MicroRNA signatures: clinical biomarkers for the diagnosis and treatment of breast cancer

Review

MicroRNA signatures: clinical biomarkers for the diagnosis and treatment of breast cancer Cathy A. Andorfer, Brian M. Necela, E. Aubrey Thompson and Edith A. Perez Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, USA, 32224

Recognition that breast cancer is a heterogeneous disease in which each patient’s tumor has specific characteristics has led to a search for biomarkers and combinations of markers (signatures) to improve the diagnosis, prognostic classification and prediction of therapeutic benefit versus toxicity for individual tumors and patients. Many microRNAs (miRNAs) are aberrantly expressed in cancer and seem to influence tumor behavior and progression. miRNAs have great potential to evolve into effective biomarkers in the clinic because of their extreme stability and ease of detection. However, there are several major technical challenges as well as numerous discrepancies among currently reported miRNA signatures. In this review, we discuss the use of miRNA signatures for breast cancer treatment and discuss the challenges in the field. An introduction to microRNAs (miRNAs) miRNAs have emerged as a class of modulators involved in cancer that might prove to be important predictors of disease risk and progression. miRNAs are evolutionally conserved, small (18–25 nucleotides), endogenously expressed RNAs that can silence gene expression by binding the 30 untranslated regions (UTRs) of target mRNAs, repressing translation or directing the sequence-specific degradation of target mRNAs [1,2]. In addition, increasing evidence suggests that miRNAs also induce gene expression [3,4]. Computational algorithms have estimated that miRNAs could target >30% of the human genome [5]. Importantly, miRNAs can regulate more than one gene, and likewise a single gene can be regulated by multiple miRNAs. miRNAs, therefore, can ‘fine tune’ the activity of entire signaling networks to regulate diverse biological processes such as development, angiogenesis, differentiation, immune cell function, proliferation, apoptosis and wound healing. An explosion of basic research is being pursued to identify the individual genes and pathways targeted by aberrantly expressed miRNAs in cancer. However, a single miRNA might have >1000 computationally predicted targets, and one major challenge is to confirm which of these predicted targets are directly regulated by the miRNA. Yet, despite the functional complexity of miRNAs, tremendous

Corresponding author: Perez, E.A. ([email protected]).

progress is being made in linking these transcripts to key signaling factors and pathways in cancer. In this review, we discuss the potential use of miRNAs as biomarkers in breast cancer, highlighting both the theoretical strengths and technical difficulties associated with their detection and application in the clinical setting. We focus on the current needs for biomarkers in breast cancer treatment decision-making and present key findings from recent profiling studies. The aim of this review is to generate enthusiasm for the potential use of miRNAs as biomarkers and at the same time emphasize the significant discrepancies and technical difficulties that must be overcome before clinically relevant signatures will arise. miRNAs as potential biomarkers Despite the complexities of understanding how miRNAs influence tumorigenesis, aberrantly expressed miRNAs have considerable potential for use as biomarkers for the detection, diagnosis, classification and treatment of cancer. Different tissue types have unique expression levels of individual miRNAs, from as low as a few copies to a million copies per cell, and thereby have unique miRNA ‘signatures.’ Likewise, each tumor type seems to have a unique miRNA signature, and such signatures are being exploited to identify the tissue of origin of metastatic tumors and to differentiate between different cancer subtypes [6]. Moreover, miRNA expression signatures have been linked to several clinicopathological variables such as tumor stage, receptor status and patient survival. Owing to their small sizes, miRNAs are highly resistant to degradation and can be easily extracted from nearly every cell and tissue type. Indeed, miRNAs have been shown to be well preserved in archived formalin-fixed paraffin-embedded sections up to 10 years old [7], allowing the retroactive analysis of patient samples. Moreover, circulating miRNAs can easily be measured in whole blood or serum [7]. Several studies have identified cancer-specific miRNAs elevated in the circulation of cancer patients [8]. Therefore, the ability to monitor disease progression by measuring circulating miRNAs is likely to have a significant clinical impact. It is important to note that although differences in miRNA expression profiles between normal and tumor tissues, or between tumor tissue types, might reflect deregulation within cancer cells, it is also possible that these changes might reflect events occurring in surrounding

