Advances in Anatomic Pathology:
Modern Classification of Breast Cancer: Should we Stick With Morphology or Convert to Molecular Profile Characteristics
Rakha, Emad A. FRCPath, MD*,†; Ellis, Ian O. FRCPath, MD*,†
*Department of Histopathology, Nottingham University Hospitals NHS Trust
†University of Nottingham, Nottingham, UK
Disclosures: The author(s) have no conflicts of interest or funding to disclose.
Reprints: Emad Rakha, FRCPath, MD, Department of Histopathology, Nottingham University Hospitals NHS Trust, Nottingham City Hospital Campus, Hucknall Road, Nottingham, NG5 1PB, UK (e-mail: email@example.com).
Breast cancer represents a heterogeneous group of tumors with varied morphologic and biological features, behavior, and response to therapy. The present routine clinical management of breast cancer relies on the availability of robust prognostic and predictive factors to support decision making. Breast cancer patients are stratified into risk groups based on a combination of classical time-dependent prognostic variables (staging) and biological prognostic and predictive variables. Staging variables include tumor size, lymph node stage, and extent of tumor spread. Classical biological variables include morphologic variables such as tumor grade and molecular markers such as hormone receptor and human epidermal growth factor receptor 2 status. Although individual molecular markers were introduced in the field of breast cancer management many years ago, the concept of molecular classification was raised after the introduction of global gene expression profiling and the identification of multigene classifiers. Although there is no doubt that gene expression profiling technology has revolutionized the field of breast cancer research and have been widely expected to improve breast cancer prognostication, the unprecedented speed of progress and publicity associated with the introduction of these commercially-based multigene classifiers should not lead us to expect this technology to replace the classical classification systems. These multigene classifiers have the potential to complement traditional methods through provision of additional biological prognostic and predictive information in presently indeterminate risk groups. Here we present updated information on the present clinical value of classical clinicopathologic factors, molecular taxonomy, and multigene classifiers in routine patients management and provide some critical views and practical expectations.
Breast cancer (BC) represents a heterogeneous group of tumors with varied morphologic and biological features, behavior, and response to therapy. Treatment of BC is based on local control (ie, surgery) with or without systemic therapy. Systemic therapy of BC includes hormonal therapy, cytotoxic chemotherapy, immunotherapy, and targeted therapy such as Herceptin for human epidermal growth factor receptor 2 (HER2)-positive tumors. These medications are used in the neoadjuvant, adjuvant, and metastatic settings. In general, systemic therapies have been shown to be beneficial or to have a direct effect in approximately 90% of primary BC and 50% of metastatic cases; however, overtime innate or acquired resistance develops and a proportion of those tumors initially showing evidence of response will progress.1–3 Despite survival advantages achieved using systemic therapy in many women with early-stage BC; there are significant toxicities, quality of life-related side effects, and costs associated with such therapy. The variety of available treatments for BC impacts on present routine clinical management, which increasingly relies on the availability of robust well-validated clinical and pathologic prognostic and predictive factors to support treatment decision making. To ensure the highest chance of benefit and the least harm to the patient, there is an increasing need for identification, refinement, and validation of prognostic and predictive factors in BC management.
A prognostic factor is defined as any patient or tumor characteristic that is predictive of the patient's tumors natural history unrelated to systemic therapy, whereas a predictive factor is defined as a specific patient or tumor characteristics that correlate with response or lack of response to a specific treatment. An overlap between prognostic and predictive factors exists and a proportion of them exhibit both characteristics although 1 may predominate. Prognostic factors in BC include time-dependent prognostic variables and biological prognostic variables in addition to patient-related variables such as age and menopausal status. Time-dependent prognostic variables include tumor size, lymph node (LN) stage, and extent of distant tumor spread (tumor stage/morphologic features). These variables constitute all the 3 components of the American Joint Committee on Cancer tumor, node and metastasis (TNM) staging system,4 and the LN stage and tumor size are one of the main components of other prognostic algorithms (eg, Adjuvant Online5), guidelines (eg, St. Gallen guidelines6), and indices (eg, Nottingham Prognostic Index7) presently used to determine the likelihood of tumor behavior and guide the use of systemic therapy for early-stage BC. Biological prognostic variables are primary tumor biological characteristics that determine tumor behavior and response to therapy. Biological variables can be assessed using morphologic surrogates such as tumor differentiation (eg, tumor grade and histologic type), proliferation status, growth rate, and molecular parameters such as assessment of gene/protein status individually or in consort (eg, biomarker expression and molecular profiling at the level of DNA, RNA, or protein). For a biological marker to be of value in a clinical setting, its assay results must reflect the associated biological process though this association does not necessarily imply clinical utility. If assessment of a biological marker does not lead to a decision in clinical practice that results in a more favorable clinical outcome such as survival, quality of life, and/or cost of care, then its use in routine practice is discouraged.8 However, for a research purpose, correlations with biological end points are still important, as these correlations might be valuable if therapeutic advances for the disease are achieved.
