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International Journal of Molecular Sciences logoLink to International Journal of Molecular Sciences
. 2021 Aug 1;22(15):8290. doi: 10.3390/ijms22158290

The Role of MicroRNA as Clinical Biomarkers for Breast Cancer Surgery and Treatment

Matthew G Davey 1,*, Molly Davies 1, Aoife J Lowery 1, Nicola Miller 1, Michael J Kerin 1
Editors: Damjan Glavač1, Metka Ravnik-Glavač1
PMCID: PMC8346977  PMID: 34361056

Abstract

Breast cancer is the most common cancer diagnosed in women. In recent times, survival outcomes have improved dramatically in accordance with our enhanced understanding of the molecular processes driving breast cancer proliferation and development. Refined surgical approaches, combined with novel and targeted treatment options, have aided the personalisation of breast cancer patient care. Despite this, some patients will unfortunately succumb to the disease. In recent times, translational research efforts have been focused on identifying novel biomarkers capable of informing patient outcome; microRNAs (miRNAs) are small non-coding molecules, which regulate gene expression at a post-transcriptional level. Aberrant miRNA expression profiles have been observed in cancer proliferation and development. The measurement and correlation of miRNA expression levels with oncological outcomes such as response to current conventional therapies, and disease recurrence are being investigated. Herein, we outline the clinical utility of miRNA expression profiles in informing breast cancer prognosis, predicting response to treatment strategies as well as their potential as therapeutic targets to enhance treatment modalities in the era of precision oncology.

Keywords: breast cancer, miRNA, non-coding RNA, precision oncology, personalised medicine

1. Clinical Breast Cancer: Tumour Heterogeneity and Precision Oncology

Breast cancer is the most common cancer in women, with estimations suggesting 1.67 million women are diagnosed and treated for new breast cancers each year [1]. Despite the increase in breast cancer incidence and the disease now being recognised as the second most common cause of cancer death in female patients, significant progress has been made in breast cancer patient management, with anticipated 5-year survival rates improved from 40% to 87% over the past five decades [2]. Our enhanced understanding of the biological processes driving the disease and the increasing discovery of effective treatment options have resulted in a decrease in breast cancer mortality of 2–3% per year in the developed world [3]. While complete surgical resection remains the cornerstone of breast cancer control, recent advances in treatment options have facilitated more refined and personalised approach to breast cancer patient care. These timely enhancements of breast cancer care coincide with our heightened appreciation for molecular, cellular, and genomic properties driving oncogenesis in the molecular era. We now recognise a novel taxonomy of breast cancer which classifies four distinct clinically relevant molecular subtypes, i.e., Luminal A breast cancer (LABC), Luminal B breast cancer (LBBC), human epidermal growth factor Receptor-2-enriched breast cancer (HER2) and basal-like triple-negative breast cancer (TNBC) [4]. The gold standard in classifying breast tumours into these intrinsic biological subtypes is determined using multigene signatures (such as PAM50 assay from NanoString Technologies, Seattle, Washington, USA). However, the routine immunohistochemical appraisal of the estrogen (ER), progesterone (PgR) and HER2 receptor, as well as proliferation indices (Ki-67) in locally accredited histopathology laboratories, are also utilised in practice [5].

Despite our efforts to substratify cancers into prognostic subgroups, tumour behaviour and prognosis remains unpredictable and adds difficulty in attempts to optimise strategies to improve disease control while minimising toxicities to patients. Precision oncology relies on strategies such as genomic profiling to personalise care for breast cancer patients; the 21-gene expression assay (OncotypeDX Recurrence Score©, Genomic Health Inc., Redwood City, CA, USA) is routinely used in ER+/HER2-node-negative early breast cancer patients to select those who will derive the most benefit from systemic chemotherapy prescription, with first results from trial data supporting the expansion of indications to include those with 1–3 positive axillary nodes [6]. Within hereditary breast cancer, genetic profiling is used to identify patients with BRCA1/2 mutations to determine strategies surrounding prophylactic mastectomy. Furthermore, breast oncology has progressed in recent years to recognise the inherent value of treating patients with chemotherapy in the neoadjuvant setting. Advantages such as tumour downstaging and increased breast conserving surgery are beneficial for patients hoping to avoid mastectomy [7,8]. Moreover, the neoadjuvant prescription of systemic therapies allows for the generation of in-vivo data in relation to tumour sensitivity, which has been illustrated to carry prognostic significance for disease recurrence and survival. These modern facets of conventional breast cancer management provide insight into the potential utility of novel biomarkers in enhancing the current treatment paradigm. At present, there is a paucity of biomarkers capable of accurately predicting response and resistance to current systemic and targeted therapies, while efforts to employ non-invasive techniques to capture such biomarkers have proven futile to some extent. This reinforces the high priority for scientists to detect novel biomarkers capable of detecting response to treatment, inform the prognosis of patients diagnosed with breast cancer and provide clinicians with novel therapeutic strategies to target oncogenesis. This review focuses on the role of microRNA (miRNA) as emerging clinical biomarkers within the context of breast cancer surgery and treatment.

2. miRNAs as Breast Cancer Biomarkers

miRNAs are small (19–25 nucleotides in length), endogenous, non-coding RNA understood to play important regulatory roles in governing gene expression and cellular activity. Aberrant miRNA expression profiles have been observed in a diversity of pathological processes, including cancer development [9]. miRNAs have been demonstrated to regulate gene expression at a post-transcriptional level via binding to 3′ or 5′ untranslated regions of target messenger RNA (mRNA), directly impairing the mRNA degradation or inhibition of translation. In addition to their inhibitory role, miRNAs have been described to facilitate increase in transcript levels, increasing gene expression in certain circumstances [10].

First described by Lee et al. in 1993 [11], miRNA expression has been critically implicated in the development of human cancers, with translational research efforts growing exponentially in recent years [12,13]. miRNA biogenesis is a complex, multistep processes which is initiated in the cellular nucleus, where miRNA genes undergo transcription by RNA polymerase II/III to form large capped and polyadenylated primary miRNA transcripts (pri-miRNAs). The cleavage of these molecules by the coupled RNase III enzyme Drosha and its complementary binding partner DCGR8 produce pre-miRNA (70–90 nucleotides in length). These pre-miRNAs are the precursors to miRNA and are transported out of the cellular nucleus by the export protein Exportin 5, in their “imperfect” hairpin structures [14]. In the cytoplasm, these pre-miRNAs are cleaved by RNase type III Dicer with either the trans-activating RNA-binding protein (TRBP) or the protein activator of the interferon-induced protein kinase (PACT) [15], with one strand of this miRNA duplex representing mature miRNA which forms the RNA-induced silencing complex with other proteins [16]. This mature strand is preferentially incorporated into the miRNA-associated RNA-induced silencing complex (miRISC), which guides the RISC to target mRNA with complementary sequences to the mature miRNA. This ultimate step is responsible for impacting cellular activity.

miRNAs may be used to further substratify breast cancers into distinct subtypes, and miRNA expression profiles have successfully been utilised to predict steroid hormone receptor status [17], implicating targeting such biomarkers may be an advantageous strategy in dysregulated-receptor-associated miRNAs. Aberrant miRNA expression has been correlated to epithelial–mesenchymal transition (EMT), highlighting their critical role in cancer pathways capable of inducing distant metastasis [18,19]. These are examples of the crucial role of miRNAs within the breast cancer paradigm and are vital for the clinical scientists in the efforts to develop novel therapeutic strategies to enhance patient outcomes and inform prognoses. Data supporting miRNAs as modulators of genetic expression within breast cancer place them as obvious candidate prognostic and diagnostic biomarkers [20], as well as potential therapeutic targets. Furthermore, the unique capability of these molecules to maintain their stability over prolonged time makes them favourable informative biological parameters [21]. However, there remains limitations of miRNAs as biomarkers in breast cancer: At present, the absolute quantification of miRNAs following quantitative real-time polymerase chain reactions provides challenging to the current translational research effort, with inconsistencies observed in results limiting their implementation into clinical practice. The quantification of miRNAs in liquid biopsy form also yields inconsistent results, with apparent uncertainty being cast over what the optimal medium is (i.e., serum, plasma or whole blood) to evaluate miRNA expression levels [22]. These physical properties add further complexity to the routine implementation of miRNAs as biomarkers in the clinical setting of breast cancer workup and diagnosis.