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nonepithelial stromal cells. It will be important to further develop methods to interpret whether the up- or downregulation of miRNAs is associated with changes in the tumor itself or in the surrounding tissue. To that end, several groups have been working to develop reliable and sensitive in situ methods of miRNA detection [9,10]. However, the use of in situ hybridization raises additional questions about the sensitivity and specificity of the assay and how these variables might influence the comparison of data obtained by such a protocol compared with more conventional (and less technically demanding) techniques for quantifying miRNAs in total RNA extracts. The availability of numerous miRNA isolation kits and detection platforms allows for the accurate quantification of miRNA biomarkers in both tissues and body fluids. Commercially available detection platforms rely on either PCR amplification or direct hybridization and these are routinely updated to cover the growing list of miRNAs (currently 940 human miRNAs, miRBASEv.15). Most detection platforms can be adapted to measure both precursor and mature miRNAs and customized to quantify user-specified miRNA signatures. In addition, the development of next-generation technology allows for the sequencing of individual miRNAs. This can identify posttranscriptional modifications to mature miRNAs such as an additional nucleotide incorporated at either end. Initial studies have suggested that these post-transcriptionally modified, so-called isomiRs, might be evidence of tissuespecific or even tumor-specific distribution, and could therefore serve as biomarkers [11,12] Taken together, these characteristics, including their extreme stability, ease of detection and biological relevance, indicate that miRNAs represent highly attractive putative biomarkers.

Aberrant expression of miRNAs in breast cancer To date, every type of breast tumor analyzed by miRNA profiling has shown significantly different miRNA profiles (for mature and/or precursor miRNAs) compared with normal cells from the same tissue. A review of the published large-scale miRNA profiles reveals that several miRNAs are consistently deregulated in tumors from breast cancer patients (Table 1). A comprehensive review of the function of individual miRNAs in breast cancer biology has been performed elsewhere [13]. It is important to note that these studies generally did not control for clinicopathological variables and were thereby likely to identify miRNAs that are generally associated with the transformation of breast epithelial cells. Indeed, many of these miRNAs, such as miR-21, miR-155, miR-145 and miR-31, are deregulated in multiple types of cancer, including colon, lung and liver cancers [14–17]. Most profiling studies have focused on miRNAs deregulated in the primary breast cancer tissue or breast cancer cell lines. However, because of their resistance to degradation, miRNAs seem to be stable in blood, and there is emerging interest in profiling circulating miRNAs as noninvasive surrogate markers. Circulating miRNAs have been found to be significantly elevated in the blood of cancer patients compared with healthy controls, and these levels are reflected in the primary tumors. Moreover, the removal of the primary tumor leads to the loss of elevated circulating miRNAs, suggesting that many of these elevated circulating miRNAs are ‘tumor-derived’ and cancerspecific. The current belief is that these ‘tumor-derived’ circulating miRNAs are released from the primary tumor via exosome vesicles and apoptotic bodies [18,19], although the exact mechanisms of release are still emerging [20]. To date, only a few studies have begun to profile circulating

Table 1. Commonly regulated miRNAs and their targets in breast cancera miRNA miR-21

Tumor expression level Up

Refs [33,48–50,52,59,61–65]

miR-125b

Down

[47–50,52,60]

miR-155 miR-145 miR-210 miR-29c miR-100 miR-10b let-7a-2 miR-205 miR-125b-2 miR-196a miR-497 miR-213 miR-31 miR-143 miR-191 miR-203 miR-29b miR-93 miR-130b

Up Down Up Up Down Down Down Down Down Up Down Up Down/up Down Up Up Up Up Down/up

[47–49,52,59] [33,49,50,52,59–61] [48–50,52] [50,52,59] [50,52,60] [49,50,60] [33,49,52] [33,47,52,66] [49–52] [48–50] [50,59,61] [17,48,49] [17,52,59b] [49,50] [48,49] [49,50] [52,59] [48,50] [47b,50]

a

Validated targets BCL2, TPM1, PDCD4, PTEN, MASPIN, RHOB, MMP3 BAK, HER2, CRAF, MUC1, ERA, RTKN FOXO3A, SOCS1, RHOA MUC1, ERA, RTKN MNT, RAD52