There is a strong relationship between morphologic and molecular features and between biological variables and tumor stage; biologically aggressive tumors are more likely to present at an advance stage and the majority of advanced tumors show poor biological prognostic features. Biologically indolent tumors are likely to be slowly growing and to be detected at an earlier stage. The relationship between time and tumor stage is, in fact, more obvious among tumors of similar biological characteristics. Tumor stage, and not biological characteristics, is the fundamental principal of BC-screening programs, which aim for early detection of tumors at an early stage regardless of their biological features. In early/operable BC, knowledge about tumor stage provides important prognostic information and indicates the likelihood of recurrences or death from the disease; patients with larger primary tumors or LN-positive tumors are more likely to develop recurrence or die of their disease than patients with smaller tumors or with LN-negative tumors. Despite the lack of direct predictive value, tumor stage is conventionally used to guide the use of systemic therapy by reflecting the extent of tumor burden and tumor spread and the associated prognostic information in the form of risk of tumor recurrence. On the other hand, knowledge about biological features of a given BC provides information on the inherent nature and potential behavior of that tumor and are reflected in the outcome characteristics such as the time to recurrence; patients with biologically aggressive tumors either develop recurrence early after diagnosis or show long-term evidence of cure from their disease. On the other hand, patients with indolent tumors are at risk of recurrences over a long period of time.9–12 Therefore, knowledge about both tumor stage and biological variables have to be considered in combination during planning treatment of BC. Although advanced stage is an indication for systemic therapy, in early-stage disease the therapy is mainly determined based on biological factors. In addition, although tumor stage is an indication of effective proportionally aggressive therapy, knowledge about biological tumor characteristics is needed for determining the nature and type of systemic therapy. Cancer staging can be performed using clinical assessment (clinical stage) and pathologic assessment (pathologic stage) at the time of diagnosis or after therapy or even recurrence, and patients with similar prognosis are grouped into anatomic stage/prognostic groups (stage groups). Tumor biological features are best assessed by pathologic/molecular examination of tumor tissue and stratified according to the prognostic and/or predictive value of the biological features assessed. However, it is also important to realize that assessment of biological features may not be as straightforward as assessment of tumor stage. It often suffers from inherited subjectivity, may be influenced by processing and fixation of tissue, and assessment may be of limited value in small size tumors. It is not always possible to link biological features of the primary tumor to BC metastasis and disease-related deaths in cases of development of intervening new primary or inbreast recurrences with different biological features.
In routine practice, a small proportion of BC patients present with locally advance or metastatic disease, whereas the majority (approximately 80% to 90%) of present at early/operable stages; and with the use of population-based screening programs, there is a significant shift to early-stage disease and smaller size LN-negative tumors. This has resulted in the increasing interest in studying biological prognostic and predictive variables. Special attention is therefore now being paid to molecular biological factors and to a lesser degree to the validation of classical clinicopathologic morphologic features to evaluate their joint contribution in multivariate prognostic indices.
Traditional BC classifiers include well-established clinicopathologic and molecular prognostic and predictive variables that have been validated in several independent studies and proven to be useful in clinical patient management4–7,11,13–24 and included in BC routine synoptic reports.25 They can be assessed in routine practice by histopathologic examination of breast carcinoma specimens based on published guidelines and defined protocols such as LN status, tumor size, estrogen receptor (ER), progesterone receptor (PR), and HER2 status.20,23,26,27 However, there is a perception that the traditional factors presently available are insufficient to reflect the whole clinical and genetic heterogeneity of BC, and less than perfectly adapted to each patient particularly with the increasing range of treatment options. It has been estimated for instance that all these traditional clinicopathologic and molecular factors, which presently form the basis for determining adjuvant therapy, assign these patients into risk groups at an approximate absolute specificity level of only 10% to achieve an acceptable degree of sensitivity.28 Therefore, major efforts are now aimed at defining more molecular prognostic and predictive factors that aim to improve patients risk stratification and targeting of treatment to those who will truly benefit, thereby avoiding iatrogenic morbidity in those who will not. Recent advances in human genome research and high-throughput molecular technologies have begun to tackle the molecular complexity of BC and have contributed to the realization that the biologic heterogeneity of BC has implications for treatment. Genome-wide profiling of chromosomal changes and rapid screening of genes for mutations/single nucleotide polymorphisms (SNPs) and methylation can be performed using high-resolution SNP arrays (SNP chips),29 array comparative genomic hybridization,30 multiplex polymerase chain reaction (PCR), and massively parallel sequencing (Next-generation sequencing).31 Transcriptome and proteome profiling techniques include differential display,32 serial analysis of gene expression,33 and gene expression microarray (Gene expression profiling; GEP),34 which is presently the most high profile or popular method. These molecular techniques hold promise for improving diagnosis, for the prediction of recurrence, and in aiding selection of therapies for individual patients.
