare LABC patients at the three different treatment stages (different letters denote significance between stages).

ROC curve analysis revealed significant AUC values for candidate plasma miRs, including miR-10b, miR-21, miR-181a, miR-145, and let-7a, as well as serum CA 15-3 and CEA (0.73, 0.78, 0.70, 0.70, 0.72, 0.71, and 0.75, respectively). At the optimal cut-off values for each marker, the sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy percent were calculated and presented in Table 2. Absolute specificity (100%) values were recorded for both miR-10b and miR-21, whereas the highest diagnostic accuracy was recorded for miR-21.

Table 2.

Diagnostic values (sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy %) of significant biomarkers to distinguish LABC patients at baseline (pre-treatment) from control subjects.

Parameter	AUC	p<	Cut-off	Sensitivity (%)	Specificity (%)	PPV (%)	NPV (%)	Diagnostic accuracy (%)
miR-10b	0.73	0.01	2.52	53.3	100	100	58.8	72
miR-21	0.78	0.01	4.94	63.3	100	100	64.5	78
miR-181a	0.70	0.05	1.51	50	80	78.9	51.6	62
miR-145	0.70	0.05	0.78	45	83.3	69.4	64.3	68
let-7a	0.72	0.01	0.52	50	93.3	73.7	83.3	76
CA 15-3 (U/mL)	0.71	0.05	22.5	60	75	78.3	55.6	66
CEA (ng/mL)	0.75	0.01	2.05	56.7	75	77.3	53.6	64

LABC: locally advanced breast cancer; AUC: area under the curve; PPV: positive predictive value; NPV: negative predictive value; CA: carcinoma antigen; CEA: carcinoembryonic antigen.

Table 3 illustrates significant correlations between different plasma miR profiles (miR-10b, miR-21, miR-145, and let-7a), serum tumor marker (CA 15-3), and tumor size in LABC patients at initial diagnosis (pre-treatment). MiR-10b had a significant positive correlation with plasma miR-21, serum CA 15-3, and tumor size (r = 0.62, 0.54, and 0.4, respectively), and a significant negative correlation with miR-145 and let-7a (r = 0.57 and 0.54, respectively). However, plasma miR-21 had a positive correlation with serum CA 15-3 and tumor size (r = 0.73 and 0.74, respectively), and a negative correlation with plasma miR-145 and let-7a (r = 0.88 and 0.58, respectively). Plasma miR-145 showed a significant positive correlation with plasma let-7a (r = 0.69), and a significant negative correlation with serum CA 15-3 and tumor size (r = 0.70 and 0.60, respectively). Plasma let-7a demonstrated a significant negative correlation with serum CA 15-3 and tumor size (r = 0.43 and 0.42, respectively). Finally, serum CA 15-3 had a significant positive correlation with tumor size (r = 0.48).

Table 3.

Significant correlations between different parameters in LABC patients at baseline (pre-treatment).

Parameter	Correlated parameters	Correlation coefficient (r)	p<
miR-10b	miR-21	0.62	0.001
	miR-145	−0.57	0.01
	let-7a	−0.54	0.01
	CA 15-3	0.54	0.01
	Tumor size	0.4	0.05
miR-21	miR-145	−0.88	0.001
	let-7a	−0.58	0.001
	CA 15-3	0.73	0.001
	Tumor size	0.74	0.001
miR-145	let-7a	0.69	0.001
	CA 15-3	−0.7	0.001
	Tumor size	−0.6	0.001
let-7a	CA 15-3	−0.43	0.05
	Tumor size	−0.42	0.05
CA 15-3	Tumor size	0.48	0.01

LABC: locally advanced breast cancer; CA: carcinoma antigen.

Spearman correlation for non-parametric data was applied.