3. MicroRNAs in Predicting Response and Resistance to Neoadjuvant Therapies

Oncological outcomes are enhanced by systemic chemotherapy prescription prior to or following cancer surgery, in particular when a multimodal therapeutic approach including endocrine agents, targeted therapies and radiotherapy are utilised [23]. The first chemotherapeutical regimen for operable breast cancer was prescribed in 1976 by Bonadanna et al. [24], where cyclophosphamide, methotrexate and 5-fluorouracil (CMF) significantly reduced breast cancer recurrence rates in 207 breast cancer patients compared to in controls (recurrence: 5.3% vs. 24.0%). Bernard Fisher and the National Surgical Adjuvant Breast and Bowel Projects (NSABP) first investigated the concept of systemic chemotherapy to enhance clinical outcomes in breast cancer through prospective, randomised control trials (RCTs): The seminal NSABP-B18 RCT involved the randomisation of over 1500 women to receive neoadjuvant or adjuvant doxorubicin and cyclophosphamide and was the original study investigating systemic chemotherapy prescription in the neoadjuvant setting [25]. Although results from NSABP-B18 (and more recent meta-analysis of RCTs) outlined no survival advantage for chemotherapy prescription in the neoadjuvant or adjuvant settings [26], an increase in the number of cancers amenable to breast conservation surgery (BCS) [25] was observed following a neoadjuvant approach. Since then, the focus has been adjusted to predict response rates to neoadjuvant chemotherapies (NAC) with efforts centred around predicting those likely to achieve favourable responses, such as pathological complete response (pCR), defined as complete eradication of the tumour from the breast and/or axilla, or those which are likely to develop resistance to treatment. Traditional molecular biomarkers such as ER, PgR, Ki-67 indices and Nottingham grade have all been used as predictive biomarkers of response to NAC. In more recent times, miRNA profiling has proven useful in dichotomising patients into those unlikely to response and those likely to achieve partial response or complete response to NAC (Table 1) [27,28,29,30,31,32,33,34,35,36,37]. Furthermore, the real-time monitoring of miRNA expression levels has the potential to enhance the sensitivity of current systemic therapies on the tumour or identify cancers likely to be resistant to treatment. Kolacinska et al. demonstrate the ability of miRNA panels to predict the response of basal carcinoma to NAC, with increased expression levels of miR-200b-3p and miR-190a differentiating good from poor responses [37], as did decreased expression of miR-512-5p. Bockhorn et al. describe the chemoresistant role of miR-30c through the regulation of the twinfilin1 actin-binding protein, a known promoter of EMT. MiR-30a inversely correlates with interleukin-11 expression in breast cancer, with low interleukin-11 correlating with relapse-free survival [38].

Table 1.

Studies correlating microRNA (miRNA) expression profiles to response to neoadjuvant chemotherapy.

Author Year Country Tissue N LOE Neoadjuvant Treatment miRNA Expression
Liu
[27]
2017 China Serum 86 N/R EC & DTX At the end of C2, reduced miR-34a correlated to response to NAC.
Ohzawa
[28]
2017 Japan Tumour tissue 47 Retrospective (III) Anthracycline, DTX & Trastuzumab The decreased expression of 13 miRNA predicted pCR and the increased expression of 4 miRNA-predicted pCR in HER2+ disease.
Garcia-Vazquez
[29]
2019 Mexico Tumour tissue 35 Retrospective (III) 5-FU, cisplatin
& PTX
Low miR-143 predicted pCR in TNBC patients.
Garcia-Garcia
[30]
2019 Mexico Tumour tissue 32 Retrospective (III) N/R MiR-145-5p expression is associated with pCR in TNBC.
De Mattos-Arruda
[31]
2015 Spain Tumour tissue 52 Retrospective (III) Anthracycline, DTX & Trastuzumab Increased miR-21 expression levels correlated to response to treatment in HER2+ cancers.
Zhao
[32]
2011 China Plasma 27 Retrospective (III) Epirubicin, DTX
or PTX
Increased miR-221 expression levels predicted poor response to neoadjuvant therapies.
Raychaudhuri
[33]
2017 Germany Tumour tissue 64 Retrospective (III) Epirubicin & PTX
or EC & DTX
High miR-7 and reduced mir340 expression levels predicted response to NAC.
Liu
[34]
2019 China Serum 83 Retrospective (III) DTX, Paraplatin
& Trastuzumab
Decreased miR-21 expression levels in serum associated with clinical response to NAC
Liu
[35]
2017 China Serum 118 Retrospective (III) EC & DTX Serum measurements of miR-21 and miR-125b predicted response to NAC (combined AUC: 0.958)
Chekhun
[36]
2020 Ukraine Serum 182 Retrospective (III) 5-FU, DXR & cyclophosphamide or DXR & cyclophosphamide Aberrant levels of miR-21, miR-182 and miR-205 predicted response to NAC in Luminal A breast cancer.
Kolacinska
[37]
2014 Poland Tumour tissue 11 Retrospective (III) Various Increased miR-190a, miR-200b-3p and miR-512-5p expression levels predicted pCR in TNBC.

N, number; LOE, level of evidence; NAC, neoadjuvant chemotherapy; C2, cycle 2; N/R, not reported; EC, epirubicin and cyclophosphamide; DTX, docetaxel; PTX, paclitaxel; 5FU, 5-fluorouracil; DXR, doxorubicin; TNBC, triple-negative breast cancer; HER2, human epidermal growth factor receptor-2; AUC, area under the curve.

In their analysis of the blood serum of 56 breast cancer patients, Wang et al. illustrate reduced miR-125b levels to correlate with resistance to four cycles of neoadjuvant 5-fluorouracil, epirubicin and cyclophosphamide (FEC) [39]. Chen et al. describe the downregulation of miR-200c to correlate clinically with drug resistance in 39 breast cancer patients in receipt of 2–6 cycles of epirubicin with or without docetaxel [40], which were validated subsequently through the work of Kopp et al. [41]. Within the context of HER2-positive breast cancer, Jung et al. describe increased miR-210 levels in patients with residual disease following treatment with trastuzumab-based NAC [42], indicating chemoresistance. Zhao et al. present results from 93 breast cancer patients and 32 “healthy” controls outlining the predictive value of miR-221 in identifying patients likely to develop chemoresistance to NAC [32]. Such studies provide clinical relevance in identifying patients with large, locally advanced disease who are likely to respond to neoadjuvant therapies and facilitate BCS by proxy through tumour downstaging.

As described, in vitro studies have successfully identified miRNA likely to inform treatment response, while real-world data from the translational arms of the prospective, multicentre translational Neoadjuvant Lapatinib and/or Trastuzumab Treatment Optimization [NeoALLTO] trial and Clinical Trials Ireland All-Ireland Cooperative Oncology Research Group [CTRIAL-IE ICORG] 10/11 trial clinicals highlight the significance of circulating biomarkers to indicate response to neoadjuvant therapies (Table 2) [42,43,44,45,46,47,48,49,50,51,52]. In the NeoALLTO trial, an analysis of miRNAs as circulating biomarkers in 451 female patients was conducted, with 30 and 6 miRNA signatures developed to predict pCR at baseline and after 2 weeks of neoadjuvant treatment, respectively [43]. Of these, four miRNAs were validated in predicting response to neoadjuvant therapies. In trials similar to the aforementioned studies, pCR has become incorporated as a primary analytical endpoint in the next generation of prospective, neoadjuvant clinical trials. This is rationalised by the novel prognostic significance correlated with response to therapy within the landscape of breast cancer patient outcomes, with patients achieving pCR experiencing enhanced survival when compared to their counterparts with residual disease.

Table 2.

Prospective clinical studies correlating miRNA expression profiles to response to neoadjuvant chemotherapy.

Author Year Country Tissue N LOE Neoadjuvant Treatment miRNA Expression
Di Cosimo
[43]
2019 Italy Plasma 429 Prospective (II); NeoALLTO trial (NCT: 00553358) Trastuzumab, lapatinib
& paclitaxel
Increased miR-140a-5p, miR-148a-3p and 374a-5p associated with pCR.
McGuire
[44]
2020 Ireland Whole blood 114 Prospective (II); Clinical Trials Ireland All-Ireland Cooperative Oncology Research Group [CTRIAL-IE ICORG] 10/11 (NCT: 00553358) Various Responders had reduced miR-21 and miR-195 vs. non-responders in all breast cancer subtypes. miR-21 predicted response (OR: 0.538; 95% CI: 0.308–0.943).
Jung
[42]
2012 US/Korea Plasma 72 Prospective (II) 5-FU, EC
& trastuzumab
Lower miR-210 expression levels predicted pCR in HER2+ cancers.
Muller
[45]
2014 Germany Serum 127 Prospective (II); Geparquinto Trial (NCT: 00567554) NAC with trastuzumab or lapatinib miR-21, miR-210 and miR-373 were elevated in responders’ post-NAC for HER2+ cancers.
Al-Khanbashi [46] 2016 Oman Tumour, TAN and serum 36 Prospective (II) DXR, cyclophosphamide & DTX Serum miR-451 expression levels decreased during NAC in clinical responders.
Rodríguez-Martínez
[47]
2019 Spain Whole blood 53 Prospective (II) Various miR-21 expression levels during NAC discriminated pCR, PR and SD.
Stevic
[48]
2016 Germany Plasma 211 Prospective (II); GeparSixto Trial (NCT: 01426880) DTX or PTX
+/- Carboplatin
Aberrant miR-199a associated with pCR to NAC
Zhang
[49]
2020 China Blood 65 Prospective (II); SHPD001 (NCT:02199418) & SHPH02 (NCT: 02221999) PTX, cisplatin
& trastuzumab
Low miR-222-3p expression levels predicted those achieving pCR (OR: 0.258; 95% CI: 0.070–0.958)
Kahraman
[50]
2018 Germany Blood 21 Prospective (II); Molecular DEtection of Breast cancer (MODE-B) study Carboplatin
& PTX
Mutli-miRNA panels predicted responders from non-responders to NAC in TNBC.
Zhu
[51]
2018 China Blood 24 Prospective (II); NCT:02041338 Epirubicin
& DTX
Reduced miR-34a was observed in non-responders to NAC compared to in responders.
Di Cosimo
[52]
2020 Italy Plasma 429 Prospective (II); NeoALLTO trial (NCT: 00553358) Trastuzumab, lapatinib
& PTX
Multiple miRNA expression profiles correlated to pCR to lapatinib, trastuzumab or dual anti-HER2 therapy.