Gene expression is the technical term to describe how a particular gene is active, or how many times it is expressed or transcribed, to produce the protein it encodes. This activity is measured by counting the number of mRNA molecules in a given cell type or tissue though protein, and not the RNA, is the functional product of genes. GEP has mainly been performed to: (i) identify specific molecular classes of BC (class discovery; molecular taxonomy) that have biological and clinical relevance, which are unidentifiable by conventional means.35–37 (ii) identify specific molecular profile “gene signatures” that can predict tumor behavior38–41 and/or response to therapy42–46 (class prediction). (iii) comparison between different “predefined” classes of BC (class comparison) that aims to determine whether the expression profiles are different between these classes and, if so, to identify the differentially expressed genes.47–55 Although individual molecular markers such as ER, PR, and HER2 were introduced in the field of BC management many years ago, the concept of molecular classification was raised after the introduction of global GEP technology and the realization that several genes can be used in combination to identify distinct subclass. Over the last decade, the field of BC research was dominated by the concept of molecular taxonomy with the recognition of distinct molecular classes and the demonstration of the prognostic and predictive value of multigene classifiers (gene signatures); with the development of several multigene classifiers, some claimed it to be the predictor of relapse more accurately than classical morphologic features. At earlier stages, this technology was perceived as a future replacement to histopathologic assessment and competitor of histopathogists, but with time the expectation declined to more realistic grounds and it was considered as more accurate or objective replacement of morphologic features. More recently, it was realized that this technology should be considered at best as complementary to the present classical classification systems. Here we present updated information on the present clinical value of classical clinicopathologic factors, molecular taxonomy, and multigene classifiers in routine patients management and provide some critical views and practical expectations.
TRADITIONAL BREAST CANCER MORPHOLOGIC CLASSIFIERS
The presently used traditional prognostic factors for early-stage BC in routine practice includes TNM staging information and histologic grade. Other variables which were included in most BC synoptic reports but not necessarily used in systemic therapy decision making, include tumor histologic type, lymphovascular channel invasion, tumor focality, and presence and features of associated in situ disease in addition to margin status, completeness of excision, patients' age, family history, and menopausal status.11,23,25,56,57
Histologically confirmed locoregional LN status has repeatedly been shown to be the single most important prognostic factor in early-stage/operable BC; 15% to 30% of node-negative patients will develop recurrence within 10 years, compared with approximately 70% of patients with axillary nodal involvement.58–63 Prognosis is also related to the absolute number of positive nodes as determined by histologic examination and level of locoregional LNs involved; the greater the number of nodes involved the poorer the patient survival. Similarly, involvement of nodes in the higher levels of the axilla, and specifically the apex, carry a worse prognosis as does involvement of the internal mammary nodes.63 A further refinement of LN staging may be provided by the size of the metastatic deposits63–65 and the ratio of positive nodes to the total number of harvested nodes.18 In symptomatic BC, approximately one third (range, 30% to 40%) of operable BC patients present with positive nodes including 7% to 15% with >3 positive nodes.17 The frequency of node positivity declines in patients presenting through established breast mammographic screening programs to levels <20%.
Tumor size is one of the most powerful predictors of tumor behavior in BC.66–68 Tumor size is directly related to the frequency of nodal metastases. Patients with tumors of <1.0 cm in size show node positivity in 10% to 20%, at a size of 2.0 cm 40% of patients are nodes positive which reaches 50% at a size of >2.0 cm.17 Tumors <1.0 cm in size have a 10-year disease-free survival rate of approximately 90%, which declines to 75% for tumors 1 to 2 cm and to 60% for tumors 2 to 5 cm.11,67,69–71 Tumors >5 cm in size may be an indication for systemic therapy with or without local control. Precise assessment of tumor size is necessary to properly stratify patients, particularly as screening mammography has resulted in a steadily increasing proportion of pT1 cancers. For correlation with prognosis, the size of tumors should only be assessed on pathologic specimens, as clinical measurement is notoriously inaccurate.72 Clinical assessment of tumor size supported by an ultrasonic measurement may be performed for preoperative therapeutic planning purposes.
Invasive breast carcinomas are presently subdivided morphologically according to their growth patterns and degree of differentiation, which reflects how closely they resemble normal breast epithelial cells. This is achieved by assessing histologic type and histologic grade, respectively. Assessment of tumor differentiation has qualitative differences when compared with stage variables through its role as an intrinsic biological prognostic factor rather than a time-dependent factor. In addition, it provides important prognostic and predictive information in tumors of similar staging categories.
