Beyond Lymph Node Staging_molecular Predictors Of Outcome In Breast Cancer

Surg Oncol Clin N Am 14 (2005) 69–84

Beyond lymph node staging: molecular predictors of outcome in breast cancer David G. Sheldon, MD* Section of Surgical Oncology, Geisinger Health System, 100 North Academy Avenue, MC 21–70, Danville, PA 17822-2170, USA

How do the characteristics of a breast tumor define the outcome for the disease? Clinicians have a wide array of prognostic and predictive factors at their disposal that provide useful information concerning outcomes in breast cancer. Prognostic factors are patient or tumor characteristics that are used to estimate outcomes for the disease, independent of treatment variability. They can be used to select appropriate patients for therapy. Well-recognized prognostic factors in breast cancer include tumor size, grade, and the presence or absence of lymph node metastases. These variables have been incorporated into a widely used, validated scheme—the Nottingham Prognostic Index [1,2]. Predictive factors are clinical, pathologic, or biologic features of the tumor that are used to estimate a response to a treatment, such as systemic chemotherapy or endocrine therapy [3,4]. There has been an increased emphasis on identifying and validating predictive factors for outcomes in breast cancer as more sophisticated molecular techniques define tumor characteristics. Predictive factors, based on an individual molecular analysis of the tumor, can be used to tailor therapy. We are on the threshold of routinely implementing targeted therapies with ‘‘designer’’ regimens based on the genetic signatures of an individual tumor. Recent guidelines for adjuvant therapy of breast cancer result in treatment of greater than more than 90% of patients, despite benefit in less than 10% of all patients who are exposed to the hazards of chemotherapy [5–8]. The reason for casting such a broad net is that we are unable to predict accurately which tumors will have a bad outcome. Most node-negative breast cancers are cured with surgery and local radiation alone, yet 30% to 40% [9,10] of

* Geisinger Health System, Department of General Surgery, Surgical Oncology and Endocrinology, 100 North Academy Avenue, Danville, PA 17822-2170. E-mail address: [email protected] 1055-3207/05/$ - see front matter Ó 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.soc.2004.07.007

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these patients relapse and ultimately may die of disseminated disease. Why? Overall, up to 40% of patients who are node-positive will be alive at 10 years, despite having tumor characteristics that are similar to the other 60% [6]. New insights into the molecular biology of breast cancer may clarify this problem and tell us how a particular tumor will behave in the future; how it will respond to cytotoxic, endocrine, or biologic therapy; and whether the tumor has metastasized—all from a core needle biopsy that is performed in the surgeon’s office. This article briefly reviews the exciting, yet unproven, reports of alternate methods of predicting outcomes in breast cancer and highlights new molecular methods of diagnosing, classifying, and treating this disease. The author begins by reviewing well-known factors in breast cancer with which all alternate methods of staging and predicting outcomes must be compared prospectively.

Histologic factors of the tumor Tumor size and grade Tumor size long has been viewed as a primary indicator of prognosis in breast cancer. It is clear from screening mammography trials that if tumors are detected earlier (ie, at a smaller size), survival is improved [11–13]. Multiple randomized, controlled studies have confirmed that tumor size alone is a primary indicator of outcome in breast cancer. Using Surveillance, Epidemiology and End-Results data, Carter et al [14] demonstrated that tumor size correlated with recurrence-free and overall survival. The risk of harboring axillary lymph node metastases from breast cancer also is a function of the size of the tumor; the rate of node positivity and the rate of systemic metastases increase linearly with increasing tumor size [15,16]. Patients who have small tumors have a better outcome than those who have large tumors [14,17]. For any given size of tumor, a higher nuclear or pathologic grade leads to a worse outcome [18]. Tumor grade is prognostic for recurrence-free and overall survival. Higher-grade tumors also are more responsive to cytotoxic chemotherapy [19]. Pathologists commonly report a histologic grade of 1 (best), 2, or 3 (worst), although the subjective nature of the assessment makes observations that are based solely on tumor grade difficult [19,20]. Angiolymphatic invasion Vascular or angioinvasion, as identified by careful histologic examination of the primary tumor, is correlated highly with local, regional, and systemic metastases and is a marker for recurrence of disease and overall survival [21–23].