Pathways Apoptosis, invasion, metastasis

Refs [62–65]

Proliferation, apoptosis, migration

[51,67,68]

Proliferation, TGF-b signaling Proliferation, apoptosis, invasion Hypoxia

[69–71] [72–74] [75,76]

TIAM, HOXD10

Migration, invasion, metastasis

[77–79]

HER3, VEGFA, EMT

Proliferation, invasion

[49,66,80]

ANXA1

Proliferation, apoptosis

[81]

ITGA5, RDX, RHOA

Metastasis

[17,82]

This table represents miRNAs whose expressions are significantly regulated in clinical samples (tumors of human patients). downregulated in this study.

b

314

Review miRNAs in blood (serum or plasma) [21–24]. For example, a recent study investigating circulating miRNAs from preoperative cancer patients (breast, prostate, colon, renal and melanoma) compared with healthy age- and sex-matched controls found elevated levels of let-7a, miR-10b and miR-155 in the majority of cancer patients [8]. Significantly, elevated levels of circulating miR-195 were breast cancer-specific, and could be used to differentiate breast cancer from other cancers [8]. This is an exciting proof-of-principle that could have an impact on our ability to monitor disease progression in a noninvasive way; there is considerable enthusiasm for the concept that circulating miRNAs might facilitate the early detection of metastasis. Although circulating miRNAs have been found to be elevated in breast cancer patients, common breast cancer-specific miRNAs have yet to emerge across studies, and it is too soon to interpret the significance of individual circulating miRNAs. The analysis of circulating miRNAs is at an early stage of development, and there is a pressing need for additional profiling studies to identify and validate circulating miRNA biomarkers in breast cancer. miRNA profiling to improve diagnosis and therapy Commonly deregulated miRNAs Despite the identification of aberrant expression in breast cancer, there are significant discrepancies among reported miRNA signatures (Table 1). Given the intrinsic heterogeneity present in breast cancer tumors, variability in miRNA profiles can arise from clinicopathological variables such as HER2, estrogen receptor (ER) or progesterone receptor (PR) status, tumor stage, vascular invasion or proliferation indexes. A major focus will be developing miRNA biomarker signatures that accurately reflect these variables. In this respect, we discuss the potential impact of miRNA signatures as biomarkers of intrinsic molecular phenotypes and of clinicopathological characteristics for the diagnosis and treatment of breast cancer. miRNA signatures to predict tumor subtypes At the simplest level, breast cancer comprises three general molecular subtypes that can be detected by routine histological/pathological means: hormone receptor-positive (ER/PR+), human epidermal growth factor receptor type 2 enriched (HER2+) and triple negative (ER, PR, HER2). ER/PR+ tumors account for nearly 60–70% of diagnosed breast cancers, with the remaining 30–40% more or less being evenly split between HER2+ breast cancers and triple-negative breast cancers [25]. Genomic mRNA profiling using microarrays to identify the tumorspecific patterns of gene expression has further subdivided breast tumors into four so-called intrinsic subtypes: luminal A (ER+ and low grade), luminal B (ER+ and high grade), HER2+ and basal-like (primarily triple negative) [26]. However, it is probable that these subtypes represent a high-level view of the heterogeneity within tumor samples, and there is consensus among clinicians and tumor biologists that additional heterogeneity exists within breast tumors. This is linked to the natural history of individual tumors and is likely to provide important information that will guide both prognosis and prediction. miRNA signatures might provide an additional level of granularity to

