Multigene Classifiers, Prognostic Factors, and Predictors... : Advances in Anatomic Pathology (original) (raw)
Whole genome profiling technologies are now widely used to study the genes and genetic pathways associated with the progression of breast cancer and its response to therapy.1–4 This has led to the introduction of a variety of commercialized multigene prognostic and predictive tests designed to individualize the management of the disease.5–7 Both slide-based diagnostics such as immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) and nucleic acid-based assays including quantitative real time polymerase chain reaction (qRT-PCR) and genomic microarrays have entered the molecular diagnostics landscape with the integrated unique statistical data analysis tools and algorithms designed to calculate the test results.7–9 Some of the tests can use readily available formalin-fixed paraffin-embedded (FFPE) specimens, whereas others require fresh samples stored in an RNA preserving solution.5 Although several organizations have sought and achieved regulatory approval for their tests, others have not and offer their tests as “homebrew” assays. A number of these commercialized new multigene assays have been tested against conventional diagnostic and prognostic tests in a variety of multivariate analysis models with the results reported in peer-reviewed, well-respected scientific journals.5–7 Several multigene predictor kits, which are now on the market, have essentially been tested only “in house” and do not have any accompanying medical literature to support their developer's claims of clinical utility and value.
IHC is a standard of practice for breast cancer management with the assays for estrogen receptor (ER) and progesterone receptor (PR) performed by this method on all new primary tumors (Table 1).10 Although the number of markers that can be assessed by IHC is limited, the statistical analysis of IHC-based assays using multiple markers may become problematic both because of the nonlinear nature of IHC staining, different subcellular localization of different markers, and the impact of different slide scoring thresholds for different immunostains. IHC is widely used measure prognostic factors [ie, ER, human epidermal growth factor receptor 2 (HER2), Ki-67] and to predict response to both hormonal and HER2 targeted therapies,10,11 but is not established as a predictor of either the efficacy or toxicity of cytotoxic drugs. One commercialized IHC-based multigene predictor is in late stage clinical development12 and another has recently entered the market as a centralized testing service.13 In contrast to the higher cost of molecular assays, the cost of commercialized IHC multigene predictors ranges from an estimated 300to300 to 300to600 per test.
Comparison of Breast Cancer Multigene Predictor Test Platforms*
FISH is primarily used for determining the copy number of the HER2 gene and the selection of targeted anti-HER2 therapies.3 Although FISH has been used to measure chromosomal aneusomies and amplifications of cell proliferation associated genes, these assays have not been widely used.3 A 3-color FISH assay has been recently commercialized to assess stand alone prognosis in ER-positive and ER-negative stage I breast cancers.14
qRT-PCR has enabled a rapid growth in gene expression studies for both hematologic malignancies and solid tumors.15 A variety of commercial closed system qRT-PCR technologies are used for clinical applications with the TaqMan system (Applied Biosystems Inc, Foster City, CA) and LightCycler (Roche Diagnostics Inc, Indianapolis, IN) system used by 3 commercialized breast cancer multigene predictors.16–26 Although RT-PCR is often considered the “gold” standard for the quantification of mRNA, it is far from being a standardized assay, demonstrating significant variability in RNA templates and protocols used as well as in inappropriate data normalization and data analysis methodologies employed.27 RT-PCR procedures designed to predict outcome in breast cancer can be performed on either fresh or FFPE samples. Morphologic review of the tissue from which the mRNA will be extracted is recommended and microdissection may be required to make certain that the mRNA extracted for analysis is highly enriched for invasive carcinoma and not excessively diluted with the cells from benign tissues and in situ carcinoma areas.10,17 The heterogeneous expression of important mRNAs such as ER, HER2, and Ki-67, often reflected in the varying histologic grades observed in larger tumors can influence the predictive accuracy of transcriptional profiling measurements. In addition, the area sampled in a resection specimen must avoid including extracted mRNA from a zone of wound healing associated with a recent previous biopsy. The number of genes that can be simultaneously assessed by multiplex qRT-PCR is significantly greater than that for IHC and requires a more complex statistical evaluation of the gene expression profiles. The RT-PCR technique has been used to predict overall prognosis and the responses to both hormonal and cytotoxic therapies.16–26
Microarray profiling has been used to define cellular functions, biochemical pathways, cell proliferation activity, and regulatory mechanisms in breast cancer.5,28 A variety of commercial sources of microarray chips and slides have been used with the Affymetrix U133 GeneChip (Affymetrix Corporation, Santa Clara, CA) and the Agilent Custom Microarrays (Agilent Technologies, Santa Clara, CA) being the most prominent. These technologies have required the use of freshly prepared mRNA extracts and have not, to date, been fully adapted to FFPE tissues. Tumor mRNA expression heterogeneity and the relative tumor cell versus benign tissue volumes in fine needle aspirations or core needle biopsies may give a significantly different transcriptional profile than that of the completely resected tumor.29 Interpretation of microarray results is also very different from interpretation of conventional prognostic markers in that complex bioanalytic techniques are used which have, to date, not been fully standardized. One microarray based multigene predictor test for breast cancer has received US Food and Drug Administration (FDA) clearance.2,30–35 Commercialized microarray-based multigene predictors have been developed as stand alone prognostic biomarkers,36–40 predictors of response to hormonal therapy,2,22–26,30–35 and predictors of response to multiagent cytotoxic chemotherapy.41–50 The FDA is currently leading an effort to further standardize the microarray technology and related analytical methodology to facilitate broader clinical adaptation.51 The anticipated costs for the RT-PCR and microarray based multigene predictors for breast cancer is in the $3000 range per test. A potential promise of the microarray-based tests is that multiple distinct predictions including prognosis, ER and HER status, and sensitivity to various treatment modalities may be generated from a single gene chip.