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Lymphovascular invasion (LVI) is difficult to discern from angioinvasion on histologic examinations, but is associated with a worse outcome. A review of the University of Southern California/Van Nuys database indicated that LVI is an independent marker for risk of death from breast cancer [24]. It was suggested that LVI can be a surrogate for nodal metastasis; it is a strong negative prognostic factor and is an indication for aggressive chemotherapy in the absence of nodal metastasis [25]. Tumor angiogenesis, a necessary component of the metastatic phenotype, can be assayed by immunohistochemistry. High levels of angiogenesis are correlated independently with poor survival and metastasis [26]. Axillary nodal metastases In 2004, the most relevant prognostic factor in breast cancer remains axillary nodal status. The gold standard for staging of breast cancer is the histologic examination of the axillary lymph nodes because it is the most sensitive indicator of prognosis. Axillary nodal staging is performed most reliably by a level I and II axillary nodal dissection, when greater than 10 lymph nodes are examined [27,28]. Clinical staging of axillary lymph nodes by physical examination is, by itself, highly inaccurate with false-negative rates of 30% to 40% [29]. For any given size of a primary breast tumor, axillary nodal metastases imply a significantly poorer prognosis for the patient as compared with patients who have similar tumor size but no nodal metastases [14]. Nodal metastases reduce the mean 10-year overall survival by approximately half [30,31]. The presence of nodal metastases, the total numbers of nodes, and the level from which they were harvested are important [17,32]. Despite the fact that nodal status is the most sensitive factor for the estimation of risk, it is not a good indicator of outcome. Nodal status cannot predict reliably which of the approximately 30% of patients who are node-negative will relapse and which of the approximately 40% of patients who are node-positive will survive for 10 years without evidence of disease [33,34]. Perhaps the most controversial report of axillary nodal status as it relates to outcome is the National Surgical Adjuvant Breast and Bowel Project (NSABP) study, B-04 [35,36]. The node-negative portion of this large trial randomized women who had clinically-staged early breast cancer to (1) modified radical mastectomy (MRM); (2) total mastectomy with axillary radiation (TM/XRT); or (3) total mastectomy alone (TM). Patients did not receive adjuvant systemic therapy. At 10 and 25 years of follow-up, the recurrence rates and axillary failure rates in the arms who received MRM and TM/XRT were similar. As expected, the axillary failure rate in the arm that underwent TM was much higher than the rate in the two arms that included axillary treatments (24% versus 4%); however, this rate was only half of the nodal positivity rate of the arm that underwent MRM which

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indicated that positive axillary lymph nodes always do not become clinically apparent. Another important finding was that nodal relapse in the arm that received no axillary treatment (ie, TM) did not diminish survival at 25 years of follow-up. This raises an interesting biologic question—how can axillary lymph node metastases be the most sensitive indicator of future systemic disease recurrence and death from breast cancer when half never become clinically apparent and delayed treatment does not affect survival? Although lymph node status is a strong predictor of outcome, axillary dissection is not without morbidity. The risk of permanent lymphedema is 4% to 36%, depending on the extent of surgery and whether nodal basin irradiation is used postoperatively [37]. With the advent of sentinel node biopsy as the standard of care for axillary nodal staging in high-volume centers [38], the morbidity rate is reduced significantly, but is not zero. With accurate nodal staging alone, it is not possible to predict reliably which patients will experience eventual systemic relapse, and thus, die of their disease.