Using the cut-off value of 4.94 for plasma miR-21, it was possible to significantly sort out 60%, 33.3%, 0%, and 0% of LABC patients with luminal A (LA), luminal B (LB), HER2, and triple-negative (TN) subtypes, respectively, with lower cut-off values, out of 40%, 66.7%, 100%, and 100% of LABC patients with LA, LB, HER2, and TN subtypes, respectively, with higher cut-off values. Also, using the cut-off value of a positive/negative family history, it was possible to significantly sort out 0%, 0%, 40%, and 75% of LABC patients with LA, LB, HER2, and TN subtypes, respectively, having a positive family history, out of 100%, 100%, 60%, and 25% of LABC patients with LA, LB, HER2, and TN subtypes, respectively, having a negative family history (Table 4).

Table 4.

Cross-tabulation showing the ability of plasma miR-21 and family history to sort out tumor subtypes of LABC at baseline (pre-treatment).

Marker	Cut-off	Breast cancer subtypes					χ²	LR
			LA (N = 15)	LB (N = 6)	HER2 (N = 5)	TN (N = 4)
miR-21	<4.94	N	9	2	0	0	0.05	11.60
		%	60	33.3	0	0
	≥4.94	N	6	4	5	4
		%	40	66.7	100	100
Family history	Positive	N	0	0	2	3	0.01	15.8
	Positive	%	0	0	40	75
	Negative	N	15	6	3	1
	Negative	%	100	100	60	25

LABC: locally advanced breast cancer; LR: likelihood ratio; LA: luminal A; LB: luminal B; HER2: human epidermal growth factor receptor 2.

Using the cut-off values of 2.52, 4.94, and 22.5 for miR-10b, miR-21, and CA 15-3, respectively, it was possible to significantly sort out 81.8%, 72.7%, and 72.7%, respectively, of LABC patients without lymph nodes involvement with lower cut-off values, out of 73.7%, 84.2%, and 78.9%, respectively, of LABC patients with positive lymph nodes having higher cut-off values (Table 5). Also, using the cut-off values of some combined markers, such as CA 15-3 + miR-10b, CA 15-3 + miR-21, and CA 15-3 + miR-181a, we found that 75%, 75%, and 65% of healthy controls had both markers below their cut-off values, respectively, whereas 66.7%, 70%, and 76.7% of LABC patients had one or both markers above their specified cut-off values, respectively. In addition, the cut-off values of CEA + miR-10b, CEA + miR-21, and CEA + miR-181a showed that 75%, 75%, and 60% of healthy controls had both markers below their cut-off levels, respectively, whereas 73.3%, 76.7%, and 76.7% of LABC patients had one or both markers above their specified cut-off values, respectively. However, the cut-off values of CA 15-3 + CEA + miR-10b, CA 15-3 + CEA + miR-21, and CA 15-3 + CEA + miR-181a demonstrated that 60%, 60%, and 50% of healthy controls had all of these aforementioned markers below their cut-off levels, respectively, whereas 80%, 80%, and 86.7% of LABC patients had at least one marker above their cut-off values, respectively. Also, the cut-off values of miR-10b + miR-21, miR-10b + miR-181a, and miR-21 + miR-181a revealed that 100%, 80%, and 80% of healthy controls had both markers below their cut-off levels, respectively, whereas 63.3%, 66.7%, and 76.7% of LABC patients had one or both markers above their specified cut-off values, respectively. By contrast, the cut-off values of miR-145 + let-7a revealed that all LABC patients (100%) had one or both markers below their cut-off values, whereas 35% of healthy controls had both markers above their cut-off values. However, the cut-off values of miR-10b + miR-21 + miR-181a showed that 80% of healthy controls had all markers below their cut-off levels, whereas 76.7% of LABC patients had at least one marker above its cut-off value. The highest diagnostic accuracy for all combinations (78%) was reported for miR-181a with either miR-10b or miR-21, or all of the three combinations (Table 6).

Table 5.

Cross-tabulation showing the ability of miR-10b, miR-21, and CA 15-3 to sort out LABC patients at baseline (pre-treatment) according to lymph nodes involvement.