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facilitate the accurate identification of a patient’s tumor subtype and guide treatment decisions. There are currently several complications in the accurate diagnosis of tumor subtypes that might be addressed by the development of miRNA signatures. Current recommendations from the American Society of Clinical Oncology/College of American Pathologists for HER2 testing suggest using immunohistochemistry to measure the amount of HER2 protein expressed in cancer cells and a FISH (fluorescence in situ hybridization) assay to measure either the total number of copies of the HER2 in a tumor cell or the ratio of HER2 to chromosome 17 copies. Two prospective meta-analyses of randomized clinical trials investigating the adjuvant use of trastuzumab found that 20% of HER2 assays incorrectly classified tumors when reevaluated in a high-volume central testing laboratory [27,28]. Furthermore, tests for hormone receptors can be wrong at least 10% of the time [29]. .Clearly, owing to such high rates of inaccuracy, the identification of subtypespecific miRNA signatures (detected in a tumor specimen or from a patient’s blood) would be of significant value to at least complement current methods of classification. Only a few studies have attempted to profile miRNA expression in breast tumors as a function of breast cancer subtype, and none of these studies has provided a comprehensive attempt to profile all known miRNAs in any specific breast cancer subtype. For example, 309 miRNAs (out of a total of over 900 known miRNA species) in 93 breast tumors of known molecular tumor subtypes were quantified [30]. miRNAs were differentially expressed according to tumor subtype (luminal A, luminal B, basal-like, normal-like and HER+), although miRNA signature did not predict tumor status. However, the miRNA signature could correctly classify basal versus luminal subtypes in an independent, albeit small test set, suggesting that the expression patterns of miRNA differ among tumor subtypes and highlighting the possibility of defining a predictive signature for hormone receptor status. A recent analysis of 453 known miRNAs in 29 early-stage breast cancer tumors identified predictive signatures corresponding to ER (miR-342, miR-299, miR217, miR-190, miR-135b and miR-218), PR (miR-520 g, miR-377, miR-527-518a, and miR-520f-520c) and HER2 (miR-520d, miR-181c, miR-302c, miR-376b, and miR30e) status [31]. These signatures correctly discriminated among cases with 100% accuracy compared with immunohistochemistry results. However, although this model showed high accuracy for the tumors analyzed, the dataset was small and the tumors were homogeneous with respect to tumor size and disease severity. Another study profiled 208 miRNAs in 20 breast cancer tumors to identify predictive signatures of ER (miR-30d and -30e), PR (miR-106b, miR-19a, miR-29c, and miR-30a-5p), HER2+ (let-7f, let-7 g, miR-107, miR-10b, miR-126, miR154, and miR-159) and ER/PR (miR-142-5p, miR-200a, miR-205, and miR-25) [32]. Remarkably, there was no overlap among the miRNA signatures from these two studies. This discrepancy could result, in part, because many of the miRNAs identified in each study were not examined in the other [31,32]. The miRNAs of the PR signature and two of the HER2 miRNAs (miR-520d and miR-376b) were not 315

Review analyzed in the latter study. By contrast, all the miRNAs that were associated with ER+ status were analyzed in both studies, yet no common miRNAs were found. Thus, discrepancies in the signatures of the two studies could arise from other variables such as the clinicopathological parameters of the tumors (e.g. tumor size, grade), the use of different detection platforms (e.g. RT-PCR, next-generation sequencing, version of microarray panel) or pre-analytical variables (e.g. time to collection, method of processing, length of fixation). In another study, miRNA expression patterns were profiled between normal and tumor breast tissue [33]. Although miRNAs were differentially expressed between these two types of tissue, their expression patterns did not correlate exclusively with ER or HER2 status. A particular strength of this study is that the authors were able to use in situ hybridization directly in breast tissue and thereby could examine the differential expressions of miRNAs in different cell types within a single tumor. This adds an extra layer of sensitivity to interpret whether the up- or downregulation of miRNAs is associated with changes in the tumor itself or in the surrounding stromal tissue that is likely to be included in typical tumor samples. Taken together these studies illustrate that the development of miRNA signatures to predict tumor subtype is in the early stages of development. The overall lack of profiling studies and the apparent discrepancies among reported signatures highlight the need for (i) the validation of existing signatures in larger datasets, (ii) the validation of tumor datasets with heterogeneous clinicopathological variables and (iii) validation with alternative platforms. In this respect, it could be important to capture expression data from all or most of the known 940 human miRNAs of miRBASEv.15 (http://www.mirbase.org). Sequence-based profiling might be particularly advantageous in this regard because this approach is not biased by annotation and has the potential to identify novel miRNAs biomarkers, including species not currently annotated and post-transcriptionally modified isomiRs. In addition, and perhaps more important than improving breast cancer subtype identification, miRNA signatures could potentially help identify specific subgroups of patients within different tumors that are more or less likely to respond to a particular therapy. We will elaborate on this in the following sections with respect to identifying individual patients’ responses to tamoxifen, trastuzumab and chemotherapy. Tamoxifen resistance/hormone receptor status Estrogen is a well-established growth factor for approximately 60–70% of breast cancers [34]. Successful therapies have been developed to reduce or eliminate circulating estrogen or to block the interaction of ER with genomic targets. The selective ER antagonist tamoxifen and aromatase inhibitors are recommended as adjuvant endocrine therapy agents for the treatment of hormone receptorpositive early breast cancer (reviewed in [35]). In view of the moderate efficacy and toxicity associated with these agents, several groups have started to evaluate miRNAs in ER+ breast cancers. 316