Molecular predictors and prognostic indicators in breast cancer Steroid receptors Decades of quality data validate the use of steroid receptors as a predictor of outcome in primary breast cancer [4]. Estrogen receptors and progesterone receptors are detected on tumors by ligand-binding assays, or more recently, by immunohistochemistry (IHC). Estrogen receptor–positive (ERþ) tumors have a better prognosis compared with estrogen receptor–negative (ER
) tumors. The presence of estrogen receptors on a tumor and intact cellular machinery that is regulated by estrogen is an independent prognostic factor for survival in breast cancer [39]. Estrogen receptors on a breast tumor also predict response to systemic endocrine therapy (tamoxifen), and thus, a better outcome. A large meta-analysis of more than 30,000 treated women provided level I evidence of a treatment effect for tamoxifen in ERþ tumors. The proportional recurrence reduction at 1, 2, and 5 years was 21%, 29%, and 47%, respectively [40]. The corresponding reduction in mortality was 12%, 17%, and 26%, respectively. erbB-2 (Her2/neu) The proto-oncogene, erbB-2 (also known as Her2/neu), is located on chromosome 17 and encodes a 185-kd transmembrane protein, p185, a homolog of the epidermal growth factor receptor (EGFR). EGFR is a classic transmembrane tyrosine kinase–type receptor that initiates signaling pathways upon ligand binding. It normally is present in small quantities on breast epithelium. The literature is inconsistent with regards to the predictive abilities of Her2 in breast cancer, because of methodologic differences in

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assaying for gene abnormalities and the expression of the corresponding protein receptor. A distinction must be made between gene amplification and protein overexpression. Identification of gene amplification seems to be a more sensitive indicator of poor prognosis as compared with protein overexpression and is associated with newer, more sophisticated techniques in molecular diagnosis [41–43]. An amplification of the erbB-2/Her2 gene results in the overexpression of erbB-2/Her2 receptor protein in approximately one third of invasive breast carcinomas and is associated with poor outcome [44–46]. ErbB-2 receptor protein overexpression in breast cancer was associated with lymph node metastases, higher nuclear grade, younger age at diagnosis, resistance to endocrine therapy, and a poorer prognosis [47– 49]. Similarly, the overexpression of EGFR is a predictor of early recurrence and death [50,51]. erbB-2/Her2 overexpression was the basis for multiple trials of combined cytotoxic chemotherapy and targeted biologic therapy with a monoclonal antibody (trastuzumab) against the receptor [52,53]. The finding that Her2 status is concordant between primary tumor and the systemic metastasis supports the biologic basis for this treatment [54]. Longterm data as to the efficacy of trastuzumab are forthcoming and are derived mostly from trials in the metastatic setting. p53 The TP53 gene also is on chromosome 17 and encodes for the p53 protein. It is the most commonly mutated gene in human cancer [55]. The p53 protein has many functions that relate to cell cycle arrest and induction of apoptosis in response to cellular stress. Mutation or inactivation of p53 is an almost universal requirement for human cancers to proliferate and metastasize. It is no surprise that mutant TP53 gene products are associated with a poor prognosis in breast cancer [56]. Mutations in the TP53 gene were demonstrated in node-negative and node-positive tumors. This finding independently implied reduced disease-free and overall survival and improved response to regional radiotherapy [57]. Conflicting data concerning outcomes arise when archival tissue blocks are immunohistochemically stained for abnormal protein accumulation as compared with newer techniques that use genome TP53 mutation screening on fresh tissue; the latter is much more sensitive. A recent meta-analysis of 11 studies with more than 2300 patients demonstrated that the relative risk of death from breast cancer is doubled for tumors with somatic TP53 mutations as compared with those without such mutations [58]. When p53 mutations are noted in conjunction with Her2/neu gene amplification, outcomes are significantly worse than for tumors that contain only one or neither of these abnormalities. In a large (n = 580), prospective study of Her2/neu amplification in frozen breast tumor specimens, a Toronto group noted a significant reduction in disease-free survival in patients whose tumors had the Her2/ neu gene amplified. In a subset of these tumors (n = 108), genome