Histologic tumor grade is a classification method based on the degree of differentiation of the tumor tissue and can be applied to all cases. In BC, it refers to the semiquantitative evaluation of morphologic characteristics and is a relatively simple and low-cost method, requiring only adequate tissue fixation and high-quality haematoxylin-eosin (H&E)-stained tumor tissue sections to be assessed by an appropriately trained pathologist using a standard protocol. Histologic grading as measured by the Nottingham Grading System (NGS) is based on evaluation of 3 important biology-dependent morphologic features: (i) degree of tubule or gland formation, (ii) nuclear pleomorphism, and. (iii) mitotic count.11,73–75 Histologic grade represents the morphologic assessment of tumor biological characteristics and has been shown to be able to generate important information related to the clinical behavior of BC. The clinical and biological relevance of NGS has further been supported by genome-wide microarray-based expression profiling studies, which provided evidence that the biological features captured by histologic grade are important in determining tumor behavior.76,77 The independent prognostic value of NGS has been validated in multiple independent studies.11,73,75,78,79 Although in early-stage BC, NGS has prognostic value that is equivalent to that of LN status7,11,80 and greater than that of tumor size,7,11,57,81 its prognostic value is more important in the subgroups of BC where adjuvant chemotherapy has to be determined such as in patients with LN-negative ER-positive/HER2-negative or in patients with low-volume LN metastatic disease (pN1), where the decision on use of chemotherapy cannot be determined on risk associated with more advanced tumor stage.75,82,83 In addition to patients outcome, NGS is associated with other clinicopathologic prognostic variables such as LN stage, tumor size, vascular invasion (VI),11,84–86 (Fig. 1) and expression of biomarkers of prognostic and predictive value such as hormone receptor (HR), HER2, p53, basal markers and P-cadherin, and prognostic gene signatures.88,89
Tumor proliferative activity represents one of the most thoroughly investigated cellular functions in BC for its association with tumor behavior.90 Assessment of proliferation rates has been shown to provide useful information on prognosis and aggressiveness of individual cancers and can potentially be used to guide treatment protocols in clinical practice. Recently, a meta-analysis of publicly available BC gene expression signatures have identified proliferation as key biological driver in all 9 prognostic signatures included in the study.91 Various techniques have been developed to quantify proliferation rates including morphologic (ie, mitotic count estimates) and molecular (ie, measurement of DNA synthesis and flow-cytometry) parameters.11,87,90,92 Other molecular techniques include detection of antigens closely associated with proliferation using immunohistochemistry (IHC). Although most studies of different proliferation assays displayed significant agreement in outcome predictions for individual patients, there is no consensus on the best proliferation assay.93 Mitotic index, defined as the number of mitotic figures in a given area of tumor assess on routine H&E sections, is an accurate means of estimating tumor cell proliferation and represents an integral part of the NGS. High mitotic rates have been correlated with poor clinical outcome.73,94,95
Tumor type comprises a wide range of histologic patterns that are recognized in invasive carcinoma of the breast. The latest World Health Organization classification recognizes the existence of 17 special histologic types of BC, which together account for up to 25% of all invasive cancers.96 Although the tumor type provides useful prognostic information, the majority (60% to 75%) of BC have no special type (NST) characteristics (ie, invasive ductal carcinoma of NST); those special types which show distinct prognostic significance are relatively uncommon. As a consequence, the role of histologic typing in clinical management decision making is limited.97,98 However, it well documented that some special tumor types may indicate the behavior of BC and are associated with distinct prognosis independent of stage. Pure tubular, cribriform, secretory, invasive papillary and low-grade mucinous, adenoid cystic and adenosquamous carcinomas are associated with excellent prognosis even if they are associated with LN positivity, whereas inflammatory carcinomas and a high proportion of high-grade ductal NST, invasive micropapillary, and pleomorphic lobular carcinomas are associated with dismal outcome.13,99,100 In addition, histologic typing of BC adds to our understanding of the biology of BC. For example, infiltrating lobular, tubular, cribriform carcinomas show ER expression more frequently than ductal NST carcinomas, and lobular carcinomas also have a different pattern of metastatic spread with a predilection for unusual sites such as the retroperitoneum and serosal surfaces.9
Other Morphologic Variables
Although the prognostic value of the estimation of lymphovascular invasion in BC remains disputed and some authors failed to find significant correlation with clinical outcome,101 several independent studies have shown that VI predicts for both recurrence102–105 and long-term survival.103,105–107 VI has also been shown to be a predictor of axillary LN metastasis103,105,108 and early recurrence in LN-negative patients.105,109–111 It has been proposed that VI could be used to identify a subgroup of axillary node-negative patients with an unfavorable prognosis that are likely to benefit from adjuvant chemotherapy.104,105 In the Nottingham series, we found that the presence of VI as assessed in routine practice on H&E sections in the node-negative patients' cohort has a prognostic significance regarding both development of recurrence and survival, which is equivalent (not statistically different) to that of patients with 1 or 2 positive LNs (unpublished observation). The presence of VI has been added to the St. Gallen criteria for the selection of adjuvant systemic therapy in operable BC.112 Moreover, the presence of VI is an important predictor of local recurrence in breast conservation-treated patients and for use of radiotherapy.113 However, it is important to mention that there are inherited difficulties with assessing VI in routine H&E sections mainly related to the identification of VI and the distinction of true vessels from artefactual soft tissue spaces, and these problems are reflected in the wide variation in the frequency of VI reported in the literature (20% to 54%). IHC detection of VI may be an alternative and more objective way of assessing VI; however, its application in routine practice remains a matter of debate.107
A number of other morphologic features of breast carcinoma that have been proposed as prognostic factors, but are of relatively less importance can be assessed by traditional histopathologic methods including angiogenesis, tumor necrosis, tumor-associated inflammation, and presence and extent of ductal carcinoma in situ associated with invasive carcinomas. Traditional histopathologic assessment of tumors also includes margin status and completeness of excision and tumor focality, which are important factors for guiding local control of BC and determine the need for further surgery or local radiotherapy. These latter factors become more obvious with wide use of wide local excision and increased use of oncoplastic surgery for BC, particularly with screen-detected early-stage tumors.