N, number; LOE, level of evidence, NCT, national clinical trial identifier; TAN, tumour-associated normal; OR, odds ratio; CI, confidence interval; TNBC, triple-negative breast cancer; HER2, human epidermal growth factor receptor-2; EC, epirubicin and cyclophosphamide; 5FU, 5-fluorouracil; DTX, docetaxel; PTX, paclitaxel; DXR, doxorubicin; pCR, pathological complete response; PR, partial response; SD, stable disease; NAC, neoadjuvant chemotherapy.

As outlined, miRNA profiling has proven a useful avenue to predict response and resistance to chemotherapy and other treatment modalities. Several studies suggest the reintroduction of specific miRNAs which are known to be downregulated during oncogenesis into cancer cells, in order to halt tumour growth and progression [53,54]. This hypothesis has the potential to provide therapeutic benefits; the restoration of the cells natural endogenous complement of miRNA may be achieved through the implantation of short synthetic duplex RNAs using the RISC or by inducing the genetic expression of the stem-loop pre-miRNA through extracellular vesicles. On the contrary, an alternative approach involves the utility of miRNA modulation to enhance sensitivity to current conventional therapeutic strategies; Miller at al. illustrate the role of miR-221/miR-222 overexpression in inducing tamoxifen resistance in HER2/neu-positive 4-hydroxytamoxifen-resistant (OHTR) breast cancer cell lines [55]. These effects of tamoxifen sensitivity were shown to be mediated by the direct target of miR-221 and miR-222, the cell cycle inhibitor p27Kip1. The authors manipulated levels of p27Kip1, which re-sensitised the cells to tamoxifen therapy, thereby highlighting the role in miR-221/miR-222 antagonism in cases of luminal breast cancer displaying resistance to endocrine agents.

Novel hypotheses surrounding the development of therapeutic and diagnostic strategies within breast oncology include the manipulation of heat shock proteins (HSPs), which play crucial roles in post-translational activities, in order to enhance drug delivery. Ozgur et al. have previously demonstrated that two miRNAs (miR-29a and miR-193b) are both associated with cancer through their contact with heat shock protein 70 (HSP70) [56], which provides potential to enhance treatment effects. The oncogenic role of miR-21 in cancer is well described [57,58], and Si et al. have assessed the utility of anti-miR-21 2-O-methyl or locked nucleic acid oligonucleotides for therapeutic targeting to inactivate the oncogenic impact of this “oncomiR” [59]. If combined with current conventional therapeutic strategies, these pre-clinical studies provide promise for miRNA targets to enhance cancer patient care, by reducing oncogenesis through manipulation of oncogenic miRNA expression patterns. Turning focus to the clinical setting, the seminal work of McGuire et al. in the CTRIAL-IE ICORG 10/11 prospective, multicentre translational trial highlights the value of miR-21 expression as a correlate to response to standard NAC in their analysis of 114 breast cancer patients [44]. Other studies evaluating the role of miRNAs to indicate treatment response has shown some promising results (as outlined in Table 1 and Table 2): Jung et al. implicate miR-210 as a predictive biomarker of response to trastzumab in HER2-positive breast cancer patients [42], with upregulation being associated with resistance to such therapies, while Ichikawa et al. also demonstrate the utility of miR-26a and miR-30b in mediating the impact of anti-HER2 therapies [60].

4. miRNA in Predicting Outcome in Operable Breast Cancer

Personalised breast cancer patient management is dependent upon a myriad of reliable predictive biomarkers capable of forecasting outcome. Traditionally, clinicopathogical variables such as age at diagnosis, disease burden and tumour grade provided insight into anticipated outcome and preoperative planning [61]. While the molecular era has shifted the paradigm toward encompassing intrinsic biological tumour parameters which inform treatment decisions and prognoses, the degree of disease burden remains paramount to preoperative surgical planning. The routine measurement of the ER, PgR, HER2 receptors and Ki-67 proliferation indices [62,63,64] furthers accurate prognostication through intrinsic molecular subtyping, with modern advances implicating features pertinent to the tumour microenvironment important in informing prognosis [65]. Several studies detail miRNA expression profiles in breast cancer tissue, outlining their importance in relation to nodal burden, disease recurrence and survival [58,66,67].

Although there are a limited number of studies correlating miRNAs with nodal status, Elango et al. provide a thorough report of a 40-miRNA panel capable of predicting lymph-node metastasis in breast cancer [68], with miR-205 and miR-214-3p also predicting overall survival (OS). These miRNAs could prove informative as a “double-sword” biomarkers useful for preoperative surgical planning and also acting to inform prognoses. Liu et al. describe miR-10b as a marker of distant disease recurrence in 195 patients initially naïve of nodal metastasis [69]. In their analysis of 159 breast cancer patients, Chen et al. created a novel 4-miRNA signature (miR-191-5p, miR-214-3p, miR-451a and miR-489), which is reliable in predicting lymph-node metastasis (area under curve (AUC): 0.932; OS (hazard ratio (HR)): 6.2; disease-free survival (DFS) (HR): 6.3) [70]. These promising results highlight the pertinence of miRNAs in breast cancer development and progression, with these four mi-RNAs working synergistically to act as a potential predictor of cancer metastasis and patient prognoses. Okuno et al. describe the relevance of combining typical clinicopathological data (i.e., tumour size and lymphovascular invasion) with miR-98 expression levels to predict sentinel lymph-node biopsy positivity in 100 ER+/HER2- breast cancer patients (AUC: 0.877) [71]. Although exploring the utility of miRNA expression profiles to inform preoperative surgical planning, data supporting miRNA expression in predicting survival outcomes are paramount in an attempt to personalise therapeutic strategies. Wang et al. highlight the critical role of miR-21 expression in promoting metastatic transformation in their analysis of 252 breast cancer patients [58], while Sporn et al. [67] link miR-9 expression levels with OS in 985 breast cancer patients in The Cancer Genome Atlas. Tokumaru et al. report a dual purpose of miR-143 increased expression through correlation with enhanced OS and also with the presence of favourable tumour microenvironment cells (macrophage-2 and T-helper-2 cells) in patients diagnosed with luminal breast cancer [72]. These results imply that the treatment of luminal cancers with immunomodulatory drugs may prove futile, as has been outlined in a recent meta-analysis [65]. In their cox regression analysis, Sheng et al. describe miR-4317 as a predictive biomarker of OS (HR: 2.108) [73], while Gao et al. provide log-rank Kaplan–Meier analyses to highlight the predictive value of miR-1, miR-4274 and miR-6880 (all p < 0.001) as biomarkers of survival in breast cancer. Moreover, Zhang et al. highlight the clinical relevance of increased miR-330 expression in predicting enhanced survival for breast cancer patients [49]. Table 3 outlines multi-miRNA signatures and their role in predicting outcome in breast cancer [74,75,76,77,78,79,80,81,82,83].

Table 3.

miRNA signatures and their roles in predicting outcome in breast cancer patients.