Marker	Cut-off		Positive LN (N = 19)	Negative LN (N = 11)	χ²	LR
miR-10b	<2.52	N	5	9	0.01	9.12
		%	26.3	81.8
	≥2.52	N	14	2
		%	73.7	18.2
miR-21	<4.94	N	3	8	0.01	9.96
		%	15.8	72.7
	≥4.94	N	16	3
		%	84.2	27.3
CA 15-3 (U/mL)	<22.5	N	4	8	0.05	7.9
	<22.5	%	21.1	72.7
	≥22.5	N	15	3
	≥22.5	%	78.9	27.3

LABC: locally advanced breast cancer; LN: lymph node; LR: likelihood ratio; CA: carcinoma antigen.

Table 6.

Cross-tabulation showing the reliability of significant combined biomarkers to distinguish LABC patients at baseline (pre-treatment) from healthy subjects.

Combined markers	Cut-off		Control	Pre-treatment	χ²	LR	PPV (%)	NPV (%)	Diagnostic accuracy (%)
CA 15-3 + miR-10b	Both low	N	15	10	0.01	8.63	80	60	70
		%	75	33.3
	One or both high	N	5	20
		%	25	66.7
CA 15-3 + miR-21	Both low	N	15	9	0.01	10.1	80.8	62.5	72
		%	75	30
	One or both high	N	5	21
		%	25	70
CA 15-3 + miR-181a	Both low	N	13	7	0.01	8.8	76.7	65	72
		%	65	23.3
	One or both high	N	7	23
		%	35	76.7
CEA + miR-10b	Both low	N	15	8	0.01	11.7	81.5	65.2	74
		%	75	26.7
	One or both high	N	5	22
		%	25	73.3
CEA + miR-21	Both low	N	15	7	0.001	13.5	82.1	68.2	76
		%	75	23.3
	One or both high	N	5	23
		%	25	76.7
CEA + miR-181a	Both low	N	12	7	0.01	6.9	74.2	63.2	70
		%	60	23.3
	One or both high	N	8	23
		%	40	76.7
CA 15-3 + CEA + miR-10b	All low	N	12	6	0.01	8.4	75	66.7	72
	All low	%	60	20
	At least one high	N	8	24
	At least one high	%	40	80
CA 15-3 + CEA + miR-21	All low	N	12	6	0.01	8.4	75	66.7	72
		%	60	20
	At least one high	N	8	24
		%	40	80
CA 15-3 + CEA + miR-181a	All low	N	10	4	0.01	8.01	72.2	71.4	72
		%	50	13.3
	At least one high	N	10	26
		%	50	86.7
miR-10b + miR-21	Both low	N	20	11	0.001	26.97	100	64.5	78
		%	100	36.7
	One or both high	N	0	19
		%	0	63.3
miR-10b + miR-181a	Both low	N	16	10	0.01	11.03	83.3	61.5	72
		%	80	33.3
	One or both high	N	4	20
		%	20	66.7
miR-21 + miR-181a	Both low	N	16	7	0.001	16.38	85.2	69.6	78
		%	80	23.3
	One or both high	N	4	23
		%	20	76.7
miR-145 + let-7a	Both high	N	7	0	0.001	14.59	69.8	100	74
		%	35	0
	One or both low	N	13	30
		%	65	100
miR-10b + miR-21 + miR-181a	All low	N	16	7	0.001	16.38	85.2	69.6	78
	All low	%	80	23.3
	At least one high	N	4	23
	At least one high	%	20	76.7

LABC: locally advanced breast cancer; LR: likelihood ratio; PPV; positive predictive value; NPV: negative predictive value; CEA: carcinoembryonic antigen; CA: carcinoma antigen.

A 5-year disease-free survival (DFS) follow-up for LABC patients starting after tumor resection (0 weeks) was performed. A DFS of 83.3% was obtained, where 25 out of 30 patients were free from cancer relapse or metastasis, whereas five out of 30 patients (16.7%) suffered from breast tumor relapse and metastases to the lungs, liver, or bones (Figure 3). Using the cut-off values of 2.52 and 4.94 for miR-10b and miR-21, respectively, it was possible to significantly sort out 92% (miR-10b level lower than the cut-off value of 2.52) and 92.3% (miR-21 level lower than the cut-off value of 4.94) of breast cancer patients who were free from cancer relapse or metastasis, out of 60% (miR-10b level above the cut-off value of 2.52) and 75% (miR-21 level above the cut-off value of 4.94) of breast cancer patients who suffered from breast tumor relapse and metastases (Table 7).