MOLECULAR CLASSIFICATION OF BREAST CANCER
Molecular Portaits
The original “molecular portrait” classification of breast cancer, based on gene expression profiling continues to evolve as further subdivisions are proposed (Table 2).1,52 The initial version of the molecular portraits included luminal, normal, HER2, and basal-like subtypes of invasive breast cancer. The luminal group was subsequently subdivided into luminal A and B. Luminal A tumors have the highest ER expression and a high expression of GATA binding protein 3, X-box binding protein 1, trefoil factor 3, hepatocyte nuclear factor 3, and LIV-1.52 Luminal B tumors have low to moderate expression of the luminal-specific genes some of which are HER2 positive. The frequency of mutations of the p53 tumor suppressor gene is lower in the luminal A than in the luminal B group. The basal-like group has been associated with the so-called “triple-negative breast cancer (ER-negative, PR-negative, and HER2-negative) phenotype.” All luminal breast cancers are ER-positive with two-thirds showing low or intermediate histologic grade. The vast majority (ie, 95%) of basal-like cancers are ER-negative and 91% of these tumors are high grade.53 Almost all (∼80% to 90%) triple-negative tumors cluster in the basal-like genotype, but the basal-like genotype as a whole is heterogeneous and can be divided into multiple additional subgroups.54,55 The basal-like tumors lack ER and HER2 expression and feature more frequent overexpression of basal cytokeratins, epidermal growth factor receptor, and c-KIT.54 Studies of clinical outcome based on the molecular subtypes have shown that the basal-like and HER2 positive/ER negative subtypes are more sensitive to anthracycline-based neoadjuvant chemotherapy than luminal breast cancers56 and that the basal-like and HER2 positive subgroups were associated with the highest rates of pathologic complete response to neoadjuvant multiagent chemotherapy.53 Several studies have compared and validated the molecular portraits classification with other published breast cancer gene expression signatures using different transcriptional profiling platforms with uniform success.57,58 However, recent statistical meta-analysis of previous studies concluded that only 3 subtypes are consistently identifiable across datasets, HER2 positive, ER positive/HER2 negative, and ER negative/HER2 negative.59
Multigene Classifiers, Prognostic Factors and Predictors of Breast Cancer Clinical Outcome*
Recently, a 50-gene classifier developed by RT-PCR and microarray methods moved the molecular portrait approach forward as a diagnostic test and was found to be an independent prognostic factor in a group of 761 patients and predictor of response to neoadjuvant chemotherapy in a study of 189 patients.60 In summary, the molecular portrait subgroups are heavily driven by the ER, HER2 and relative proliferation status of the tumor explaining why, despite having a greater response to chemotherapy, tumors in the basal-like subgroup have a relatively poor prognosis reflecting their higher histologic grade and inability to be impacted by hormonal targeted therapies.61 As further studies are published, it is likely that additional pathways important for the prediction of breast cancer response to specific types of chemotherapy will emerge as important new subclassifiers of the original molecular portrait system.
MAPQUANT DX MOLECULAR TUMOR GRADING
In a recent study, a series of 97 genes was identified that was capable of reclassifying the traditional 3 histologic grades of breast cancer into only 2 distinct molecular grades.4 In this study, the gene expression grade index (“molecular grade”) was strongly associated with the histologic grades 1 and 3, but not for grade 2. For patients with histologic grade 2 tumors, a high genomic grade index (GGI) was associated with a higher risk of recurrence than a low GGI suggesting the possibility that histologic grade 2 was actually a mixture of grade 1 and grade 3 tumors.4 In other words, the histologic grade 2 tumors seemed to be similar to the grade 1 or grade 3 tumors in their molecular profiles, but lacked a distinctive profile of their own. One possible partial explanation for this observation is the so-called “3+3+1” tumor, which seems to be high grade under the microscope, but is devoid of mitotic figures. A potential explanation of this observation is that the tumor has remained for a protracted period of time at room temperature before it is immersed in formalin fixative, which has allowed for the mitotic figures that would have been observed to disappear as the tumor cells completed their cell division. A Ki-67 immunostain used to assess the tumor's proliferative index could possibly serve as a surrogate for mitotic figure counting for these cases and allow for them to be reclassified as possible grade 3 lesions.62 Recently, the GGI has been used to define 2 ER-positive molecular subgroups that were highly comparable with the luminal A and B subtypes of the molecular portraits and associated with a statistically distinct clinical outcome in both untreated and tamoxifen-treated patients.63 The GGI has been licensed as the MapQuant DX to Ipsogen Inc, (Marseille, France) for commercial development.
IMMUNOHISTOCHEMISTRY BASED MULTIGENE PREDICTORS
There are 2 commercialized IHC based multigene assays for the prediction of outcome for breast cancer.12,13 The ProExBr The BD/Tripath (Tripath Oncology, Durham, NC) is a 5 antibody/5 separate slide purely prognostic IHC assay that uses an image analysis system based slide scoring system.12 The 5 antibodies in the panel are the E2F transcription factor, p21 RAS associated protein, src kinase protein, secretory leukocyte peptidase inhibitor, and the proteasome core subunit β 1. Overexpression of 2 or more of these markers (ProExBr score of 2 or higher) has been associated with the disease relapse in both lymph node-negative and positive patient cohorts. The test has not been directly linked to response to a specific therapy. The Mammostrat (Applied Genomics Inc, Huntsville, AL) has been fully commercialized and is currently available through centralized testing at the Molecular Profiling Institute (Molecular Profiling Institute, Inc, Phoenix, AZ). This standard purely prognostic IHC-based test uses 5 antibodies: p53 tumor suppressor protein, HTFqc, CECAM5, NR61 and SLC7A5 with manual slide scoring to divide cases of ER-positive, lymph node-negative tumors treated with tamoxifen alone into low, moderate, or high-risk groups. In a multivariable analysis study, the calculated risk of recurrence for Mammostrat was independent of stage, grade, and lymph-node status.13 The global reimbursement for 88342 codes is approximately $450 to 500.