Author Year Country Tissue N miRNA Expression Signatures
Lai
[74]
2019 China Tumour & TAN 1044 Six miRNA signatures (miR-147b, miR-549a, miR-4501, miR-4675, miR-6715a and miR-7974) predicted OS at 5 years (AUC: 0.789).
Hong [75] 2020 China Tumour 111 Eight miRNA expression signatures (miR-139-5p, miR-10b-5p, miR-486-5p, miR-455-3p, miR-107, miR-146b-5p, miR-324-5p and miR-20a-5p) predicted relapse and prognosis in TNBC (AUC: 800).
Cheng
[76]
2018 China Tumour & TAN 1207 Three miRNA expression signatures (including miR-133a-2, miR-204 and miR-301b) independently predicted OS (HR: 1.638; 95% CI: 1.147–2.339).
Shi
[77]
2018 China Tumour 1098 Three multi-miRNA signatures including miR-16-2, miR-31 and miR-484 predicted OS (AUC: 690).
Andrade
[78]
2020 Brazil Tumour 185 Four miRNA expression panels (miR-221, miR-1305, miR-4708 and RMDN2) substratified TNBC patients into high- and low-risk groups and independently predicted OS (HR: 0.32; 95% CI: 0.11–0.91).
Wu
[79]
2020 China Tumour & TAN 199 Aberrant expression levels of three miRNA (miR-21-3p, miR-200b-5p and miR-659-5p) independently predicted OS (HR: 7.396; 95% CI: 1.590–34.411).
Tang
[80]
2019 China Tumour 1098 Seventeen miRNA panels were constructed to predict OS, and a 13-miRNA signature predicted RFS.
Farina
[81]
2017 US Tumour 48 Six miRNA panels (miR-3124-5p, miR-1184, miR-4423-3p, miR-4529-5p, miR-7855-5p and miR-4446-3p), which predicted OS (AUC: 0.896; CI: 0.804–0.988).
Li
[82]
2018 China Serum 386 Four miRNA signatures (miR-16-5p, miR-17-3p, miR-451a and miR-940) predicted 1-year and 2-year predicted OS (AUC: 0.80 and 0.74, respectively) for metastatic HER2+ breast cancers.
Rohan [83] 2019 US Tumour 530 Thirteen miRNA expression panels were designed to predict breast cancer recurrence (AUC: 0.67; CI: 0.58–0.795).

N, number; TAN, tumour-associated normal; OS, overall survival; AUC, area under the curve; TNBC, triple-negative breast cancer; HR, hazard ratio; CI, confidence interval; RFS, recurrence-free survival; US, United States; HER2, human epidermal growth factor receptor-2.

5. Limitations and Challenges of miRNAs as Biomarkers

Despite considerable funding, investment and resource distribution into the investigation of miRNA as reliable and reproducible clinical biomarkers in breast cancer research and treatment, we are yet to undercover novel biomarkers which can rival the principal ER, PgR, and HER2 receptors to inform breast cancer diagnosis, prognosis and therapeutic strategies. Since the emergence of the molecular era, genomic signatures such as the 21-gene assay and the Mammaprint© 70-gene assay (Agendia, Amsterdam, The Netherlands) has reliably and reproducibly informed prognoses, refined therapeutic systematic chemotherapy prescription and facilitated personalised cancer treatment in early-stage luminal diseases [84,85,86,87,88]. The identification and characterisation of miRNA expression which are as reliable and reproducible as these genomic panels limit current hypotheses, suggesting miRNAs may be impactful biomarkers in malignancy [89]. Biomarker signatures currently used in clinical practice, such as the aforementioned 21-gene and 70-gene assays, all rely on the absolute quantification of genetic targets from paraffin-embedded tumour specimens and are incredibly reproducible from patient to patient. In contrast, the diagnostic, prognostic and therapeutic utilisation of miRNAs is currently dependent upon relative quantification, thus imposing less consistent and translatable results. There are a number of additional inherent challenges observed in ensuring accuracy in miRNA measurement: There remain inconsistencies in consensus in relation to the preparation of miRNAs for evaluation, for example discrepancies in results in relation to the most appropriate medium from which miRNAs are extracted [90]. There are data suggesting that whole blood is a poor biological fluid as constituent cancer cells alter miRNA expression levels in circulation [90], and consensus in relation to plasma and serum has not been reached. Varying methodologies have been employed with respect to sample preparation, anticoagulation, centrifugation and storage properties, and polymerase chain reaction protocols have all contributed to interstudy variability and inconsistencies in reported outcomes [91,92,93]. The normalisation of miRNAs has proven problematic for scientists due to the lack of a universal consensus regarding an accepted, appropriate reference miRNA. McDermott et al. implicate miR-16 and miR-425 in combination as the primary endogenous (or “housekeeping”) reference targets for breast cancer [94]; however, data from Pritchard et al. imply miR-16 is imperfect in this role, as it is impacted by haemolysis [90]. Such conundrums add further inconsistencies to current research methods, limiting conclusions which may be drawn due to the creation of heterogenous results [90,95]. The translational research effort would greatly benefit from the standardisation of protocols in order to ensure the accurate comparability of results, which may be interpreted in a homogenous nature and translated into meaningful scientific results. This may be best achieved through the collaboration of an expert consensus panel to compile their views on the appropriate measures to improve the current practice surrounding miRNA measurement. Thus, the creation and implementation of a standardized protocol for miRNA measurements seems warranted, if these molecules are to be utilised routinely as prospective diagnostic or prognostic biomarkers in cancer patient care.

The retention of the overall stability of these biomarkers in circulation between timepoints and individuals [96] remains a challenge in miRNA therapeutics, particularly with variation in expression levels at different timepoints and between certain individuals [96]. Another primary challenge in cancer therapeutics is the successful delivery of miRNAs to the target tissue in cancer, and there is an increase in the enhanced permeability and retention (EPR) effect, which causes poor blood perfusion, leading to a reduction in the efficacy of the delivery of miRNAs to local tissues [97], impacting these biomarkers as reliable treatment options. The utilisation of liposomes to increase delivery of miRNA [98], the introduction of molecules to positively impact the EPR effect [99], as well as the use of delivery vehicles such as exosome-encapsulated miRNA delivered through mesenchymal stem cells [100,101] and viral vectors have been deployed to increase miRNA delivery [99] into target tissues. Ambitions to manipulate complex facets of miRNA delivery are pertinent currently; however, promising breakthroughs are awaited eagerly.

Lastly, simple host and environmental factors such as patient age, gender, smoking habits and local trauma may impact miRNA expression profiles [102,103,104,105]. Fundamentally, this limits conclusions which may be drawn in relation to miRNA as accurate biomarkers indicative of cancer-related outcome, particularly in the setting of small patient sample sizes in pre-clinical research studies facilitating the scrutiny of results relating to miRNA expression profiles. In such incidences, the complexity of miRNA expression requires more interrogation than simple correlation with variable clinicopathological data in the hope of deriving statistically significant results. Thus, the interrogation of the scientific method with robust data is warranted in further translational research studies evaluating the relevance of miRNAs in clinical breast cancer management.

6. Future Directions

The correlation between aberrant miRNA expression patterns within tumourgenesis and disease development illustrates the hypothesis fuelling efforts to use miRNAs targeting to discover the next generation of anti-cancer therapeutics. As previously outlined, novel hypotheses and relevant therapeutic and diagnostic strategies include the alteration of HSP function, potential manipulation of “oncomiR” expression through the addition of 2-O-methyl or locked nucleic acid oligonucleotides for the therapeutic inactivation of the oncogenic impact of these targets, as well as other novel strategies to enhance tumour suppressors or reduce oncogenic miRNA expression patterns. Future directions for the next generation of prospective, translational research studies may be built on the previous scientific escapades of these previous authors to better inform patient prognostication, develop novel therapeutic strategies which utilise miRNAs as potential targets and ensure miRNA appraisal is focused at enhancing treatment effects and the improvement of clinical outcomes for those who succumb to new breast cancer diagnoses or recurrence.

Author Contributions

Conceptualization, M.G.D. and M.J.K.; investigation, M.G.D. and M.D.; resources, M.G.D.; data curation, M.G.D. and M.D.; writing—original draft preparation, M.G.D.; writing—review and editing, M.G.D., M.D., N.M. and M.J.K.; visualization, M.G.D. and M.J.K.; supervision, A.J.L., N.M. and M.J.K.; project administration, M.G.D.; funding acquisition, M.G.D., A.J.L. and M.J.K. All authors have read and agreed to the published version of the manuscript.

Funding

M.G.D. and M.D. received funding from the National Breast Cancer Research Institute, Ireland.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

None of the authors have any conflict of interest to disclose.