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The majority of miRNA expression data in tamoxifenresistant cells comes from studies on cell lines. However, Rodriguez-Gonzalez and colleagues [36] validated three miRNAs (miR-30a-3p, miR-30c, and miR-182) that were originally identified [37] for their abilities to predict the clinical benefit of tamoxifen in advanced breast cancer. The three miRNAs, when used together, were significantly associated with the benefit of tamoxifen and longer progression-free survival. Of these three miRNAs, only miR30c independently predicted clinical benefits in advanced breast cancer. These studies suggest that miRNAs could be useful predictors of hormone responsiveness; however, the correlations described thus far are probably not clinically useful at this time. Moreover, a more thorough understanding of the biological roles of any of the miRNAs in ER+ endocrine therapy resistant tumors has not yet developed. Such an understanding will probably be required before miRNA expression profiles can be used in clinical decision-making. Trastuzumab/HER2 status The overexpression of HER2 through either gene amplification or transcriptional deregulation [25,38] confers a worse prognosis, including a relative resistance to certain chemotherapeutic and hormonal agents and an increased propensity for metastasis to the brain [39]. Current therapeutic strategies aim to silence overactive HER2 with targeted compounds such as trastuzumab, a recombinant humanized monoclonal antibody against HER2 protein that blocks the HER2-mediated activation of intracellular kinases and effectors [40]. The addition of trastuzumab to systemic adjuvant chemotherapy reduces disease recurrence by 52% and risk of death by 33% compared with chemotherapy alone [41]. Moreover, concurrent trastuzumab with taxane leads to a 25% reduction in the risk of an event (disease recurrence or death) compared with administering trastuzumab in a sequential fashion after taxane. Although the combination of chemotherapy and trastuzumab prolongs survival in the adjuvant and metastatic settings, the majority of women with HER2+ metastatic disease will develop resistance to trastuzumab within one year of treatment initiation. Moreover, approximately 15–25% of women diagnosed with early HER2+ disease have trastuzumab-resistant tumors [42]. Thus, there is a crucial need to identify the mechanisms of resistance to trastuzumab and to use this information to identify patients who would benefit from anti-HER2 therapy. The identification of miRNA biomarker signatures that predict patient risk and disease outcome and tolerability to trastuzumab therapy would greatly improve the personalized management of HER2+ disease (reviewed in [43]). Unfortunately, no published studies have successfully identified a prognostic miRNA signature for trastuzumab response or toxicity. Studies in cell culture and murine models addressing the biological connection between miRNAs and the HER family of receptor tyrosine kinases are underway. For example, miR-21 can be upregulated by HER2 signaling via the mitogen-activated protein kinase pathway in breast cancer cells and increase cell invasion [44]. Additionally, miR-21 can repress the expression of the tumor suppressor PTEN [44,45], which can affect