FLUORESCENCE IN SITU HYBRIDIZATION BASED PREDICTORS
The eXagenBC (eXagen Diagnostics, Inc, Albuquerque, NM) assay is a prognostic test designed to predict breast cancer outcome in node-positive or negative patients. The eXagenBC measures the copy numbers of 3 genes on FFPE samples for ER-positive tumors: cytochrome p450 family 24 (CYP24), programmed cell death 6 interacting protein (PDCD6IP), and baculoviral IAP repeat-containing 5 [BIRC5 (surviving)] and 3 genes for ER-negative tumors: nuclear receptor subfamily 1, group D, member 1 (NR1D1), switch/sucrose nonfermentable related, matrix associated, actin dependent regulator of chromatin, subfamily e, member 1(SMARCE1), and BIRC5.14 A proprietary algorithm is used to predict the prognostic index In an independent test validation study stratified by prognostic index, recurrence rates were significantly higher among high-risk patients than low-risk patients for both ER/PR positive (odds ratio, 9.52; 95% confidence interval >2.12; _P_=0.0024) and ER/PR negative (odds ratio, 12.3; 95% confidence interval >1.45; _P_=0.0188) cancers.14 This test has been submitted to the FDA for 510(k) clearance and, when fully commercialized, is expected to be performed on site by laboratories familiar with the FISH technique. The ultimate cost to patients for this procedure will likely reflect 3 individual 88,365 global Current Procedural Terminology codes or approximately $700 to 1000).
REAL TIME POLYMERASE CHAIN REACTION BASED MULTIGENE PREDICTORS
The Oncotype DX test (Table 3) is a 21-gene multiplex prognostic and predictive RT-PCR assay performed on primary FFPE breast cancer samples. The non-FDA approved test is centralized and performed by a Clinical Laboratory Improvement Act and State of California licensed laboratory (Genomic Health, Inc, Redwood City, CA). The Oncotype Dx gene set was discovered on archived FFPE samples by transcriptional profiling and then converted to the FFPE RT-PCR assay.17 The test determines the 10 year risk of disease recurrence for ER-positive, lymph node-negative breast cancers using a continuous variable algorithm and assigning a tripartite recurrence score (RS) (up to 17, low risk; between 18 and 30, intermediate risk; and greater than 30, high risk). The proliferation and ER pathway genes are the most heavily weighted in the calculation of the RS followed by the HER2 pathway gene expression levels. Oncotype Dx is best suited for detecting breast cancers with a low potential for recurrence. The Oncotype DX discovery cohort consisted of 447 stored samples including the tamoxifen-treated arm of the National Surgical Adjuvant Breast and Bowel Project (NSABP) B-20 clinical trial. The test was subsequently validated retrospectively on 668 ER-positive, lymph node-negative cases of tamoxifen-treated breast cancer patients of various ages who were enrolled in the NSABP B-14 trial.16 In this validation cohort, 51% of patients had tumors with a low RS, and 6.8% of these recurred at 10 years. In the high RS group (27% of cases), 30.5% recurred at 10 years.16 The assay was not prognostic in a different single-center study of untreated, node-negative patients, although neither was tumor grade.64 A subsequent analysis of the available samples from the NSABP B-20 trial demonstrated that the assay predicted benefit from tamoxifen in those tumors with low and intermediate RS and benefit from chemotherapy in high RS cases.19 Oncotype Dx ability to function as a predictive factor of therapy response requires further validation in other patient cohorts.65 For example, the impact of the RS has been further validated in a community hospital-based study of 790 patients from 14 Northern California Kaiser Permanente Hospitals.66 To date, Oncotype Dx studies has been mostly retrospective with only a single prospective abstract published indicating the test's was successfully capable of guiding therapy selection.67 The Oncotype Dx assay has been studied in lymph node-positive patients with promising results, which has led the developer to, expanded clinical trials for the test in this setting.68 In a recently presented study of Oncotype Dx in ER-positive tamoxifen treated node-positive patients, the findings confirmed to a large extent, the results obtained in node-negative tumors, including the prediction of chemotherapy benefit.69 In this study, a high RS was also predictive of added benefit of the CAF (cytoxan, adriamycin, 5-fluorouracil) chemotherapy regimen in these node-positive patients.68 Finally, in a study of 93 patients in 1 community and 3 academic oncology practices, the RS was found to impact the treatment plan in 31.5% of cases.70
Comparison of OncotypeDx and MammaPrint*
The Oncotype DX is a centralized “home brew” assay, which is currently exempt from the standard review FDA requires for diagnostic kits. The original discovery and validation of the test were conducted on archived NSABP clinical samples71 and the test has been successfully marketed without classic prospective validation. According to the Genomic Health website (www.genomichealth.com), 2008 saw nearly 40,000 Oncotype Dx tests reported, a 62% increase over the 2007 year. The company further claims that the test is currently accepted by 90% of third-party payors including the Centers for Medicare and Medicaid Services and is endorsed by the most recent American Society of Clinical Oncology tumor marker guidelines. The current list price for the test is $3460.
The Trial Assigning Individualized Options For Treatment Rx Clinical Trial
The Trial Assigning Individualized Options for Treatment Rx (TAILORx is being is sponsored by the National; Cancer Institute and is being conducted by the North American Breast Cancer Intergroup and is coordinated by the Eastern Cooperative Oncology Group). The TAILORx (Table 3) trial plans to enroll at least 10,000 women with ER or PR-positive, HER2-negative, lymph node-negative breast cancer at 900 sites in North America. The trial is designed to determine whether ER-positive patients with intermediate RS benefit from chemotherapy or not. Of note is the fact that the RS criteria have been changed for the TAILORx trial with the 18 to 30 intermediate RS range of the current clinically available assay changed to 11 to 25 for the trial.22 Patients with RS of 10 or less receive hormonal therapy alone, the patients with RS of 26 or higher receive hormonal and chemotherapy and the patients with RS between 11 and 25 are randomized into either hormonal therapy alone or to hormonal therapy plus chemotherapy. Accrual to this trial seems to be progressing at a rapid rate, with a higher than predicted proportion of patients in the intermediate group, but the trial results will not be known for a number of years and likely not until at least 2013.