Footnotes

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References

  • 1.Ferlay J., Soerjomataram I., Dikshit R., Eser S., Mathers C., Rebelo M., Parkin D.M., Forman D., Bray F. Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012. Int. J. Cancer. 2015;136:E359–E386. doi: 10.1002/ijc.29210. [DOI] [PubMed] [Google Scholar]
  • 2.United Kingdom Cancer Research Breast Cancer Statistics. [(accessed on 30 May 2021)]; Available online: https://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/breast-cancer.
  • 3.Levi F., Bosetti C., Lucchini F., Negri E., La Vecchia C. Monitoring the decrease in breast cancer mortality in Europe. Eur. J. Cancer Prev. 2005;14:497–502. doi: 10.1097/00008469-200512000-00002. [DOI] [PubMed] [Google Scholar]
  • 4.Goldhirsch A., Winer E.P., Coates A., Gelber R., Piccart-Gebhart M., Thürlimann B., Senn H.-J., Albain K.S., André F., Bergh J. Personalizing the treatment of women with early breast cancer: Highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Ann. Oncol. 2013;24:2206–2223. doi: 10.1093/annonc/mdt303. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Morigi C. Highlights of the 16th St Gallen International Breast Cancer Conference, Vienna, Austria, 20–23 March 2019: Personalised treatments for patients with early breast cancer. Ecancermedicalscience. 2019;13:924. doi: 10.3332/ecancer.2019.924. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Kalinsky K., Barlow W.E., Meric-Bernstam F., Gralow J.R., Albain K.S., Hayes D., Lin N., Perez E.A., Goldstein L.J., Chia S. Abstract GS3-00: First Results from a Phase III Randomized Clinical Trial of Standard Adjuvant Endocrine Therapy (ET)+/-Chemotherapy (CT) in Patients (Pts) with 1–3 Positive Nodes, Hormone Receptor-Positive (HR+) and HER2-Negative (HER2-) Breast Cancer (BC) with Recurrence Score (RS)<25: SWOG S1007 (RxPonder) American Association for Cancer Research (AACR); Philadelphia, PA, USA: 2021. [Google Scholar]
  • 7.Cho J.H., Park J.M., Park H.S., Park S., Kim S.I., Park B.W. Oncologic safety of breast-conserving surgery compared to mastectomy in patients receiving neoadjuvant chemotherapy for locally advanced breast cancer. J. Surg. Oncol. 2013;108:531–536. doi: 10.1002/jso.23439. [DOI] [PubMed] [Google Scholar]
  • 8.Spring L.M., Fell G., Arfe A., Sharma C., Greenup R., Reynolds K.L., Smith B.L., Alexander B., Moy B., Isakoff S.J. Pathologic complete response after neoadjuvant chemotherapy and impact on breast cancer recurrence and survival: A comprehensive meta-analysis. Clin. Cancer Res. 2020;26:2838–2848. doi: 10.1158/1078-0432.CCR-19-3492. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Heneghan H.M., Miller N., Kelly R., Newell J., Kerin M.J. Systemic miRNA-195 differentiates breast cancer from other malignancies and is a potential biomarker for detecting noninvasive and early stage disease. Oncologist. 2010;15:673–682. doi: 10.1634/theoncologist.2010-0103. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Place R.F., Li L.-C., Pookot D., Noonan E.J., Dahiya R. MicroRNA-373 induces expression of genes with complementary promoter sequences. Proc. Natl. Acad. Sci. USA. 2008;105:1608–1613. doi: 10.1073/pnas.0707594105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Lee R.C., Feinbaum R.L., Ambros V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell. 1993;75:843–854. doi: 10.1016/0092-8674(93)90529-Y. [DOI] [PubMed] [Google Scholar]
  • 12.Heneghan H., Miller N., Lowery A., Sweeney K., Kerin M. MicroRNAs as novel biomarkers for breast cancer. J. Oncol. 2009;2010 doi: 10.1155/2010/950201. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Casey M.-C., Kerin M.J., Brown J.A., Sweeney K.J. Evolution of a research field—A micro (RNA) example. PeerJ. 2015;3:e829. doi: 10.7717/peerj.829. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Bohnsack M.T., Czaplinski K., Görlich D. Exportin 5 is a RanGTP-dependent dsRNA-binding protein that mediates nuclear export of pre-miRNAs. RNA. 2004;10:185–191. doi: 10.1261/rna.5167604. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Yi R., Qin Y., Macara I.G., Cullen B.R. Exportin-5 mediates the nuclear export of pre-microRNAs and short hairpin RNAs. Genes Dev. 2003;17:3011–3016. doi: 10.1101/gad.1158803. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Ha M., Kim V.N. Regulation of microRNA biogenesis. Nat. Rev. Mol. Cell Biol. 2014;15:509–524. doi: 10.1038/nrm3838. [DOI] [PubMed] [Google Scholar]
  • 17.Lowery A.J., Miller N., Devaney A., McNeill R.E., Davoren P.A., Lemetre C., Benes V., Schmidt S., Blake J., Ball G. MicroRNA signatures predict oestrogen receptor, progesterone receptor and HER2/neu receptor status in breast cancer. Breast Cancer Res. 2009;11:R27. doi: 10.1186/bcr2257. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Zhang J., Ma L. MicroRNA control of epithelial–mesenchymal transition and metastasis. Cancer Metastasis Rev. 2012;31:653–662. doi: 10.1007/s10555-012-9368-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Abba M.L., Patil N., Leupold J.H., Allgayer H. MicroRNA regulation of epithelial to mesenchymal transition. J. Clin. Med. 2016;5:8. doi: 10.3390/jcm5010008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Catalanotto C., Cogoni C., Zardo G. MicroRNA in control of gene expression: An overview of nuclear functions. Int. J. Mol. Sci. 2016;17:1712. doi: 10.3390/ijms17101712. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Glinge C., Clauss S., Boddum K., Jabbari R., Jabbari J., Risgaard B., Tomsits P., Hildebrand B., Kääb S., Wakili R. Stability of circulating blood-based microRNAs-pre-analytic methodological considerations. PLoS ONE. 2017;12:e0167969. doi: 10.1371/journal.pone.0167969. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Backes C., Meese E., Keller A. Specific miRNA disease biomarkers in blood, serum and plasma: Challenges and prospects. Mol. Diagn. Ther. 2016;20:509–518. doi: 10.1007/s40291-016-0221-4. [DOI] [PubMed] [Google Scholar]
  • 23.Waks A.G., Winer E.P. Breast cancer treatment. JAMA. 2019;321:316. doi: 10.1001/jama.2018.20751. [DOI] [PubMed] [Google Scholar]
  • 24.Bonadonna G., Brusamolino E., Valagussa P., Rossi A., Brugnatelli L., Brambilla C., De Lena M., Tancini G., Bajetta E., Musumeci R. Combination chemotherapy as an adjuvant treatment in operable breast cancer. N. Engl. J. Med. 1976;294:405–410. doi: 10.1056/NEJM197602192940801. [DOI] [PubMed] [Google Scholar]
  • 25.Fisher B., Brown A., Mamounas E., Wieand S., Robidoux A., Margolese R.G., Cruz A.B., Jr., Fisher E.R., Wickerham D.L., Wolmark N. Effect of preoperative chemotherapy on local-regional disease in women with operable breast cancer: Findings from National Surgical Adjuvant Breast and Bowel Project B-18. J. Clin. Oncol. 1997;15:2483–2493. doi: 10.1200/JCO.1997.15.7.2483. [DOI] [PubMed] [Google Scholar]
  • 26.Asselain B., Barlow W., Bartlett J., Bergh J., Bergsten-Nordström E., Bliss J., Boccardo F., Boddington C., Bogaerts J., Bonadonna G. Long-term outcomes for neoadjuvant versus adjuvant chemotherapy in early breast cancer: Meta-analysis of individual patient data from ten randomised trials. Lancet Oncol. 2018;19:27–39. doi: 10.1016/S1470-2045(17)30777-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Liu B., Su F., Li Y., Qi X., Liu X., Liang W., You K., Zhang Y., Zhang J. Changes of serum miR34a expression during neoadjuvant chemotherapy predict the treatment response and prognosis in stage II/III breast cancer. Biomed. Pharmacother. 2017;88:911–917. doi: 10.1016/j.biopha.2017.01.133. [DOI] [PubMed] [Google Scholar]