Figure 3.

Kaplan–Meier survival curve showing a 5-year disease-free survival (DFS) follow-up for LABC patients starting by the end of the treatment (post-treatment; 0 weeks).

Table 7.

Cross-tabulation showing the reliability of significant miRs at the end of the treatment (post-treatment) and DFS after 5 years.

Marker	Cut-off		Disease-free (n = 25; 83.3%)	Relapsed (n = 5; 16.7%)	χ²	LR
miR-10b	<2.52	N	23	2	0.01	6.36
		%	92	8
	≥2.52	N	2	3
		%	40	60
miR-21	<4.94	N	24	2	0.01	8.43
	<4.94	%	92.3	7.7
	≥4.94	N	1	3
	≥4.94	%	25	75

DFS: disease-free survival; LR: likelihood ratio.

Discussion

This study aims at evaluating the diagnostic and predictive role of the expression of some candidate miRs, including miR-10b, miR-21, miR-155, miR-181a, miR-145, and let-7a, in LABC. In agreement with previous findings,^40,45–52 we demonstrated that the expression of the oncomiR-10b, oncomiR-21, and oncomiR-181a was significantly increased in LABC patients, whereas tumor suppressor miR-145 and let-7a expressions were significantly down-regulated, compared to healthy subjects. Similarly, the dysregulation of serum miR-10b, miR-21, miR-125b, miR-145, miR-155, miR-191, and miR-382 in breast cancer patients has been reported by Mar-Aguilar et al.,⁵³ who concluded that these seven miRs can be used as a biomarker in breast cancer. Also, both miR-10b and miR-21 were reported to induce the invasion and proliferation of MCF-7 breast cancer cells by suppressing tumor suppressor genes.⁵⁴ Recently, Zhang et al.⁵⁵ demonstrated that the overexpression of actin fiber–associated protein 1-antisense RNA1 (AFAP1-AS1), a newly discovered lncRNA, could promote triple-negative breast cancer (TNBC) cell proliferation and invasion through competitive binding to miR-145 that in turn up-regulates MutT homolog-1 (MTH1) expression and TNBC cell proliferation.

The routinely used markers for the diagnosis of breast cancer are CEA, CA 15-3, and CA 27-29. However, they are not accurate biomarkers, as they have limited sensitivity and specificity.⁴⁰ Furthermore, they are rarely elevated before gross disease and are not seen in many patients with metastases.⁵⁶ ROC curve analysis revealed that miR-21 has a higher sensitivity than that for the routinely used tumor markers: CEA and CA 15-3 for the diagnosis of LABC. Furthermore, all of the miRs, including miR-10b, miR-21, miR-181a, miR-145, and let-7a, showed better specificity value than that for CEA and CA 15-3. However, better sensitivity and specificity were reported when combining different miRs (Table 7), demonstrating the distinctive expression patterns of candidate miRs in this study, and suggesting their values as non-invasive diagnostic molecular biomarkers for breast cancer.

A positive correlation was established between oncomiRs (miR-10b and miR-21) and the tumor suppressor miRs (miR-145 and let-7a), whereas negative correlations were observed between the oncomiR-10b and oncomiR-21 and the tumor suppressors miR-145 and let-7a, pointing out to the important association of these biomarkers in breast cancer progression. In addition to family history, plasma miR-21 was able to sort out LABC tumor subtypes according to its expression. It has been previously reported that the expression of miR-10b, miR-21, miR-145, and let-7a was closely associated with the clinical and pathologic features of breast cancer, such as lymph node status, tumor size, and expression of sex hormone.^49,50,52,57

By the end of the treatment, the altered miRs rebound to control levels. Similarly, Khalighfard et al.⁵² demonstrated that the plasma miR-10b level is significantly decreased, whereas let-7a was significantly increased in breast cancer patients after mastectomy, chemotherapy, and radiotherapy, compared to their baseline level. Similar findings were also reported for miR-21, miR-145, and miR-181a.^{45,47,50,52,58–60} Also, Badr and colleagues^61,62 found that breast cancer patients with decreased miR-21 expression following treatment had better clinical outcomes that can increase survival.