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abnormalities in TP53 exons 4–10 were noted; this group independently had worse disease-free and overall survival. This group of tumors also was more likely to be ER
, high-grade, and to harbor LVI [59]. Cyclins and cyclin-dependent kinase inhibitors Cyclins are a family of nuclear proteins that accelerate the nuclear mitotic cycle from G1 to S phase by inactivating the retinoblastoma protein, Rb. High levels of cyclin-dependent kinases (CDK) and cyclins are seen in breast cancer cell lines and were associated with poor outcomes in retrospective clinical series [60]. A recent study from the University of Houston M.D. Anderson Cancer Center showed convincingly that deregulated expression of cyclin E is associated with poor survival in breast cancer. These results are conflicting with older series [61]; the explanation is that IHC detection is unreliable for the more active, truncated isoforms of cyclin E, whereas Western blot analysis (used in the Houston series) is much more sensitive. Western blot–detected cyclin E upregulation was associated with a hazard ratio for death of 33 as compared with 2.9 for IHC-detected cyclin E on the same specimens. No patient who had normal cyclin E levels and stage I cancer (n = 102) died during the follow-up period, whereas all of the patients who had stage I disease (n = 12) and overexpressed cyclin E died of breast cancer within 48 months. This is a provocative finding, despite the fact that no information concerning adjuvant systemic therapy was given in the report. Similar results were seen in patients who had stage II or III disease. Another nuclear protein group, the cyclin-dependent kinase inhibitors (CDKI), play a role in cell cycle regulation. p27kip is a CDKI that is a negative regulator of cyclin-dependent kinases and antagonizes the activity of cyclin E. Decreased levels of p27, as demonstrated by IHC, imply increased mitotic activity and worse outcome [60]. A small study that used IHC to assay p27 activity confirmed that a decreased level of this protein in breast cancer is associated independently with shorter overall survival in patients who are node-positive [62,63]. Results of ongoing research into the CDK/CDKI system are awaited eagerly to validate cyclin expression as a predictive factor in breast cancer. Urokinase-type plasminogen activator system Extracellular matrix degradation by proteases has been evaluated extensively and is believed to be a necessary step in the malignant progression of tumors. Serine proteases, such as urokinase-type plasminogen activator (uPA), are necessary enzymes for angiogenesis, invasion, and metastasis. There is considerable evidence that increased levels of uPA and its inactivator, plasminogen activator inhibitor–1 (PAI-1), and decreased levels of the inactivator, plasminogen activator inhibitor–2, are correlated with systemic relapse and death from breast cancer [64]. A large, pooled clinical

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analysis confirmed that tumor immunoassays that are positive for uPA or PAI-1 are associated independently with a poor outcome for patients who are node-negative or node-positive [65]. Further prospective study of the uPA system as it relates to metastasis is warranted; this may represent an attractive target for antimetastatic therapy. Other markers of risk in breast tumors A multitude of other molecular predictors have been studied in breast cancer. A comprehensive review of them all is not the intent of this article. Cathespin D, Ki-67, bcl-2, E-Cadherin, nuclear S-phase fraction, and ploidy status are some of the many molecular markers that have been examined in high-risk breast cancer [66]. None has been studied in a prospective fashion in a clinical trial to demonstrate efficacy. One notable study recruited patients from a neoadjuvant protocol, examined some of these biomarkers pre- and posttreatment, and noted that a clinical response to cytotoxic chemotherapy in conjunction with favorable biomarker findings may be a surrogate for predicting survival in breast cancer [47]. None has gained prominence in daily oncology practice. Disseminated tumor cells Prospective studies of blood and bone marrow samples in unselected patients who had breast cancer revealed the presence of disseminated tumor cells (DTCs) in 20% to 40% of cases [67–69]. These cells necessarily are not metastases per se—rather, they are solitary, nonproliferating tumor cells that have malignant potential [70,71]. Fluorescent in situ hybridization analysis revealed that DTCs have malignant genotypes [72] but may not be responsive to cytotoxic chemotherapy, given their dormancy [73]. DTCs in bone marrow are strongly predictive of eventual disease relapse and do not correlate with the presence or absence of lymph node micrometastases [74,75]. Klein et al [76] studied breast tumor DNA from DTCs in 386 unselected patients; they noted that the DNA aberrations in the disseminated cells were distinct from the DNA aberrations of the lymph node metastases and the primary tumor [76]. DTCs do not express ERs consistently when compared with the primary tumor and lymph node metastases [77]. These findings are consistent with the theory that breast cancer cells are shed peripherally early in the course of disease and later acquire the genetic changes that are characteristic of metastases [78–81]. The presence of DTCs in the marrow is associated strongly with bony metastases; however, patients who have DTCs can experience long tumorfree intervals or may not ever relapse [75,82,83]. Diel et al [84] reported that DTCs, that were detected prospectively with tumor-associated glycoprotein (TAG-12), were present in 43% of patients who had primary breast cancer. At 36 months of follow-up, DTCs were superior to lymph node status as a predictor of eventual metastasis and disease-free and overall survival. This