TRADITIONAL MOLECULAR CLASSIFIERS
Traditional molecular predictive and prognostic factors for early-stage BC include HR status and HER2 status, which are essential part of the diagnostic workup of all BC patients and they are routinely determined using a standardized technique and well-defined published guidelines.20,23,25–27 It is presently recognized that the main consideration for treatment decision is endocrine responsiveness. Adjuvant endocrine therapy accounts for almost two-thirds of the overall benefit of adjuvant therapy in patients with HR-positive BC. Endocrine therapy is the primary therapy for low-risk (endocrine responsive) HR-positive disease, whereas both endocrine therapy and chemotherapy are used for high risk (uncertain endocrine response category), and chemotherapy alone for HR-negative endocrine nonresponsive disease.28,114–117 Use of anti-HER2 therapy is based on risk stratification and tumor HER2 status.112
ER status has been used since the mid 1970s in the clinical management of BC both as an indicator of endocrine responsiveness and as a prognostic factor for early recurrence. The present gold standard to assess ER status is IHC performed on formalin-fixed, paraffin-embedded cancer tissue. This diagnostic test is routinely used in the clinic, and major therapeutic decision making is dependent on the results; however, its reliability is not perfect. It has been reported that the existing IHC assays have only modest positive predictive value (30% to 60%) for response to single-agent hormonal therapies. However, the negative predictive value of ER expression is high (ie, ER negativity which accounts for 20% to 30% of BC, can identify the population of patients who will not benefit from endocrine therapy).28,114–119 Therefore, it is important to identify variables that allow identification of patients who can be safely spared adjuvant therapy, or benefit from hormone therapy alone, or combined with chemotherapy and/or targeted therapy. PR is an estrogen-regulated gene and its expression is therefore thought to indicate a functioning ER pathway. Approximately 40% of ER-positive tumors are PR-negative. Lack of PR expression in ER-positive tumors may be a surrogate marker of aberrant growth factor signaling that could contribute to tamoxifen resistance and that ER+/PR− tumors are generally less responsive than ER+/PR+ tumors.120–123 PR status can help to predict response to hormone treatment, both in patients with metastatic disease124 and in the adjuvant setting.120,125–128 Multiple studies have provided evidence for the prognostic and predictive importance of PR assessment in BC.109,110,123–125,129,130
Amplification of HER2 gene occurs in 13% to 20% of BC and > half (approximately 55%) of these cases are HR-negative.131,132 Numerous studies found that HER2 gene amplification/protein overexpression is a predictor of poor prognosis and response for systemic chemotherapy.20,133–136 After the development of a humanized monoclonal antibody against HER2 and clinical trials demonstrating benefit of the use of anti-HER2 agents in patients with HER2-positive BC,137–139 the reasons for establishing the HER2 status in routine clinical practice has changed, as it is a prerequisite for clinical use of anti-HER2 in patients with HER2-positive advanced disease140 and in the adjuvant setting for HER2-positive early-stage disease.138
HR and HER2 are assessed in routine practice to provide information on response to endocrine therapy and anti-HER2-targeted therapy, respectively. However, the expression of these biomarkers overlap and their prognostic and predictive value can be improved by using them in combination.141 Most IHC studies have used a combination of ER, PR, and HER2 as IHC surrogates to define the molecular classes initially identified by GEP. For instance, ER/PR positivity was used as a surrogate for luminal class and HER2 expression for HER2-positive tumors, whereas triple negative (ER–, PR–, HER2–) phenotype is used to define the basal-like molecular class.111,142 In addition, some authors have classified HR-positive tumors that are also HER2-positive as the luminal B subclass.142,143 Therefore, ER, PR, and HER2 status provides an accessible biological molecular classifier of BC with defined prognostic and predictive value, and their value increases when they are used in combination where they can provide a valid practical surrogate of the GEP-defined molecular classes. Furthermore, incorporation of certain other well-established IHC markers, such as proliferation-associated markers, may provide additional prognostic and predictive value to the present classification systems.144,145 IHC expression of Ki67 is now widely used as an objective molecular measure of proliferation to overcome problems related to tumor fixation and mitotic figures identification.146,147 Although IHC assessment of Ki67 is not yet incorporated in routine pathology practice,26,148 several studies have yielded promising results particularly its prognostic significance in node-negative,145,149 ER-positive,150 and in histologic grade 2 tumors151 and as a predictor of response to chemotherapy.152,153