It has been reported that plasma miR-34a can predict chemotherapeutic resistance associated with higher expression levels in non-responsive locally advanced Egyptian breast cancer patients.⁶³ Our study shows that LABC patients suffering from breast tumor relapse or metastases to the lungs, liver, or bones during a 5-year follow-up after tumor resection had miR-10b and miR-21 levels above their cut-off values. This finding indicates that monitoring miR-10b and miR-21 levels in patients at the end of treatment can predict breast cancer relapse, metastasis, or even recovery. This result is consistent with that of Liu et al.,⁶⁴ who reported that miR-21 is a useful non-invasive biomarker to predict response to chemotherapy in HER2-positive breast cancer. Similarly, Wang et al.⁶⁵ revealed that increased miR-10b expression might predict poor survival in patients with breast cancer.

In conclusion, our study verified three up-regulated oncomiRs (oncomiR-10b, oncomiR-21, and oncomiR-181a) and two down-regulated tumor suppressor miRs (miR-145 and let-7a) as potential candidate non-invasive diagnostic biomarkers of LABC, with better specificity (miR-21) and sensitivity (miR-10b, miR-21, miR-181a, miR-145, and let-7a) than the routinely used tumor markers: CEA and CA 15-3. Moreover, the mutual combination of miRs together, either alone or with CEA and CA 15-3, increases the accuracy of diagnosis. Besides, reducing oncomiRs level and increasing that of tumor suppressor miRs by the end of the treatment can be considered as a good tool to assess the proper response to the treatment. Also, our results revealed that the oncomiR-10b and oncomiR-21 may be considered promising predictive biomarkers for progression-free survival. However, large prospective clinical studies are warranted to confirm our preliminary results.

Footnotes

Acknowledgements

The authors thank members of the Cancer Biology Department and Medical Oncologists in the Egyptian National Cancer Institute (NCI) for their valuable efforts.

Author contributions

All the authors have accepted responsibility for the entire content of this submitted manuscript and have approved its submission.

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.

Ethical approval

Ethical approval was granted by the Institutional Review Board of the Egyptian National Cancer Institute (approval no. 201516010.3).

Funding

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

ORCID iDs

Alaa M Ibrahim

Mahmoud M Said

References

Bray

Ferlay

Soerjomataram

, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018; 68(6): 394–424.

Siegel

Miller

Jemal

Cancer statistics, 2018. CA Cancer J Clin 2018; 68(1): 7–30.

GLOBOCAN 2018: global health observatory, http://gco.iarc.fr/today/data/factsheets/populations/818-egypt-fact-sheets.pdf

Garg

Prakash

Current definition of locally advanced breast cancer. Curr Oncol 2015; 22(5): e409–e410.

Bartel

DP.

MicroRNAs: target recognition and regulatory functions. Cell 2009; 136(2): 215–233.

Filipów

Łaczmański

Ł.

Blood circulating miRNAs as cancer biomarkers for diagnosis and surgical treatment response. Front Genet 2019; 10: 169.

Biagioni

Bossel Ben-Moshe

Fontemaggi

, et al. The locus of microRNA-10b: a critical target for breast cancer insurgence and dissemination. Cell Cycle 2013; 12(15): 2371–2375.

Teruya-Feldstein

Weinberg

RA.

Tumour invasion and metastasis initiated by microRNA-10b in breast cancer. Nature 2007; 449(163): 682–688.

Chai

Liu

, et al. MicroRNA-10b regulates tumorigenesis in neurofibromatosis type 1. Cancer Sci 2010; 101(9): 1997–2004.

10.

Singh

Pochampally

Watabe

, et al. Exosome-mediated transfer of miR-10b promotes cell invasion in breast cancer. Mol Cancer 2014; 13(1): 256.