Theros Two Gene Expression Ratio (H/I)
The Theros Two Gene Expression Ratio test is actually a 6-gene multiplex prognostic RT-PCR assay. The test uses FFPE tissues and is based on the original study of the ability of the ratio of the relative mRNA expression of the homeobox gene-B13 (HOXB13) and the interleukin-17B receptor gene to predict recurrence in patients with ER-positive, lymph node-negative primary breast cancers.23 The HOXB13 gene is located in a region on chromosome 17 and is expressed exclusively in neoplastic breast tissue, whereas expression of the IL17BR gene is frequently lost in invasive tumors.23–26 The prognostic significance of this test has been found to show significance in both tamoxifen-treated25 and untreated patients,24 although the significance of the test in the tamoxifen-treated group has been challenged. This test was developed at the Massachusetts General Hospital/Harvard Medical School and licensed to Aviara Dx (Aviara Dx, Inc, Carlsbad, CA). As of late 2006, the test is available as a centralized test by Quest Diagnostics (Quest Diagnostics, Lyndhurst, NJ). The test is billed under the Current Procedural Terminology codes 83891, 83896×6, 83898×6, 83902, and 83912, which total approximately $1400.
Celera Metastasis Score
This 14-gene multiplex FFPE tissue ready RT-PCR assay is a prognostic test also limited to ER-positive, lymph node-negative tumors treated with tamoxifen (Celera Inc, Rockville, MD). In their preliminary studies based in multiple European institutions, the Metastasis Score for breast cancer predicted a 3.5-fold difference in risk between the 20% of women at highest risk and the 20% of women at lowest risk for disease recurrence.72 This test has been licensed for commercialization to the Laboratory Corporation of America (Lab Corp, Burlington, NC).72 The launch date for testing, FDA status, billing strategy, and cost of this test are not currently available.
The Breast BioClassifier
The Associates in Regional and University Pathologists (Salt Lake City, UT) Breast BioClassifier is a qRT-PCR assay that can identify the different biologic subtypes of breast cancer (luminal A, luminal B, HER2, and basal-like) and provide a prognostic risk assessment.73 The test consists of 50 classifier genes and 5 control genes that are measured simultaneously using a 384-well format in the LightCycler 480 (Roche Diagnostics Corporation, Indianapolis, IN). Previous studies have shown that the biologic subtypes of breast cancer can be recapitulated using a qRT-PCR assay61 and that the assay can be performed using FFPE tissues.74 The Breast BioClassifier provides prognosis within different molecular subtypes of ER-negative and ER-positive breast cancer, and identifies groups of patients that may potentially benefit from personalized therapy. This assay will be available at the Associates in Regional and University Pathologists central testing laboratory in mid-2008. The test has been submitted to the FDA for 510(k) clearance and, at the present time, the cost is not published. Recently, this database has been combined with the molecular portraits database to form a 50-gene classifier that successfully predicted response to neoadjuvant chemotherapy.60
GENOMIC MICROARRAY BASED MULTIGENE PREDICTORS
MammaPrint
The MammaPrint assay (Agendia BV, Amsterdam, Netherlands) is the first fully commercialized microarray-based multigene assay for breast cancer (Tables 2, 3). The original test is designed only for predicting prognosis and has received 510(k) clearance from the FDA's new in vitro diagnostic multivariate index assay system. The test cannot currently be performed on FFPE tissues and requires either freshly frozen tumor samples or tissues collected into an RNA preservative solution. The test has recently been marketed in the USA (Agendia, Inc, Huntington Beach, CA). The test was originally developed at the Netherlands Cancer Institute in Amsterdam as a single site using stored frozen samples from breast cancer patients under the age of 53 years and using the Rosetta Inpharmatics DNA microarray system (Merck and Co, Whitehouse Station, NJ) and then commercialized on the Agilent microarray platform (Agilent Technologies, Wilmington, DE). The 70 genes that comprise the MammaPrint assay are focused primarily on proliferation with additional genes associated with invasion, metastasis, stromal integrity, and angiogenesis. The Oncotype Dx and Mammaprint assays have only 1 individual gene in common: the SCUBE2 gene, which is a member of the ER pathway. The discovery of the MammaPrint 70-gene prognostic assay was originally criticized for including some patients in both the discovery and validation cohorts.30 However, the test was subsequently validated by the TransBIG Consortium of European Cancer Centers on a separate cohort which used the gene signatures to classify patients into the low-risk group when the test algorithm determined that they had a greater than 90% chance of being free of disease for a minimum of 5 years.34 The TransBIG Consortium also found that the MammaPrint signature could further risk stratify patients within the “Adjuvant! Online” clinicopathologic risk categories.34,75 Moreover, when compared with the St Gallen prognostic criteria, high risk patients identified by MammaPrint have a higher rate of distant metastases than the high risk patients identified by the St Gallen criteria and MammaPrint low risk have a higher likelihood of metastasis-free survival than those classified as low risk using the St Gallen criteria. The MammaPrint assay is at its best when identifying cases at the extremes of the spectrum of disease outcome: the identification of patients with very good or very poor prognosis. A number of studies designed to validate that the Mammaprint assay can also predict response to both endocrine and cytotoxic chemotherapy are on-going. Unlike the Oncotype Dx test, which features a continuous RS result, the Mammaprint test uses a dichotomous “high risk versus low risk” result format (Table 3). The cost of the test in the US is $4200.
The Mammaprint test does not include ER, PR, or HER2 in the 70-gene microarray. A new assay, TargetPrint, has recently been launched that measures the mRNA of these 3 genes on the Agilent microarray system.