MULTIPARAMETER GENE EXPRESSION CLASSIFIERS
Class Discovery (Molecular Taxonomy)
Molecular taxonomy of BC was pioneered in the study by Perou et al in 2000.35 These authors have demonstrated that BC can be classified into molecularly distinct groups based on global gene expression profiles and their results have been validated in several subsequent studies.36,154–156 On the basis of this approach, BC is classified into 3 well-defined classes; namely luminal, HER2 positive, and basal classes and few less-defined subtypes. The latter include normal breast-like class, molecular apocrine and claudin-low subtypes or the subclassification of luminal tumors (ie, luminal A, B, and C) (for review see157,158). Although molecular taxonomy of BC has attracted a lot of attention and speculation that this would result in dramatic improvements in BC management, to date actual practical adoption seems limited. Certain critical issues have been raised such as validation, reproducibility, and clinical utility. Most luminal tumors are HR-positive and can be identified in routine practice using IHC. HR expression, and not luminal phenotype, is recognized as a validated predictor to hormone therapy. The significance of luminal HR-negative tumors is not defined. Similarly, HER2-positive BC patients are likely to be offered anti-HER2 therapy when indicated regardless of their molecular classification, although it is presently not justified to offer patients with cancers classified in the HER2-postive class if their tumors did not show evidence of HER2 gene amplification. Clinical relevance needs to be considered and factored into any emerging classification system to ensure that patients are treated appropriately. Furthermore, the so-called normal breast-like class is not well-defined157 and the proportion of some classes defined by GEP varied substantially.154,156,159 Finally, 1 could argue that this molecular taxonomy is a mere reflection of HR status/HER2 status/ proliferation status of BCs. It has been shown that using simpler approaches based on IHC evaluation of expression of selected proteins associated with the genes of interest,111,142,143,160,161 can provide practical surrogate to GEP molecular classification in routine clinical samples (see above).
Molecular taxonomy have been recapitulated using simpler approaches such as applying clustering analysis to a set of proteins assessed in a large series of BC using IHC and tissue microarray technology.37,162,163 Comparable molecular clusters with similar clinical relevance have been identified; however, this alternative approach for identification of molecular biological class remains as a research method with limited translation to clinical practice to date. Thus, the expression of HR and HER2 status, which is identified as the key biomarkers driving the membership of these identified groups has emerged at present as the most practical surrogate to molecular classification in clinical practice. More sophisticated algorithms based on quantitative biomarker expression assessed by IHC are being developed and once validated may prove to the be most effective methods in routine clinical practice.161,164
Prognostic and Predictive Gene Signatures (Class Prediction)
Several multigene classifiers that predict outcome and response to therapy in BC have been developed35,38,40,42,165–169; an approach which was pioneered by Van't Veer et al in 2002.39 Presently many classifiers have been generated using different technologies such as cDNA and oligonucleotide arrays and multiplex PCR. Many of these classifiers have been developed and validated in specific cohort of BC, particularly LN-negative ER-positive patients, show wide variations in the composition of their component genes with little overlap and some have claimed independent prognostic and predictive value better than that provided by traditional classifiers; however, only few have been subjected to rigorous assay standardization, quality control, and clinical validation. The most frequently reported and validated assays are the 21-gene signature (Oncotype DX; Genomic Health, Redwood City, CA), the 70-gene MammaPrint (Agendia BV; Amsterdam, the Netherlands; also referred to as the “Amsterdam signature”), the BC Gene Expression Ratio (HOXB13/IL17BR) (AvariaDx Inc., Carlsbad, CA), and the 76-gene “Rotterdam signature” (Veridex LLC; Warren, NJ). These 4 commercial assays represent the first introduction of these technologies into clinical application. Other prognostic signatures with clinical significance include invasiveness gene signature,170 wound-response gene-expression signature,171 hypoxia gene signature,172 a 41-gene signature173 and a 95-gene signature,174 and genomic grade index.