11.

Bahena-Ocampo

Espinosa

Ceballos-Cancino

, et al. MiR-10b expression in breast cancer stem cells supports self-renewal through negative PTEN regulation and sustained AKT activation. EMBO Rep 2016; 17(5): 648–658.

12.

Cai

Hagedorn

Cullen

BR.

Human microRNAs are processed from capped, polyadenylated transcripts that can also function as mRNAs. RNA 2004; 10(12): 1957–1966.

13.

Frankel

Christoffersen

Jacobsen

, et al. Programmed cell death 4 (PDCD4) is an important functional target of the microRNA miR-21 in breast cancer cells. J Biol Chem 2008; 283(2): 1026–1033.

14.

Huang

Zhang

Guo

, et al. Clinical significance of miR-21 expression in breast cancer: SYBR-Green I-based real-time RT-PCR study of invasive ductal carcinoma. Oncol Rep 2009; 21(3): 673–679.

15.

Song

Wang

Liu

, et al. MicroRNA-21 regulates breast cancer invasion partly by targeting tissue inhibitor of metalloproteinase 3 expression. J Exp Clin Cancer Res 2010; 29(1): 1–8.

16.

Zhu

, et al. MiR-21-mediated tumor growth. Oncogene 2007; 26(19): 2799–2803.

17.

Han

Wang

, et al. MicroRNA-21 induces breast cancer cell invasion and migration by suppressing smad7 via EGF and TGF-β pathways. Oncol Rep 2016; 35(1): 73–80.

18.

Han

Wang

Liu

, et al. MiR-21 regulates epithelial-mesenchymal transition phenotype and hypoxia-inducible factor-1α expression in third-sphere forming breast cancer stem cell-like cells. Cancer Sci 2012; 103(6): 1058–1064.

19.

Quiñones-Lombraña

Blanco

JG.

Chromosome 21-derived hsa-miR-155-5p regulates mitochondrial biogenesis by targeting mitochondrial transcription factor A (TFAM). Biochim Biophys Acta 2015; 1852(7): 1420–1427.

20.

Jiang

Zhang

, et al. A novel miR-155/miR-143 cascade controls glycolysis by regulating hexokinase 2 in breast cancer cells. EMBO J 2012; 31(8): 1985–1998.

21.

Jiang

Zhang

, et al. MicroRNA-155 functions as an OncomiR in breast cancer by targeting the suppressor of cytokine signaling 1 gene. Cancer Res 2010; 70(8): 3119–3127.

22.

Gwak

Kim

, et al. MicroRNA-9 is associated with epithelial-mesenchymal transition, breast cancer stem cell phenotype, and tumor progression in breast cancer. Breast Cancer Res Treat 2014; 147(1): 39–49.

23.

Dinami

Ercolani

Petti

, et al. miR-155 drives telomere fragility in human breast cancer by targeting TRF1. Cancer Res 2014; 74(15): 4145–4156.

24.

Roth

Rack

Müller

, et al. Circulating microRNAs as blood-based markers for patients with primary and metastatic breast cancer. Breast Cancer Res 2010; 12(6): R90.

25.

Anwar

Tanjung

Fitria

, et al. Dynamic changes of circulating miR-155 expression and the potential application as a non-invasive biomarker in breast cancer. Asian Pac J Cancer Prev 2020; 21(2): 491–497.

26.

Wang

Tsuyada

, et al. Transforming growth factor-β regulates the sphere-initiating stem cell-like feature in breast cancer through miRNA-181 and ATM. Oncogene 2011; 30(12): 1470–1480.

27.

Yang

Tabatabaei

Ruan

, et al. The dual regulatory role of MiR-181a in breast cancer. Cell Physiol Biochem 2017; 44(3): 843–856.

28.

Ding

Zhang

, et al. miR-145 inhibits proliferation and migration of breast cancer cells by directly or indirectly regulating TGF-beta 1 expression. Int J Oncol 2017; 50(5): 1701–1710.

29.

Cui

Wang

Chen

LB.