The Microarray in Node-negative Disease May Avoid Chemotherapy Trial
The Microarray in Node-negative Disease may Avoid Chemotherapy (MINDACT) is sponsored by the European Organization for Research and Treatment of Cancer and opened in August of 2007 (Table 3). In this prospective trial of both primary lymph node-negative and lymph node-positive breast cancer, all patients are assessed by the standard clinicopathologic prognostic factors included on Adjuvant!Online and by the 70-gene MammaPrint assay.76 If both the traditional and molecular assays predict “high risk” status, the patient receives adjuvant cytotoxic chemotherapy and also hormonal therapy if ER-positive. If both assays indicate a “low risk,” no chemotherapy is given and ER-positive patients are given adjuvant hormonal therapy only. When there is a discordance between the traditional clinicopathologic prognostic factor prediction of risk and MammaPrint prediction of risk, the patients are randomized to receive treatment either based on the genomic profile or by the clinical prediction results.
Comparison of Oncotype Dx and MammaPrint
The priority gene lists for these 2 tests focus on 3 biologic pathways: proliferation, ER, and HER2. The Oncotype Dx has a clear advantage in being FFPE-ready especially for the US market where the smaller size of primary tumors and more diverse sites where primary tumors are biopsied will make it difficult to obtain fresh or frozen tissue samples required for the Mammaprint assay. The MammaPrint test currently has a wider indication than Oncotype Dx by including both ER-positive and ER-negative patients, which also allows for inclusion of a greater number of younger patients. On the basis of currently published studies, the Oncotype Dx test has been validated as both a stand-alone prognostic test, and has been interpreted as a predictive test for response to tamoxifen and to the CMF (cyclophosphamide, methotrexate, and fluorouracil) adjuvant chemotherapy regimen (although concurrent with tamoxifen). In contrast, the MammaPrint assay is currently only validated as a prognostic test and evidence that this test can also serve as a predictive test for specific endocrine or cytotoxic therapy regimens has not been fully validated. The MammaPrint assay has received 510(k) clearance by the FDA whereas Oncotype Dx has not. The Oncotype Dx has been designated as “recommended for use” by the American Society of Clinical Oncology Breast Cancer Tumor Markers Update Committee whereas the MammaPrint assay is currently classified by the group as “under investigation.”77
The 2 prospective trials designed to determine the potential clinical value of the molecular stratification of early stage breast cancers have different designs as described in Table 3. Both trials are attempting to prospectively evaluate the clinical value of these multigene molecular signatures. The TAILORx trial is designed to determine whether intermediate risk ER-positive patients benefit from adjuvant chemotherapy or not, whereas the MINDACT trial is designed to determine whether a molecular test is more accurate than Adjuvant!Online to identify low risk patients who can be spared from cytotoxic therapy. Neither trial is focused on lymph node-positive tumors although the MINDACT trial has recently allowed accrual of node-positive cases. Although the MINDACT trial allows for a wider patient eligibility, including both ER-positive and negative patients, the accrual rate to date seems to be greater for the TAILORx trial. The TAILORx trial has been criticized for “performing a randomized comparison in a stratum of intermediate-risk patients” featuring a RS algorithm that has been modified from the current test indication (low score <10 vs. low score <18) without any effort being made to compare this with a traditional clinical prediction.78 The Oncotype Dx assay has been shown to be cost-effective in 1 pharmacoeconomic study.79 A cost effectiveness study for MammaPrint has not been published to date. However, it is important to understand that cost-effectiveness results are highly dependent on assumptions how physicians use the test results and alter their treatment plan based on molecular data. Finally, it should be noted that it will take at least 5 more years before either trial can be fully evaluated for both clinical significance and thus impact the true assessment of the cost effectiveness of either assay.
Rotterdam Signature
The Rotterdam Signature, also known as the 76-gene assay, was developed as a pure prognostic assay at the Erasmus University Cancer Center in Rotterdam, The Netherlands, and is being commercially developed by the Veridex Corp (Veridex LLC, Warren, NJ). Sharing no genes in common with either Oncotype Dx or MammaPrint, and run on the Affymetrix U-133 GeneChip System (Affymetrix, Inc, Santa Clara, CA), this assay is validated for lymph node-negative patients independent of hormone receptor status.36,37 The most recent validation of this assay was performed in 4 European cancer centers achieving high stand-alone prognostic significance and the ability to predict recurrence in ER-positive patients treated with tamoxifen alone.37–39 The gene list for this assay is heavily weighted towards proliferation genes. This assay requires fresh/frozen extracted mRNA. The test has not been commercially launched and its FDA approval status and cost have not been announced.
Invasiveness Signature
The Invasiveness Signature is a prognostic assay that also uses the Affymetrix U-133 GeneChip and is currently being developed as a stand-alone prognostic test (OncoMed Pharmaceuticals, Redwood City, CA).40 This assay is designed for node-negative and positive and ER-negative and positive patients. The Invasiveness Gene Signature consists of 186 genes possibly related to tumor stem cells, and may predict prognosis for lung and prostate cancers as well as medulloblastoma. The launch date, FDA status, and cost of this assay are not currently available.
NuvoSelect
The NuvoSelect (Nuvera Biosciences, Woburn, MA) is a combination of several pharmacogenomic genesets obtained from resected tumor specimens (index) or from fine needle aspiration specimens (chemotherapy response predictor). Rather than serving as a stand-alone prognostic assay, NuvoSelect is primarily a predictive test for guiding selection of therapy. One gene set (30 genes) predicts complete response to preoperative TFAC [paclitaxel (Taxol), 5-fluouracil, (doxorubicin) Adriamycin, cyclophosphamide] chemotherapy and the other gene set (200 genes) predicts outcome after 5 years of endocrine therapy.46,47 This database found that overexpression of microtubule associated protein tau mRNA was a major predictor of resistance to the TFAC regimen and a predictor of increased sensitivity to endocrine therapy among the ER-positive patients.48 The NuvoSelect test also provides the ER and HER2 mRNA status.80 FDA approval strategy, commercial launch date, and cost for this test have not been released.