Review sensitivity to trastuzumab [46]. However, the role of miRNAs in determining the response to HER2-targeted therapies and their potential utility as biomarkers remain an open question. In addition to aiding prognostic predictions to trastuzumab response, miRNAs could also be exploited to directly target HER2 overexpression. Based on MicroCosm and TargetScan target databases, approximately 79 unique miRNAs are predicted to target the 30 UTR of HER2. The downregulation of miRNAs that target HER2 might account for a subset of HER2-enriched tumors, whereas the therapeutic delivery of such miRNAs could hold great promise in treating HER2+ tumors. For example, miR125b targets HER2 and seems consistently downregulated in breast cancer [32,47–52]. The enforced overexpression of miR-125b in breast cancer cell lines suppresses HER2 and ERBB3 at the transcript and protein levels, resulting in impaired anchorage-dependent growth, migration and invasion capacities [51]. Similarly, miR-331-3p is downregulated in prostate cancer, and the forced expression of miR331-3p blocks HER2 expression and downstream signaling [53]. Other miRNAs such as miR-548d-3p and miR-559 also directly regulate HER2 expression [54]; however, their impacts on cancer have not been addressed. As such, the profiling and therapeutic targeting of miRNAs linked to HER2 expression remains a relatively unexplored avenue for the treatment of breast cancer. Chemotherapy response, multidrug resistance (MDR) and miRNAs Although chemotherapy is the primary method available to treat patients with advanced or aggressive disease, tumor cells frequently develop resistance to chemotherapeutic agents and often develop MDR. Drug resistance is widely accepted as the main cause of treatment failure. Therefore, additional biomarkers are needed to identify patients with sensitivity to particular chemotherapeutic agents. Recent work has shown a possible link between miRNA deregulation and drug resistance. The deletion of chromosome 11q, a region containing the gene for miR-125b, can predict benefit from anthracyclinebased chemotherapy in node-negative breast cancer patients [55]. In breast cancer cell studies, miR-451 and miR-27 have both been implicated in the development of resistance to doxorubicin (Dox) [56,57]. The development of MDR is also thought to result from the increased expression of ATP-binding cassette (ABC) transporters. The ABC transporter MRP1 is regulated by miR-326 and modulates breast cancer cell sensitivity to several chemotherapeutic agents (Dox and VP-16). Of particular note was the finding of decreased miR-326 expression in a panel of advanced breast cancer tissues [58]. miRNAs that affect drug sensitivity, therefore, represent an important and potentially fruitful area of further investigation, both in terms of the clinical management of breast cancer patients and in understanding the mechanisms that contribute to drug resistance. Concluding remarks The ultimate goal for clinicians is to tailor treatment to the individual patient, balancing relative benefit with relative

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risk to improve the personalized management of breast cancer. Here, we have highlighted several areas relevant to the diagnosis and treatment of breast cancer patients in which individual miRNAs and miRNA signatures could be useful. There is much more work to do, including the validation of particular miRNA candidates and larger prospective studies in breast cancer to better define predictive signatures. The ease of detection and stability of miRNAs make them uniquely suited to monitoring the progress of patients and their responses to treatment. Ultimately, it could be possible to develop profiles that define a potential relation among circulating miRNAs, disease status, intrinsic subtype and HER2+ status, response to therapy and risk of metastasis. Despite the ease of detection of miRNAs in clinical samples, several major technical challenges remain. The first of these is purely analytical and has to do with the extent to which different pre-analytical and analytical variables affect the interpretation of miRNA profiling data. In this regard, there is reason to suspect that some of numerous discrepancies among reported miRNA signatures arise from analytical rather than biological variability. Studies have not analyzed large numbers of samples across different platforms, so it is difficult to determine to what degree the platform influences the detected expression profiles. Second, expression profiling has largely been limited to relatively small tumor datasets with homogeneous clinicopathological characteristics, and none of these studies has interrogated more than a subset of the known miRNAs. The most daunting challenge remaining is deducing miRNA function. The clinical application of miRNA signatures will probably require that we understand not only differences in expression but also the functional consequences of those differences. Indeed, understanding miRNA function within the context of disease is the greatest challenge limiting our ability to develop miRNAs as either diagnostic markers or therapeutic targets. Acknowledgments The authors would like to acknowledge the Breast Cancer Research Foundation and the Donna Foundation for their financial support.

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