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study has been criticized for its short follow-up interval and because TAG-12 may be expressed in marrow myeloid precursors and could have confounded the results. An often-cited report by Braun, [67] however, confirmed the negative prognostic impact of DTCs in a well-controlled, prospective study of bone marrow aspirates in benign and malignant disease of the breast that used IHC-detected cytokeratins. The false positive rate was only 1% (2 of 191 control specimens) as determined by analysis of marrow specimens from patients who had benign breast disease. Multivariate analysis confirmed that DTC is associated independently with early systemic recurrence and death from breast cancer. This study provided strong evidence that DTCs are independently predictive of outcome, compared with other tumor factors and lymph node status, and contradicted earlier findings [82,83]. More recent reports confirmed the findings of Braun and Diel et al and concluded that bone marrow aspiration for detection of DTC is complementary to traditional prognostic indicators in breast cancer [85]. DTCs can overexpress Her-2/neu and other tumor markers and this finding is a poor prognostic indicator [86]. Labeling with IHC revealed that approximately 70% of DTCs express Her2/neu, 65% express epithelial cell adhesion marker, 77% express uPA, and up to 100% express extracellular matrix metalloproteinase inducer [68]. These molecular markers of phenotypic malignancy represent interesting targets for novel biologic therapies after systemic therapy with minimal residual microscopic disease. Tumor genome analysis: microarrays In DNA microarray analysis, mRNA from snap frozen fresh tissue is extracted and complimentary double-stranded DNA is created. Reverse transcription is undertaken and the resultant amplified cRNA is labeled with fluorescent dye and hybridized to a panel of up to 25,000 oligonucleotides; each one represents a single gene on a chip that is similar to a glass microscope slide. Qualitative and quantitative assessment of the amount of fluorescence enables computer-aided statistical programs to discern patterns of gene expression—either up-regulated or down-regulated. The presence or absence of tumor mRNA for each of the 25,000 genes is indicated on the chip and this is interpreted as evidence of gene expression, but not necessarily protein product translation or functional gene products. This extremely powerful tool generates vast amounts of data that can revolutionize the diagnosis and management of many diseases, most notably cancer. Although long-term prospective data are lacking, initial findings from microarray analysis of tumor tissue has yielded extremely provocative information. Expression profiling demonstrates that breast tumors are genetically heterogenous and that they could be subclassified by the differential expression of known genes [87,88]. Analysis of these patterns can predict ER status, response to cytotoxic chemotherapy, and potentially