CytoChrome p450 CYP2D6 Genotyping
A wide variety of drugs are metabolized by a group of liver enzymes known as cytochrome P450 or CYP. The CYP2D6 enzyme activates tamoxifen by metabolizing it to endoxifen, the potent antiestrogen. It is now known that patients with low or completely deficient levels of CYP2D6 fail to activate tamoxifen and are thus unable to benefit from its anti-tumor effects.81–84 Thus, it has been suggested that, for patients deficient in CYP2D6 who have been diagnosed with ER-positive breast cancers, aromatase inhibitors may be the preferred hormonal therapeutics rather than tamoxifen. The test platforms used for determining the CYP2D6 genotype include PCR with restriction fragment length polymorphism assay, a proteomics approach using gas chromatography and mass spectroscopy and the FDA-approved genomic microarray approach. The Roche AmpliChip technology (Roche Diagnostics Inc, Indianapolis, IN) has been customized to detect CYP2D6 deficiency at the DNA level in the germ line of newly diagnosed breast cancer patients and has been the most widely employed technique for the study of tamoxifen response.80–82 This assay has been approved by FDA and recently, the Laboratory Corporation of America has announced a partnership with Medco Health Solutions (Medco Health Solutions Inc, Franklin Lakes, NJ), designed to offer CYP2D6 testing on a large scale. A number of smaller laboratories have announced the availability of homebrew assays for this biomarker. It is too early to know whether this approach towards personalizing the selection of hormonal therapy will become widely used.
CONCLUSIONS
The commercialized multigene predictors for breast cancer are summarized in Table 2. The 2 tests that have achieved the most advanced commercial success are Oncotype Dx and MammaPrint. As the process of commercialization continues in this extremely competitive landscape, concerns continue to arise over the scientific validity, clinical utility, and cost/benefit ratios for these expensive molecular tests. Experts in oncology and biostatistics continue to raise concerns as to whether the level of significance for these new assays will hold up over time as more patients are tested. Rapid adoption of these assays before they have been proven in their clinical effectiveness remains a serious concern among both breast cancer oncologists and healthcare economists. In addition, it has been noted that these new tests can easily be misused including employing the test in the wrong clinical settings and ending up with misleading reassurance about the test-driven decisions.78 Although the prospective clinical trials that are currently underway should provide significant information about the clinical value of these multigene predictors, many questions will remain unanswered for the next several years.
REFERENCES
1. Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature. 2000;406:747–752.
2. van 't Veer LJ, Dai H, van de Vijver MJ, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature. 2002;415:530–536.
3. Ross JS, Linette GP, Stec J, et al. Breast cancer biomarkers and molecular medicine. Expert Rev Mol Diagn. 2003;3:573–585.
4. Sotiriou C, Wirapati P, Loi S, et al. Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst. 2006;98:262–272.
5. Pusztai L, Cristofanilli M, Paik S. New generation of molecular prognostic and predictive tests for breast cancer. Semin Oncol. 2007;34:S10–S16.
6. Ross JS, Hatzis C, Symmans WF, et al. Commercialized multigene predictors of clinical outcome for breast cancer. Oncologist. 2008;13:477–493.
7. Sotiriou C, Pusztai L. Gene-expression signatures in breast cancer. N Engl J Med. 2009;360:790–800.
8. Stec J, Wang J, Coombes K, et al. Comparison of the predictive accuracy of DNA array-based multigene classifiers across cDNA arrays and Affymetrix GeneChips. J Mol Diagn. 2005;7:357–367.
9. Gruvberger-Saal SK, Cunliffe HE, Carr KM, et al. Microarrays in breast cancer research and clinical practice--the future lies ahead. Endocr Relat Cancer. 2006;13:1017–1031.
10. Ross JS, Symmans WF, Pusztai L, et al. Standardizing slide-based assays in breast cancer: hormone receptors, HER2, and sentinel lymph nodes. Clin Cancer Res. 2007;13:2831–2835.
11. Ross JS, Symmans WF, Pusztai L, et al. Breast cancer biomarkers. Adv Clin Chem. 2005;40:99–125.
12. Whitehead CM, Nelson R, Hudson P, et al. Selection and optimization of a panel of early stage breast cancer prognostic molecular markers. Mod Pathol. 2004;17:50A.
13. Ring BZ, Seitz RS, Beck R, et al. Novel prognostic immunohistochemical biomarker panel for estrogen receptor-positive breast cancer. J Clin Oncol. 2006;24:3039–3047.
14. Davis LM, Harris C, Tang L, et al. Amplification patterns of three genomic regions predict distant recurrence in breast carcinoma. J Mol Diagn. 2007;9:327–336.
15. Jung R, Soondrum K, Neumaier M. Quantitative PCR. Clin Chem Lab Med. 2000;38:833–836.
16. Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med. 2004;351:2817–2826.
17. Paik S, Kim CY, Song YK, et al. Technology insight: application of molecular techniques to formalin-fixed paraffin-embedded tissues from breast cancer. Nat Clin Pract Oncol. 2005;2:246–254.
18. Paik S. Methods for gene expression profiling in clinical trials of adjuvant breast cancer therapy. Clin Cancer Res. 2006;12:1019s–1023s.
19. Paik S, Tang G, Shak S, et al. Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol. 2006;24:3726–3734.
20. Kaklamani V. A genetic signature can predict prognosis and response to therapy in breast cancer: Oncotype DX. Expert Rev Mol Diagn. 2006;6:803–809.
21. Cronin M, Sangli C, Liu ML, et al. Analytical validation of the Oncotype DX genomic diagnostic test for recurrence prognosis and therapeutic response prediction in node-negative, estrogen receptor-positive breast cancer. Clin Chem. 2007;53:1084–1091.
22. Paik S. Development and clinical utility of a 21-gene recurrence score prognostic assay in patients with early breast cancer treated with tamoxifen. Oncologist. 2007;12:631–635.
23. Ma XJ, Wang Z, Ryan PD, et al. A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen. Cancer Cell. 2004;5:607–616.
24. Ma XJ, Hilsenbeck SG, Wang W, et al. The HOXB13: IL17BR expression index is a prognostic factor in early-stage breast cancer. J Clin Oncol. 2006;24:4611–4619.