Micro RNA-145: a potent tumour suppressor that regulates multiple cellular pathways. J Cell Mol Med 2014; 18(10): 1913–1926.

30.

Min

Wang

, et al. The expression and significance of five types of miRNAs in breast cancer. Med Sci Monit Basic Res 2014; 20: 97–104.

31.

Yan

Chen

Liang

, et al. MiR-143 and miR-145 synergistically regulate ERBB3 to suppress cell proliferation and invasion in breast cancer. Mol Cancer 2014; 13(1): 1–14.

32.

Tang

Zhang

Tan

, et al. MiR-145-5p suppresses breast cancer progression by Inhibiting SOX₂. J Surg Res 2019; 236: 278–287.

33.

Yao

Zhu

, et al. let-7 regulates self-renewal and tumorigenicity of breast cancer cells. Cell 2007; 131(6): 1109–1123.

34.

Mansoori

Mohammadi

Shirjang

, et al. Micro RNA 34a and Let-7a expression in human breast cancers is associated with apoptotic expression genes. Asian Pac J Cancer Prev 2016; 17(4): 1887–1890.

35.

Lee

Dutta

The tumor suppressor microRNA let-7 represses the HMGA2 oncogene. Genes Dev 2007; 21(9): 1025–1030.

36.

Johnson

Grosshans

Shingara

, et al. RAS is regulated by the let-7 microRNA family. Cell 2005; 120(5): 635–647.

37.

Sampson

Rong

Han

, et al. MicroRNA let-7a down-regulates MYC and reverts MYC-induced growth in Burkitt lymphoma cells. Cancer Res 2007; 67(20): 9762–9770.

38.

Dong

Meng

Wang

, et al. MicroRNA let-7a inhibits proliferation of human prostate cancer cells in vitro and in vivo by targeting E2F2 and CCND2. PLoS ONE 2010; 5(4): e10147.

39.

Han

Zuo

, et al. Let-7c functions as a metastasis suppressor by targeting MMP11 and PBX3 in colorectal cancer. J Pathol 2012; 226(3): 544–555.

40.

Marques

Evangelista

Macedo

, et al. Expression of tumor suppressors miR-195 and let-7a as potential biomarkers of invasive breast cancer. Clinics 2018; 73: e184.

41.

Sharma

Singh

Combinatorial effect of DCA and let-7a on triple-negative MDA-MB-231 cells: A metabolic approach of treatment. Integr Cancer Ther 2020; 19: 911437.

42.

Hamouda

SKM

Wahed

Abo Alez

, et al. Robust breast cancer prediction system based on rough set theory at National Cancer Institute of Egypt. Comput Methods Programs Biomed 2018; 153: 259–268.

43.

American Society of Clinical Oncology. 2007 update of recommendations for the use of tumor markers in breast cancer. J Oncol Pract 2007; 3: 336–339.

44.

Schmittgen

Livak

KJ.

Analyzing real-time PCR data by the comparative CT method. Nat Protoc 2008; 3(6): 1101–1108.

45.

Al-Khanbashi

Caramuta

Alajmi

, et al. Tissue and serum miRNA profile in locally advanced breast cancer (LABC) in response to neo-adjuvant chemotherapy (NAC) treatment. PLoS ONE 2016; 11(4): e0152032.

46.

Alunni-Fabbroni

Majunke

Trapp

, et al. Whole blood microRNAs as potential biomarkers in post-operative early breast cancer patients. BMC Cancer 2018; 18(1): 141.

47.

Huang

Luo

Peng

, et al. A panel of serum noncoding RNAs for the diagnosis and monitoring of response to therapy in patients with breast cancer. Med Sci Monit 2018; 24: 2476–2488.

48.

Tsai

Huang

, et al. Differential microRNA expression in breast cancer with different onset age. PLoS ONE 2018; 13(1): e0191195.

49.

Zhang

Yang

Zhang

, et al. MicroRNA-10b expression in breast cancer and its clinical association. PLoS ONE 2018; 13(2): e0192509.

50.