The Oncotype DX has been endorsed by the American Society of Clinical Oncology for clinical use26 and included in recent National Comprehensive Cancer Network guidelines. Oncotype DX is a real-time (RT)-PCR assay developed by Genomic Health from a prospectively chosen 250-candidate gene set.167,175 It measures the expression of 21 genes (16 cancer-related genes and 5 reference genes) in RNA extracted from formalin-fixed samples. The levels of expression of these 21 genes are manipulated by an empirically derived, prospectively defined mathematical algorithm to calculate a recurrence score (RS), which is then used to assign a patient to 1 of 3 groups by estimated risk of distant metastasis: low, intermediate, and high. The assay was initially developed to estimate the risk of recurrence in HR-positive patients, and in LN-negative patients who received tamoxifen therapy. It has been suggested that tamoxifen-treated patients with a low RS may be spared adjuvant chemotherapy, whereas patients with a high RS seem to achieve a higher proportional benefit from adjuvant chemotherapy than those with low or intermediate RSs. Subsequent studies have demonstrated the clinical utility of Oncotype DX in LN-positive postmenopausal women treated with hormone therapy,176 node-negative patients who did not receive systemic therapy (hormone therapy or chemotherapy),167 and as a predictor of the likelihood of pathologic complete response.177,178
MammaPrint is another prognostic multigene classifier composed of 70-genes identified from an initially unselected set of >25 000 candidate genes by researchers at the Netherlands Cancer Institute (Amsterdam) and collaborating institutions. This test is approved by Food and Drug Administration for use in the US for LN-negative BC patients <61 years of age with tumors of <5 cm in size. However, this test, which uses oligonucleotide microarrays, requires a fresh sample of tissue that is composed of a minimum of 30% malignant cells and must be received by the company in their kit transport medium within 5 days of obtaining tumor resection. This assay was first validated in untreated LN-negative patients.39,179 These studies have demonstrated that MammaPrint can identify groups of patients with very good or very poor prognosis. It was reported that the MammaPrint test provided prognostic information beyond that of Adjuvant Online.179,180 The Rotterdam Signature is a gene expression test based on research initially conducted at the Erasmus MC/Daniel den Hoed Cancer Center, Rotterdam, and consists of a 76-gene microarray assay that does not overlap with either the Oncotype DX or MammaPrint assays.38,40 The gene list for this assay is heavily weighted toward proliferation genes and unlike the previous 2 assays, this test is specifically studied in all LN-negative BC patients, regardless of age, tumor size and grade, or HR-status. Similar to MammaPrint, this assay requires whole sections of frozen tissue. Another real-time (RT)-PCR-based assay is the BC Gene Expression Ratio test that measures the ratio of the HOXB13 and IL17BR genes, and is marketed as a marker of recurrence risk in ER-positive/node-negative patients treated with tamoxifen.181,182 The precise clinical utility and appropriate application for other multiparameter assays are under investigation.
Drive for a Change and Future Classifications: Critical Views
Routine clinical management of BC relies on the availability of robust prognostic and predictive factors including morphologic and few individual molecular factors. These factors are used in combination to form indices, algorithms, and guidelines that can stratify patients into distinct categories with defined prognostic and predictive value to indicate the potential value of additional treatment and to ensure BC patients receive optimal treatment. However, these traditional classification systems have limitations and may not be adequate for patient-tailored treatment strategies particularly with the recent and continuous advancement in drug therapy, the shift to early-stage disease, breast conservative surgery, and rising patients expectations. In the last decade, BC research was dominated by the introduction of GEP molecular classification system and the emergence of numerous multigene classifiers that aim to outdo these traditional predictive and prognostic factors. The following issues are to be addressed:
(A) Despite initial promising results of the class discovery studies and the identification of distinct molecular classes, it remains unknown how many molecular classes exist and more importantly how many classes can be reliably identified with the presently available data. There remain major limitations in the ability to consistently assign a molecular class to new cases of BC. The rather subjective nature of class assignment based on hierarchical clustering must be acknowledged. The 4 main molecular classes frequently reported can be considered as an oversimplification of a novel molecular classification system and add little to our understanding of the biology and behavior of BC. Subclassification of the largest “luminal” class remains unresolved and the so-called normal breast-like class is not well-defined and may be an artifact of GEP due to samples with disproportionately high content of stromal and normal breast epithelial cells.157 The clinical difference between basal-like (GEP) and triple-negative (IHC) is disputed with triple negativity providing more practical and routinely applicable classification preferred by oncologists. Lumping of pure tubular carcinoma with micropapillary, invasive lobular, or ductal NST carcinomas into a single luminal class or high-grade ductal NST, high-grade metaplastic and medullary carcinomas with low-grade adenosquamous, and adenoid cystic carcinomas into basal-like class cannot be justified biologically or clinically. Molecular classification based on combination of the classical well-defined IHC markers can be considered as a simpler and more practical approach, and it is expected to remain as such unless novel target molecules driving individual classes are identified.141
(B) Assessment of HR and HER2 status in BC was introduced decades ago and they are routinely determined using a standardized technique and well-defined published guidelines; however, there remains substantial intralaboratory and interlaboratory variation in their assessment.20,27 With new technologies, similar challenges are expected to arise. Standardization of methodology has to be established and intralaboratory and interlaboratory reproducibility of results must be determined. GEP assays are generally performed in a centralized manner, whereas routine pathologic evaluation is mostly done on a decentralized basis, making the comparison of these methods difficult. To be applicable in routine clinical practice, these genomic assays, which are presently carried out in commercial and academic laboratories need to be performed in local laboratories or at least the sensitivity of prediction results to tissue acquisition methods, sample handling, and experimental noise needs to be defined as part of the clinical evaluation process. Performance is not necessarily identical to the marketed test, because many test procedures can differ. The potential for standardization and quality control of laboratory procedures used for these multigene classifiers including information about their reproducibility remains limited. Other technical issues such as tumors mixed with extensive in situ components, heterogeneous, mixed and multifocal tumors, and tumors with prominent inflammation may affect the performance of these nonpathologists-based multiparameter assays in individual cases.