25. Goetz MP, Suman VJ, Ingle JN, et al. A two-gene expression ratio of homeobox 13 and interleukin-17B receptor for prediction of recurrence and survival in women receiving adjuvant tamoxifen. Clin Cancer Res. 2006;12:2080–2087.
26. Wang Z, Dahiya S, Provencher H, et al. The prognostic biomarkers HOXB13, IL17BR, and CHDH are regulated by estrogen in breast cancer. Clin Cancer Res. 2007;13:6327–6334.
27. Nolan T, Hands RE, Bustin SA. Quantification of mRNA using real-time RT-PCR. Nat Protoc. 2006;1:1559–1582.
28. Bertucci F, Houlgatte R, Benziane A, et al. Gene expression profiling of primary breast carcinomas using arrays of candidate genes. Hum Mol Genet. 2000;9:2981–2991.
29. Symmans WF, Ayers M, Clark EA, et al. Total RNA yield and microarray gene expression profiles from fine-needle aspiration biopsy and core-needle biopsy samples of breast carcinoma. Cancer. 2003;97:2960–2971.
30. van de Vijver MJ, He YD, van't Veer LJ, et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med. 2002;347:1999–2009.
31. van 't Veer LJ, Dai H, van de Vijver MJ, et al. Expression profiling predicts outcome in breast cancer. Breast Cancer Res. 2003;5:57–58.
32. Cleator S, Ashworth A. Molecular profiling of breast cancer: clinical implications. Br J Cancer. 2004;90:1120–1124.
33. Weigelt B, Hu Z, He X, et al. Molecular portraits and 70-gene prognosis signature are preserved throughout the metastatic process of breast cancer. Cancer Res. 2005;65:9155–9158.
34. Buyse M, Loi S, van't Veer L, et al; TRANSBIG Consortium. Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer. J Natl Cancer Inst. 2006;98:1183–1189.
35. Nuyten DS, van de Vijver MJ. Gene expression signatures to predict the development of metastasis in breast cancer. Breast Dis. 2006–2007;26:149–156.
36. Wang Y, Klijn JG, Zhang Y, et al. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet. 2005;365:671–679.
37. Foekens JA, Atkins D, Zhang Y, et al. Multicenter validation of a gene expression-based prognostic signature in lymph node-negative primary breast cancer. J Clin Oncol. 2006;24:1665–1671.
38. Yu JX, Sieuwerts AM, Zhang Y, et al. Pathway analysis of gene signatures predicting metastasis of node-negative primary breast cancer. BMC Cancer. 2007;7:182.
39. Desmedt C, Piette F, Loi S, et al; TRANSBIG Consortium. Strong time dependence of the 76-gene prognostic signature for node-negative breast cancer patients in the TRANSBIG multicenter independent validation series. Clin Cancer Res. 2007;13:3207–3214.
40. Liu R, Wang X, Chen GY, et al. The prognostic role of a gene signature from tumorigenic breast-cancer cells. N Engl J Med. 2007;356:217–226.
41. Chang JC, Wooten EC, Tsimelzon A, et al. Gene expression profiling for the prediction of therapeutic response to docetaxel in patients with breast cancer. Lancet. 2003;362:362–369.
42. Chang JC, Wooten EC, Tsimelzon A, et al. Patterns of resistance and incomplete response to docetaxel by gene expression profiling in breast cancer patients. J Clin Oncol. 2005;23:1169–1177.
43. Cleator S, Tsimelzon A, Ashworth A, et al. Gene expression patterns for doxorubicin (Adriamycin) and cyclophosphamide (Cytoxan) (AC) response and resistance. Breast Cancer Res Treat. 2006;95:229–233.
44. Ayers M, Symmans WF, Stec J, et al. Gene expression profiles predict complete pathologic response to neoadjuvant paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide chemotherapy in breast cancer. J Clin Oncol. 2004;22:2284–2293.
45. Rouzier R, Pusztai L, Delaloge S, et al. Nomograms to predict pathologic complete response and metastasis-free survival after preoperative chemotherapy for breast cancer. J Clin Oncol. 2005;23:8331–8339.
46. Wagner P, Wang B, Clark E, et al. Microtubule associated protein (MAP)-Tau: a novel mediator of paclitaxel sensitivity in vitro and in vivo. Cell Cycle. 2005;4:1149–1152.
47. Rouzier R, Rajan R, Wagner P, et al. Microtubule-associated protein tau: a marker of paclitaxel sensitivity in breast cancer. Proc Natl Acad Sci U S A. 2005;102:8315–8320.
48. Hess KR, Anderson K, Symmans WF, et al. Pharmacogenomic predictor of sensitivity to preoperative chemotherapy with paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide in breast cancer. J Clin Oncol. 2006;24:4236–4244.
49. Peintinger F, Anderson K, Mazouni C, et al. Thirty-gene pharmacogenomic test correlates with residual cancer burden after preoperative chemotherapy for breast cancer. Clin Cancer Res. 2007;13:4078–4082.
50. Andre F, Hatzis C, Anderson K, et al. Microtubule-associated protein-tau is a bifunctional predictor of endocrine sensitivity and chemotherapy resistance in estrogen receptor-positive breast cancer. Clin Cancer Res. 2007;13:2061–2067.
51. Shi L, Reid LH, Jones WD, et al. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. Nat Biotechnol. 2006;24:1151–1161.
52. Sørlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A. 2001;98:10869–10874.
53. Rouzier R, Perou CM, Symmans WF, et al. Breast cancer molecular subtypes respond differently to preoperative chemotherapy. Clin Cancer Res. 2005;11:5678–5685.
54. Nielsen TO, Hsu FD, Jensen K, et al. Immunohistochemical and clinical characterization of the basal-like subtype of invasive breast carcinoma. Clin Cancer Res. 2004;10:5367–5374.
55. Kreike B, van Kouwenhove M, Horlings H, et al. Gene expression profiling and histopathological characterization of triple negative/basal-like breast carcinomas. Breast Cancer Res. 2007;9:R65.
