William E. Gillanders, Kaidi Mikhitarian, Renee Hebert, Patrick D. Mauldin, Yuko Palesch, Christian Walters, Marshall M. Urist, G Bruce Mann, Gerard Doherty, Virginia M. Herrmann, Arnold D. Hill, Oleg Eremin, Mohamed El-Sheemy, Richard K. Orr, Alvaro A. Valle, Michael A. Henderson, Robert L. Dewitty, Sonia L. Sugg, Eric Frykberg, Karen Yeh, Richard M. Bell, John S. Metcalf, Bruce M. Elliott, Thomas Brothers, Jay Robison, Michael Mitas, and David J. Cole
The primary objective of cancer staging is to be able to classify patients by the extent of disease into groups with similar clinical outcomes and so facilitate patient management. In the setting of breast cancer, one of the most important prognostic indicators is the presence of axillary lymph node (ALN) metastases. Frequently, ALN disease status is the critical parameter for determining whether adjuvant systemic chemo or hormonal therapy is recommended.1–3 As a result, staging for newly diagnosed clinical stage I and II breast cancer patients has traditionally included an ipsilateral ALN dissection (ALND). Unfortunately, standard H&E histopathologic analysis of ALN has limitations. A number of studies have shown that performing additional tissue sections and/or immunohistochemical staining (IHC) of ALN increases metastases detection by up to 25%.4–6 Furthermore, these retrospective studies suggest that the prognosis for patients with occult disease is similar to patients with pathology-positive ALN.4,5,7 These findings imply that the development of more sensitive methods to detect micrometastatic disease in ALN could significantly improve breast cancer staging. The recent identification of genes overexpressed in breast cancer combined with advances in molecular biology provide such an opportunity for improving breast cancer staging.8–16 We and others have shown that the reverse transcription polymerase chain reaction (RT-PCR) is capable of detecting metastatic disease in ALN of breast cancer patients,15,17 with a sensitivity of up to one cancer cell per 107 normal cells.18–20 Ironically, the exquisite sensitivity of RT-PCR has hindered its clinical application because the majority of potential markers have some baseline expression in normal tissues.21,22 Due to the fact that conventional RT-PCR techniques are at best semiquantitative, it has been difficult to differentiate between baseline gene expression in normal tissues and increased gene expression associated with breast cancer.8,21,23–29 As a result, some investigators consider PCR technology to be problematic for clinical application with false positive and/or clinically irrelevant results a concern.8,21,23,25–27,29–31 Real-time RT-PCR solves these limitations through the use of an online fluorescence detection system that precisely quantifies the amount of PCR product. We have previously shown that real-time RT-PCR can differentiate between baseline gene expression in normal tissues and cancer-associated gene overexpression.32,33 For example, CEA, CK19, and muc1 have detectable baseline expression in normal lymph nodes, but expression levels in ALN with metastatic breast cancer is 5-fold to 3500-fold higher.32 Our data indicate that a combination of multimarker analysis and quantitative real-time RT-PCR can be a precise and powerful tool for the detection of breast cancer ALN metastases. Furthermore, the genes mam, PIP, PDEF, CK19, CEA, muc1, and mamB have particular promise for breast cancer detection.15,32,33 Although these results suggest that molecular markers could serve as valid surrogates for metastatic and micrometastatic breast cancer, their clinical relevance is unproven. To address this, the Minimally Invasive Molecular Staging of Breast Cancer (MIMS) trial was initiated. This trial represents the first prospective cohort study in which a multimarker, real-time RT-PCR analysis was applied to the detection of breast cancer micrometastases in ALN. Sentinel and/or nonsentinel ALN from 489 breast cancer subjects with T1–T3 primary tumors were analyzed by standard histopathology and multimarker, real-time RT-PCR analysis. The study was designed with sufficient statistical power to correlate molecular analyses with clinical outcome at 5 years. Although the clinical outcome data are not yet available, we show in this interim report that real-time RT-PCR is able to sensitively detect metastatic breast cancer in ALN and that overexpression of breast cancer–associated genes in subjects with pathology-negative ALN is correlated with traditional indicators of poor prognosis.