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tailor such therapy, based on specific profiles [89–93]. Based on their genetic classification of breast tumors, Hedenfalk et al [94] were able to identify hereditary versus sporadic breast cancer and correctly classify BRCA1- and BRCA2-mutated tumors. This information can be obtained simply from an in vivo fine needle aspiration biopsy of tumor tissue [95]. Some of the most exciting data from using DNA expression profiles showed that the ultimate outcome of the disease may be predicted from the genetic make-up of the tumor at the time of harvesting. In a small, prospective study of 55 patients who had breast cancer, Ahr et al [96] classified all patients, regardless of nodal status, into two groups according to a clustered, 41-gene analysis. The analysis successfully identified patients who had synchronous metastatic disease and early relapse; this finding was independent of nodal status. Similarly, the group that was headed by Van’t Veer [97] demonstrated in a pilot study that gene expression profiling could predict clinical outcome in lymph node–negative breast cancer. They established a 70-gene profile that could predict outcome reliably in terms of systemic relapse (odds ratio of 15 for development of metastases). In a follow-up study of 295 consecutive patients (61 patients were included in the original report), Van de Vijver et al [98] demonstrated the usefulness of the same 70-gene profile in predicting the outcome of early (stage I or II) breast cancer. Using the profile, they retrospectively assigned each patient to a ‘‘good prognosis’’ (n = 115) or ‘‘bad prognosis’’ (n = 180). The profile was strongly predictive of ultimate outcome; the 5-year freedom from distant metastasis rate (DFS) was 61% in the group that had a poor prognosis and was 95% in the group that had a good prognosis. At 10 years, the DFS rates were 50% and 85%, respectively. What is most remarkable in this report is that the patients who had lymph node metastases were distributed evenly in the two groups. Most patients who were lymph node–negative (141/151) did not receive adjuvant therapy, whereas most patients who were node-positive (120/144) did receive adjuvant systemic chemotherapy or endocrine therapy. This exciting study has been criticized for its retrospective nature, patient selection bias, and the inclusion of pilot data in the manuscript; however, it is a preview of how microarray data may be used in daily oncology practice. The finding that the expression profile of a primary tumor is identical to its distant metastasis that appears later validates the theory that outcomes can be determined at the initial presentation of the tumor [99]. What cannot be determined by the Van de Vijver et al [98] study is the fate of patients who do not receive adjuvant systemic therapy but are lymph node–positive and have a good prognosis. Gene-expression profiling, if validated in ongoing trials, has the potential to answer the question of when to treat aggressively the lymph node–negative patient who ultimately will relapse and when not to treat the lymph node–positive patient who will have a good outcome, regardless of therapy. This represents the ‘‘holy grail’’ for clinicians who treat cancer patients.

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Perspective Powerful, exciting, thought-provoking, expensive—all of these words describe the new tools that are available to the physician collaborator who treats cancer. The sequence of the human genome was reported in 2001 [100,101]; genome research is revealing a plethora of translational applications for molecular diagnostic techniques. The new discipline of ‘‘discovery science’’ turns out information concerning the molecular biology of neoplasia almost daily. What should be done with all of the data? First, comparisons of the most promising of the molecular prognostic variables (eg, DTCs, cyclin E, or gene-expression profiles) need to be examined in a prospective manner with a critical light and be compared with accepted standards. To say that long-term data are lacking is almost superfluous. Advancements in cancer treatments are based on observations from prospective clinical trials. Data from DTCs and molecular profiling can be obtained in almost real-time and may accelerate the pace of discovery if, for instance, the eradication of viable DTCs in the marrow [102] or the normalization of gene-expression profile with therapy, is validated as an outcome equivalent. The surgeon must play an integral role in this process. The paradigm of neoadjuvant therapy for breast carcinoma that provides linear data points by interrogating the tumor genome pretherapy, posttherapy, and postexcision is well-suited for the multi-disciplinary clinic. Soon, we should have prospective gene-expression data on individual breast tumors and their associated in situ carcinoma, lymph node metastases, and DTCs. The differences in expression profiles of each of these tissues should shed much light on the molecular biology of breast cancer. The corollary to this paradigm is the necessity of a well-run team of clinicians and scientists with an infrastructure that is designed to handle large amounts of information that are derived from tissues as soon as it is procured. Many of these new techniques require high-quality RNA that is obtained from immediately frozen tissue and an accessible tissue bank. Recently, a technique to obtain gene expression data from paraffinembedded archival tissue blocks using reverse transcriptase polymerase chain reaction was reported in abstract form and in the lay press, before any formal peer-reviewed process [103]. Private industry has reserved the rights to the 21-gene profile that is specific to the report and has marketed the test commercially to clinicians. This should be cause for alarm among academic oncologists; the data that were obtained from the test have not been examined critically before commercial application. If validated, however, this process could have a tremendous impact on routine examinations of breast cancer specimens. Can molecular profiles predict who does not need systemic chemotherapy? This should be a component of future study design. If and when tumor genetic profiles confidently predict who does and who does not need aggressive treatment we will have arrived as clinicians. When the current

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standard of care calls for treatment of more than 90% patients to the benefit of less than 10%, much work needs to be done.

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