(C) The expected added value of these recent molecular classifiers may require more than demonstrating an association between a given classifier and clinical outcome for proving clinical benefit. The biological roles of the genes included in most of these tests are not completely understood and it is often unclear which clinical or tumor characteristics are being measured. Although proliferation-related genes are essential component in most classifiers, there is little overlap and instabilities among different gene lists exist. In addition, the test gene set of the Oncotype DX contains HR set, HER2 set, a proliferation set, and an invasion-related gene set (13 of 16 genes), traditional markers such as HRs, HER-2, Ki67, and VI evaluate the same cellular pathways, and therefore the significance of its routine application may be doubtful if these standard assays are performed in a high-quality laboratory and are considered in combination.161
(D) Although it was claimed that there is a considerable subjective element in the assessment of classical BC classifiers such as histologic grade, this is an expected phenomenon of assessing biological variables. The problem of reproducibility was also noted in GEP studies.75,183,184 For example, in the studies by Sorlie et al156 and Chang et al171 only a proportion of cases could be accurately classified into the molecular subtypes, 9% to 15% of tumors could not be assigned as grade 1 and grade 3 by genomic grade index,76,77 and 19% to 24% of cases showed discordance among different gene expression signatures applied to the same set of tumors.89 Although 1 of the main criticisms of histologic grade is the high proportion of cases classified in the intermediate group (grade 2),75 when Oncotype DX was applied to ER-positive LN-negative BC cohort, 32% to 66% of tumors were classified as intermediate risk.168,185
(E) The traditional methods were developed and validated to be used in BC as a whole, therefore, the subgroups identified vary in size and application of the present classical classifiers may not be enough to identify the heterogeneous nature of tumors within some of these subgroups. For instance, in the LN-negative/HR-positive cases, which constitutes >50% of operable BC, there is a need for additional information as powerful factors such as extent of metastatic disease have been discounted. In addition, in modern practice with early detection of disease through greater awareness and mammographic screening, tumor size may have a limited prognostic value as most of these tumors are relatively small at diagnosis. The clinically indeterminate risk subgroups were included in several studies to determine the prognostic significance of multigene classifiers and, therefore, their prognostic significance is expected to be maintained in multivariate models based only on some of these category 1 classifiers.168 In the original study by Paik et al,175 it was mentioned that RS is an independent predictor of recurrence, however, the multivariate model included only tumor size and age, and size was already not significant before inclusion of RS. Interestingly, when additional (category 2) traditional prognostic factors such as VI, mitotic counts, and PR status are used in the ER-positive LN-negative subgroups, prognostic significance comparable to that provided by multigene classifiers can be obtained.185 In addition, most of the recently introduced classifiers were not tested against a combination of other classical routinely assessed biomarkers to proof or dispute their prognostic superiority before applying them to routine practice. Furthermore, the cost of multigene classifiers, which are orders of magnitude higher than that of comparable classical biological variables, such as histologic grading and Ki67 IHC, needs to be considered when compared with surrogate classical classifiers.
(F) Although research results indicate that these multigene molecular assays can reclassify some BC patients who are ranked as high risk using the traditional classification systems into low risk (ie, reducing the number of patients who might unnecessarily undergo chemotherapy) and vice versa,186 available data are insufficient to challenge classical classification systems and to justify withholding chemotherapy for high-risk patients if classified as low-risk using multigene assay. Correlation between projected risk of recurrence by Oncotype DX and Adjuvant Online was reported to be minimal.168 However, it should be acknowledged that these assays can potentially provide important prognostic information in clinically indeterminate subgroups and in such situations combining this test with conventional predictors yields the most information. For instance, high grade but small (<10 mm) size, LN-negative BC may be offered systemic therapy if it is classified as high risk using multigene assays, as staging information in such cases may be insufficient to reflect the behavior of these early-detected tumors.
In conclusion, although there is no doubt that GEP technology has revolutionized the field of BC research and are expected to support BC prognostication, the unprecedented speed of progress and publicity associated with the introduction of these commercially-based multigene classifiers should not lead us to expect this technology to replace the classical BC classification systems. Replacement of conventional classification seems unfounded and incorporation of multigene molecular classifiers to conventional BC classification systems seems more realistic and practical to support more effective tailoring of therapy in the future. These multigene classifiers can complement traditional methods through provision of additional biological prognostic and predictive information by identifying important clinically relevant biological processes better than that determined using morphologic factors or individual molecular markers. It also remains to be seen whether more robust and simpler methods based on IHC will provide comparable information and be more suited to routine clinical practice. Certainly, although multigene assays can be introduced into routine practice, in countries in which these costly assays cannot be afforded, more effort should be paid to improve the accuracy and reproducibility of assessing surrogate classical morphologic and molecular biological factors in routine practice.
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