  • 28.Ohzawa H., Miki A., Teratani T., Shiba S., Sakuma Y., Nishimura W., Noda Y., Fukushima N., Fujii H., Hozumi Y. Usefulness of miRNA profiles for predicting pathological responses to neoadjuvant chemotherapy in patients with human epidermal growth factor receptor 2-positive breast cancer. Oncol. Lett. 2017;13:1731–1740. doi: 10.3892/ol.2017.5628. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.García-Vázquez R., Marchat L.A., Ruíz-García E., De La Vega H.A., Meneses-García A., Arce-Salinas C., Bargallo-Rocha E., Carlos-Reyes Á., López-González J.S., Pérez-Plasencia C. MicroRNA-143 is associated with pathological complete response and regulates multiple signaling proteins in breast cancer. Technol. Cancer Res. Treat. 2019;18 doi: 10.1177/1533033819827309. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.García-García F., Salinas-Vera Y.M., García-Vázquez R., Marchat L.A., Rodríguez-Cuevas S., López-González J.S., Carlos-Reyes Á., Ramos-Payán R., Aguilar-Medina M., Pérez-Plasencia C. miR-145-5p is associated with pathological complete response to neoadjuvant chemotherapy and impairs cell proliferation by targeting TGFβR2 in breast cancer. Oncol. Rep. 2019;41:3527–3534. doi: 10.3892/or.2019.7102. [DOI] [PubMed] [Google Scholar]
  • 31.De Mattos-Arruda L., Bottai G., Nuciforo P.G., Di Tommaso L., Giovannetti E., Peg V., Losurdo A., Pérez-Garcia J., Masci G., Corsi F. MicroRNA-21 links epithelial-to-mesenchymal transition and inflammatory signals to confer resistance to neoadjuvant trastuzumab and chemotherapy in HER2-positive breast cancer patients. Oncotarget. 2015;6:37269. doi: 10.18632/oncotarget.5495. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Zhao R., Wu J., Jia W., Gong C., Yu F., Ren Z., Chen K., He J., Su F. Plasma miR-221 as a predictive biomarker for chemoresistance in breast cancer patients who previously received neoadjuvant chemotherapy. Oncol. Res. Treat. 2011;34:675–680. doi: 10.1159/000334552. [DOI] [PubMed] [Google Scholar]
  • 33.Raychaudhuri M., Bronger H., Buchner T., Kiechle M., Weichert W., Avril S. MicroRNAs miR-7 and miR-340 predict response to neoadjuvant chemotherapy in breast cancer. Breast Cancer Res. Treat. 2017;162:511–521. doi: 10.1007/s10549-017-4132-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Liu B., Su F., Lv X., Zhang W., Shang X., Zhang Y., Zhang J. Serum microRNA-21 predicted treatment outcome and survival in HER2-positive breast cancer patients receiving neoadjuvant chemotherapy combined with trastuzumab. Cancer Chemother. Pharmacol. 2019;84:1039–1049. doi: 10.1007/s00280-019-03937-9. [DOI] [PubMed] [Google Scholar]
  • 35.Liu B., Su F., Chen M., Li Y., Qi X., Xiao J., Li X., Liu X., Liang W., Zhang Y., et al. Serum miR-21 and miR-125b as markers predicting neoadjuvant chemotherapy response and prognosis in stage II/III breast cancer. Hum. Pathol. 2017;64:44–52. doi: 10.1016/j.humpath.2017.03.016. [DOI] [PubMed] [Google Scholar]
  • 36.Chekhun V., Borikun T., Bazas V., Andriiv A., Klyusov O., Yalovenko T., Lukianova N.Y. Association of circulating miR-21,-205, and-182 with response of luminal breast cancers to neoadjuvant FAC and AC treatment. Exp. Oncol. 2020;42:162–166. doi: 10.32471/exp-oncology.2312-8852.vol-42-no-3.14805. [DOI] [PubMed] [Google Scholar]
  • 37.Kolacinska A., Morawiec J., Fendler W., Malachowska B., Morawiec Z., Szemraj J., Pawlowska Z., Chowdhury D., Choi Y.E., Kubiak R. Association of microRNAs and pathologic response to preoperative chemotherapy in triple negative breast cancer: Preliminary report. Mol. Biol. Rep. 2014;41:2851–2857. doi: 10.1007/s11033-014-3140-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Bockhorn J., Dalton R., Nwachukwu C., Huang S., Prat A., Yee K., Chang Y.-F., Huo D., Wen Y., Swanson K.E. MicroRNA-30c inhibits human breast tumour chemotherapy resistance by regulating TWF1 and IL-11. Nat. Commun. 2013;4:1393. doi: 10.1038/ncomms2393. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Wang H., Tan G., Dong L., Cheng L., Li K., Wang Z., Luo H. Circulating MiR-125b as a marker predicting chemoresistance in breast cancer. PLoS ONE. 2012;7:e34210. doi: 10.1371/journal.pone.0034210. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Chen J., Tian W., Cai H., He H., Deng Y. Down-regulation of microRNA-200c is associated with drug resistance in human breast cancer. Med. Oncol. 2012;29:2527–2534. doi: 10.1007/s12032-011-0117-4. [DOI] [PubMed] [Google Scholar]
  • 41.Kopp F., Oak P.S., Wagner E., Roidl A. miR-200c sensitizes breast cancer cells to doxorubicin treatment by decreasing TrkB and Bmi1 expression. PLoS ONE. 2012;7:e50469. doi: 10.1371/journal.pone.0050469. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Jung E.J., Santarpia L., Kim J., Esteva F.J., Moretti E., Buzdar A.U., Di Leo A., Le X.F., Bast R.C., Jr., Park S.T. Plasma microRNA 210 levels correlate with sensitivity to trastuzumab and tumor presence in breast cancer patients. Cancer. 2012;118:2603–2614. doi: 10.1002/cncr.26565. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Di Cosimo S., Appierto V., Pizzamiglio S., Tiberio P., Iorio M.V., Hilbers F., De Azambuja E., De La Peña L., Izquierdo M., Huober J. Plasma miRNA levels for predicting therapeutic response to neoadjuvant treatment in HER2-positive breast cancer: Results from the NeoALTTO trial. Clin. Cancer Res. 2019;25:3887–3895. doi: 10.1158/1078-0432.CCR-18-2507. [DOI] [PubMed] [Google Scholar]
  • 44.McGuire A., Casey M.-C., Waldron R.M., Heneghan H., Kalinina O., Holian E., McDermott A., Lowery A.J., Newell J., Dwyer R.M. Prospective Assessment of Systemic MicroRNAs as Markers of Response to Neoadjuvant Chemotherapy in Breast Cancer. Cancers. 2020;12:1820. doi: 10.3390/cancers12071820. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Müller V., Gade S., Steinbach B., Loibl S., von Minckwitz G., Untch M., Schwedler K., Lübbe K., Schem C., Fasching P.A. Changes in serum levels of miR-21, miR-210, and miR-373 in HER2-positive breast cancer patients undergoing neoadjuvant therapy: A translational research project within the Geparquinto trial. Breast Cancer Res. Treat. 2014;147:61–68. doi: 10.1007/s10549-014-3079-3. [DOI] [PubMed] [Google Scholar]
  • 46.Al-Khanbashi M., Caramuta S., Alajmi A.M., Al-Haddabi I., Al-Riyami M., Lui W.-O., Al-Moundhri M.S. Tissue and serum miRNA profile in locally advanced breast cancer (LABC) in response to neo-adjuvant chemotherapy (NAC) treatment. PLoS ONE. 2016;11:e0152032. doi: 10.1371/journal.pone.0152032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Rodríguez-Martínez A., de Miguel-Pérez D., Ortega F.G., García-Puche J.L., Robles-Fernández I., Exposito J., Martorell-Marugan J., Carmona-Sáez P., del Carmen Garrido-Navas M., Rolfo C. Exosomal miRNA profile as complementary tool in the diagnostic and prediction of treatment response in localized breast cancer under neoadjuvant chemotherapy. Breast Cancer Res. 2019;21:21. doi: 10.1186/s13058-019-1109-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Stevic I., Müller V., Weber K., Fasching P.A., Karn T., Marmé F., Schem C., Stickeler E., Denkert C., van Mackelenbergh M. Specific microRNA signatures in exosomes of triple-negative and HER2-positive breast cancer patients undergoing neoadjuvant therapy within the GeparSixto trial. BMC Med. 2018;16:179. doi: 10.1186/s12916-018-1163-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Zhang H., Wang X., Zhang F. Correlations of the MiR-330 expression with the pathogenesis and prognosis of breast cancer. Eur. Rev. Med. Pharmacol. Sci. 2019;23:1584–1590. doi: 10.26355/eurrev_201902_17117. [DOI] [PubMed] [Google Scholar]