56. Carey LA, Dees EC, Sawyer L, et al. The triple negative paradox: primary tumor chemosensitivity of breast cancer subtypes. Clin Cancer Res. 2007;13:2329–2334.
57. Fan C, Oh DS, Wessels L, et al. Concordance among gene-expression-based predictors for breast cancer. N Engl J Med. 2006;355:560–569.
58. Hu Z, Fan C, Oh DS, et al. The molecular portraits of breast tumors are conserved across microarray platforms. BMC Genomics. 2006;7:96.
59. Kapp AV, Jeffrey SS, Langerod A, et al. Discovery and validation of breast cancer subtypes. BMC Genomics. 2006;7:231.
60. Kapp AV, Tibshirani R. Are clusters found in one dataset present in another dataset? Biostatistics. 2007;8:9–31.
61. Parker JS, Mullins M, Cheang MC, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol. 2009;27:1160–1167.
62. Liedtke C, Mazouni C, Hess KR, et al. Response to neoadjuvant therapy and long-term survival in patients with triple-negative breast cancer. J Clin Oncol. 2008;26:1275–1281.
63. van Diest PJ, van der Wall E, Baak JP. Prognostic value of proliferation in invasive breast cancer: a review. J Clin Pathol. 2004;57:675–681.
64. Loi S, Haibe-Kains B, Desmedt C, et al. Definition of clinically distinct molecular subtypes in estrogen receptor-positive breast carcinomas through genomic grade. J Clin Oncol. 2007;25:1239–1246.
65. Esteva FJ, Sahin AA, Cristofanilli M, et al. Prognostic role of a multigene reverse transcriptase-PCR assay in patients with node-negative breast cancer not receiving adjuvant systemic therapy. Clin Cancer Res. 2005;11:3315–3319.
66. Henry NL, Hayes DF. Uses and abuses of tumor markers in the diagnosis, monitoring, and treatment of primary and metastatic breast cancer. Oncologist. 2006;11:541–552.
67. Habel LA, Shak S, Jacobs MK, et al. A population-based study of tumor gene expression and risk of breast cancer death among lymph node-negative patients. Breast Cancer Res. 2006;8:R25.
68. Mumby PB, Lo SS, Norton J, et al. Prospective multicenter study of the impact of the 21-gene recurrence score assay on patient satisfaction, anxiety and decisional conflict for adjuvant breast cancer treatment selection [abstract]. Breast Cancer Res treat. 2007;106(suppl 1):S73.
69. Cobleigh MA, Tabesh B, Bitterman P, et al. Tumor gene expression and prognosis in breast cancer patients with 10 or more positive lymph nodes. Clin Cancer Res. 2005;11(24 Pt 1):8623–8631.
70. Albain K, Barlow W, Shak S, et al. Prognostic and predictive value of the 21-gene recurrence score assay in postmenopausal, node-positive, ER-positive breast cancer. Breast Cancer Res Treat. 2008;84:S8814.
71. Lo SS, Norton J, Mumby PB, et al. Prospective multicenter study of the impact of the 21-gene recurrence score (RS) assay on medical oncologist (MO) and patient (pt) adjuvant breast cancer (BC) treatment selection. J Clin Oncol (2007 ASCO Annual Meeting Proceedings Part I). 2007;25(18S):577.
72. Sparano JA. TAILORx: trial assigning individualized options for treatment (Rx). Clin Breast Cancer. 2006;7:347–350.
73. Garber K. Gene expression tests foretell breast cancer's future. Science. 2007;303:1754–1755.
74. Perreard L, Fan C, Quackenbush JF, et al. Classification and risk stratification of invasive breast carcinomas using a real-time quantitative RT-PCR assay. Breast Cancer Res. 2006;8:R23.
75. Mullins M, Perreard L, Quackenbush JF, et al. Agreement in breast cancer classification between microarray and quantitative reverse transcription PCR from fresh-frozen and formalin-fixed, paraffin-embedded tissues. Clin Chem. 2007;53:1273–1279.
76. Ravdin PM, Siminoff LA, Davis GJ, et al. Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol. 2001;19:980–991.
77. Bogaerts J, Cardoso F, Buyse M, et al; TRANSBIG consortium. Gene signature evaluation as a prognostic tool: challenges in the design of the MINDACT trial. Nat Clin Pract Oncol. 2006;3:540–551.
78. Harris L, Fritsche H, Mennel R, et al. American Society of Clinical Oncology 2007 Update of Recommendations for the Use of Tumor Markers in Breast Cancer. J Clin Oncol. 2007;25:118–145.
79. Ioannidis JP. Is molecular profiling ready for use in clinical decision making?. Oncologist. 2007;12:301–311.
80. Lyman GH, Cosler LE, Kuderer NM, et al. Impact of a 21-gene RT-PCR assay on treatment decisions in early-stage breast cancer: an economic analysis based on prognostic and predictive validation studies. Cancer. 2007;109:1011–1018.
81. Gong Y, Yan K, Lin F, et al. Determination of oestrogen-receptor status and ERBB2 status of breast carcinoma: a gene-expression profiling study. Lancet Oncol. 2007;8:203–211.
82. Goetz MP, Rae JM, Suman VJ, et al. Pharmacogenetics of tamoxifen biotransformation is associated with clinical outcomes of efficacy and hot flashes. J Clin Oncol. 2005;23:9312–9318.
83. Jin Y, Desta Z, Stearns V, et al. CYP2D6 genotype, antidepressant use, and tamoxifen metabolism during adjuvant breast cancer treatment. J Natl Cancer Inst. 2005;97:30–39.
84. Goetz MP, Knox SK, Suman VJ, et al. The impact of cytochrome P450 2D6 metabolism in women receiving adjuvant tamoxifen. Breast Cancer Res Treat. 2007;101:113–121.
Keywords:
breast cancer; Oncotype Dx; Mammaprint; Rotterdam signature; invasiveness signature; two gene expression ratio
© 2009 Lippincott Williams & Wilkins, Inc.