Zhu

Liu

Fan

, et al. Dynamics of circulating microRNAs as a novel indicator of clinical response to neoadjuvant chemotherapy in breast cancer. Cancer Med 2018; 7(9): 4420–4433.

51.

Anwar

Sari

DNI

Kartika

, et al. Upregulation of circulating MiR-21 expression as a potential biomarker for therapeutic monitoring and clinical outcome in breast cancer. Asian Pac J Cancer Prev 2019; 20(4): 1223–1228.

52.

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(1): 1–11.

53.

Mar-Aguilar

Mendoza-Ramirez

Malagon-Santiago

, et al. Serum circulating microRNA profiling for identification of potential breast cancer biomarkers. Dis Markers 2013; 34(3): 163–169.

54.

Huang

Fan

Wang

, et al. Maspin inhibits MCF-7 cell invasion and proliferation by downregulating miR-21 and increasing the expression of its target genes. Oncol Lett 2020; 19(4): 2621–2628.

55.

Zhang

Zhou

Mao

, et al. lncRNA AFAP1-AS1 promotes triple negative breast cancer cell proliferation and invasion via targeting miR-145 to regulate MTH1 expression. Sci Rep 2020; 10(1): 7662.

56.

Marić

Ozretić

Levanat

, et al. Tumor markers in breast cancer-evaluation of their clinical usefulness. Coll Antropol 2011; 35(1): 241–247.

57.

Isanejad

Alizadeh

Amani Shalamzari

, et al. MicroRNA-206, let-7a and microRNA-21 pathways involved in the anti-angiogenesis effects of the interval exercise training and hormone therapy in breast cancer. Life Sci 2016; 151: 30–40.

58.

Xia

, et al. miRNA expression patterns in chemoresistant breast cancer tissues. Biomed Pharmacother 2014; 68(8): 935–942.

59.

Niu

Xue

Chi

, et al. Induction of miRNA-181a by genotoxic treatments promotes chemotherapeutic resistance and metastasis in breast cancer. Oncogene 2016; 35(10): 1302–1313.

60.

Oliveras-Ferraros

Cufí

Vazquez-Martin

, et al. Micro (mi) RNA expression profile of breast cancer epithelial cells treated with the anti-diabetic drug metformin: induction of the tumor suppressor miRNA let-7a and suppression of the TGFβ-induced oncomiR miRNA-181a. Cell Cycle 2011; 10(7): 1144–1151.

61.

Badr

Potential role of miR-21 in breast cancer diagnosis and therapy. Biotec Bioeng 2016; 3(5): 1068–1075.

62.

Badr

Said

Louka

, et al. MicroRNA-21 as a predictor and prognostic factor for trastuzumab therapy in human epidermal growth factor receptor 2-positive metastatic breast cancer. J Cell Biochem 2019; 120(3): 3459–3466.

63.

Kassem

Makar

Kassem

, et al. Circulating miR-34a and miR-125b as promising non invasive biomarkers in Egyptian locally advanced breast cancer patients. Asian Pac J Cancer Prev 2019; 20(9): 2749–2755.

64.

Liu

, et al. Serum microRNA-21 predicted treatment outcome and survival in HER2-positive breast cancer patients receiving neoadjuvant chemotherapy combined with trastuzumab. Cancer Chemother Pharmacol 2019; 84(5): 1039–1049.

65.

Wang

Chen

Huang

, et al. Prognostic significance of microRNA-10b overexpression in breast cancer: a metaanalysis. Genet Mol Res 2016; 15(2): 027350.

Candidate circulating microRNAs as potential diagnostic and predictive biomarkers for the monitoring of locally advanced breast cancer patients

Abstract

Keywords

Introduction

Subjects and methods

Subjects

Ethics approval and consent to participate

Study design

Blood sample collection and storage

RNA extraction, cDNA synthesis, and quantitative real-time polymerase chain reaction analysis of selected miRs

Serum CEA and CA 15-3 analyses

Bioinformatics

Statistical analysis

Results

Discussion

Footnotes

Acknowledgements

Author contributions

Declaration of conflicting interests

Ethical approval

Funding

ORCID iDs

References