  • 50.Kahraman M., Röske A., Laufer T., Fehlmann T., Backes C., Kern F., Kohlhaas J., Schrörs H., Saiz A., Zabler C. MicroRNA in diagnosis and therapy monitoring of early-stage triple-negative breast cancer. Sci. Rep. 2018;8:1–11. doi: 10.1038/s41598-018-29917-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Zhu W., Liu M., Fan Y., Ma F., Xu N., Xu B. Dynamics of circulating micro RNA s as a novel indicator of clinical response to neoadjuvant chemotherapy in breast cancer. Cancer Med. 2018;7:4420–4433. doi: 10.1002/cam4.1723. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Di Cosimo S., Appierto V., Pizzamiglio S., Silvestri M., Baselga J., Piccart M., Huober J., Izquierdo M., Pena L.D.L., Hilbers F.S. Early modulation of circulating microRNAs levels in HER2-positive breast cancer patients treated with trastuzumab-based neoadjuvant therapy. Int. J. Mol. Sci. 2020;21:1386. doi: 10.3390/ijms21041386. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Garzon R., Marcucci G., Croce C.M. Targeting microRNAs in cancer: Rationale, strategies and challenges. Nat. Rev. Drug Discov. 2010;9:775–789. doi: 10.1038/nrd3179. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Bader A.G., Brown D., Winkler M. The promise of microRNA replacement therapy. Cancer Res. 2010;70:7027–7030. doi: 10.1158/0008-5472.CAN-10-2010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Miller T.E., Ghoshal K., Ramaswamy B., Roy S., Datta J., Shapiro C.L., Jacob S., Majumder S. MicroRNA-221/222 Confers Tamoxifen Resistance in Breast Cancer by Targeting p27Kip1*. J. Biol. Chem. 2008;283:29897–29903. doi: 10.1074/jbc.M804612200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Ozgur A., Tutar L., Tutar Y. Regulation of heat shock proteins by miRNAs in human breast cancer. Microrna. 2014;3:118–135. doi: 10.2174/2211536604666141216214140. [DOI] [PubMed] [Google Scholar]
  • 57.Feng Y.-H., Tsao C.-J. Emerging role of microRNA-21 in cancer. Biomed. Rep. 2016;5:395–402. doi: 10.3892/br.2016.747. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Wang H., Tan Z., Hu H., Liu H., Wu T., Zheng C., Wang X., Luo Z., Wang J., Liu S. microRNA-21 promotes breast cancer proliferation and metastasis by targeting LZTFL1. BMC Cancer. 2019;19:738. doi: 10.1186/s12885-019-5951-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Si M., Zhu S., Wu H., Lu Z., Wu F., Mo Y. miR-21-mediated tumor growth. Oncogene. 2007;26:2799–2803. doi: 10.1038/sj.onc.1210083. [DOI] [PubMed] [Google Scholar]
  • 60.Ichikawa T., Sato F., Terasawa K., Tsuchiya S., Toi M., Tsujimoto G., Shimizu K. Trastuzumab produces therapeutic actions by upregulating miR-26a and miR-30b in breast cancer cells. PLoS ONE. 2012;7:e31422. doi: 10.1371/journal.pone.0031422. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.Davey M., Ryan É., McAnena P., Boland M., Barry M., Sweeney K., Malone C., McLaughlin R., Lowery A., Kerin M. Disease recurrence and oncological outcome of patients treated surgically with curative intent for estrogen receptor positive, lymph node negative breast cancer. Surg. Oncol. 2021;37:101531. doi: 10.1016/j.suronc.2021.101531. [DOI] [PubMed] [Google Scholar]
  • 62.Davey M., Ryan É.J., Folan P., O’Halloran N., Boland M., Barry M., Sweeney K., Malone C., McLaughlin R., Kerin M. The impact of progesterone receptor negativity on oncological outcomes in oestrogen-receptor-positive breast cancer. BJS Open. 2021;5:zrab040. doi: 10.1093/bjsopen/zrab040. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Kanyılmaz G., Yavuz B.B., Aktan M., Karaağaç M., Uyar M., Fındık S. Prognostic importance of Ki-67 in breast cancer and its relationship with other prognostic factors. Eur. J. Breast Health. 2019;15:256. doi: 10.5152/ejbh.2019.4778. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64.Davey M.G., Kerin E., O’Flaherty C., Maher E., Richard V., McAnena P.F., McLaughlin R.P., Sweeney K.J., Barry M.K., Malone C.M., et al. Clinicopathological response to neoadjuvant therapies and pathological complete response as a biomarker of survival in human epidermal growth factor receptor-2 enriched breast cancer—A retrospective cohort study. Breast. 2021 doi: 10.1016/j.breast.2021.06.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Davey M., Ryan É.J., Davey M., Lowery A., Miller N., Kerin M. Clinicopathological and prognostic significance of programmed cell death ligand 1 expression in patients diagnosed with breast cancer: Meta-analysis. Br. J. Surg. 2021 doi: 10.1093/bjs/znab103. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Cai W.-L., Huang W.-D., Li B., Chen T.-R., Li Z.-X., Zhao C.-L., Li H.-Y., Wu Y.-M., Yan W.-J., Xiao J.-R. microRNA-124 inhibits bone metastasis of breast cancer by repressing Interleukin-11. Mol. Cancer. 2018;17:9. doi: 10.1186/s12943-017-0746-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Sporn J.C., Katsuta E., Yan L., Takabe K. Expression of MicroRNA-9 is associated with overall survival in breast cancer patients. J. Surg. Res. 2019;233:426–435. doi: 10.1016/j.jss.2018.08.020. [DOI] [PubMed] [Google Scholar]
  • 68.Elango R., Alsaleh K.A., Vishnubalaji R., Manikandan M., Ali A.M., El-Aziz A., Altheyab A., Al-Rikabi A., Alfayez M., Aldahmash A. MicroRNA expression profiling on paired primary and lymph node metastatic breast cancer revealed distinct microRNA profile associated with LNM. Front. Oncol. 2020;10:756. doi: 10.3389/fonc.2020.00756. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69.Liu X., Guan Y., Wang L., Niu Y. MicroRNA-10b expression in node-negative breast cancer-correlation with metastasis and angiogenesis. Oncol. Lett. 2017;14:5845–5852. doi: 10.3892/ol.2017.6914. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70.Chen X., Wang Y.-W., Zhu W.-J., Li Y., Liu L., Yin G., Gao P. A 4-microRNA signature predicts lymph node metastasis and prognosis in breast cancer. Hum. Pathol. 2018;76:122–132. doi: 10.1016/j.humpath.2018.03.010. [DOI] [PubMed] [Google Scholar]
  • 71.Okuno J., Miyake T., Sota Y., Tanei T., Kagara N., Naoi Y., Shimoda M., Shimazu K., Kim S.J., Noguchi S. Development of prediction model including microRNA expression for sentinel lymph node metastasis in ER-positive and HER2-negative breast cancer. Ann. Surg. Oncol. 2021;28:310–319. doi: 10.1245/s10434-020-08735-9. [DOI] [PubMed] [Google Scholar]
  • 72.Tokumaru Y., Asaoka M., Oshi M., Katsuta E., Yan L., Narayanan S., Sugito N., Matsuhashi N., Futamura M., Akao Y. High expression of microRNA-143 is associated with favorable tumor immune microenvironment and better survival in estrogen receptor positive breast cancer. Int. J. Mol. Sci. 2020;21:3213. doi: 10.3390/ijms21093213. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 73.Sheng Y., Hu R., Zhang Y., Luo W. MicroRNA-4317 predicts the prognosis of breast cancer and inhibits tumor cell proliferation, migration, and invasion. Clin. Exp. Med. 2020;20:417–425. doi: 10.1007/s10238-020-00625-4. [DOI] [PubMed] [Google Scholar]
  • 74.Lai J., Wang H., Pan Z., Su F. A novel six-microRNA-based model to improve prognosis prediction of breast cancer. Aging. 2019;11:649. doi: 10.18632/aging.101767. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 75.Hong H.-C., Chuang C.-H., Huang W.-C., Weng S.-L., Chen C.-H., Chang K.-H., Liao K.-W., Huang H.-D. A panel of eight microRNAs is a good predictive parameter for triple-negative breast cancer relapse. Theranostics. 2020;10:8771. doi: 10.7150/thno.46142. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 76.Cheng D., He H., Liang B. A three-microRNA signature predicts clinical outcome in breast cancer patients. Eur. Rev. Med. Pharm. Sci. 2018;22:6386–6395. doi: 10.26355/eurrev_201810_16051. [DOI] [PubMed] [Google Scholar]
  • 77.Shi W., Dong F., Jiang Y., Lu L., Wang C., Tan J., Yang W., Guo H., Ming J., Huang T. Construction of prognostic microRNA signature for human invasive breast cancer by integrated analysis. OncoTargets Ther. 2019;12:1979. doi: 10.2147/OTT.S189265. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 78.Andrade F., Nakata A., Gotoh N., Fujita A. Large miRNA survival analysis reveals a prognostic four-biomarker signature for triple negative breast cancer. Genet. Mol. Biol. 2020;43:e20180269. doi: 10.1590/1678-4685-gmb-2018-0269. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 79.Wu X., Ding M., Lin J. Three-microRNA expression signature predicts survival in triple-negative breast cancer. Oncol. Lett. 2020;19:301–308. doi: 10.3892/ol.2019.11118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 80.Tang J., Ma W., Zeng Q., Tan J., Cao K., Luo L. Identification of miRNA-based signature as a novel potential prognostic biomarker in patients with breast cancer. Dis. Markers. 2019;2019 doi: 10.1155/2019/3815952. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 81.Farina N.H., Ramsey J.E., Cuke M.E., Ahern T.P., Shirley D.J., Stein J.L., Stein G.S., Lian J.B., Wood M.E. Development of a predictive miRNA signature for breast cancer risk among high-risk women. Oncotarget. 2017;8:112170. doi: 10.18632/oncotarget.22750. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 82.Li H., Liu J., Chen J., Wang H., Yang L., Chen F., Fan S., Wang J., Shao B., Yin D. A serum microRNA signature predicts trastuzumab benefit in HER2-positive metastatic breast cancer patients. Nat. Commun. 2018;9:1614. doi: 10.1038/s41467-018-03537-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 83.Rohan T.E., Wang T., Weinmann S., Wang Y., Lin J., Ginsberg M., Loudig O. A miRNA expression signature in breast tumor tissue is associated with risk of distant metastasis. Cancer Res. 2019;79:1705–1713. doi: 10.1158/0008-5472.CAN-18-2779. [DOI] [PubMed] [Google Scholar]
  • 84.Davey M.G., Ryan É.J., Abd Elwahab S., Elliott J.A., McAnena P.F., Sweeney K.J., Malone C.M., McLaughlin R., Barry M.K., Keane M.M. Clinicopathological correlates, oncological impact, and validation of Oncotype DX™ in a European Tertiary Referral Centre. Breast J. 2021 doi: 10.1111/tbj.14217. [DOI] [PubMed] [Google Scholar]
  • 85.Cardoso F., van’t Veer L.J., Bogaerts J., Slaets L., Viale G., Delaloge S., Pierga J.-Y., Brain E., Causeret S., DeLorenzi M., et al. 70-Gene Signature as an Aid to Treatment Decisions in Early-Stage Breast Cancer. N. Engl. J. Med. 2016;375:717–729. doi: 10.1056/NEJMoa1602253. [DOI] [PubMed] [Google Scholar]
  • 86.Sparano J.A., Gray R.J., Makower D.F., Pritchard K.I., Albain K.S., Hayes D.F., Geyer C.E., Dees E.C., Goetz M.P., Olson J.A., et al. Adjuvant Chemotherapy Guided by a 21-Gene Expression Assay in Breast Cancer. N. Engl. J. Med. 2018;379:111–121. doi: 10.1056/NEJMoa1804710. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 87.Davey M.G., Ryan É.J., Boland M.R., Barry M.K., Lowery A.J., Kerin M.J. Clinical utility of the 21-gene assay in predicting response to neoadjuvant endocrine therapy in breast cancer: A systematic review and meta-analysis. Breast. 2021;58:113–120. doi: 10.1016/j.breast.2021.04.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 88.Boland M.R., Al-Maksoud A., Ryan É.J., Balasubramanian I., Geraghty J., Evoy D., McCartan D., Prichard R.S., McDermott E.W. Value of a 21-gene expression assay on core biopsy to predict neoadjuvant chemotherapy response in breast cancer: Systematic review and meta-analysis. Br. J. Surg. 2021;108:24–31. doi: 10.1093/bjs/znaa048. [DOI] [PubMed] [Google Scholar]
  • 89.Godoy P.M., Barczak A.J., DeHoff P., Srinivasan S., Etheridge A., Galas D., Das S., Erle D.J., Laurent L.C. Comparison of reproducibility, accuracy, sensitivity, and specificity of mirna quantification platforms. Cell Rep. 2019;29:4212–4222. doi: 10.1016/j.celrep.2019.11.078. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 90.Pritchard C.C., Kroh E., Wood B., Arroyo J.D., Dougherty K.J., Miyaji M.M., Tait J.F., Tewari M. Blood cell origin of circulating microRNAs: A cautionary note for cancer biomarker studies. Cancer Prev. Res. 2012;5:492–497. doi: 10.1158/1940-6207.CAPR-11-0370. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 91.Kroh E.M., Parkin R.K., Mitchell P.S., Tewari M. Analysis of circulating microRNA biomarkers in plasma and serum using quantitative reverse transcription-PCR (qRT-PCR) Methods. 2010;50:298–301. doi: 10.1016/j.ymeth.2010.01.032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 92.Kim D.-J., Linnstaedt S., Palma J., Park J.C., Ntrivalas E., Kwak-Kim J.Y., Gilman-Sachs A., Beaman K., Hastings M.L., Martin J.N. Plasma components affect accuracy of circulating cancer-related microRNA quantitation. J. Mol. Diagn. 2012;14:71–80. doi: 10.1016/j.jmoldx.2011.09.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 93.Cheng H.H., Yi H.S., Kim Y., Kroh E.M., Chien J.W., Eaton K.D., Goodman M.T., Tait J.F., Tewari M., Pritchard C.C. Plasma processing conditions substantially influence circulating microRNA biomarker levels. PLoS ONE. 2013;8:e64795. doi: 10.1371/journal.pone.0064795. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 94.McDermott A.M., Kerin M.J., Miller N. Identification and Validation of miRNAs as Endogenous Controls for RQ-PCR in Blood Specimens for Breast Cancer Studies. PLoS ONE. 2014;8:e83718. doi: 10.1371/journal.pone.0083718. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 95.Wang K., Yuan Y., Cho J.-H., McClarty S., Baxter D., Galas D.J. Comparing the MicroRNA spectrum between serum and plasma. PLoS ONE. 2012;7:e41561. doi: 10.1371/journal.pone.0041561. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 96.Segal M., Biscans A., Gilles M.-E., Anastasiadou E., De Luca R., Lim J., Khvorova A., Slack F.J. Hydrophobically modified let-7b miRNA enhances biodistribution to NSCLC and downregulates HMGA2 in vivo. Mol. Ther. Nucleic Acids. 2020;19:267–277. doi: 10.1016/j.omtn.2019.11.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 97.Segal M., Slack F.J. Challenges identifying efficacious miRNA therapeutics for cancer. Expert Opin. Drug Discov. 2020;15:987–991. doi: 10.1080/17460441.2020.1765770. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 98.Karlsen T.A., Brinchmann J.E. Liposome delivery of microRNA-145 to mesenchymal stem cells leads to immunological off-target effects mediated by RIG-I. Mol. Ther. 2013;21:1169–1181. doi: 10.1038/mt.2013.55. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 99.Li J., Liang H., Liu J., Wang Z. Poly (amidoamine)(PAMAM) dendrimer mediated delivery of drug and pDNA/siRNA for cancer therapy. Int. J. Pharm. 2018;546:215–225. doi: 10.1016/j.ijpharm.2018.05.045. [DOI] [PubMed] [Google Scholar]
  • 100.Li X., Corbett A.L., Taatizadeh E., Tasnim N., Little J.P., Garnis C., Daugaard M., Guns E., Hoorfar M., Li I.T. Challenges and opportunities in exosome research—Perspectives from biology, engineering, and cancer therapy. APL Bioeng. 2019;3:011503. doi: 10.1063/1.5087122. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 101.O’Brien K.P., Gilligan K., Khan S., Moloney B., Thompson K., Lalor P., Dockery P., Ingoldsby H., Kerin M.J., Dwyer R.M. Engineering Mesenchymal Stem Cells (MSCs) to Support Tumor-Targeted Delivery of Exosome-Encapsulated MicroRNA-379. American Association for Cancer Research (AACR); Philadelphia, PA, USA: 2017. [Google Scholar]
  • 102.Atif H., Hicks S.D. A review of microRNA biomarkers in traumatic brain injury. J. Exp. Neurosci. 2019;13 doi: 10.1177/1179069519832286. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 103.Willinger C.M., Rong J., Tanriverdi K., Courchesne P.L., Huan T., Wasserman G.A., Lin H., Dupuis J., Joehanes R., Jones M.R. MicroRNA signature of cigarette smoking and evidence for a putative causal role of microRNAs in smoking-related inflammation and target organ damage. Circ. Cardiovasc. Genet. 2017;10:e001678. doi: 10.1161/CIRCGENETICS.116.001678. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 104.Huan T., Chen G., Liu C., Bhattacharya A., Rong J., Chen B.H., Seshadri S., Tanriverdi K., Freedman J.E., Larson M.G. Age-associated micro RNA expression in human peripheral blood is associated with all-cause mortality and age-related traits. Aging Cell. 2018;17:e12687. doi: 10.1111/acel.12687. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 105.Cui C., Yang W., Shi J., Zhou Y., Yang J., Cui Q., Zhou Y. Identification and analysis of human sex-biased microRNAs. Genom. Proteom. Bioinform. 2018;16:200–211. doi: 10.1016/j.gpb.2018.03.004. [DOI] [PMC free article] [PubMed] [Google Scholar]

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